NP – Nonlinear Processes in Geosciences
NP1.1 – Mathematics of Planet Earth
EGU2020-1670 | Displays | NP1.1
Linear response theory for macroscopic observables in high-dimensional systems: when is it valid and when not?Georg Gottwald and Caroline Wormell
The long-term average response of observables of chaotic systems to dynamical perturbations can often be predicted using linear response theory, but not all chaotic systems possess a linear response. Macroscopic observables of complex dissipative chaotic systems, however, are widely assumed to have a linear response even if the microscopic variables do not, but the mechanism for this is not well-understood.
We present a comprehensive picture for the linear response of macroscopic observables in high-dimensional coupled deterministic dynamical systems, where the coupling is via a mean field and the microscopic subsystems may or may not obey linear response theory. We derive stochastic reductions of the dynamics of these observables from statistics of the microscopic system, and provide conditions for linear response theory to hold in finite dimensional systems and in the thermodynamic limit. In particular, we show that for large systems of finite size, linear response is induced via self-generated noise.
We present examples in the thermodynamic limit where the macroscopic observable satisfies LRT, although the microscopic subsystems individually violate LRT, as well a converse example where the macroscopic observable does not satisfy LRT despite all microscopic subsystems satisfying LRT when uncoupled. This latter, maybe surprising, example is associated with emergent non-trivial dynamics of the macroscopic observable. We provide numerical evidence for our results on linear response as well as some analytical intuition.
How to cite: Gottwald, G. and Wormell, C.: Linear response theory for macroscopic observables in high-dimensional systems: when is it valid and when not?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1670, https://doi.org/10.5194/egusphere-egu2020-1670, 2020.
The long-term average response of observables of chaotic systems to dynamical perturbations can often be predicted using linear response theory, but not all chaotic systems possess a linear response. Macroscopic observables of complex dissipative chaotic systems, however, are widely assumed to have a linear response even if the microscopic variables do not, but the mechanism for this is not well-understood.
We present a comprehensive picture for the linear response of macroscopic observables in high-dimensional coupled deterministic dynamical systems, where the coupling is via a mean field and the microscopic subsystems may or may not obey linear response theory. We derive stochastic reductions of the dynamics of these observables from statistics of the microscopic system, and provide conditions for linear response theory to hold in finite dimensional systems and in the thermodynamic limit. In particular, we show that for large systems of finite size, linear response is induced via self-generated noise.
We present examples in the thermodynamic limit where the macroscopic observable satisfies LRT, although the microscopic subsystems individually violate LRT, as well a converse example where the macroscopic observable does not satisfy LRT despite all microscopic subsystems satisfying LRT when uncoupled. This latter, maybe surprising, example is associated with emergent non-trivial dynamics of the macroscopic observable. We provide numerical evidence for our results on linear response as well as some analytical intuition.
How to cite: Gottwald, G. and Wormell, C.: Linear response theory for macroscopic observables in high-dimensional systems: when is it valid and when not?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1670, https://doi.org/10.5194/egusphere-egu2020-1670, 2020.
EGU2020-19177 | Displays | NP1.1
Studying heat waves and warm summers in numerical climate models with a rare event algorithmFrancesco Ragone and Freddy Bouchet
Extreme events are a major topic of interest in climate science. Studying rare extreme events with complex numerical climate models is computationally challenging, since in principle very long simulations are needed to sample a sufficient number of events to provide a reliable statistics. This problem can be tackled using rare event algorithms, numerical tools developed in the past decades in mathematics and statistical physics, dedicated to the reduction of the computational effort required to sample rare events in dynamical systems. Typically they are designed as genetic algorithms, in which a set of suppression and cloning rules are applied to an ensemble simulation in order to focus the computational effort on the trajectories leading to the events of interest. Recently we showed the great potential of rare event algorithms for climate modelling, applying a rare event algorithm to study extremes of European surface temperature in Plasim, an intermediate complexity model, in absence of external time dependent forcings (no seasonal and daily cycles). Here we go beyond these limitations, studying extreme heat waves and warm summers in the Northern extratropics in fully realistic conditions including daily and seasonal cycles, both in Plasim and in the state of the art Earth system model CESM. We show how the algorithm allows to sample extreme events characterised by persistency on different time scales, discussing links with large deviation theory. We show how one can characterise the statistics of heat waves and warm summers with extremely large return times, with computational costs orders of magnitude smaller than with direct sampling, and reach ultra rare events that would have been impossible to observe otherwise. We analyse the emergence of teleconnection patterns during the extreme events and their relation to the dynamics of planetary waves. Finally we discuss how these results open the way to the systematic application of these techniques to a vast range of applicative and theoretical studies.
How to cite: Ragone, F. and Bouchet, F.: Studying heat waves and warm summers in numerical climate models with a rare event algorithm, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19177, https://doi.org/10.5194/egusphere-egu2020-19177, 2020.
Extreme events are a major topic of interest in climate science. Studying rare extreme events with complex numerical climate models is computationally challenging, since in principle very long simulations are needed to sample a sufficient number of events to provide a reliable statistics. This problem can be tackled using rare event algorithms, numerical tools developed in the past decades in mathematics and statistical physics, dedicated to the reduction of the computational effort required to sample rare events in dynamical systems. Typically they are designed as genetic algorithms, in which a set of suppression and cloning rules are applied to an ensemble simulation in order to focus the computational effort on the trajectories leading to the events of interest. Recently we showed the great potential of rare event algorithms for climate modelling, applying a rare event algorithm to study extremes of European surface temperature in Plasim, an intermediate complexity model, in absence of external time dependent forcings (no seasonal and daily cycles). Here we go beyond these limitations, studying extreme heat waves and warm summers in the Northern extratropics in fully realistic conditions including daily and seasonal cycles, both in Plasim and in the state of the art Earth system model CESM. We show how the algorithm allows to sample extreme events characterised by persistency on different time scales, discussing links with large deviation theory. We show how one can characterise the statistics of heat waves and warm summers with extremely large return times, with computational costs orders of magnitude smaller than with direct sampling, and reach ultra rare events that would have been impossible to observe otherwise. We analyse the emergence of teleconnection patterns during the extreme events and their relation to the dynamics of planetary waves. Finally we discuss how these results open the way to the systematic application of these techniques to a vast range of applicative and theoretical studies.
How to cite: Ragone, F. and Bouchet, F.: Studying heat waves and warm summers in numerical climate models with a rare event algorithm, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19177, https://doi.org/10.5194/egusphere-egu2020-19177, 2020.
EGU2020-9554 | Displays | NP1.1
Recent progress and new methods for detecting causal relations in large nonlinear time series datasetsJakob Runge
Detecting causal relationships from observational time series datasets is a key problem in better understanding the complex dynamical system Earth. Recent methodological advances have addressed major challenges such as high-dimensionality and nonlinearity, e.g., PCMCI (Runge et al. Sci. Adv. 2019), but many more remain. In this talk I will give an overview of challenges and methods and present a novel algorithm to identify causal directions among contemporaneous (or instantaneous) relationships. Such contemporaneous relations frequently appear when time series are aggregated (e.g., at a monthly resolution). Then approaches such as Granger Causality and PCMCI fail because they currently only address time-lagged causal relations.
We present extensive numerical examples and results on the causal relations among major climate modes of variability. The work overcomes a major drawback of current causal discovery methods and opens up entirely new possibilities to discover causal relations from time series in climate research and other fields in geosciences.
Runge et al., Detecting and quantifying causal associations in large nonlinear time series datasets, Science Advances eeaau4996 (2019).
How to cite: Runge, J.: Recent progress and new methods for detecting causal relations in large nonlinear time series datasets, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9554, https://doi.org/10.5194/egusphere-egu2020-9554, 2020.
Detecting causal relationships from observational time series datasets is a key problem in better understanding the complex dynamical system Earth. Recent methodological advances have addressed major challenges such as high-dimensionality and nonlinearity, e.g., PCMCI (Runge et al. Sci. Adv. 2019), but many more remain. In this talk I will give an overview of challenges and methods and present a novel algorithm to identify causal directions among contemporaneous (or instantaneous) relationships. Such contemporaneous relations frequently appear when time series are aggregated (e.g., at a monthly resolution). Then approaches such as Granger Causality and PCMCI fail because they currently only address time-lagged causal relations.
We present extensive numerical examples and results on the causal relations among major climate modes of variability. The work overcomes a major drawback of current causal discovery methods and opens up entirely new possibilities to discover causal relations from time series in climate research and other fields in geosciences.
Runge et al., Detecting and quantifying causal associations in large nonlinear time series datasets, Science Advances eeaau4996 (2019).
How to cite: Runge, J.: Recent progress and new methods for detecting causal relations in large nonlinear time series datasets, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9554, https://doi.org/10.5194/egusphere-egu2020-9554, 2020.
EGU2020-19640 | Displays | NP1.1
Insensitivety to initial condition/prior in data assimilation for the case of the optimal filter and deterministic modelLea Oljaca, Jochen Broecker, and Tobias Kuna
Data assimilation is a term used to describe efforts to improve our knowledge
of a system by combining incomplete observations with imperfect models.
This is more generally known as filtering, which is ’optimal’ estimation of
the state of a system as it evolves over time, in the mean square sense. In
a Bayesian framework, the optimal filter is therefore naturally a sequence of
conditional probabilities of a signal given the observations and can be up-
dated recursively with new observations with Bayes’ formula. When, the
dynamics and observations errors are linear, this is equivalent to the Kalman
filter. In the nonlinear case, deriving an explicit form for the posterior dis-
tribution is in general not possible.
One of the important difficulties with applying the nonlinear filter in practice
is that the initial condition, the prior, is required to initialise the filtering.
However we are unlikely to know the correct initial distribution accurately
or at all. A filter is called stable if it is insensitive with respect to the
prior, that is, it converges to the same distribution, regardless of the initial
condition.
A body of work exists showing stability of the filter which rely on the stochas-
ticity of the underlying dynamics. In contrast, we show stability of the op-
timal filter for a class of nonlinear and deterministic dynamical systems and
our result relies on the intrinsic chaotic properties of the dynamics. We build
on the considerable knowledge that exists on the existence of SRB measures
in uniformly hyperbolic dynamical systems and we view the conditional prob-
abilities as SRB measures ‘conditional on the observation’ which are shown
to be absolutely continuous along the unstable manifold. This is in line with
the result of Bouquet, Carrassi et al [1] regarding data assimilation in the
“unstable subspace”, where they show stability of the filter if the unstable
and neutral subspaces are uniformly observed.
[1] M. Bocquet et al. “Degenerate Kalman Filter Error Covariances and
Their Convergence onto the Unstable Subspace”. In: SIAM/ASA Jour-
nal on Uncertainty Quantification 5.1 (2017), pp. 304–333. url: https:
//doi.org/10.1137/16M1068712.
How to cite: Oljaca, L., Broecker, J., and Kuna, T.: Insensitivety to initial condition/prior in data assimilation for the case of the optimal filter and deterministic model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19640, https://doi.org/10.5194/egusphere-egu2020-19640, 2020.
Data assimilation is a term used to describe efforts to improve our knowledge
of a system by combining incomplete observations with imperfect models.
This is more generally known as filtering, which is ’optimal’ estimation of
the state of a system as it evolves over time, in the mean square sense. In
a Bayesian framework, the optimal filter is therefore naturally a sequence of
conditional probabilities of a signal given the observations and can be up-
dated recursively with new observations with Bayes’ formula. When, the
dynamics and observations errors are linear, this is equivalent to the Kalman
filter. In the nonlinear case, deriving an explicit form for the posterior dis-
tribution is in general not possible.
One of the important difficulties with applying the nonlinear filter in practice
is that the initial condition, the prior, is required to initialise the filtering.
However we are unlikely to know the correct initial distribution accurately
or at all. A filter is called stable if it is insensitive with respect to the
prior, that is, it converges to the same distribution, regardless of the initial
condition.
A body of work exists showing stability of the filter which rely on the stochas-
ticity of the underlying dynamics. In contrast, we show stability of the op-
timal filter for a class of nonlinear and deterministic dynamical systems and
our result relies on the intrinsic chaotic properties of the dynamics. We build
on the considerable knowledge that exists on the existence of SRB measures
in uniformly hyperbolic dynamical systems and we view the conditional prob-
abilities as SRB measures ‘conditional on the observation’ which are shown
to be absolutely continuous along the unstable manifold. This is in line with
the result of Bouquet, Carrassi et al [1] regarding data assimilation in the
“unstable subspace”, where they show stability of the filter if the unstable
and neutral subspaces are uniformly observed.
[1] M. Bocquet et al. “Degenerate Kalman Filter Error Covariances and
Their Convergence onto the Unstable Subspace”. In: SIAM/ASA Jour-
nal on Uncertainty Quantification 5.1 (2017), pp. 304–333. url: https:
//doi.org/10.1137/16M1068712.
How to cite: Oljaca, L., Broecker, J., and Kuna, T.: Insensitivety to initial condition/prior in data assimilation for the case of the optimal filter and deterministic model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19640, https://doi.org/10.5194/egusphere-egu2020-19640, 2020.
EGU2020-13794 | Displays | NP1.1 | Highlight
Data-driven parametrizations in numerical models using data assimilation and machine learning.Julien Brajard, Alberto Carrassi, Marc Bocquet, and Laurent Bertino
Can we build a machine learning parametrization in a numerical model using sparse and noisy observations?
In recent years, machine learning (ML) has been proposed to devise data-driven parametrizations of unresolved processes in dynamical numerical models. In most of the cases, ML is trained by coarse-graining high-resolution simulations to provide a dense, unnoisy target state (or even the tendency of the model).
Our goal is to go beyond the use of high-resolution simulations and train ML-based parametrization using direct data. Furthermore, we intentionally place ourselves in the realistic scenario of noisy and sparse observations.
The algorithm proposed in this work derives from the algorithm presented by the same authors in https://arxiv.org/abs/2001.01520.The principle is to first apply data assimilation (DA) techniques to estimate the full state of the system from a non-parametrized model, referred hereafter as the physical model. The parametrization term to be estimated is viewed as a model error in the DA system. In a second step, ML is used to define the parametrization, e.g., a predictor of the model error given the state of the system. Finally, the ML system is incorporated within the physical model to produce a hybrid model, combining a physical core with a ML-based parametrization.
The approach is applied to dynamical systems from low to intermediate complexity. The DA component of the proposed approach relies on an ensemble Kalman filter/smoother while the parametrization is represented by a convolutional neural network.
We show that the hybrid model yields better performance than the physical model in terms of both short-term (forecast skill) and long-term (power spectrum, Lyapunov exponents) properties. Sensitivity to the noise and density of observation is also assessed.
How to cite: Brajard, J., Carrassi, A., Bocquet, M., and Bertino, L.: Data-driven parametrizations in numerical models using data assimilation and machine learning., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13794, https://doi.org/10.5194/egusphere-egu2020-13794, 2020.
Can we build a machine learning parametrization in a numerical model using sparse and noisy observations?
In recent years, machine learning (ML) has been proposed to devise data-driven parametrizations of unresolved processes in dynamical numerical models. In most of the cases, ML is trained by coarse-graining high-resolution simulations to provide a dense, unnoisy target state (or even the tendency of the model).
Our goal is to go beyond the use of high-resolution simulations and train ML-based parametrization using direct data. Furthermore, we intentionally place ourselves in the realistic scenario of noisy and sparse observations.
The algorithm proposed in this work derives from the algorithm presented by the same authors in https://arxiv.org/abs/2001.01520.The principle is to first apply data assimilation (DA) techniques to estimate the full state of the system from a non-parametrized model, referred hereafter as the physical model. The parametrization term to be estimated is viewed as a model error in the DA system. In a second step, ML is used to define the parametrization, e.g., a predictor of the model error given the state of the system. Finally, the ML system is incorporated within the physical model to produce a hybrid model, combining a physical core with a ML-based parametrization.
The approach is applied to dynamical systems from low to intermediate complexity. The DA component of the proposed approach relies on an ensemble Kalman filter/smoother while the parametrization is represented by a convolutional neural network.
We show that the hybrid model yields better performance than the physical model in terms of both short-term (forecast skill) and long-term (power spectrum, Lyapunov exponents) properties. Sensitivity to the noise and density of observation is also assessed.
How to cite: Brajard, J., Carrassi, A., Bocquet, M., and Bertino, L.: Data-driven parametrizations in numerical models using data assimilation and machine learning., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13794, https://doi.org/10.5194/egusphere-egu2020-13794, 2020.
EGU2020-17313 | Displays | NP1.1
Ergodicity of a stochastic Two Layer Quasi Geostrophic ModelGiulia Carigi, Jochen Bröcker, and Tobias Kuna
In the Climate Sciences, there is great interest in understanding the long term average behaviour of the climate system. In the context of climate models, this behaviour can be expressed intrinsically by concepts from the theory of dynamical systems such as attractors and invariant measures. In particular to ensure long term statistics of the model are well defined from a mathematical perspective, the model needs to admit a unique ergodic invariant probability measure.
In this work we consider a classic two layer quasi geostrophic model, with the upper layer perturbed by additive noise, white in time and coloured in space, in order to account for random forcing, for instance through wind shear. Existence and uniqueness of an ergodic invariant measure is established using a technique from stochastic analysis called asymptotic coupling as described in [1]. The main difficulty in the proof is to show that two copies of the system that are driven by the same noise realisation can be synchronised through a coupling. This coupling has to be finite dimensional and act only on the upper layer.
Our results will be a key step to allow rigorous investigation of the response theory for the system under concern.
[1] Glatt-Holtz, N., Mattingly, J.C. & Richards, G. J Stat Phys (2017) 166: 618.
How to cite: Carigi, G., Bröcker, J., and Kuna, T.: Ergodicity of a stochastic Two Layer Quasi Geostrophic Model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17313, https://doi.org/10.5194/egusphere-egu2020-17313, 2020.
In the Climate Sciences, there is great interest in understanding the long term average behaviour of the climate system. In the context of climate models, this behaviour can be expressed intrinsically by concepts from the theory of dynamical systems such as attractors and invariant measures. In particular to ensure long term statistics of the model are well defined from a mathematical perspective, the model needs to admit a unique ergodic invariant probability measure.
In this work we consider a classic two layer quasi geostrophic model, with the upper layer perturbed by additive noise, white in time and coloured in space, in order to account for random forcing, for instance through wind shear. Existence and uniqueness of an ergodic invariant measure is established using a technique from stochastic analysis called asymptotic coupling as described in [1]. The main difficulty in the proof is to show that two copies of the system that are driven by the same noise realisation can be synchronised through a coupling. This coupling has to be finite dimensional and act only on the upper layer.
Our results will be a key step to allow rigorous investigation of the response theory for the system under concern.
[1] Glatt-Holtz, N., Mattingly, J.C. & Richards, G. J Stat Phys (2017) 166: 618.
How to cite: Carigi, G., Bröcker, J., and Kuna, T.: Ergodicity of a stochastic Two Layer Quasi Geostrophic Model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17313, https://doi.org/10.5194/egusphere-egu2020-17313, 2020.
EGU2020-10973 | Displays | NP1.1 | Highlight
The Lorenz convection model's random attractor (LORA) and its robust topologyMichael Ghil, Gisela D. Charó, Denisse Sciamarella, and Mickael D. Chekroun
Chekroun et al. (Physica D, 240, 2011) studied the global random attractor associated with the Lorenz (1963) model driven by multiplicative noise; they dubbed this time-evolving attractor LORA for short. The present talk examines the topological structure of the snapshots that approximate LORA’s evolution in time.
Sciamarella & Mindlin (Phys. Rev. Lett., 82, 1999; Phys. Rev. E, 64, 2001) introduced the methodology of Branched Manifold Analysis through Homologies (BraMAH) to the study of chaotic flows. Here, the BraMAH methodology is extended for the first time, to the best of our knowledge, from deterministically chaotic flows to nonlinear noise-driven systems.
The BraMAH algorithm starts from a cloud of points given by a large number of orbits and it builds a rough skeleton of the underlying branched manifold on which the points lie. This construction is achieved by local approximations of the manifold that use Euclidean closed sets; the nature of these sets depends on their topological dimension, e.g., segments or disks. The skeleton is mathematically expressed as a complex of cells, whose algebraic topology is analyzed by computing its homology groups.
The analysis is performed for a fixed realization of the driving noise at different time instants. We show that the topology of LORA changes in time and that it is quite distinct from the time-independent one of the classical Lorenz (1963) convection model, for the same values of the parameters. Topological tipping points are also studied by varying the parameter values from the classical ones.
How to cite: Ghil, M., Charó, G. D., Sciamarella, D., and Chekroun, M. D.: The Lorenz convection model's random attractor (LORA) and its robust topology, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10973, https://doi.org/10.5194/egusphere-egu2020-10973, 2020.
Chekroun et al. (Physica D, 240, 2011) studied the global random attractor associated with the Lorenz (1963) model driven by multiplicative noise; they dubbed this time-evolving attractor LORA for short. The present talk examines the topological structure of the snapshots that approximate LORA’s evolution in time.
Sciamarella & Mindlin (Phys. Rev. Lett., 82, 1999; Phys. Rev. E, 64, 2001) introduced the methodology of Branched Manifold Analysis through Homologies (BraMAH) to the study of chaotic flows. Here, the BraMAH methodology is extended for the first time, to the best of our knowledge, from deterministically chaotic flows to nonlinear noise-driven systems.
The BraMAH algorithm starts from a cloud of points given by a large number of orbits and it builds a rough skeleton of the underlying branched manifold on which the points lie. This construction is achieved by local approximations of the manifold that use Euclidean closed sets; the nature of these sets depends on their topological dimension, e.g., segments or disks. The skeleton is mathematically expressed as a complex of cells, whose algebraic topology is analyzed by computing its homology groups.
The analysis is performed for a fixed realization of the driving noise at different time instants. We show that the topology of LORA changes in time and that it is quite distinct from the time-independent one of the classical Lorenz (1963) convection model, for the same values of the parameters. Topological tipping points are also studied by varying the parameter values from the classical ones.
How to cite: Ghil, M., Charó, G. D., Sciamarella, D., and Chekroun, M. D.: The Lorenz convection model's random attractor (LORA) and its robust topology, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10973, https://doi.org/10.5194/egusphere-egu2020-10973, 2020.
EGU2020-9994 | Displays | NP1.1
Energy Transfers Between Balanced and Unbalanced Motions in Geophysical FlowsManita Chouksey
Geophysical flows such as the atmosphere and the ocean are characterized by rotation and stratification, which together give rise to two dominant motions: the slow balanced and the fast unbalanced motions. The interaction between the balanced and unbalanced motions and the energy transfers between them impact the energy and momentum cycle of the flow, and is therefore crucial to understand the underlying energetics of the atmosphere and the ocean. Balanced motions, for instance mesoscale eddies, can transfer their energy to unbalanced motions, such as internal gravity waves, by spontaneous loss of balance amongst other processes. The exact mechanism of wave generation, however, remain less understood and is hindered to an extent by the challenge of separating the flow field into balanced and unbalanced motions.
This separation is achieved using two different balancing procedures in an identical model setup and assess the differences in the obtained balanced state and the resultant energy transfer to unbalanced motions. The first procedure we implement is a non-linear initialisation procedure based on Machenhauer (1977) but extended to higher orders in Rossby number. The second procedure implemented is the optimal potential vorticity balance to achieve the balanced state. The results show that the numerics of the model affect the obtained balanced state from the two procedures, and thus the residual signal which we interpret as the unbalanced motions, i.e. internal gravity waves. A further complication is the presence of slaved modes, which appear along the unbalanced motions but are tied to the balanced motions, for which we need to extend the separation to higher orders in Rossby number. Further, we assess the energy transfers between balanced and unbalanced motions in experiments with different Rossby numbers and for different orders in Rossby number. We find that it is crucial to consider the effect of the numerics in models and make a suitable choice of the balancing procedure, as well as diagnose the unbalanced motions at higher orders to precisely detect the unbalanced wave signal.
How to cite: Chouksey, M.: Energy Transfers Between Balanced and Unbalanced Motions in Geophysical Flows, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9994, https://doi.org/10.5194/egusphere-egu2020-9994, 2020.
Geophysical flows such as the atmosphere and the ocean are characterized by rotation and stratification, which together give rise to two dominant motions: the slow balanced and the fast unbalanced motions. The interaction between the balanced and unbalanced motions and the energy transfers between them impact the energy and momentum cycle of the flow, and is therefore crucial to understand the underlying energetics of the atmosphere and the ocean. Balanced motions, for instance mesoscale eddies, can transfer their energy to unbalanced motions, such as internal gravity waves, by spontaneous loss of balance amongst other processes. The exact mechanism of wave generation, however, remain less understood and is hindered to an extent by the challenge of separating the flow field into balanced and unbalanced motions.
This separation is achieved using two different balancing procedures in an identical model setup and assess the differences in the obtained balanced state and the resultant energy transfer to unbalanced motions. The first procedure we implement is a non-linear initialisation procedure based on Machenhauer (1977) but extended to higher orders in Rossby number. The second procedure implemented is the optimal potential vorticity balance to achieve the balanced state. The results show that the numerics of the model affect the obtained balanced state from the two procedures, and thus the residual signal which we interpret as the unbalanced motions, i.e. internal gravity waves. A further complication is the presence of slaved modes, which appear along the unbalanced motions but are tied to the balanced motions, for which we need to extend the separation to higher orders in Rossby number. Further, we assess the energy transfers between balanced and unbalanced motions in experiments with different Rossby numbers and for different orders in Rossby number. We find that it is crucial to consider the effect of the numerics in models and make a suitable choice of the balancing procedure, as well as diagnose the unbalanced motions at higher orders to precisely detect the unbalanced wave signal.
How to cite: Chouksey, M.: Energy Transfers Between Balanced and Unbalanced Motions in Geophysical Flows, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9994, https://doi.org/10.5194/egusphere-egu2020-9994, 2020.
EGU2020-18301 | Displays | NP1.1 | Highlight
Analysing Conceptual Climate Models with Monte Carlo Basin Bifurcation AnalysisMaximilian Gelbrecht, Jürgen Kurths, and Frank Hellmann
Many high-dimensional complex systems such as climate models exhibit an enormously complex landscape of possible asymptotic state. On most occasions these are challenging to analyse with traditional bifurcation analysis methods. Often, one is also more broadly interested in classes of asymptotic states. Here, we present a novel numerical approach prepared for analysing such high-dimensional multistable complex systems: Monte Carlo Basin Bifurcation Analysis (MCBB). Based on random sampling and clustering methods, we identify the type of dynamic regimes with the largest basins of attraction and track how the volume of these basins change with the system parameters. In order to due this suitable, easy to compute, statistics of trajectories with randomly generated initial conditions and parameters are clustered by an algorithm such as DBSCAN. Due to the modular and flexible nature of the method, it has a wide range of possible applications. While initially oscillator networks were one of the main applications of this methods, here we present an analysis of a simple conceptual climate model setup up by coupling an energy balance model to the Lorenz96 system. The method is available to use as a package for the Julia language.
How to cite: Gelbrecht, M., Kurths, J., and Hellmann, F.: Analysing Conceptual Climate Models with Monte Carlo Basin Bifurcation Analysis, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18301, https://doi.org/10.5194/egusphere-egu2020-18301, 2020.
Many high-dimensional complex systems such as climate models exhibit an enormously complex landscape of possible asymptotic state. On most occasions these are challenging to analyse with traditional bifurcation analysis methods. Often, one is also more broadly interested in classes of asymptotic states. Here, we present a novel numerical approach prepared for analysing such high-dimensional multistable complex systems: Monte Carlo Basin Bifurcation Analysis (MCBB). Based on random sampling and clustering methods, we identify the type of dynamic regimes with the largest basins of attraction and track how the volume of these basins change with the system parameters. In order to due this suitable, easy to compute, statistics of trajectories with randomly generated initial conditions and parameters are clustered by an algorithm such as DBSCAN. Due to the modular and flexible nature of the method, it has a wide range of possible applications. While initially oscillator networks were one of the main applications of this methods, here we present an analysis of a simple conceptual climate model setup up by coupling an energy balance model to the Lorenz96 system. The method is available to use as a package for the Julia language.
How to cite: Gelbrecht, M., Kurths, J., and Hellmann, F.: Analysing Conceptual Climate Models with Monte Carlo Basin Bifurcation Analysis, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18301, https://doi.org/10.5194/egusphere-egu2020-18301, 2020.
EGU2020-11557 | Displays | NP1.1
Correcting Budyko-Sellers boundary conditions: The Half-order Energy Balance Equation (HEBE)Shaun Lovejoy, Lenin Del Rio Amador, and Roman Procyk
The conventional 1-D energy balance equation (EBE) has no vertical coordinate so that radiative imbalances between the earth and outer space are redirected in the horizontal in an ad hoc manner. We retain the basic EBE but add a vertical coordinate so that the imbalances drive the system by imposing heat fluxes through the surface. While this is theoretically correct, it leads to (apparently) difficult mixed boundary conditions. However, using Babenko’s method, we directly obtain simple analytic equations for (2D) surface temperature anomalies Ts(x,t): the Half-order Energy Balance Equation (HEBE) and the Generalized HEBE, (GHEBE) [Lovejoy, 2019a]. The HEBE anomaly equation only depends on the local climate sensitivities and relaxation times. We analytically solve the HEBE and GHEBE for Ts(x,t) and provide evidence that the HEBE applies at scales >≈10km. We also calculate very long time diffusive transport dominated climate states as well as space-time statistics including the cross-correlation matrix needed for empirical orthogonal functions.
The HEBE is the special H = 1/2 case of the Fractional EBE (FEBE) [Lovejoy, 2019b], [Lovejoy, 2019c] and has a long (power law) memory up to its relaxation time t. Several papers have empirically estimated H ≈ 0.5, as well as t ≈ 4 years, whereas the classical zero-dimensional EBE has H = 1 and t ≈ 4 years. The former values permit accurate macroweather forecasts and low uncertainty climate projections; this suggests that the HEBE could apply to time scales as short as a month. Future generalizations include albedo-temperature feedbacks and more realistic treatments of past and future climate states.
References
Lovejoy, S., The half-order energy balance equation, J. Geophys. Res. (Atmos.), (submitted, Nov. 2019), 2019a.
Lovejoy, S., Weather, Macroweather and Climate: our random yet predictable atmosphere, 334 pp., Oxford U. Press, 2019b.
Lovejoy, S., Fractional Relaxation noises, motions and the stochastic fractional relxation equation Nonlinear Proc. in Geophys. Disc., https://doi.org/10.5194/npg-2019-39, 2019c.
How to cite: Lovejoy, S., Del Rio Amador, L., and Procyk, R.: Correcting Budyko-Sellers boundary conditions: The Half-order Energy Balance Equation (HEBE), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11557, https://doi.org/10.5194/egusphere-egu2020-11557, 2020.
The conventional 1-D energy balance equation (EBE) has no vertical coordinate so that radiative imbalances between the earth and outer space are redirected in the horizontal in an ad hoc manner. We retain the basic EBE but add a vertical coordinate so that the imbalances drive the system by imposing heat fluxes through the surface. While this is theoretically correct, it leads to (apparently) difficult mixed boundary conditions. However, using Babenko’s method, we directly obtain simple analytic equations for (2D) surface temperature anomalies Ts(x,t): the Half-order Energy Balance Equation (HEBE) and the Generalized HEBE, (GHEBE) [Lovejoy, 2019a]. The HEBE anomaly equation only depends on the local climate sensitivities and relaxation times. We analytically solve the HEBE and GHEBE for Ts(x,t) and provide evidence that the HEBE applies at scales >≈10km. We also calculate very long time diffusive transport dominated climate states as well as space-time statistics including the cross-correlation matrix needed for empirical orthogonal functions.
The HEBE is the special H = 1/2 case of the Fractional EBE (FEBE) [Lovejoy, 2019b], [Lovejoy, 2019c] and has a long (power law) memory up to its relaxation time t. Several papers have empirically estimated H ≈ 0.5, as well as t ≈ 4 years, whereas the classical zero-dimensional EBE has H = 1 and t ≈ 4 years. The former values permit accurate macroweather forecasts and low uncertainty climate projections; this suggests that the HEBE could apply to time scales as short as a month. Future generalizations include albedo-temperature feedbacks and more realistic treatments of past and future climate states.
References
Lovejoy, S., The half-order energy balance equation, J. Geophys. Res. (Atmos.), (submitted, Nov. 2019), 2019a.
Lovejoy, S., Weather, Macroweather and Climate: our random yet predictable atmosphere, 334 pp., Oxford U. Press, 2019b.
Lovejoy, S., Fractional Relaxation noises, motions and the stochastic fractional relxation equation Nonlinear Proc. in Geophys. Disc., https://doi.org/10.5194/npg-2019-39, 2019c.
How to cite: Lovejoy, S., Del Rio Amador, L., and Procyk, R.: Correcting Budyko-Sellers boundary conditions: The Half-order Energy Balance Equation (HEBE), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11557, https://doi.org/10.5194/egusphere-egu2020-11557, 2020.
EGU2020-10021 | Displays | NP1.1
Network models for ponding on sea iceMichael Coughlan, Ian Hewitt, Sam Howison, and Andrew Wells
Arctic sea ice forms a thin but significant layer at the ocean surface, mediating key climate feedbacks. During summer, surface melting produces considerable volumes of water, which collect on the ice surface in ponds. These ponds have long been suggested as a contributing factor to the discrepancy between observed and predicted sea ice extent. When viewed at large scales ponds have a complicated, approximately fractal geometry and vary in area from tens to thousands of square meters. Increases in pond depth and area lead to further increases in heat absorption and overall melting, contributing to the ice-albedo feedback.
Previous modelling work has focussed either on the physics of individual ponds or on the statistical behaviour of systems of ponds. We present a physically-based network model for systems of ponds which accounts for both the individual and collective behaviour of ponds. Each pond initially occupies a distinct catchment basin and evolves according to a mass-conserving differential equation representing the melting dynamics for bare and water-covered ice. Ponds can later connect together to form a network with fluxes of water between catchment areas, constrained by the ice topography and pond water levels.
We use the model to explore how the evolution of pond area and hence melting depends on the governing parameters, and to explore how the connections between ponds develop over the melt season. Comparisons with observations are made to demonstrate the ways in which the model qualitatively replicates properties of pond systems, including fractal dimension of pond areas and two distinct regimes of pond complexity that are observed during their development cycle. Different perimeter-area relationships exist for ponds in the two regimes. The model replicates these relationships and exhibits a percolation transition around the transition between these regimes, a facet of pond behaviour suggested by previous studies. Our results reinforce the findings of these studies on percolation thresholds in pond systems and further allow us to constrain pond coverage at this threshold - an important quantity in measuring the scale and effects of the ice-albedo feedback.
How to cite: Coughlan, M., Hewitt, I., Howison, S., and Wells, A.: Network models for ponding on sea ice, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10021, https://doi.org/10.5194/egusphere-egu2020-10021, 2020.
Arctic sea ice forms a thin but significant layer at the ocean surface, mediating key climate feedbacks. During summer, surface melting produces considerable volumes of water, which collect on the ice surface in ponds. These ponds have long been suggested as a contributing factor to the discrepancy between observed and predicted sea ice extent. When viewed at large scales ponds have a complicated, approximately fractal geometry and vary in area from tens to thousands of square meters. Increases in pond depth and area lead to further increases in heat absorption and overall melting, contributing to the ice-albedo feedback.
Previous modelling work has focussed either on the physics of individual ponds or on the statistical behaviour of systems of ponds. We present a physically-based network model for systems of ponds which accounts for both the individual and collective behaviour of ponds. Each pond initially occupies a distinct catchment basin and evolves according to a mass-conserving differential equation representing the melting dynamics for bare and water-covered ice. Ponds can later connect together to form a network with fluxes of water between catchment areas, constrained by the ice topography and pond water levels.
We use the model to explore how the evolution of pond area and hence melting depends on the governing parameters, and to explore how the connections between ponds develop over the melt season. Comparisons with observations are made to demonstrate the ways in which the model qualitatively replicates properties of pond systems, including fractal dimension of pond areas and two distinct regimes of pond complexity that are observed during their development cycle. Different perimeter-area relationships exist for ponds in the two regimes. The model replicates these relationships and exhibits a percolation transition around the transition between these regimes, a facet of pond behaviour suggested by previous studies. Our results reinforce the findings of these studies on percolation thresholds in pond systems and further allow us to constrain pond coverage at this threshold - an important quantity in measuring the scale and effects of the ice-albedo feedback.
How to cite: Coughlan, M., Hewitt, I., Howison, S., and Wells, A.: Network models for ponding on sea ice, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10021, https://doi.org/10.5194/egusphere-egu2020-10021, 2020.
EGU2020-8689 | Displays | NP1.1
Morphology of scallop patterns in erosion by dissolutionMichael Berhanu, Raphael Dubourg, Arthur Walbecq, Cyril Ozouf, Adrien Guerin, Julien Derr, and Sylvain Courrech du Pont
Erosion by dissolution is a decisive process shaping small-scale landscape morphology [1]. For fast dissolving minerals, the erosion rate is controlled by the solute transport [2] and characteristic erosion patterns can appear due to hydrodynamics mechanisms. Among the diversity of the dissolution patterns, the scallops are small depressions in a dissolving wall, appearing as cups with sharp edges. Their size varies from few millimeters to around ten centimeters. The scallops occur typically as the final steady form of ripple patterns created by the action of a turbulent flow on a dissolving surface [3,4]. Moreover, very similar shapes are also met, without imposed external flow, when the fluid motion results from the solutal convection induced by the dissolution [2,5,6]. Finally, scallop patterns resulting from similar mechanisms appear also on ice surfaces by melting in presence of a turbulent flow [7] or a convection flow [6].
Using three-dimensional surface reconstruction, we characterize quantitatively the scallop patterns mainly for experimental samples patterned by solutal convection. The temporal evolution of the scallop shape, of their spatial distribution and of the induced roughness are specifically investigated, in order to determine mechanisms explaining the generic aspects of dissolution patterns.
[1] P. Meakin and B. Jamtveit, Geological pattern formation by growth and dissolution in aqueous systems, Proc. R. Soc. A 466 659-694 (2010)
[2] J. Philippi, M. Berhanu, J. Derr and S. Courrech du Pont, Solutal convection induced by dissolution, Phys. Rev. Fluids, 4, 103801 (2019)
[3] P.N. Blumberg and R.L. Curl, Experimental and theoretical studies of dissolution roughness, J. Fluid Mech. 65, 735 (1974)
[4] P. Claudin, O. Durán and B. Andreotti, Dissolution instability and roughening transition, J. Fluid Mech. 832, R2 (1974)
[5] T.S. Sullivan, Y. Liu and R. E. Ecke, Turbulent solutal convection and surface patterning in solid dissolution, Phys. Rev. E 54, (1) 486, (1996)
[6] C. Cohen, M. Berhanu, J. Derr and S. Courrech du Pont, Erosion patterns on dissolving and melting bodies (2015 Gallery of Fluid motion), Phys. Rev. Fluids, 1, 050508 (2016)
[7] M. Bushuk, D. M. Holland, T. P. Stanton, A. Stern and C. Gray. Ice scallops: a laboratory investigation of the Ice-water interface, J. Fluid Mech. 873, 942 (2019)
How to cite: Berhanu, M., Dubourg, R., Walbecq, A., Ozouf, C., Guerin, A., Derr, J., and Courrech du Pont, S.: Morphology of scallop patterns in erosion by dissolution, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8689, https://doi.org/10.5194/egusphere-egu2020-8689, 2020.
Erosion by dissolution is a decisive process shaping small-scale landscape morphology [1]. For fast dissolving minerals, the erosion rate is controlled by the solute transport [2] and characteristic erosion patterns can appear due to hydrodynamics mechanisms. Among the diversity of the dissolution patterns, the scallops are small depressions in a dissolving wall, appearing as cups with sharp edges. Their size varies from few millimeters to around ten centimeters. The scallops occur typically as the final steady form of ripple patterns created by the action of a turbulent flow on a dissolving surface [3,4]. Moreover, very similar shapes are also met, without imposed external flow, when the fluid motion results from the solutal convection induced by the dissolution [2,5,6]. Finally, scallop patterns resulting from similar mechanisms appear also on ice surfaces by melting in presence of a turbulent flow [7] or a convection flow [6].
Using three-dimensional surface reconstruction, we characterize quantitatively the scallop patterns mainly for experimental samples patterned by solutal convection. The temporal evolution of the scallop shape, of their spatial distribution and of the induced roughness are specifically investigated, in order to determine mechanisms explaining the generic aspects of dissolution patterns.
[1] P. Meakin and B. Jamtveit, Geological pattern formation by growth and dissolution in aqueous systems, Proc. R. Soc. A 466 659-694 (2010)
[2] J. Philippi, M. Berhanu, J. Derr and S. Courrech du Pont, Solutal convection induced by dissolution, Phys. Rev. Fluids, 4, 103801 (2019)
[3] P.N. Blumberg and R.L. Curl, Experimental and theoretical studies of dissolution roughness, J. Fluid Mech. 65, 735 (1974)
[4] P. Claudin, O. Durán and B. Andreotti, Dissolution instability and roughening transition, J. Fluid Mech. 832, R2 (1974)
[5] T.S. Sullivan, Y. Liu and R. E. Ecke, Turbulent solutal convection and surface patterning in solid dissolution, Phys. Rev. E 54, (1) 486, (1996)
[6] C. Cohen, M. Berhanu, J. Derr and S. Courrech du Pont, Erosion patterns on dissolving and melting bodies (2015 Gallery of Fluid motion), Phys. Rev. Fluids, 1, 050508 (2016)
[7] M. Bushuk, D. M. Holland, T. P. Stanton, A. Stern and C. Gray. Ice scallops: a laboratory investigation of the Ice-water interface, J. Fluid Mech. 873, 942 (2019)
How to cite: Berhanu, M., Dubourg, R., Walbecq, A., Ozouf, C., Guerin, A., Derr, J., and Courrech du Pont, S.: Morphology of scallop patterns in erosion by dissolution, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8689, https://doi.org/10.5194/egusphere-egu2020-8689, 2020.
EGU2020-182 | Displays | NP1.1
Proto-dune formation under a bimodal wind regimePauline Delorme, Giles Wiggs, Matthew Baddock, Joanna Nield, James Best, Kenneth Christensen, Nathaniel Bristow, Andrew Valdez, and Philippe Claudin
Early-stage aeolian bedforms develop into sand dunes through complex interactions between flow, sediment transport and surface topography. Depending on the specific environmental and wind conditions the mechanisms of dune formation, and ultimately the shape of the nascent dunes, may differ. Here, we investigate the formation of a proto-dune-field, located in the Great Sand Dunes National Park ( Colorado, USA), using a three dimensional linear stability analysis.
We use in-situ measurements of wind and sediment transport, collected during a one-month field campaign, as part of a linear stability analysis to predict the orientation and wavelength of the proto-dunes.
We find that the output of the linear stability analysis compares well to high-resolution Digital Elevation Models measured using terrestrial laser scanning. Our findings suggest that the bed instability mechanism is a good predictor of proto-dune development on sandy surfaces with a bimodal wind regime.
How to cite: Delorme, P., Wiggs, G., Baddock, M., Nield, J., Best, J., Christensen, K., Bristow, N., Valdez, A., and Claudin, P.: Proto-dune formation under a bimodal wind regime, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-182, https://doi.org/10.5194/egusphere-egu2020-182, 2020.
Early-stage aeolian bedforms develop into sand dunes through complex interactions between flow, sediment transport and surface topography. Depending on the specific environmental and wind conditions the mechanisms of dune formation, and ultimately the shape of the nascent dunes, may differ. Here, we investigate the formation of a proto-dune-field, located in the Great Sand Dunes National Park ( Colorado, USA), using a three dimensional linear stability analysis.
We use in-situ measurements of wind and sediment transport, collected during a one-month field campaign, as part of a linear stability analysis to predict the orientation and wavelength of the proto-dunes.
We find that the output of the linear stability analysis compares well to high-resolution Digital Elevation Models measured using terrestrial laser scanning. Our findings suggest that the bed instability mechanism is a good predictor of proto-dune development on sandy surfaces with a bimodal wind regime.
How to cite: Delorme, P., Wiggs, G., Baddock, M., Nield, J., Best, J., Christensen, K., Bristow, N., Valdez, A., and Claudin, P.: Proto-dune formation under a bimodal wind regime, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-182, https://doi.org/10.5194/egusphere-egu2020-182, 2020.
EGU2020-11309 | Displays | NP1.1
Optimality in landscape channelization and analogy with turbulenceMilad Hooshyar, Sara Bonetti, Arvind Singh, Efi Foufoula-Georgiou, and Amilcare Porporato
The channelization cascade observed in terrestrial landscapes describes the progressive formation of large channels from smaller ones starting from diffusion-dominated hillslopes. This behavior is reminiscent of other non-equilibrium complex systems, particularly fluids turbulence, where larger vortices break down into smaller ones until viscous dissipation dominates. Based on this analogy, we show that topographic surfaces emerging between parallel zero-elevation boundaries present a logarithmic scaling in the mean-elevation profile, which resembles the well-known logarithmic velocity profile in wall-bounded turbulence. Within this region of elevation fluctuation, the power spectrum exhibits a power-law decay resembling the Kolmogorov -5/3 scaling of turbulence. We also demonstrate that similar scaling behaviors emerge in surfaces from a laboratory experiment, natural basins, and constructed following optimality principles. In general, we show that the steady-state solutions of the governing equations of landscape evolution are the stationary surfaces of a functional defined as the average domain elevation. Depending on the exponent of the specific drainage area in the erosion term (m), the steady-state surfaces are local minimum (m<1) or maximum (m>1) of the average domain elevation.
How to cite: Hooshyar, M., Bonetti, S., Singh, A., Foufoula-Georgiou, E., and Porporato, A.: Optimality in landscape channelization and analogy with turbulence, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11309, https://doi.org/10.5194/egusphere-egu2020-11309, 2020.
The channelization cascade observed in terrestrial landscapes describes the progressive formation of large channels from smaller ones starting from diffusion-dominated hillslopes. This behavior is reminiscent of other non-equilibrium complex systems, particularly fluids turbulence, where larger vortices break down into smaller ones until viscous dissipation dominates. Based on this analogy, we show that topographic surfaces emerging between parallel zero-elevation boundaries present a logarithmic scaling in the mean-elevation profile, which resembles the well-known logarithmic velocity profile in wall-bounded turbulence. Within this region of elevation fluctuation, the power spectrum exhibits a power-law decay resembling the Kolmogorov -5/3 scaling of turbulence. We also demonstrate that similar scaling behaviors emerge in surfaces from a laboratory experiment, natural basins, and constructed following optimality principles. In general, we show that the steady-state solutions of the governing equations of landscape evolution are the stationary surfaces of a functional defined as the average domain elevation. Depending on the exponent of the specific drainage area in the erosion term (m), the steady-state surfaces are local minimum (m<1) or maximum (m>1) of the average domain elevation.
How to cite: Hooshyar, M., Bonetti, S., Singh, A., Foufoula-Georgiou, E., and Porporato, A.: Optimality in landscape channelization and analogy with turbulence, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11309, https://doi.org/10.5194/egusphere-egu2020-11309, 2020.
EGU2020-4854 | Displays | NP1.1
Response and Sensitivity Using Markov ChainsManuel Santos Gutiérrez and Valerio Lucarini
Dynamical systems are often subject to forcing or changes in their governing parameters and it is of interest to study
how this affects their statistical properties. A prominent real-life example of this class of problems is the investigation
of climate response to perturbations. In this respect, it is crucial to determine what the linear response of a system is
as a quantification of sensitivity. Alongside previous work, here we use the transfer operator formalism to study the
response and sensitivity of a dynamical system undergoing perturbations. By projecting the transfer operator onto a
suitable finite dimensional vector space, one is able to obtain matrix representations which determine finite Markov
processes. Further, using perturbation theory for Markov matrices, it is possible to determine the linear and nonlinear
response of the system given a prescribed forcing. Here, we suggest a methodology which puts the scope on the
evolution law of densities (the Liouville/Fokker-Planck equation), allowing to effectively calculate the sensitivity and
response of two representative dynamical systems.
How to cite: Santos Gutiérrez, M. and Lucarini, V.: Response and Sensitivity Using Markov Chains, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4854, https://doi.org/10.5194/egusphere-egu2020-4854, 2020.
Dynamical systems are often subject to forcing or changes in their governing parameters and it is of interest to study
how this affects their statistical properties. A prominent real-life example of this class of problems is the investigation
of climate response to perturbations. In this respect, it is crucial to determine what the linear response of a system is
as a quantification of sensitivity. Alongside previous work, here we use the transfer operator formalism to study the
response and sensitivity of a dynamical system undergoing perturbations. By projecting the transfer operator onto a
suitable finite dimensional vector space, one is able to obtain matrix representations which determine finite Markov
processes. Further, using perturbation theory for Markov matrices, it is possible to determine the linear and nonlinear
response of the system given a prescribed forcing. Here, we suggest a methodology which puts the scope on the
evolution law of densities (the Liouville/Fokker-Planck equation), allowing to effectively calculate the sensitivity and
response of two representative dynamical systems.
How to cite: Santos Gutiérrez, M. and Lucarini, V.: Response and Sensitivity Using Markov Chains, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4854, https://doi.org/10.5194/egusphere-egu2020-4854, 2020.
EGU2020-9174 | Displays | NP1.1
Predicting Climate Change through Response Operators in a Coupled General Circulation ModelValerio Lembo, Valerio Lucarini, and Francesco Ragone
Global Climate Models are key tools for predicting the future response of the climate system to a variety of natural and anthropogenic forcings. Typically, an ensemble of simulations is performed considering a scenario of forcing, in order to analyse the response of the climate system to the specific forcing signal. Given that the the climate response spans a very large range of timescales, such a strategy often requires a dramatic amount of computational resources. In this paper we show how to use statistical mechanics to construct operators able to flexibly predict climate change for a variety of climatic variables of interest, going beyond the limitation of having to consider specific time patterns of forcing. We perform our study on a fully coupled GCM - MPI-ESM v.1.2 - and for the first time we prove the effectiveness of response theory in predicting future climate response to CO2 increase on a vast range of temporal scales. We specifically treat atmospheric (surface temperature) and oceanic variables (strength of the Atlantic Meridional Overturning Circulation and of the Antarctic Circumpolar Current), as well as the global ocean heat uptake.
How to cite: Lembo, V., Lucarini, V., and Ragone, F.: Predicting Climate Change through Response Operators in a Coupled General Circulation Model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9174, https://doi.org/10.5194/egusphere-egu2020-9174, 2020.
Global Climate Models are key tools for predicting the future response of the climate system to a variety of natural and anthropogenic forcings. Typically, an ensemble of simulations is performed considering a scenario of forcing, in order to analyse the response of the climate system to the specific forcing signal. Given that the the climate response spans a very large range of timescales, such a strategy often requires a dramatic amount of computational resources. In this paper we show how to use statistical mechanics to construct operators able to flexibly predict climate change for a variety of climatic variables of interest, going beyond the limitation of having to consider specific time patterns of forcing. We perform our study on a fully coupled GCM - MPI-ESM v.1.2 - and for the first time we prove the effectiveness of response theory in predicting future climate response to CO2 increase on a vast range of temporal scales. We specifically treat atmospheric (surface temperature) and oceanic variables (strength of the Atlantic Meridional Overturning Circulation and of the Antarctic Circumpolar Current), as well as the global ocean heat uptake.
How to cite: Lembo, V., Lucarini, V., and Ragone, F.: Predicting Climate Change through Response Operators in a Coupled General Circulation Model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9174, https://doi.org/10.5194/egusphere-egu2020-9174, 2020.
EGU2020-17967 | Displays | NP1.1
Effective forcing in CMIP5 assuming nonconstant feedback parameter and linear responseHege-Beate Fredriksen
We investigate a new algorithm for estimating time-evolving global forcing in climate models. The method is an extension of a previous method by Forster et al. (2013), but here we also allow for a globally nonlinear feedback. We assume the nonlinearity of this global feedback can be explained as a time-scale dependence, associated with linear temperature responses to the forcing on different time scales, as in Proistosescu and Huybers (2017). With this method we obtain stronger forcing estimates than previously believed for the representative concentration pathway experiments in CMIP5 models. The reason for the higher future forcing is that the global feedback has a higher magnitude at the smaller time scales than at the longer time scales – this is closely related to provided arguments for the equilibrium climate sensitivity showing changes with time.
We find also that the linear temperature response to our new forcing predicts the modelled response quite well, although the response is a little overestimated for some CMIP5 models. Finally, we discuss the assumptions made in our study, and consistency of our assumptions with other leading hypotheses for why the global feedback is nonlinear.
References:
Forster, P. M., T. Andrews, P. Good, J. M. Gregory, L. S. Jackson, and M. Zelinka (2013), Evaluating adjusted forcing and model spread for historical and future scenarios in the cmip5 generation of climate models, Journal of Geophysical Research, 118, 1139–1150, doi:10.1002/jgrd.50174.
Proistosescu, C., and P. J. Huybers (2017), Slow climate mode reconciles historical and model-based estimates of climate sensitivity, Sci. Adv., 3, e1602, 821, doi:10.1126/sciadv.1602821
How to cite: Fredriksen, H.-B.: Effective forcing in CMIP5 assuming nonconstant feedback parameter and linear response, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17967, https://doi.org/10.5194/egusphere-egu2020-17967, 2020.
We investigate a new algorithm for estimating time-evolving global forcing in climate models. The method is an extension of a previous method by Forster et al. (2013), but here we also allow for a globally nonlinear feedback. We assume the nonlinearity of this global feedback can be explained as a time-scale dependence, associated with linear temperature responses to the forcing on different time scales, as in Proistosescu and Huybers (2017). With this method we obtain stronger forcing estimates than previously believed for the representative concentration pathway experiments in CMIP5 models. The reason for the higher future forcing is that the global feedback has a higher magnitude at the smaller time scales than at the longer time scales – this is closely related to provided arguments for the equilibrium climate sensitivity showing changes with time.
We find also that the linear temperature response to our new forcing predicts the modelled response quite well, although the response is a little overestimated for some CMIP5 models. Finally, we discuss the assumptions made in our study, and consistency of our assumptions with other leading hypotheses for why the global feedback is nonlinear.
References:
Forster, P. M., T. Andrews, P. Good, J. M. Gregory, L. S. Jackson, and M. Zelinka (2013), Evaluating adjusted forcing and model spread for historical and future scenarios in the cmip5 generation of climate models, Journal of Geophysical Research, 118, 1139–1150, doi:10.1002/jgrd.50174.
Proistosescu, C., and P. J. Huybers (2017), Slow climate mode reconciles historical and model-based estimates of climate sensitivity, Sci. Adv., 3, e1602, 821, doi:10.1126/sciadv.1602821
How to cite: Fredriksen, H.-B.: Effective forcing in CMIP5 assuming nonconstant feedback parameter and linear response, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17967, https://doi.org/10.5194/egusphere-egu2020-17967, 2020.
EGU2020-18823 | Displays | NP1.1
Unstable Periodic Orbits Sampling in Climate ModelsChiara Cecilia Maiocchi, Valerio Lucarini, Andrey Gritsun, and Grigorios Pavliotis
Unstable periodic orbits (UPOs) have been proved to be a relevant mathematical tool in the study of Climate Science. In a recent paper Lucarini and Gritsun [1] provided an alternative approach for understanding the properties of the atmosphere. Climate can be interpreted as a non-equilibrium steady state system and, as such, statistical mechanics can provide us with tools for its study.
UPOs decomposition plays a relevant role in the study of chaotic dynamical systems. In fact, UPOs densely populate the attractor of a chaotic system, and can therefore be thought as building blocks to construct the dynamic of the system itself. Since they are dense in the attractor, it is always possible to find a UPO arbitrarily near to a chaotic trajectory: the trajectory will remain close to the UPO, but it will never follow it indefinitely, because of its instability. Loosely speaking, a chaotic trajectory is repelled between neighbourhoods of different UPOs and can thus be approximated in terms of these periodic orbits. The characteristics of the system can then be reconstructed from the full set of periodic orbits in this fashion.
The sampling of UPOs is therefore a relevant problem for describing chaotic dynamical systems and can represent an interesting topic for the study of Climate Science. In this work we address this problem and present an algorithm to numerically extract UPOs from the attractor of a simple Climate Model such as Lorenz-63.
[1] V. Lucarini and A. Gritsun, “A new mathematical framework for atmospheric blocking events,” Climate Dynamics, vol. 54, pp. 575–598, Jan 2020.
How to cite: Maiocchi, C. C., Lucarini, V., Gritsun, A., and Pavliotis, G.: Unstable Periodic Orbits Sampling in Climate Models , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18823, https://doi.org/10.5194/egusphere-egu2020-18823, 2020.
Unstable periodic orbits (UPOs) have been proved to be a relevant mathematical tool in the study of Climate Science. In a recent paper Lucarini and Gritsun [1] provided an alternative approach for understanding the properties of the atmosphere. Climate can be interpreted as a non-equilibrium steady state system and, as such, statistical mechanics can provide us with tools for its study.
UPOs decomposition plays a relevant role in the study of chaotic dynamical systems. In fact, UPOs densely populate the attractor of a chaotic system, and can therefore be thought as building blocks to construct the dynamic of the system itself. Since they are dense in the attractor, it is always possible to find a UPO arbitrarily near to a chaotic trajectory: the trajectory will remain close to the UPO, but it will never follow it indefinitely, because of its instability. Loosely speaking, a chaotic trajectory is repelled between neighbourhoods of different UPOs and can thus be approximated in terms of these periodic orbits. The characteristics of the system can then be reconstructed from the full set of periodic orbits in this fashion.
The sampling of UPOs is therefore a relevant problem for describing chaotic dynamical systems and can represent an interesting topic for the study of Climate Science. In this work we address this problem and present an algorithm to numerically extract UPOs from the attractor of a simple Climate Model such as Lorenz-63.
[1] V. Lucarini and A. Gritsun, “A new mathematical framework for atmospheric blocking events,” Climate Dynamics, vol. 54, pp. 575–598, Jan 2020.
How to cite: Maiocchi, C. C., Lucarini, V., Gritsun, A., and Pavliotis, G.: Unstable Periodic Orbits Sampling in Climate Models , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18823, https://doi.org/10.5194/egusphere-egu2020-18823, 2020.
EGU2020-11345 | Displays | NP1.1
Nonlinear Climate Dynamics: from Deterministic Behavior to Stochastic Excitability and ChaosMichel Crucifix, Dmitri Alexandrov, irina Bashkirtseva, and Lev Ryashko
Glacial-interglacial cycles are global climatic changes which have characterised the last 3 million years. The eight latest
glacial-interglacial cycles represent changes in sea level over 100 m, and their average duration was around 100 000 years. There is a
long tradition of modelling glacial-interglacial cycles with low-order dynamical systems. In one view, the cyclic phenomenon is caused by
non-linear interactions between components of the climate system: The dynamical system model which represents Earth dynamics has a limit cycle. In an another view, the variations in ice volume and ice sheet extent are caused by changes in Earth's orbit, possibly amplified by feedbacks.
This response and internal feedbacks need to be non-linear to explain the asymmetric character of glacial-interglacial cycles and their duration. A third view sees glacial-interglacial cycles as a limit cycle synchronised on the orbital forcing.
The purpose of the present contribution is to pay specific attention to the effects of stochastic forcing. Indeed, the trajectories
obtained in presence of noise are not necessarily noised-up versions of the deterministic trajectories. They may follow pathways which
have no analogue in the deterministic version of the model. Our purpose is to
demonstrate the mechanisms by which stochastic excitation may generate such large-scale oscillations and induce intermittency. To this end, we
consider a series of models previously introduced in the literature, starting by autonomous models with two variables, and then three
variables. The properties of stochastic trajectories are understood by reference to the bifurcation diagram, the vector field, and a
method called stochastic sensitivity analysis. We then introduce models accounting for the orbital forcing, and distinguish forced and
synchronised ice-age scenarios, and show again how noise may generate trajectories which have no immediate analogue in the determinstic model.
How to cite: Crucifix, M., Alexandrov, D., Bashkirtseva, I., and Ryashko, L.: Nonlinear Climate Dynamics: from Deterministic Behavior to Stochastic Excitability and Chaos, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11345, https://doi.org/10.5194/egusphere-egu2020-11345, 2020.
Glacial-interglacial cycles are global climatic changes which have characterised the last 3 million years. The eight latest
glacial-interglacial cycles represent changes in sea level over 100 m, and their average duration was around 100 000 years. There is a
long tradition of modelling glacial-interglacial cycles with low-order dynamical systems. In one view, the cyclic phenomenon is caused by
non-linear interactions between components of the climate system: The dynamical system model which represents Earth dynamics has a limit cycle. In an another view, the variations in ice volume and ice sheet extent are caused by changes in Earth's orbit, possibly amplified by feedbacks.
This response and internal feedbacks need to be non-linear to explain the asymmetric character of glacial-interglacial cycles and their duration. A third view sees glacial-interglacial cycles as a limit cycle synchronised on the orbital forcing.
The purpose of the present contribution is to pay specific attention to the effects of stochastic forcing. Indeed, the trajectories
obtained in presence of noise are not necessarily noised-up versions of the deterministic trajectories. They may follow pathways which
have no analogue in the deterministic version of the model. Our purpose is to
demonstrate the mechanisms by which stochastic excitation may generate such large-scale oscillations and induce intermittency. To this end, we
consider a series of models previously introduced in the literature, starting by autonomous models with two variables, and then three
variables. The properties of stochastic trajectories are understood by reference to the bifurcation diagram, the vector field, and a
method called stochastic sensitivity analysis. We then introduce models accounting for the orbital forcing, and distinguish forced and
synchronised ice-age scenarios, and show again how noise may generate trajectories which have no immediate analogue in the determinstic model.
How to cite: Crucifix, M., Alexandrov, D., Bashkirtseva, I., and Ryashko, L.: Nonlinear Climate Dynamics: from Deterministic Behavior to Stochastic Excitability and Chaos, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11345, https://doi.org/10.5194/egusphere-egu2020-11345, 2020.
EGU2020-20030 | Displays | NP1.1
Unique solvability of a system of ordinary differential equations modeling a warm cloud parcel and avoiding saturation adjustmentNikolas Porz
The representation of cloud processes in weather and climate models is crucial for their feedback on atmospheric flows. Since there is no general macroscopic theory of clouds, the parameterization of clouds in corresponding simulation software depends fundamentally on the underlying modeling assumptions. We present a new model of intermediate complexity (a one-and-a-half moment scheme) for warm clouds, which is derived from physical principles. Our model consists of a system of differential-algebraic equations which allows for supersaturation and thus avoids the commonly used but somewhat outdated concept of so called 'saturation adjustment'. This is made possible by a non-Lipschitz right-hand side, which allows for nontrivial solutions. In a recent effort we have proved under mild assumptions on the external forcing that this system of equations has a unique physically consistent solution, i.e., a solution with a nonzero droplet population in the supersaturated regime. For the numerical solution of this system we have developed a semi-implicit integration scheme, with efficient solvers for the implicit parts. The model conserves air and water (if one accounts for the precipitation), and it comes with eight parameters that cannot be measured since they describe simplified processes, so they need to be fitted to the data. For further studies we implemented our cloud micro physics model into ICON, the weather forecast model operated by the German forecast center DWD.
How to cite: Porz, N.: Unique solvability of a system of ordinary differential equations modeling a warm cloud parcel and avoiding saturation adjustment, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20030, https://doi.org/10.5194/egusphere-egu2020-20030, 2020.
The representation of cloud processes in weather and climate models is crucial for their feedback on atmospheric flows. Since there is no general macroscopic theory of clouds, the parameterization of clouds in corresponding simulation software depends fundamentally on the underlying modeling assumptions. We present a new model of intermediate complexity (a one-and-a-half moment scheme) for warm clouds, which is derived from physical principles. Our model consists of a system of differential-algebraic equations which allows for supersaturation and thus avoids the commonly used but somewhat outdated concept of so called 'saturation adjustment'. This is made possible by a non-Lipschitz right-hand side, which allows for nontrivial solutions. In a recent effort we have proved under mild assumptions on the external forcing that this system of equations has a unique physically consistent solution, i.e., a solution with a nonzero droplet population in the supersaturated regime. For the numerical solution of this system we have developed a semi-implicit integration scheme, with efficient solvers for the implicit parts. The model conserves air and water (if one accounts for the precipitation), and it comes with eight parameters that cannot be measured since they describe simplified processes, so they need to be fitted to the data. For further studies we implemented our cloud micro physics model into ICON, the weather forecast model operated by the German forecast center DWD.
How to cite: Porz, N.: Unique solvability of a system of ordinary differential equations modeling a warm cloud parcel and avoiding saturation adjustment, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20030, https://doi.org/10.5194/egusphere-egu2020-20030, 2020.
EGU2020-22524 | Displays | NP1.1
Reduced stochastic aggregation of convection conditioned by large scale dynamics in the atmosphereRobert Malte Polzin, Annette Müller, Peter Nevir, Henning Rust, and Peter Koltai
The presented work contains an investigation of the stochastic aggregation of convective structures on different scales in the atmosphere. A
computational framework is applied that provides highly scalable identification of reduced Bayesian models. The deterministic large scale
flow variables are reduced into latent states, whereas the stochastic small scale convective structures are affiliated to these. The analysis of
the latent states in number and maximization reduction improves the understanding for the large scale forcing of convective processes. The
convective structures are determined by vertical velocities. Different variables of the large-scale flow, such as the convective available
potential energy, available moisture, vertical windshear and the Dynamic State Index (DSI), a diabaticity indicator, are investigated. Our approach
does not require a distributional assumption but works instead with a discretised and categorised state vector.
How to cite: Polzin, R. M., Müller, A., Nevir, P., Rust, H., and Koltai, P.: Reduced stochastic aggregation of convection conditioned by large scale dynamics in the atmosphere, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22524, https://doi.org/10.5194/egusphere-egu2020-22524, 2020.
The presented work contains an investigation of the stochastic aggregation of convective structures on different scales in the atmosphere. A
computational framework is applied that provides highly scalable identification of reduced Bayesian models. The deterministic large scale
flow variables are reduced into latent states, whereas the stochastic small scale convective structures are affiliated to these. The analysis of
the latent states in number and maximization reduction improves the understanding for the large scale forcing of convective processes. The
convective structures are determined by vertical velocities. Different variables of the large-scale flow, such as the convective available
potential energy, available moisture, vertical windshear and the Dynamic State Index (DSI), a diabaticity indicator, are investigated. Our approach
does not require a distributional assumption but works instead with a discretised and categorised state vector.
How to cite: Polzin, R. M., Müller, A., Nevir, P., Rust, H., and Koltai, P.: Reduced stochastic aggregation of convection conditioned by large scale dynamics in the atmosphere, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22524, https://doi.org/10.5194/egusphere-egu2020-22524, 2020.
EGU2020-7336 | Displays | NP1.1 | Highlight
On the connection between heat waves and large deviations of temperatureJeroen Wouters, Vera Melinda Galfi, and Valerio Lucarini
We use large deviation theory to study persistent extreme events of temperature, like heat waves or cold spells. We consider the mid-latitudes of a simplified yet Earth-like general circulation model of the atmosphere and numerically estimate large deviation rate functions of near-surface temperature averages over different spatial scales. We find that, in order to represent persistent extreme events based on large deviation theory, one has to look at temporal averages of spatially averaged observables. The spatial averaging scale is crucial, and has to correspond with the scale of the event of interest. Accordingly, the computed rate functions indicate substantially different statistical properties of temperature averages over intermediate spatial scales (larger, but still of the order of the typical scale), as compared to the ones related to any other scale. Thus, heat waves (or cold spells) can be interpreted as large deviations of temperature averaged over intermediate spatial scales. Furthermore, we find universal characteristics of rate functions, based on the equivalence of temporal, spatial, and spatio-temporal rate functions if we perform a re-normalisation by the integrated auto-correlation.
How to cite: Wouters, J., Galfi, V. M., and Lucarini, V.: On the connection between heat waves and large deviations of temperature, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7336, https://doi.org/10.5194/egusphere-egu2020-7336, 2020.
We use large deviation theory to study persistent extreme events of temperature, like heat waves or cold spells. We consider the mid-latitudes of a simplified yet Earth-like general circulation model of the atmosphere and numerically estimate large deviation rate functions of near-surface temperature averages over different spatial scales. We find that, in order to represent persistent extreme events based on large deviation theory, one has to look at temporal averages of spatially averaged observables. The spatial averaging scale is crucial, and has to correspond with the scale of the event of interest. Accordingly, the computed rate functions indicate substantially different statistical properties of temperature averages over intermediate spatial scales (larger, but still of the order of the typical scale), as compared to the ones related to any other scale. Thus, heat waves (or cold spells) can be interpreted as large deviations of temperature averaged over intermediate spatial scales. Furthermore, we find universal characteristics of rate functions, based on the equivalence of temporal, spatial, and spatio-temporal rate functions if we perform a re-normalisation by the integrated auto-correlation.
How to cite: Wouters, J., Galfi, V. M., and Lucarini, V.: On the connection between heat waves and large deviations of temperature, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7336, https://doi.org/10.5194/egusphere-egu2020-7336, 2020.
EGU2020-16406 | Displays | NP1.1
Extremes for high dimensional chaotic systemsTobias Kuna, Valerio Lucarini, Davide Faranda, Jerouen Wouters, and Viviane Baladi
Extremes are related to high impact and serious hazard events and hence their study and prediction have been and continue to be highly relevant for all kind of applications in geoscience and beyond. Extreme value theory is promising to be able to predict them reliably and robustly. In the last fifteen years the classical extreme value theory for stochastic processes has been extended to dynamical systems and has been related to properties of physical measure (statistical properties of the system), return and hitting times. We will review what one can say for highly dimensional perfectly chaotic systems. We will concentrate on relations between the index of the extreme distribution and invariants of the underlying dynamical system which are stable, in the sense that they will continuously depend on changing parameters in the dynamics. Furthermore, we explore whether there exists a response theory for extremes, that is, whether the change of extremes can be quantitatilvely expressed in terms of changing parameters.
How to cite: Kuna, T., Lucarini, V., Faranda, D., Wouters, J., and Baladi, V.: Extremes for high dimensional chaotic systems, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16406, https://doi.org/10.5194/egusphere-egu2020-16406, 2020.
Extremes are related to high impact and serious hazard events and hence their study and prediction have been and continue to be highly relevant for all kind of applications in geoscience and beyond. Extreme value theory is promising to be able to predict them reliably and robustly. In the last fifteen years the classical extreme value theory for stochastic processes has been extended to dynamical systems and has been related to properties of physical measure (statistical properties of the system), return and hitting times. We will review what one can say for highly dimensional perfectly chaotic systems. We will concentrate on relations between the index of the extreme distribution and invariants of the underlying dynamical system which are stable, in the sense that they will continuously depend on changing parameters in the dynamics. Furthermore, we explore whether there exists a response theory for extremes, that is, whether the change of extremes can be quantitatilvely expressed in terms of changing parameters.
How to cite: Kuna, T., Lucarini, V., Faranda, D., Wouters, J., and Baladi, V.: Extremes for high dimensional chaotic systems, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16406, https://doi.org/10.5194/egusphere-egu2020-16406, 2020.
EGU2020-20739 | Displays | NP1.1
Consistent Modelling of Non-Equilibrium Thermodynamic Processes in the AtmospherePaul Bowen
Approximations in the moist thermodynamics of atmospheric/weather models are often inconsistent. Different parts of numerical models may handle the thermodynamics in different ways, or the approximations may disagree with the laws of thermodynamics. In order to address these problems, we may derive all relevant thermodynamic quantities from a defined thermodynamic potential; approximations are then instead made to the potential itself — this guarantees self-consistency. This concept is viable for vapor and liquid water mixtures in a moist atmospheric system using the Gibbs function but on extension to include the ice phase an ambiguity presents itself at the triple-point. In order to resolve this the energy function must be utilised instead; constrained maximisation methods can then be used on the entropy in order to solve the system equilibrium state. Once this is done however, a further extension is necessary for atmospheric systems. In the Earth’s atmosphere many important non-equilibrium processes take place; for example, freezing of super-cooled water, evaporation, and precipitation. To fully capture these processes the equilibrium method must be reformulated to involve finite rates of approach towards equilibrium. This may be done using various principles of non-equilibrium thermodynamics, principally Onsager reciprocal relations. A numerical scheme may then be implemented which models competing finite processes in a moist thermodynamic system.
How to cite: Bowen, P.: Consistent Modelling of Non-Equilibrium Thermodynamic Processes in the Atmosphere, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20739, https://doi.org/10.5194/egusphere-egu2020-20739, 2020.
Approximations in the moist thermodynamics of atmospheric/weather models are often inconsistent. Different parts of numerical models may handle the thermodynamics in different ways, or the approximations may disagree with the laws of thermodynamics. In order to address these problems, we may derive all relevant thermodynamic quantities from a defined thermodynamic potential; approximations are then instead made to the potential itself — this guarantees self-consistency. This concept is viable for vapor and liquid water mixtures in a moist atmospheric system using the Gibbs function but on extension to include the ice phase an ambiguity presents itself at the triple-point. In order to resolve this the energy function must be utilised instead; constrained maximisation methods can then be used on the entropy in order to solve the system equilibrium state. Once this is done however, a further extension is necessary for atmospheric systems. In the Earth’s atmosphere many important non-equilibrium processes take place; for example, freezing of super-cooled water, evaporation, and precipitation. To fully capture these processes the equilibrium method must be reformulated to involve finite rates of approach towards equilibrium. This may be done using various principles of non-equilibrium thermodynamics, principally Onsager reciprocal relations. A numerical scheme may then be implemented which models competing finite processes in a moist thermodynamic system.
How to cite: Bowen, P.: Consistent Modelling of Non-Equilibrium Thermodynamic Processes in the Atmosphere, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20739, https://doi.org/10.5194/egusphere-egu2020-20739, 2020.
EGU2020-9572 | Displays | NP1.1
Comparing water, energy and entropy budgets of aquaplanet climate attractorsCharline Ragon, Valerio Lembo, Valerio Lucarini, Jérôme Kasparian, and Maura Brunetti
The climate system can be seen as a thermal engine that generates entropy by irreversible processes and achieves a steady state by redistributing the input solar energy among its different components (ocean, atmosphere, etc) and by balancing the energy, water mass and entropy budgets over all the spatial scales. Biases in modern climate models are generally related to the fact that their statistical properties are not well represented, giving rise to imperfect closures of the energy cycle. Thus, a proper measurement of the efficiency of the thermal engine in each climate model is needed. Moreover, possible steady states (attractors) that can be approached at climate tipping-points are characterised by different feedbacks becoming dominant in the thermal engine.
We apply the Thermodynamic Diagnostic Tool (TheDiaTo) [1] to the attractors recently obtained using the MIT general circulation model (MITgcm) in a coupled aquaplanet [2], a planet where the ocean covers the entire globe. Such coupled aquaplanets, where nonlinear interactions between atmosphere, ocean and sea ice are fully taken into account, provide a relevant framework to understand the role of the main feedbacks at play in the climate system. Five attractors have been found, ranging from snowball (where ice covers the entire planet) to hot state conditions (where ice completely disappears) [2].
Using TheDiaTo, we analyse the five climate attractors by estimating: a) the energy budgets and meridional energy transports; b) the water mass and latent energy budgets and respective meridional transports; c) the Lorenz Energy Cycle; d) the material entropy production. We consider different coupled atmosphere-ocean-sea ice configurations and cloud parameterizations of MITgcm where the energy balance at the top of the atmosphere is progressively better closed in order to understand the occurrence of possible biases in the statistical properties of each attractor.
Our contribution will help clarify the thermodynamic differences in climate attractors and their stability to external perturbations that could shift the climate from a steady state to the other.
[1] Lembo V., Lunkeit F., Lucarini V., TheDiaTo (v1.0) – a new diagnostic tool for water, energy amd entropy budgets in climate models, Geosci. Model Dev. 12, 3805-3834 (2019)
[2] Brunetti M., Kasparian J., Vérard C., Co-existing climate attractors in a coupled aquaplanet, Climate Dynamics 53, 6293-6308 (2019)
How to cite: Ragon, C., Lembo, V., Lucarini, V., Kasparian, J., and Brunetti, M.: Comparing water, energy and entropy budgets of aquaplanet climate attractors, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9572, https://doi.org/10.5194/egusphere-egu2020-9572, 2020.
The climate system can be seen as a thermal engine that generates entropy by irreversible processes and achieves a steady state by redistributing the input solar energy among its different components (ocean, atmosphere, etc) and by balancing the energy, water mass and entropy budgets over all the spatial scales. Biases in modern climate models are generally related to the fact that their statistical properties are not well represented, giving rise to imperfect closures of the energy cycle. Thus, a proper measurement of the efficiency of the thermal engine in each climate model is needed. Moreover, possible steady states (attractors) that can be approached at climate tipping-points are characterised by different feedbacks becoming dominant in the thermal engine.
We apply the Thermodynamic Diagnostic Tool (TheDiaTo) [1] to the attractors recently obtained using the MIT general circulation model (MITgcm) in a coupled aquaplanet [2], a planet where the ocean covers the entire globe. Such coupled aquaplanets, where nonlinear interactions between atmosphere, ocean and sea ice are fully taken into account, provide a relevant framework to understand the role of the main feedbacks at play in the climate system. Five attractors have been found, ranging from snowball (where ice covers the entire planet) to hot state conditions (where ice completely disappears) [2].
Using TheDiaTo, we analyse the five climate attractors by estimating: a) the energy budgets and meridional energy transports; b) the water mass and latent energy budgets and respective meridional transports; c) the Lorenz Energy Cycle; d) the material entropy production. We consider different coupled atmosphere-ocean-sea ice configurations and cloud parameterizations of MITgcm where the energy balance at the top of the atmosphere is progressively better closed in order to understand the occurrence of possible biases in the statistical properties of each attractor.
Our contribution will help clarify the thermodynamic differences in climate attractors and their stability to external perturbations that could shift the climate from a steady state to the other.
[1] Lembo V., Lunkeit F., Lucarini V., TheDiaTo (v1.0) – a new diagnostic tool for water, energy amd entropy budgets in climate models, Geosci. Model Dev. 12, 3805-3834 (2019)
[2] Brunetti M., Kasparian J., Vérard C., Co-existing climate attractors in a coupled aquaplanet, Climate Dynamics 53, 6293-6308 (2019)
How to cite: Ragon, C., Lembo, V., Lucarini, V., Kasparian, J., and Brunetti, M.: Comparing water, energy and entropy budgets of aquaplanet climate attractors, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9572, https://doi.org/10.5194/egusphere-egu2020-9572, 2020.
EGU2020-8084 | Displays | NP1.1
A blueprint for thermodynamically consistent box models and a test bed for thermodynamic optimality principlesStan Schymanski and Martijn Westhoff
Thermodynamic optimality principles, such as maximum entropy production or maximum power extraction, hold a great promise to help explain self-organisation of various compartments of planet Earth, including the climate system, catchments and ecosystems. There is a growing number of examples for more or less successful use of these principles in earth system science, but a common systematic approach to the formulation of the relevant system boundaries, state variables and exchange fluxes has not yet emerged. Here we present a blueprint for the thermodynamically consistent formulation of box models and rigorous testing of optimality principles, in particular the maximum entropy production (MEP) and the maximum power (MP) principle. We investigate under what conditions these principles can be used to predict energy transfer coefficients across internal system boundaries and demonstrate that, contrary to common perception, these principles do not lead to similar predictions if energy and entropy balances are explicitly considered for the whole system and the defined sub-systems. We further highlight various pitfalls that may result in thermodynamically inconsistent models and potentially wrong conclusions about the implications of thermodynamic optimality principles.
The analysis is performed in an open source mathematical framework, using the notebook interface Jupyter, the programming language Python, Sympy and a newly developed package for Python, "Environmental Science using Symbolic Math" (ESSM, https://github.com/environmentalscience/essm). This ensures easy verifiability of the results and enables users to re-use and modify variable definitions, equations and mathematical solutions to suit their own thermodynamic problems.
How to cite: Schymanski, S. and Westhoff, M.: A blueprint for thermodynamically consistent box models and a test bed for thermodynamic optimality principles, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8084, https://doi.org/10.5194/egusphere-egu2020-8084, 2020.
Thermodynamic optimality principles, such as maximum entropy production or maximum power extraction, hold a great promise to help explain self-organisation of various compartments of planet Earth, including the climate system, catchments and ecosystems. There is a growing number of examples for more or less successful use of these principles in earth system science, but a common systematic approach to the formulation of the relevant system boundaries, state variables and exchange fluxes has not yet emerged. Here we present a blueprint for the thermodynamically consistent formulation of box models and rigorous testing of optimality principles, in particular the maximum entropy production (MEP) and the maximum power (MP) principle. We investigate under what conditions these principles can be used to predict energy transfer coefficients across internal system boundaries and demonstrate that, contrary to common perception, these principles do not lead to similar predictions if energy and entropy balances are explicitly considered for the whole system and the defined sub-systems. We further highlight various pitfalls that may result in thermodynamically inconsistent models and potentially wrong conclusions about the implications of thermodynamic optimality principles.
The analysis is performed in an open source mathematical framework, using the notebook interface Jupyter, the programming language Python, Sympy and a newly developed package for Python, "Environmental Science using Symbolic Math" (ESSM, https://github.com/environmentalscience/essm). This ensures easy verifiability of the results and enables users to re-use and modify variable definitions, equations and mathematical solutions to suit their own thermodynamic problems.
How to cite: Schymanski, S. and Westhoff, M.: A blueprint for thermodynamically consistent box models and a test bed for thermodynamic optimality principles, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8084, https://doi.org/10.5194/egusphere-egu2020-8084, 2020.
EGU2020-7100 | Displays | NP1.1
Poroelastic aspects in geothermicsBianca Kretz, Willi Freeden, and Volker Michel
The aspect of poroelasticity is anywhere interesting where a solid material and a fluid come into play and have an effect on each other. This is the case in many applications and we want to focus on geothermics. It is useful to consider this aspect since the replacement of the water in the reservoir below the Earth's surface has an effect on the sorrounding material and vice versa. The underlying physical processes can be described by partial differential equations, called the quasistatic equations of poroelasticity (QEP). From a mathematical point of view, we have a set of three (for two space and one time dimension) partial differential equations with the unknowns u (displacement) and p (pore pressure) depending on the space and the time.
Our aim is to do a decomposition of the data given for u and p in order that we can see underlying structures in the different decomposition scales that cannot be seen in the whole data.
For this process, we need the fundamental solution tensor of the QEP (cf. [1],[5]).
That means we assume that we have given data for u and p (they can be obtained for example by a method of fundamental solutions, cf. [1]) and want to investigate a post-processing method to these data. Here we follow the basic approaches for the Laplace-, Helmholtz- and d'Alembert equation (cf. [2],[4],[6]) and the Cauchy-Navier equation as a tensor-valued ansatz (cf. [3]). That means we want to modify our elements of the fundamental solution tensor in such a way that we smooth the singularity concerning a parameter set τ=(τx,τt).
With the help of these modified functions, we construct scaling functions which have to fulfil the properties of an approximate identity.
They are convolved with the given data to extract more details of u and p.
References
[1] M. Augustin: A method of fundamental solutions in poroelasticity to model the stress field in geothermal reservoirs, PhD Thesis, University of Kaiserslautern, 2015, Birkhäuser, New York, 2015.
[2] C. Blick, Multiscale potential methods in geothermal research: decorrelation reflected post-processing and locally based inversion, PhD Thesis, Geomathematics Group, Department of Mathematics, University of Kaiserslautern, 2015.
[3] C. Blick, S. Eberle, Multiscale density decorrelation by Cauchy-Navier wavelets, Int. J. Geomath. 10, 2019, article 24.
[4] C. Blick, W. Freeden, H. Nutz: Feature extraction of geological signatures by multiscale gravimetry. Int. J. Geomath. 8: 57-83, 2017.
[5] A.H.D. Cheng and E. Detournay: On singular integral equations and fundamental solutions of poroelasticity. Int. J. Solid. Struct. 35, 4521-4555, 1998.
[6] W. Freeden, C. Blick: Signal decorrelation by means of multiscale methods, World of Mining, 65(5):304-317, 2013.
How to cite: Kretz, B., Freeden, W., and Michel, V.: Poroelastic aspects in geothermics, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7100, https://doi.org/10.5194/egusphere-egu2020-7100, 2020.
The aspect of poroelasticity is anywhere interesting where a solid material and a fluid come into play and have an effect on each other. This is the case in many applications and we want to focus on geothermics. It is useful to consider this aspect since the replacement of the water in the reservoir below the Earth's surface has an effect on the sorrounding material and vice versa. The underlying physical processes can be described by partial differential equations, called the quasistatic equations of poroelasticity (QEP). From a mathematical point of view, we have a set of three (for two space and one time dimension) partial differential equations with the unknowns u (displacement) and p (pore pressure) depending on the space and the time.
Our aim is to do a decomposition of the data given for u and p in order that we can see underlying structures in the different decomposition scales that cannot be seen in the whole data.
For this process, we need the fundamental solution tensor of the QEP (cf. [1],[5]).
That means we assume that we have given data for u and p (they can be obtained for example by a method of fundamental solutions, cf. [1]) and want to investigate a post-processing method to these data. Here we follow the basic approaches for the Laplace-, Helmholtz- and d'Alembert equation (cf. [2],[4],[6]) and the Cauchy-Navier equation as a tensor-valued ansatz (cf. [3]). That means we want to modify our elements of the fundamental solution tensor in such a way that we smooth the singularity concerning a parameter set τ=(τx,τt).
With the help of these modified functions, we construct scaling functions which have to fulfil the properties of an approximate identity.
They are convolved with the given data to extract more details of u and p.
References
[1] M. Augustin: A method of fundamental solutions in poroelasticity to model the stress field in geothermal reservoirs, PhD Thesis, University of Kaiserslautern, 2015, Birkhäuser, New York, 2015.
[2] C. Blick, Multiscale potential methods in geothermal research: decorrelation reflected post-processing and locally based inversion, PhD Thesis, Geomathematics Group, Department of Mathematics, University of Kaiserslautern, 2015.
[3] C. Blick, S. Eberle, Multiscale density decorrelation by Cauchy-Navier wavelets, Int. J. Geomath. 10, 2019, article 24.
[4] C. Blick, W. Freeden, H. Nutz: Feature extraction of geological signatures by multiscale gravimetry. Int. J. Geomath. 8: 57-83, 2017.
[5] A.H.D. Cheng and E. Detournay: On singular integral equations and fundamental solutions of poroelasticity. Int. J. Solid. Struct. 35, 4521-4555, 1998.
[6] W. Freeden, C. Blick: Signal decorrelation by means of multiscale methods, World of Mining, 65(5):304-317, 2013.
How to cite: Kretz, B., Freeden, W., and Michel, V.: Poroelastic aspects in geothermics, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7100, https://doi.org/10.5194/egusphere-egu2020-7100, 2020.
EGU2020-7031 | Displays | NP1.1
A model for the longitudinal patterns shaped by water on erodible rocksMatteo Bernard Bertagni and Carlo Camporeale
The interactions between water and rocks create an extensive variety of marvelous patterns, which span on several classes of time and space scales. In this work, we provide a mathematical model for the formation of longitudinal erosive patterns commonly found in karst and alpine environments. The model couples the hydrodynamics of a laminar flow of water (Orr-Somerfield equation) to the concentration field of the eroded-rock chemistry. Results show that an instability of the plane rock wetted by the water film leads to a longitudinal channelization responsible for the pattern formation. The spatial scales predicted by the model span over different orders of magnitude depending on the flow intensity and this may explain why similar patterns of different sizes are observed in nature (millimetric microrills, centimetric rillenkarren, decametric solution runnels).
How to cite: Bertagni, M. B. and Camporeale, C.: A model for the longitudinal patterns shaped by water on erodible rocks, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7031, https://doi.org/10.5194/egusphere-egu2020-7031, 2020.
The interactions between water and rocks create an extensive variety of marvelous patterns, which span on several classes of time and space scales. In this work, we provide a mathematical model for the formation of longitudinal erosive patterns commonly found in karst and alpine environments. The model couples the hydrodynamics of a laminar flow of water (Orr-Somerfield equation) to the concentration field of the eroded-rock chemistry. Results show that an instability of the plane rock wetted by the water film leads to a longitudinal channelization responsible for the pattern formation. The spatial scales predicted by the model span over different orders of magnitude depending on the flow intensity and this may explain why similar patterns of different sizes are observed in nature (millimetric microrills, centimetric rillenkarren, decametric solution runnels).
How to cite: Bertagni, M. B. and Camporeale, C.: A model for the longitudinal patterns shaped by water on erodible rocks, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7031, https://doi.org/10.5194/egusphere-egu2020-7031, 2020.
EGU2020-11841 | Displays | NP1.1
Troposphere-Stratosphere Coupling and the Role of Critical Layer NonlinearityImogen Dell
There exists a coupling mechanism between the troposphere and the stratosphere, which plays a fundamental role in weather and climate. The coupling is highly complex and rests upon radiative and chemical feedbacks, as well as dynamical coupling by Rossby waves. The troposphere acts as a source of Rossby waves which propagate upwards in to the stratosphere, affecting the zonal mean flow. Rossby waves are also likely to play a significant role in downward communication of information via reflection from the stratosphere in to the troposphere. A mechanism for this reflection could be from a so-called critical layer. A shear flow exhibits a critical layer where the phase speed equals the flow velocity, where viscous and nonlinear effects become important. A wave incident upon a critical layer may be absorbed, reflected or overreflected, whereby the amplitude of the reflected wave is larger than that of the incident wave. In the case of troposphere-stratosphere coupling, the concept of critical layer overreflection is key to understanding atmospheric instability.
Motivated by this, a mathematical framework for understanding the coupling will be presented together with an investigation in to the role of nonlinearity versus viscosity inside the critical layer.
How to cite: Dell, I.: Troposphere-Stratosphere Coupling and the Role of Critical Layer Nonlinearity, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11841, https://doi.org/10.5194/egusphere-egu2020-11841, 2020.
There exists a coupling mechanism between the troposphere and the stratosphere, which plays a fundamental role in weather and climate. The coupling is highly complex and rests upon radiative and chemical feedbacks, as well as dynamical coupling by Rossby waves. The troposphere acts as a source of Rossby waves which propagate upwards in to the stratosphere, affecting the zonal mean flow. Rossby waves are also likely to play a significant role in downward communication of information via reflection from the stratosphere in to the troposphere. A mechanism for this reflection could be from a so-called critical layer. A shear flow exhibits a critical layer where the phase speed equals the flow velocity, where viscous and nonlinear effects become important. A wave incident upon a critical layer may be absorbed, reflected or overreflected, whereby the amplitude of the reflected wave is larger than that of the incident wave. In the case of troposphere-stratosphere coupling, the concept of critical layer overreflection is key to understanding atmospheric instability.
Motivated by this, a mathematical framework for understanding the coupling will be presented together with an investigation in to the role of nonlinearity versus viscosity inside the critical layer.
How to cite: Dell, I.: Troposphere-Stratosphere Coupling and the Role of Critical Layer Nonlinearity, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11841, https://doi.org/10.5194/egusphere-egu2020-11841, 2020.
EGU2020-11603 | Displays | NP1.1
Variational Model Reduction for Rotating Geophysical Flows with Full Coriolis ForceGözde Özden and Marcel Oliver
Consider the motion of a rotating fluid governed by the Boussinesq equations with full Coriolis parameter. This is contrary to the so-called ''traditional approximation'' in which the horizontal part of the Coriolis parameter is zero. The model is obtained using variational principle which depends on Lagrangian dynamics. The full Coriolis force is used since the horizontal component of the angular velocity has a crucial role in that it introduces a dependence on the direction of the geostrophic flow in the horizontal geostrophical plane. We aim that singularity near the equatorial region can be solved with this assumption. This gives a consistent balance relation for any latitude on the Earth. We follow the similar strategy to that Oliver and Vasylkevych (2016) for the system to derive the Euler-Poincaré equations. Firstly, the system is transformed into desired scale giving the differences with the other scales. We derive the balance model Lagrangian as called L1 model, R. Salmon, using Hamiltonian principles. Near identity transformation is applied to simplify the Hamiltonian. Whole calculations are done considering the smallness assumption of the Rossby number. Long term, we aim that results help to understand the global energy cycle with the goal of validity and improving climate models.
How to cite: Özden, G. and Oliver, M.: Variational Model Reduction for Rotating Geophysical Flows with Full Coriolis Force, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11603, https://doi.org/10.5194/egusphere-egu2020-11603, 2020.
Consider the motion of a rotating fluid governed by the Boussinesq equations with full Coriolis parameter. This is contrary to the so-called ''traditional approximation'' in which the horizontal part of the Coriolis parameter is zero. The model is obtained using variational principle which depends on Lagrangian dynamics. The full Coriolis force is used since the horizontal component of the angular velocity has a crucial role in that it introduces a dependence on the direction of the geostrophic flow in the horizontal geostrophical plane. We aim that singularity near the equatorial region can be solved with this assumption. This gives a consistent balance relation for any latitude on the Earth. We follow the similar strategy to that Oliver and Vasylkevych (2016) for the system to derive the Euler-Poincaré equations. Firstly, the system is transformed into desired scale giving the differences with the other scales. We derive the balance model Lagrangian as called L1 model, R. Salmon, using Hamiltonian principles. Near identity transformation is applied to simplify the Hamiltonian. Whole calculations are done considering the smallness assumption of the Rossby number. Long term, we aim that results help to understand the global energy cycle with the goal of validity and improving climate models.
How to cite: Özden, G. and Oliver, M.: Variational Model Reduction for Rotating Geophysical Flows with Full Coriolis Force, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11603, https://doi.org/10.5194/egusphere-egu2020-11603, 2020.
EGU2020-9302 | Displays | NP1.1
The strange instability of the equatorial Kelvin waveStephen Griffiths
The Kelvin wave is perhaps the most important of the equatorially trapped waves in the terrestrial atmosphere and ocean, and plays a role in various phenomena such as tropical convection and El Nino. Theoretically, it can be understood from the linear dynamics of a stratified fluid on an equatorial β-plane, which, with simple assumptions about the disturbance structure, leads to wavelike solutions propagating along the equator, with exponential decay in latitude. However, when the simplest possible background flow is added (with uniform latitudinal shear), the Kelvin wave (but not the other equatorial waves) becomes unstable. This happens in an extremely unusual way: there is instability for arbitrarily small nondimensional shear λ, and the growth rate is proportional to exp(-1/λ^2) as λ → 0. This in contrast to most hydrodynamic instabilities, in which the growth rate typically scales as a positive power of λ-λc as the control parameter λ passes through a critical value λc.
This Kelvin wave instability has been established numerically by Natarov and Boyd, who also speculated as to the underlying mathematical cause by analysing a quantum harmonic oscillator perturbed by a potential with a remote pole. Here we show how the growth rate and full spatial structure of the Kelvin wave instability may be derived using matched asymptotic expansions applied to the (linear) equations of motion. This involves an adventure with confluent hypergeometric functions in the exponentially-decaying tails of the Kelvin waves, and a trick to reveal the exponentially small growth rate from a formulation that only uses regular perturbation expansions. Numerical verification of the analysis is also interesting and challenging, since special high-precision solutions of the governing ordinary differential equations are required even when the nondimensional shear is not that small (circa 0.5).
How to cite: Griffiths, S.: The strange instability of the equatorial Kelvin wave , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9302, https://doi.org/10.5194/egusphere-egu2020-9302, 2020.
The Kelvin wave is perhaps the most important of the equatorially trapped waves in the terrestrial atmosphere and ocean, and plays a role in various phenomena such as tropical convection and El Nino. Theoretically, it can be understood from the linear dynamics of a stratified fluid on an equatorial β-plane, which, with simple assumptions about the disturbance structure, leads to wavelike solutions propagating along the equator, with exponential decay in latitude. However, when the simplest possible background flow is added (with uniform latitudinal shear), the Kelvin wave (but not the other equatorial waves) becomes unstable. This happens in an extremely unusual way: there is instability for arbitrarily small nondimensional shear λ, and the growth rate is proportional to exp(-1/λ^2) as λ → 0. This in contrast to most hydrodynamic instabilities, in which the growth rate typically scales as a positive power of λ-λc as the control parameter λ passes through a critical value λc.
This Kelvin wave instability has been established numerically by Natarov and Boyd, who also speculated as to the underlying mathematical cause by analysing a quantum harmonic oscillator perturbed by a potential with a remote pole. Here we show how the growth rate and full spatial structure of the Kelvin wave instability may be derived using matched asymptotic expansions applied to the (linear) equations of motion. This involves an adventure with confluent hypergeometric functions in the exponentially-decaying tails of the Kelvin waves, and a trick to reveal the exponentially small growth rate from a formulation that only uses regular perturbation expansions. Numerical verification of the analysis is also interesting and challenging, since special high-precision solutions of the governing ordinary differential equations are required even when the nondimensional shear is not that small (circa 0.5).
How to cite: Griffiths, S.: The strange instability of the equatorial Kelvin wave , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9302, https://doi.org/10.5194/egusphere-egu2020-9302, 2020.
EGU2020-13284 | Displays | NP1.1
Wave-mean flow interaction, forced triads, and recharge-discharge Processes as noncanonical Hamiltonian SystemsRichard Blender and Joscha Fregin
We consider recharge-discharge processes in a forced wave-mean flow interaction model and in a forced Rossby wave triad. Such processes are common in atmospheric dynamics and are typically modelled by nonlinear oscillators, for example for mid-latitude storms by Ambaum and Novak (2013) and for convective cycles by Yano and Plant (2012). A similar behaviour can be seen in the simulation of a forced wave number triad by Lynch (2009). Here we construct noncanonical Hamiltonian and Nambu representations in three-dimensional phase space for available and prescribed conservation laws during the recharge and discharge regimes. Divergence in phase space is modelled by a pre-factor. The approach allows the design of conservative and forced dynamical systems.
How to cite: Blender, R. and Fregin, J.: Wave-mean flow interaction, forced triads, and recharge-discharge Processes as noncanonical Hamiltonian Systems, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13284, https://doi.org/10.5194/egusphere-egu2020-13284, 2020.
We consider recharge-discharge processes in a forced wave-mean flow interaction model and in a forced Rossby wave triad. Such processes are common in atmospheric dynamics and are typically modelled by nonlinear oscillators, for example for mid-latitude storms by Ambaum and Novak (2013) and for convective cycles by Yano and Plant (2012). A similar behaviour can be seen in the simulation of a forced wave number triad by Lynch (2009). Here we construct noncanonical Hamiltonian and Nambu representations in three-dimensional phase space for available and prescribed conservation laws during the recharge and discharge regimes. Divergence in phase space is modelled by a pre-factor. The approach allows the design of conservative and forced dynamical systems.
How to cite: Blender, R. and Fregin, J.: Wave-mean flow interaction, forced triads, and recharge-discharge Processes as noncanonical Hamiltonian Systems, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13284, https://doi.org/10.5194/egusphere-egu2020-13284, 2020.
EGU2020-8740 | Displays | NP1.1
Inverting fluvial network topology to understand landscape dynamicsStuart Grieve, Simon Mudd, Fiona Clubb, Michael Singer, Katerina Michaelides, and Shiuan-An Chen
The topology of fluvial networks has long been studied, with Horton's laws describing relationships between stream order, stream density, and stream length often cited as fundamental governing principles of drainage basin development. Building upon these principles, small scale studies have identified patterns of self-similarity in drainage networks in the continental USA, suggesting that to some extent, river networks self-organise in a scale invariant manner. More stringent measures of self-similarity have also been developed, which quantify the fractal nature of side branching structures in fluvial networks. Using such metrics, studies have identified similarities between leaf vein structures and fluvial networks, and have identified a potential climatic signature in North American river topology.
The appeal of such techniques over traditional methods of channel analysis using topographic data is that in self-similar networks, the precise location of channel heads is unimportant, allowing analysis to be performed at unprecedented scales, and in locations where data quality is limited. Here, we attempt to reconcile these two suites of techniques to understand the potential and limitations of network topology as an indicator of broader landscape dynamics. We achieve this through the analysis of fluvial networks extracted at a global scale from the Shuttle Radar Topography Mission dataset alongside other global earth observation data.
How to cite: Grieve, S., Mudd, S., Clubb, F., Singer, M., Michaelides, K., and Chen, S.-A.: Inverting fluvial network topology to understand landscape dynamics, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8740, https://doi.org/10.5194/egusphere-egu2020-8740, 2020.
The topology of fluvial networks has long been studied, with Horton's laws describing relationships between stream order, stream density, and stream length often cited as fundamental governing principles of drainage basin development. Building upon these principles, small scale studies have identified patterns of self-similarity in drainage networks in the continental USA, suggesting that to some extent, river networks self-organise in a scale invariant manner. More stringent measures of self-similarity have also been developed, which quantify the fractal nature of side branching structures in fluvial networks. Using such metrics, studies have identified similarities between leaf vein structures and fluvial networks, and have identified a potential climatic signature in North American river topology.
The appeal of such techniques over traditional methods of channel analysis using topographic data is that in self-similar networks, the precise location of channel heads is unimportant, allowing analysis to be performed at unprecedented scales, and in locations where data quality is limited. Here, we attempt to reconcile these two suites of techniques to understand the potential and limitations of network topology as an indicator of broader landscape dynamics. We achieve this through the analysis of fluvial networks extracted at a global scale from the Shuttle Radar Topography Mission dataset alongside other global earth observation data.
How to cite: Grieve, S., Mudd, S., Clubb, F., Singer, M., Michaelides, K., and Chen, S.-A.: Inverting fluvial network topology to understand landscape dynamics, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8740, https://doi.org/10.5194/egusphere-egu2020-8740, 2020.
EGU2020-4259 | Displays | NP1.1
The Origin of Aeolian Dunes – PIV measurements of flow structure over early stage protodunes in a refractive-index-matching flumeNathaniel Bristow, James Best, Kenneth Christensen, Matthew Baddock, Giles Wiggs, Pauline Delorme, and Joanna Nield
Understanding the initiation of aeolian dunes poses significant challenges due to the strong couplings between turbulent fluid flow, sediment transport, and bedform morphology. While much is known concerning the dynamics of more mature bedforms, open questions remain as to how protodunes are formed, as well as the mechanisms by which they continue to evolve. The structure of the turbulent flow field drives the mobilization or deposition of sediment, thus controlling the initial formation of sand patches, yet is also strongly influenced itself by local conditions such as surface roughness and moisture. Furthermore, an additional feedback on the flow and transport is exerted by the sand patches themselves once they begin to form.
As protodunes begin to develop from this initial deposition, their morphologies possess unique characteristics involving a reverse asymmetry of the stoss and lee sides, wherein the crest begins upstream, close to the toe, and gradually shifts downstream toward the "regular" asymmetric profile exhibited by more mature dunes. However, these early stages of development also involve very gentle slopes and low profiles which make field measurements of the associated flow particularly challenging.
The current research effort involves a combination of field measurements, documenting the initiation and morphological development of sand patches and protodunes, in concert with detailed measurements of the flow-form interactions in a laboratory flume. The work presented herein focuses primarily on experiments conducted in a unique flow facility wherein high-resolution measurements of the turbulent flow field associated with the early stages of protodune development are obtained utilizing particle-image velocimetry (PIV) in a refractive-index-matched (RIM) environment. The RIM technique facilitates flow measurements extremely close to model surfaces as well as unimpeded optical access which are critical to understanding the flow-form coupling. A series idealized, fixed-bed models are fabricated to mimic the key morphological characteristics of early protodune development observed in the field, and the flow measurements associated with them are analyzed to reveal the mechanisms controlling the bedform dynamics.
How to cite: Bristow, N., Best, J., Christensen, K., Baddock, M., Wiggs, G., Delorme, P., and Nield, J.: The Origin of Aeolian Dunes – PIV measurements of flow structure over early stage protodunes in a refractive-index-matching flume, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4259, https://doi.org/10.5194/egusphere-egu2020-4259, 2020.
Understanding the initiation of aeolian dunes poses significant challenges due to the strong couplings between turbulent fluid flow, sediment transport, and bedform morphology. While much is known concerning the dynamics of more mature bedforms, open questions remain as to how protodunes are formed, as well as the mechanisms by which they continue to evolve. The structure of the turbulent flow field drives the mobilization or deposition of sediment, thus controlling the initial formation of sand patches, yet is also strongly influenced itself by local conditions such as surface roughness and moisture. Furthermore, an additional feedback on the flow and transport is exerted by the sand patches themselves once they begin to form.
As protodunes begin to develop from this initial deposition, their morphologies possess unique characteristics involving a reverse asymmetry of the stoss and lee sides, wherein the crest begins upstream, close to the toe, and gradually shifts downstream toward the "regular" asymmetric profile exhibited by more mature dunes. However, these early stages of development also involve very gentle slopes and low profiles which make field measurements of the associated flow particularly challenging.
The current research effort involves a combination of field measurements, documenting the initiation and morphological development of sand patches and protodunes, in concert with detailed measurements of the flow-form interactions in a laboratory flume. The work presented herein focuses primarily on experiments conducted in a unique flow facility wherein high-resolution measurements of the turbulent flow field associated with the early stages of protodune development are obtained utilizing particle-image velocimetry (PIV) in a refractive-index-matched (RIM) environment. The RIM technique facilitates flow measurements extremely close to model surfaces as well as unimpeded optical access which are critical to understanding the flow-form coupling. A series idealized, fixed-bed models are fabricated to mimic the key morphological characteristics of early protodune development observed in the field, and the flow measurements associated with them are analyzed to reveal the mechanisms controlling the bedform dynamics.
How to cite: Bristow, N., Best, J., Christensen, K., Baddock, M., Wiggs, G., Delorme, P., and Nield, J.: The Origin of Aeolian Dunes – PIV measurements of flow structure over early stage protodunes in a refractive-index-matching flume, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4259, https://doi.org/10.5194/egusphere-egu2020-4259, 2020.
EGU2020-10258 | Displays | NP1.1
Data-driven reduced order modelling of tide-induced sand bars in confined channelsTjebbe Hepkema, Huib de Swart, and Henk Schuttelaars
How to cite: Hepkema, T., de Swart, H., and Schuttelaars, H.: Data-driven reduced order modelling of tide-induced sand bars in confined channels, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10258, https://doi.org/10.5194/egusphere-egu2020-10258, 2020.
How to cite: Hepkema, T., de Swart, H., and Schuttelaars, H.: Data-driven reduced order modelling of tide-induced sand bars in confined channels, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10258, https://doi.org/10.5194/egusphere-egu2020-10258, 2020.
EGU2020-1958 | Displays | NP1.1
Using a first-order autonomous dynamical system to evaluate residence time of the Greenland freshwater anomaly in the Subpolar GyreDmitry Dukhovskoy
Increasing Greenland discharge has contributed more than 5000 km3 of surplus fresh water to the Subpolar North Atlantic since the early 1990s. The volume of this freshwater anomaly is projected to cause freshening in the North Atlantic leading to changes in the intensity of deep convection and thermohaline circulation in the subpolar North Atlantic. This is roughly half of the freshwater volume of the Great Salinity Anomaly of the 1970s that caused notable freshening in the Subpolar North Atlantic. In analogy with the Great Salinity Anomaly, it has been proposed that, over the years, this additional Greenland freshwater discharge might have a great impact on convection driving thermohaline circulation in the North Atlantic with consequent impact on climate. Previous numerical studies demonstrate that roughly half of this Greenland freshwater anomaly accumulates in the Subpolar Gyre. However, time scales over which the Greenland freshwater anomaly can accumulate in the subpolar basins is not known. This study estimates the residence time of the Greenland freshwater anomaly in the Subpolar Gyre by approximating the process of the anomaly accumulation in the study domain with a first order autonomous dynamical system forced by the Greenland freshwater anomaly discharge. General solutions are obtained for two types of the forcing function. First, the Greenland freshwater anomaly discharge is a constant function imposed as a step function. Second, the surplus discharge is a linearly increasing function. The solutions are deduced by utilizing results from the numerical experiments that tracked spreading of the Greenland fresh water with a passive tracer. The residence time of the freshwater anomaly is estimated to be about 10–15 years. The main differences in the solutions is that under the linearly increasing discharge rate, the volume of the accumulated Greenland freshwater anomaly in the Subpolar Gyre does not reach a steady state. By contrast, solution for the constant discharge rate reaches a steady state quickly asymptoting the new steady state value for time exceeding the residence time. Estimated residence time is compared with the numerical experiments and observations.
How to cite: Dukhovskoy, D.: Using a first-order autonomous dynamical system to evaluate residence time of the Greenland freshwater anomaly in the Subpolar Gyre, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1958, https://doi.org/10.5194/egusphere-egu2020-1958, 2020.
Increasing Greenland discharge has contributed more than 5000 km3 of surplus fresh water to the Subpolar North Atlantic since the early 1990s. The volume of this freshwater anomaly is projected to cause freshening in the North Atlantic leading to changes in the intensity of deep convection and thermohaline circulation in the subpolar North Atlantic. This is roughly half of the freshwater volume of the Great Salinity Anomaly of the 1970s that caused notable freshening in the Subpolar North Atlantic. In analogy with the Great Salinity Anomaly, it has been proposed that, over the years, this additional Greenland freshwater discharge might have a great impact on convection driving thermohaline circulation in the North Atlantic with consequent impact on climate. Previous numerical studies demonstrate that roughly half of this Greenland freshwater anomaly accumulates in the Subpolar Gyre. However, time scales over which the Greenland freshwater anomaly can accumulate in the subpolar basins is not known. This study estimates the residence time of the Greenland freshwater anomaly in the Subpolar Gyre by approximating the process of the anomaly accumulation in the study domain with a first order autonomous dynamical system forced by the Greenland freshwater anomaly discharge. General solutions are obtained for two types of the forcing function. First, the Greenland freshwater anomaly discharge is a constant function imposed as a step function. Second, the surplus discharge is a linearly increasing function. The solutions are deduced by utilizing results from the numerical experiments that tracked spreading of the Greenland fresh water with a passive tracer. The residence time of the freshwater anomaly is estimated to be about 10–15 years. The main differences in the solutions is that under the linearly increasing discharge rate, the volume of the accumulated Greenland freshwater anomaly in the Subpolar Gyre does not reach a steady state. By contrast, solution for the constant discharge rate reaches a steady state quickly asymptoting the new steady state value for time exceeding the residence time. Estimated residence time is compared with the numerical experiments and observations.
How to cite: Dukhovskoy, D.: Using a first-order autonomous dynamical system to evaluate residence time of the Greenland freshwater anomaly in the Subpolar Gyre, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1958, https://doi.org/10.5194/egusphere-egu2020-1958, 2020.
EGU2020-21710 | Displays | NP1.1
Explicit inclusion of connectivity in geostatistical facies modelling.Tom Manzocchi, Deirdre Walsh, Carneiro Marcus, Javier López-Cabrera, and Soni Kishan
Irrespective of the specific technique (variogram-based, object-based or training image-based) applied, geostatistical facies models usually use facies proportions as the constraining input parameter to be honoured in the output model. The three-dimensional interconnectivity of the facies bodies in these models increases as the facies proportion increases, and the universal percolation thresholds that define the onset of macroscopic connectivity in idealized statistical physics models define also the connectivity of these facies models. Put simply, the bodies are well connected when the model net:gross ratio exceeds about 30%, and because of the similar behaviour of different geostatistical approaches, some researchers have concluded that the same threshold applies to geological systems.
In this contribution we contend that connectivity in geological systems has more degrees of freedom than it does in conventional geostatistical facies models, and hence that geostatistical facies modelling should be constrained at input by a facies connectivity parameter as well as a facies proportion parameter. We have developed a method that decouples facies proportion from facies connectivity in the modelling process, and which allows systems to be generated in which both are defined independently at input. This so-called compression-based modelling approach applies the universal link between the connectivity and volume fraction in geostatistical modelling to first generate a model with the correct connectivity but incorrect volume fraction using a conventional geostatistical approach, and then applies a geometrical transform which scales the model to the correct facies proportions while maintaining the connectivity of the original model. The method is described and illustrated using examples representative of different geological systems. These include situations in which connectivity is both higher (e.g. fluid-driven injectite or karst networks) and lower (e.g. many depositional systems) than can be achieved in conventional geostatistical facies models.
How to cite: Manzocchi, T., Walsh, D., Marcus, C., López-Cabrera, J., and Kishan, S.: Explicit inclusion of connectivity in geostatistical facies modelling., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21710, https://doi.org/10.5194/egusphere-egu2020-21710, 2020.
Irrespective of the specific technique (variogram-based, object-based or training image-based) applied, geostatistical facies models usually use facies proportions as the constraining input parameter to be honoured in the output model. The three-dimensional interconnectivity of the facies bodies in these models increases as the facies proportion increases, and the universal percolation thresholds that define the onset of macroscopic connectivity in idealized statistical physics models define also the connectivity of these facies models. Put simply, the bodies are well connected when the model net:gross ratio exceeds about 30%, and because of the similar behaviour of different geostatistical approaches, some researchers have concluded that the same threshold applies to geological systems.
In this contribution we contend that connectivity in geological systems has more degrees of freedom than it does in conventional geostatistical facies models, and hence that geostatistical facies modelling should be constrained at input by a facies connectivity parameter as well as a facies proportion parameter. We have developed a method that decouples facies proportion from facies connectivity in the modelling process, and which allows systems to be generated in which both are defined independently at input. This so-called compression-based modelling approach applies the universal link between the connectivity and volume fraction in geostatistical modelling to first generate a model with the correct connectivity but incorrect volume fraction using a conventional geostatistical approach, and then applies a geometrical transform which scales the model to the correct facies proportions while maintaining the connectivity of the original model. The method is described and illustrated using examples representative of different geological systems. These include situations in which connectivity is both higher (e.g. fluid-driven injectite or karst networks) and lower (e.g. many depositional systems) than can be achieved in conventional geostatistical facies models.
How to cite: Manzocchi, T., Walsh, D., Marcus, C., López-Cabrera, J., and Kishan, S.: Explicit inclusion of connectivity in geostatistical facies modelling., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21710, https://doi.org/10.5194/egusphere-egu2020-21710, 2020.
EGU2020-6447 | Displays | NP1.1
Log-log linearity of the asymptotic distribution - a valid indicator of multi-fractality?Peter Bossew
The asymptotic shape of the marginal frequency distribution of geochemical variables has been proposed as indicator of multi-fractality. Transition into a certain statistical regime as inferred from the distribution function may be considered as criterion to delineate geochemical anomalies, including mineral resources or pollutants such as radioactive fallout or geogenic radon.
The argument is that asymptotic linearity in log-log scale, log(F(z)) = a - b log(z) as z→∞, b>0 a constant, indicates multi-fractality.
We discuss this with respect to two issues:
(1) What are the consequences of estimating the slope b for non-ergodic, in particular non-representative and preferential sampling schemes, as often the case in geochemical or pollution surveys?
(2) Frequently in geochemistry, multiplicative cascades are considered valid generators of multifractal fields, corroborated by observed f(α) functions and variograms (Matèrn or power, for low lags). This generator leads to marginally asymptotically (high cascade orders) log-normal distributions, which in log-log scale are asymptotically (high z) parabolic, not linear.
Theoretical aspects are addressed as well as examples given.
How to cite: Bossew, P.: Log-log linearity of the asymptotic distribution - a valid indicator of multi-fractality?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6447, https://doi.org/10.5194/egusphere-egu2020-6447, 2020.
The asymptotic shape of the marginal frequency distribution of geochemical variables has been proposed as indicator of multi-fractality. Transition into a certain statistical regime as inferred from the distribution function may be considered as criterion to delineate geochemical anomalies, including mineral resources or pollutants such as radioactive fallout or geogenic radon.
The argument is that asymptotic linearity in log-log scale, log(F(z)) = a - b log(z) as z→∞, b>0 a constant, indicates multi-fractality.
We discuss this with respect to two issues:
(1) What are the consequences of estimating the slope b for non-ergodic, in particular non-representative and preferential sampling schemes, as often the case in geochemical or pollution surveys?
(2) Frequently in geochemistry, multiplicative cascades are considered valid generators of multifractal fields, corroborated by observed f(α) functions and variograms (Matèrn or power, for low lags). This generator leads to marginally asymptotically (high cascade orders) log-normal distributions, which in log-log scale are asymptotically (high z) parabolic, not linear.
Theoretical aspects are addressed as well as examples given.
How to cite: Bossew, P.: Log-log linearity of the asymptotic distribution - a valid indicator of multi-fractality?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6447, https://doi.org/10.5194/egusphere-egu2020-6447, 2020.
EGU2020-268 | Displays | NP1.1
Multiscale measures of phase-space trajectoriesTommaso Alberti, Giuseppe Consolini, Peter D. Ditlevsen, Reik V. Donner, and Virgilio Quattrociocchi
Several attempts have been made in characterizing the multiscale nature of fluctuations from nonlinear and nonstationary time series. Particularly, the study of their fractal structure has made use of different approaches like the structure function analysis, the evaluation of the generalized dimensions, and so on. Here we report on a different approach for characterizing phase-space trajectories by using the empirical modes derived via the Empirical Mode Decomposition (EMD) method. We show how the derived Intrinsic Mode Functions (IMFs) can be used as source of local (in terms of scales) information allowing us in deriving multiscale measures when looking at the behavior of the generalized fractal dimensions at different scales. This formalism is applied to three pedagogical examples like the Lorenz system, the Henon map, and the standard map. We also show that this formalism is readily applicable to characterize both the behavior of the Earth’s climate during the past 5 Ma and the dynamical properties of the near-Earth electromagnetic environment as monitored by the SYM-H index.
How to cite: Alberti, T., Consolini, G., Ditlevsen, P. D., Donner, R. V., and Quattrociocchi, V.: Multiscale measures of phase-space trajectories, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-268, https://doi.org/10.5194/egusphere-egu2020-268, 2020.
Several attempts have been made in characterizing the multiscale nature of fluctuations from nonlinear and nonstationary time series. Particularly, the study of their fractal structure has made use of different approaches like the structure function analysis, the evaluation of the generalized dimensions, and so on. Here we report on a different approach for characterizing phase-space trajectories by using the empirical modes derived via the Empirical Mode Decomposition (EMD) method. We show how the derived Intrinsic Mode Functions (IMFs) can be used as source of local (in terms of scales) information allowing us in deriving multiscale measures when looking at the behavior of the generalized fractal dimensions at different scales. This formalism is applied to three pedagogical examples like the Lorenz system, the Henon map, and the standard map. We also show that this formalism is readily applicable to characterize both the behavior of the Earth’s climate during the past 5 Ma and the dynamical properties of the near-Earth electromagnetic environment as monitored by the SYM-H index.
How to cite: Alberti, T., Consolini, G., Ditlevsen, P. D., Donner, R. V., and Quattrociocchi, V.: Multiscale measures of phase-space trajectories, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-268, https://doi.org/10.5194/egusphere-egu2020-268, 2020.
EGU2020-2299 | Displays | NP1.1
Fragmentation of steaming Surtseyan bombsMark McGuinness and Emma Greenbank
A Surtseyan volcanic eruption involves a bulk interaction between water and hot magma, mediated by the return of ejected ash. Surtsey Island, off the coast of Iceland, was born during such an eruption process in the 1940s. Mount Ruapehu in New Zealand also undergoes Surtseyan eruptions, due to its crater lake.
One feature of such eruptions is ejected lava bombs, trailing steam, with evidence that watery slurry was trapped inside them during the ejection process. Simple calculations indicate that the pressures developed due to boiling inside such a bomb should shatter it. Yet intact bombs are routinely discovered in debris piles. In an attempt to crack this problem, and provide a criterion for fragmentation of Surtseyan bombs, a transient mathematical model of the flashing of water to steam inside one of these hot erupted lava balls is developed, with a particular focus on the maximum pressure attained, and how it depends on magma and fluid properties. Numerical and asymptotic solutions provide some answers for volcanologists.
How to cite: McGuinness, M. and Greenbank, E.: Fragmentation of steaming Surtseyan bombs, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2299, https://doi.org/10.5194/egusphere-egu2020-2299, 2020.
A Surtseyan volcanic eruption involves a bulk interaction between water and hot magma, mediated by the return of ejected ash. Surtsey Island, off the coast of Iceland, was born during such an eruption process in the 1940s. Mount Ruapehu in New Zealand also undergoes Surtseyan eruptions, due to its crater lake.
One feature of such eruptions is ejected lava bombs, trailing steam, with evidence that watery slurry was trapped inside them during the ejection process. Simple calculations indicate that the pressures developed due to boiling inside such a bomb should shatter it. Yet intact bombs are routinely discovered in debris piles. In an attempt to crack this problem, and provide a criterion for fragmentation of Surtseyan bombs, a transient mathematical model of the flashing of water to steam inside one of these hot erupted lava balls is developed, with a particular focus on the maximum pressure attained, and how it depends on magma and fluid properties. Numerical and asymptotic solutions provide some answers for volcanologists.
How to cite: McGuinness, M. and Greenbank, E.: Fragmentation of steaming Surtseyan bombs, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2299, https://doi.org/10.5194/egusphere-egu2020-2299, 2020.
EGU2020-20491 | Displays | NP1.1
Solving the erosion transport equation on three dimensional catchmentsMichal Kuraz and Petr Mayer
Modeling the kinematic wave equation and sediment transport equation enables a deterministic approach for predicting surface runoff and resulting sediment transport. Both the kinematic wave equation and the sediment transport equation are first order differential equations. Moreover the kinematic wave equation is a quasilinear problem. In many engineering applications this set of equations is solved on one-dimensional representative cross-sections. However, a proper selection of representative cross-section(s) is cumbersome. On the other hand integrating this set of equations on real catchment topography yields difficulties for standard variational methods such as continous Galerkin method. These difficulties are two-fold (1) the nonlinearity of the kinematic wave, and (2) the absence of diffusion term, which acts as a stabilization term for convection-diffusion equation. In a theory, the Peclet number of numerical stability reaches infinity.
In this contribution we will focus on a stable numerical approximation of this convection-only problem using least square method. With this method we are able to reliably solve both the kinematic wave equation and the sediment transport equation on computational domains representing real catchment topography. Several examples representing real-world scenarios will be given.
How to cite: Kuraz, M. and Mayer, P.: Solving the erosion transport equation on three dimensional catchments, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20491, https://doi.org/10.5194/egusphere-egu2020-20491, 2020.
Modeling the kinematic wave equation and sediment transport equation enables a deterministic approach for predicting surface runoff and resulting sediment transport. Both the kinematic wave equation and the sediment transport equation are first order differential equations. Moreover the kinematic wave equation is a quasilinear problem. In many engineering applications this set of equations is solved on one-dimensional representative cross-sections. However, a proper selection of representative cross-section(s) is cumbersome. On the other hand integrating this set of equations on real catchment topography yields difficulties for standard variational methods such as continous Galerkin method. These difficulties are two-fold (1) the nonlinearity of the kinematic wave, and (2) the absence of diffusion term, which acts as a stabilization term for convection-diffusion equation. In a theory, the Peclet number of numerical stability reaches infinity.
In this contribution we will focus on a stable numerical approximation of this convection-only problem using least square method. With this method we are able to reliably solve both the kinematic wave equation and the sediment transport equation on computational domains representing real catchment topography. Several examples representing real-world scenarios will be given.
How to cite: Kuraz, M. and Mayer, P.: Solving the erosion transport equation on three dimensional catchments, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20491, https://doi.org/10.5194/egusphere-egu2020-20491, 2020.
EGU2020-2040 | Displays | NP1.1
Conditions for the emergence and growth of aeolian sand structuresElena Malinovskaya and Otto Chkhetiani
One of the important characteristics of the wind process of dust removal is a critical or threshold wind velocity [1]. Saltating flow grows with increasing of the effective roughness [2] that affecting shear stress and friction velocity [3]. The drag coefficient increases depending on the density of the coating by particles of the surface [4]. The location of particles in the aeolian structure, their size and relative position determine their resistance to wind influence. Aeolian structures change the structure of flows and the balance of mass transfer of particles deposited and rising from the surface [5]. The surface microstructures and ripples significantly affect of sand removal.
The flow of particles with a size of 100 μm on the surface has been considered using the OPEN FOAM with LES model. The calculation area has sizes of 5x5x2 mm. For the velocity at the upper boundary, 2.8 m/s select in accordance with the experimental data [6]. It should be noted that with a relative increase in the distance between pairs of particles and a change in the level of the upper surface, the pressure difference between the base and top of the particle increases by 10-30 percents. Depending on the distance between the particles, the buoyant force acting from the side of the air flow, the critical velocity, and the departure velocity of the particle also change. When the distances between the surfaces of the particles are close to its size, the buoyant force is greater than the adhesion and gravity forces. As a result, areas with different probability for the sand removal by wind, due to which, in particular, the occurrence of aeolian ripples occurs.
The average critical velocity increases when moving up the windward slope of the dune [7, 8]. This phenomenon is possibly associated with the influence of ripples on the air flow. The flow around of the micro-ripples with a height of 0.1-1 mm was considered for air flow velocity of 2-4 m/s at a height of 1-2 cm. The addition of supplementary elements of heterogeneity at the apex near the rough surface of the streamlined aeolian structure leads to a displacement of the separation point of the ascending flows. Also we have a change in the length of the recirculation zone and the time intervals of the strengthening of the wind at the apex, which was observed in [6].
The study was supported by the RFBR project 19-05-50110 and partial support of the program of the Presidium of the Russian Academy of Sciences No. 12.
1. Shao Y. Physics and modeling of wind erosion. Springer.2008.p.452.
2. Martin R.L., Kok J.F. J.Geophys.Res.2018.123(7).1546-1565.
3. Turpin C et al. Earth Surf. Proc. and Land.2010.35(12). 1418-1429.
4. Yang X.I.A. et al. J. Fluid Mech.2019.880. 992-1019.
5. Luna M.C.M.M. et al. Geomorph.2011.129(3-4). 215-224.
6. Semenov O.E. Introduction to experimental meteorology and climatology of the sand storms. Almaty. 2011. p.580 (in Russian).
7. Neuman C.M.K et al. Sediment. 2000. 47(1). 211-226.
8. Malinovskaya E.A. Izv. Atmos. Oceanic Phys. 2019. 55(2). 86-92.
How to cite: Malinovskaya, E. and Chkhetiani, O.: Conditions for the emergence and growth of aeolian sand structures , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2040, https://doi.org/10.5194/egusphere-egu2020-2040, 2020.
One of the important characteristics of the wind process of dust removal is a critical or threshold wind velocity [1]. Saltating flow grows with increasing of the effective roughness [2] that affecting shear stress and friction velocity [3]. The drag coefficient increases depending on the density of the coating by particles of the surface [4]. The location of particles in the aeolian structure, their size and relative position determine their resistance to wind influence. Aeolian structures change the structure of flows and the balance of mass transfer of particles deposited and rising from the surface [5]. The surface microstructures and ripples significantly affect of sand removal.
The flow of particles with a size of 100 μm on the surface has been considered using the OPEN FOAM with LES model. The calculation area has sizes of 5x5x2 mm. For the velocity at the upper boundary, 2.8 m/s select in accordance with the experimental data [6]. It should be noted that with a relative increase in the distance between pairs of particles and a change in the level of the upper surface, the pressure difference between the base and top of the particle increases by 10-30 percents. Depending on the distance between the particles, the buoyant force acting from the side of the air flow, the critical velocity, and the departure velocity of the particle also change. When the distances between the surfaces of the particles are close to its size, the buoyant force is greater than the adhesion and gravity forces. As a result, areas with different probability for the sand removal by wind, due to which, in particular, the occurrence of aeolian ripples occurs.
The average critical velocity increases when moving up the windward slope of the dune [7, 8]. This phenomenon is possibly associated with the influence of ripples on the air flow. The flow around of the micro-ripples with a height of 0.1-1 mm was considered for air flow velocity of 2-4 m/s at a height of 1-2 cm. The addition of supplementary elements of heterogeneity at the apex near the rough surface of the streamlined aeolian structure leads to a displacement of the separation point of the ascending flows. Also we have a change in the length of the recirculation zone and the time intervals of the strengthening of the wind at the apex, which was observed in [6].
The study was supported by the RFBR project 19-05-50110 and partial support of the program of the Presidium of the Russian Academy of Sciences No. 12.
1. Shao Y. Physics and modeling of wind erosion. Springer.2008.p.452.
2. Martin R.L., Kok J.F. J.Geophys.Res.2018.123(7).1546-1565.
3. Turpin C et al. Earth Surf. Proc. and Land.2010.35(12). 1418-1429.
4. Yang X.I.A. et al. J. Fluid Mech.2019.880. 992-1019.
5. Luna M.C.M.M. et al. Geomorph.2011.129(3-4). 215-224.
6. Semenov O.E. Introduction to experimental meteorology and climatology of the sand storms. Almaty. 2011. p.580 (in Russian).
7. Neuman C.M.K et al. Sediment. 2000. 47(1). 211-226.
8. Malinovskaya E.A. Izv. Atmos. Oceanic Phys. 2019. 55(2). 86-92.
How to cite: Malinovskaya, E. and Chkhetiani, O.: Conditions for the emergence and growth of aeolian sand structures , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2040, https://doi.org/10.5194/egusphere-egu2020-2040, 2020.
NP2.1 – Nonlinear Multiscale and Stochastic Dynamics of the Earth System
EGU2020-2035 | Displays | NP2.1
A DNS-based Turbulence Parametrization for Global Climate Models: Doubly Diffusive ConvectionYuchen Ma and William Peltier
Global coupled climate modeling requires the representation of multiple widely separated scales in each model component. In the ocean component, the separation of scales is especially dramatic as small scale turbulence exerts significant control on the global scale overturning circulation. The importance of this control is demonstrated in the context of analyses of the Dansgaard-Oeschger oscillation of Marine Isotope Stage 3 (MIS 3; see Peltier and Vettoretti, 2014)). In the University of Toronto version of CCSM4 water column diapycnal diffusivity is represented using the KPP parameterization of Large et al (1994). This includes explicit contributions due to double diffusion processes which demonstrably play an important role in determining the period of the D-O oscillation itself.
We have developed a DNS-based methodology to test the accuracy of the doubly diffusive contributions to KPP. High-resolution turbulence data sets have been produced based upon two different models: the “unbounded gradient model” and the “interface model” with depth-dependent temperature and salinity gradients. By fitting the vertical fluxes in the unbounded gradient model (for equilibrium states) as a function of density ratio (the governing non-dimensional parameter) we derive a functional form on the basis of which KPP can be revised. By applying the revised scheme to the interface model we demonstrate that the local fluxes predicted agree well with those from the numerical simulations. The difference between this new parametrization scheme and KPP demonstrates that KPP may significantly overestimate the diffusivities for both heat and salt at low-density ratio.
How to cite: Ma, Y. and Peltier, W.: A DNS-based Turbulence Parametrization for Global Climate Models: Doubly Diffusive Convection, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2035, https://doi.org/10.5194/egusphere-egu2020-2035, 2020.
Global coupled climate modeling requires the representation of multiple widely separated scales in each model component. In the ocean component, the separation of scales is especially dramatic as small scale turbulence exerts significant control on the global scale overturning circulation. The importance of this control is demonstrated in the context of analyses of the Dansgaard-Oeschger oscillation of Marine Isotope Stage 3 (MIS 3; see Peltier and Vettoretti, 2014)). In the University of Toronto version of CCSM4 water column diapycnal diffusivity is represented using the KPP parameterization of Large et al (1994). This includes explicit contributions due to double diffusion processes which demonstrably play an important role in determining the period of the D-O oscillation itself.
We have developed a DNS-based methodology to test the accuracy of the doubly diffusive contributions to KPP. High-resolution turbulence data sets have been produced based upon two different models: the “unbounded gradient model” and the “interface model” with depth-dependent temperature and salinity gradients. By fitting the vertical fluxes in the unbounded gradient model (for equilibrium states) as a function of density ratio (the governing non-dimensional parameter) we derive a functional form on the basis of which KPP can be revised. By applying the revised scheme to the interface model we demonstrate that the local fluxes predicted agree well with those from the numerical simulations. The difference between this new parametrization scheme and KPP demonstrates that KPP may significantly overestimate the diffusivities for both heat and salt at low-density ratio.
How to cite: Ma, Y. and Peltier, W.: A DNS-based Turbulence Parametrization for Global Climate Models: Doubly Diffusive Convection, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2035, https://doi.org/10.5194/egusphere-egu2020-2035, 2020.
EGU2020-2398 | Displays | NP2.1
Effects of large scale advection and small scale turbulence on vertical phytoplankton dynamicsVinicius Beltram Tergolina, Stefano Berti, and Gilmar Mompean
When studying the life cycle of phytoplankton frequently one is interested in the survival or death conditions of a population (bloom/no bloom). These dynamics have been studied extensively in the literature through a range of modelling scenarios but in summary the main factors affecting the vertical dynamics are: Water column mixing intensity, solar energy distribution, nutrients availability and predatory activity. The later two can be represented by different biological models whereas the vertical mixing is usually parameterized by a diffusive process. Even though turbulence has been recognized as a paramount factor in the survival dynamics of sinking phytoplankton species, dealing with the multi scale nature of turbulence is a formidable challenge from the modelling point of view. In addition, convective motions are being recognized to play a role in the survival of phytoplankton throughout winter stocking. With this in mind, in this work we revisit a theoretically appealing model for phytoplankton vertical dynamics with turbulent diffusivity and numerically study how large-scale fluid motions affect its survival and extinction conditions. To achieve this and to work with realistic parameter values, we adopt a kinematic flow field to account for the different spatial and temporal scales of turbulent motions. The dynamics of the population density are described by a reaction-advection-diffusion model with a growth term proportional to sun light availability. Light depletion is modelled accounting for water turbidity and plankton self-shading; advection is represented by a sinking speed and a two-dimensional, multiscale, chaotic flow. Preliminary results show that under appropriate conditions for the flow, our model reproduces past results based on turbulent diffusivity. Furthermore, the presence of large scale vortices (such as those one might expect during winter convection) seems to hinder survival, an effect that is partially mitigated by turbulent diffusion.
How to cite: Beltram Tergolina, V., Berti, S., and Mompean, G.: Effects of large scale advection and small scale turbulence on vertical phytoplankton dynamics, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2398, https://doi.org/10.5194/egusphere-egu2020-2398, 2020.
When studying the life cycle of phytoplankton frequently one is interested in the survival or death conditions of a population (bloom/no bloom). These dynamics have been studied extensively in the literature through a range of modelling scenarios but in summary the main factors affecting the vertical dynamics are: Water column mixing intensity, solar energy distribution, nutrients availability and predatory activity. The later two can be represented by different biological models whereas the vertical mixing is usually parameterized by a diffusive process. Even though turbulence has been recognized as a paramount factor in the survival dynamics of sinking phytoplankton species, dealing with the multi scale nature of turbulence is a formidable challenge from the modelling point of view. In addition, convective motions are being recognized to play a role in the survival of phytoplankton throughout winter stocking. With this in mind, in this work we revisit a theoretically appealing model for phytoplankton vertical dynamics with turbulent diffusivity and numerically study how large-scale fluid motions affect its survival and extinction conditions. To achieve this and to work with realistic parameter values, we adopt a kinematic flow field to account for the different spatial and temporal scales of turbulent motions. The dynamics of the population density are described by a reaction-advection-diffusion model with a growth term proportional to sun light availability. Light depletion is modelled accounting for water turbidity and plankton self-shading; advection is represented by a sinking speed and a two-dimensional, multiscale, chaotic flow. Preliminary results show that under appropriate conditions for the flow, our model reproduces past results based on turbulent diffusivity. Furthermore, the presence of large scale vortices (such as those one might expect during winter convection) seems to hinder survival, an effect that is partially mitigated by turbulent diffusion.
How to cite: Beltram Tergolina, V., Berti, S., and Mompean, G.: Effects of large scale advection and small scale turbulence on vertical phytoplankton dynamics, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2398, https://doi.org/10.5194/egusphere-egu2020-2398, 2020.
EGU2020-4239 | Displays | NP2.1
Monitoring marine coastal areasAna M. Mancho, Guillermo Garcia-Sanchez, and José Antonio Jimenez-Madrid
The European Commission has invested in developing services such as the Copernicus Marine Environment Monitoring Services that offer opportunities to new downstream applications. This presentation describes the development of monitoring services in coastal areas at the submesoscale, by addressing synergies between different available marine technologies and products such as satellite images, autonomous surface and underwater vehicles, drone images, downscaled hydrodynamic models, etc, that get inspired in recent success cases [1, 2]. In particular ongoing efforts will be discussed that address the operational implementation of these tools for the management of marine pollution in harbors and coasts with a focus in the hydrodynamic modelling aspects.
Support is acknowledged from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 821922 (IMPRESSIVE) and from Fundacion Biodiversidad and European Commission (BEWATS).
References
[1] A. G. Ramos, V. J. García-Garrido, A. M. Mancho, S. Wiggins, J. Coca, S. Glenn, O. Schofield, J. Kohut, D. Aragon, J. Kerfoot, T. Haskins, T. Miles, C. Haldeman, N. Strandskov, B. Allsup, C. Jones, J. Shapiro. Lagrangian coherent structure assisted path planning for transoceanic autonomous underwater vehicle missions. Sci. Rep. 8, 4575 (2018).
[2] V. J. Garcia-Garrido, A. Ramos, A. M. Mancho, J. Coca, S. Wiggins. A dynamical systems perspective for a real-time response to a marine oil spill. Mar. Pollut. Bull. 112, 201-210, (2016).
How to cite: Mancho, A. M., Garcia-Sanchez, G., and Jimenez-Madrid, J. A.: Monitoring marine coastal areas, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4239, https://doi.org/10.5194/egusphere-egu2020-4239, 2020.
The European Commission has invested in developing services such as the Copernicus Marine Environment Monitoring Services that offer opportunities to new downstream applications. This presentation describes the development of monitoring services in coastal areas at the submesoscale, by addressing synergies between different available marine technologies and products such as satellite images, autonomous surface and underwater vehicles, drone images, downscaled hydrodynamic models, etc, that get inspired in recent success cases [1, 2]. In particular ongoing efforts will be discussed that address the operational implementation of these tools for the management of marine pollution in harbors and coasts with a focus in the hydrodynamic modelling aspects.
Support is acknowledged from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 821922 (IMPRESSIVE) and from Fundacion Biodiversidad and European Commission (BEWATS).
References
[1] A. G. Ramos, V. J. García-Garrido, A. M. Mancho, S. Wiggins, J. Coca, S. Glenn, O. Schofield, J. Kohut, D. Aragon, J. Kerfoot, T. Haskins, T. Miles, C. Haldeman, N. Strandskov, B. Allsup, C. Jones, J. Shapiro. Lagrangian coherent structure assisted path planning for transoceanic autonomous underwater vehicle missions. Sci. Rep. 8, 4575 (2018).
[2] V. J. Garcia-Garrido, A. Ramos, A. M. Mancho, J. Coca, S. Wiggins. A dynamical systems perspective for a real-time response to a marine oil spill. Mar. Pollut. Bull. 112, 201-210, (2016).
How to cite: Mancho, A. M., Garcia-Sanchez, G., and Jimenez-Madrid, J. A.: Monitoring marine coastal areas, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4239, https://doi.org/10.5194/egusphere-egu2020-4239, 2020.
EGU2020-17781 | Displays | NP2.1
Scaling Analysis of the China France Oceanography Satellite Along Track Wave and Wind DataYang Gao, Francois G Schmitt, Jianyu Hu, and Yongxiang Huang
Turbulence or turbulence-like phenomena are ubiquitous in nature, often showing a power-law behavior of the Fourier power spectrum in either spatial or temporal domains. This power-law behavior is due to interactions among different scales of motion, and to the absence of characteristic scale among several scale ranges. It can be further interpreted in the framework of turbulent cascade with movements on continuous range of scales. The power-law feature and the associate cascade picture are vitally important to our understanding of the ocean and atmosphere dynamics. In this work, we consider the China France Oceanography SATellite (CFOSAT) data in the general framework of ocean and atmosphere multi-scale dynamics. We apply both Fourier power spectrum analysis and second-order structure-function analysis, used in the fields of turbulence, to extract multiscale information from the wind speed (WS) and significant wave-height (Hs) data provided by CFOSAT project. The data analyzed here are along track data spatially collected from 29th July to 31th December 2019. The measured Fourier power spectrums for both WS and Hs illustrate a dual power-law behavior respectively from 5 to 25 km, and 30 to 500 km with measured scaling exponents β close to 2 and 5/3. The measured second-order structure-functions confirm the existence of the dual power-law behavior. The corresponding measured scaling exponents ζ(2) close to 1 and 2/3 for the spatial scales mentioned above. Our preliminary results confirm the relevance of using multiscale statistical tools and turbulent theory to characterize the large-scale movements of both ocean and atmosphere.
How to cite: Gao, Y., Schmitt, F. G., Hu, J., and Huang, Y.: Scaling Analysis of the China France Oceanography Satellite Along Track Wave and Wind Data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17781, https://doi.org/10.5194/egusphere-egu2020-17781, 2020.
Turbulence or turbulence-like phenomena are ubiquitous in nature, often showing a power-law behavior of the Fourier power spectrum in either spatial or temporal domains. This power-law behavior is due to interactions among different scales of motion, and to the absence of characteristic scale among several scale ranges. It can be further interpreted in the framework of turbulent cascade with movements on continuous range of scales. The power-law feature and the associate cascade picture are vitally important to our understanding of the ocean and atmosphere dynamics. In this work, we consider the China France Oceanography SATellite (CFOSAT) data in the general framework of ocean and atmosphere multi-scale dynamics. We apply both Fourier power spectrum analysis and second-order structure-function analysis, used in the fields of turbulence, to extract multiscale information from the wind speed (WS) and significant wave-height (Hs) data provided by CFOSAT project. The data analyzed here are along track data spatially collected from 29th July to 31th December 2019. The measured Fourier power spectrums for both WS and Hs illustrate a dual power-law behavior respectively from 5 to 25 km, and 30 to 500 km with measured scaling exponents β close to 2 and 5/3. The measured second-order structure-functions confirm the existence of the dual power-law behavior. The corresponding measured scaling exponents ζ(2) close to 1 and 2/3 for the spatial scales mentioned above. Our preliminary results confirm the relevance of using multiscale statistical tools and turbulent theory to characterize the large-scale movements of both ocean and atmosphere.
How to cite: Gao, Y., Schmitt, F. G., Hu, J., and Huang, Y.: Scaling Analysis of the China France Oceanography Satellite Along Track Wave and Wind Data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17781, https://doi.org/10.5194/egusphere-egu2020-17781, 2020.
EGU2020-18620 | Displays | NP2.1
Submesoscales variability from surface drifter and HF radar measurements: scale and wind dependence of kinematic propertiesMaristella Berta, Annalisa Griffa, Lorenzo Corgnati, Marcello Magaldi, Carlo Mantovani, Helga Huntley, Andrew Poje, and Tamay Ozgokmen
The dynamics of the near-surface ocean currents result from the nonlinear interaction of simultaneous mechanisms at different scales. Of these, the submesoscale range (a few hundred meters to 10 km, hours to a few days) remains particularly challenging to observe directly, due to the high variability in both time and space. In this study, the scale-dependence of kinematic properties (divergence, vorticity and strain) in the submesoscale range, as well as their response to atmospheric forcing, is investigated in two distinct geographic regions: the Ligurian (NW-Mediterranean) Sea and the Northern Gulf of Mexico. The two applications are characterized by different dynamics, and the estimates of kinematic properties are derived from distinctly different observational approaches: in situ GPS drifters observations and remote HF radar data.
The Ligurian Sea application is based on HF radar measurements obtained for the JERICO-NEXT (Joint European Research Infrastructure network for Coastal Observatory – Novel European eXpertise for coastal observaTories) and IMPACT (Port Impact on Protected Marine Areas: Cooperative Cross-Border Actions) projects. Surface current measurements span 40 km off the coast with 1.5 km resolution, available every hour. The velocity fields are used to estimate the kinematic properties with an Eulerian approach, which allows the identification of structures such as eddies and jets of the order of a few km. We focus in particular on the response of the submesoscales to an extreme wind event that was captured by the observations. The deformation of the spatial structures suggests nonlinear interactions with the wind forcing, and the kinematic properties' magnitudes are almost doubled (exceeding the Coriolis parameter, f).
In the Gulf of Mexico, velocity observations are available from a series of massive, nearly simultaneous drifter releases conducted by CARTHE (Consortium for Advanced Research of Transport of Hydrocarbons in the Environment). Drifter triplets are analysed to estimate the kinematic properties of the flow at scales between 100 m and 5 km over a time scale of a day. Results show that the mean kinematic properties increase in magnitude with decreasing scales, with winter values generally higher than summer ones. For winter flows, vorticity and divergence distributions have more substantial tails of values multiple times the Coriolis paramater f at scales up to 2 km, while in the summer such large values are restricted to smaller scales (100-500 m).
The Lagrangian estimates of kinematic properties obtained in the Gulf of Mexico were also compared to Eulerian estimates from concurrent X-band radar measurements, showing good correlation and validating the comparison across observational methods. Moreover, the scale-dependence of the kinematic properties from drifter triplets was found to be consistent with turbulence scaling laws evaluated as two-particle statistics. We conclude that the kinematic properties metric provides a robust complementary methodology to characterize submesoscales and can be used both with Lagrangian and Eulerian observations.
How to cite: Berta, M., Griffa, A., Corgnati, L., Magaldi, M., Mantovani, C., Huntley, H., Poje, A., and Ozgokmen, T.: Submesoscales variability from surface drifter and HF radar measurements: scale and wind dependence of kinematic properties, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18620, https://doi.org/10.5194/egusphere-egu2020-18620, 2020.
The dynamics of the near-surface ocean currents result from the nonlinear interaction of simultaneous mechanisms at different scales. Of these, the submesoscale range (a few hundred meters to 10 km, hours to a few days) remains particularly challenging to observe directly, due to the high variability in both time and space. In this study, the scale-dependence of kinematic properties (divergence, vorticity and strain) in the submesoscale range, as well as their response to atmospheric forcing, is investigated in two distinct geographic regions: the Ligurian (NW-Mediterranean) Sea and the Northern Gulf of Mexico. The two applications are characterized by different dynamics, and the estimates of kinematic properties are derived from distinctly different observational approaches: in situ GPS drifters observations and remote HF radar data.
The Ligurian Sea application is based on HF radar measurements obtained for the JERICO-NEXT (Joint European Research Infrastructure network for Coastal Observatory – Novel European eXpertise for coastal observaTories) and IMPACT (Port Impact on Protected Marine Areas: Cooperative Cross-Border Actions) projects. Surface current measurements span 40 km off the coast with 1.5 km resolution, available every hour. The velocity fields are used to estimate the kinematic properties with an Eulerian approach, which allows the identification of structures such as eddies and jets of the order of a few km. We focus in particular on the response of the submesoscales to an extreme wind event that was captured by the observations. The deformation of the spatial structures suggests nonlinear interactions with the wind forcing, and the kinematic properties' magnitudes are almost doubled (exceeding the Coriolis parameter, f).
In the Gulf of Mexico, velocity observations are available from a series of massive, nearly simultaneous drifter releases conducted by CARTHE (Consortium for Advanced Research of Transport of Hydrocarbons in the Environment). Drifter triplets are analysed to estimate the kinematic properties of the flow at scales between 100 m and 5 km over a time scale of a day. Results show that the mean kinematic properties increase in magnitude with decreasing scales, with winter values generally higher than summer ones. For winter flows, vorticity and divergence distributions have more substantial tails of values multiple times the Coriolis paramater f at scales up to 2 km, while in the summer such large values are restricted to smaller scales (100-500 m).
The Lagrangian estimates of kinematic properties obtained in the Gulf of Mexico were also compared to Eulerian estimates from concurrent X-band radar measurements, showing good correlation and validating the comparison across observational methods. Moreover, the scale-dependence of the kinematic properties from drifter triplets was found to be consistent with turbulence scaling laws evaluated as two-particle statistics. We conclude that the kinematic properties metric provides a robust complementary methodology to characterize submesoscales and can be used both with Lagrangian and Eulerian observations.
How to cite: Berta, M., Griffa, A., Corgnati, L., Magaldi, M., Mantovani, C., Huntley, H., Poje, A., and Ozgokmen, T.: Submesoscales variability from surface drifter and HF radar measurements: scale and wind dependence of kinematic properties, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18620, https://doi.org/10.5194/egusphere-egu2020-18620, 2020.
EGU2020-3681 | Displays | NP2.1
Why can't models get the mesoscale atmospheric spectrum right?Jih-Wang Aaron Wang and Prashant Sardeshmukh
Despite decades of development, global atmospheric models continue to have trouble in capturing the -5/3 slope of the atmospheric mesoscale kinetic energy (KE) spectrum suggested by conventional turbulence theory and upper tropospheric aircraft observations in the 1980s (e.g., Nastrom and Gage 1986). We have approached this issue in two ways: 1) How certain can we be that the “real” spectrum has a -5/3 slope? and 2) Are turbulent cascades the only determinants of the mesoscale spectrum? To address the first issue, especially in light of the vastly greater number of upper-air observations that have been analyzed since the 1980s, we have examined the 200-hPa KE spectra in several high-resolution global reanalysis datasets, including the NCEP GFS (resolution T1534 and T254), ERA-Interim (T255), ERA5 (T639), and JRA-55 (T319) datasets. We find that the mesoscale portions of the global spectra are highly mutually inconsistent. This is primarily because the global mesoscale KE has a large contribution from the KE in convective regions, which differs greatly among the various reanalyses. There is thus indeed some ambiguity concerning the slope of the “true” mesoscale spectrum.
To address the second issue, especially given the sensitivity of the reanalysis spectra to representations of convection and damping in the reanalysis models, we assessed the sensitivity of the model spectra in two ways: (a) by stochastically perturbing the physical tendencies and (b) by decreasing the hyper-viscosity coefficient, in large ensembles of 10-day forecasts made with the NCEP GFS (T254) model. Both changes increased the mesoscale KE and decreased the steep spectral slope. The impact of the stochastic physics varied with the specified length scale of the stochastic perturbations.
Our conclusions about issues 1) and 2) raised above are that (1) we do not really know the “true” mesoscale KE spectrum, and (2) model KE spectra are sensitive to and can be manipulated by stochastically perturbing the parameterized physical tendencies and tuning the horizontal diffusion in a model. It may therefore be misleading for modelers to pursue the -5/3 slope of the Nastrom-Gage spectrum.
How to cite: Wang, J.-W. A. and Sardeshmukh, P.: Why can't models get the mesoscale atmospheric spectrum right?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3681, https://doi.org/10.5194/egusphere-egu2020-3681, 2020.
Despite decades of development, global atmospheric models continue to have trouble in capturing the -5/3 slope of the atmospheric mesoscale kinetic energy (KE) spectrum suggested by conventional turbulence theory and upper tropospheric aircraft observations in the 1980s (e.g., Nastrom and Gage 1986). We have approached this issue in two ways: 1) How certain can we be that the “real” spectrum has a -5/3 slope? and 2) Are turbulent cascades the only determinants of the mesoscale spectrum? To address the first issue, especially in light of the vastly greater number of upper-air observations that have been analyzed since the 1980s, we have examined the 200-hPa KE spectra in several high-resolution global reanalysis datasets, including the NCEP GFS (resolution T1534 and T254), ERA-Interim (T255), ERA5 (T639), and JRA-55 (T319) datasets. We find that the mesoscale portions of the global spectra are highly mutually inconsistent. This is primarily because the global mesoscale KE has a large contribution from the KE in convective regions, which differs greatly among the various reanalyses. There is thus indeed some ambiguity concerning the slope of the “true” mesoscale spectrum.
To address the second issue, especially given the sensitivity of the reanalysis spectra to representations of convection and damping in the reanalysis models, we assessed the sensitivity of the model spectra in two ways: (a) by stochastically perturbing the physical tendencies and (b) by decreasing the hyper-viscosity coefficient, in large ensembles of 10-day forecasts made with the NCEP GFS (T254) model. Both changes increased the mesoscale KE and decreased the steep spectral slope. The impact of the stochastic physics varied with the specified length scale of the stochastic perturbations.
Our conclusions about issues 1) and 2) raised above are that (1) we do not really know the “true” mesoscale KE spectrum, and (2) model KE spectra are sensitive to and can be manipulated by stochastically perturbing the parameterized physical tendencies and tuning the horizontal diffusion in a model. It may therefore be misleading for modelers to pursue the -5/3 slope of the Nastrom-Gage spectrum.
How to cite: Wang, J.-W. A. and Sardeshmukh, P.: Why can't models get the mesoscale atmospheric spectrum right?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3681, https://doi.org/10.5194/egusphere-egu2020-3681, 2020.
EGU2020-6170 | Displays | NP2.1
The maximum likelihood climate change for global warming under the influence of greenhouse effect and Levy noiseYayun Zheng
An abrupt climatic transition could be triggered by a single extreme event, and an alpha-stable non-Gaussian Levy noise is regarded as a type of noise to generate such extreme events. In contrast with the classic Gaussian noise, a comprehensive approach of the most probable transition path for systems under alpha-stable Levy noise is still lacking. We develop here a probabilistic framework, based on the nonlocal Fokker-Planck equation, to investigate the maximum likelihood climate change for an energy balance system under the influence of greenhouse effect and Levy fluctuations. We find that a period of the cold climate state can be interrupted by a sharp shift to the warmer one due to larger noise jumps with low frequency. Additionally, the climate change for warming 1.5 degree under an enhanced greenhouse effect generates a step-like growth process. These results provide important insights into the underlying mechanisms of abrupt climate transitions triggered by a Levy process.
How to cite: Zheng, Y.: The maximum likelihood climate change for global warming under the influence of greenhouse effect and Levy noise, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6170, https://doi.org/10.5194/egusphere-egu2020-6170, 2020.
An abrupt climatic transition could be triggered by a single extreme event, and an alpha-stable non-Gaussian Levy noise is regarded as a type of noise to generate such extreme events. In contrast with the classic Gaussian noise, a comprehensive approach of the most probable transition path for systems under alpha-stable Levy noise is still lacking. We develop here a probabilistic framework, based on the nonlocal Fokker-Planck equation, to investigate the maximum likelihood climate change for an energy balance system under the influence of greenhouse effect and Levy fluctuations. We find that a period of the cold climate state can be interrupted by a sharp shift to the warmer one due to larger noise jumps with low frequency. Additionally, the climate change for warming 1.5 degree under an enhanced greenhouse effect generates a step-like growth process. These results provide important insights into the underlying mechanisms of abrupt climate transitions triggered by a Levy process.
How to cite: Zheng, Y.: The maximum likelihood climate change for global warming under the influence of greenhouse effect and Levy noise, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6170, https://doi.org/10.5194/egusphere-egu2020-6170, 2020.
EGU2020-1667 | Displays | NP2.1
Detecting regime transitions in time series using dynamic mode decompositionGeorg Gottwald and Federica Gugole
We employ the framework of the Koopman operator and dynamic mode decomposition to devise a computationally cheap and easily implementable method to detect transient dynamics and regime changes in time series. We argue that typically transient dynamics experiences the full state space dimension with subsequent fast relaxation towards the attractor. In equilibrium, on the other hand, the dynamics evolves on a slower time scale on a lower dimensional attractor. The reconstruction error of a dynamic mode decomposition is used to monitor the inability of the time series to resolve the fast relaxation towards the attractor as well as the effective dimension of the dynamics. We illustrate our method by detecting transient dynamics in the Kuramoto-Sivashinsky equation. We further apply our method to atmospheric reanalysis data; our diagnostics detects the transition from a predominantly negative North Atlantic Oscillation (NAO) to a predominantly positive NAO around 1970, as well as the recently found regime change in the Southern Hemisphere atmospheric circulation around 1970.
How to cite: Gottwald, G. and Gugole, F.: Detecting regime transitions in time series using dynamic mode decomposition, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1667, https://doi.org/10.5194/egusphere-egu2020-1667, 2020.
We employ the framework of the Koopman operator and dynamic mode decomposition to devise a computationally cheap and easily implementable method to detect transient dynamics and regime changes in time series. We argue that typically transient dynamics experiences the full state space dimension with subsequent fast relaxation towards the attractor. In equilibrium, on the other hand, the dynamics evolves on a slower time scale on a lower dimensional attractor. The reconstruction error of a dynamic mode decomposition is used to monitor the inability of the time series to resolve the fast relaxation towards the attractor as well as the effective dimension of the dynamics. We illustrate our method by detecting transient dynamics in the Kuramoto-Sivashinsky equation. We further apply our method to atmospheric reanalysis data; our diagnostics detects the transition from a predominantly negative North Atlantic Oscillation (NAO) to a predominantly positive NAO around 1970, as well as the recently found regime change in the Southern Hemisphere atmospheric circulation around 1970.
How to cite: Gottwald, G. and Gugole, F.: Detecting regime transitions in time series using dynamic mode decomposition, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1667, https://doi.org/10.5194/egusphere-egu2020-1667, 2020.
EGU2020-4849 | Displays | NP2.1
Screening the coupled atmosphere-ocean system based on Covariant Lyapunov VectorsVera Melinda Galfi, Lesley de Cruz, Valerio Lucarini, and Sebastian Schubert
We analyze linear perturbations of a coupled quasi-geostrophic atmosphere-ocean model based on Covariant Lyapunov Vectors (CLVs). CLVs reveal the local geometrical structure of the attractor, and point into the direction of linear perturbations applied to the trajectory. Thus they represent a link between the geometry of the attractor and basic dynamical properties of the system, and they are physically meaningful. We compute the CLVs based on the so-called Ginelli method using the tangent linear version of the quasi-geostrophic atmosphere-ocean model MAOOAM (Modular Arbitrary-Order Ocean-Atmosphere Model). Based on the CLVs, we can quantify the contribution of each model variable on each scale to the development of linear instabilities. We also study the changes in the structure of the attractor - and, consequently, in the basic dynamical properties of our system - as an effect of the ocean-atmopshere coupling strength and the model resolution.
How to cite: Galfi, V. M., de Cruz, L., Lucarini, V., and Schubert, S.: Screening the coupled atmosphere-ocean system based on Covariant Lyapunov Vectors, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4849, https://doi.org/10.5194/egusphere-egu2020-4849, 2020.
We analyze linear perturbations of a coupled quasi-geostrophic atmosphere-ocean model based on Covariant Lyapunov Vectors (CLVs). CLVs reveal the local geometrical structure of the attractor, and point into the direction of linear perturbations applied to the trajectory. Thus they represent a link between the geometry of the attractor and basic dynamical properties of the system, and they are physically meaningful. We compute the CLVs based on the so-called Ginelli method using the tangent linear version of the quasi-geostrophic atmosphere-ocean model MAOOAM (Modular Arbitrary-Order Ocean-Atmosphere Model). Based on the CLVs, we can quantify the contribution of each model variable on each scale to the development of linear instabilities. We also study the changes in the structure of the attractor - and, consequently, in the basic dynamical properties of our system - as an effect of the ocean-atmopshere coupling strength and the model resolution.
How to cite: Galfi, V. M., de Cruz, L., Lucarini, V., and Schubert, S.: Screening the coupled atmosphere-ocean system based on Covariant Lyapunov Vectors, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4849, https://doi.org/10.5194/egusphere-egu2020-4849, 2020.
EGU2020-14052 | Displays | NP2.1
Explicit nonlinear waves of fluid models on extended domains and unbounded growth with backscatterArtur Prugger and Jens Rademacher
Large scale motions in geophysical fluid models are often characterised by linear waves, which are obtained by linearising the equations. But there are also many explicit solutions of the fully nonlinear equations when posed the full space. The exact solutions we are investigating often characterise Rossby waves, since they are in geostrophic balance. They also can be compositions of waves, some are interacting with each other and some do not, showing wave interactions as explicit solutions in the fully nonlinear problem.
In this talk I will briefly introduce the idea behind these explicit nonlinear waves and show some of their properties, and their occurrence in different fluid models in extended domains.
As an application, we especially focus on a rotating shallow water model with simplified backscatter. In this case one finds not only geostrophic explicit solutions, but also ageostrophic ones. Moreover, here energy accumulates in selected scales due to the backscatter terms and causes exponentially and unboundedly growing ageostrophic nonlinear waves. This also relates to instability of coexisting stationary waves and is an instance of the role of nonlinear waves in energy transfer, and illustrates their role in preventing energy equidistribution for general data.
How to cite: Prugger, A. and Rademacher, J.: Explicit nonlinear waves of fluid models on extended domains and unbounded growth with backscatter, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-14052, https://doi.org/10.5194/egusphere-egu2020-14052, 2020.
Large scale motions in geophysical fluid models are often characterised by linear waves, which are obtained by linearising the equations. But there are also many explicit solutions of the fully nonlinear equations when posed the full space. The exact solutions we are investigating often characterise Rossby waves, since they are in geostrophic balance. They also can be compositions of waves, some are interacting with each other and some do not, showing wave interactions as explicit solutions in the fully nonlinear problem.
In this talk I will briefly introduce the idea behind these explicit nonlinear waves and show some of their properties, and their occurrence in different fluid models in extended domains.
As an application, we especially focus on a rotating shallow water model with simplified backscatter. In this case one finds not only geostrophic explicit solutions, but also ageostrophic ones. Moreover, here energy accumulates in selected scales due to the backscatter terms and causes exponentially and unboundedly growing ageostrophic nonlinear waves. This also relates to instability of coexisting stationary waves and is an instance of the role of nonlinear waves in energy transfer, and illustrates their role in preventing energy equidistribution for general data.
How to cite: Prugger, A. and Rademacher, J.: Explicit nonlinear waves of fluid models on extended domains and unbounded growth with backscatter, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-14052, https://doi.org/10.5194/egusphere-egu2020-14052, 2020.
EGU2020-5723 | Displays | NP2.1
What could we learn about climate sensitivity from variability in the surface temperature record?James Annan, Julia Hargreaves, Thorsten Mauritsen, and Bjorn Stevens
We examine what can be learnt about climate sensitivity from variability in the surface air temperature record over the instrumental period, from around 1880 to the present. While many previous studies have used the trend in the time series to constrain equilibrium climate sensitivity, it has recently been argued that temporal variability may also be a powerful constraint. We explore this question in the context of a simple widely used energy balance model of the climate system. We consider two recently-proposed summary measures of variability and also show how the full information content can be optimally used in this idealised scenario. We find that the constraint provided by variability is inherently skewed and its power is inversely related to the sensitivity itself, discriminating most strongly between low sensitivity values and weakening substantially for higher values. As a result of this, is only when the sensitivity is very low that the variability can provide a tight constraint. Our results support the analysis of variability as a potentially useful tool in helping to constrain equilibrium climate sensitivity, but suggest caution in the interpretation of precise results.
How to cite: Annan, J., Hargreaves, J., Mauritsen, T., and Stevens, B.: What could we learn about climate sensitivity from variability in the surface temperature record?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5723, https://doi.org/10.5194/egusphere-egu2020-5723, 2020.
We examine what can be learnt about climate sensitivity from variability in the surface air temperature record over the instrumental period, from around 1880 to the present. While many previous studies have used the trend in the time series to constrain equilibrium climate sensitivity, it has recently been argued that temporal variability may also be a powerful constraint. We explore this question in the context of a simple widely used energy balance model of the climate system. We consider two recently-proposed summary measures of variability and also show how the full information content can be optimally used in this idealised scenario. We find that the constraint provided by variability is inherently skewed and its power is inversely related to the sensitivity itself, discriminating most strongly between low sensitivity values and weakening substantially for higher values. As a result of this, is only when the sensitivity is very low that the variability can provide a tight constraint. Our results support the analysis of variability as a potentially useful tool in helping to constrain equilibrium climate sensitivity, but suggest caution in the interpretation of precise results.
How to cite: Annan, J., Hargreaves, J., Mauritsen, T., and Stevens, B.: What could we learn about climate sensitivity from variability in the surface temperature record?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5723, https://doi.org/10.5194/egusphere-egu2020-5723, 2020.
EGU2020-4671 | Displays | NP2.1
Extreme sensitivity and climate tipping pointsAnna von der Heydt and Peter Ashwin
The equilibrium climate sensitivity (ECS) is widely used as a measure for possible future global warming. It has been determined from a wide range of climate models, observations and palaeoclimate records, however, it still remains relatively unconstrained. In particular, large values of warming as a consequence of atmospheric greenhouse gas increase cannot be excluded, with some of the most recent state-of-the-art climate models (CMIP6) supporting (much) more warming than previous generations of climate models. Moreover, a number of tipping elements have been identified within the climate system, some of which may affect the global mean temperature. Therefore, it is interesting to explore how the climate systems response (e.g. ECS) behaves when the system is close to a tipping point.
A climate state close to a tipping point will have a degenerate linear response to perturbations, which can be associated with extreme values of the equilibrium climate sensitivity (ECS). In this talk we contrast linearized ('instantaneous') with fully nonlinear geometric ('two-point') notions of ECS, in both presence and absence of tipping points. For a stochastic energy balance model of the global mean surface temperature with two stable regimes, we confirm that tipping events cause the appearance of extremes in both notions of ECS. Moreover, multiple regimes with different mean sensitivities are visible in the two-point ECS. We confirm some of our findings in a physics-based multi-box model of the climate system.
Reference
P. Ashwin and A. S. von der Heydt (2019), Extreme Sensitivity and Climate Tipping Points, J. Stat. Phys. 370, 1166–24. http://doi.org/10.1007/s10955-019-02425-x.
How to cite: von der Heydt, A. and Ashwin, P.: Extreme sensitivity and climate tipping points, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4671, https://doi.org/10.5194/egusphere-egu2020-4671, 2020.
The equilibrium climate sensitivity (ECS) is widely used as a measure for possible future global warming. It has been determined from a wide range of climate models, observations and palaeoclimate records, however, it still remains relatively unconstrained. In particular, large values of warming as a consequence of atmospheric greenhouse gas increase cannot be excluded, with some of the most recent state-of-the-art climate models (CMIP6) supporting (much) more warming than previous generations of climate models. Moreover, a number of tipping elements have been identified within the climate system, some of which may affect the global mean temperature. Therefore, it is interesting to explore how the climate systems response (e.g. ECS) behaves when the system is close to a tipping point.
A climate state close to a tipping point will have a degenerate linear response to perturbations, which can be associated with extreme values of the equilibrium climate sensitivity (ECS). In this talk we contrast linearized ('instantaneous') with fully nonlinear geometric ('two-point') notions of ECS, in both presence and absence of tipping points. For a stochastic energy balance model of the global mean surface temperature with two stable regimes, we confirm that tipping events cause the appearance of extremes in both notions of ECS. Moreover, multiple regimes with different mean sensitivities are visible in the two-point ECS. We confirm some of our findings in a physics-based multi-box model of the climate system.
Reference
P. Ashwin and A. S. von der Heydt (2019), Extreme Sensitivity and Climate Tipping Points, J. Stat. Phys. 370, 1166–24. http://doi.org/10.1007/s10955-019-02425-x.
How to cite: von der Heydt, A. and Ashwin, P.: Extreme sensitivity and climate tipping points, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4671, https://doi.org/10.5194/egusphere-egu2020-4671, 2020.
EGU2020-9262 | Displays | NP2.1
Wavenumber Decomposition and Extremes of Atmospheric Meridional Energy Transport in the Northern Hemisphere MidlatitudesValerio Lembo, Gabriele Messori, Rune Graversen, and Valerio Lucarini
The atmospheric meridional energy transport in the Northern Hemisphere midlatitudes is mainly accomplished by planetary and synoptic waves. A decomposition into wave components highlights the strong seasonal dependence of the transport, with both the total transport and the contributions from planetary and synoptic waves peaking in winter. In both winter and summer months, poleward transport extremes primarily result from a constructive interference between planetary and synoptic motions. The contribution of the mean meridional circulation is close to climatology. Equatorward transport extremes feature a mean meridional equatorward transport in winter, while the planetary and synoptic modes mostly transport energy poleward. In summer, a systematic destructive interference occurs, with planetary modes mostly transporting energy equatorward and synoptic modes again poleward. This underscores that baroclinic conversion dominates regardless of season in the synoptic wave modes, whereas the planetary waves can be either free or forced, depending on the season.
How to cite: Lembo, V., Messori, G., Graversen, R., and Lucarini, V.: Wavenumber Decomposition and Extremes of Atmospheric Meridional Energy Transport in the Northern Hemisphere Midlatitudes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9262, https://doi.org/10.5194/egusphere-egu2020-9262, 2020.
The atmospheric meridional energy transport in the Northern Hemisphere midlatitudes is mainly accomplished by planetary and synoptic waves. A decomposition into wave components highlights the strong seasonal dependence of the transport, with both the total transport and the contributions from planetary and synoptic waves peaking in winter. In both winter and summer months, poleward transport extremes primarily result from a constructive interference between planetary and synoptic motions. The contribution of the mean meridional circulation is close to climatology. Equatorward transport extremes feature a mean meridional equatorward transport in winter, while the planetary and synoptic modes mostly transport energy poleward. In summer, a systematic destructive interference occurs, with planetary modes mostly transporting energy equatorward and synoptic modes again poleward. This underscores that baroclinic conversion dominates regardless of season in the synoptic wave modes, whereas the planetary waves can be either free or forced, depending on the season.
How to cite: Lembo, V., Messori, G., Graversen, R., and Lucarini, V.: Wavenumber Decomposition and Extremes of Atmospheric Meridional Energy Transport in the Northern Hemisphere Midlatitudes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9262, https://doi.org/10.5194/egusphere-egu2020-9262, 2020.
EGU2020-12286 | Displays | NP2.1
Stochastic modelling and prediction of monthly surface temperatures: StocSIPSLenin Del Rio Amador and Shaun Lovejoy
From hourly to decadal time scales, atmospheric fields are characterized by two scaling regimes: at high frequencies the weather, with fluctuations increasing with the time scale, and at low frequencies, macroweather with fluctuations decreasing with scale, the transition between the two at τw. This transition time is the lifetime of planetary structures and is therefore close to the deterministic predictability limit of conventional numerical weather prediction models. While it is thus the outer scale of deterministic weather models, conversely, it is the inner scale of stochastic macroweather models.
Here we explore the spatial dependence of this transition time. Starting at the surface (2m temperature) we found that the monthly average temperature falls in the macroweather regime for almost any location in the globe, except for parts of the tropical ocean where τw ∼ 1 - 2 years. As we increase in altitude, the dependence of τw with the location becomes more homogeneous and above 850mb τw < 1 month almost everywhere. The longer tropical ocean transition scales are presumably the deterministic outer scales of the “ocean weather” regime.
Knowledge of τw is fundamental for stochastic macroweather forecasting. Such forecasting is based on symmetries, primarily the power-law behavior of the fluctuations that implies a huge memory that can be exploited for forecasts up to several years. In addition, there is another approximate symmetry called “statistical space-time factorization” relating spatial and temporal statistics. Finally, while weather regime temperature fluctuations are highly intermittent, in macroweather the intermittency is much lower, fluctuations are quasi Gaussian.
The Stochastic Seasonal and Interannual Prediction System (StocSIPS[1,2]) is a stochastic data-driven model that exploits these symmetries to perform macroweather (long-term) forecasts. Compared to traditional global circulation models (GCM), it has the advantage of forcing predictions to converge to the real-world climate (not the model climate). It extracts the internal variability (weather noise) directly from past data and does not suffer from model drift. Some other practical advantages include much lower computational cost, no need for downscaling and no ad hoc postprocessing.
We show that StocSIPS can predict monthly average surface temperature (nearly) to its stochastic predictability limits. Using monthly to annual lead time hindcasts, we compare StocSIPS predictions with those from the CanSIPS[3] GCM. Beyond a month, and especially over land, StocSIPS generally has higher skill. For regular StocSIPS forecasts, see http://www.physics.mcgill.ca/StocSIPS/.
References
[1] Del Rio Amador, L. and Lovejoy, S. (2019) Clim Dyn, 53: 4373. https://doi.org/10.1007/s00382-019-04791-4
[2] Lovejoy, S., Del Rio Amador, L., Hébert, R. (2017) In Nonlinear Advances in Geosciences, A.A. Tsonis ed. Springer Nature, 305–355 DOI: 10.1007/978-3-319-58895-7
[3] Merryfield WJ, Denis B, Fontecilla JS, Lee WS, Kharin S, Hodgson J, Archambault B (2011) Rep., 51pp, Environment Canada.
How to cite: Del Rio Amador, L. and Lovejoy, S.: Stochastic modelling and prediction of monthly surface temperatures: StocSIPS, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12286, https://doi.org/10.5194/egusphere-egu2020-12286, 2020.
From hourly to decadal time scales, atmospheric fields are characterized by two scaling regimes: at high frequencies the weather, with fluctuations increasing with the time scale, and at low frequencies, macroweather with fluctuations decreasing with scale, the transition between the two at τw. This transition time is the lifetime of planetary structures and is therefore close to the deterministic predictability limit of conventional numerical weather prediction models. While it is thus the outer scale of deterministic weather models, conversely, it is the inner scale of stochastic macroweather models.
Here we explore the spatial dependence of this transition time. Starting at the surface (2m temperature) we found that the monthly average temperature falls in the macroweather regime for almost any location in the globe, except for parts of the tropical ocean where τw ∼ 1 - 2 years. As we increase in altitude, the dependence of τw with the location becomes more homogeneous and above 850mb τw < 1 month almost everywhere. The longer tropical ocean transition scales are presumably the deterministic outer scales of the “ocean weather” regime.
Knowledge of τw is fundamental for stochastic macroweather forecasting. Such forecasting is based on symmetries, primarily the power-law behavior of the fluctuations that implies a huge memory that can be exploited for forecasts up to several years. In addition, there is another approximate symmetry called “statistical space-time factorization” relating spatial and temporal statistics. Finally, while weather regime temperature fluctuations are highly intermittent, in macroweather the intermittency is much lower, fluctuations are quasi Gaussian.
The Stochastic Seasonal and Interannual Prediction System (StocSIPS[1,2]) is a stochastic data-driven model that exploits these symmetries to perform macroweather (long-term) forecasts. Compared to traditional global circulation models (GCM), it has the advantage of forcing predictions to converge to the real-world climate (not the model climate). It extracts the internal variability (weather noise) directly from past data and does not suffer from model drift. Some other practical advantages include much lower computational cost, no need for downscaling and no ad hoc postprocessing.
We show that StocSIPS can predict monthly average surface temperature (nearly) to its stochastic predictability limits. Using monthly to annual lead time hindcasts, we compare StocSIPS predictions with those from the CanSIPS[3] GCM. Beyond a month, and especially over land, StocSIPS generally has higher skill. For regular StocSIPS forecasts, see http://www.physics.mcgill.ca/StocSIPS/.
References
[1] Del Rio Amador, L. and Lovejoy, S. (2019) Clim Dyn, 53: 4373. https://doi.org/10.1007/s00382-019-04791-4
[2] Lovejoy, S., Del Rio Amador, L., Hébert, R. (2017) In Nonlinear Advances in Geosciences, A.A. Tsonis ed. Springer Nature, 305–355 DOI: 10.1007/978-3-319-58895-7
[3] Merryfield WJ, Denis B, Fontecilla JS, Lee WS, Kharin S, Hodgson J, Archambault B (2011) Rep., 51pp, Environment Canada.
How to cite: Del Rio Amador, L. and Lovejoy, S.: Stochastic modelling and prediction of monthly surface temperatures: StocSIPS, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12286, https://doi.org/10.5194/egusphere-egu2020-12286, 2020.
EGU2020-6031 | Displays | NP2.1
Scaling and anisotropic heterogeneities of ocean SST images from satellite dataFrancois Schmitt, Hussein Yahia, Joel Sudre, Véronique Garçon, and Guillaume Charria
Oceanic fields display a large variability over large temporal and spatial scales. One way to characterize such variability, borrowed from the field of turbulence, is to consider scaling regimes and multi-scaling properties.
He we use 2D power spectral analysis as well as 2D structure functions <X(M)-X(N)q>=F(q,d(M,N)), between tow points M and N belonging to the region of interest. By performing statistics with respect to the distance d(M,N), one may extract the scaling property of the 2D field, for a range of distances Lmin<d<Lmax, of the form F(q,d)=dζ(q). This approach can be used even for irregular images (having missing values due to cloud coverage) or for part of images in order to estimate the statistical heterogeneity of different zones of a given image.
In the framework of the French CNRS/IMECO project, we consider MODIS Aqua SST images, in France (English Channel versus Gascogne Golf) and in Chili (Eastern Boundary Upwelling System). We illustrate the use of the 2D structure function analysis for different part of these images and also different times. Scaling ranges and also scaling exponents are compared. To take into account the anisotropy of some of these zones, an anisotropic version of the 2D structure functions is also used.
How to cite: Schmitt, F., Yahia, H., Sudre, J., Garçon, V., and Charria, G.: Scaling and anisotropic heterogeneities of ocean SST images from satellite data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6031, https://doi.org/10.5194/egusphere-egu2020-6031, 2020.
Oceanic fields display a large variability over large temporal and spatial scales. One way to characterize such variability, borrowed from the field of turbulence, is to consider scaling regimes and multi-scaling properties.
He we use 2D power spectral analysis as well as 2D structure functions <X(M)-X(N)q>=F(q,d(M,N)), between tow points M and N belonging to the region of interest. By performing statistics with respect to the distance d(M,N), one may extract the scaling property of the 2D field, for a range of distances Lmin<d<Lmax, of the form F(q,d)=dζ(q). This approach can be used even for irregular images (having missing values due to cloud coverage) or for part of images in order to estimate the statistical heterogeneity of different zones of a given image.
In the framework of the French CNRS/IMECO project, we consider MODIS Aqua SST images, in France (English Channel versus Gascogne Golf) and in Chili (Eastern Boundary Upwelling System). We illustrate the use of the 2D structure function analysis for different part of these images and also different times. Scaling ranges and also scaling exponents are compared. To take into account the anisotropy of some of these zones, an anisotropic version of the 2D structure functions is also used.
How to cite: Schmitt, F., Yahia, H., Sudre, J., Garçon, V., and Charria, G.: Scaling and anisotropic heterogeneities of ocean SST images from satellite data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6031, https://doi.org/10.5194/egusphere-egu2020-6031, 2020.
EGU2020-8195 | Displays | NP2.1
Mesoscale eddy characteristics in the Labrador Sea from observations and a 1/60° numerical modelArne Bendinger, Johannes Karstensen, Julien Le Sommer, Aurélie Albert, and Fehmi Dilmahamod
Mesoscale eddies play an important role in lateral property fluxes. Observational studies often use sea level anomaly maps from satellite altimetry to estimate eddy statistics (incl. eddy kinetic energy). Recent findings suggest that altimetry derived eddy characteristics may suffer from the low spatial resolution of past and current satellite-tracks in high-latitude oceans associated with small Rossby radii. Here we present results of an eddy reconstruction based on a nonlinear damping Gauss-Newton optimisation algorithm using ship based current profiler observations from two research expeditions in the Labrador Sea in 2014 and 2016. Overall we detect 14 eddies with radii ranging from 7 to 35 km.
In order to verify the skill of the reconstruction we used the submesoscale permitting NATL60 model (1/60°) as a reference data set. Spectral analysis of the horizontal velocity implies that the mesoscale regime is well represented in NATL60 compared with the observations. The submesoscale regime in the model spectra shows deviations to the observations at scales smaller than 10km near the ocean surface. The representation of the submesoscale flow further decreases in the model with increasing depth.
By subsampling the NATL60 model velocities along artificial ship tracks, applying our eddy reconstruction algorithm, and comparing the results with the full model field, a skill assessment of the reconstruction is done. We show that the reconstruction of the eddy characteristics can be affected by the location of the ship track through the velocity field.
In comparison with the observed eddies the NATL60 eddies have smaller radii and higher azimuthal velocities and thus are more nonlinear. The inner core velocity structure for observations and NATL60 suggests solid body rotation for 2/3 of the radius. The maximum azimuthal velocity may deviate by up to 50% from solid body rotation.
The seasonality of the submesoscale regime can be seen in the data as the power spectrum is reduced from spring to summer in both the ship-based measurements and model.
How to cite: Bendinger, A., Karstensen, J., Le Sommer, J., Albert, A., and Dilmahamod, F.: Mesoscale eddy characteristics in the Labrador Sea from observations and a 1/60° numerical model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8195, https://doi.org/10.5194/egusphere-egu2020-8195, 2020.
Mesoscale eddies play an important role in lateral property fluxes. Observational studies often use sea level anomaly maps from satellite altimetry to estimate eddy statistics (incl. eddy kinetic energy). Recent findings suggest that altimetry derived eddy characteristics may suffer from the low spatial resolution of past and current satellite-tracks in high-latitude oceans associated with small Rossby radii. Here we present results of an eddy reconstruction based on a nonlinear damping Gauss-Newton optimisation algorithm using ship based current profiler observations from two research expeditions in the Labrador Sea in 2014 and 2016. Overall we detect 14 eddies with radii ranging from 7 to 35 km.
In order to verify the skill of the reconstruction we used the submesoscale permitting NATL60 model (1/60°) as a reference data set. Spectral analysis of the horizontal velocity implies that the mesoscale regime is well represented in NATL60 compared with the observations. The submesoscale regime in the model spectra shows deviations to the observations at scales smaller than 10km near the ocean surface. The representation of the submesoscale flow further decreases in the model with increasing depth.
By subsampling the NATL60 model velocities along artificial ship tracks, applying our eddy reconstruction algorithm, and comparing the results with the full model field, a skill assessment of the reconstruction is done. We show that the reconstruction of the eddy characteristics can be affected by the location of the ship track through the velocity field.
In comparison with the observed eddies the NATL60 eddies have smaller radii and higher azimuthal velocities and thus are more nonlinear. The inner core velocity structure for observations and NATL60 suggests solid body rotation for 2/3 of the radius. The maximum azimuthal velocity may deviate by up to 50% from solid body rotation.
The seasonality of the submesoscale regime can be seen in the data as the power spectrum is reduced from spring to summer in both the ship-based measurements and model.
How to cite: Bendinger, A., Karstensen, J., Le Sommer, J., Albert, A., and Dilmahamod, F.: Mesoscale eddy characteristics in the Labrador Sea from observations and a 1/60° numerical model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8195, https://doi.org/10.5194/egusphere-egu2020-8195, 2020.
EGU2020-8222 | Displays | NP2.1
Multi-scale coastal surface temperature in the Bay of Biscay and the English ChannelGuillaume Charria, Sébastien Theetten, Adam Ayouche, Coline Poppeschi, Joël Sudre, Hussein Yahia, Véronique Garçon, and François Schmitt
The Bay of Biscay and the English Channel, in the North-eastern Atlantic, are considered as a natural laboratory to explore the coastal dynamics at different spatial and temporal scales. In those regions, the coastal circulation is constrained by a complex topography (e.g. varying width of the continental shelf, canyons), river runoffs, strong tides and a seasonally contrasted wind-driven circulation.
Based on different numerical model experiments (from 400m to 4km spatial resolution, from 40 to 100 sigma vertical layers using 3D primitive equation ocean models), different features of the Bay of Biscay and English Channel circulation are assessed and explored. Both spatial (submesoscale and mesoscale) and temporal (from hourly to monthly) scales are considered. Modelled spatial scales, with a specific focus on the variability of fine scale features (e.g. fronts, filaments, eddies), are compared with remotely sensed observations (i.e. Sea Surface Temperature). Different methodologies as singularity and Lyapunov exponents allow describing fine scales features and are applied on both modelled and observed datasets. For temporal scales, in situ high frequency surface temperature measurements from coastal moorings (from COAST-HF observing network) provide a reference for the temporal variability to be modelled. Exploring differences in the temporal scales (from an Empirical Mode Decomposition) advises on the efficiency of our coastal modelling approach.
This result overview in the Bay of Biscay and the English Channel aims illustrating the input of coastal modelling activities in understanding multi-scale interactions (spatial and temporal).
How to cite: Charria, G., Theetten, S., Ayouche, A., Poppeschi, C., Sudre, J., Yahia, H., Garçon, V., and Schmitt, F.: Multi-scale coastal surface temperature in the Bay of Biscay and the English Channel, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8222, https://doi.org/10.5194/egusphere-egu2020-8222, 2020.
The Bay of Biscay and the English Channel, in the North-eastern Atlantic, are considered as a natural laboratory to explore the coastal dynamics at different spatial and temporal scales. In those regions, the coastal circulation is constrained by a complex topography (e.g. varying width of the continental shelf, canyons), river runoffs, strong tides and a seasonally contrasted wind-driven circulation.
Based on different numerical model experiments (from 400m to 4km spatial resolution, from 40 to 100 sigma vertical layers using 3D primitive equation ocean models), different features of the Bay of Biscay and English Channel circulation are assessed and explored. Both spatial (submesoscale and mesoscale) and temporal (from hourly to monthly) scales are considered. Modelled spatial scales, with a specific focus on the variability of fine scale features (e.g. fronts, filaments, eddies), are compared with remotely sensed observations (i.e. Sea Surface Temperature). Different methodologies as singularity and Lyapunov exponents allow describing fine scales features and are applied on both modelled and observed datasets. For temporal scales, in situ high frequency surface temperature measurements from coastal moorings (from COAST-HF observing network) provide a reference for the temporal variability to be modelled. Exploring differences in the temporal scales (from an Empirical Mode Decomposition) advises on the efficiency of our coastal modelling approach.
This result overview in the Bay of Biscay and the English Channel aims illustrating the input of coastal modelling activities in understanding multi-scale interactions (spatial and temporal).
How to cite: Charria, G., Theetten, S., Ayouche, A., Poppeschi, C., Sudre, J., Yahia, H., Garçon, V., and Schmitt, F.: Multi-scale coastal surface temperature in the Bay of Biscay and the English Channel, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8222, https://doi.org/10.5194/egusphere-egu2020-8222, 2020.
EGU2020-9821 | Displays | NP2.1
Detection and characterization of SCVs in the North AtlanticAshwita Chouksey, Xavier Carton, and Jonathan Gula
In recent years, the oceanographic community has devoted considerable interest to the study of SCVs (Submesoscale Coherent Vortices, i.e. vortices with radii between 2-30 km, below the first internal radius of deformation); indeed, both mesoscale and submesoscale eddies contribute to the transport and mixing of water masses and of tracers (active and passive), affecting the heat transport, the ventilation pathways and thus having an impact on the large scale circulation.
In different areas of the ocean, SCVs have been detected, via satellite or in-situ measurements, at the surface or at depth. From these data, SCVs were found to be of different shapes and sizes depending on their place of origin and on their location. Here, we will concentrate rather on the SCVs at depth.
In this study, we use a high resolution simulation of the North Atlantic ocean with the ROMS-CROCO model. In this simulation, we also identify the SCVs at different depths and densities; we analyse their site and mechanism of generation, their drift, the physical processes conducting to this drift and their interactions with the surrounding flows. We also quantify their physical characteristics (radius, thickness, intensity/vorticity, bias in polarity: cyclones versus anticyclones). We provide averages for these characteristics and standard deviations.
We compare the model results with the observational data, in particular temperature and salinity profiles from Argo floats and velocity data from currentmeter recordings.
This study is a first step in the understanding of the formation, occurrences and structure of SCVs in the North Atlantic Ocean, of help to improve their in-situ sampling.
How to cite: Chouksey, A., Carton, X., and Gula, J.: Detection and characterization of SCVs in the North Atlantic, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9821, https://doi.org/10.5194/egusphere-egu2020-9821, 2020.
In recent years, the oceanographic community has devoted considerable interest to the study of SCVs (Submesoscale Coherent Vortices, i.e. vortices with radii between 2-30 km, below the first internal radius of deformation); indeed, both mesoscale and submesoscale eddies contribute to the transport and mixing of water masses and of tracers (active and passive), affecting the heat transport, the ventilation pathways and thus having an impact on the large scale circulation.
In different areas of the ocean, SCVs have been detected, via satellite or in-situ measurements, at the surface or at depth. From these data, SCVs were found to be of different shapes and sizes depending on their place of origin and on their location. Here, we will concentrate rather on the SCVs at depth.
In this study, we use a high resolution simulation of the North Atlantic ocean with the ROMS-CROCO model. In this simulation, we also identify the SCVs at different depths and densities; we analyse their site and mechanism of generation, their drift, the physical processes conducting to this drift and their interactions with the surrounding flows. We also quantify their physical characteristics (radius, thickness, intensity/vorticity, bias in polarity: cyclones versus anticyclones). We provide averages for these characteristics and standard deviations.
We compare the model results with the observational data, in particular temperature and salinity profiles from Argo floats and velocity data from currentmeter recordings.
This study is a first step in the understanding of the formation, occurrences and structure of SCVs in the North Atlantic Ocean, of help to improve their in-situ sampling.
How to cite: Chouksey, A., Carton, X., and Gula, J.: Detection and characterization of SCVs in the North Atlantic, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9821, https://doi.org/10.5194/egusphere-egu2020-9821, 2020.
EGU2020-17939 | Displays | NP2.1
Scaling Analysis of the Algal BloomsYongxiang Huang, Yang Gao, Qianguo Xing, Francois Schmitt, and Jianyu Hu
Algal blooms, also known as ‘red tide’, are extremely harmful to the marine ecosystem since they infuse toxins into seawater and stifle oxygen in the water columns. Visually, they demonstrate rich patterns in spatial due to the interaction between the ocean current and the wind. Using the satelliate remote sensing data provided by the Chinese satellite Gaofeng 1, we first derive a normalized difference vegetation index (NDVI), which can be used to separate efficiently different types of cases, e.g., no algae bloom (NAB), macro algae bloom (MAB), and phytoplankton algae bloom (PAB), etc. The classical structure-function analysis is performed. Our preliminary results confirm the existence of the power-law behavior on the spatial scale range from 100 m to 400 m for the case of MAB. The corresponding scaling exponents are close to the ones of the classical passive scalar in three-dimension hydrodynamic turbulence. It suggests that the MAB could be treated as a passive scalar, which leads to not only a better understanding of the dynamics of algal blooms, but also a challenge of the modelling.
How to cite: Huang, Y., Gao, Y., Xing, Q., Schmitt, F., and Hu, J.: Scaling Analysis of the Algal Blooms, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17939, https://doi.org/10.5194/egusphere-egu2020-17939, 2020.
Algal blooms, also known as ‘red tide’, are extremely harmful to the marine ecosystem since they infuse toxins into seawater and stifle oxygen in the water columns. Visually, they demonstrate rich patterns in spatial due to the interaction between the ocean current and the wind. Using the satelliate remote sensing data provided by the Chinese satellite Gaofeng 1, we first derive a normalized difference vegetation index (NDVI), which can be used to separate efficiently different types of cases, e.g., no algae bloom (NAB), macro algae bloom (MAB), and phytoplankton algae bloom (PAB), etc. The classical structure-function analysis is performed. Our preliminary results confirm the existence of the power-law behavior on the spatial scale range from 100 m to 400 m for the case of MAB. The corresponding scaling exponents are close to the ones of the classical passive scalar in three-dimension hydrodynamic turbulence. It suggests that the MAB could be treated as a passive scalar, which leads to not only a better understanding of the dynamics of algal blooms, but also a challenge of the modelling.
How to cite: Huang, Y., Gao, Y., Xing, Q., Schmitt, F., and Hu, J.: Scaling Analysis of the Algal Blooms, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17939, https://doi.org/10.5194/egusphere-egu2020-17939, 2020.
EGU2020-3570 | Displays | NP2.1
Assessment of Surface Exchange Coefficients in the Noah-MP Land Surface Model for Different Land Cover Types over ChinaXia Zhang, Liang Chen, Zhuguo Ma, and Yanhong Gao
The parameterization of surface exchange coefficients (Ch) representing land–atmosphere coupling strength plays a key role in land surface modeling. Previous studies have found that land–atmosphere coupling in land surface models (LSMs) is overestimated, which affects the predictability of weather and climate evolution. To improve the representation of land–atmosphere interactions in LSMs, this study investigated the dynamic canopy-height-dependent coupling strength in the offline Noah LSM with multiparameterization options (Noah-MP) when applied to China. Comparison with the default Noah-MP LSM showed the dynamic scheme significantly improved the Ch calculations and realistically reduced the biases of simulated surface energy and water components against observations. It is noteworthy that the improvements brought by the dynamic scheme differed across land cover types. The scheme was found superior in reproducing the observed Ch as well as surface energy and water variables for short vegetation (grass, crop, and shrub), while the improvement for tall canopy (forest) was found not significant, although the estimations were reasonable. The improved version benefits from the treatment of the roughness length for heat. Overall, the dynamic coupling scheme markedly affects the simulation of land–atmosphere interactions, and altering the dynamics of surface coupling has potential for improving the representation of land–atmosphere interactions and thus furthering LSM development.
How to cite: Zhang, X., Chen, L., Ma, Z., and Gao, Y.: Assessment of Surface Exchange Coefficients in the Noah-MP Land Surface Model for Different Land Cover Types over China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3570, https://doi.org/10.5194/egusphere-egu2020-3570, 2020.
The parameterization of surface exchange coefficients (Ch) representing land–atmosphere coupling strength plays a key role in land surface modeling. Previous studies have found that land–atmosphere coupling in land surface models (LSMs) is overestimated, which affects the predictability of weather and climate evolution. To improve the representation of land–atmosphere interactions in LSMs, this study investigated the dynamic canopy-height-dependent coupling strength in the offline Noah LSM with multiparameterization options (Noah-MP) when applied to China. Comparison with the default Noah-MP LSM showed the dynamic scheme significantly improved the Ch calculations and realistically reduced the biases of simulated surface energy and water components against observations. It is noteworthy that the improvements brought by the dynamic scheme differed across land cover types. The scheme was found superior in reproducing the observed Ch as well as surface energy and water variables for short vegetation (grass, crop, and shrub), while the improvement for tall canopy (forest) was found not significant, although the estimations were reasonable. The improved version benefits from the treatment of the roughness length for heat. Overall, the dynamic coupling scheme markedly affects the simulation of land–atmosphere interactions, and altering the dynamics of surface coupling has potential for improving the representation of land–atmosphere interactions and thus furthering LSM development.
How to cite: Zhang, X., Chen, L., Ma, Z., and Gao, Y.: Assessment of Surface Exchange Coefficients in the Noah-MP Land Surface Model for Different Land Cover Types over China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3570, https://doi.org/10.5194/egusphere-egu2020-3570, 2020.
EGU2020-5632 | Displays | NP2.1
Power-law behaviour of hourly precipitation intensity and dry spell duration over the United StatesChristian Franzke, Lichao Yang, and Zuntao Fu
Precipitation is an important meteorological variable which is critical for weather risk assessment. For instance, intense but short precipitation events can lead to flash floods and landslides. Most statistical modelling studies assume that the occurrence of precipitation events is based on a Poisson process with exponentially distributed waiting times while precipitation intensities are typically described by a gamma distribution or a mixture of two exponential distributions. Here, we show by using hourly precipitation data over the United States that the waiting time between precipitation events is non-exponentially distributed and best described by a fractional Poisson process. A systematic model selection procedure reveals that the hourly precipitation intensities are best represented by a two-distribution model for about 90% of all stations. The two-distribution model consists of (a) a generalized Pareto distribution (GPD) model for bulk precipitation event sizes and (b) a power-law distribution for large and extreme events. Finally, we analyse regional climate model output to evaluate how the climate models represent the high-frequency temporal structure of U.S. precipitation. Our results reveal that these regional climate models fail to accurately reproduce the power-law behaviour of intensities and severely underestimate the long durations between events.
How to cite: Franzke, C., Yang, L., and Fu, Z.: Power-law behaviour of hourly precipitation intensity and dry spell duration over the United States, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5632, https://doi.org/10.5194/egusphere-egu2020-5632, 2020.
Precipitation is an important meteorological variable which is critical for weather risk assessment. For instance, intense but short precipitation events can lead to flash floods and landslides. Most statistical modelling studies assume that the occurrence of precipitation events is based on a Poisson process with exponentially distributed waiting times while precipitation intensities are typically described by a gamma distribution or a mixture of two exponential distributions. Here, we show by using hourly precipitation data over the United States that the waiting time between precipitation events is non-exponentially distributed and best described by a fractional Poisson process. A systematic model selection procedure reveals that the hourly precipitation intensities are best represented by a two-distribution model for about 90% of all stations. The two-distribution model consists of (a) a generalized Pareto distribution (GPD) model for bulk precipitation event sizes and (b) a power-law distribution for large and extreme events. Finally, we analyse regional climate model output to evaluate how the climate models represent the high-frequency temporal structure of U.S. precipitation. Our results reveal that these regional climate models fail to accurately reproduce the power-law behaviour of intensities and severely underestimate the long durations between events.
How to cite: Franzke, C., Yang, L., and Fu, Z.: Power-law behaviour of hourly precipitation intensity and dry spell duration over the United States, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5632, https://doi.org/10.5194/egusphere-egu2020-5632, 2020.
EGU2020-13481 | Displays | NP2.1
Nonlinear time series models for the North Atlantic OscillationAbdel Hannachi, Thomas Önskog, and Christian Franzke
The North Atlantic Oscillation (NAO) is the dominant mode of climate variability over the North Atlantic basin and has a significant impact on seasonal climate and surface weather conditions. This is the result of complex and nonlinear interactions between many spatio-temporal scales. Here, the authors study a number of linear and nonlinear models for a station-based time series of the daily winter NAO index. It is found that nonlinear autoregressive models including both short and long lags perform excellently in reproducing the characteristic statistical properties of the NAO, such as skewness and fat tails of the distribution and the different time scales of the two phases. As a spinoff of the modelling procedure, we are able to deduce that the interannual dependence of the NAO mostly affects the positive phase and that timescales of one to three weeks are more dominant for the negative phase. The statistical properties of the model makes it useful for the generation of realistic climate noise.
How to cite: Hannachi, A., Önskog, T., and Franzke, C.: Nonlinear time series models for the North Atlantic Oscillation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13481, https://doi.org/10.5194/egusphere-egu2020-13481, 2020.
The North Atlantic Oscillation (NAO) is the dominant mode of climate variability over the North Atlantic basin and has a significant impact on seasonal climate and surface weather conditions. This is the result of complex and nonlinear interactions between many spatio-temporal scales. Here, the authors study a number of linear and nonlinear models for a station-based time series of the daily winter NAO index. It is found that nonlinear autoregressive models including both short and long lags perform excellently in reproducing the characteristic statistical properties of the NAO, such as skewness and fat tails of the distribution and the different time scales of the two phases. As a spinoff of the modelling procedure, we are able to deduce that the interannual dependence of the NAO mostly affects the positive phase and that timescales of one to three weeks are more dominant for the negative phase. The statistical properties of the model makes it useful for the generation of realistic climate noise.
How to cite: Hannachi, A., Önskog, T., and Franzke, C.: Nonlinear time series models for the North Atlantic Oscillation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13481, https://doi.org/10.5194/egusphere-egu2020-13481, 2020.
EGU2020-8544 | Displays | NP2.1
Understanding long-term persistence and multifractal behaviors in river runoff: A detailed study over ChinaNaiming Yuan, Wenlu Wu, Fenghua Xie, and Yanjun Qi
Long-term persistence (LTP) and multifractality in river runoff fluctuations have been well recognized over the recent decades, but the origins of these characteristics are still under debate. In this study, runoff and precipitation data from China are analyzed using detrended fluctuation analysis (DFA) and its generalized version, multifractal detrended fluctuation analysis (MF-DFA). By comparing the results between runoff and the nearby precipitation data, we find the multifractal behaviors in river runoff may be propagated from the nearby precipitation data, but the LTP is not inherited from precipitation. The LTP in river runoff may arise from the spatial aggregation effect, as it is closely related with the catchment area, especially for stations with large catchment areas. These findings are based on data from China, which was not analyzed systematically due to the poor data availability. Since the existence of LTP and multifractality makes the runoff change not completely random, one should further introduce these characteristics into hydrological models, for improved water managements and better estimations of hazard risks.
How to cite: Yuan, N., Wu, W., Xie, F., and Qi, Y.: Understanding long-term persistence and multifractal behaviors in river runoff: A detailed study over China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8544, https://doi.org/10.5194/egusphere-egu2020-8544, 2020.
Long-term persistence (LTP) and multifractality in river runoff fluctuations have been well recognized over the recent decades, but the origins of these characteristics are still under debate. In this study, runoff and precipitation data from China are analyzed using detrended fluctuation analysis (DFA) and its generalized version, multifractal detrended fluctuation analysis (MF-DFA). By comparing the results between runoff and the nearby precipitation data, we find the multifractal behaviors in river runoff may be propagated from the nearby precipitation data, but the LTP is not inherited from precipitation. The LTP in river runoff may arise from the spatial aggregation effect, as it is closely related with the catchment area, especially for stations with large catchment areas. These findings are based on data from China, which was not analyzed systematically due to the poor data availability. Since the existence of LTP and multifractality makes the runoff change not completely random, one should further introduce these characteristics into hydrological models, for improved water managements and better estimations of hazard risks.
How to cite: Yuan, N., Wu, W., Xie, F., and Qi, Y.: Understanding long-term persistence and multifractal behaviors in river runoff: A detailed study over China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8544, https://doi.org/10.5194/egusphere-egu2020-8544, 2020.
EGU2020-10741 | Displays | NP2.1
Stochastic modeling of extreme El-Niño and La Niña events by nonlinearly coupled oscillatorsCarlos Pires and Abdel Hannachi
The El-Niño index behaves as a nonlinear and non-Gaussian stochastic process. A well-known characteristic is its positive skewness coming from the occurrence of stronger episodes of El-Niño than of La Niña. Here, we use the period 1870-2018 of the standardized El-Niño index x(t), sampled in trimesters to analyze the spectral origin of the bicorrelation: sk(t1,t2)=E[x(t)x(t+t1)x(t+t2)] and skewness sk(0,0). For that, we estimate the two-dimensional Fourier transform of sk(t1,t2) or bispectrum B(f1,f2). Its sum over bi-frequencies (f1,f2) equals the skewness (0.45 in our case). Positive and negative bispectrum peaks are due to phase locking of frequency triplets: (f1,f2,f1+f2), contributing to extreme El-Niños and La Niñas respectively. Moreover, the most significant positive and/or negative bispectrum regions are rather well localized in the bispectrum domain. Here, we propose a partition of the El Niño signal into a set of band-pass spectrally separated components whose self and cross interactions can explain the broad structure of bispectrum. In the simplest case where the signal is decomposed into a fast and a slow component (with a cutoff frequency of (1/2.56) cycles/yr.), we verifty that slow-slow interactions (or phase locking) explain most of La-Niñas, particularly at the frequency triplet (1/4.9, 1/15 and 1/3.7 cycles/yr) whereas the fast-slow interactions explain most of El Niños, particularly at the frequency triplet (1/4.9, 1/4.9 and 1/2.5 cycles/yr). In order to simulate this stochastic behavior, we calibrate a set of nonlinearly coupled oscillators (Auto-regressive processes, forced by self and cross quadratic component terms), one for each component. In the case of weak cross-component interactions, and thus weak nonlinearity, the coupling coefficients between spectral-band components are proportional to the corresponding cross-skewnesses, which represent good first guesses in the calibration of the model parameters. The predictability of the model is then assessed, in particular for the anticipation of big El Niños and la Niñas. The authors would like to acknowledge the financial support FCT through project UIDB/50019/2020 – IDL.
How to cite: Pires, C. and Hannachi, A.: Stochastic modeling of extreme El-Niño and La Niña events by nonlinearly coupled oscillators, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10741, https://doi.org/10.5194/egusphere-egu2020-10741, 2020.
The El-Niño index behaves as a nonlinear and non-Gaussian stochastic process. A well-known characteristic is its positive skewness coming from the occurrence of stronger episodes of El-Niño than of La Niña. Here, we use the period 1870-2018 of the standardized El-Niño index x(t), sampled in trimesters to analyze the spectral origin of the bicorrelation: sk(t1,t2)=E[x(t)x(t+t1)x(t+t2)] and skewness sk(0,0). For that, we estimate the two-dimensional Fourier transform of sk(t1,t2) or bispectrum B(f1,f2). Its sum over bi-frequencies (f1,f2) equals the skewness (0.45 in our case). Positive and negative bispectrum peaks are due to phase locking of frequency triplets: (f1,f2,f1+f2), contributing to extreme El-Niños and La Niñas respectively. Moreover, the most significant positive and/or negative bispectrum regions are rather well localized in the bispectrum domain. Here, we propose a partition of the El Niño signal into a set of band-pass spectrally separated components whose self and cross interactions can explain the broad structure of bispectrum. In the simplest case where the signal is decomposed into a fast and a slow component (with a cutoff frequency of (1/2.56) cycles/yr.), we verifty that slow-slow interactions (or phase locking) explain most of La-Niñas, particularly at the frequency triplet (1/4.9, 1/15 and 1/3.7 cycles/yr) whereas the fast-slow interactions explain most of El Niños, particularly at the frequency triplet (1/4.9, 1/4.9 and 1/2.5 cycles/yr). In order to simulate this stochastic behavior, we calibrate a set of nonlinearly coupled oscillators (Auto-regressive processes, forced by self and cross quadratic component terms), one for each component. In the case of weak cross-component interactions, and thus weak nonlinearity, the coupling coefficients between spectral-band components are proportional to the corresponding cross-skewnesses, which represent good first guesses in the calibration of the model parameters. The predictability of the model is then assessed, in particular for the anticipation of big El Niños and la Niñas. The authors would like to acknowledge the financial support FCT through project UIDB/50019/2020 – IDL.
How to cite: Pires, C. and Hannachi, A.: Stochastic modeling of extreme El-Niño and La Niña events by nonlinearly coupled oscillators, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10741, https://doi.org/10.5194/egusphere-egu2020-10741, 2020.
EGU2020-12542 | Displays | NP2.1
Impact of the November Eurasian teleconnection on the following January Arctic OscillationShaobo Qiao
Using observations and model simulations, the impact of the November Eurasian (EU) teleconnection on the following January Arctic Oscillation (Arctic Oscillation) and the possible mechanisms are investigated in this study. We found that the positive (negative) phase of the November EU pattern favors the negative (positive) phase of AO during the subsequent January, and both the stratosphere-troposphere interactionsand the tropospheric Blocking High (BH) activity anomalies over the Euro-Atlantic sector play an important role in their connections. When the EU pattern is positive (negative) phase in November, the increased (decreased) vertical wave activity over Eurasia and North Atlantic gradually weakens (enhances) the Stratospheric polar vortex (SPV)from November to the following early January, which is then conducive to a downward propagation of positive height anomalies from the stratosphere to troposphere. On the other hand, due to the persistent stronger (weaker) and southward (northward) shifted storm tracks over the Euro-Atlantic sector from November to the following early January, the BH activities over this region are significantly decreased (increased) during the same period, whichthen contributesto positive (negative) height anomalies over the Arctic via the propagation of a zonal wave number 1-3. As both the SPVand BHanomalies over the Euro-Atlantic sector reach the maximum around the late December-early January, the resultant equivalent barotropic AO dipole patterndevelops and finally establishes during the following January.These results are useful for the predictability of the middle winter climate
How to cite: Qiao, S.: Impact of the November Eurasian teleconnection on the following January Arctic Oscillation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12542, https://doi.org/10.5194/egusphere-egu2020-12542, 2020.
Using observations and model simulations, the impact of the November Eurasian (EU) teleconnection on the following January Arctic Oscillation (Arctic Oscillation) and the possible mechanisms are investigated in this study. We found that the positive (negative) phase of the November EU pattern favors the negative (positive) phase of AO during the subsequent January, and both the stratosphere-troposphere interactionsand the tropospheric Blocking High (BH) activity anomalies over the Euro-Atlantic sector play an important role in their connections. When the EU pattern is positive (negative) phase in November, the increased (decreased) vertical wave activity over Eurasia and North Atlantic gradually weakens (enhances) the Stratospheric polar vortex (SPV)from November to the following early January, which is then conducive to a downward propagation of positive height anomalies from the stratosphere to troposphere. On the other hand, due to the persistent stronger (weaker) and southward (northward) shifted storm tracks over the Euro-Atlantic sector from November to the following early January, the BH activities over this region are significantly decreased (increased) during the same period, whichthen contributesto positive (negative) height anomalies over the Arctic via the propagation of a zonal wave number 1-3. As both the SPVand BHanomalies over the Euro-Atlantic sector reach the maximum around the late December-early January, the resultant equivalent barotropic AO dipole patterndevelops and finally establishes during the following January.These results are useful for the predictability of the middle winter climate
How to cite: Qiao, S.: Impact of the November Eurasian teleconnection on the following January Arctic Oscillation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12542, https://doi.org/10.5194/egusphere-egu2020-12542, 2020.
EGU2020-13084 | Displays | NP2.1
Predictability of the Wintertime 500 hPa Geopotential Height over Ural-Siberia in the NCEP Climate Forecast SystemMeng Zou
Using hindcast and forecastdata from the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2)for the period 1982-2017, we comprehensively assess the predictability of the climatology, interannual variability, and dominant modes of the wintertime 500 hPa geopotential height over Ural-Siberia (40-80°Nand 30-100°E). Although the climatic mean 500 hPa heightover Ural-Siberia simulated by NCEP CFSv2has a negative bias, especially over the eastern part of the region, NCEP CFSv2 well predicts the spatial distribution of the two major modes(EOF1 and EOF2) over this region 2 months in advance.The forecasting skill of the principal component (PC) of the two major modes,PC1 (PC2), is highest1 (0) month in advance, where the linear correlation coefficient between the predicted and observed time series reaches +0.36 (+0.67), exceeding the 95% confidence level. Conversely, the forecasting skill of PC1 (PC2) is very low 0 (1) month in advance. The main reason for the poorer(better) prediction of PC1 0 (1) month in advance is associated with a less (more) accurate response of the Eurasian teleconnection to SST anomalies over the southwestern Atlantic. For PC2, the better (poorer) prediction of PC2 0 (1) month in advance may be due to more (less) accurate responses of the stratospheric polar vortex and the Scandinavian teleconnection to the dipole SST anomalies over the North Pacific. These results are useful for evaluating the predictability of the East Asian winter climate.
How to cite: Zou, M.: Predictability of the Wintertime 500 hPa Geopotential Height over Ural-Siberia in the NCEP Climate Forecast System, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13084, https://doi.org/10.5194/egusphere-egu2020-13084, 2020.
Using hindcast and forecastdata from the National Centers for Environmental Prediction (NCEP) Climate Forecast System version 2 (CFSv2)for the period 1982-2017, we comprehensively assess the predictability of the climatology, interannual variability, and dominant modes of the wintertime 500 hPa geopotential height over Ural-Siberia (40-80°Nand 30-100°E). Although the climatic mean 500 hPa heightover Ural-Siberia simulated by NCEP CFSv2has a negative bias, especially over the eastern part of the region, NCEP CFSv2 well predicts the spatial distribution of the two major modes(EOF1 and EOF2) over this region 2 months in advance.The forecasting skill of the principal component (PC) of the two major modes,PC1 (PC2), is highest1 (0) month in advance, where the linear correlation coefficient between the predicted and observed time series reaches +0.36 (+0.67), exceeding the 95% confidence level. Conversely, the forecasting skill of PC1 (PC2) is very low 0 (1) month in advance. The main reason for the poorer(better) prediction of PC1 0 (1) month in advance is associated with a less (more) accurate response of the Eurasian teleconnection to SST anomalies over the southwestern Atlantic. For PC2, the better (poorer) prediction of PC2 0 (1) month in advance may be due to more (less) accurate responses of the stratospheric polar vortex and the Scandinavian teleconnection to the dipole SST anomalies over the North Pacific. These results are useful for evaluating the predictability of the East Asian winter climate.
How to cite: Zou, M.: Predictability of the Wintertime 500 hPa Geopotential Height over Ural-Siberia in the NCEP Climate Forecast System, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13084, https://doi.org/10.5194/egusphere-egu2020-13084, 2020.
EGU2020-20698 | Displays | NP2.1
Intraseasonal temperature variability features in Northern Eurasia regions under changing climateMaria Parfenova and Igor I. Mokhov
The estimations of various factors influence on weather regimes formation in Russian regions in transitional (spring, fall) seasons are presented. Changes in those regimes comparing to the middle of 20th century are analyzed, considering atmospheric circulation features under the changes in meridional heat transfer and Rossby waves stationary modes. Using long-term observations of surface air temperature from several locations across Russia, the multimodal features of the probability density functions (PDF) in several decades of 20th and 21st centuries are identified. Focusing on surface temperature anomalies in transitional seasons, we examine the connection between the multimodal features of their PDFs and the nonlinear dependence of surface albedo on temperature during the formation and melting of snow cover. We investigate the impacts of other mechanisms that can facilitate these features, including blocking of zonal atmospheric transport in middle latitudes and formation of blocking anticyclones (blockings) and stationary Rossby waves.
How to cite: Parfenova, M. and Mokhov, I. I.: Intraseasonal temperature variability features in Northern Eurasia regions under changing climate, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20698, https://doi.org/10.5194/egusphere-egu2020-20698, 2020.
The estimations of various factors influence on weather regimes formation in Russian regions in transitional (spring, fall) seasons are presented. Changes in those regimes comparing to the middle of 20th century are analyzed, considering atmospheric circulation features under the changes in meridional heat transfer and Rossby waves stationary modes. Using long-term observations of surface air temperature from several locations across Russia, the multimodal features of the probability density functions (PDF) in several decades of 20th and 21st centuries are identified. Focusing on surface temperature anomalies in transitional seasons, we examine the connection between the multimodal features of their PDFs and the nonlinear dependence of surface albedo on temperature during the formation and melting of snow cover. We investigate the impacts of other mechanisms that can facilitate these features, including blocking of zonal atmospheric transport in middle latitudes and formation of blocking anticyclones (blockings) and stationary Rossby waves.
How to cite: Parfenova, M. and Mokhov, I. I.: Intraseasonal temperature variability features in Northern Eurasia regions under changing climate, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20698, https://doi.org/10.5194/egusphere-egu2020-20698, 2020.
EGU2020-22546 | Displays | NP2.1
Non-linear, long-term evolution of sea surface temperature across the World OceanBenjamin Martinez-Lopez
Sea surface temperature (SST) is the only oceanic parameter on which depend heat fluxes between ocean and atmosphere and, therefore, SST is one of the key factors that influence climate and its variability. Over the twentieth century, SSTs have significantly increased around the global ocean, warming that has been attributed to anthropogenic climate change, although it is not yet clear how much of it is related to natural causes and how much is due to human activities. A considerable part of available literature regarding climate change has been built based on the global or hemispheric analysis of surface temperature trends. There are, however, some key open questions that need to be answered and for this task estimates of long-term SST trend patterns represent a source of valuable information. Unfortunately, long-term SST trend patterns have large uncertainties and although SST constitutes one of the most-measured ocean variables of our historic records, their poor spatial and temporal sampling, as well as inhomogeneous measurements technics, hinder an accurate determination of long-term SST trends, which increases their uncertainty and, therefore, limit their physical interpretation as well as their use in the verification of climate simulations.
Most of the long-term SST trend patterns have been built using linear techniques, which are very usefull when they are used to extract information of measurements satisfying two key assumptions: linearity and stationarity. The global warming resulting of our economic activities, however, affect the state of the World Ocean and the atmosphere inducing changes in the climate that may result in oscillatory modes of variability of different frequencies, which may undergo non-stationary and non-linear evolutions. In this work, we construct long-term SST trend patterns by using non-linear techniques to extract non-linear, long-term trends in each grid-point of two available global SST datasets: the National Oceanic and Atmospheric Administration Extended Reconstructed SST (ERSST) and from the Hadley Centre sea ice and SST (HadISST). The used non-linear technique makes a good job even if the SST data are non-linear and non-stationary. Additionally, the nonlinearity of the extracted trends allows the use of the first and second derivative to get more information about the global, long-term evolution of the SST fields, favoring thus a deeper understanding and interpretation of the observed changes in SST. Particularly, our results clearly show, in both ERSST and HadISST datasets, the non-uniform warming observed in the tropical Pacific, which seems to be related to the enhanced vertical heat flux in the eastern equatorial Pacific and the strengthening of the warm pool in the western Pacific. By using the second derivative of the nonlinear SST trends, emerges an interesting pattern delimiting several zones in the Pacific Ocean which have been responded in a different way to the impose warming of the last century.
How to cite: Martinez-Lopez, B.: Non-linear, long-term evolution of sea surface temperature across the World Ocean, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22546, https://doi.org/10.5194/egusphere-egu2020-22546, 2020.
Sea surface temperature (SST) is the only oceanic parameter on which depend heat fluxes between ocean and atmosphere and, therefore, SST is one of the key factors that influence climate and its variability. Over the twentieth century, SSTs have significantly increased around the global ocean, warming that has been attributed to anthropogenic climate change, although it is not yet clear how much of it is related to natural causes and how much is due to human activities. A considerable part of available literature regarding climate change has been built based on the global or hemispheric analysis of surface temperature trends. There are, however, some key open questions that need to be answered and for this task estimates of long-term SST trend patterns represent a source of valuable information. Unfortunately, long-term SST trend patterns have large uncertainties and although SST constitutes one of the most-measured ocean variables of our historic records, their poor spatial and temporal sampling, as well as inhomogeneous measurements technics, hinder an accurate determination of long-term SST trends, which increases their uncertainty and, therefore, limit their physical interpretation as well as their use in the verification of climate simulations.
Most of the long-term SST trend patterns have been built using linear techniques, which are very usefull when they are used to extract information of measurements satisfying two key assumptions: linearity and stationarity. The global warming resulting of our economic activities, however, affect the state of the World Ocean and the atmosphere inducing changes in the climate that may result in oscillatory modes of variability of different frequencies, which may undergo non-stationary and non-linear evolutions. In this work, we construct long-term SST trend patterns by using non-linear techniques to extract non-linear, long-term trends in each grid-point of two available global SST datasets: the National Oceanic and Atmospheric Administration Extended Reconstructed SST (ERSST) and from the Hadley Centre sea ice and SST (HadISST). The used non-linear technique makes a good job even if the SST data are non-linear and non-stationary. Additionally, the nonlinearity of the extracted trends allows the use of the first and second derivative to get more information about the global, long-term evolution of the SST fields, favoring thus a deeper understanding and interpretation of the observed changes in SST. Particularly, our results clearly show, in both ERSST and HadISST datasets, the non-uniform warming observed in the tropical Pacific, which seems to be related to the enhanced vertical heat flux in the eastern equatorial Pacific and the strengthening of the warm pool in the western Pacific. By using the second derivative of the nonlinear SST trends, emerges an interesting pattern delimiting several zones in the Pacific Ocean which have been responded in a different way to the impose warming of the last century.
How to cite: Martinez-Lopez, B.: Non-linear, long-term evolution of sea surface temperature across the World Ocean, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22546, https://doi.org/10.5194/egusphere-egu2020-22546, 2020.
NP2.3 – Extremes in Geophysical Sciences: Dynamics, Thermodynamics and Impacts
EGU2020-21105 | Displays | NP2.3
Cross-timescale interference and predictability of extremes: a chimera?Ángel G. Muñoz
Cross-timescale interference involves linear and non-linear interactions between climate modes acting at multiple timescales (Muñoz et al., 2015, 2016, 2017; Robertson et al., 2015; Moron et al., 2015), and that are related to windows of opportunity for enhanced predictive skill (Mariotti et al., 2020), with relevant societal impacts (e.g., Doss-Gollin et al., 2018; Anderson et al., 2020). Using a simple mathematical model, reanalysis data and gridded observations, here we analyze plausible mechanisms for cross-timescale interference, describing conditions for coupling of oscillating modes and its impact on extreme rainfall occurrence and predictive skill. Concrete examples for Northeast North America and southern South America are discussed, as well as implications for climate model diagnostics.
How to cite: Muñoz, Á. G.: Cross-timescale interference and predictability of extremes: a chimera?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21105, https://doi.org/10.5194/egusphere-egu2020-21105, 2020.
Cross-timescale interference involves linear and non-linear interactions between climate modes acting at multiple timescales (Muñoz et al., 2015, 2016, 2017; Robertson et al., 2015; Moron et al., 2015), and that are related to windows of opportunity for enhanced predictive skill (Mariotti et al., 2020), with relevant societal impacts (e.g., Doss-Gollin et al., 2018; Anderson et al., 2020). Using a simple mathematical model, reanalysis data and gridded observations, here we analyze plausible mechanisms for cross-timescale interference, describing conditions for coupling of oscillating modes and its impact on extreme rainfall occurrence and predictive skill. Concrete examples for Northeast North America and southern South America are discussed, as well as implications for climate model diagnostics.
How to cite: Muñoz, Á. G.: Cross-timescale interference and predictability of extremes: a chimera?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21105, https://doi.org/10.5194/egusphere-egu2020-21105, 2020.
EGU2020-3062 | Displays | NP2.3
Interannual-to-decadal variability of the Kuroshio extension: Analyzing an ensemble of global hindcasts from a Dynamical System viewpoint.Giusy Fedele, Thierry Penduff, Stefano Pierini, M. Carmen Alvarez-Castro, Alessio Bellucci, and Simona Masina
The Kuroshio Extension (KE) is the inertial meandering jet formed by the convergence of the Kuroshio and Oyashio currents in the Northern Pacific. It is widely mentioned in the literature that the KE variability is bimodal on the decadal time scale. The nature of this low frequency variability (LFV) is still under debate; some authors suggest that internal oceanic mechanisms play a fundamental role in the phenomenon but there is also evidence from the observations that the KE LFV is connected with changes in broader patterns of variability such as the Pacific Decadal Oscillation.
We first inspect the interplay between the ocean and the atmosphere in the KE by taking advantage of the OCCIPUT 1/4° model dataset: it consists in an ensemble of 50 global ocean–sea-ice hindcasts performed over the period 1960–2015 (hereafter OCCITENS), and in a one-member 330-yr climatological simulation (hereafter OCCICLIM). In this context, OCCITENS simulates both the intrinsic and forced variability and allows for their separation via ensemble statistics, while OCCICLIM simulates the "pure" intrinsic variability of the jet. We then explore some features of the KE dynamical system attractor in the quasi-autonomous (OCCICLIM) and nonautonomous (OCCITENS) regimes: we thus assess the KE predictability in the OCCIPUT dataset in order to better understand the ocean-atmosphere interactions and the source of the associated predictability.
Our analyses show that both oceanic and atmospheric drivers control the KE LFV variability. In this framework, the results suggest that the jet oscillates between the two intrinsic oceanic modes with transitions triggered by the atmosphere.
How to cite: Fedele, G., Penduff, T., Pierini, S., Alvarez-Castro, M. C., Bellucci, A., and Masina, S.: Interannual-to-decadal variability of the Kuroshio extension: Analyzing an ensemble of global hindcasts from a Dynamical System viewpoint., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3062, https://doi.org/10.5194/egusphere-egu2020-3062, 2020.
The Kuroshio Extension (KE) is the inertial meandering jet formed by the convergence of the Kuroshio and Oyashio currents in the Northern Pacific. It is widely mentioned in the literature that the KE variability is bimodal on the decadal time scale. The nature of this low frequency variability (LFV) is still under debate; some authors suggest that internal oceanic mechanisms play a fundamental role in the phenomenon but there is also evidence from the observations that the KE LFV is connected with changes in broader patterns of variability such as the Pacific Decadal Oscillation.
We first inspect the interplay between the ocean and the atmosphere in the KE by taking advantage of the OCCIPUT 1/4° model dataset: it consists in an ensemble of 50 global ocean–sea-ice hindcasts performed over the period 1960–2015 (hereafter OCCITENS), and in a one-member 330-yr climatological simulation (hereafter OCCICLIM). In this context, OCCITENS simulates both the intrinsic and forced variability and allows for their separation via ensemble statistics, while OCCICLIM simulates the "pure" intrinsic variability of the jet. We then explore some features of the KE dynamical system attractor in the quasi-autonomous (OCCICLIM) and nonautonomous (OCCITENS) regimes: we thus assess the KE predictability in the OCCIPUT dataset in order to better understand the ocean-atmosphere interactions and the source of the associated predictability.
Our analyses show that both oceanic and atmospheric drivers control the KE LFV variability. In this framework, the results suggest that the jet oscillates between the two intrinsic oceanic modes with transitions triggered by the atmosphere.
How to cite: Fedele, G., Penduff, T., Pierini, S., Alvarez-Castro, M. C., Bellucci, A., and Masina, S.: Interannual-to-decadal variability of the Kuroshio extension: Analyzing an ensemble of global hindcasts from a Dynamical System viewpoint., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3062, https://doi.org/10.5194/egusphere-egu2020-3062, 2020.
EGU2020-17899 | Displays | NP2.3
Greatness from small beginnings: Impact of oceanic mesoscale on weather extremes and large-scale atmospheric circulation in midlatitudesJoakim Kjellsson, Wonsun Park, Torge Martin, Eric Maisonnave, and Mojib Latif
We study how mesoscale air-sea interactions over the North Atlantic can influence weather extremes, e.g. heavy precipitation and wind storms, and the overall atmospheric circulation both locally and downstream in the midlatitudes. We use a global coupled climate model with a high-resolution North Atlantic grid (dx ~ 8 km) and an atmosphere model resolution of either 125 km or 25 km. The high-resolution North Atlantic grid allows the model to resolve the current systems and SST fronts associated with e.g. the Gulf Stream and North Atlantic Current. As air-sea fluxes of momentum, heat and freshwater are calculated on the atmosphere grid, spatial variations in fluxes associated with sharp SST fronts are much better represented when using the high-resolution atmosphere then when using the low-resolution model.
Preliminary results show that coupling to the high-resolution (dx ~ 25 km) rather than low-resolution (dx ~ 125 km) atmosphere model increases the intensity and variance of surface heat and freshwater fluxes over eddy-rich regions such as the Gulf Stream. As a result, the high-resolution model simulates more intense heavy precipitation events over most of the North Atlantic Ocean. We also show that more frequent coupling between the atmosphere and ocean components increases the intensity of the air-sea fluxes, in particular wind stress, which has a large impact on the ocean. More intense air-sea fluxes can provide more energy for cyclogenesis and we will discuss how the oceanic mesoscale, in particular in the eddy-rich regions, can alter the storm tracks and jet stream to influence extreme weather and the climate over Europe.
The coupled model comprises NEMO 3.6/LIM2 ocean and OpenIFS 40r1 atmosphere, and works by allowing the global OpenIFS model to send and receive fields from both a global coarse-resolution ocean grid and a refined grid over the North Atlantic grid via the OASIS3-MCT4 coupler. The ability to run these simulations is a very recent development and we will give a brief overview of the coupled modelling system and benefits of using regional grid refinement in coupled models.
How to cite: Kjellsson, J., Park, W., Martin, T., Maisonnave, E., and Latif, M.: Greatness from small beginnings: Impact of oceanic mesoscale on weather extremes and large-scale atmospheric circulation in midlatitudes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17899, https://doi.org/10.5194/egusphere-egu2020-17899, 2020.
We study how mesoscale air-sea interactions over the North Atlantic can influence weather extremes, e.g. heavy precipitation and wind storms, and the overall atmospheric circulation both locally and downstream in the midlatitudes. We use a global coupled climate model with a high-resolution North Atlantic grid (dx ~ 8 km) and an atmosphere model resolution of either 125 km or 25 km. The high-resolution North Atlantic grid allows the model to resolve the current systems and SST fronts associated with e.g. the Gulf Stream and North Atlantic Current. As air-sea fluxes of momentum, heat and freshwater are calculated on the atmosphere grid, spatial variations in fluxes associated with sharp SST fronts are much better represented when using the high-resolution atmosphere then when using the low-resolution model.
Preliminary results show that coupling to the high-resolution (dx ~ 25 km) rather than low-resolution (dx ~ 125 km) atmosphere model increases the intensity and variance of surface heat and freshwater fluxes over eddy-rich regions such as the Gulf Stream. As a result, the high-resolution model simulates more intense heavy precipitation events over most of the North Atlantic Ocean. We also show that more frequent coupling between the atmosphere and ocean components increases the intensity of the air-sea fluxes, in particular wind stress, which has a large impact on the ocean. More intense air-sea fluxes can provide more energy for cyclogenesis and we will discuss how the oceanic mesoscale, in particular in the eddy-rich regions, can alter the storm tracks and jet stream to influence extreme weather and the climate over Europe.
The coupled model comprises NEMO 3.6/LIM2 ocean and OpenIFS 40r1 atmosphere, and works by allowing the global OpenIFS model to send and receive fields from both a global coarse-resolution ocean grid and a refined grid over the North Atlantic grid via the OASIS3-MCT4 coupler. The ability to run these simulations is a very recent development and we will give a brief overview of the coupled modelling system and benefits of using regional grid refinement in coupled models.
How to cite: Kjellsson, J., Park, W., Martin, T., Maisonnave, E., and Latif, M.: Greatness from small beginnings: Impact of oceanic mesoscale on weather extremes and large-scale atmospheric circulation in midlatitudes, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17899, https://doi.org/10.5194/egusphere-egu2020-17899, 2020.
EGU2020-13802 | Displays | NP2.3
Storylines of the 2018 Northern Hemisphere heat wave at pre-industrial and higher global warming levelsKathrin Wehrli, Mathias Hauser, and Sonia I. Seneviratne
The 2018 summer was unusually hot in large areas of the Northern Hemisphere and simultaneous heat waves on three continents led to major impacts to agriculture and society. The event was driven by the anomalous atmospheric circulation pattern during that summer and it was only possible in a climate with global warming. There are indications that in a future, warmer climate similar events might occur regularly, affecting major ‘breadbasket’ regions of the Northern Hemisphere.
This study aims to understand the role of climate change for driving the intensity of the 2018 summer and to explore the sensitivity to changing warming levels. Model simulations are performed using the Community Earth System Model to investigate storylines for the extreme 2018 summer given the observed atmospheric large-scale circulation but different levels of background global warming: no human imprint, the 2018 conditions, and different mean global warming levels (1.5°C, 2°C, 3°C, and 4°C). The storylines explore the consequences of the event in an alternative warmer or colder world and thus help to increase our understanding of the drivers involved. The results reveal a strong contribution by the present-day level of global warming and provide an outlook to similar events in a possible future climate.
How to cite: Wehrli, K., Hauser, M., and Seneviratne, S. I.: Storylines of the 2018 Northern Hemisphere heat wave at pre-industrial and higher global warming levels, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13802, https://doi.org/10.5194/egusphere-egu2020-13802, 2020.
The 2018 summer was unusually hot in large areas of the Northern Hemisphere and simultaneous heat waves on three continents led to major impacts to agriculture and society. The event was driven by the anomalous atmospheric circulation pattern during that summer and it was only possible in a climate with global warming. There are indications that in a future, warmer climate similar events might occur regularly, affecting major ‘breadbasket’ regions of the Northern Hemisphere.
This study aims to understand the role of climate change for driving the intensity of the 2018 summer and to explore the sensitivity to changing warming levels. Model simulations are performed using the Community Earth System Model to investigate storylines for the extreme 2018 summer given the observed atmospheric large-scale circulation but different levels of background global warming: no human imprint, the 2018 conditions, and different mean global warming levels (1.5°C, 2°C, 3°C, and 4°C). The storylines explore the consequences of the event in an alternative warmer or colder world and thus help to increase our understanding of the drivers involved. The results reveal a strong contribution by the present-day level of global warming and provide an outlook to similar events in a possible future climate.
How to cite: Wehrli, K., Hauser, M., and Seneviratne, S. I.: Storylines of the 2018 Northern Hemisphere heat wave at pre-industrial and higher global warming levels, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13802, https://doi.org/10.5194/egusphere-egu2020-13802, 2020.
EGU2020-6687 | Displays | NP2.3
Characterizing large-scale circulation triggering heavy precipitation amounts over the northern French AlpsAntoine Blanc, Juliette Blanchet, and Jean-Dominique Creutin
Large-scale circulations (LSCs) explain a significant part of Alpine precipitations. Characterizing circulations triggering heavy precipitation is usually done using weather-type classifications. A different characterization is implemented here, based on analogy using the atmospheric descriptors proposed in Blanchet et al 2018, 2019. These descriptors are both related to the dynamics of LSC and to their relative position in the atmospheric space. This work is applied to the Isère river catchment for the 1950-2011 period, considering a 3-day time step. The 500 hPa and 1000 hPa geopotential heights covering part of the western Europe are used separately to represent LSC. Two analogy criteria are investigated for constructing the atmospheric descriptors, namely TWS and RMSE.
Our results reveal that LSCs triggering heavy precipitation amounts correspond to strong geostrophic wind with quasi constant direction during the three days, corresponding to blocking situations in altitude. Moreover, those patterns of circulation are among the least singulars, and they show the highest degree of clustering in the atmospheric space. We interpret the latest results by the fact that heavy precipitation LSCs feature twin circulation patterns. In addition, the 500 hPa geopotential height appears to discriminate better heavy precipitation situations than the 1000 hPa one. Finally, our work points out the benefit of a combined use of TWS and RMSE. TWS gives information about the direction of geostrophic wind, while RMSE -combined with TWS- informs about its strength.
References:
Blanchet, J., Stalla, S., and Creutin, J.-D. (2018). Analogy of multi-day sequences of atmospheric circulation favoring large rainfall accumulation over the French Alps. Atmospheric Science Letters.
Blanchet, J., Creutin, J-D. (2019). Modelling rainfall accumulations over several days in the French Alps using low-dimensional atmospheric predictors based on analogy. Journal of Applied Meteorology and Climatology.
How to cite: Blanc, A., Blanchet, J., and Creutin, J.-D.: Characterizing large-scale circulation triggering heavy precipitation amounts over the northern French Alps, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6687, https://doi.org/10.5194/egusphere-egu2020-6687, 2020.
Large-scale circulations (LSCs) explain a significant part of Alpine precipitations. Characterizing circulations triggering heavy precipitation is usually done using weather-type classifications. A different characterization is implemented here, based on analogy using the atmospheric descriptors proposed in Blanchet et al 2018, 2019. These descriptors are both related to the dynamics of LSC and to their relative position in the atmospheric space. This work is applied to the Isère river catchment for the 1950-2011 period, considering a 3-day time step. The 500 hPa and 1000 hPa geopotential heights covering part of the western Europe are used separately to represent LSC. Two analogy criteria are investigated for constructing the atmospheric descriptors, namely TWS and RMSE.
Our results reveal that LSCs triggering heavy precipitation amounts correspond to strong geostrophic wind with quasi constant direction during the three days, corresponding to blocking situations in altitude. Moreover, those patterns of circulation are among the least singulars, and they show the highest degree of clustering in the atmospheric space. We interpret the latest results by the fact that heavy precipitation LSCs feature twin circulation patterns. In addition, the 500 hPa geopotential height appears to discriminate better heavy precipitation situations than the 1000 hPa one. Finally, our work points out the benefit of a combined use of TWS and RMSE. TWS gives information about the direction of geostrophic wind, while RMSE -combined with TWS- informs about its strength.
References:
Blanchet, J., Stalla, S., and Creutin, J.-D. (2018). Analogy of multi-day sequences of atmospheric circulation favoring large rainfall accumulation over the French Alps. Atmospheric Science Letters.
Blanchet, J., Creutin, J-D. (2019). Modelling rainfall accumulations over several days in the French Alps using low-dimensional atmospheric predictors based on analogy. Journal of Applied Meteorology and Climatology.
How to cite: Blanc, A., Blanchet, J., and Creutin, J.-D.: Characterizing large-scale circulation triggering heavy precipitation amounts over the northern French Alps, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6687, https://doi.org/10.5194/egusphere-egu2020-6687, 2020.
EGU2020-8990 | Displays | NP2.3
More perceived but not faster evolution of heat stress than temperature extremes in the futureAudrey Brouillet and Sylvie Joussaume
Global warming is projected to intensify during the 21st century. This warming will be more readily perceived by human populations if it occurs rapidly and if it induces a thermal heat stress on the human body. Yet, only few studies investigate how climate change could be felt by future populations. Here we assess this possible perceived evolution between 1959 and 2100 only combining thermodynamic and statistical indicators. We analyse extremes of temperature (T99) and simplified Wet-Bulb Globe Temperature (WBGT99), a common heat stress index assessing the combined effect of elevated temperature and humidity on the human body. For each year of the period, we define the speed of change as a difference between two successive 20-year periods (i.e. with a moving baseline), and assess how these running changes emerge from each last 20-y inter-annual variability.
According to a subset of 12 CMIP5 Earth System Models and the RCP8.5 scenario, the change of T99 and WBGT99 will be twice as fast in the future compared to the current speed of change in the mid-latitudes, and by up to four times faster tropical regions such as Amazonia. Warming accelerations are thus similar for both T99 and WBGT99. However, in tropical regions by 2080, the speed is projected to be 2.3 times larger than the recent inter-annual variability for WBGT99, and only 1.5 to 1.8 times larger for T99. Currently, speeds of change are only 0.2 to 0.8 times as large as the recent year-to-year variability for both metrics. We also show that 36% of the total world population will experience an emergent WBGT99 intensification in 2080, but only 15% of the population for T99. According to future projections, the accelerated warming of future heat extremes will be more felt by populations than current changes, and this perceived change will be more severe for WBGT99 than for T99, particularly in the tropics.
How to cite: Brouillet, A. and Joussaume, S.: More perceived but not faster evolution of heat stress than temperature extremes in the future, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8990, https://doi.org/10.5194/egusphere-egu2020-8990, 2020.
Global warming is projected to intensify during the 21st century. This warming will be more readily perceived by human populations if it occurs rapidly and if it induces a thermal heat stress on the human body. Yet, only few studies investigate how climate change could be felt by future populations. Here we assess this possible perceived evolution between 1959 and 2100 only combining thermodynamic and statistical indicators. We analyse extremes of temperature (T99) and simplified Wet-Bulb Globe Temperature (WBGT99), a common heat stress index assessing the combined effect of elevated temperature and humidity on the human body. For each year of the period, we define the speed of change as a difference between two successive 20-year periods (i.e. with a moving baseline), and assess how these running changes emerge from each last 20-y inter-annual variability.
According to a subset of 12 CMIP5 Earth System Models and the RCP8.5 scenario, the change of T99 and WBGT99 will be twice as fast in the future compared to the current speed of change in the mid-latitudes, and by up to four times faster tropical regions such as Amazonia. Warming accelerations are thus similar for both T99 and WBGT99. However, in tropical regions by 2080, the speed is projected to be 2.3 times larger than the recent inter-annual variability for WBGT99, and only 1.5 to 1.8 times larger for T99. Currently, speeds of change are only 0.2 to 0.8 times as large as the recent year-to-year variability for both metrics. We also show that 36% of the total world population will experience an emergent WBGT99 intensification in 2080, but only 15% of the population for T99. According to future projections, the accelerated warming of future heat extremes will be more felt by populations than current changes, and this perceived change will be more severe for WBGT99 than for T99, particularly in the tropics.
How to cite: Brouillet, A. and Joussaume, S.: More perceived but not faster evolution of heat stress than temperature extremes in the future, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8990, https://doi.org/10.5194/egusphere-egu2020-8990, 2020.
EGU2020-6177 | Displays | NP2.3
The influence of greenhouse gases on the 1930s Dust Bowl heat waves across central United StatesSabine Undorf, Tim Cowan, Gabi Hegerl, Luke Harrington, and Friederike Otto
The central United States experienced the hottest summers of the twentieth century in 1934 and 1936, with over 40 heat wave days and maximum temperatures surpassing 44°C at some locations like Kansas and Oklahoma. In fact, as of 2019, the summer of 1936 is still the hottest on record. The heat waves coincided with the decade-long Dust Bowl drought, that caused wide-spread crop failures, dust storms that penetrated to New York and considerable out-migration. In a very-large ensemble regional modelling framework, we show that greenhouse gas increases slightly enhanced the frequency and duration of the Dust Bowl heat waves, and would strongly enhance similar heat waves in the present day under current, further elevated greenhouse gas levels. Specifically, present-day atmospheric greenhouse gas forcing would reduce the return period of a rare (less than once in a century) heat wave summer as observed in 1936 to about 1-in 40-years, with further contribution by sea surface warming. Here, we show that a key driver of this elevated heat wave risk is the reduction in evaporative cooling and increase in sensible heating during dry springs and summers. Hence, we conclude that a warmer world is creating the potential for future extreme heat in moisture-limited regions, with potentially very damaging impacts.
How to cite: Undorf, S., Cowan, T., Hegerl, G., Harrington, L., and Otto, F.: The influence of greenhouse gases on the 1930s Dust Bowl heat waves across central United States, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6177, https://doi.org/10.5194/egusphere-egu2020-6177, 2020.
The central United States experienced the hottest summers of the twentieth century in 1934 and 1936, with over 40 heat wave days and maximum temperatures surpassing 44°C at some locations like Kansas and Oklahoma. In fact, as of 2019, the summer of 1936 is still the hottest on record. The heat waves coincided with the decade-long Dust Bowl drought, that caused wide-spread crop failures, dust storms that penetrated to New York and considerable out-migration. In a very-large ensemble regional modelling framework, we show that greenhouse gas increases slightly enhanced the frequency and duration of the Dust Bowl heat waves, and would strongly enhance similar heat waves in the present day under current, further elevated greenhouse gas levels. Specifically, present-day atmospheric greenhouse gas forcing would reduce the return period of a rare (less than once in a century) heat wave summer as observed in 1936 to about 1-in 40-years, with further contribution by sea surface warming. Here, we show that a key driver of this elevated heat wave risk is the reduction in evaporative cooling and increase in sensible heating during dry springs and summers. Hence, we conclude that a warmer world is creating the potential for future extreme heat in moisture-limited regions, with potentially very damaging impacts.
How to cite: Undorf, S., Cowan, T., Hegerl, G., Harrington, L., and Otto, F.: The influence of greenhouse gases on the 1930s Dust Bowl heat waves across central United States, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6177, https://doi.org/10.5194/egusphere-egu2020-6177, 2020.
EGU2020-4896 | Displays | NP2.3 | Highlight
Storyline approach to extreme event characterizationTheodore Shepherd
Extreme climate events are invariably highly nonlinear, complex events, resulting from the confluence of multiple causal factors, and often quite singular. In any complex system there is a tension between analysis methods that respect the singularity of the extreme events at the price of statistical repeatability, and those that emphasize statistical repeatability at the price of nonlinearity and complexity; this dichotomy is found across all areas of science. In the climate context, the ‘storyline’ approach has emerged in recent years as a way of following the first of these two pathways. I will discuss how the storyline approach can be cast within the mathematical framework of causal networks, which provides a way to bridge between the storyline and probabilistic approaches. This also provides a way to interpret data in an appropriately conditional manner, thereby aiding model-measurement comparison.
How to cite: Shepherd, T.: Storyline approach to extreme event characterization, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4896, https://doi.org/10.5194/egusphere-egu2020-4896, 2020.
Extreme climate events are invariably highly nonlinear, complex events, resulting from the confluence of multiple causal factors, and often quite singular. In any complex system there is a tension between analysis methods that respect the singularity of the extreme events at the price of statistical repeatability, and those that emphasize statistical repeatability at the price of nonlinearity and complexity; this dichotomy is found across all areas of science. In the climate context, the ‘storyline’ approach has emerged in recent years as a way of following the first of these two pathways. I will discuss how the storyline approach can be cast within the mathematical framework of causal networks, which provides a way to bridge between the storyline and probabilistic approaches. This also provides a way to interpret data in an appropriately conditional manner, thereby aiding model-measurement comparison.
How to cite: Shepherd, T.: Storyline approach to extreme event characterization, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4896, https://doi.org/10.5194/egusphere-egu2020-4896, 2020.
EGU2020-4441 | Displays | NP2.3
The substructure of extremely hot summers in the Northern HemisphereMatthias Röthlisberger, Michael Sprenger, Emmanouil Flaounas, Urs Beyerle, and Heini Wernli
In the last decades, extremely hot summers (hereafter extreme summers) have challenged societies worldwide through their adverse ecological, economic and public health effects. In this study, extreme summers are identified at all grid points in the Northern Hemisphere in the upper tail of the July–August (JJA) seasonal mean 2-meter temperature (T2m) distribution, separately in ERA-Interim reanalyses and in 700 simulated years with the Community Earth System Model (CESM) large ensemble for present-day climate conditions. A novel approach is introduced to characterize the substructure of extreme summers, i.e., to elucidate whether an extreme summer is mainly the result of the warmest days being anomalously hot, or of the coldest days being anomalously mild, or of a general shift towards warmer temperatures on all days of the season. Such a statistical characterization can be obtained from considering so-called rank day anomalies for each extreme summer, that is, by sorting the 92 daily mean T2m values of an extreme summer and by calculating, for every rank, the deviation from the climatological mean rank value of T2m.
Applying this method in the entire Northern Hemisphere reveals spatially strongly varying extreme summer substructures, which agree remarkably well in the reanalysis and climate model data sets. For example, in eastern India the hottest 30 days of an extreme summer contribute more than 70% to the total extreme summer T2m anomaly, while the colder days are close to climatology. In the high Arctic, however, extreme summers occur when the coldest 30 days are substantially warmer than climatology. Furthermore, in roughly half of the Northern Hemisphere land area, the coldest third of summer days contribute more to extreme summers than the hottest third, which highlights that milder than normal coldest summer days are a key ingredient of many extreme summers. In certain regions, e.g., over western Europe and western Russia, the substructure of different extreme summers shows large variability and no common characteristic substructure emerges. Furthermore, we show that the typical extreme summer substructure in a certain region is directly related to the region’s overall T2m rank day variability pattern. This indicates that in regions where the warmest summer days vary particularly strongly from one year to the other, these warmest days are also particularly anomalous in extreme summers (and analogously for regions where variability is largest for the coldest days). Finally, for three selected regions, thermodynamic and dynamical causes of extreme summer substructures are briefly discussed, indicating that, for instance, the onset of monsoons, physical boundaries like the sea ice edge, or the frequency of occurrence of Rossby wave breaking, strongly determine the substructure of extreme summers in certain regions.
How to cite: Röthlisberger, M., Sprenger, M., Flaounas, E., Beyerle, U., and Wernli, H.: The substructure of extremely hot summers in the Northern Hemisphere, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4441, https://doi.org/10.5194/egusphere-egu2020-4441, 2020.
In the last decades, extremely hot summers (hereafter extreme summers) have challenged societies worldwide through their adverse ecological, economic and public health effects. In this study, extreme summers are identified at all grid points in the Northern Hemisphere in the upper tail of the July–August (JJA) seasonal mean 2-meter temperature (T2m) distribution, separately in ERA-Interim reanalyses and in 700 simulated years with the Community Earth System Model (CESM) large ensemble for present-day climate conditions. A novel approach is introduced to characterize the substructure of extreme summers, i.e., to elucidate whether an extreme summer is mainly the result of the warmest days being anomalously hot, or of the coldest days being anomalously mild, or of a general shift towards warmer temperatures on all days of the season. Such a statistical characterization can be obtained from considering so-called rank day anomalies for each extreme summer, that is, by sorting the 92 daily mean T2m values of an extreme summer and by calculating, for every rank, the deviation from the climatological mean rank value of T2m.
Applying this method in the entire Northern Hemisphere reveals spatially strongly varying extreme summer substructures, which agree remarkably well in the reanalysis and climate model data sets. For example, in eastern India the hottest 30 days of an extreme summer contribute more than 70% to the total extreme summer T2m anomaly, while the colder days are close to climatology. In the high Arctic, however, extreme summers occur when the coldest 30 days are substantially warmer than climatology. Furthermore, in roughly half of the Northern Hemisphere land area, the coldest third of summer days contribute more to extreme summers than the hottest third, which highlights that milder than normal coldest summer days are a key ingredient of many extreme summers. In certain regions, e.g., over western Europe and western Russia, the substructure of different extreme summers shows large variability and no common characteristic substructure emerges. Furthermore, we show that the typical extreme summer substructure in a certain region is directly related to the region’s overall T2m rank day variability pattern. This indicates that in regions where the warmest summer days vary particularly strongly from one year to the other, these warmest days are also particularly anomalous in extreme summers (and analogously for regions where variability is largest for the coldest days). Finally, for three selected regions, thermodynamic and dynamical causes of extreme summer substructures are briefly discussed, indicating that, for instance, the onset of monsoons, physical boundaries like the sea ice edge, or the frequency of occurrence of Rossby wave breaking, strongly determine the substructure of extreme summers in certain regions.
How to cite: Röthlisberger, M., Sprenger, M., Flaounas, E., Beyerle, U., and Wernli, H.: The substructure of extremely hot summers in the Northern Hemisphere, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4441, https://doi.org/10.5194/egusphere-egu2020-4441, 2020.
EGU2020-5162 | Displays | NP2.3
From severe droughts in South America to marine heatwaves in the South AtlanticRegina Rodrigues, Andrea Taschetto, Alex Sen Gupta, and Gregory Foltz
In 2013/14 eastern South America experienced one of its worst droughts, leading to water shortages in São Paulo, the world’s fourth most populated city. This event was also responsible for a dengue fever outbreak that tripled the usual number of fatalities and reduced Brazilian coffee production leading to a global shortages and worldwide price increases. The drought was associated with an anomalous anticyclonic circulation off southeast South America that prevented synoptic systems reaching the region while inhibiting the development of the South Atlantic Convergence Zone and its associated rainfall. A concomitant and unprecedented marine heatwave also developed in the southwest Atlantic. Here we show from observations that such droughts and adjacent marine heatwaves have a common remote cause. Atmospheric blocking triggered by tropical convection in the Indian and Pacific oceans can cause persistent anticyclonic circulation that not only leads to severe drought but also generates marine heatwaves in the adjacent ocean. We show that increased shortwave radiation due to reduced cloud cover and reduced ocean heat loss from weaker winds are the main contributors to the establishment of marine heatwaves in the region. The proposed mechanism, which involves droughts, extreme air temperature over land and atmospheric blocking explains approximately 60% of the marine heatwave events in the western South Atlantic. We also identified an increase in frequency, duration, intensity and extension of marine heatwave events over the satellite period 1982–2016. Moreover, surface primary production was reduced during these events with implications for regional fisheries.
How to cite: Rodrigues, R., Taschetto, A., Sen Gupta, A., and Foltz, G.: From severe droughts in South America to marine heatwaves in the South Atlantic, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5162, https://doi.org/10.5194/egusphere-egu2020-5162, 2020.
In 2013/14 eastern South America experienced one of its worst droughts, leading to water shortages in São Paulo, the world’s fourth most populated city. This event was also responsible for a dengue fever outbreak that tripled the usual number of fatalities and reduced Brazilian coffee production leading to a global shortages and worldwide price increases. The drought was associated with an anomalous anticyclonic circulation off southeast South America that prevented synoptic systems reaching the region while inhibiting the development of the South Atlantic Convergence Zone and its associated rainfall. A concomitant and unprecedented marine heatwave also developed in the southwest Atlantic. Here we show from observations that such droughts and adjacent marine heatwaves have a common remote cause. Atmospheric blocking triggered by tropical convection in the Indian and Pacific oceans can cause persistent anticyclonic circulation that not only leads to severe drought but also generates marine heatwaves in the adjacent ocean. We show that increased shortwave radiation due to reduced cloud cover and reduced ocean heat loss from weaker winds are the main contributors to the establishment of marine heatwaves in the region. The proposed mechanism, which involves droughts, extreme air temperature over land and atmospheric blocking explains approximately 60% of the marine heatwave events in the western South Atlantic. We also identified an increase in frequency, duration, intensity and extension of marine heatwave events over the satellite period 1982–2016. Moreover, surface primary production was reduced during these events with implications for regional fisheries.
How to cite: Rodrigues, R., Taschetto, A., Sen Gupta, A., and Foltz, G.: From severe droughts in South America to marine heatwaves in the South Atlantic, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5162, https://doi.org/10.5194/egusphere-egu2020-5162, 2020.
EGU2020-8636 | Displays | NP2.3
The role of spatial and temporal model resolution in a flood event storyline approach in Western NorwayNathalie Schaller, Jana Sillmann, Malte Müller, Reindert Haarsma, Wilco Hazeleger, Trine Jahr Hegdahl, Timo Kelder, Gijs van den Oord, Albrecht Weerts, and Kirien Whan
A physical climate storyline approach is applied to an autumn flood event caused by an atmospheric river in the West Coast of Norway. The aim is to demonstrate the value and challenges of higher spatial and temporal resolution in simulating impacts. The modelling chain used is the same as the one used operationally, to issue flood warnings for example. Its output is therefore familiar to many users, which we expect will facilitate stakeholder engagement. Two different versions of a hydrological model are run to show that on the one hand, the higher spatial resolution between the global and regional model is necessary to realistically simulate the high spatial variability of precipitation in such a mountainous region. On the other hand we also show that the intensity of the peak streamflow is only captured realistically with hourly data. The higher resolution regional atmospheric model is able to simulate the fact that with the passage of an atmospheric river, some valleys receive high amounts of precipitation and others not. However, the coarser resolution global model shows uniform precipitation in the whole region. Translating the event into the future leads to similar results: while in some catchments, a future flood might be 50% larger than a present one, in others no event occurs because the atmospheric river does not hit that catchment.
How to cite: Schaller, N., Sillmann, J., Müller, M., Haarsma, R., Hazeleger, W., Jahr Hegdahl, T., Kelder, T., van den Oord, G., Weerts, A., and Whan, K.: The role of spatial and temporal model resolution in a flood event storyline approach in Western Norway, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8636, https://doi.org/10.5194/egusphere-egu2020-8636, 2020.
A physical climate storyline approach is applied to an autumn flood event caused by an atmospheric river in the West Coast of Norway. The aim is to demonstrate the value and challenges of higher spatial and temporal resolution in simulating impacts. The modelling chain used is the same as the one used operationally, to issue flood warnings for example. Its output is therefore familiar to many users, which we expect will facilitate stakeholder engagement. Two different versions of a hydrological model are run to show that on the one hand, the higher spatial resolution between the global and regional model is necessary to realistically simulate the high spatial variability of precipitation in such a mountainous region. On the other hand we also show that the intensity of the peak streamflow is only captured realistically with hourly data. The higher resolution regional atmospheric model is able to simulate the fact that with the passage of an atmospheric river, some valleys receive high amounts of precipitation and others not. However, the coarser resolution global model shows uniform precipitation in the whole region. Translating the event into the future leads to similar results: while in some catchments, a future flood might be 50% larger than a present one, in others no event occurs because the atmospheric river does not hit that catchment.
How to cite: Schaller, N., Sillmann, J., Müller, M., Haarsma, R., Hazeleger, W., Jahr Hegdahl, T., Kelder, T., van den Oord, G., Weerts, A., and Whan, K.: The role of spatial and temporal model resolution in a flood event storyline approach in Western Norway, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8636, https://doi.org/10.5194/egusphere-egu2020-8636, 2020.
EGU2020-12772 | Displays | NP2.3 | Highlight
Causality and information transfer in systems with extreme eventsMilan Palus
The mathematical formulation of causality in measurable terms of predictability was given by the father of cybernetics N. Wiener [1] and formulated for time series by C.W.J. Granger [2]. The Granger causality is based on the evaluation of predictability in bivariate autoregressive models. This concept has been generalized for nonlinear systems using methods rooted in information theory [3,4]. The information-theoretic approach, defining causality as information transfer, has been successful in many applications and generalized to multivariate data and causal networks [e.g., 5]. This approach, rooted in the information theory of Shannon, usually ignores two important properties of complex systems, such as the Earth climate: the systems evolve on multiple time scales and their variables have heavy-tailed probability distributions. While the multiscale character of complex dynamics, such as air temperature variability, can be studied within the Shannonian framework [6, 7], the entropy concepts of Rényi and Tsallis have been proposed to cope with variables with heavy-tailed probability distributions. We will discuss how such non-Shannonian entropy concepts can be applied in inference of causality in systems with heavy-tailed probability distributions and extreme events, using examples from the climate system.
This study was supported by the Czech Science Foundation, project GA19-16066S.
[1] N. Wiener, in: E. F. Beckenbach (Editor), Modern Mathematics for Engineers (McGraw-Hill, New York, 1956)
[2] C.W.J. Granger, Econometrica 37 (1969) 424
[3] K. Hlaváčková-Schindler et al., Phys. Rep. 441 (2007) 1
[4] M. Paluš, M. Vejmelka, Phys. Rev. E 75 (2007) 056211
[5] J. Runge et al., Nature Communications 6 (2015) 8502
[6] M. Paluš, Phys. Rev. Lett. 112 (2014) 078702
[7] N. Jajcay, J. Hlinka, S. Kravtsov, A. A. Tsonis, M. Paluš, Geophys. Res. Lett. 43(2) (2016) 902–909
How to cite: Palus, M.: Causality and information transfer in systems with extreme events, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12772, https://doi.org/10.5194/egusphere-egu2020-12772, 2020.
The mathematical formulation of causality in measurable terms of predictability was given by the father of cybernetics N. Wiener [1] and formulated for time series by C.W.J. Granger [2]. The Granger causality is based on the evaluation of predictability in bivariate autoregressive models. This concept has been generalized for nonlinear systems using methods rooted in information theory [3,4]. The information-theoretic approach, defining causality as information transfer, has been successful in many applications and generalized to multivariate data and causal networks [e.g., 5]. This approach, rooted in the information theory of Shannon, usually ignores two important properties of complex systems, such as the Earth climate: the systems evolve on multiple time scales and their variables have heavy-tailed probability distributions. While the multiscale character of complex dynamics, such as air temperature variability, can be studied within the Shannonian framework [6, 7], the entropy concepts of Rényi and Tsallis have been proposed to cope with variables with heavy-tailed probability distributions. We will discuss how such non-Shannonian entropy concepts can be applied in inference of causality in systems with heavy-tailed probability distributions and extreme events, using examples from the climate system.
This study was supported by the Czech Science Foundation, project GA19-16066S.
[1] N. Wiener, in: E. F. Beckenbach (Editor), Modern Mathematics for Engineers (McGraw-Hill, New York, 1956)
[2] C.W.J. Granger, Econometrica 37 (1969) 424
[3] K. Hlaváčková-Schindler et al., Phys. Rep. 441 (2007) 1
[4] M. Paluš, M. Vejmelka, Phys. Rev. E 75 (2007) 056211
[5] J. Runge et al., Nature Communications 6 (2015) 8502
[6] M. Paluš, Phys. Rev. Lett. 112 (2014) 078702
[7] N. Jajcay, J. Hlinka, S. Kravtsov, A. A. Tsonis, M. Paluš, Geophys. Res. Lett. 43(2) (2016) 902–909
How to cite: Palus, M.: Causality and information transfer in systems with extreme events, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12772, https://doi.org/10.5194/egusphere-egu2020-12772, 2020.
EGU2020-13047 | Displays | NP2.3
Early warning of the Pacific Decadal Oscillation phase transition using complex network analysisZhenghui Lu, Naiming Yuan, Zhuguo Ma, Qing Yang, and Juergen Kurths
The different phases of the Pacific Decadal Oscillation (PDO) are a primary source of internal decadal climate variability which have distinct impacts on global climate and human society. However, obtaining a reliable prediction of the PDO phase transition is still challenging. Here, we employed the new technique of climate network analysis to uncover early warning signals prior to a PDO phase transition. An examination of cooperative behaviors in the PDO region revealed an enhanced signal that propagated from the western Pacific, passed through the Kuroshio extension (KE) and the subtropical oceanic frontal (STF) regions, and finally reached the northwest coast of the Americas. This signal captured all six of the PDO phase transitions from the 1890s to 2000s, with a warning time of 6.5±2.3 years in advance. It also underpinned the possible PDO phase transition at years around 2015, which may be triggered by the strong El Niño in 2014-2016.
How to cite: Lu, Z., Yuan, N., Ma, Z., Yang, Q., and Kurths, J.: Early warning of the Pacific Decadal Oscillation phase transition using complex network analysis, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13047, https://doi.org/10.5194/egusphere-egu2020-13047, 2020.
The different phases of the Pacific Decadal Oscillation (PDO) are a primary source of internal decadal climate variability which have distinct impacts on global climate and human society. However, obtaining a reliable prediction of the PDO phase transition is still challenging. Here, we employed the new technique of climate network analysis to uncover early warning signals prior to a PDO phase transition. An examination of cooperative behaviors in the PDO region revealed an enhanced signal that propagated from the western Pacific, passed through the Kuroshio extension (KE) and the subtropical oceanic frontal (STF) regions, and finally reached the northwest coast of the Americas. This signal captured all six of the PDO phase transitions from the 1890s to 2000s, with a warning time of 6.5±2.3 years in advance. It also underpinned the possible PDO phase transition at years around 2015, which may be triggered by the strong El Niño in 2014-2016.
How to cite: Lu, Z., Yuan, N., Ma, Z., Yang, Q., and Kurths, J.: Early warning of the Pacific Decadal Oscillation phase transition using complex network analysis, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13047, https://doi.org/10.5194/egusphere-egu2020-13047, 2020.
EGU2020-22377 | Displays | NP2.3
Robust extreme value analysis: the bulk matching methodFrank Kwasniok
Traditional extreme value analysis based on the generalised ex-
treme value (GEV) or generalised Pareto distribution (GPD) suffers
from two drawbacks: (i) Both methods are wasteful of data as only
block maxima or exceedances over a high threshold are taken into ac-
count and the bulk of the data is disregarded. (ii) Moreover, in the
GPD approach, there is no systematic way to determine the threshold
parameter. Here, all the data are fitted simultaneously using a gener-
alised exponential family model for the bulk and a GPD model for the
tail. At the threshold, the two distributions are linked together with
appropriate matching conditions. The model parameters are estimated
from the likelihood function of all the data. Also the threshold param-
eter can be determined via maximum likelihood in an outer loop. The
method is exemplified on wind speed data from an atmospheric model.
How to cite: Kwasniok, F.: Robust extreme value analysis: the bulk matching method , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22377, https://doi.org/10.5194/egusphere-egu2020-22377, 2020.
Traditional extreme value analysis based on the generalised ex-
treme value (GEV) or generalised Pareto distribution (GPD) suffers
from two drawbacks: (i) Both methods are wasteful of data as only
block maxima or exceedances over a high threshold are taken into ac-
count and the bulk of the data is disregarded. (ii) Moreover, in the
GPD approach, there is no systematic way to determine the threshold
parameter. Here, all the data are fitted simultaneously using a gener-
alised exponential family model for the bulk and a GPD model for the
tail. At the threshold, the two distributions are linked together with
appropriate matching conditions. The model parameters are estimated
from the likelihood function of all the data. Also the threshold param-
eter can be determined via maximum likelihood in an outer loop. The
method is exemplified on wind speed data from an atmospheric model.
How to cite: Kwasniok, F.: Robust extreme value analysis: the bulk matching method , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22377, https://doi.org/10.5194/egusphere-egu2020-22377, 2020.
EGU2020-1723 | Displays | NP2.3
A Dynamical Systems Characterisation of Atmospheric Jet Regimes in a Simple Model and Reanalysis DataNili Harnik, Gabriele Messori, Erica Madonna, Orly Lachmy, and Davide Farranda
Atmospheric jet streams are typically separated into primarily "eddy-driven", or "polar-front" jets and primarily "thermally-driven", or "subtropical" jets. Some regions also display “merged” jets, resulting from the (quasi) co-location of the regions of eddy generation with the subtropical jet. The different location and driving mechanisms of the two jet structures, plus the intermediate “merged” jet, issue from very different underlying mechanisms, and result in very different jet characteristics. Here, we link our understanding of the dynamical jet maintenance mechanisms, mostly issuing from conceptual or idealised models, to the phenomena observed in reanalysis data. We specifically focus on developing a unitary analysis framework, grounded in dynamical systems theory, which may be applied to both the model and reanalysis data and allow for direct intercomparison. Our results provide a proof-of-concept for using dynamical systems indicators to diagnose jet regimes in a versatile, conceptually intuitive and computationally efficient fashion.
How to cite: Harnik, N., Messori, G., Madonna, E., Lachmy, O., and Farranda, D.: A Dynamical Systems Characterisation of Atmospheric Jet Regimes in a Simple Model and Reanalysis Data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1723, https://doi.org/10.5194/egusphere-egu2020-1723, 2020.
Atmospheric jet streams are typically separated into primarily "eddy-driven", or "polar-front" jets and primarily "thermally-driven", or "subtropical" jets. Some regions also display “merged” jets, resulting from the (quasi) co-location of the regions of eddy generation with the subtropical jet. The different location and driving mechanisms of the two jet structures, plus the intermediate “merged” jet, issue from very different underlying mechanisms, and result in very different jet characteristics. Here, we link our understanding of the dynamical jet maintenance mechanisms, mostly issuing from conceptual or idealised models, to the phenomena observed in reanalysis data. We specifically focus on developing a unitary analysis framework, grounded in dynamical systems theory, which may be applied to both the model and reanalysis data and allow for direct intercomparison. Our results provide a proof-of-concept for using dynamical systems indicators to diagnose jet regimes in a versatile, conceptually intuitive and computationally efficient fashion.
How to cite: Harnik, N., Messori, G., Madonna, E., Lachmy, O., and Farranda, D.: A Dynamical Systems Characterisation of Atmospheric Jet Regimes in a Simple Model and Reanalysis Data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1723, https://doi.org/10.5194/egusphere-egu2020-1723, 2020.
EGU2020-5626 | Displays | NP2.3
Increasing Strength of Compound Hot-Wet Dynamical Extremes Over the MediterraneanPaolo De Luca, Gabriele Messori, Davide Faranda, and Dim Coumou
The Mediterranean (MED) basin is a hot-spot for climate change impacts. We present recently developed techniques derived from Dynamical System Theory to investigate long-term changes in compound hot-wet extremes over the MED. We use three reanalysis products, spanning a 40-year period from 1979 to 2018: ERA5, ERA-Interim and ERA5 10-member ensemble. From these datasets, we extract daily maximum temperature (degC) and total precipitation (mm), which we then use in the dynamical systems analysis.
Results show that the strength of the dynamical coupling between hot and wet extremes increased significantly at both annual and summer (June-August) timescales during the reanalysis period. This means that, regardless of changes in the occurrence of individual hot or wet extremes, joint occurrences may be becoming more frequent.
Compound hot-wet extremes mostly occur during July and August, and correspond to a low-pressure core over the Aegean Sea and the eastern MED. The increasing trends in compound extremes may be associated with surface MED warming. Such enhanced warming can therefore drive compound hot-wet extremes especially during the summer, when localised convection or mesoscale systems such as medicanes are responsible for extreme precipitation events.
How to cite: De Luca, P., Messori, G., Faranda, D., and Coumou, D.: Increasing Strength of Compound Hot-Wet Dynamical Extremes Over the Mediterranean, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5626, https://doi.org/10.5194/egusphere-egu2020-5626, 2020.
The Mediterranean (MED) basin is a hot-spot for climate change impacts. We present recently developed techniques derived from Dynamical System Theory to investigate long-term changes in compound hot-wet extremes over the MED. We use three reanalysis products, spanning a 40-year period from 1979 to 2018: ERA5, ERA-Interim and ERA5 10-member ensemble. From these datasets, we extract daily maximum temperature (degC) and total precipitation (mm), which we then use in the dynamical systems analysis.
Results show that the strength of the dynamical coupling between hot and wet extremes increased significantly at both annual and summer (June-August) timescales during the reanalysis period. This means that, regardless of changes in the occurrence of individual hot or wet extremes, joint occurrences may be becoming more frequent.
Compound hot-wet extremes mostly occur during July and August, and correspond to a low-pressure core over the Aegean Sea and the eastern MED. The increasing trends in compound extremes may be associated with surface MED warming. Such enhanced warming can therefore drive compound hot-wet extremes especially during the summer, when localised convection or mesoscale systems such as medicanes are responsible for extreme precipitation events.
How to cite: De Luca, P., Messori, G., Faranda, D., and Coumou, D.: Increasing Strength of Compound Hot-Wet Dynamical Extremes Over the Mediterranean, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5626, https://doi.org/10.5194/egusphere-egu2020-5626, 2020.
EGU2020-7579 | Displays | NP2.3 | Highlight
Dynamical Systems Theory Sheds New Light on Compound Climate Extremes in Europe and Eastern North AmericaFlavio Pons, Paolo De Luca, Gabriele Messori, and Davide Faranda
We propose a novel approach to the study of compound extremes, grounded in dynamical systems theory. Specifically, we present the co-recurrence ratio (α), which elucidates the dependence structure between maps by quantifying their joint recurrences. This approach is applied to daily climate extremes, derived from the ERA-Interim reanalysis over the 1979-2018 period. The analysis focuses on concurrent (i.e. same-day) wet (total precipitation) and windy (10m wind gusts) extremes in Europe and concurrent cold (2m temperature) extremes in Eastern North America and wet extremes in Europe. Results for wet and windy extremes in Europe, which we use as a test-bed for our methodology, show that α peaks during boreal winter. High αvalues correspond to wet and windy extremes in north-western Europe, and to large-scale conditions resembling the positive phase of the North Atlantic Oscillation (NAO). This confirms earlier findings which link the positive NAO to a heightened frequency of extra-tropical cyclones impacting north-western Europe, resulting in frequent wet and windy extremes. For the Eastern North America-Europe case, α extremes once again reflect concurrent climate extremes -- in this case cold extremes over North America and wet extremes over Europe. Our analysis provides detailed spatial information on regional hotspots for these compound extreme occurrences, and encapsulates information on their spatial footprint which is typically not included in a conventional co-occurrence analysis. We conclude that α successfully characterises compound extremes by reflecting the evolution of the associated meteorological maps. This approach is entirely general, and may be applied to different types of compound extremes and geographical regions.
How to cite: Pons, F., De Luca, P., Messori, G., and Faranda, D.: Dynamical Systems Theory Sheds New Light on Compound Climate Extremes in Europe and Eastern North America, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7579, https://doi.org/10.5194/egusphere-egu2020-7579, 2020.
We propose a novel approach to the study of compound extremes, grounded in dynamical systems theory. Specifically, we present the co-recurrence ratio (α), which elucidates the dependence structure between maps by quantifying their joint recurrences. This approach is applied to daily climate extremes, derived from the ERA-Interim reanalysis over the 1979-2018 period. The analysis focuses on concurrent (i.e. same-day) wet (total precipitation) and windy (10m wind gusts) extremes in Europe and concurrent cold (2m temperature) extremes in Eastern North America and wet extremes in Europe. Results for wet and windy extremes in Europe, which we use as a test-bed for our methodology, show that α peaks during boreal winter. High αvalues correspond to wet and windy extremes in north-western Europe, and to large-scale conditions resembling the positive phase of the North Atlantic Oscillation (NAO). This confirms earlier findings which link the positive NAO to a heightened frequency of extra-tropical cyclones impacting north-western Europe, resulting in frequent wet and windy extremes. For the Eastern North America-Europe case, α extremes once again reflect concurrent climate extremes -- in this case cold extremes over North America and wet extremes over Europe. Our analysis provides detailed spatial information on regional hotspots for these compound extreme occurrences, and encapsulates information on their spatial footprint which is typically not included in a conventional co-occurrence analysis. We conclude that α successfully characterises compound extremes by reflecting the evolution of the associated meteorological maps. This approach is entirely general, and may be applied to different types of compound extremes and geographical regions.
How to cite: Pons, F., De Luca, P., Messori, G., and Faranda, D.: Dynamical Systems Theory Sheds New Light on Compound Climate Extremes in Europe and Eastern North America, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7579, https://doi.org/10.5194/egusphere-egu2020-7579, 2020.
EGU2020-5279 | Displays | NP2.3
Evaluation of CMIP6 simulations of temperature extremes using proper evaluation methods, observations and reanalysesThordis Thorarinsdottir, Jana Sillmann, and Marion Haugen
Climate models aim to project future changes in important drivers of climate including atmosphere, oceans and ice, and their interactions. A comprehensive evaluation of climate models thus requires evaluation methods, or performance measures, that are flexible, specific and can address also extreme events. Climate models have traditionally been assessed by comparing summary statistics or point estimates that derive from the simulated model output to corresponding observed quantities using e.g. RMSE. However, it has been argued persuasively that probability distributions of model output need to be compared to the corresponding empirical distributions of observations or observation-based data products. Observation-based gridded datasets for climate extremes, despite having limitations, are particularly useful and necessary to assess model performance with respect to extremes. We discuss proper performance measures for comparing distributions of model output against corresponding distributions from data products that are flexible and robust enough to handle the particular aspects of extremes such as limited data availability. The new measures are applied to evaluate CMIP5 and CMIP6 projections of extreme temperature indices over Europe and North-America against the HadEX2 data set as well as the ERA5 and ERA-Interim reanalyses. Several models perform well to the extent that when compared to the HadEX2 data product, these models' performance is competitive with the performance of the reanalysis. While the model rankings vary with region, season and index, the model evaluation is robust against changes in the grid resolution considered in the analysis.
How to cite: Thorarinsdottir, T., Sillmann, J., and Haugen, M.: Evaluation of CMIP6 simulations of temperature extremes using proper evaluation methods, observations and reanalyses, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5279, https://doi.org/10.5194/egusphere-egu2020-5279, 2020.
Climate models aim to project future changes in important drivers of climate including atmosphere, oceans and ice, and their interactions. A comprehensive evaluation of climate models thus requires evaluation methods, or performance measures, that are flexible, specific and can address also extreme events. Climate models have traditionally been assessed by comparing summary statistics or point estimates that derive from the simulated model output to corresponding observed quantities using e.g. RMSE. However, it has been argued persuasively that probability distributions of model output need to be compared to the corresponding empirical distributions of observations or observation-based data products. Observation-based gridded datasets for climate extremes, despite having limitations, are particularly useful and necessary to assess model performance with respect to extremes. We discuss proper performance measures for comparing distributions of model output against corresponding distributions from data products that are flexible and robust enough to handle the particular aspects of extremes such as limited data availability. The new measures are applied to evaluate CMIP5 and CMIP6 projections of extreme temperature indices over Europe and North-America against the HadEX2 data set as well as the ERA5 and ERA-Interim reanalyses. Several models perform well to the extent that when compared to the HadEX2 data product, these models' performance is competitive with the performance of the reanalysis. While the model rankings vary with region, season and index, the model evaluation is robust against changes in the grid resolution considered in the analysis.
How to cite: Thorarinsdottir, T., Sillmann, J., and Haugen, M.: Evaluation of CMIP6 simulations of temperature extremes using proper evaluation methods, observations and reanalyses, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5279, https://doi.org/10.5194/egusphere-egu2020-5279, 2020.
EGU2020-5795 | Displays | NP2.3
Extreme Value Theory for ObservationsTheophile caby, Davide Faranda, Sandro Vaienti, and Pascal Yiou
We study the properties of recurrence of a smooth observable computed along a trajectory of a chaotic system near a particular value of interest . Using the framework of Extreme Value Theory, we are able to derive a limit law which is a Gumbel distribution whose parameters relate to the dimensions of the image measure. We show that this approach allows to have access to the fine structure of the attractor, by using directly observational data. In particular, we are able to compute local dimensions associated to the underlying attractor whenever the dimensionality of the observable is larger than the dimension of the attractor.
How to cite: caby, T., Faranda, D., Vaienti, S., and Yiou, P.: Extreme Value Theory for Observations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5795, https://doi.org/10.5194/egusphere-egu2020-5795, 2020.
We study the properties of recurrence of a smooth observable computed along a trajectory of a chaotic system near a particular value of interest . Using the framework of Extreme Value Theory, we are able to derive a limit law which is a Gumbel distribution whose parameters relate to the dimensions of the image measure. We show that this approach allows to have access to the fine structure of the attractor, by using directly observational data. In particular, we are able to compute local dimensions associated to the underlying attractor whenever the dimensionality of the observable is larger than the dimension of the attractor.
How to cite: caby, T., Faranda, D., Vaienti, S., and Yiou, P.: Extreme Value Theory for Observations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5795, https://doi.org/10.5194/egusphere-egu2020-5795, 2020.
EGU2020-6113 | Displays | NP2.3
Evaluating CMIP6 Model Fidelity at Simulating Non-Gaussian Temperature Distribution TailsArielle Catalano, Paul Loikith, and J. David Neelin
Under global warming, changes in extreme temperatures will manifest in more complex ways in locations where temperature distribution tails deviate from Gaussian. For example, uniform warming applied to a temperature distribution with a shorter-than-Gaussian warm tail would lead to greater exceedances in warm-side temperature extremes compared with a Gaussian distribution. Confidence in projections of future temperature extremes and associated impacts under global warming therefore relies on the ability of global climate models (GCMs) to realistically simulate observed temperature distribution tail behavior. This presentation examines the ability of the latest state-of-the-art ensemble of GCMs from the Coupled Model Intercomparison Project phase six (CMIP6) to capture historical global surface temperature distribution tail shape in hemispheric winter and summer seasons. Comparisons between the multi-model ensemble mean and a reanalysis product reveal strong agreement on coherent spatial patterns of longer- and shorter-than-Gaussian tails for the cold and warm sides of the temperature distribution, suggesting that CMIP6 is broadly capturing tail behavior for plausible physical and dynamical reasons. Most individual GCMs are also reasonably skilled at capturing historical tail shape on a global scale, but a division of the domain into sub-regions reveals considerable model and spatial variability. To explore potential mechanisms driving these differences, a back trajectory analysis examining patterns in the origin of air masses on days experiencing extreme temperatures is also discussed.
How to cite: Catalano, A., Loikith, P., and Neelin, J. D.: Evaluating CMIP6 Model Fidelity at Simulating Non-Gaussian Temperature Distribution Tails, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6113, https://doi.org/10.5194/egusphere-egu2020-6113, 2020.
Under global warming, changes in extreme temperatures will manifest in more complex ways in locations where temperature distribution tails deviate from Gaussian. For example, uniform warming applied to a temperature distribution with a shorter-than-Gaussian warm tail would lead to greater exceedances in warm-side temperature extremes compared with a Gaussian distribution. Confidence in projections of future temperature extremes and associated impacts under global warming therefore relies on the ability of global climate models (GCMs) to realistically simulate observed temperature distribution tail behavior. This presentation examines the ability of the latest state-of-the-art ensemble of GCMs from the Coupled Model Intercomparison Project phase six (CMIP6) to capture historical global surface temperature distribution tail shape in hemispheric winter and summer seasons. Comparisons between the multi-model ensemble mean and a reanalysis product reveal strong agreement on coherent spatial patterns of longer- and shorter-than-Gaussian tails for the cold and warm sides of the temperature distribution, suggesting that CMIP6 is broadly capturing tail behavior for plausible physical and dynamical reasons. Most individual GCMs are also reasonably skilled at capturing historical tail shape on a global scale, but a division of the domain into sub-regions reveals considerable model and spatial variability. To explore potential mechanisms driving these differences, a back trajectory analysis examining patterns in the origin of air masses on days experiencing extreme temperatures is also discussed.
How to cite: Catalano, A., Loikith, P., and Neelin, J. D.: Evaluating CMIP6 Model Fidelity at Simulating Non-Gaussian Temperature Distribution Tails, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6113, https://doi.org/10.5194/egusphere-egu2020-6113, 2020.
EGU2020-6180 | Displays | NP2.3
The thermal waters of the Portugal Star Geopark - methods for understanding its origin and sustainable exploitation.Elsa Salzedas
EGU2020-7555 | Displays | NP2.3 | Highlight
Simulating compound weather extremes responsible for critical crop failure with stochastic weather generatorsPascal Yiou, Peter Pfleiderer, Aglaé Jézéquel, Juliette Legrand, Natacha Legrix, Jason Markantonis, and Edoardo Vignotto
In 2016, northern France experienced an unprecedented wheat crop loss. This extreme event was likely due to particular meteorological conditions, i.e. too few cold days in late autumn and an abnormally high precipitation during the spring season. The cause of this event is not fully understood yet and none of the most used crop forecast models were able to predict the event (Ben-Ari et al, 2018).
This work is motivated by two main questions: were the 2016 meteorological conditions the most extreme we could imagine under current climate? and what would be the worst case scenario we could expect that could lead to even worst crop loss? To answer these questions, instead of relying on computationally intensive climate model simulations, we use an analogue based importance sampling algorithm that was recently introduced into this field of research (Yiou and Jézéquel, 2019). This algorithm is a modification of a stochastic weather generator (SWG), which gives more weight to trajectories with more extreme meteorological conditions (here temperature and precipitation). This data driven technique constructs artificial weather events by combining daily observations in a dynamically realistic manner and in a relatively fast way.
This is the first application of SWGs to simulate warm winters and wet springs. We show that with some adjustments both (new) weather events can be adequately simulated with SWGs, highlighting the wide applicability of the method.
While the number of cold days in late autumn 2015 was close to the plausible maximum, our simulations of extreme spring precipitation show that considerably wetter springs than what was observed in 2016 are possible. Although the crop loss of 2016 is not fully understood yet, these results indicate that similar events with higher impacts could be possible.
How to cite: Yiou, P., Pfleiderer, P., Jézéquel, A., Legrand, J., Legrix, N., Markantonis, J., and Vignotto, E.: Simulating compound weather extremes responsible for critical crop failure with stochastic weather generators, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7555, https://doi.org/10.5194/egusphere-egu2020-7555, 2020.
In 2016, northern France experienced an unprecedented wheat crop loss. This extreme event was likely due to particular meteorological conditions, i.e. too few cold days in late autumn and an abnormally high precipitation during the spring season. The cause of this event is not fully understood yet and none of the most used crop forecast models were able to predict the event (Ben-Ari et al, 2018).
This work is motivated by two main questions: were the 2016 meteorological conditions the most extreme we could imagine under current climate? and what would be the worst case scenario we could expect that could lead to even worst crop loss? To answer these questions, instead of relying on computationally intensive climate model simulations, we use an analogue based importance sampling algorithm that was recently introduced into this field of research (Yiou and Jézéquel, 2019). This algorithm is a modification of a stochastic weather generator (SWG), which gives more weight to trajectories with more extreme meteorological conditions (here temperature and precipitation). This data driven technique constructs artificial weather events by combining daily observations in a dynamically realistic manner and in a relatively fast way.
This is the first application of SWGs to simulate warm winters and wet springs. We show that with some adjustments both (new) weather events can be adequately simulated with SWGs, highlighting the wide applicability of the method.
While the number of cold days in late autumn 2015 was close to the plausible maximum, our simulations of extreme spring precipitation show that considerably wetter springs than what was observed in 2016 are possible. Although the crop loss of 2016 is not fully understood yet, these results indicate that similar events with higher impacts could be possible.
How to cite: Yiou, P., Pfleiderer, P., Jézéquel, A., Legrand, J., Legrix, N., Markantonis, J., and Vignotto, E.: Simulating compound weather extremes responsible for critical crop failure with stochastic weather generators, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7555, https://doi.org/10.5194/egusphere-egu2020-7555, 2020.
EGU2020-8006 | Displays | NP2.3
Comparison of mega-heatwaves in preindustrial and present-day simulations over EuropeJongsoo Shin and Soon-Il An
Heatwaves are likely to occur more frequent, longer, and stronger due to the rise in CO2 concentrations. It is related to the change in the mean of a climate distribution, as well as through the change in variance. Mega-heatwaves, in particular, have a crucial impact on human health. Many studies are trying to understand the mechanisms of mega-heatwaves and also their characteristics included amplitude, duration, frequency. In spite of these efforts, researches are limited because of the small number of mega-heatwaves. In order to overcome these limitations, Earth system model should be needed. This study aims to figure out the comprehensive characteristics of mega-heatwaves using Community Earth System Model (CESM). First, the possibility of the occurrence of mega-heatwaves in preindustrial period in Europe was analyzed. Second, the relation between decadal climate variabilities and mega-heatwaves was investigated. In addition, changes in characteristics of mega-heatwaves were compared between preindustrial and present-day simulations.
How to cite: Shin, J. and An, S.-I.: Comparison of mega-heatwaves in preindustrial and present-day simulations over Europe, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8006, https://doi.org/10.5194/egusphere-egu2020-8006, 2020.
Heatwaves are likely to occur more frequent, longer, and stronger due to the rise in CO2 concentrations. It is related to the change in the mean of a climate distribution, as well as through the change in variance. Mega-heatwaves, in particular, have a crucial impact on human health. Many studies are trying to understand the mechanisms of mega-heatwaves and also their characteristics included amplitude, duration, frequency. In spite of these efforts, researches are limited because of the small number of mega-heatwaves. In order to overcome these limitations, Earth system model should be needed. This study aims to figure out the comprehensive characteristics of mega-heatwaves using Community Earth System Model (CESM). First, the possibility of the occurrence of mega-heatwaves in preindustrial period in Europe was analyzed. Second, the relation between decadal climate variabilities and mega-heatwaves was investigated. In addition, changes in characteristics of mega-heatwaves were compared between preindustrial and present-day simulations.
How to cite: Shin, J. and An, S.-I.: Comparison of mega-heatwaves in preindustrial and present-day simulations over Europe, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8006, https://doi.org/10.5194/egusphere-egu2020-8006, 2020.
EGU2020-8138 | Displays | NP2.3
Influence of Pacific Decadal Oscillation on global precipitation extremes on decadal time scalesWenguang Wei, Zhongwei Yan, and Zhen Li
On the decadal time scales, while the influence of Pacific Decadal Oscillation (PDO) on total or average precipitation had been extensively studied, works about its influence on precipitation extremes were limited, especially lack of a global picture. Using two independent methods, nonstationary generalized extreme value (GEV) model which directly incorporates PDO index into its location parameter and moving GEV model which fits the annual extremes with a sliding window of 30 years and regresses the resulted changing location parameter onto the PDO index, we show that precipitation extremes over a large portion of stations are significantly affected by the PDO with stations in the Pacific Rim demonstrating distinct regional patterns. Over eastern China, the famous ‘southern flood and norther drought’ pattern corresponding to a positive PDO phase extends to extreme rainfalls; over Australia, a tri-polar pattern was revealed, in which the extremes over central Australia positively correlate with the PDO index and those over eastern and western Australia show a negative correlation; and the North America also demonstrates a dipole pattern, by which the northwest (southeast) experiences less (more) intense extreme rainfall in a PDO positive phase. Moreover, the western Europe and the large area between the Ural mountain and eastern Europe were discovered to hold a positive correlation with the PDO in their precipitation extremes. A comparative analysis to the local circulation controlling the precipitation extremes under different PDO phases further confirms the discovered relationships above. These findings have important implication for the future projection of extreme precipitation over related regions because the internal climate variability should be appropriately accounted for beyond the effects induced by global warming.
How to cite: Wei, W., Yan, Z., and Li, Z.: Influence of Pacific Decadal Oscillation on global precipitation extremes on decadal time scales, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8138, https://doi.org/10.5194/egusphere-egu2020-8138, 2020.
On the decadal time scales, while the influence of Pacific Decadal Oscillation (PDO) on total or average precipitation had been extensively studied, works about its influence on precipitation extremes were limited, especially lack of a global picture. Using two independent methods, nonstationary generalized extreme value (GEV) model which directly incorporates PDO index into its location parameter and moving GEV model which fits the annual extremes with a sliding window of 30 years and regresses the resulted changing location parameter onto the PDO index, we show that precipitation extremes over a large portion of stations are significantly affected by the PDO with stations in the Pacific Rim demonstrating distinct regional patterns. Over eastern China, the famous ‘southern flood and norther drought’ pattern corresponding to a positive PDO phase extends to extreme rainfalls; over Australia, a tri-polar pattern was revealed, in which the extremes over central Australia positively correlate with the PDO index and those over eastern and western Australia show a negative correlation; and the North America also demonstrates a dipole pattern, by which the northwest (southeast) experiences less (more) intense extreme rainfall in a PDO positive phase. Moreover, the western Europe and the large area between the Ural mountain and eastern Europe were discovered to hold a positive correlation with the PDO in their precipitation extremes. A comparative analysis to the local circulation controlling the precipitation extremes under different PDO phases further confirms the discovered relationships above. These findings have important implication for the future projection of extreme precipitation over related regions because the internal climate variability should be appropriately accounted for beyond the effects induced by global warming.
How to cite: Wei, W., Yan, Z., and Li, Z.: Influence of Pacific Decadal Oscillation on global precipitation extremes on decadal time scales, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8138, https://doi.org/10.5194/egusphere-egu2020-8138, 2020.
EGU2020-12919 | Displays | NP2.3
Model evaluation for Heatwaves over South Korea in CMIP6 modelsJi-Seon Oh, Maeng-Ki Kim, Dae-Geun Yu, and Jeong Sang
In this study, we defined diagnostic indices to evaluate the CMIP6 models based on the heatwaves mechanisms of Korea presented in previous studies. Based on this, the simulation performance of the model was quantitatively evaluated using Relative Error (RE), Inter-annual Variability Skill-score (IVS), and Correlation Coefficient (CC). The REs in diagnostic indices are still large, especially in heat wave circulation index (HWCI) and Indian summer monsoon rainfall index (IMRI), which is mainly due to weak convective activity bias over the northwestern Pacific Ocean and the northwestern India. However, the IVSs in diagnostic indices have been improved overall in the CMIP6 compared to the CMIP5, especially in the IMRI. The CC between the daily maximum temperature (TMAX) and the diagnostic factors in the model is very higher in HWCI than other indices, indicating that the convective activity over the northwestern Pacific is very important in heat wave in Korea. As a result, the total ranking of the model performance for heatwaves in Korea suggested that EC-Earth3-Veg, EC-Earth3, and UKESM-1-0-LL ranked high in CMIP6.
This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMI(KMI2018-03410)
How to cite: Oh, J.-S., Kim, M.-K., Yu, D.-G., and Sang, J.: Model evaluation for Heatwaves over South Korea in CMIP6 models, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12919, https://doi.org/10.5194/egusphere-egu2020-12919, 2020.
In this study, we defined diagnostic indices to evaluate the CMIP6 models based on the heatwaves mechanisms of Korea presented in previous studies. Based on this, the simulation performance of the model was quantitatively evaluated using Relative Error (RE), Inter-annual Variability Skill-score (IVS), and Correlation Coefficient (CC). The REs in diagnostic indices are still large, especially in heat wave circulation index (HWCI) and Indian summer monsoon rainfall index (IMRI), which is mainly due to weak convective activity bias over the northwestern Pacific Ocean and the northwestern India. However, the IVSs in diagnostic indices have been improved overall in the CMIP6 compared to the CMIP5, especially in the IMRI. The CC between the daily maximum temperature (TMAX) and the diagnostic factors in the model is very higher in HWCI than other indices, indicating that the convective activity over the northwestern Pacific is very important in heat wave in Korea. As a result, the total ranking of the model performance for heatwaves in Korea suggested that EC-Earth3-Veg, EC-Earth3, and UKESM-1-0-LL ranked high in CMIP6.
This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMI(KMI2018-03410)
How to cite: Oh, J.-S., Kim, M.-K., Yu, D.-G., and Sang, J.: Model evaluation for Heatwaves over South Korea in CMIP6 models, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12919, https://doi.org/10.5194/egusphere-egu2020-12919, 2020.
EGU2020-13717 | Displays | NP2.3
Predictability of large scale drivers leading intense Mediterranean cyclonesM. Carmen Alvarez-Castro, Silvio Gualdi, Pascal Yiou, Mathieu Vrac, Robert Vautard, Leone Cavicchia, David Gallego, Pedro Ribera, Cristina Pena-Ortiz, and Davide Faranda
Windstorms, extreme precipitations and instant floods seems to strike the Mediterranean area with increasing frequency. These events occur simultaneously during intense tropical-like Mediterranean cyclones. These intense Mediterranean cyclones are frequently associated with wind, heavy precipitation and changes in temperature, generating high risk situations such as flash floods and large-scale floods with significant impacts on human life and built environment. Although the dynamics of these phenomena is well understood, little is know about their climatology. It is therefore very difficult to make statements about the frequency of occurrence and its response to climate change. Thus, intense Mediterranean cyclones have many different physical aspects that can not be captured by a simple standard approach.
The first challenge of this work is to provide an extended catalogue and climatology of these phenomena by reconstructing a database of intense Mediterranean cyclones dating back up to 1969 using the satellite, the literature and reanalyses. Applying a method based on dynamical systems theory we analyse and attribute their future changes under different anthropogenic forcings by using future simulations within CMIP framework. Preliminary results show a decrease of the large-scale circulation patterns favoring intense Mediterranean cyclones in all the seasons except summer.
How to cite: Alvarez-Castro, M. C., Gualdi, S., Yiou, P., Vrac, M., Vautard, R., Cavicchia, L., Gallego, D., Ribera, P., Pena-Ortiz, C., and Faranda, D.: Predictability of large scale drivers leading intense Mediterranean cyclones, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13717, https://doi.org/10.5194/egusphere-egu2020-13717, 2020.
Windstorms, extreme precipitations and instant floods seems to strike the Mediterranean area with increasing frequency. These events occur simultaneously during intense tropical-like Mediterranean cyclones. These intense Mediterranean cyclones are frequently associated with wind, heavy precipitation and changes in temperature, generating high risk situations such as flash floods and large-scale floods with significant impacts on human life and built environment. Although the dynamics of these phenomena is well understood, little is know about their climatology. It is therefore very difficult to make statements about the frequency of occurrence and its response to climate change. Thus, intense Mediterranean cyclones have many different physical aspects that can not be captured by a simple standard approach.
The first challenge of this work is to provide an extended catalogue and climatology of these phenomena by reconstructing a database of intense Mediterranean cyclones dating back up to 1969 using the satellite, the literature and reanalyses. Applying a method based on dynamical systems theory we analyse and attribute their future changes under different anthropogenic forcings by using future simulations within CMIP framework. Preliminary results show a decrease of the large-scale circulation patterns favoring intense Mediterranean cyclones in all the seasons except summer.
How to cite: Alvarez-Castro, M. C., Gualdi, S., Yiou, P., Vrac, M., Vautard, R., Cavicchia, L., Gallego, D., Ribera, P., Pena-Ortiz, C., and Faranda, D.: Predictability of large scale drivers leading intense Mediterranean cyclones, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13717, https://doi.org/10.5194/egusphere-egu2020-13717, 2020.
EGU2020-19940 | Displays | NP2.3
Application of an artificial neural network to generate wave projections at southern African coastsFelix Soltau, Matthias Hirt, Jessica Kelln, Sara Santamaria-Aguilar, Sönke Dangendorf, and Jürgen Jensen
In the past decades, severe so called ‚compound events‘ led to critical high water levels at the coasts of southern Africa and as a consequence to property damage and loss of human life. The co-occurrence of storm surges, wind waves, heavy precipitation and resulting runoff increases the risk of coastal flooding and exacerbates the impacts along the vulnerable southern African coasts (e.g. Couasnon et al. 2019). To mitigate these high-impacts, it is essential to understand the underlying processes and driving factors (Wahl et al. 2015). As compound flooding events at southern African coasts are dominated by wind waves, it is of great importance to investigate the regional wave climate to understand the wave forcing as well as the origin of the wave energy.
Wind waves around southern African coasts are affected by the complex interactions between the Agulhas current and the atmosphere. In the research project CASISAC* we analyse the present evolution of the Agulhas Current system and quantify its impact on the future regional wave climate. Ocean waves contributing to high sea levels can be generated offshore resulting in swell or closer to the coasts by strong onshore winds. To identify responsible atmospheric pressure fields that force high wind wave events we apply a hybrid approach: (1) linking south hemispheric pressure fields with offshore wave data using an artificial neural network and (2) determine the prevailing nearshore wave conditions by regional numerical wave propagation models (SWAN). By validating the modelled nearshore wave data from hindcast runs with wave buoy records, this approach allows us to predict future extreme wind wave events and thus potential flooding. In a next step, extreme value analysis is used to determine future return periods of extreme wave events. These results can contribute to the development of more reliable adaptive protection strategies for southern African coast.
*CASISAC (Changes in the Agulhas System and its Impact on Southern African Coasts: Sea level and coastal extremes) is funded by the German Federal Ministry of Education and Research (BMBF) through the project management of Projektträger Jülich PTJ under the grant number 03F0796C
Couasnon, Eilander, Muis, Veldkamp, Haigh, Wahl, Winsemius, Ward (2019): Measuring compound flood potential from river discharge and storm surge extremes at the global scale and its implications for flood hazard. In: Natural Hazards and Earth System Sciences, Discussion Paper, S. 1–24. DOI: 10.5194/nhess-2019-205, in review.
Wahl, Jain, Bender, Meyers, Luther (2015): Increasing risk of compound flooding from storm surge and rainfall for major US cities. In: Nature Climate Change 5 (12), S. 1093–1097. DOI: 10.1038/nclimate2736.
How to cite: Soltau, F., Hirt, M., Kelln, J., Santamaria-Aguilar, S., Dangendorf, S., and Jensen, J.: Application of an artificial neural network to generate wave projections at southern African coasts, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19940, https://doi.org/10.5194/egusphere-egu2020-19940, 2020.
In the past decades, severe so called ‚compound events‘ led to critical high water levels at the coasts of southern Africa and as a consequence to property damage and loss of human life. The co-occurrence of storm surges, wind waves, heavy precipitation and resulting runoff increases the risk of coastal flooding and exacerbates the impacts along the vulnerable southern African coasts (e.g. Couasnon et al. 2019). To mitigate these high-impacts, it is essential to understand the underlying processes and driving factors (Wahl et al. 2015). As compound flooding events at southern African coasts are dominated by wind waves, it is of great importance to investigate the regional wave climate to understand the wave forcing as well as the origin of the wave energy.
Wind waves around southern African coasts are affected by the complex interactions between the Agulhas current and the atmosphere. In the research project CASISAC* we analyse the present evolution of the Agulhas Current system and quantify its impact on the future regional wave climate. Ocean waves contributing to high sea levels can be generated offshore resulting in swell or closer to the coasts by strong onshore winds. To identify responsible atmospheric pressure fields that force high wind wave events we apply a hybrid approach: (1) linking south hemispheric pressure fields with offshore wave data using an artificial neural network and (2) determine the prevailing nearshore wave conditions by regional numerical wave propagation models (SWAN). By validating the modelled nearshore wave data from hindcast runs with wave buoy records, this approach allows us to predict future extreme wind wave events and thus potential flooding. In a next step, extreme value analysis is used to determine future return periods of extreme wave events. These results can contribute to the development of more reliable adaptive protection strategies for southern African coast.
*CASISAC (Changes in the Agulhas System and its Impact on Southern African Coasts: Sea level and coastal extremes) is funded by the German Federal Ministry of Education and Research (BMBF) through the project management of Projektträger Jülich PTJ under the grant number 03F0796C
Couasnon, Eilander, Muis, Veldkamp, Haigh, Wahl, Winsemius, Ward (2019): Measuring compound flood potential from river discharge and storm surge extremes at the global scale and its implications for flood hazard. In: Natural Hazards and Earth System Sciences, Discussion Paper, S. 1–24. DOI: 10.5194/nhess-2019-205, in review.
Wahl, Jain, Bender, Meyers, Luther (2015): Increasing risk of compound flooding from storm surge and rainfall for major US cities. In: Nature Climate Change 5 (12), S. 1093–1097. DOI: 10.1038/nclimate2736.
How to cite: Soltau, F., Hirt, M., Kelln, J., Santamaria-Aguilar, S., Dangendorf, S., and Jensen, J.: Application of an artificial neural network to generate wave projections at southern African coasts, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19940, https://doi.org/10.5194/egusphere-egu2020-19940, 2020.
NP4.1 – Complex geoscientific time series: linear, nonlinear, and computer science perspectives
EGU2020-1313 | Displays | NP4.1 | Highlight
A nonlinear dynamics approach to data-enabled science: Reconstructing soil-moisture dynamics from big data collected by wireless sensor networksRay Huffaker and Rafael Munoz-Carpena
The complex soil biome is a center piece in providing essential ecosystem services that humans rely on (carbon sequestration, food security, one-health interactions). Agricultural engineers and soil scientists are developing wireless sensor networks (WSN) that collect large/big data on the soil key state variables (water content, temperature, chemistry) to better understand the soil biome primary environmental drivers. The profession extracts information from WSN records with methods including soil-process modeling and artificial-intelligence (AI) algorithms. However, these approaches carry their own limitations. A recent review article faulted current soil-process modeling for inadequately detecting and resolving model structural (abstraction) errors. AI experts themselves caution against indiscriminant use of AI methods because of: a) problems including replication of past results due to inconsistent experimental methods; b) difficulty in explaining how a particular method arrives at its conclusions (the black box problem) and thus in correcting algorithms that learn ‘bad lessons’; and c) lack of rigorous criteria for selecting AI architectures. An alternative approach to address these limitations is to investigate new strategies for reducing large/big data problems into smaller, more interpretable causal abstractions of the soil system.
We develop an innovative data diagnostics framework—based on empirical nonlinear dynamics techniques from physics—that addresses the above concerns over soil-process modeling and AI algorithms. We diagnose whether WSN and other similar environmental large/big data are likely generated by dimension-reducing (i.e., dissipative) nonlinear dynamics. An n-dimensional nonlinear dynamic system is dissipative if long-term dynamics are bounded within m<<n dimensions, so that the problem of modeling long-term dynamics shrinks by the n-m inactive degrees of freedom. If so, long-term system dynamics can be investigated with relatively few degrees of freedom that capture the complexity of the overall system generating observed data. To make this diagnosis, we first apply signal processing to isolate structured variation (signal) from unstructured variation (noise) in large/big data time series records, and test signals for nonlinear stationarity. We resolve the structure of isolated signals by distinguishing between stochastic-forcing and deterministic nonlinear dynamics; reconstruct phase space dynamics most likely generating signals, and test the statistical significance of reconstructed dynamics with surrogate data. If the reconstructed phase space is dimension-reducing, we can formulate low-dimensional (phenomenological) ODE models to investigate nonlinear causal interactions between key soil environmental driving factors. When we do not diagnose dimension-reducing nonlinear real-world dynamics, then underlying dynamics are most likely high dimensional and the information-extraction problem cannot be shrunk without losing essential dynamic information. In this case, other high-dimensional analysis techniques like AI offer a better modeling alternative for mapping out interactions. Our framework supplies a decision-support tool for data practitioners toward the most informative and parsimonious information-extraction method—a win-win result.
We will share preliminary results applying this empirical framework to three soil moisture sensor time series records analyzed with machine learning methods in Bean, Huffaker, and Migliaccio (2018).
How to cite: Huffaker, R. and Munoz-Carpena, R.: A nonlinear dynamics approach to data-enabled science: Reconstructing soil-moisture dynamics from big data collected by wireless sensor networks, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1313, https://doi.org/10.5194/egusphere-egu2020-1313, 2020.
The complex soil biome is a center piece in providing essential ecosystem services that humans rely on (carbon sequestration, food security, one-health interactions). Agricultural engineers and soil scientists are developing wireless sensor networks (WSN) that collect large/big data on the soil key state variables (water content, temperature, chemistry) to better understand the soil biome primary environmental drivers. The profession extracts information from WSN records with methods including soil-process modeling and artificial-intelligence (AI) algorithms. However, these approaches carry their own limitations. A recent review article faulted current soil-process modeling for inadequately detecting and resolving model structural (abstraction) errors. AI experts themselves caution against indiscriminant use of AI methods because of: a) problems including replication of past results due to inconsistent experimental methods; b) difficulty in explaining how a particular method arrives at its conclusions (the black box problem) and thus in correcting algorithms that learn ‘bad lessons’; and c) lack of rigorous criteria for selecting AI architectures. An alternative approach to address these limitations is to investigate new strategies for reducing large/big data problems into smaller, more interpretable causal abstractions of the soil system.
We develop an innovative data diagnostics framework—based on empirical nonlinear dynamics techniques from physics—that addresses the above concerns over soil-process modeling and AI algorithms. We diagnose whether WSN and other similar environmental large/big data are likely generated by dimension-reducing (i.e., dissipative) nonlinear dynamics. An n-dimensional nonlinear dynamic system is dissipative if long-term dynamics are bounded within m<<n dimensions, so that the problem of modeling long-term dynamics shrinks by the n-m inactive degrees of freedom. If so, long-term system dynamics can be investigated with relatively few degrees of freedom that capture the complexity of the overall system generating observed data. To make this diagnosis, we first apply signal processing to isolate structured variation (signal) from unstructured variation (noise) in large/big data time series records, and test signals for nonlinear stationarity. We resolve the structure of isolated signals by distinguishing between stochastic-forcing and deterministic nonlinear dynamics; reconstruct phase space dynamics most likely generating signals, and test the statistical significance of reconstructed dynamics with surrogate data. If the reconstructed phase space is dimension-reducing, we can formulate low-dimensional (phenomenological) ODE models to investigate nonlinear causal interactions between key soil environmental driving factors. When we do not diagnose dimension-reducing nonlinear real-world dynamics, then underlying dynamics are most likely high dimensional and the information-extraction problem cannot be shrunk without losing essential dynamic information. In this case, other high-dimensional analysis techniques like AI offer a better modeling alternative for mapping out interactions. Our framework supplies a decision-support tool for data practitioners toward the most informative and parsimonious information-extraction method—a win-win result.
We will share preliminary results applying this empirical framework to three soil moisture sensor time series records analyzed with machine learning methods in Bean, Huffaker, and Migliaccio (2018).
How to cite: Huffaker, R. and Munoz-Carpena, R.: A nonlinear dynamics approach to data-enabled science: Reconstructing soil-moisture dynamics from big data collected by wireless sensor networks, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1313, https://doi.org/10.5194/egusphere-egu2020-1313, 2020.
EGU2020-8763 | Displays | NP4.1 | Highlight
Probability estimation of a Carrington-like geomagnetic stormIsabel Serra, David Moriña, Pere Puig, and Álvaro Corral
Intense geomagnetic storms can cause severe damage to electrical systems and communications. this work proposes a counting process with Weibull inter-occurrence times in order to estimate the probability of extreme geomagnetic events. It is found that the scale parameter of the inter-occurrence time distribution grows exponentially with the absolute value of the intensity threshold defining the storm, whereas the shape parameter keeps rather constant. The model is able to forecast the probability of occurrence of an event for a given intensity threshold; in particular, the probability of occurrence on the next decade of an extreme event of a magnitude comparable or larger than the well-known Carrington event of 1859 is explored, and estimated to be between 0.46% and 1.88% (with a 95% confidence), a much lower value than those reported in the existing literature.
How to cite: Serra, I., Moriña, D., Puig, P., and Corral, Á.: Probability estimation of a Carrington-like geomagnetic storm, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8763, https://doi.org/10.5194/egusphere-egu2020-8763, 2020.
Intense geomagnetic storms can cause severe damage to electrical systems and communications. this work proposes a counting process with Weibull inter-occurrence times in order to estimate the probability of extreme geomagnetic events. It is found that the scale parameter of the inter-occurrence time distribution grows exponentially with the absolute value of the intensity threshold defining the storm, whereas the shape parameter keeps rather constant. The model is able to forecast the probability of occurrence of an event for a given intensity threshold; in particular, the probability of occurrence on the next decade of an extreme event of a magnitude comparable or larger than the well-known Carrington event of 1859 is explored, and estimated to be between 0.46% and 1.88% (with a 95% confidence), a much lower value than those reported in the existing literature.
How to cite: Serra, I., Moriña, D., Puig, P., and Corral, Á.: Probability estimation of a Carrington-like geomagnetic storm, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8763, https://doi.org/10.5194/egusphere-egu2020-8763, 2020.
EGU2020-13714 | Displays | NP4.1
Automatic transient signal detection and volcanic tremor extraction using music information retrieval strategiesZahra Zali, Frank Scherbaum, Matthias Ohrnberger, and Fabrice Cotton
Volcanic tremor is one of the most important signal in volcano seismology because of its potential to be a tool for forecasting eruptions and better understanding of underlying volcanic process. Despite different suggested mechanisms for volcanic tremor generation, the exact process of that is not well understood yet. This signal usually comes along with large number of earthquakes happening during unrest period that affect the shape and amplitude of tremor. A delicate signal processing is required to separate earthquakes and other transient signals from seismic waveform to derive a time series of volcanic tremor which can provide a new insight into tremor source investigations. Exploiting the idea of harmonic and percussive separation in musical signal processing we have developed a method to extract volcanic tremor and transient events from the seismic signal. By using the concept of periodicity as underlying generation process of tremor, we are able to extract the volcanic tremor signal based on the self similarity properties of spectra in time-frequency domain. The separation process results in two spectrograms representing repeating (long-lasting) and non-repeating (short-lived) patterns.
From the spectrogram of the repeating pattern we reconstruct the signal in time domain by adding the original spectrogram’s phase information, thus creating an modified version of the long-lasting tremor signal.
Further, we can derive a characteristic function for transient events by integrating the amplitude of the non-repeating spectrogram in each time frame. This function has non zero value in transient event instances and zero value in time periods devoid of such events. Considering transient events as earthquakes we apply an onset detector to time first arrivals of the transient signal by using the slope of the function. First we determine local maxima of the function showing good correspondence to even the tiniest transient signals. From the peak locations we calculate the slope of each point within a period of 6 seconds preceding each peak. The uncertainty of positive P peaks is up to 0.32 seconds which is equal to the hope size of the calculated spectrogram. The advantage of timing earthquakes through this method is the ability of detecting very low seismic events, although due to the small window size of short time Fourier transform the process is time consuming. The result of this study is promising, while further testing is on-going to validate the method as well as determine applications and limitations.
How to cite: Zali, Z., Scherbaum, F., Ohrnberger, M., and Cotton, F.: Automatic transient signal detection and volcanic tremor extraction using music information retrieval strategies, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13714, https://doi.org/10.5194/egusphere-egu2020-13714, 2020.
Volcanic tremor is one of the most important signal in volcano seismology because of its potential to be a tool for forecasting eruptions and better understanding of underlying volcanic process. Despite different suggested mechanisms for volcanic tremor generation, the exact process of that is not well understood yet. This signal usually comes along with large number of earthquakes happening during unrest period that affect the shape and amplitude of tremor. A delicate signal processing is required to separate earthquakes and other transient signals from seismic waveform to derive a time series of volcanic tremor which can provide a new insight into tremor source investigations. Exploiting the idea of harmonic and percussive separation in musical signal processing we have developed a method to extract volcanic tremor and transient events from the seismic signal. By using the concept of periodicity as underlying generation process of tremor, we are able to extract the volcanic tremor signal based on the self similarity properties of spectra in time-frequency domain. The separation process results in two spectrograms representing repeating (long-lasting) and non-repeating (short-lived) patterns.
From the spectrogram of the repeating pattern we reconstruct the signal in time domain by adding the original spectrogram’s phase information, thus creating an modified version of the long-lasting tremor signal.
Further, we can derive a characteristic function for transient events by integrating the amplitude of the non-repeating spectrogram in each time frame. This function has non zero value in transient event instances and zero value in time periods devoid of such events. Considering transient events as earthquakes we apply an onset detector to time first arrivals of the transient signal by using the slope of the function. First we determine local maxima of the function showing good correspondence to even the tiniest transient signals. From the peak locations we calculate the slope of each point within a period of 6 seconds preceding each peak. The uncertainty of positive P peaks is up to 0.32 seconds which is equal to the hope size of the calculated spectrogram. The advantage of timing earthquakes through this method is the ability of detecting very low seismic events, although due to the small window size of short time Fourier transform the process is time consuming. The result of this study is promising, while further testing is on-going to validate the method as well as determine applications and limitations.
How to cite: Zali, Z., Scherbaum, F., Ohrnberger, M., and Cotton, F.: Automatic transient signal detection and volcanic tremor extraction using music information retrieval strategies, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13714, https://doi.org/10.5194/egusphere-egu2020-13714, 2020.
EGU2020-17092 | Displays | NP4.1
Spatio-temporal missing data reconstruction in satellite displacement measurement time seriesAlexandre Hippert-Ferrer, Yajing Yan, and Philippe Bolon
Time series analysis constitutes a thriving subject in satellite image derived displacement measurement, especially since the launching of Sentinel satellites which provide free and systematic satellite image acquisitions with extended spatial coverage and reduced revisiting time. Large volumes of satellite images are available for monitoring numerous targets at the Earth’s surface, which allows for significant improvements of the displacement measurement precision by means of advanced multi-temporal methods. However, satellite image derived displacement time series can suffer from missing data, which is mainly due to technical limitations of the ground displacement computation methods (e.g. offset tracking) and surface property changes from one acquisition to another. Missing data can hinder the full exploitation of the displacement time series, which can potentially weaken both knowledge and interpretation of the physical phenomenon under observation. Therefore, an efficient missing data imputation approach seems of particular importance for data completeness. In this work, an iterative method, namely extended Expectation Maximization - Empirical Orthogonal Functions (EM-EOF) is proposed to retrieve missing values in satellite image derived displacement time series. The method uses both spatial and temporal correlations in the displacement time series for reconstruction. For this purpose, the spatio-temporal covariance of the time series is iteratively estimated and decomposed into different EOF modes by solving the eigenvalue problem in an EM-like scheme. To determine the optimal number of EOFs modes, two robust metrics, the cross validation error and a confidence index obtained from eigenvalue uncertainty, are defined. The former metric is also used as a convergence criterion of the iterative update of the missing values. Synthetic simulations are first performed in order to demonstrate the ability of missing data imputation of the extended EM-EOF method in cases of complex displacement, gaps and noise behaviors. Then, the method is applied to time series of offset tracking displacement measurement of Sentinel-2 images acquired between January 2017 and September 2019 over Fox Glacier in the Southern Alps of New Zealand. Promising results confirm the efficiency of the extended EM-EOF method in missing data imputation of satellite image derived displacement time series.
How to cite: Hippert-Ferrer, A., Yan, Y., and Bolon, P.: Spatio-temporal missing data reconstruction in satellite displacement measurement time series, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17092, https://doi.org/10.5194/egusphere-egu2020-17092, 2020.
Time series analysis constitutes a thriving subject in satellite image derived displacement measurement, especially since the launching of Sentinel satellites which provide free and systematic satellite image acquisitions with extended spatial coverage and reduced revisiting time. Large volumes of satellite images are available for monitoring numerous targets at the Earth’s surface, which allows for significant improvements of the displacement measurement precision by means of advanced multi-temporal methods. However, satellite image derived displacement time series can suffer from missing data, which is mainly due to technical limitations of the ground displacement computation methods (e.g. offset tracking) and surface property changes from one acquisition to another. Missing data can hinder the full exploitation of the displacement time series, which can potentially weaken both knowledge and interpretation of the physical phenomenon under observation. Therefore, an efficient missing data imputation approach seems of particular importance for data completeness. In this work, an iterative method, namely extended Expectation Maximization - Empirical Orthogonal Functions (EM-EOF) is proposed to retrieve missing values in satellite image derived displacement time series. The method uses both spatial and temporal correlations in the displacement time series for reconstruction. For this purpose, the spatio-temporal covariance of the time series is iteratively estimated and decomposed into different EOF modes by solving the eigenvalue problem in an EM-like scheme. To determine the optimal number of EOFs modes, two robust metrics, the cross validation error and a confidence index obtained from eigenvalue uncertainty, are defined. The former metric is also used as a convergence criterion of the iterative update of the missing values. Synthetic simulations are first performed in order to demonstrate the ability of missing data imputation of the extended EM-EOF method in cases of complex displacement, gaps and noise behaviors. Then, the method is applied to time series of offset tracking displacement measurement of Sentinel-2 images acquired between January 2017 and September 2019 over Fox Glacier in the Southern Alps of New Zealand. Promising results confirm the efficiency of the extended EM-EOF method in missing data imputation of satellite image derived displacement time series.
How to cite: Hippert-Ferrer, A., Yan, Y., and Bolon, P.: Spatio-temporal missing data reconstruction in satellite displacement measurement time series, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17092, https://doi.org/10.5194/egusphere-egu2020-17092, 2020.
EGU2020-3744 | Displays | NP4.1
Inference On Streamflow Predictability Using Horizontal Visibility Graph Based NetworksGanesh Ghimire, Navid Jadidoleslam, Witold Krajewski, and Anastasios Tsonis
Streamflow is a dynamical process that integrates water movement in space and time within basin boundaries. The authors characterize the dynamics associated with streamflow time series data from about seventy-one U.S. Geological Survey (USGS) stream-gauge stations in the state of Iowa. They employ a novel approach called visibility graph (VG). It uses the concept of mapping time series into complex networks to investigate the time evolutionary behavior of dynamical system. The authors focus on a simple variant of VG algorithm called horizontal visibility graph (HVG). The tracking of dynamics and hence, the predictability of streamflow processes, are carried out by extracting two key pieces of information called characteristic exponent, λ of degree distribution and global clustering coefficient, GC pertaining to HVG derived network. The authors use these two measures to identify whether streamflow process has its origin in random or chaotic processes. They show that the characterization of streamflow dynamics is sensitive to data attributes. Through a systematic and comprehensive analysis, the authors illustrate that streamflow dynamics characterization is sensitive to the normalization, and the time-scale of streamflow time-series. At daily scale, streamflow at all stations used in the analysis, reveals randomness with strong spatial scale (basin size) dependence. This has implications for predictability of streamflow and floods. The authors demonstrate that dynamics transition through potentially chaotic to randomly correlated process as the averaging time-scale increases. Finally, the temporal trends of λ and GC are statistically significant at about 40% of the total number of stations analyzed. Attributing this trend to factors such as changing climate or land use requires further research.
How to cite: Ghimire, G., Jadidoleslam, N., Krajewski, W., and Tsonis, A.: Inference On Streamflow Predictability Using Horizontal Visibility Graph Based Networks, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3744, https://doi.org/10.5194/egusphere-egu2020-3744, 2020.
Streamflow is a dynamical process that integrates water movement in space and time within basin boundaries. The authors characterize the dynamics associated with streamflow time series data from about seventy-one U.S. Geological Survey (USGS) stream-gauge stations in the state of Iowa. They employ a novel approach called visibility graph (VG). It uses the concept of mapping time series into complex networks to investigate the time evolutionary behavior of dynamical system. The authors focus on a simple variant of VG algorithm called horizontal visibility graph (HVG). The tracking of dynamics and hence, the predictability of streamflow processes, are carried out by extracting two key pieces of information called characteristic exponent, λ of degree distribution and global clustering coefficient, GC pertaining to HVG derived network. The authors use these two measures to identify whether streamflow process has its origin in random or chaotic processes. They show that the characterization of streamflow dynamics is sensitive to data attributes. Through a systematic and comprehensive analysis, the authors illustrate that streamflow dynamics characterization is sensitive to the normalization, and the time-scale of streamflow time-series. At daily scale, streamflow at all stations used in the analysis, reveals randomness with strong spatial scale (basin size) dependence. This has implications for predictability of streamflow and floods. The authors demonstrate that dynamics transition through potentially chaotic to randomly correlated process as the averaging time-scale increases. Finally, the temporal trends of λ and GC are statistically significant at about 40% of the total number of stations analyzed. Attributing this trend to factors such as changing climate or land use requires further research.
How to cite: Ghimire, G., Jadidoleslam, N., Krajewski, W., and Tsonis, A.: Inference On Streamflow Predictability Using Horizontal Visibility Graph Based Networks, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3744, https://doi.org/10.5194/egusphere-egu2020-3744, 2020.
EGU2020-20335 | Displays | NP4.1
Fusion and mining of glacier surface flow velocity time seriesLaurane Charrier, Yajing Yan, Elise Koeniguer, Emmanuel Trouvé, Romain Millan, Jérémie Mouginot, and Anna Derkacheva
Glacier response to climate change results in natural hazards, sea level rise and changes in freshwater resources. To evaluate this response, glacier surface flow velocity constitutes a crucial parameter to study. Nowadays, more and more velocity maps at regional or global scales issued from satellite SAR and/or optical images tend to be available online or on-demand. Such amount of data requires appropriate data fusion strategies in order to generate displacement time series with improved precision and spatio-temporal coverage. The improved displacement time series can then be used by advanced multi-temporal analysis approaches for further physical interpretations of the phenomenon under observation. In this work, time series of Sentinel-2 (10~m resolution, every 5 days), Landsat-8 (15~m resolution, every 16 days) and Venus (5~m resolution, every 2 days) images acquired between January 2017 and September 2018, over the Fox glacier in the Southern Alps of New Zealand are investigated. Velocities are generated with an offset tracking technique using an automatic processing chain for every possible repeat cycles (2 days-100 days and 300 days to 400 days). Thousands of velocity maps are available, and they are subject to both uncertainty and data gaps. In order to produce a displacement time series as precise/complete as possible , we propose three fusion strategies: 1) use all the available Sentinel-2 displacement maps with different time spans. The goal is to construct a time series of displacement with respect to a common master by means of an inversion 2) take only Sentinel-2 displacement maps with as small time spans as possible, at the same time, keep as much as possible redundancy in the network to be able to construct a common master displacement time series by inversion 3) follow the previous strategy but use all available displacement maps from 3 sensors, with different temporal sampling and measurement precision taken into account. Afterwards, the common master displacement time series will be analysed by a data mining approach in order to extract unusual spatio-temporal patterns in the time series.
How to cite: Charrier, L., Yan, Y., Koeniguer, E., Trouvé, E., Millan, R., Mouginot, J., and Derkacheva, A.: Fusion and mining of glacier surface flow velocity time series, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20335, https://doi.org/10.5194/egusphere-egu2020-20335, 2020.
Glacier response to climate change results in natural hazards, sea level rise and changes in freshwater resources. To evaluate this response, glacier surface flow velocity constitutes a crucial parameter to study. Nowadays, more and more velocity maps at regional or global scales issued from satellite SAR and/or optical images tend to be available online or on-demand. Such amount of data requires appropriate data fusion strategies in order to generate displacement time series with improved precision and spatio-temporal coverage. The improved displacement time series can then be used by advanced multi-temporal analysis approaches for further physical interpretations of the phenomenon under observation. In this work, time series of Sentinel-2 (10~m resolution, every 5 days), Landsat-8 (15~m resolution, every 16 days) and Venus (5~m resolution, every 2 days) images acquired between January 2017 and September 2018, over the Fox glacier in the Southern Alps of New Zealand are investigated. Velocities are generated with an offset tracking technique using an automatic processing chain for every possible repeat cycles (2 days-100 days and 300 days to 400 days). Thousands of velocity maps are available, and they are subject to both uncertainty and data gaps. In order to produce a displacement time series as precise/complete as possible , we propose three fusion strategies: 1) use all the available Sentinel-2 displacement maps with different time spans. The goal is to construct a time series of displacement with respect to a common master by means of an inversion 2) take only Sentinel-2 displacement maps with as small time spans as possible, at the same time, keep as much as possible redundancy in the network to be able to construct a common master displacement time series by inversion 3) follow the previous strategy but use all available displacement maps from 3 sensors, with different temporal sampling and measurement precision taken into account. Afterwards, the common master displacement time series will be analysed by a data mining approach in order to extract unusual spatio-temporal patterns in the time series.
How to cite: Charrier, L., Yan, Y., Koeniguer, E., Trouvé, E., Millan, R., Mouginot, J., and Derkacheva, A.: Fusion and mining of glacier surface flow velocity time series, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20335, https://doi.org/10.5194/egusphere-egu2020-20335, 2020.
EGU2020-2274 | Displays | NP4.1
A new singular spectrum analysis approach for processing incomplete time series polluted by multiplicative noiseYunzhong Shen, Fengwei Wang, and Qiujie Chen
Since a time series is usually incomplete, the missing data are usually interpolated before employing singular spectrum analysis (SSA). We develop a new SSA for processing incomplete time series based on the property that an original time series can be reproduced from its principal components which are then estimated based on minimum norm criterion. When an incomplete time series is polluted by multiplicative noise, we first convert the multiplicative noise to additive noise by multiplying the signal estimate of the time series, then process the time series with weighted SSA, where the weight factor is determined according to the variance of additive noise, since the converted additive noise is heterogeneous. The proposed SSA approach is employed to process the real incomplete time series data of suspended-sediment concentration from San Francisco Bay compared to the traditional SSA and homomorphic log-transformation SSA approach. The first 10 principal components derived by our proposed SSA approach can capture more of the total variance and with less fitting error than traditional SSA approach and homomorphic log-transformation SSA approach. Furthermore, the results from the simulation cases conform that our proposed SSA outperform both traditional and homomorphic log-transformation SSA approaches.
How to cite: Shen, Y., Wang, F., and Chen, Q.: A new singular spectrum analysis approach for processing incomplete time series polluted by multiplicative noise, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2274, https://doi.org/10.5194/egusphere-egu2020-2274, 2020.
Since a time series is usually incomplete, the missing data are usually interpolated before employing singular spectrum analysis (SSA). We develop a new SSA for processing incomplete time series based on the property that an original time series can be reproduced from its principal components which are then estimated based on minimum norm criterion. When an incomplete time series is polluted by multiplicative noise, we first convert the multiplicative noise to additive noise by multiplying the signal estimate of the time series, then process the time series with weighted SSA, where the weight factor is determined according to the variance of additive noise, since the converted additive noise is heterogeneous. The proposed SSA approach is employed to process the real incomplete time series data of suspended-sediment concentration from San Francisco Bay compared to the traditional SSA and homomorphic log-transformation SSA approach. The first 10 principal components derived by our proposed SSA approach can capture more of the total variance and with less fitting error than traditional SSA approach and homomorphic log-transformation SSA approach. Furthermore, the results from the simulation cases conform that our proposed SSA outperform both traditional and homomorphic log-transformation SSA approaches.
How to cite: Shen, Y., Wang, F., and Chen, Q.: A new singular spectrum analysis approach for processing incomplete time series polluted by multiplicative noise, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2274, https://doi.org/10.5194/egusphere-egu2020-2274, 2020.
EGU2020-1030 | Displays | NP4.1
Disentangling synchrony from serial dependency in complex climate networks: Comparing Event Synchronization and Event Coincidence AnalysisAdrian Odenweller and Reik Donner
The quantification of synchronization phenomena of extreme events has recently aroused a great deal of interest in various disciplines. Climatological studies therefore commonly draw on spatially embedded climate networks in conjunction with nonlinear time series analysis. Among the multitude of similarity measures available to construct climate networks, Event Synchronization and Event Coincidence Analysis (ECA) stand out as two conceptually and computationally simple nonlinear methods. While ES defines synchrony in a data adaptive local way that does not distinguish between different time scales, ECA requires the selection of a specific time scale for synchrony detection.
Herein, we provide evidence that, due to its parameter-free structure, ES has structural difficulties to disentangle synchrony from serial dependency, whereas ECA is less prone to such biases. We use coupled autoregressive processes to numerically study the sensitivity of results from both methods to changes of coupling and autoregressive parameters. This reveals that ES has difficulties to detect synchronies if events tend to occur temporally clustered, which can be expected from climate time series with extreme events exceeding certain percentiles.
These conceptual concerns are not only reproducible in numerical simulations, but also have implications for real world data. We construct a climate network from satellite-based precipitation data of the Tropical Rainfall Measuring Mission (TRMM) for the Indian Summer Monsoon, thereby reproducing results of previously published studies. We demonstrate that there is an undesirable link between the fraction of events on subsequent days and the degree density at each grid point of the climate network. This indicates that the explanatory power of ES climate networks might be hampered since trivial local properties of the underlying time series significantly predetermine the final network structure, which holds especially true for areas that had previously been reported as important for governing monsoon dynamics at large spatial scales. In contrast, ECA does not appear to be as vulnerable to these biases and additionally allows to trace the spatiotemporal propagation of synchrony in climate networks.
Our analysis rests on corrected versions of both methods that alleviate different normalization problems of the original definitions, which is especially important for short time series. Our finding suggest that careful event detection and diligent preprocessing is recommended when applying ES, while this is less crucial for ECA. Results obtained from ES climate networks therefore need to be interpreted with caution.
How to cite: Odenweller, A. and Donner, R.: Disentangling synchrony from serial dependency in complex climate networks: Comparing Event Synchronization and Event Coincidence Analysis, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1030, https://doi.org/10.5194/egusphere-egu2020-1030, 2020.
The quantification of synchronization phenomena of extreme events has recently aroused a great deal of interest in various disciplines. Climatological studies therefore commonly draw on spatially embedded climate networks in conjunction with nonlinear time series analysis. Among the multitude of similarity measures available to construct climate networks, Event Synchronization and Event Coincidence Analysis (ECA) stand out as two conceptually and computationally simple nonlinear methods. While ES defines synchrony in a data adaptive local way that does not distinguish between different time scales, ECA requires the selection of a specific time scale for synchrony detection.
Herein, we provide evidence that, due to its parameter-free structure, ES has structural difficulties to disentangle synchrony from serial dependency, whereas ECA is less prone to such biases. We use coupled autoregressive processes to numerically study the sensitivity of results from both methods to changes of coupling and autoregressive parameters. This reveals that ES has difficulties to detect synchronies if events tend to occur temporally clustered, which can be expected from climate time series with extreme events exceeding certain percentiles.
These conceptual concerns are not only reproducible in numerical simulations, but also have implications for real world data. We construct a climate network from satellite-based precipitation data of the Tropical Rainfall Measuring Mission (TRMM) for the Indian Summer Monsoon, thereby reproducing results of previously published studies. We demonstrate that there is an undesirable link between the fraction of events on subsequent days and the degree density at each grid point of the climate network. This indicates that the explanatory power of ES climate networks might be hampered since trivial local properties of the underlying time series significantly predetermine the final network structure, which holds especially true for areas that had previously been reported as important for governing monsoon dynamics at large spatial scales. In contrast, ECA does not appear to be as vulnerable to these biases and additionally allows to trace the spatiotemporal propagation of synchrony in climate networks.
Our analysis rests on corrected versions of both methods that alleviate different normalization problems of the original definitions, which is especially important for short time series. Our finding suggest that careful event detection and diligent preprocessing is recommended when applying ES, while this is less crucial for ECA. Results obtained from ES climate networks therefore need to be interpreted with caution.
How to cite: Odenweller, A. and Donner, R.: Disentangling synchrony from serial dependency in complex climate networks: Comparing Event Synchronization and Event Coincidence Analysis, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1030, https://doi.org/10.5194/egusphere-egu2020-1030, 2020.
EGU2020-12938 | Displays | NP4.1
Detecting dynamical anomalies in time series from different palaeoclimate proxy archives using windowed recurrence network analysisReik Donner and Jaqueline Lekscha
Analysing palaeoclimate proxy time series using windowed recurrence network analysis (wRNA) has been shown to provide valuable information on past climate variability. In turn, it has also been found that the robustness of the obtained results differs among proxies from different palaeoclimate archives. To systematically test the suitability of wRNA for studying different types of palaeoclimate proxy time series, we use the framework of forward proxy modelling. For this, we create artificial input time series with different properties and compare the areawise significant anomalies detected using wRNA of the input and the model output time series. Also, taking into account results for general filtering of different time series, we find that the variability of the network transitivity is altered for stochastic input time series while being rather robust for deterministic input. In terms of significant anomalies of the network transitivity, we observe that these anomalies may be missed by proxies from tree and lake archives after the non-linear filtering by the corresponding proxy system models. For proxies from speleothems, we additionally observe falsely identified significant anomalies that are not present in the input time series. Finally, for proxies from ice cores, the wRNA results show the best correspondence with those for the input data. Our results contribute to improve the interpretation of windowed recurrence network analysis results obtained from real-world palaeoclimate time series.
How to cite: Donner, R. and Lekscha, J.: Detecting dynamical anomalies in time series from different palaeoclimate proxy archives using windowed recurrence network analysis, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12938, https://doi.org/10.5194/egusphere-egu2020-12938, 2020.
Analysing palaeoclimate proxy time series using windowed recurrence network analysis (wRNA) has been shown to provide valuable information on past climate variability. In turn, it has also been found that the robustness of the obtained results differs among proxies from different palaeoclimate archives. To systematically test the suitability of wRNA for studying different types of palaeoclimate proxy time series, we use the framework of forward proxy modelling. For this, we create artificial input time series with different properties and compare the areawise significant anomalies detected using wRNA of the input and the model output time series. Also, taking into account results for general filtering of different time series, we find that the variability of the network transitivity is altered for stochastic input time series while being rather robust for deterministic input. In terms of significant anomalies of the network transitivity, we observe that these anomalies may be missed by proxies from tree and lake archives after the non-linear filtering by the corresponding proxy system models. For proxies from speleothems, we additionally observe falsely identified significant anomalies that are not present in the input time series. Finally, for proxies from ice cores, the wRNA results show the best correspondence with those for the input data. Our results contribute to improve the interpretation of windowed recurrence network analysis results obtained from real-world palaeoclimate time series.
How to cite: Donner, R. and Lekscha, J.: Detecting dynamical anomalies in time series from different palaeoclimate proxy archives using windowed recurrence network analysis, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12938, https://doi.org/10.5194/egusphere-egu2020-12938, 2020.
EGU2020-2705 | Displays | NP4.1
Analysis of long-term catchment data: a nonlinear perspectiveHolger Lange, Michael Hauhs, Katharina Funk, Sebastian Sippel, and Henning Meesenburg
We analyze time series from several forested headwater catchments located adjacent to each other in the Bramke valley, Harz mountains (Germany) which are monitored since decades for hydrology, hydrochemistry and forest growth. The data sets include meteorological variables, runoff rates, streamwater chemical concentrations, and others. The basic temporal resolution is daily for hydrometeorology and two-weekly for streamwater chemistry (in addition, standing biomass of a Norway spruce stand is measured every couple of years).
A model was calibrated and run for the streamflow from one of the catchments, based on precipitation, temperature and (simulated) evapotranspiration of the growing trees, to elucidate the effect of forest growth on catchment hydrology.
The catchments exhibit long-term changes and spatial gradients related to atmospheric deposition, management and changing climate. After providing a short multivariate summary of the dataset, we present several nonlinear metrics suitable to detect and quantify subtle changes and to describe different behavior, both between different variables from the same catchment, as well as for the same variable across catchments. The methods include, but are not limited to: Tarnopolski analysis, permutation entropy and complexity, q- and α-complexities, and Horizontal Visibility Graphs.
The detection of these changes is remarkable, because linear trends have already been removed prior to analysis. Hence, their presence reflects intrinsic changes in the patterns of the time series. The metrics also allow for a detailed model evaluation from a nonlinear perspective.
An important methodological aspect is the temporal resolution of the time series. We investigate the scaling behavior of the nonlinear metrics through aggregation or decimation to coarser resolutions and conclude on what the scaling behavior may imply for inverse (hydrological) modelling tasks.
How to cite: Lange, H., Hauhs, M., Funk, K., Sippel, S., and Meesenburg, H.: Analysis of long-term catchment data: a nonlinear perspective, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2705, https://doi.org/10.5194/egusphere-egu2020-2705, 2020.
We analyze time series from several forested headwater catchments located adjacent to each other in the Bramke valley, Harz mountains (Germany) which are monitored since decades for hydrology, hydrochemistry and forest growth. The data sets include meteorological variables, runoff rates, streamwater chemical concentrations, and others. The basic temporal resolution is daily for hydrometeorology and two-weekly for streamwater chemistry (in addition, standing biomass of a Norway spruce stand is measured every couple of years).
A model was calibrated and run for the streamflow from one of the catchments, based on precipitation, temperature and (simulated) evapotranspiration of the growing trees, to elucidate the effect of forest growth on catchment hydrology.
The catchments exhibit long-term changes and spatial gradients related to atmospheric deposition, management and changing climate. After providing a short multivariate summary of the dataset, we present several nonlinear metrics suitable to detect and quantify subtle changes and to describe different behavior, both between different variables from the same catchment, as well as for the same variable across catchments. The methods include, but are not limited to: Tarnopolski analysis, permutation entropy and complexity, q- and α-complexities, and Horizontal Visibility Graphs.
The detection of these changes is remarkable, because linear trends have already been removed prior to analysis. Hence, their presence reflects intrinsic changes in the patterns of the time series. The metrics also allow for a detailed model evaluation from a nonlinear perspective.
An important methodological aspect is the temporal resolution of the time series. We investigate the scaling behavior of the nonlinear metrics through aggregation or decimation to coarser resolutions and conclude on what the scaling behavior may imply for inverse (hydrological) modelling tasks.
How to cite: Lange, H., Hauhs, M., Funk, K., Sippel, S., and Meesenburg, H.: Analysis of long-term catchment data: a nonlinear perspective, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2705, https://doi.org/10.5194/egusphere-egu2020-2705, 2020.
EGU2020-11492 | Displays | NP4.1
Testing for Dynamical Dependence: Application to the Surface Mass Balance Over AntarcticaQuentin Dalaiden, Stephane Vannitsem, and Hugues Goosse
Dynamical dependence between key observables and the surface mass balance (SMB) over Antarctica is analyzed in two historical runs performed with the MPI‐ESM‐P and the CESM1‐CAM5 climate models. The approach used is a novel method allowing for evaluating the rate of information transfer between observables that goes beyond the classical correlation analysis and allows for directional characterization of dependence. It reveals that a large proportion of significant correlations do not lead to dependence. In addition, three coherent results concerning the dependence of SMB emerge from the analysis of both models: (i) The SMB over the Antarctic Plateau is mostly influenced by the surface temperature and sea ice concentration and not by large‐scale circulation changes; (ii) the SMB of the Weddell Sea and the Dronning Maud Land coasts are not influenced significantly by the surface temperature; and (iii) the Weddell Sea coast is not significantly influenced by the sea ice concentration.
How to cite: Dalaiden, Q., Vannitsem, S., and Goosse, H.: Testing for Dynamical Dependence: Application to the Surface Mass Balance Over Antarctica, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11492, https://doi.org/10.5194/egusphere-egu2020-11492, 2020.
Dynamical dependence between key observables and the surface mass balance (SMB) over Antarctica is analyzed in two historical runs performed with the MPI‐ESM‐P and the CESM1‐CAM5 climate models. The approach used is a novel method allowing for evaluating the rate of information transfer between observables that goes beyond the classical correlation analysis and allows for directional characterization of dependence. It reveals that a large proportion of significant correlations do not lead to dependence. In addition, three coherent results concerning the dependence of SMB emerge from the analysis of both models: (i) The SMB over the Antarctic Plateau is mostly influenced by the surface temperature and sea ice concentration and not by large‐scale circulation changes; (ii) the SMB of the Weddell Sea and the Dronning Maud Land coasts are not influenced significantly by the surface temperature; and (iii) the Weddell Sea coast is not significantly influenced by the sea ice concentration.
How to cite: Dalaiden, Q., Vannitsem, S., and Goosse, H.: Testing for Dynamical Dependence: Application to the Surface Mass Balance Over Antarctica, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11492, https://doi.org/10.5194/egusphere-egu2020-11492, 2020.
EGU2020-9270 * | Displays | NP4.1 | Highlight
Causal Discovery for Climate Time Series in the Presence of Unobserved VariablesAndreas Gerhardus and Jakob Runge
Scientific inquiry seeks to understand natural phenomena by understanding their underlying processes, i.e., by identifying cause and effect. In addition to mere scientific curiosity, an understanding of cause and effect relationships is necessary to predict the effect of changing dynamical regimes and for the attribution of extreme events to potential causes. It is thus an important question to ask how, in cases where controlled experiments are not feasible, causation can still be inferred from the statistical dependencies in observed time series.
A central obstacle for such an inference is the potential existence of unobserved causally relevant variables. Arguably, this is more likely to be the case than not, for example unmeasured deep oceanic variables in atmospheric processes. Unobserved variables can act as confounders (meaning they are a common cause of two or more observed variables) and thus introduce spurious, i.e., non-causal dependencies. Despite these complications, the last three decades have seen the development of so-called causal discovery algorithms (an example being FCI by Spirtes et al., 1999) that are often able to identify spurious associations and to distinguish them from genuine causation. This opens the possibility for a data-driven approach to infer cause and effect relationships among climate variables, thereby contributing to a better understanding of Earth's complex climate system.
These methods are, however, not yet well adapted to some specific challenges that climate time series often come with, e.g. strong autocorrelation, time lags and nonlinearities. To close this methodological gap, we generalize the ideas of the recent PCMCI causal discovery algorithm (Runge et al., 2019) to time series where unobserved causally relevant variables may exist (in contrast, PCMCI made the assumption of no confounding). Further, we present preliminary applications to modes of climate variability.
How to cite: Gerhardus, A. and Runge, J.: Causal Discovery for Climate Time Series in the Presence of Unobserved Variables, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9270, https://doi.org/10.5194/egusphere-egu2020-9270, 2020.
Scientific inquiry seeks to understand natural phenomena by understanding their underlying processes, i.e., by identifying cause and effect. In addition to mere scientific curiosity, an understanding of cause and effect relationships is necessary to predict the effect of changing dynamical regimes and for the attribution of extreme events to potential causes. It is thus an important question to ask how, in cases where controlled experiments are not feasible, causation can still be inferred from the statistical dependencies in observed time series.
A central obstacle for such an inference is the potential existence of unobserved causally relevant variables. Arguably, this is more likely to be the case than not, for example unmeasured deep oceanic variables in atmospheric processes. Unobserved variables can act as confounders (meaning they are a common cause of two or more observed variables) and thus introduce spurious, i.e., non-causal dependencies. Despite these complications, the last three decades have seen the development of so-called causal discovery algorithms (an example being FCI by Spirtes et al., 1999) that are often able to identify spurious associations and to distinguish them from genuine causation. This opens the possibility for a data-driven approach to infer cause and effect relationships among climate variables, thereby contributing to a better understanding of Earth's complex climate system.
These methods are, however, not yet well adapted to some specific challenges that climate time series often come with, e.g. strong autocorrelation, time lags and nonlinearities. To close this methodological gap, we generalize the ideas of the recent PCMCI causal discovery algorithm (Runge et al., 2019) to time series where unobserved causally relevant variables may exist (in contrast, PCMCI made the assumption of no confounding). Further, we present preliminary applications to modes of climate variability.
How to cite: Gerhardus, A. and Runge, J.: Causal Discovery for Climate Time Series in the Presence of Unobserved Variables, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9270, https://doi.org/10.5194/egusphere-egu2020-9270, 2020.
EGU2020-18778 | Displays | NP4.1
On the Ensemble Transfer Entropy Analysis of Non-Stationary Geophysical Time Series: The Case of Magnetospheric ResponseMirko Stumpo, Giuseppe Consolini, Tommaso Alberti, and Virgilio Quattrociocchi
The fundamental question what causes what has always been the motivating motto for natural sciences, being the study of causality a crucial point for characterizing dynamical relationships. In the framework of complex dynamical systems, both linear statistical tools and Granger causality models drastically fail to detect causal relationships between time series, while a powerful model-free statistical framework is offered by the information theory.
Here we discuss how to deal with the problem of measuring causal information in non-stationary complex systems by considering a local estimation of the information-theoretic functionals via an ensemble-based statistics. Then, its application for investigating the dynamical coupling and relationships between the solar wind and the Earth’s magnetosphere is also presented.
How to cite: Stumpo, M., Consolini, G., Alberti, T., and Quattrociocchi, V.: On the Ensemble Transfer Entropy Analysis of Non-Stationary Geophysical Time Series: The Case of Magnetospheric Response, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18778, https://doi.org/10.5194/egusphere-egu2020-18778, 2020.
The fundamental question what causes what has always been the motivating motto for natural sciences, being the study of causality a crucial point for characterizing dynamical relationships. In the framework of complex dynamical systems, both linear statistical tools and Granger causality models drastically fail to detect causal relationships between time series, while a powerful model-free statistical framework is offered by the information theory.
Here we discuss how to deal with the problem of measuring causal information in non-stationary complex systems by considering a local estimation of the information-theoretic functionals via an ensemble-based statistics. Then, its application for investigating the dynamical coupling and relationships between the solar wind and the Earth’s magnetosphere is also presented.
How to cite: Stumpo, M., Consolini, G., Alberti, T., and Quattrociocchi, V.: On the Ensemble Transfer Entropy Analysis of Non-Stationary Geophysical Time Series: The Case of Magnetospheric Response, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18778, https://doi.org/10.5194/egusphere-egu2020-18778, 2020.
EGU2020-7063 | Displays | NP4.1
New insights and best practices for the succesful use of Empirical Mode Decomposition, Iterative Filtering and derived algorithms in the decomposition of nonlinear and nonstationary signalsAntonio Cicone, Angela Stallone, Massimo Materassi, and Haomin Zhou
Nonlinear and nonstationary signals are ubiquitous in real life. Their time–frequency analysis and features extraction can help in solving open problems in many fields of research. Two decades ago, the Empirical Mode Decomposition (EMD) algorithm was introduced to tackle highly nonlinear and nonstationary signals. It consists of a local and adaptive data–driven method which relaxes several limitations of the standard Fourier transform and the wavelet Transform techniques, yielding an accurate time-frequency representation of a signal. Over the years, several variants of the EMD algorithm have been proposed to improve the original technique, such as the Ensemble Empirical Mode Decomposition (EEMD) and the Iterative Filtering (IF).
The versatility of these techniques has opened the door to their application in many applied fields, like geophysics, physics, medicine, and finance. Although the EMD– and IF–based techniques are more suitable than traditional methods for the analysis of nonlinear and nonstationary data, they could easily be misused if their known limitations, together with the assumptions they rely on, are not carefully considered. Here we call attention to some of the pitfalls encountered when implementing these techniques. Specifically, there are three critical factors that are often neglected: boundary effects; presence of spikes in the original signal; signals containing a high degree of stochasticity. We show how an inappropriate implementation of the EMD and IF methods could return an artefact–prone decomposition of the original signal. We conclude with best practice guidelines for researchers who intend to use these techniques for their signal analysis.
How to cite: Cicone, A., Stallone, A., Materassi, M., and Zhou, H.: New insights and best practices for the succesful use of Empirical Mode Decomposition, Iterative Filtering and derived algorithms in the decomposition of nonlinear and nonstationary signals , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7063, https://doi.org/10.5194/egusphere-egu2020-7063, 2020.
Nonlinear and nonstationary signals are ubiquitous in real life. Their time–frequency analysis and features extraction can help in solving open problems in many fields of research. Two decades ago, the Empirical Mode Decomposition (EMD) algorithm was introduced to tackle highly nonlinear and nonstationary signals. It consists of a local and adaptive data–driven method which relaxes several limitations of the standard Fourier transform and the wavelet Transform techniques, yielding an accurate time-frequency representation of a signal. Over the years, several variants of the EMD algorithm have been proposed to improve the original technique, such as the Ensemble Empirical Mode Decomposition (EEMD) and the Iterative Filtering (IF).
The versatility of these techniques has opened the door to their application in many applied fields, like geophysics, physics, medicine, and finance. Although the EMD– and IF–based techniques are more suitable than traditional methods for the analysis of nonlinear and nonstationary data, they could easily be misused if their known limitations, together with the assumptions they rely on, are not carefully considered. Here we call attention to some of the pitfalls encountered when implementing these techniques. Specifically, there are three critical factors that are often neglected: boundary effects; presence of spikes in the original signal; signals containing a high degree of stochasticity. We show how an inappropriate implementation of the EMD and IF methods could return an artefact–prone decomposition of the original signal. We conclude with best practice guidelines for researchers who intend to use these techniques for their signal analysis.
How to cite: Cicone, A., Stallone, A., Materassi, M., and Zhou, H.: New insights and best practices for the succesful use of Empirical Mode Decomposition, Iterative Filtering and derived algorithms in the decomposition of nonlinear and nonstationary signals , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7063, https://doi.org/10.5194/egusphere-egu2020-7063, 2020.
EGU2020-11461 | Displays | NP4.1
Advanced Exploratory Analysis of Air Pollution Multivariate Spatio-Temporal DataMikhail Kanevski, Federico Amato, and Fabian Guignard
The research deals with an application of advanced exploratory tools to study hourly spatio-temporal air pollution data collected by NABEL monitoring network in Switzerland. Data analyzed consist of several pollutants, mainly NO2, O3, PM2.5, measured during last two years at 16 stations distributed over the country. The data are considered in two different ways: 1) as multivariate time series measured at the same station (different pollutants and environmental variables, like temperature), 2) as a spatially distributed time series of the same pollutant. In the first case, it is interesting to study both univariate and multivariate time series and their complexity. In the second case, similarity between time series distributed in space can signify the similar underlying phenomena and environmental conditions giving rise to the pollution. An important aspect of the data is that they are collected at the places of different land use classes – urban, suburban, rural etc., which helps in understanding and interpretation of the results.
Nowadays, unsupervised learning algorithms are widely applied in intelligent exploratory data analysis. Well known tasks of unsupervised learning include manifold learning, dimensionality reduction and clustering. In the present research, intrinsic and fractal dimensions, measures characterizing the similarity and redundancy in data and machine learning clustering algorithms were adapted and applied. The results obtained give a new and important information on the air pollution spatio-temporal patterns. The following results, between others, can be mentioned: 1) some measures of similarity (e.g., complexity-independent distance) are efficient in discriminating between time series; 2) intrinsic dimension, characterizing the ensemble of monitoring data, is pollutant dependent; 3) clustering of time series observed can be interpreted using the available information on land use.
How to cite: Kanevski, M., Amato, F., and Guignard, F.: Advanced Exploratory Analysis of Air Pollution Multivariate Spatio-Temporal Data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11461, https://doi.org/10.5194/egusphere-egu2020-11461, 2020.
The research deals with an application of advanced exploratory tools to study hourly spatio-temporal air pollution data collected by NABEL monitoring network in Switzerland. Data analyzed consist of several pollutants, mainly NO2, O3, PM2.5, measured during last two years at 16 stations distributed over the country. The data are considered in two different ways: 1) as multivariate time series measured at the same station (different pollutants and environmental variables, like temperature), 2) as a spatially distributed time series of the same pollutant. In the first case, it is interesting to study both univariate and multivariate time series and their complexity. In the second case, similarity between time series distributed in space can signify the similar underlying phenomena and environmental conditions giving rise to the pollution. An important aspect of the data is that they are collected at the places of different land use classes – urban, suburban, rural etc., which helps in understanding and interpretation of the results.
Nowadays, unsupervised learning algorithms are widely applied in intelligent exploratory data analysis. Well known tasks of unsupervised learning include manifold learning, dimensionality reduction and clustering. In the present research, intrinsic and fractal dimensions, measures characterizing the similarity and redundancy in data and machine learning clustering algorithms were adapted and applied. The results obtained give a new and important information on the air pollution spatio-temporal patterns. The following results, between others, can be mentioned: 1) some measures of similarity (e.g., complexity-independent distance) are efficient in discriminating between time series; 2) intrinsic dimension, characterizing the ensemble of monitoring data, is pollutant dependent; 3) clustering of time series observed can be interpreted using the available information on land use.
How to cite: Kanevski, M., Amato, F., and Guignard, F.: Advanced Exploratory Analysis of Air Pollution Multivariate Spatio-Temporal Data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11461, https://doi.org/10.5194/egusphere-egu2020-11461, 2020.
EGU2020-3374 | Displays | NP4.1
Thirteen years of hindsight into hydrological and sediment dynamics of a humid badlands catchmentCarmelo Juez and Estela Nadal-Romero
Sediment transport is the major driver of changes in most catchments systems. Beyond landscape evolution and river geomorphology, sediment dynamics are an important component of a number of physical, chemical and biological processes in river basins. Sediments thus impact the ecology of rivers, sustainability of human infrastructure and basin level fluxes of nutrients and carbon. For this reason, it is important to understand the temporal sediment response of mountain catchments regarding precipitation and run-off. This response is not unique and features intra-annual, annual and multi-year scales components. In this research, we analyse a humid mountain badland area located in the Central Spanish Pyrenees. This typology of badlands is characterized by its non-linearity and non-stationary precipitation and run-off cycles, which ultimately lead to complex sediment dynamics and yields. Based on spectral frequency analysis and wavelet decomposition we were able to determine the dominant time scales of the local hydrological and sediment dynamics. Intra-annual and annual time scales were linked with the climatological characteristics of the catchment site. The multi-year response in the sediment yields reveals the importance of the sediment storage/depletion cycle of the catchment. The frequency and amplitude of precipitation, run-off and sediment yields fluctuations were accurately predicted with the spectral frequency analysis and wavelet decomposition technique used.
How to cite: Juez, C. and Nadal-Romero, E.: Thirteen years of hindsight into hydrological and sediment dynamics of a humid badlands catchment , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3374, https://doi.org/10.5194/egusphere-egu2020-3374, 2020.
Sediment transport is the major driver of changes in most catchments systems. Beyond landscape evolution and river geomorphology, sediment dynamics are an important component of a number of physical, chemical and biological processes in river basins. Sediments thus impact the ecology of rivers, sustainability of human infrastructure and basin level fluxes of nutrients and carbon. For this reason, it is important to understand the temporal sediment response of mountain catchments regarding precipitation and run-off. This response is not unique and features intra-annual, annual and multi-year scales components. In this research, we analyse a humid mountain badland area located in the Central Spanish Pyrenees. This typology of badlands is characterized by its non-linearity and non-stationary precipitation and run-off cycles, which ultimately lead to complex sediment dynamics and yields. Based on spectral frequency analysis and wavelet decomposition we were able to determine the dominant time scales of the local hydrological and sediment dynamics. Intra-annual and annual time scales were linked with the climatological characteristics of the catchment site. The multi-year response in the sediment yields reveals the importance of the sediment storage/depletion cycle of the catchment. The frequency and amplitude of precipitation, run-off and sediment yields fluctuations were accurately predicted with the spectral frequency analysis and wavelet decomposition technique used.
How to cite: Juez, C. and Nadal-Romero, E.: Thirteen years of hindsight into hydrological and sediment dynamics of a humid badlands catchment , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3374, https://doi.org/10.5194/egusphere-egu2020-3374, 2020.
EGU2020-708 | Displays | NP4.1
Unified Scaling Law for Earthquakes: space-time dependent assessment in Kamchatka regionAnastasia Nekrasova and Vladimir Kossobokov
The observed variability of seismic dynamics of the Kamchatka Region is characterized in terms of several moving averages, including (i) seismic rate, (ii) the Benioff strain release, (iii) inter-event time, τ, and (iv) the USLE control parameter, η (where USLE stands for Unified Scaling Law for Earthquakes, i.e. a generalization of the Gutenberg-Richter relationship accounting for naturally fractal distribution of earthquake loci, which states that the distribution of inter-event times τ depends only on the value of variable η).
The variability of seismic dynamics have been evaluated and compared at each of four out of ten separate seismic focal zones of the Kamchatka region and the adjacent areas defined by Levina et al. (2013), i.e., (1) seismic focal zone of the Kuril and South Kamchatka, (2) the northern part of the Kamchatka seismic focal zone, (3) commander segment of the Aleutian arc; and (4) the continental region of Kamchatka. In particular, we considered all magnitude 3.5 or larger earthquakes in 1996-2019 available from open data catalog of the Kamchatka Branch of GS RAS, Earthquakes Catalogue for Kamchatka and the Commander Islands (1962–present) http://sdis.emsd.ru/info/earthquakes/catalogue.ph).
How to cite: Nekrasova, A. and Kossobokov, V.: Unified Scaling Law for Earthquakes: space-time dependent assessment in Kamchatka region, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-708, https://doi.org/10.5194/egusphere-egu2020-708, 2020.
The observed variability of seismic dynamics of the Kamchatka Region is characterized in terms of several moving averages, including (i) seismic rate, (ii) the Benioff strain release, (iii) inter-event time, τ, and (iv) the USLE control parameter, η (where USLE stands for Unified Scaling Law for Earthquakes, i.e. a generalization of the Gutenberg-Richter relationship accounting for naturally fractal distribution of earthquake loci, which states that the distribution of inter-event times τ depends only on the value of variable η).
The variability of seismic dynamics have been evaluated and compared at each of four out of ten separate seismic focal zones of the Kamchatka region and the adjacent areas defined by Levina et al. (2013), i.e., (1) seismic focal zone of the Kuril and South Kamchatka, (2) the northern part of the Kamchatka seismic focal zone, (3) commander segment of the Aleutian arc; and (4) the continental region of Kamchatka. In particular, we considered all magnitude 3.5 or larger earthquakes in 1996-2019 available from open data catalog of the Kamchatka Branch of GS RAS, Earthquakes Catalogue for Kamchatka and the Commander Islands (1962–present) http://sdis.emsd.ru/info/earthquakes/catalogue.ph).
How to cite: Nekrasova, A. and Kossobokov, V.: Unified Scaling Law for Earthquakes: space-time dependent assessment in Kamchatka region, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-708, https://doi.org/10.5194/egusphere-egu2020-708, 2020.
NP5.1 – Data Assimilation, Predictability, Error Identification and Uncertainty Quantification in Geosciences
EGU2020-332 | Displays | NP5.1 | Highlight
Idealised satellite data assimilation experiments with clouds and precipitationLuca Cantarello, Onno Bokhove, Gordon Inverarity, Stefano Migliorini, and Steve Tobias
Operational data assimilation (DA) schemes rely significantly on satellite observations with much research aimed at their optimisation, leading to a great deal of progress. Here, we investigate the impact of the spatial-temporal variability of satellite observations for DA: is there a case for concentrating effort into the assimilation of small-scale convective features over the large-scale dynamics, or vice versa?
We conduct our study in an isentropic one-and-a-half layer model that mimics convection and precipitation, a revised and more realistic version of the idealised model based on the shallow water equations in [1,2]. Forecast-assimilation experiments are performed by means of a twin-setting configuration, in which pseudo-observations from a high-resolution nature run are combined with lower-resolution forecasts. The DA algorithm used is the deterministic Ensemble Kalman Filter (see [3]). We focus our research on polar-orbit satellites regarding emitted microwave radiation.
We have developed a new observation operator and a representative observing system in which both ground and satellite observations can be assimilated. The convection thresholds in the model are used as a proxy for cloud formation, clouds, and precipitation. To imitate the use of weighting functions in real satellite applications, radiance values are computed as a weighted sum with contributions from both layers. In the presence of clouds and/or precipitation, we model the response of passive microwave radiation to either precipitating or non-precipitating clouds. The horizontal resolution of satellite observations can be varied to investigate the impact of scale-dependency on the analysis.
New, preliminary results from experiments including both transverse jets and rotation in a periodic domain will be reported and discussed.
References:
[1] Kent, T., Bokhove, O., & Tobias, S. (2017). Dynamics of an idealized fluid model for investigating convective-scale data assimilation. Tellus A: Dynamic Meteorology and Oceanography, 69(1), 1369332.
[2] Kent, T. (2016). An idealised fluid model for convective-scale NWP: dynamics and data assimilation (Doctoral dissertation, PhD Thesis, University of Leeds).
[3] Sakov, P., & Oke, P. R. (2008). A deterministic formulation of the ensemble Kalman filter: an alternative to ensemble square root filters. Tellus A: Dynamic Meteorology and Oceanography, 60(2), 361-371.
How to cite: Cantarello, L., Bokhove, O., Inverarity, G., Migliorini, S., and Tobias, S.: Idealised satellite data assimilation experiments with clouds and precipitation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-332, https://doi.org/10.5194/egusphere-egu2020-332, 2020.
Operational data assimilation (DA) schemes rely significantly on satellite observations with much research aimed at their optimisation, leading to a great deal of progress. Here, we investigate the impact of the spatial-temporal variability of satellite observations for DA: is there a case for concentrating effort into the assimilation of small-scale convective features over the large-scale dynamics, or vice versa?
We conduct our study in an isentropic one-and-a-half layer model that mimics convection and precipitation, a revised and more realistic version of the idealised model based on the shallow water equations in [1,2]. Forecast-assimilation experiments are performed by means of a twin-setting configuration, in which pseudo-observations from a high-resolution nature run are combined with lower-resolution forecasts. The DA algorithm used is the deterministic Ensemble Kalman Filter (see [3]). We focus our research on polar-orbit satellites regarding emitted microwave radiation.
We have developed a new observation operator and a representative observing system in which both ground and satellite observations can be assimilated. The convection thresholds in the model are used as a proxy for cloud formation, clouds, and precipitation. To imitate the use of weighting functions in real satellite applications, radiance values are computed as a weighted sum with contributions from both layers. In the presence of clouds and/or precipitation, we model the response of passive microwave radiation to either precipitating or non-precipitating clouds. The horizontal resolution of satellite observations can be varied to investigate the impact of scale-dependency on the analysis.
New, preliminary results from experiments including both transverse jets and rotation in a periodic domain will be reported and discussed.
References:
[1] Kent, T., Bokhove, O., & Tobias, S. (2017). Dynamics of an idealized fluid model for investigating convective-scale data assimilation. Tellus A: Dynamic Meteorology and Oceanography, 69(1), 1369332.
[2] Kent, T. (2016). An idealised fluid model for convective-scale NWP: dynamics and data assimilation (Doctoral dissertation, PhD Thesis, University of Leeds).
[3] Sakov, P., & Oke, P. R. (2008). A deterministic formulation of the ensemble Kalman filter: an alternative to ensemble square root filters. Tellus A: Dynamic Meteorology and Oceanography, 60(2), 361-371.
How to cite: Cantarello, L., Bokhove, O., Inverarity, G., Migliorini, S., and Tobias, S.: Idealised satellite data assimilation experiments with clouds and precipitation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-332, https://doi.org/10.5194/egusphere-egu2020-332, 2020.
EGU2020-2182 | Displays | NP5.1 | Highlight
Implicitly localized MCMC sampler to cope with nonlocal/nonlinear data constraints in large-size inverse problemsJean-Michel Brankart
Many practical applications involve the resolution of large-size inverse problems, without providing more than a moderate-size sample to describe the prior probability distribution. In this situation, additional information must be supplied to augment the effective dimension of the available sample, for instance using a covariance localization approach. In this study, it is suggested that covariance localization can be efficiently applied to an approximate variant of the Metropolis/Hastings algorithm, by modulating the ensemble members by the large-scale patterns of other members. Modulation is used to design a (global) proposal probability distribution (i) that can be sampled at a very low cost, (ii) that automatically accounts for a localized prior covariance, and (iii) that leads to an efficient sampler for the augmented prior probability distribution or for the posterior probability distribution. The resulting algorithm is applied to an academic example, illustrating (i) the effectiveness of covariance localization, (ii) the ability of the method to deal with nonlocal/nonlinear observation operators and non-Gaussian observation errors, (iii) the reliability, resolution and optimality of the updated ensemble, using probabilistic scores appropriate to a non-Gaussian posterior distribution, and (iv) the scalability of the algorithm as a function of the size of the problem. The codes are openly available from github.com/brankart/ensdam.
How to cite: Brankart, J.-M.: Implicitly localized MCMC sampler to cope with nonlocal/nonlinear data constraints in large-size inverse problems, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2182, https://doi.org/10.5194/egusphere-egu2020-2182, 2020.
Many practical applications involve the resolution of large-size inverse problems, without providing more than a moderate-size sample to describe the prior probability distribution. In this situation, additional information must be supplied to augment the effective dimension of the available sample, for instance using a covariance localization approach. In this study, it is suggested that covariance localization can be efficiently applied to an approximate variant of the Metropolis/Hastings algorithm, by modulating the ensemble members by the large-scale patterns of other members. Modulation is used to design a (global) proposal probability distribution (i) that can be sampled at a very low cost, (ii) that automatically accounts for a localized prior covariance, and (iii) that leads to an efficient sampler for the augmented prior probability distribution or for the posterior probability distribution. The resulting algorithm is applied to an academic example, illustrating (i) the effectiveness of covariance localization, (ii) the ability of the method to deal with nonlocal/nonlinear observation operators and non-Gaussian observation errors, (iii) the reliability, resolution and optimality of the updated ensemble, using probabilistic scores appropriate to a non-Gaussian posterior distribution, and (iv) the scalability of the algorithm as a function of the size of the problem. The codes are openly available from github.com/brankart/ensdam.
How to cite: Brankart, J.-M.: Implicitly localized MCMC sampler to cope with nonlocal/nonlinear data constraints in large-size inverse problems, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2182, https://doi.org/10.5194/egusphere-egu2020-2182, 2020.
EGU2020-19831 | Displays | NP5.1 | Highlight
Development of a nonlinear ensemble data assimilation method with global state-space covariance localizationMilija Zupanski
High-dimensional ensemble data assimilation applications require error covariance localization in order to address the problem of insufficient degrees of freedom, typically accomplished using the observation-space covariance localization. However, this creates a challenge for vertically integrated observations, such as satellite radiances, aerosol optical depth, etc., since the exact observation location in vertical does not exist. For nonlinear problems, there is an implied inconsistency in iterative minimization due to using observation-space localization which effectively prevents finding the optimal global minimizing solution. Using state-space localization, however, in principal resolves both issues associated with observation space localization.
In this work we present a new nonlinear ensemble data assimilation method that employs covariance localization in state space and finds an optimal analysis solution. The new method resembles “modified ensembles” in the sense that ensemble size is increased in the analysis, but it differs in methodology used to create ensemble modifications, calculate the analysis error covariance, and define the initial ensemble perturbations for data assimilation cycling. From a practical point of view, the new method is considerably more efficient and potentially applicable to realistic high-dimensional data assimilation problems. A distinct characteristic of the new algorithm is that the localized error covariance and minimization are global, i.e. explicitly defined over all state points. The presentation will focus on examining feasible options for estimating the analysis error covariance and for defining the initial ensemble perturbations.
How to cite: Zupanski, M.: Development of a nonlinear ensemble data assimilation method with global state-space covariance localization, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19831, https://doi.org/10.5194/egusphere-egu2020-19831, 2020.
High-dimensional ensemble data assimilation applications require error covariance localization in order to address the problem of insufficient degrees of freedom, typically accomplished using the observation-space covariance localization. However, this creates a challenge for vertically integrated observations, such as satellite radiances, aerosol optical depth, etc., since the exact observation location in vertical does not exist. For nonlinear problems, there is an implied inconsistency in iterative minimization due to using observation-space localization which effectively prevents finding the optimal global minimizing solution. Using state-space localization, however, in principal resolves both issues associated with observation space localization.
In this work we present a new nonlinear ensemble data assimilation method that employs covariance localization in state space and finds an optimal analysis solution. The new method resembles “modified ensembles” in the sense that ensemble size is increased in the analysis, but it differs in methodology used to create ensemble modifications, calculate the analysis error covariance, and define the initial ensemble perturbations for data assimilation cycling. From a practical point of view, the new method is considerably more efficient and potentially applicable to realistic high-dimensional data assimilation problems. A distinct characteristic of the new algorithm is that the localized error covariance and minimization are global, i.e. explicitly defined over all state points. The presentation will focus on examining feasible options for estimating the analysis error covariance and for defining the initial ensemble perturbations.
How to cite: Zupanski, M.: Development of a nonlinear ensemble data assimilation method with global state-space covariance localization, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19831, https://doi.org/10.5194/egusphere-egu2020-19831, 2020.
EGU2020-22521 | Displays | NP5.1 | Highlight
A framework for causality under data assimilationNachiketa Chakraborty, Peter Jan van Leeuwen, Michael de Caria, and Manuel Pulido
Time varying processes in nature are often complex with non-linear and non-gaussian components. Complexity of environments and processes make it hard to disentangle different causal mechanisms which drives the observed time-series. It also makes it harder to make forecasts. The standard ways of studying causal relation in the geosciences which includes information theoretic measures of causation as well as predictive framework have deficiencies when applied to non-linear dynamical systems. Here we focus on investigating building a predictive causal framework that allows us to make predictions in simpler systems in a consistent way. We use a Bayesian framework to embed causal measures akin to mutual information from information theory to quantify relations between different random processes in this system. We examine causal relations in toy models and simple systems with a view to eventually applying to the interocean exchange problem in the Indian, the South Atlantic and the Southern Ocean.
How to cite: Chakraborty, N., van Leeuwen, P. J., de Caria, M., and Pulido, M.: A framework for causality under data assimilation , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22521, https://doi.org/10.5194/egusphere-egu2020-22521, 2020.
Time varying processes in nature are often complex with non-linear and non-gaussian components. Complexity of environments and processes make it hard to disentangle different causal mechanisms which drives the observed time-series. It also makes it harder to make forecasts. The standard ways of studying causal relation in the geosciences which includes information theoretic measures of causation as well as predictive framework have deficiencies when applied to non-linear dynamical systems. Here we focus on investigating building a predictive causal framework that allows us to make predictions in simpler systems in a consistent way. We use a Bayesian framework to embed causal measures akin to mutual information from information theory to quantify relations between different random processes in this system. We examine causal relations in toy models and simple systems with a view to eventually applying to the interocean exchange problem in the Indian, the South Atlantic and the Southern Ocean.
How to cite: Chakraborty, N., van Leeuwen, P. J., de Caria, M., and Pulido, M.: A framework for causality under data assimilation , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22521, https://doi.org/10.5194/egusphere-egu2020-22521, 2020.
EGU2020-8979 | Displays | NP5.1
Spatio-temporal Inversion using the Selection Kalman ModelMaxime Conjard and Henning Omre
The challenge in data assimilation for models representing spatio-temporal phenomena is made harder when the spatial histogram of the variable of interest appears with multiple modes. Pollution source identification constitutes one example where the pollution release represents an extreme event in a fairly homogeneous background. Consequently, our prior belief is that the spatial histogram is bimodal. The traditional Kalman model is based on a Gaussian initial distribution and Gauss-linear dynamic and observation models. This model is contained in the class of Gaussian distribution and is therefore analytically tractable. These properties that make its strenght also render it unsuitable for representing multimodality. To address the issue, we define the selection Kalman model. It is based on a selection-Gaussian initial distribution and Gauss-linear dynamic and observation models. The selection-Gaussian distribution may represent multimodality, skewness and peakedness. It can be seen as a generalization of the Gaussian distribution. The proposed selection Kalman model is contained in the class of selection-Gaussian distributions and therefore analytically tractable. The recursive algorithm used for assessing the selection Kalman model is specified. We present a synthetic case study of spatio-temporal inversion of an initial state containing an extreme event. The study is inspired by pollution monitoring. The results suggest that the use of the selection Kalman model offers significant improvements compared to the traditional Kalman model when reconstructing discontinuous initial states.
How to cite: Conjard, M. and Omre, H.: Spatio-temporal Inversion using the Selection Kalman Model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8979, https://doi.org/10.5194/egusphere-egu2020-8979, 2020.
The challenge in data assimilation for models representing spatio-temporal phenomena is made harder when the spatial histogram of the variable of interest appears with multiple modes. Pollution source identification constitutes one example where the pollution release represents an extreme event in a fairly homogeneous background. Consequently, our prior belief is that the spatial histogram is bimodal. The traditional Kalman model is based on a Gaussian initial distribution and Gauss-linear dynamic and observation models. This model is contained in the class of Gaussian distribution and is therefore analytically tractable. These properties that make its strenght also render it unsuitable for representing multimodality. To address the issue, we define the selection Kalman model. It is based on a selection-Gaussian initial distribution and Gauss-linear dynamic and observation models. The selection-Gaussian distribution may represent multimodality, skewness and peakedness. It can be seen as a generalization of the Gaussian distribution. The proposed selection Kalman model is contained in the class of selection-Gaussian distributions and therefore analytically tractable. The recursive algorithm used for assessing the selection Kalman model is specified. We present a synthetic case study of spatio-temporal inversion of an initial state containing an extreme event. The study is inspired by pollution monitoring. The results suggest that the use of the selection Kalman model offers significant improvements compared to the traditional Kalman model when reconstructing discontinuous initial states.
How to cite: Conjard, M. and Omre, H.: Spatio-temporal Inversion using the Selection Kalman Model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8979, https://doi.org/10.5194/egusphere-egu2020-8979, 2020.
EGU2020-5772 | Displays | NP5.1
p-norm regularization in variational data assimilationAntoine Bernigaud, Serge Gratton, Flavia Lenti, Ehouarn Simon, and Oumaima Sohab
We introduce a new formulation of the 4DVAR objective function by using as a penalty term a p-norm with 1 < p < 2. So far, only the 2-norm, the 1-norm or a mixed of both have been considered as regularization term. This approach is motivated by the nature of the problems encountered in data assimilation, for which such a norm may be more suited to tackle the distribution of the variables. It also aims at making a compromise between the 2-norm that tends to oversmooth the solution or produce Gibbs oscillations, and the 1-norm that tends to "oversparcify" it, in addition to making the problem non-smooth.
The performance of the proposed technique are assessed for different p-values by twin experiments on a linear advection equation. The experiments are then conducted using two different true states in order to assess the performances of the p-norm regularized 4DVAR algorithm in sparse (rectangular function) and "almost" sparse cases (rectangular function with a smoother slope). In this setup, the background and the measurements noise covariance are known.
In order to minimize the 4DVAR objective function with a p-norm as a regularization term we use a gradient descent algorithm that requires the use of duality operators to work on a non-euclidean space. Indeed, Rn together with the p-norm (1 < p < 2) is a Banach space. Finally, to tune the regularization parameter appearing in the formulation of the objective function, we use the Morozov's discrepancy principle.
How to cite: Bernigaud, A., Gratton, S., Lenti, F., Simon, E., and Sohab, O.: p-norm regularization in variational data assimilation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5772, https://doi.org/10.5194/egusphere-egu2020-5772, 2020.
We introduce a new formulation of the 4DVAR objective function by using as a penalty term a p-norm with 1 < p < 2. So far, only the 2-norm, the 1-norm or a mixed of both have been considered as regularization term. This approach is motivated by the nature of the problems encountered in data assimilation, for which such a norm may be more suited to tackle the distribution of the variables. It also aims at making a compromise between the 2-norm that tends to oversmooth the solution or produce Gibbs oscillations, and the 1-norm that tends to "oversparcify" it, in addition to making the problem non-smooth.
The performance of the proposed technique are assessed for different p-values by twin experiments on a linear advection equation. The experiments are then conducted using two different true states in order to assess the performances of the p-norm regularized 4DVAR algorithm in sparse (rectangular function) and "almost" sparse cases (rectangular function with a smoother slope). In this setup, the background and the measurements noise covariance are known.
In order to minimize the 4DVAR objective function with a p-norm as a regularization term we use a gradient descent algorithm that requires the use of duality operators to work on a non-euclidean space. Indeed, Rn together with the p-norm (1 < p < 2) is a Banach space. Finally, to tune the regularization parameter appearing in the formulation of the objective function, we use the Morozov's discrepancy principle.
How to cite: Bernigaud, A., Gratton, S., Lenti, F., Simon, E., and Sohab, O.: p-norm regularization in variational data assimilation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5772, https://doi.org/10.5194/egusphere-egu2020-5772, 2020.
EGU2020-285 | Displays | NP5.1 | Highlight
Learning missing part of physics-based models within a variational data assimilation schemeArthur Filoche, Julien Brajard, Anastase Charantonis, and Dominique Béréziat
The analogy between data assimilation and machine learning has already been shown and is still being investigated to address the problem of improving physics-based models. Even though both techniques learn from data, machine learning focuses on inferring model parameters while data assimilation concentrates on hidden system state estimation with the help of a dynamical model.
Also, neural networks and more precisely ResNet-like architectures can be seen as dynamical systems and numerical schemes, respectively. They are now considered state of the art in a vast amount of tasks involving spatio-temporal forecasting. But to train such networks, one needs dense and representative data which is rarely the case in earth sciences. At the same time, data assimilation offers a proper Bayesian framework allowing to learn from partial, noisy and indirect observations. Thus, each of this field can profit from the other by providing either a learnable class of dynamical models or dense data sets.
In this work, we benefit from powerful and flexible tools provided by the deep learning community based on automatic differentiation that are clearly suitable for variational data assimilation, avoiding explicit adjoint modelling. We use a hybrid model divided into 2 terms. The first term is a numerical scheme that comes from the discretisation of physics-based equations, the second is a convolutional neural network that represents the unresolved part of the dynamics. From the Data Assimilation point of view, our network can be seen as a particular parametrisation of the model error. We then jointly learn this parameterisation and estimate hidden system states within a variational data assimilation scheme. Indirectly, the issue of incorporating physical knowledge into machine learning models is also addressed.
We show that the hybrid model improves forecast skill compared to traditional data assimilation techniques. The generalisation of the method on different models and data will also be discussed.
How to cite: Filoche, A., Brajard, J., Charantonis, A., and Béréziat, D.: Learning missing part of physics-based models within a variational data assimilation scheme, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-285, https://doi.org/10.5194/egusphere-egu2020-285, 2020.
The analogy between data assimilation and machine learning has already been shown and is still being investigated to address the problem of improving physics-based models. Even though both techniques learn from data, machine learning focuses on inferring model parameters while data assimilation concentrates on hidden system state estimation with the help of a dynamical model.
Also, neural networks and more precisely ResNet-like architectures can be seen as dynamical systems and numerical schemes, respectively. They are now considered state of the art in a vast amount of tasks involving spatio-temporal forecasting. But to train such networks, one needs dense and representative data which is rarely the case in earth sciences. At the same time, data assimilation offers a proper Bayesian framework allowing to learn from partial, noisy and indirect observations. Thus, each of this field can profit from the other by providing either a learnable class of dynamical models or dense data sets.
In this work, we benefit from powerful and flexible tools provided by the deep learning community based on automatic differentiation that are clearly suitable for variational data assimilation, avoiding explicit adjoint modelling. We use a hybrid model divided into 2 terms. The first term is a numerical scheme that comes from the discretisation of physics-based equations, the second is a convolutional neural network that represents the unresolved part of the dynamics. From the Data Assimilation point of view, our network can be seen as a particular parametrisation of the model error. We then jointly learn this parameterisation and estimate hidden system states within a variational data assimilation scheme. Indirectly, the issue of incorporating physical knowledge into machine learning models is also addressed.
We show that the hybrid model improves forecast skill compared to traditional data assimilation techniques. The generalisation of the method on different models and data will also be discussed.
How to cite: Filoche, A., Brajard, J., Charantonis, A., and Béréziat, D.: Learning missing part of physics-based models within a variational data assimilation scheme, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-285, https://doi.org/10.5194/egusphere-egu2020-285, 2020.
EGU2020-559 | Displays | NP5.1
Effect of inaccurate specification of time-correlated model error in an Ensemble SmootherHaonan Ren, Peter Jan Van Leeuwen, and Javier Amezcua
Data assimilation has been often performed under the perfect model assumption known as the strong-constraint setting. There is an increasing number of researches accounting for the model errors, the weak-constrain setting, but often with different degrees of approximation or simplification without knowing their impact on the data assimilation results. We investigate what effect inaccurate model errors, in particular, the an inaccurate time correlation, can have on data assimilation results, with a Kalman Smoother and the Ensemble Kalman Smoother.
We choose a linear auto-regressive model for the experiment. We assume the true state of the system has the correct and fixed correlation time-scale ωr in the model errors, and the prior or the background generated by the model contains the model error with the fixed, guessed time-scale ωg which differs from the correct one and is also used in the data assimilation process. There are 10 variables in the system and we separate the simulation period into multiple time-windows. And we use a fairly large ensemble size (up to 200 ensemble members) to improve the accuracy of the data assimilation results. In order to evaluate the performance of the EnKS with auto-correlated model errors, we calculate the ratio of root-mean-square error over the spread of all ensemble members.
The results with a single observation at the end of the simulation time-window show that, using an underestimated correlation time-scale leads to overestimated spread of the ensemble, and with an overestimated time-scale, the results show underestimation in the ensemble spread. However, with very dense observation frequency, observing every time-step for instance, the results are completely opposite to the results with a single observation. In order to understand the results, we derive the expression for the true posterior state covariance and the posterior covariance using the incorrect decorrelation time-scale. We do this for a Kalman Smoother to avoid the sampling uncertainties. The results are richer than expected and highly dependent on the observation frequency. From the analytical solution of the analysis, we find that the RMSE is a function of both ωr and ωg, and the spread or the variance only depends on ωg. We also find that the analyzed variance is not always a monotonically increasing function of ωg, and it also depends on the observation frequency. In general, the results show the effect of the correlated model error and the incorrect correlation time-scale on data assimilation result, which is also affected by the observation frequency.
How to cite: Ren, H., Van Leeuwen, P. J., and Amezcua, J.: Effect of inaccurate specification of time-correlated model error in an Ensemble Smoother, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-559, https://doi.org/10.5194/egusphere-egu2020-559, 2020.
Data assimilation has been often performed under the perfect model assumption known as the strong-constraint setting. There is an increasing number of researches accounting for the model errors, the weak-constrain setting, but often with different degrees of approximation or simplification without knowing their impact on the data assimilation results. We investigate what effect inaccurate model errors, in particular, the an inaccurate time correlation, can have on data assimilation results, with a Kalman Smoother and the Ensemble Kalman Smoother.
We choose a linear auto-regressive model for the experiment. We assume the true state of the system has the correct and fixed correlation time-scale ωr in the model errors, and the prior or the background generated by the model contains the model error with the fixed, guessed time-scale ωg which differs from the correct one and is also used in the data assimilation process. There are 10 variables in the system and we separate the simulation period into multiple time-windows. And we use a fairly large ensemble size (up to 200 ensemble members) to improve the accuracy of the data assimilation results. In order to evaluate the performance of the EnKS with auto-correlated model errors, we calculate the ratio of root-mean-square error over the spread of all ensemble members.
The results with a single observation at the end of the simulation time-window show that, using an underestimated correlation time-scale leads to overestimated spread of the ensemble, and with an overestimated time-scale, the results show underestimation in the ensemble spread. However, with very dense observation frequency, observing every time-step for instance, the results are completely opposite to the results with a single observation. In order to understand the results, we derive the expression for the true posterior state covariance and the posterior covariance using the incorrect decorrelation time-scale. We do this for a Kalman Smoother to avoid the sampling uncertainties. The results are richer than expected and highly dependent on the observation frequency. From the analytical solution of the analysis, we find that the RMSE is a function of both ωr and ωg, and the spread or the variance only depends on ωg. We also find that the analyzed variance is not always a monotonically increasing function of ωg, and it also depends on the observation frequency. In general, the results show the effect of the correlated model error and the incorrect correlation time-scale on data assimilation result, which is also affected by the observation frequency.
How to cite: Ren, H., Van Leeuwen, P. J., and Amezcua, J.: Effect of inaccurate specification of time-correlated model error in an Ensemble Smoother, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-559, https://doi.org/10.5194/egusphere-egu2020-559, 2020.
EGU2020-10752 | Displays | NP5.1
Data assimilation framework around the LPJ-GUESS model for the optimised simulation of CH4 emission from Northern wetlandsJalisha Theanutti Kallingal, Marko Scholze, Janne Rinne, and Johan Lindstrom
Wetlands in the boreal zone are a significant source of atmospheric methane, and hence they have been intensively studied with mechanistic models for the assessment of methane dynamics. The arctic-enabled dynamic global vegetation model LPJ-GUESS is one of the models that allow quantification and understanding of the natural methane fluxes at various scales ranging from local to regional and global, but with several uncertainties. Complexity in the underlying environmental processes, warming driven alternative paths of meteorological phenomena and changes in hydrological and vegetation conditions are exigent for a calibrated and optimised LPJ-GUESS. In this study, we used the Markov chain Monte Carlo (using Metropolis-Hastings formula) algorithm to quantify the uncertainties of LPJ-GUESS. Application of this method allows greater search of the posterior distribution, leading to a more complete characterisation of the posterior distribution with reduced risk of sample impoverishment. We will present first results from an assimilation experiment optimising LPJ-GUESS model process parameters using the flux measurement data from 2005 to 2015 from the Siikaneva wetlands in southern Finland. We analyse the parameter efficiency of LPJ-GUESS by looking into the posterior parameter distributions, parameter correlations, and the interconnections of the processes they control. As a part of this work, knowledge about how the methane data can constrain the parameters and processes is derived.
How to cite: Theanutti Kallingal, J., Scholze, M., Rinne, J., and Lindstrom, J.: Data assimilation framework around the LPJ-GUESS model for the optimised simulation of CH4 emission from Northern wetlands, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10752, https://doi.org/10.5194/egusphere-egu2020-10752, 2020.
Wetlands in the boreal zone are a significant source of atmospheric methane, and hence they have been intensively studied with mechanistic models for the assessment of methane dynamics. The arctic-enabled dynamic global vegetation model LPJ-GUESS is one of the models that allow quantification and understanding of the natural methane fluxes at various scales ranging from local to regional and global, but with several uncertainties. Complexity in the underlying environmental processes, warming driven alternative paths of meteorological phenomena and changes in hydrological and vegetation conditions are exigent for a calibrated and optimised LPJ-GUESS. In this study, we used the Markov chain Monte Carlo (using Metropolis-Hastings formula) algorithm to quantify the uncertainties of LPJ-GUESS. Application of this method allows greater search of the posterior distribution, leading to a more complete characterisation of the posterior distribution with reduced risk of sample impoverishment. We will present first results from an assimilation experiment optimising LPJ-GUESS model process parameters using the flux measurement data from 2005 to 2015 from the Siikaneva wetlands in southern Finland. We analyse the parameter efficiency of LPJ-GUESS by looking into the posterior parameter distributions, parameter correlations, and the interconnections of the processes they control. As a part of this work, knowledge about how the methane data can constrain the parameters and processes is derived.
How to cite: Theanutti Kallingal, J., Scholze, M., Rinne, J., and Lindstrom, J.: Data assimilation framework around the LPJ-GUESS model for the optimised simulation of CH4 emission from Northern wetlands, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10752, https://doi.org/10.5194/egusphere-egu2020-10752, 2020.
EGU2020-5717 | Displays | NP5.1
Reducing the memory requirements of parameter estimation using model order reductionMartin Verlaan, Xiaohui Wang, and Hai Xiang Lin
Previous development of a parameter estimation scheme for a Global Tide and Surge Model (GTSM) showed that accurate estimation of the parameters is currently limited by the memory use of the analysis step and the computational demand. Because the estimation algorithm solver requires storage of the model output matching each observation for each parameter (or ensemble member), the requirement of memory storage gets out of control as the model simulation time increases, the model output and observation matrix become too large. The popular approach of localization does not work here because the tides propagate all over the globe in days, while parameter estimation requires weeks at least. Proper Orthogonal Decomposition (POD) is a useful technique to reduce the high dimension system with a smaller linear subspace. Singular values decomposition (SVD) is one of the methods to derive the POD modes, which is generally applied for space patterns. In this study, we focus on the application of POD in time patterns by using SVD to reduce the dimension in time patterns. As expected, the time patterns show a strong resemblance to the tidal constituents, but the same method is likely to work for a wider range of problems, which indicate that the memory requirements can be reduced dramatically by projection the model output and observations onto the time-POD patterns.
How to cite: Verlaan, M., Wang, X., and Lin, H. X.: Reducing the memory requirements of parameter estimation using model order reduction, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5717, https://doi.org/10.5194/egusphere-egu2020-5717, 2020.
Previous development of a parameter estimation scheme for a Global Tide and Surge Model (GTSM) showed that accurate estimation of the parameters is currently limited by the memory use of the analysis step and the computational demand. Because the estimation algorithm solver requires storage of the model output matching each observation for each parameter (or ensemble member), the requirement of memory storage gets out of control as the model simulation time increases, the model output and observation matrix become too large. The popular approach of localization does not work here because the tides propagate all over the globe in days, while parameter estimation requires weeks at least. Proper Orthogonal Decomposition (POD) is a useful technique to reduce the high dimension system with a smaller linear subspace. Singular values decomposition (SVD) is one of the methods to derive the POD modes, which is generally applied for space patterns. In this study, we focus on the application of POD in time patterns by using SVD to reduce the dimension in time patterns. As expected, the time patterns show a strong resemblance to the tidal constituents, but the same method is likely to work for a wider range of problems, which indicate that the memory requirements can be reduced dramatically by projection the model output and observations onto the time-POD patterns.
How to cite: Verlaan, M., Wang, X., and Lin, H. X.: Reducing the memory requirements of parameter estimation using model order reduction, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5717, https://doi.org/10.5194/egusphere-egu2020-5717, 2020.
EGU2020-3128 | Displays | NP5.1 | Highlight
The Data Assimilation Research Testbed: Nonlinear Algorithms and Novel Applications for Community Ensemble Data AssimilationJeffrey Anderson, Nancy Collins, Moha El Gharamti, Timothy Hoar, Kevin Raeder, Frederic Castruccio, Jingjing LIang, John Lin, James McCreight, Seongjin Noh, Brett Raczka, and Arezoo Arezoo Rfieeinasab
The Data Assimilation Research Testbed (DART) is a community facility for ensemble data assimilation developed and maintained by the National Center for Atmospheric Research (NCAR). DART provides ensemble data assimilation capabilities for NCAR community earth system models and many other prediction models. It is straightforward to add interfaces for new models and new observations to DART.
DART provides traditional ensemble data assimilation algorithms that implicitly assume Gaussianity and linearity. Traditional algorithms can still work when these assumptions are violated. However, it is possible to greatly improve results by extending ensemble algorithms to explicitly account for aspects of nonlinearity and non-Gaussianity. Two new algorithms have been added to DART. 1). Anamorphosis transforms variables to make the assimilation problem more linear and Gaussian before transforming posterior estimates back to the original model variables; 2). The marginal correction rank histogram filter (MCRHF) directly represents arbitrary non-Gaussian distributions. These methods are particularly valuable for data assimilation for bounded quantities like tracers or streamflow.
DART is being applied to a number of novel applications. Examples in the poster include 1). An eddy-resolving global ocean ensemble reanalysis with the POP ocean model and an ensemble optimal interpolation; 2). The WRF-Hydro/DART system now includes a multi-parametric ensemble, anamorphosis, and spatially-correlated noise for the forcing fields. 3). Results from the Carbon Monitoring System over Mountains using CLM5 to assimilate remotely-sensed observations (LAI, biomass, and SIF) for a field site in Colorado; 4). Assimilation of MODIS snow cover fraction and daily GRACE total water storage data and its impact on soil moisture using the DART/NOAH-MP system. 5). An ensemble atmospheric reanalysis using the CAM general circulation model.
How to cite: Anderson, J., Collins, N., El Gharamti, M., Hoar, T., Raeder, K., Castruccio, F., LIang, J., Lin, J., McCreight, J., Noh, S., Raczka, B., and Arezoo Rfieeinasab, A.: The Data Assimilation Research Testbed: Nonlinear Algorithms and Novel Applications for Community Ensemble Data Assimilation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3128, https://doi.org/10.5194/egusphere-egu2020-3128, 2020.
The Data Assimilation Research Testbed (DART) is a community facility for ensemble data assimilation developed and maintained by the National Center for Atmospheric Research (NCAR). DART provides ensemble data assimilation capabilities for NCAR community earth system models and many other prediction models. It is straightforward to add interfaces for new models and new observations to DART.
DART provides traditional ensemble data assimilation algorithms that implicitly assume Gaussianity and linearity. Traditional algorithms can still work when these assumptions are violated. However, it is possible to greatly improve results by extending ensemble algorithms to explicitly account for aspects of nonlinearity and non-Gaussianity. Two new algorithms have been added to DART. 1). Anamorphosis transforms variables to make the assimilation problem more linear and Gaussian before transforming posterior estimates back to the original model variables; 2). The marginal correction rank histogram filter (MCRHF) directly represents arbitrary non-Gaussian distributions. These methods are particularly valuable for data assimilation for bounded quantities like tracers or streamflow.
DART is being applied to a number of novel applications. Examples in the poster include 1). An eddy-resolving global ocean ensemble reanalysis with the POP ocean model and an ensemble optimal interpolation; 2). The WRF-Hydro/DART system now includes a multi-parametric ensemble, anamorphosis, and spatially-correlated noise for the forcing fields. 3). Results from the Carbon Monitoring System over Mountains using CLM5 to assimilate remotely-sensed observations (LAI, biomass, and SIF) for a field site in Colorado; 4). Assimilation of MODIS snow cover fraction and daily GRACE total water storage data and its impact on soil moisture using the DART/NOAH-MP system. 5). An ensemble atmospheric reanalysis using the CAM general circulation model.
How to cite: Anderson, J., Collins, N., El Gharamti, M., Hoar, T., Raeder, K., Castruccio, F., LIang, J., Lin, J., McCreight, J., Noh, S., Raczka, B., and Arezoo Rfieeinasab, A.: The Data Assimilation Research Testbed: Nonlinear Algorithms and Novel Applications for Community Ensemble Data Assimilation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3128, https://doi.org/10.5194/egusphere-egu2020-3128, 2020.
EGU2020-6121 | Displays | NP5.1
Development of Ensemble-based Assimilation System for Aerosol Forecasting and Reanalysis at NOAAMariusz Pagowski, Cory Martin, Bo Huang, Daryl Kleist, and Shobha Kondragunta
In 2016 NOAA chose the FV3 (Finite Volume) dynamical core as a basis for its future global modeling system. For aerosol modeling this dynamical core was supplemented with GFS (Global Forecast System) physics and coupled through an interface with GOCART (Goddard Global Ozone Chemistry Aerosol Radiation and Transport) parameterization. The assimilation methodology relies on a hybrid variational-ensemble approach within the newly developed model-agnostic JEDI (Joint Effort for Data assimilation Integration) framework. Observations include 550 nm AOD retrievals from VIIRS (Visible Infrared Imaging Radiometer Suite) instruments on polar-orbiting SNPP and NOAA-20 satellites. The system is under development and early its results are compared with NASA'a MERRA-2 and ECMWF's CAMSiRA reanalyses.
How to cite: Pagowski, M., Martin, C., Huang, B., Kleist, D., and Kondragunta, S.: Development of Ensemble-based Assimilation System for Aerosol Forecasting and Reanalysis at NOAA, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6121, https://doi.org/10.5194/egusphere-egu2020-6121, 2020.
In 2016 NOAA chose the FV3 (Finite Volume) dynamical core as a basis for its future global modeling system. For aerosol modeling this dynamical core was supplemented with GFS (Global Forecast System) physics and coupled through an interface with GOCART (Goddard Global Ozone Chemistry Aerosol Radiation and Transport) parameterization. The assimilation methodology relies on a hybrid variational-ensemble approach within the newly developed model-agnostic JEDI (Joint Effort for Data assimilation Integration) framework. Observations include 550 nm AOD retrievals from VIIRS (Visible Infrared Imaging Radiometer Suite) instruments on polar-orbiting SNPP and NOAA-20 satellites. The system is under development and early its results are compared with NASA'a MERRA-2 and ECMWF's CAMSiRA reanalyses.
How to cite: Pagowski, M., Martin, C., Huang, B., Kleist, D., and Kondragunta, S.: Development of Ensemble-based Assimilation System for Aerosol Forecasting and Reanalysis at NOAA, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6121, https://doi.org/10.5194/egusphere-egu2020-6121, 2020.
EGU2020-6366 | Displays | NP5.1
Optimal Error Analysis of MJO Prediction Associated with Uncertainties in Sea Surface Temperature over Indian OceanXiaojing Li and Youmin Tang
In this study, the predictability of the Madden-Julian Oscillation (MJO) is investigated using the coupled Community Earth System Model (CESM) and the climatically relevant singular vector (CSV) method. The CSV method is an ensemble-based strategy to calculate the optimal growth of the initial error on the climate scale. We focus on the CSV analysis of MJO initialized at phase II, facilitating the investigation of the effect of the initial errors of the sea surface temperature (SST) in the Indian Ocean on it. Six different MJO events are chosen as the study cases to ensure the robustness of the results.
The results indicate that for all the study cases, the optimal perturbation structure of the SST, denoted by the leading mode of the singular vectors (SVs), is a meridional dipole-like pattern between the Bay of Bengal and the southern central Indian Ocean. The MJO signal tends to be more converged and significant in the Eastern Hemisphere while the model is perturbed by leading SV. The moist static energy analysis results indicate that the eastward propagation is much more evident in the terms of vertical advection and radiation flux than others. Therefore, the SV perturbation can strengthen and converge the MJO signal mostly by increasing the vertical advection of the moist static energy.
Further, the sensitivity studies indicate that the structure of the leading SV is not sensitive to the initial states, which suggests that we might not need to calculate SVs for each initial time in constructing the ensemble prediction, significantly saving computational time in the operational forecast systems.
How to cite: Li, X. and Tang, Y.: Optimal Error Analysis of MJO Prediction Associated with Uncertainties in Sea Surface Temperature over Indian Ocean, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6366, https://doi.org/10.5194/egusphere-egu2020-6366, 2020.
In this study, the predictability of the Madden-Julian Oscillation (MJO) is investigated using the coupled Community Earth System Model (CESM) and the climatically relevant singular vector (CSV) method. The CSV method is an ensemble-based strategy to calculate the optimal growth of the initial error on the climate scale. We focus on the CSV analysis of MJO initialized at phase II, facilitating the investigation of the effect of the initial errors of the sea surface temperature (SST) in the Indian Ocean on it. Six different MJO events are chosen as the study cases to ensure the robustness of the results.
The results indicate that for all the study cases, the optimal perturbation structure of the SST, denoted by the leading mode of the singular vectors (SVs), is a meridional dipole-like pattern between the Bay of Bengal and the southern central Indian Ocean. The MJO signal tends to be more converged and significant in the Eastern Hemisphere while the model is perturbed by leading SV. The moist static energy analysis results indicate that the eastward propagation is much more evident in the terms of vertical advection and radiation flux than others. Therefore, the SV perturbation can strengthen and converge the MJO signal mostly by increasing the vertical advection of the moist static energy.
Further, the sensitivity studies indicate that the structure of the leading SV is not sensitive to the initial states, which suggests that we might not need to calculate SVs for each initial time in constructing the ensemble prediction, significantly saving computational time in the operational forecast systems.
How to cite: Li, X. and Tang, Y.: Optimal Error Analysis of MJO Prediction Associated with Uncertainties in Sea Surface Temperature over Indian Ocean, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6366, https://doi.org/10.5194/egusphere-egu2020-6366, 2020.
EGU2020-15879 | Displays | NP5.1
Towards non-linear inverse problem for atmospheric source term determinationOndřej Tichý and Václav Šmídl
How to cite: Tichý, O. and Šmídl, V.: Towards non-linear inverse problem for atmospheric source term determination, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15879, https://doi.org/10.5194/egusphere-egu2020-15879, 2020.
How to cite: Tichý, O. and Šmídl, V.: Towards non-linear inverse problem for atmospheric source term determination, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15879, https://doi.org/10.5194/egusphere-egu2020-15879, 2020.
EGU2020-18771 | Displays | NP5.1
LOTOS-EUROS 4DEnVar Data Assimilation using TROPOMI data for ColombiaAndres Yarce, Santiago Lopez, Diego Acosta, Olga Lucia Quintero, Nicolas Pinel, Arjo Segers, and Arnold Heemink
Chemical Transport Models (CTMs) simulate the emission, transformation, and transport of atmospheric chemical species, providing concentration and deposition estimates. While greatly sophisticated, these are still imperfect representations of reality. Data Assimilation (DA), a technique whereby observations are integrated into the simulations, helps alleviate the models' weaknesses, improving their simulation outputs and enabling parameter and state estimation. The variational DA method is an efficient approach for large-scale parameter and state estimation, but it is not straightforward to implement due to the need for a tangent linear matrix of the adjoint model forecast operator. To circumvent this difficulty, the ensemble-based 4DEnVar DA technique was used in this work.
Daily NO2 observations from the TROPOspheric Monitoring Instrument (TROPOMI) at resolutions of 3x5 km were acquired for 2019 and assimilated into the LOTOS-EUROS CTM. Due to the scarcity of ground-based monitoring stations for atmospheric gases in Colombia, especially outside urban areas, satellite data provide an attractive alternative for DA.
The 4DEnVar DA was first evaluated via the Design of Experiments (DOE) methodology with the Lorenz96 model assimilating synthetic data. Different parameters were changed (ensemble number, spread, forcing factor and width of the assimilation time window) according to a complete 24 factorial design followed by a Box Behnken design, providing an empirical model that guided the selection about how to modify those tuning parameters. The evaluation criteria used to test the 4DEnVar DA performance was the Root-Mean-Square (RMS) error between the analysis step and the synthetic data. Once this methodology was implemented, it was scaled up to the high-dimensional LOTOS-EUROS experiment.
The setup for the LOTOS-EUROS DA experiment was simplified in terms of domain area, chemical species of interest, dominant dynamics and considerations about how to perturb the parameters or initial conditions. A range of ensemble-members generated from perturbed parameters or input initial states were studied in conjunction with ensemble inflation experiments and Singular Value Decomposition projections, characterizing the degeneracy of the Gaussian assumption through the time propagation of the ensemble. Additionally, a complimentary analysis of this Gaussian ensemble degeneration was performed using the Shapiro-Wilk and Kolmogorov-Smirnov normality tests, which permitted a rational selection of the spin-up time of the model before the start of the assimilation window and the DA window size.
The assimilation of satellite NO2 observations into LOTOS-EUROS made possible the estimation of parameters and states. Before the DA, the non-assimilated model overestimated the magnitude of the observation, this technique improves the simulation in the sense that the analysis result approaches the observations reducing the RMS. Through this methodology, it was possible to circumvent the absence of an adjoint model associated with the chemical components of this CTM. To our knowledge, this is the first application of ensemble variational DA on a CTM for the Northwestern South America region.
How to cite: Yarce, A., Lopez, S., Acosta, D., Quintero, O. L., Pinel, N., Segers, A., and Heemink, A.: LOTOS-EUROS 4DEnVar Data Assimilation using TROPOMI data for Colombia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18771, https://doi.org/10.5194/egusphere-egu2020-18771, 2020.
Chemical Transport Models (CTMs) simulate the emission, transformation, and transport of atmospheric chemical species, providing concentration and deposition estimates. While greatly sophisticated, these are still imperfect representations of reality. Data Assimilation (DA), a technique whereby observations are integrated into the simulations, helps alleviate the models' weaknesses, improving their simulation outputs and enabling parameter and state estimation. The variational DA method is an efficient approach for large-scale parameter and state estimation, but it is not straightforward to implement due to the need for a tangent linear matrix of the adjoint model forecast operator. To circumvent this difficulty, the ensemble-based 4DEnVar DA technique was used in this work.
Daily NO2 observations from the TROPOspheric Monitoring Instrument (TROPOMI) at resolutions of 3x5 km were acquired for 2019 and assimilated into the LOTOS-EUROS CTM. Due to the scarcity of ground-based monitoring stations for atmospheric gases in Colombia, especially outside urban areas, satellite data provide an attractive alternative for DA.
The 4DEnVar DA was first evaluated via the Design of Experiments (DOE) methodology with the Lorenz96 model assimilating synthetic data. Different parameters were changed (ensemble number, spread, forcing factor and width of the assimilation time window) according to a complete 24 factorial design followed by a Box Behnken design, providing an empirical model that guided the selection about how to modify those tuning parameters. The evaluation criteria used to test the 4DEnVar DA performance was the Root-Mean-Square (RMS) error between the analysis step and the synthetic data. Once this methodology was implemented, it was scaled up to the high-dimensional LOTOS-EUROS experiment.
The setup for the LOTOS-EUROS DA experiment was simplified in terms of domain area, chemical species of interest, dominant dynamics and considerations about how to perturb the parameters or initial conditions. A range of ensemble-members generated from perturbed parameters or input initial states were studied in conjunction with ensemble inflation experiments and Singular Value Decomposition projections, characterizing the degeneracy of the Gaussian assumption through the time propagation of the ensemble. Additionally, a complimentary analysis of this Gaussian ensemble degeneration was performed using the Shapiro-Wilk and Kolmogorov-Smirnov normality tests, which permitted a rational selection of the spin-up time of the model before the start of the assimilation window and the DA window size.
The assimilation of satellite NO2 observations into LOTOS-EUROS made possible the estimation of parameters and states. Before the DA, the non-assimilated model overestimated the magnitude of the observation, this technique improves the simulation in the sense that the analysis result approaches the observations reducing the RMS. Through this methodology, it was possible to circumvent the absence of an adjoint model associated with the chemical components of this CTM. To our knowledge, this is the first application of ensemble variational DA on a CTM for the Northwestern South America region.
How to cite: Yarce, A., Lopez, S., Acosta, D., Quintero, O. L., Pinel, N., Segers, A., and Heemink, A.: LOTOS-EUROS 4DEnVar Data Assimilation using TROPOMI data for Colombia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18771, https://doi.org/10.5194/egusphere-egu2020-18771, 2020.
EGU2020-18684 | Displays | NP5.1
Quantifying uncertainty in the ESA Ocean Colour – Climate Change Initiative dataset for assimilation of total chlorophyll and phytoplankton functional typesAlison Fowler, Jozef Skákala, and Stefano Ciavatta
Monitoring biogeochemistry in shelf seas is of great significance for the economy, ecosystems understanding and climate studies. Data assimilation can aid the realism of marine biogeochemistry models by incorporating information from observations. An important source of information about phytoplankton groups and total chlorophyll is available from the ESA OC-CCI (ocean colour - climate change initiative) dataset.
For any assimilation system to be successful it is important to accurately represent all sources of data uncertainty. For the ocean colour product, the propagation of errors throughout the ocean colour algorithm makes the characterisation of the uncertainty challenging. However, the problem can be simplified by assuming that the uncertainty is a function of optical water type (OWT), which characterises the water column of each observed pixel in terms of their reflectance properties.
Within this work we apply the well-known Desroziers et al. (2005) consistency diagnostics to the Met Office’s NEMOVAR 3D-VAR DA system used to create daily biogeochemistry forecasts on the North-West European Shelf. The derived estimates of monthly ocean colour error covariances stratified by OWT are compared to previously derived estimates of the root mean square errors and biases using in-situ data match ups (Brewin et al. 2017). It is found that the agreement between the two estimates of the error variances have a strong seasonal and OWT dependence. The error correlations (which can only be estimated with the Desroziers’ method) in some instances are found to be significant out to a few 100km particularly for more turbid waters during the spring bloom. The reliability and limitation of these two estimates of the ocean colour uncertainty are discussed along with the implications for the future assimilation of ocean colour products and for ecosystem and climate studies.
How to cite: Fowler, A., Skákala, J., and Ciavatta, S.: Quantifying uncertainty in the ESA Ocean Colour – Climate Change Initiative dataset for assimilation of total chlorophyll and phytoplankton functional types, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18684, https://doi.org/10.5194/egusphere-egu2020-18684, 2020.
Monitoring biogeochemistry in shelf seas is of great significance for the economy, ecosystems understanding and climate studies. Data assimilation can aid the realism of marine biogeochemistry models by incorporating information from observations. An important source of information about phytoplankton groups and total chlorophyll is available from the ESA OC-CCI (ocean colour - climate change initiative) dataset.
For any assimilation system to be successful it is important to accurately represent all sources of data uncertainty. For the ocean colour product, the propagation of errors throughout the ocean colour algorithm makes the characterisation of the uncertainty challenging. However, the problem can be simplified by assuming that the uncertainty is a function of optical water type (OWT), which characterises the water column of each observed pixel in terms of their reflectance properties.
Within this work we apply the well-known Desroziers et al. (2005) consistency diagnostics to the Met Office’s NEMOVAR 3D-VAR DA system used to create daily biogeochemistry forecasts on the North-West European Shelf. The derived estimates of monthly ocean colour error covariances stratified by OWT are compared to previously derived estimates of the root mean square errors and biases using in-situ data match ups (Brewin et al. 2017). It is found that the agreement between the two estimates of the error variances have a strong seasonal and OWT dependence. The error correlations (which can only be estimated with the Desroziers’ method) in some instances are found to be significant out to a few 100km particularly for more turbid waters during the spring bloom. The reliability and limitation of these two estimates of the ocean colour uncertainty are discussed along with the implications for the future assimilation of ocean colour products and for ecosystem and climate studies.
How to cite: Fowler, A., Skákala, J., and Ciavatta, S.: Quantifying uncertainty in the ESA Ocean Colour – Climate Change Initiative dataset for assimilation of total chlorophyll and phytoplankton functional types, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18684, https://doi.org/10.5194/egusphere-egu2020-18684, 2020.
EGU2020-20271 | Displays | NP5.1
Accounting for model error in atmospheric forecastsWilliam Crawford, Sergey Frolov, Justin McLay, Carolyn Reynolds, Craig Bishop, Benjamin Ruston, and Neil Barton
The presented work will illustrate the impact of analysis correction based additive inflation (ACAI) on atmospheric forecasts. ACAI uses analysis corrections from the NAVGEM data assimilation system as a representation of model error and is shown to simultaneously improve ensemble spread-skill, reduce model bias and improve the RMS error in the ensemble mean. Results are presented from a myriad of experiments exercising ACAI in stand-alone NAVGEM forecasts using two different ensemble systems; (1) the current operational EPS at FNMOC based on the ensemble transform method and (2) the Navy-ESPC EPS based on perturbed observations. The method of relaxation-to-prior-perturbations (RTPP) has also been implemented in the Navy-ESPC EPS and is shown to further improve the ensemble spread-skill relationship by allowing variance generated during the forecast to impact the initial-time ensemble variance in the subsequent cycle. Results from a simplified implementation of ACAI in the NAVGEM deterministic system will also be shown and indicate positive impact to model biases and RMSE.
How to cite: Crawford, W., Frolov, S., McLay, J., Reynolds, C., Bishop, C., Ruston, B., and Barton, N.: Accounting for model error in atmospheric forecasts, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20271, https://doi.org/10.5194/egusphere-egu2020-20271, 2020.
The presented work will illustrate the impact of analysis correction based additive inflation (ACAI) on atmospheric forecasts. ACAI uses analysis corrections from the NAVGEM data assimilation system as a representation of model error and is shown to simultaneously improve ensemble spread-skill, reduce model bias and improve the RMS error in the ensemble mean. Results are presented from a myriad of experiments exercising ACAI in stand-alone NAVGEM forecasts using two different ensemble systems; (1) the current operational EPS at FNMOC based on the ensemble transform method and (2) the Navy-ESPC EPS based on perturbed observations. The method of relaxation-to-prior-perturbations (RTPP) has also been implemented in the Navy-ESPC EPS and is shown to further improve the ensemble spread-skill relationship by allowing variance generated during the forecast to impact the initial-time ensemble variance in the subsequent cycle. Results from a simplified implementation of ACAI in the NAVGEM deterministic system will also be shown and indicate positive impact to model biases and RMSE.
How to cite: Crawford, W., Frolov, S., McLay, J., Reynolds, C., Bishop, C., Ruston, B., and Barton, N.: Accounting for model error in atmospheric forecasts, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20271, https://doi.org/10.5194/egusphere-egu2020-20271, 2020.
EGU2020-7163 | Displays | NP5.1
Combined state-parameter estimation with the LETKF for convective-scale weather forecastingYvonne Ruckstuhl and Tijana Janjic
We investigate the feasibility of addressing model error by perturbing and estimating uncertain static model parameters using the localized ensemble transform Kalman filter. In particular we use the augmented state approach, where parameters are updated by observations via their correlation with observed state variables. This online approach offers a flexible, yet consistent way to better fit model variables affected by the chosen parameters to observations, while ensuring feasible model states. We show in a nearly-operational convection-permitting configuration that the prediction of clouds and precipitation with the COSMO-DE model is improved if the two dimensional roughness length parameter is estimated with the augmented state approach. Here, the targeted model error is the roughness length itself and the surface fluxes, which influence the initiation of convection. At analysis time, Gaussian noise with a specified correlation matrix is added to the roughness length to regulate the parameter spread. In the northern part of the COSMO-DE domain, where the terrain is mostly flat and assimilated surface wind measurements are dense, estimating the roughness length led to improved forecasts of up to six hours of clouds and precipitation. In the southern part of the domain, the parameter estimation was detrimental unless the correlation length scale of the Gaussian noise that is added to the roughness length is increased. The impact of the parameter estimation was found to be larger when synoptic forcing is weak and the model output is more sensitive to the roughness length.
How to cite: Ruckstuhl, Y. and Janjic, T.: Combined state-parameter estimation with the LETKF for convective-scale weather forecasting, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7163, https://doi.org/10.5194/egusphere-egu2020-7163, 2020.
We investigate the feasibility of addressing model error by perturbing and estimating uncertain static model parameters using the localized ensemble transform Kalman filter. In particular we use the augmented state approach, where parameters are updated by observations via their correlation with observed state variables. This online approach offers a flexible, yet consistent way to better fit model variables affected by the chosen parameters to observations, while ensuring feasible model states. We show in a nearly-operational convection-permitting configuration that the prediction of clouds and precipitation with the COSMO-DE model is improved if the two dimensional roughness length parameter is estimated with the augmented state approach. Here, the targeted model error is the roughness length itself and the surface fluxes, which influence the initiation of convection. At analysis time, Gaussian noise with a specified correlation matrix is added to the roughness length to regulate the parameter spread. In the northern part of the COSMO-DE domain, where the terrain is mostly flat and assimilated surface wind measurements are dense, estimating the roughness length led to improved forecasts of up to six hours of clouds and precipitation. In the southern part of the domain, the parameter estimation was detrimental unless the correlation length scale of the Gaussian noise that is added to the roughness length is increased. The impact of the parameter estimation was found to be larger when synoptic forcing is weak and the model output is more sensitive to the roughness length.
How to cite: Ruckstuhl, Y. and Janjic, T.: Combined state-parameter estimation with the LETKF for convective-scale weather forecasting, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7163, https://doi.org/10.5194/egusphere-egu2020-7163, 2020.
EGU2020-15517 | Displays | NP5.1
Bayesian inference of dynamics from partial and noisy observations using data assimilation and machine learningMarc Bocquet, Julien Brajard, Alberto Carrassi, and Laurent Bertino
The reconstruction from observations of the dynamics of high-dimensional chaotic models such as geophysical fluids is hampered by (i) the inevitably partial and noisy observations that can realistically be obtained, (ii) the need and difficulty to learn from long time series of data, and (iii) the unstable nature of the dynamics. To achieve such inference from the observations over long time series, it has recently been suggested to combine data assimilation and machine learning in several ways. We first rigorously show how to unify these approaches from a Bayesian perspective, yielding a non-trivial loss function.
Existing techniques to optimize the loss function (or simplified variants thereof) are re-interpreted here as coordinate descent schemes. The expectation-maximization (EM) method is used to estimate jointly the most likely model and model error statistics. The main algorithm alternates two steps: first, a posterior ensemble is derived using a traditional data assimilation step using an ensemble Kalman smoother (EnKS); second, both the surrogate model and the model error are updated using machine learning tools, a quasi-Newton optimizer, and analytical formula. In our case, the spatially extended surrogate model is formalized as a neural network with convolutional layers leveraging on the locality of the dynamics.
This scheme has been successfully tested on two low-order chaotic models with distinct identifiability, namely the 40-variable and the two-scale Lorenz models. Additionally, an approximate algorithm is tested to mitigate the numerical cost, yielding similar performances. Using indicators that probe short-term and asymptotic properties of the surrogate model, we investigate the sensitivity of the inference to the length of the training window, to the observation error magnitude, to the density of the monitoring network, and to the lag of the EnKS. In these iterative schemes, model error statistics are automatically adjusted to the improvement of the surrogate model dynamics. The outcome of the minimization is not only a deterministic surrogate model but also its associated stochastic correction, representative of the uncertainty attached to the deterministic part and which accounts for residual model errors.
How to cite: Bocquet, M., Brajard, J., Carrassi, A., and Bertino, L.: Bayesian inference of dynamics from partial and noisy observations using data assimilation and machine learning, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15517, https://doi.org/10.5194/egusphere-egu2020-15517, 2020.
The reconstruction from observations of the dynamics of high-dimensional chaotic models such as geophysical fluids is hampered by (i) the inevitably partial and noisy observations that can realistically be obtained, (ii) the need and difficulty to learn from long time series of data, and (iii) the unstable nature of the dynamics. To achieve such inference from the observations over long time series, it has recently been suggested to combine data assimilation and machine learning in several ways. We first rigorously show how to unify these approaches from a Bayesian perspective, yielding a non-trivial loss function.
Existing techniques to optimize the loss function (or simplified variants thereof) are re-interpreted here as coordinate descent schemes. The expectation-maximization (EM) method is used to estimate jointly the most likely model and model error statistics. The main algorithm alternates two steps: first, a posterior ensemble is derived using a traditional data assimilation step using an ensemble Kalman smoother (EnKS); second, both the surrogate model and the model error are updated using machine learning tools, a quasi-Newton optimizer, and analytical formula. In our case, the spatially extended surrogate model is formalized as a neural network with convolutional layers leveraging on the locality of the dynamics.
This scheme has been successfully tested on two low-order chaotic models with distinct identifiability, namely the 40-variable and the two-scale Lorenz models. Additionally, an approximate algorithm is tested to mitigate the numerical cost, yielding similar performances. Using indicators that probe short-term and asymptotic properties of the surrogate model, we investigate the sensitivity of the inference to the length of the training window, to the observation error magnitude, to the density of the monitoring network, and to the lag of the EnKS. In these iterative schemes, model error statistics are automatically adjusted to the improvement of the surrogate model dynamics. The outcome of the minimization is not only a deterministic surrogate model but also its associated stochastic correction, representative of the uncertainty attached to the deterministic part and which accounts for residual model errors.
How to cite: Bocquet, M., Brajard, J., Carrassi, A., and Bertino, L.: Bayesian inference of dynamics from partial and noisy observations using data assimilation and machine learning, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15517, https://doi.org/10.5194/egusphere-egu2020-15517, 2020.
EGU2020-2686 | Displays | NP5.1
A new method for computing horizontally anisotropic background error covariance matrices for data assimilation in ocean models.Jose M Gonzalez-Ondina, Lewis Sampson, and Georgy Shapiro
Current operational ocean modelling systems often use variational data assimilation (DA) to improve the skill of the ocean predictions by combining the numerical model with observational data. Many modern methods are derivatives of objective (optimal) interpolation techniques developed by L. S. Gandin in the 1950s, which requires computation of the background error covariance matrix (BECM), and much research has been devoted into overcoming the difficulties surrounding its calculation and improving its accuracy. In practice, due to time and memory constraints, the BECM is never fully computed. Instead, a simplified model is used, where the correlation at each point is modelled using a simple function while the variance and length scales are computed using error estimation methods such as the Hollingsworth-Lonnberg or the NMC (National Meteorological Centre). Usually, the correlation is assumed to be horizontally isotropic, or to have a predefined anisotropy based on latitude. However, observations indicate that horizontal diffusion is sometimes anisotropic, hence this has to be propagated into BECM. It is suggested that including these anisotropies would improve the accuracy of the model predictions.
We present a new method to compute the BECM which allows to extract horizontal anisotropic components from observational data. Our method, unlike current techniques, is fundamentally multidimensional and can be applied to 2D or 3D sets of un-binned data. It also works better than other methods when observations are sparse, so there is no penalty when trying to extract the additional anisotropic components from the data.
Data Assimilation tools like NEMOVar use a matrix decomposition technique for the BECM in order to minimise the cost function. Our method is well suited to work with this type of decomposition, producing the different components of the decomposition which can be readily used by NEMOVar.
We have been able to show the spatial stability of our method to quantify anisotropy in areas of sparse observations. While also demonstrating the importance of including anisotropic representation within the background error. Using the coastal regions of the Arabian Sea, it is possible to analyse where improvements to diffusion can be included. Further extensions of this method could lead to a fully anisotropic diffusion operator for the calculation of BECM in NEMOVar. However further testing and optimization are needed to correctly implement this into operational assimilation systems.
How to cite: Gonzalez-Ondina, J. M., Sampson, L., and Shapiro, G.: A new method for computing horizontally anisotropic background error covariance matrices for data assimilation in ocean models. , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2686, https://doi.org/10.5194/egusphere-egu2020-2686, 2020.
Current operational ocean modelling systems often use variational data assimilation (DA) to improve the skill of the ocean predictions by combining the numerical model with observational data. Many modern methods are derivatives of objective (optimal) interpolation techniques developed by L. S. Gandin in the 1950s, which requires computation of the background error covariance matrix (BECM), and much research has been devoted into overcoming the difficulties surrounding its calculation and improving its accuracy. In practice, due to time and memory constraints, the BECM is never fully computed. Instead, a simplified model is used, where the correlation at each point is modelled using a simple function while the variance and length scales are computed using error estimation methods such as the Hollingsworth-Lonnberg or the NMC (National Meteorological Centre). Usually, the correlation is assumed to be horizontally isotropic, or to have a predefined anisotropy based on latitude. However, observations indicate that horizontal diffusion is sometimes anisotropic, hence this has to be propagated into BECM. It is suggested that including these anisotropies would improve the accuracy of the model predictions.
We present a new method to compute the BECM which allows to extract horizontal anisotropic components from observational data. Our method, unlike current techniques, is fundamentally multidimensional and can be applied to 2D or 3D sets of un-binned data. It also works better than other methods when observations are sparse, so there is no penalty when trying to extract the additional anisotropic components from the data.
Data Assimilation tools like NEMOVar use a matrix decomposition technique for the BECM in order to minimise the cost function. Our method is well suited to work with this type of decomposition, producing the different components of the decomposition which can be readily used by NEMOVar.
We have been able to show the spatial stability of our method to quantify anisotropy in areas of sparse observations. While also demonstrating the importance of including anisotropic representation within the background error. Using the coastal regions of the Arabian Sea, it is possible to analyse where improvements to diffusion can be included. Further extensions of this method could lead to a fully anisotropic diffusion operator for the calculation of BECM in NEMOVar. However further testing and optimization are needed to correctly implement this into operational assimilation systems.
How to cite: Gonzalez-Ondina, J. M., Sampson, L., and Shapiro, G.: A new method for computing horizontally anisotropic background error covariance matrices for data assimilation in ocean models. , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2686, https://doi.org/10.5194/egusphere-egu2020-2686, 2020.
EGU2020-6241 | Displays | NP5.1
On the modification of operational oceanography forecasting system for South China Sea in National Marine Environmental Forecasting Center of ChinaZiqing Zu, Xueming Zhu, and Hui Wang
Based on ROMS and Ensemble Optimal Interpolation (EnOI) method, the South China Sea operational Oceanography Forecasting System (SCSOFS) is implemented in National Marine Environmental Forecasting Center (NMEFC), to provide the forecast of the currents, temperature and salinity in South China Sea for the future 5 days. Recently, a systematic modification has been carried out to SCSOFS to improve its forecast skill.
For the data assimilation system, new methods have been implemented, such as using Increment Analysis Update (IAU) and First Guess at Appropriate Time (FGAT), using a high-pass filter to evaluate the background error, assimilating multi-source observations, using non-uniform localization radius. In addition, the respective contribution of each method will also be discussed.
An optimization system is implemented for evaluating the values of physical parameters in ROMS, to remove the long-term bias of simulation. Argo temperature profiles is assimilated in the first half of 2017, to obtain the optimal coefficients of horizontal/vertical viscosity/diffusion and linear bottom drag. An independent validation from July of 2017 to December of 2018 shows that the simulation is improved using the optimal values.
How to cite: Zu, Z., Zhu, X., and Wang, H.: On the modification of operational oceanography forecasting system for South China Sea in National Marine Environmental Forecasting Center of China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6241, https://doi.org/10.5194/egusphere-egu2020-6241, 2020.
Based on ROMS and Ensemble Optimal Interpolation (EnOI) method, the South China Sea operational Oceanography Forecasting System (SCSOFS) is implemented in National Marine Environmental Forecasting Center (NMEFC), to provide the forecast of the currents, temperature and salinity in South China Sea for the future 5 days. Recently, a systematic modification has been carried out to SCSOFS to improve its forecast skill.
For the data assimilation system, new methods have been implemented, such as using Increment Analysis Update (IAU) and First Guess at Appropriate Time (FGAT), using a high-pass filter to evaluate the background error, assimilating multi-source observations, using non-uniform localization radius. In addition, the respective contribution of each method will also be discussed.
An optimization system is implemented for evaluating the values of physical parameters in ROMS, to remove the long-term bias of simulation. Argo temperature profiles is assimilated in the first half of 2017, to obtain the optimal coefficients of horizontal/vertical viscosity/diffusion and linear bottom drag. An independent validation from July of 2017 to December of 2018 shows that the simulation is improved using the optimal values.
How to cite: Zu, Z., Zhu, X., and Wang, H.: On the modification of operational oceanography forecasting system for South China Sea in National Marine Environmental Forecasting Center of China, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6241, https://doi.org/10.5194/egusphere-egu2020-6241, 2020.
EGU2020-6596 | Displays | NP5.1
A Flow-dependent Targeted Observation MethodYoumin Tang and Yaling Wu
In this study, we developed a flow-dependent ensemble-based targeted observation method, by minimizing the analysis error variance under the framework of Ensemble Kalman filter (EnKF) data assimilation system. This method estimates the background error statistics as a flow dependent function. The covariance localization is also introduced for computing efficiency and alleviating the spurious observations. As a test bed, an optimal observation array of sea level anomalies (SLA) is designed for its seasonal prediction over the tropical Indian Ocean (TIO) region. Furthermore, the observing system simulation experiments (OSSEs) is used to verify the resultant optimal observational array using our recently developed coupled data assimilation system. A comparison between this flow-dependent method and the traditional method is also given.
How to cite: Tang, Y. and Wu, Y.: A Flow-dependent Targeted Observation Method , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6596, https://doi.org/10.5194/egusphere-egu2020-6596, 2020.
In this study, we developed a flow-dependent ensemble-based targeted observation method, by minimizing the analysis error variance under the framework of Ensemble Kalman filter (EnKF) data assimilation system. This method estimates the background error statistics as a flow dependent function. The covariance localization is also introduced for computing efficiency and alleviating the spurious observations. As a test bed, an optimal observation array of sea level anomalies (SLA) is designed for its seasonal prediction over the tropical Indian Ocean (TIO) region. Furthermore, the observing system simulation experiments (OSSEs) is used to verify the resultant optimal observational array using our recently developed coupled data assimilation system. A comparison between this flow-dependent method and the traditional method is also given.
How to cite: Tang, Y. and Wu, Y.: A Flow-dependent Targeted Observation Method , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6596, https://doi.org/10.5194/egusphere-egu2020-6596, 2020.
NP5.2 – New approaches to predictions and predictability estimation for geophysical fluid
EGU2020-19959 | Displays | NP5.2
Paleo-drip rates from trace metal concentrations in stalagmites: An inverse modeling problem with data uncertaintiesBedartha Goswami, Adam Hartland, Chaoyong Hu, Sebastian Hoepker, Bethany R. S. Fox, Norbert Marwan, and Sebastian F. M. Breitenbach
The concentration of trace elements such as Ni, Co, and Cu in a stalagmite is determined by (i) the amount of these elements present in so-called organic-metal complexes (OMCs) that trap the ionic forms of such elements in the dripwater, and (ii) the amount that is able to decay from the OMCs into the aqueous phase, from where the elements can adsorb to the growing stalagmite surface (and remain captured within the stalagmite crystal structure). A statistical treatment of the decay of a population of trace element ions from OMCs allow us to model the rates at which the dripwater dropped from the roof of the cave on to the stalagmite’s surface. The problem is however made challenging due to: (i) the lack of reliable monitoring data that quantifies the relationship between OMC trace metal ion concentration and stalagmite trace metal ion concentration, and (ii) the presence of chronological uncertainties in our estimates of trace element concentrations at past time points from the depth-based measurements along the stalagmite. We present here a semi-heuristic, semi-theoretical approach that estimates dripwater rates using a theoretical model based on the population-level chemical kinetics of trace element decay from OMCs, and a heuristic choice of calibration data sets based on precipitation and temperature from nearby weather station data. Our approach is applied to trace metal data from the Heshang Cave in southeastern China, and we are able to reconstruct a driprate proxy time series — a first quantitative hydrological proxy record presented along with well-defined estimates of uncertainty.
How to cite: Goswami, B., Hartland, A., Hu, C., Hoepker, S., Fox, B. R. S., Marwan, N., and Breitenbach, S. F. M.: Paleo-drip rates from trace metal concentrations in stalagmites: An inverse modeling problem with data uncertainties, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19959, https://doi.org/10.5194/egusphere-egu2020-19959, 2020.
The concentration of trace elements such as Ni, Co, and Cu in a stalagmite is determined by (i) the amount of these elements present in so-called organic-metal complexes (OMCs) that trap the ionic forms of such elements in the dripwater, and (ii) the amount that is able to decay from the OMCs into the aqueous phase, from where the elements can adsorb to the growing stalagmite surface (and remain captured within the stalagmite crystal structure). A statistical treatment of the decay of a population of trace element ions from OMCs allow us to model the rates at which the dripwater dropped from the roof of the cave on to the stalagmite’s surface. The problem is however made challenging due to: (i) the lack of reliable monitoring data that quantifies the relationship between OMC trace metal ion concentration and stalagmite trace metal ion concentration, and (ii) the presence of chronological uncertainties in our estimates of trace element concentrations at past time points from the depth-based measurements along the stalagmite. We present here a semi-heuristic, semi-theoretical approach that estimates dripwater rates using a theoretical model based on the population-level chemical kinetics of trace element decay from OMCs, and a heuristic choice of calibration data sets based on precipitation and temperature from nearby weather station data. Our approach is applied to trace metal data from the Heshang Cave in southeastern China, and we are able to reconstruct a driprate proxy time series — a first quantitative hydrological proxy record presented along with well-defined estimates of uncertainty.
How to cite: Goswami, B., Hartland, A., Hu, C., Hoepker, S., Fox, B. R. S., Marwan, N., and Breitenbach, S. F. M.: Paleo-drip rates from trace metal concentrations in stalagmites: An inverse modeling problem with data uncertainties, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19959, https://doi.org/10.5194/egusphere-egu2020-19959, 2020.
EGU2020-4966 | Displays | NP5.2
Contrasting the skills and biases of deterministic predictions for the two types of El NiñoFei Zheng, Jin-Yi Yu, and Jiang Zhu
The tropical Pacific has experienced a new type of El Niño, which has occurred particularly frequently during the last decade and is referred to as the central Pacific (CP) El Niño. Various coupled models with different degrees of complexities have been used to make real-time El Niño predictions, but large uncertainties still exist in the forecasts. It is still not yet known how much of the uncertainty is specifically related to the new CP type of El Niño and how much is common to both this type and the conventional Eastern Pacific (EP) type of El Niño. In this study, the deterministic performance of an El Niño-Southern Oscillation (ENSO) ensemble prediction system (EPS) is examined for these two types of El Niño. Ensemble hindcasts are performed for the nine EP El Niño events and twelve CP El Niño events that have occurred since 1950. The results show that (1) the skill scores for the EP events are significantly better than those for the CP events at all lead times; (2) the systematic forecast biases come mostly from the prediction of the CP events; and (3) the systematic error is characterized by an overly warm eastern Pacific during the spring season, indicating a stronger spring prediction barrier for the CP El Niño. Further improvements of coupled atmosphere-ocean models in CP El Niño prediction should be recognized as a major challenge and high-priority task for the climate prediction community.
How to cite: Zheng, F., Yu, J.-Y., and Zhu, J.: Contrasting the skills and biases of deterministic predictions for the two types of El Niño, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4966, https://doi.org/10.5194/egusphere-egu2020-4966, 2020.
The tropical Pacific has experienced a new type of El Niño, which has occurred particularly frequently during the last decade and is referred to as the central Pacific (CP) El Niño. Various coupled models with different degrees of complexities have been used to make real-time El Niño predictions, but large uncertainties still exist in the forecasts. It is still not yet known how much of the uncertainty is specifically related to the new CP type of El Niño and how much is common to both this type and the conventional Eastern Pacific (EP) type of El Niño. In this study, the deterministic performance of an El Niño-Southern Oscillation (ENSO) ensemble prediction system (EPS) is examined for these two types of El Niño. Ensemble hindcasts are performed for the nine EP El Niño events and twelve CP El Niño events that have occurred since 1950. The results show that (1) the skill scores for the EP events are significantly better than those for the CP events at all lead times; (2) the systematic forecast biases come mostly from the prediction of the CP events; and (3) the systematic error is characterized by an overly warm eastern Pacific during the spring season, indicating a stronger spring prediction barrier for the CP El Niño. Further improvements of coupled atmosphere-ocean models in CP El Niño prediction should be recognized as a major challenge and high-priority task for the climate prediction community.
How to cite: Zheng, F., Yu, J.-Y., and Zhu, J.: Contrasting the skills and biases of deterministic predictions for the two types of El Niño, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4966, https://doi.org/10.5194/egusphere-egu2020-4966, 2020.
EGU2020-3475 | Displays | NP5.2
Detection of Dynamical Regime Transitions with Lacunarity as a Multiscale Recurrence Quantification MeasureTobias Braun, Norbert Marwan, Vishnu R. Unni, Raman I. Sujith, and Juergen Kurths
We propose Lacunarity as a novel recurrence quantification measure and apply it in the context of dynamical regime transitions. Many complex real-world systems exhibit abrupt regime shifts. We carry out a recurrence plot based analysis for different paradigmatic systems and thermoacoustic combustion time series in order to demonstrate the ability of our method to detect dynamical transitions on variable temporal scales. Lacunarity is usually interpreted as a measure of ‘gappiness’ of an arbitrary spatial pattern. In application to recurrence plots, it quantifies the degree of heterogenity in the temporal recurrent patterns. Our method succeeds to distinguish states of varying dynamical complexity in presence of noise and short time series length. In contrast to traditional recurrence quantifiers, no specification of minimal line lengths is required and features beyond the scope of line structures can be accounted for. Applied to acoustic pressure fluctuation time series, it captures both the rich variability in dynamical complexity and detects shifts of characteristic time scales.
How to cite: Braun, T., Marwan, N., Unni, V. R., Sujith, R. I., and Kurths, J.: Detection of Dynamical Regime Transitions with Lacunarity as a Multiscale Recurrence Quantification Measure, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3475, https://doi.org/10.5194/egusphere-egu2020-3475, 2020.
We propose Lacunarity as a novel recurrence quantification measure and apply it in the context of dynamical regime transitions. Many complex real-world systems exhibit abrupt regime shifts. We carry out a recurrence plot based analysis for different paradigmatic systems and thermoacoustic combustion time series in order to demonstrate the ability of our method to detect dynamical transitions on variable temporal scales. Lacunarity is usually interpreted as a measure of ‘gappiness’ of an arbitrary spatial pattern. In application to recurrence plots, it quantifies the degree of heterogenity in the temporal recurrent patterns. Our method succeeds to distinguish states of varying dynamical complexity in presence of noise and short time series length. In contrast to traditional recurrence quantifiers, no specification of minimal line lengths is required and features beyond the scope of line structures can be accounted for. Applied to acoustic pressure fluctuation time series, it captures both the rich variability in dynamical complexity and detects shifts of characteristic time scales.
How to cite: Braun, T., Marwan, N., Unni, V. R., Sujith, R. I., and Kurths, J.: Detection of Dynamical Regime Transitions with Lacunarity as a Multiscale Recurrence Quantification Measure, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3475, https://doi.org/10.5194/egusphere-egu2020-3475, 2020.
EGU2020-10984 | Displays | NP5.2
Detecting regimes of the mid-latitude atmospheric circulation by nonlinear data decompositionDmitry Mukhin and Abdel Hannachi
We suggest a method for nonlinear analysis of atmospheric circulation regimes in the middle latitudes. The method is based on the kernel principal component analysis allowing to separate principal modes of dynamics entangled in data. We propose a new kernel function accounting specifics of large-scale wave patterns in the mid-latitude atmosphere. First, capabilities of the method are shown by the analysis of the 3-layer quasi-geostrophic model of the Northern hemisphere atmosphere: a statistically significant set of modes can be detected by the method from relatively short (several thousand days) time series. Next, we consider reanalysis data of wintertime geopotential height anomalies over the Northern hemisphere from 1950 to the present. The principal components obtained uncover several recurrent and persistent wave structures which are associated with different weather regimes. We find that there is a pronounced inter-annual and decadal variability in the dominance of different modes in different years. Possible climatic and external forcings which impact such variability as well as long-term predictability of anomalous weather seasons based on the obtained components are discussed.
How to cite: Mukhin, D. and Hannachi, A.: Detecting regimes of the mid-latitude atmospheric circulation by nonlinear data decomposition, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10984, https://doi.org/10.5194/egusphere-egu2020-10984, 2020.
We suggest a method for nonlinear analysis of atmospheric circulation regimes in the middle latitudes. The method is based on the kernel principal component analysis allowing to separate principal modes of dynamics entangled in data. We propose a new kernel function accounting specifics of large-scale wave patterns in the mid-latitude atmosphere. First, capabilities of the method are shown by the analysis of the 3-layer quasi-geostrophic model of the Northern hemisphere atmosphere: a statistically significant set of modes can be detected by the method from relatively short (several thousand days) time series. Next, we consider reanalysis data of wintertime geopotential height anomalies over the Northern hemisphere from 1950 to the present. The principal components obtained uncover several recurrent and persistent wave structures which are associated with different weather regimes. We find that there is a pronounced inter-annual and decadal variability in the dominance of different modes in different years. Possible climatic and external forcings which impact such variability as well as long-term predictability of anomalous weather seasons based on the obtained components are discussed.
How to cite: Mukhin, D. and Hannachi, A.: Detecting regimes of the mid-latitude atmospheric circulation by nonlinear data decomposition, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10984, https://doi.org/10.5194/egusphere-egu2020-10984, 2020.
EGU2020-19079 | Displays | NP5.2
Learnt variability as a tool for climate prediction and predictabilityBalasubramanya Nadiga
Whether it is turbulence fluid flows or climate variability, there is a big gap between our ability to develop understanding of underlying phenomena/processes and our ability to produce skillful predictions. We focus on near-term prediction of climate as an example. In this context, the state-of-the-art is such that we are able to predict how 30-year global averages of surface temperature will change, but we are unable to predict shorter time scale regional changes. We investigate a range of deep learning approaches to the problem ranging from reservoir computing to deep convolutional Long Short-Term Memory network architectures. The best performing architectures are seen to be capable of predicting an Earth System Model’s leading modes of global temperature variability with prediction lead times of up to a year. This approach is proposed as a useful practical tool for climate prediction. Further insight into the difficulty of the prediction problem is provided by considering the Lorenz '63 model: Long prediction horizons seen when the system is fully observed is seen to be progressively degraded as the system is less thoroughly observed, while noting the difficulty of fully observing the earth system
How to cite: Nadiga, B.: Learnt variability as a tool for climate prediction and predictability, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19079, https://doi.org/10.5194/egusphere-egu2020-19079, 2020.
Whether it is turbulence fluid flows or climate variability, there is a big gap between our ability to develop understanding of underlying phenomena/processes and our ability to produce skillful predictions. We focus on near-term prediction of climate as an example. In this context, the state-of-the-art is such that we are able to predict how 30-year global averages of surface temperature will change, but we are unable to predict shorter time scale regional changes. We investigate a range of deep learning approaches to the problem ranging from reservoir computing to deep convolutional Long Short-Term Memory network architectures. The best performing architectures are seen to be capable of predicting an Earth System Model’s leading modes of global temperature variability with prediction lead times of up to a year. This approach is proposed as a useful practical tool for climate prediction. Further insight into the difficulty of the prediction problem is provided by considering the Lorenz '63 model: Long prediction horizons seen when the system is fully observed is seen to be progressively degraded as the system is less thoroughly observed, while noting the difficulty of fully observing the earth system
How to cite: Nadiga, B.: Learnt variability as a tool for climate prediction and predictability, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19079, https://doi.org/10.5194/egusphere-egu2020-19079, 2020.
EGU2020-2113 | Displays | NP5.2 | Highlight
Improving the forecast skill of El Nino diversity: A nonlinear forcing singular vector approachLingjiang Tao, Wansuo Duan, and Stephane Vannitsem
Observations indicate that there exist two types of El Niño events: one is the EP-El Niño with a warming center in the eastern tropical Pacific, and the other is the CP-El Niño with large positive SST anomalies in the central tropical Pacific. Most current numerical models show low skills in identifying the El Niño diversity. The present study examines the dynamical properties of the ENSO forecast system NFSV-ICM which combines an intermediate complexity ENSO model (ICM) with a nonlinear forcing singular vector (NFSV)-tendency perturbation forecast model. This system is able to distinguish different types of El Niño in simulations and predictions. It is shown that the NFSV-ICM system is able to capture the horizontal distribution of the SST anomalies and their amplitudes in the mature phase of not only EP-El Niño but also CP-El Niño. At the same time, the NFSV-ICM is able to describe the evolution of SST anomalies associated with the two types of El Niño up to at least two-season lead time, while the corresponding forecasts with the ICM is only limited to at most one-season lead time. These improvements are associated with the modifications of atmospheric and ocean processes described by the ICM through the NFSV-tendency perturbations. In particular, the thermocline and zonal advection feedback are strongly modified and improve the conditions of emergence of both the EP- and CP-El Niño events. The NFSV-ICM therefore provides a useful platform for studying ENSO dynamics and predictability associated with El Niño diversities.
How to cite: Tao, L., Duan, W., and Vannitsem, S.: Improving the forecast skill of El Nino diversity: A nonlinear forcing singular vector approach, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2113, https://doi.org/10.5194/egusphere-egu2020-2113, 2020.
Observations indicate that there exist two types of El Niño events: one is the EP-El Niño with a warming center in the eastern tropical Pacific, and the other is the CP-El Niño with large positive SST anomalies in the central tropical Pacific. Most current numerical models show low skills in identifying the El Niño diversity. The present study examines the dynamical properties of the ENSO forecast system NFSV-ICM which combines an intermediate complexity ENSO model (ICM) with a nonlinear forcing singular vector (NFSV)-tendency perturbation forecast model. This system is able to distinguish different types of El Niño in simulations and predictions. It is shown that the NFSV-ICM system is able to capture the horizontal distribution of the SST anomalies and their amplitudes in the mature phase of not only EP-El Niño but also CP-El Niño. At the same time, the NFSV-ICM is able to describe the evolution of SST anomalies associated with the two types of El Niño up to at least two-season lead time, while the corresponding forecasts with the ICM is only limited to at most one-season lead time. These improvements are associated with the modifications of atmospheric and ocean processes described by the ICM through the NFSV-tendency perturbations. In particular, the thermocline and zonal advection feedback are strongly modified and improve the conditions of emergence of both the EP- and CP-El Niño events. The NFSV-ICM therefore provides a useful platform for studying ENSO dynamics and predictability associated with El Niño diversities.
How to cite: Tao, L., Duan, W., and Vannitsem, S.: Improving the forecast skill of El Nino diversity: A nonlinear forcing singular vector approach, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2113, https://doi.org/10.5194/egusphere-egu2020-2113, 2020.
EGU2020-5916 | Displays | NP5.2
Study of Tropical Cyclones in the North Indian Ocean basin using Percolation in Climate NetworksShraddha Gupta, Jürgen Kurths, and Florian Pappenberger
Every point on the Earth’s surface is a dynamical system which behaves in a complex way while interacting with other dynamical systems. Network theory captures this feature of climate to study the collective behaviour of these interacting systems giving new insights into the problem. Recently, climate networks have been a promising approach to the study of climate phenomena such as El Niño, Indian monsoon, etc. These phenomena, however, occur over a long period of time. Weather phenomena such as tropical cyclones (TCs) that are relatively short-lived, destructive events are a major concern to life and property especially for densely populated coastlines such as in the North Indian Ocean (NIO) basin. Here, we study TCs in the NIO basin by constructing climate networks using the ERA5 Sea Surface Temperature and Air temperature at 1000 hPa. We analyze these networks using the percolation framework for the post-monsoon (October-November-December) season which experiences a high frequency of TCs every year. We find significant signatures of TCs in the network structure which appear as abrupt discontinuities in the percolation-based parameters during the period of a TC. This shows the potential of climate networks towards forecasting of tropical cyclones.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 813844.
How to cite: Gupta, S., Kurths, J., and Pappenberger, F.: Study of Tropical Cyclones in the North Indian Ocean basin using Percolation in Climate Networks, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5916, https://doi.org/10.5194/egusphere-egu2020-5916, 2020.
Every point on the Earth’s surface is a dynamical system which behaves in a complex way while interacting with other dynamical systems. Network theory captures this feature of climate to study the collective behaviour of these interacting systems giving new insights into the problem. Recently, climate networks have been a promising approach to the study of climate phenomena such as El Niño, Indian monsoon, etc. These phenomena, however, occur over a long period of time. Weather phenomena such as tropical cyclones (TCs) that are relatively short-lived, destructive events are a major concern to life and property especially for densely populated coastlines such as in the North Indian Ocean (NIO) basin. Here, we study TCs in the NIO basin by constructing climate networks using the ERA5 Sea Surface Temperature and Air temperature at 1000 hPa. We analyze these networks using the percolation framework for the post-monsoon (October-November-December) season which experiences a high frequency of TCs every year. We find significant signatures of TCs in the network structure which appear as abrupt discontinuities in the percolation-based parameters during the period of a TC. This shows the potential of climate networks towards forecasting of tropical cyclones.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 813844.
How to cite: Gupta, S., Kurths, J., and Pappenberger, F.: Study of Tropical Cyclones in the North Indian Ocean basin using Percolation in Climate Networks, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5916, https://doi.org/10.5194/egusphere-egu2020-5916, 2020.
EGU2020-2408 | Displays | NP5.2
Identifying the sensitive area in targeted observation for improving the vertical thermal structure prediction in the summer Yellow SeaKun Liu, Jingyi Liu, Huiqin Hu, Wuhong Guo, and Baolong Cui
The sensitive area of targeted observation for the short-term prediction of the vertical thermal structure in the summer Yellow Sea is investigated by utilizing the Conditional Nonlinear Optimal Perturbation (CNOP) method and a adjoint-free algorithm with the Regional Ocean Modeling System. We use a vertical integration scheme of temperature to locate the sensitive area, in which reducing the initial errors are expected to yield great improvements in vertical thermal structure prediction of the verification area. We perform a series of sensitivity experiments to evaluate the effectiveness of the identified sensitive area. Our results show that, initially adding random perturbations in the sensitive area have the greatest negative effects on the prediction than in other areas (eg. the verification area, regions east and northeast of the verification area). Moreover, Observing System Simulation Experiments (OSSEs) indicate that, eliminating the initial errors in the sensitive area can lead to a more refined prediction than in other selected areas (including the verification area itself). Our study suggests that implementing targeted observation is a feasible way to improve the short-term prediction of the vertical thermal structure in the summer Yellow Sea.
How to cite: Liu, K., Liu, J., Hu, H., Guo, W., and Cui, B.: Identifying the sensitive area in targeted observation for improving the vertical thermal structure prediction in the summer Yellow Sea, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2408, https://doi.org/10.5194/egusphere-egu2020-2408, 2020.
The sensitive area of targeted observation for the short-term prediction of the vertical thermal structure in the summer Yellow Sea is investigated by utilizing the Conditional Nonlinear Optimal Perturbation (CNOP) method and a adjoint-free algorithm with the Regional Ocean Modeling System. We use a vertical integration scheme of temperature to locate the sensitive area, in which reducing the initial errors are expected to yield great improvements in vertical thermal structure prediction of the verification area. We perform a series of sensitivity experiments to evaluate the effectiveness of the identified sensitive area. Our results show that, initially adding random perturbations in the sensitive area have the greatest negative effects on the prediction than in other areas (eg. the verification area, regions east and northeast of the verification area). Moreover, Observing System Simulation Experiments (OSSEs) indicate that, eliminating the initial errors in the sensitive area can lead to a more refined prediction than in other selected areas (including the verification area itself). Our study suggests that implementing targeted observation is a feasible way to improve the short-term prediction of the vertical thermal structure in the summer Yellow Sea.
How to cite: Liu, K., Liu, J., Hu, H., Guo, W., and Cui, B.: Identifying the sensitive area in targeted observation for improving the vertical thermal structure prediction in the summer Yellow Sea, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2408, https://doi.org/10.5194/egusphere-egu2020-2408, 2020.
EGU2020-2901 | Displays | NP5.2 | Highlight
On the use of near-neutral backward Lyapunov vectors to get reliable ensemble forecasts in coupled ocean-atmosphere systemsStéphane Vannitsem and Wansuo Duan
The use of coupled Backward Lyapunov vectors (BLv) for ensemble forecast is demonstrated in a coupled ocean-atmosphere system of reduced order, the Modular Arbitrary Order Ocean-Atmosphere sytem (MAOOAM). It is found that the best set of BLvs to build a coupled ocean-atmosphere forecasting system are the ones associated with near-neutral or slightly negative Lyapunov exponents. This counter intuitive result is related to the fact that these sets display larger projections on the ocean variables than the others, leading to an appropriate spread for the ocean, and at the same time a rapid transfer of these errors toward the most unstable BLvs affecting predominantly the atmosphere is experienced. The latter dynamics is a natural property of any generic perturbation in nonlinear chaotic dynamical systems, allowing for a reliable spread with the atmosphere too. The implications of these results for operational ensemble forecasts in coupled ocean-atmosphere systems are discussed.
How to cite: Vannitsem, S. and Duan, W.: On the use of near-neutral backward Lyapunov vectors to get reliable ensemble forecasts in coupled ocean-atmosphere systems, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2901, https://doi.org/10.5194/egusphere-egu2020-2901, 2020.
The use of coupled Backward Lyapunov vectors (BLv) for ensemble forecast is demonstrated in a coupled ocean-atmosphere system of reduced order, the Modular Arbitrary Order Ocean-Atmosphere sytem (MAOOAM). It is found that the best set of BLvs to build a coupled ocean-atmosphere forecasting system are the ones associated with near-neutral or slightly negative Lyapunov exponents. This counter intuitive result is related to the fact that these sets display larger projections on the ocean variables than the others, leading to an appropriate spread for the ocean, and at the same time a rapid transfer of these errors toward the most unstable BLvs affecting predominantly the atmosphere is experienced. The latter dynamics is a natural property of any generic perturbation in nonlinear chaotic dynamical systems, allowing for a reliable spread with the atmosphere too. The implications of these results for operational ensemble forecasts in coupled ocean-atmosphere systems are discussed.
How to cite: Vannitsem, S. and Duan, W.: On the use of near-neutral backward Lyapunov vectors to get reliable ensemble forecasts in coupled ocean-atmosphere systems, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2901, https://doi.org/10.5194/egusphere-egu2020-2901, 2020.
EGU2020-2942 | Displays | NP5.2
Sensitivity on tendency perturbations of tropical cyclone short-range intensity forecasts generated by WRFXiaohao Qin, Wansuo Duan, and Hui Xu
The present study uses the nonlinear singular vector (NFSV) approach to identify the optimally-growing tendency perturbations of the Weather Research and Forecasting (WRF) model for tropical cyclone (TC) intensity forecasts. For nine selected TC cases, the NFSV-tendency perturbations of the WRF model, including components of potential temperature and/or moisture, are calculated when TC intensities are forecasted with a 24-hour lead time, and their respective potential temperature components are demonstrated to have more impact on the TC intensity forecasts. The perturbations coherently show barotropic structure around the central location of the TCs at the 24-hour lead time, and their dominant energies concentrate in the middle layers of the atmosphere. Moreover, such structures do not depend on TC intensities and subsequent development of the TC. The NFSV-tendency perturbations may indicate that the model uncertainty that is represented by tendency perturbations but associated with the inner-core of TCs, makes larger contributions to the TC intensity forecast uncertainty. Further analysis shows that the TC intensity forecast skill could be greatly improved as preferentially superimposing an appropriate tendency perturbation associated with the sensitivity of NFSVs to correct the model, even if using a WRF with coarse resolution.
How to cite: Qin, X., Duan, W., and Xu, H.: Sensitivity on tendency perturbations of tropical cyclone short-range intensity forecasts generated by WRF, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2942, https://doi.org/10.5194/egusphere-egu2020-2942, 2020.
The present study uses the nonlinear singular vector (NFSV) approach to identify the optimally-growing tendency perturbations of the Weather Research and Forecasting (WRF) model for tropical cyclone (TC) intensity forecasts. For nine selected TC cases, the NFSV-tendency perturbations of the WRF model, including components of potential temperature and/or moisture, are calculated when TC intensities are forecasted with a 24-hour lead time, and their respective potential temperature components are demonstrated to have more impact on the TC intensity forecasts. The perturbations coherently show barotropic structure around the central location of the TCs at the 24-hour lead time, and their dominant energies concentrate in the middle layers of the atmosphere. Moreover, such structures do not depend on TC intensities and subsequent development of the TC. The NFSV-tendency perturbations may indicate that the model uncertainty that is represented by tendency perturbations but associated with the inner-core of TCs, makes larger contributions to the TC intensity forecast uncertainty. Further analysis shows that the TC intensity forecast skill could be greatly improved as preferentially superimposing an appropriate tendency perturbation associated with the sensitivity of NFSVs to correct the model, even if using a WRF with coarse resolution.
How to cite: Qin, X., Duan, W., and Xu, H.: Sensitivity on tendency perturbations of tropical cyclone short-range intensity forecasts generated by WRF, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2942, https://doi.org/10.5194/egusphere-egu2020-2942, 2020.
EGU2020-3293 | Displays | NP5.2
Evaluating the effect of tropical and extratropical Pacific initial errors on two types of El Niño prediction using particle filter approachMeiyi Hou and Xiefei Zhi
Different types of El Niño-Southern Oscillation (ENSO) predictions are sensitive to the initial errors in different key areas in the Pacific Ocean. And it is known that the prediction can be improved by removing the initial errors by using assimilation methods. However yet, few studies have quantified to what extent can different types of ENSO predictions be improved by assimilating variable in different key areas. In Hou et.al (2019), 4 types of ocean temperature initial error patterns were classified for two types of El Niño prediction. It was indicated that initial errors in the north Pacific, covering the Victoria Mode region, along with south Pacific, covering the South Pacific Meridional Mode region, and subsurface layer of western equatorial Pacific have strong influence on the ENSO prediction. Following the data analysis method and the initial error patterns they proposed, we assimilate ocean temperature in these three key areas of Pacific Ocean by using CMIP5 pi-control dataset and particle filter method. Most EP- and CP-El Niño predictions in December are improved after assimilating the ocean temperature in southeast Pacific, north Pacific and western equatorial Pacific from January to March. Specially, for the prediction ensemble which contains EP(CP)-type-1 initial errors, the EP(CP)-El Niño prediction skill raises the most after assimilating the Tropical Pacific temperature, comparing with the result of assimilating the south Pacific and north Pacific. As for the prediction ensemble which contains EP-type-2 initial errors, which present similar pattern to EP-type-1 but with opposite sign, the EP-El Niño prediction skill increases the most by assimilating the north Pacific temperature. The results verify that the initial errors in the north Pacific exert contrary influences on the ENSO prediction with that in the southeast Pacific and western tropical Pacific. In addition, the initial errors in the north Pacific is more of concern for the SST prediction in the central tropical Pacific in December, while those in the southeast Pacific and tropical western Pacific is more related to the SST prediction in the central-eastern tropical Pacific. In conclusion, to better predict the types of El Niño, attentions should be paid to the initial ocean temperature accuracy not only in the tropical Pacific but also in the north and south Pacific.
How to cite: Hou, M. and Zhi, X.: Evaluating the effect of tropical and extratropical Pacific initial errors on two types of El Niño prediction using particle filter approach, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3293, https://doi.org/10.5194/egusphere-egu2020-3293, 2020.
Different types of El Niño-Southern Oscillation (ENSO) predictions are sensitive to the initial errors in different key areas in the Pacific Ocean. And it is known that the prediction can be improved by removing the initial errors by using assimilation methods. However yet, few studies have quantified to what extent can different types of ENSO predictions be improved by assimilating variable in different key areas. In Hou et.al (2019), 4 types of ocean temperature initial error patterns were classified for two types of El Niño prediction. It was indicated that initial errors in the north Pacific, covering the Victoria Mode region, along with south Pacific, covering the South Pacific Meridional Mode region, and subsurface layer of western equatorial Pacific have strong influence on the ENSO prediction. Following the data analysis method and the initial error patterns they proposed, we assimilate ocean temperature in these three key areas of Pacific Ocean by using CMIP5 pi-control dataset and particle filter method. Most EP- and CP-El Niño predictions in December are improved after assimilating the ocean temperature in southeast Pacific, north Pacific and western equatorial Pacific from January to March. Specially, for the prediction ensemble which contains EP(CP)-type-1 initial errors, the EP(CP)-El Niño prediction skill raises the most after assimilating the Tropical Pacific temperature, comparing with the result of assimilating the south Pacific and north Pacific. As for the prediction ensemble which contains EP-type-2 initial errors, which present similar pattern to EP-type-1 but with opposite sign, the EP-El Niño prediction skill increases the most by assimilating the north Pacific temperature. The results verify that the initial errors in the north Pacific exert contrary influences on the ENSO prediction with that in the southeast Pacific and western tropical Pacific. In addition, the initial errors in the north Pacific is more of concern for the SST prediction in the central tropical Pacific in December, while those in the southeast Pacific and tropical western Pacific is more related to the SST prediction in the central-eastern tropical Pacific. In conclusion, to better predict the types of El Niño, attentions should be paid to the initial ocean temperature accuracy not only in the tropical Pacific but also in the north and south Pacific.
How to cite: Hou, M. and Zhi, X.: Evaluating the effect of tropical and extratropical Pacific initial errors on two types of El Niño prediction using particle filter approach, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3293, https://doi.org/10.5194/egusphere-egu2020-3293, 2020.
EGU2020-7885 | Displays | NP5.2
Global-scale teleconnections of extreme rainfall revealed by complex networksNiklas Boers, Bedartha Goswami, Aljoscha Rheinwalt, Bodo Bookhagen, Brian Hoskins, and Jürgen Kurths
Extreme rainfall events are often coupled across long spatial distances due to atmospheric teleconnections. Revealing such linkages is important for our understanding of extreme events and related atmospheric circulation patterns, but also for enhancing the forecast skill of such events [1]. Here, we present recent results [2] on how complex networks can be employed to discover extreme rainfall teleconnections from high-resolution satellite data. Our method allows to quantitatively distinguish regional weather systems from global-scale teleconnections coupling the individual weather systems. Several lines of evidence suggest that the most relevant mechanisms for global-scale teleconnections of extreme rainfall events are related to atmospheric Rossby waves. We exemplify our approach with a focus on extreme rainfall events in the mountain regions of South-Central Asia (including Northern Pakistan and India), and show that they are statistically significantly coupled to preceding events in Europe as well as succeeding events in eastern China. An analysis of the corresponding atmospheric circulation patterns shows that a previously revealed, quasi-stationary Rossby wave termed the ‘silk road pattern’ [3] is responsible for this instance of long-range coupling between extreme rainfall events. Overall, our findings give new insights into the connections between atmospheric Rossby waves and extreme rainfall events, and thus into the potential predictability of related natural hazards. Moreover, they give promising clues in how to constrain state-of-the-art climate models with respect to their simulation of extreme rainfall.
[1] B. Hoskins: The potential for skill across the range of the seamless weather-climate prediction problem: A stimulus for our science, QJRMS 2013
[2] N. Boers, B. Goswami, A. Rheinwalt, B. Bookhagen, B. Hoskins, J. Kurths: Complex networks reveal global pattern of extreme-rainfall teleconnections, Nature 2019
[3] T. Enomoto, B. Hoskins, Y. Matsuda: The formation mechanism of the Bonin high in August, QJRMS 2003
How to cite: Boers, N., Goswami, B., Rheinwalt, A., Bookhagen, B., Hoskins, B., and Kurths, J.: Global-scale teleconnections of extreme rainfall revealed by complex networks, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7885, https://doi.org/10.5194/egusphere-egu2020-7885, 2020.
Extreme rainfall events are often coupled across long spatial distances due to atmospheric teleconnections. Revealing such linkages is important for our understanding of extreme events and related atmospheric circulation patterns, but also for enhancing the forecast skill of such events [1]. Here, we present recent results [2] on how complex networks can be employed to discover extreme rainfall teleconnections from high-resolution satellite data. Our method allows to quantitatively distinguish regional weather systems from global-scale teleconnections coupling the individual weather systems. Several lines of evidence suggest that the most relevant mechanisms for global-scale teleconnections of extreme rainfall events are related to atmospheric Rossby waves. We exemplify our approach with a focus on extreme rainfall events in the mountain regions of South-Central Asia (including Northern Pakistan and India), and show that they are statistically significantly coupled to preceding events in Europe as well as succeeding events in eastern China. An analysis of the corresponding atmospheric circulation patterns shows that a previously revealed, quasi-stationary Rossby wave termed the ‘silk road pattern’ [3] is responsible for this instance of long-range coupling between extreme rainfall events. Overall, our findings give new insights into the connections between atmospheric Rossby waves and extreme rainfall events, and thus into the potential predictability of related natural hazards. Moreover, they give promising clues in how to constrain state-of-the-art climate models with respect to their simulation of extreme rainfall.
[1] B. Hoskins: The potential for skill across the range of the seamless weather-climate prediction problem: A stimulus for our science, QJRMS 2013
[2] N. Boers, B. Goswami, A. Rheinwalt, B. Bookhagen, B. Hoskins, J. Kurths: Complex networks reveal global pattern of extreme-rainfall teleconnections, Nature 2019
[3] T. Enomoto, B. Hoskins, Y. Matsuda: The formation mechanism of the Bonin high in August, QJRMS 2003
How to cite: Boers, N., Goswami, B., Rheinwalt, A., Bookhagen, B., Hoskins, B., and Kurths, J.: Global-scale teleconnections of extreme rainfall revealed by complex networks, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7885, https://doi.org/10.5194/egusphere-egu2020-7885, 2020.
EGU2020-3319 | Displays | NP5.2
Contributions of tropical-extratropical oceans to the prediction skill of ENSO after 2000Liang Shi, Ruiqiang Ding, and Yu-heng Tseng
The skills of most ENSO prediction models have declined significantly since 2000. This decline may be due to a weakening of the correlation between tropical predictors and ENSO. Moreover, the effects of extratropical ocean variability on ENSO have increased during this period. To improve ENSO predictability, we investigate the influence of the tropical-extratropical Atlantic and Pacific sea surface temperature(SST) on ENSO during the periods of pre-2000 and post-2000. We find that the influence of the northern tropical Atlantic(NTA) SST on ENSO has significantly increase since 2000. Meanwhile, there is a much earlier and stronger SST responses between NTA SST and ENSO over the central-eastern Pacific during June–July–August in the post-2000 period compared with the pre-2000 period. Furthermore, the extratropical Pacific SST predictors for ENSO still retain a ~10-month lead time after 2000. We use SST signals in the extratropical Atlantic and Pacific to predict ENSO using a statistical prediction model. These results reveal a significant improvement in ENSO prediction skills. These results indicate that the Atlantic and Pacific SSTAs can make substantial contributions to ENSO prediction, and can be further used to enhance ENSO predictability after 2000.
How to cite: Shi, L., Ding, R., and Tseng, Y.: Contributions of tropical-extratropical oceans to the prediction skill of ENSO after 2000, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3319, https://doi.org/10.5194/egusphere-egu2020-3319, 2020.
The skills of most ENSO prediction models have declined significantly since 2000. This decline may be due to a weakening of the correlation between tropical predictors and ENSO. Moreover, the effects of extratropical ocean variability on ENSO have increased during this period. To improve ENSO predictability, we investigate the influence of the tropical-extratropical Atlantic and Pacific sea surface temperature(SST) on ENSO during the periods of pre-2000 and post-2000. We find that the influence of the northern tropical Atlantic(NTA) SST on ENSO has significantly increase since 2000. Meanwhile, there is a much earlier and stronger SST responses between NTA SST and ENSO over the central-eastern Pacific during June–July–August in the post-2000 period compared with the pre-2000 period. Furthermore, the extratropical Pacific SST predictors for ENSO still retain a ~10-month lead time after 2000. We use SST signals in the extratropical Atlantic and Pacific to predict ENSO using a statistical prediction model. These results reveal a significant improvement in ENSO prediction skills. These results indicate that the Atlantic and Pacific SSTAs can make substantial contributions to ENSO prediction, and can be further used to enhance ENSO predictability after 2000.
How to cite: Shi, L., Ding, R., and Tseng, Y.: Contributions of tropical-extratropical oceans to the prediction skill of ENSO after 2000, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3319, https://doi.org/10.5194/egusphere-egu2020-3319, 2020.
EGU2020-4017 | Displays | NP5.2
Preliminary application of machine learning in ensemble forecastingJunjie Ma and Wansuo Duan
The optimal perturbation method is a beneficial way to generate ensemble members to be used in ensemble forecasting. With orthogonal optimal perturbation, orthogonal conditional nonlinear optimal perturbations (O-CNOPs) generating initial perturbations and orthogonal nonlinear forcing singular vectors (O-NFSVs) generating model perturbations are two kinds of skillful ensemble forecasting methods. There is main disadvantage that O-CNOPs and O-NFSVs generate optimal perturbation members may need a lot of time, but in practical weather prediction, the ensemble members usually need to be generated quickly. In order to benefit from O-CNOPs and O-NFSVs, as well as considering the cost of calculation, therefore, we present a way with the big data and machine learning thinking to simplify the process of the optimal perturbation ensemble methods. Using the historical samples and their optimal perturbations to establish a database, we look for the historical sample which is analogous to what need to be forecasted currently from the database by using the convolutional neural network (CNN). In comparison with using optimization algorithm to get O-CNOPs and O-NFSVs directly, this way gets O-CNOPs and O-NFSVs faster which still obtain acceptable prediction performance. In addition, once the CNN model is trained completely, the cost of time for prediction will be saved. We illustrate the advantage by numerical simulations of a Lorenz 96 model.
Further more, based on above study, some comparison of the ensemble forecasting skill of O-CNOPs and O-NFSVs has been done, and there are three results for the reference: (1) in the early stage (1-6 days), the O-CNOPs method perform more skillfully, and in the later stage (6-12 days), the O-NFSVs method perform more skillfully; (2) within 1-5 days, if the development of analysis error is bigger than or close to the average value of the analysis error development of historical samples, the O-CNOPs method is preferred, else the O-NFSVs method is preferred; (3) within 0-3 days, if the development of energy is bigger than or close to the average value of the energy development of the historical samples, the O-CNOPs method is preferred, else the O-NFVS method is preferred. Next, further work is required to examine and explore more and deeper research using machine learning in ensemble forecasting studies of atmosphere and other systems.
How to cite: Ma, J. and Duan, W.: Preliminary application of machine learning in ensemble forecasting, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4017, https://doi.org/10.5194/egusphere-egu2020-4017, 2020.
The optimal perturbation method is a beneficial way to generate ensemble members to be used in ensemble forecasting. With orthogonal optimal perturbation, orthogonal conditional nonlinear optimal perturbations (O-CNOPs) generating initial perturbations and orthogonal nonlinear forcing singular vectors (O-NFSVs) generating model perturbations are two kinds of skillful ensemble forecasting methods. There is main disadvantage that O-CNOPs and O-NFSVs generate optimal perturbation members may need a lot of time, but in practical weather prediction, the ensemble members usually need to be generated quickly. In order to benefit from O-CNOPs and O-NFSVs, as well as considering the cost of calculation, therefore, we present a way with the big data and machine learning thinking to simplify the process of the optimal perturbation ensemble methods. Using the historical samples and their optimal perturbations to establish a database, we look for the historical sample which is analogous to what need to be forecasted currently from the database by using the convolutional neural network (CNN). In comparison with using optimization algorithm to get O-CNOPs and O-NFSVs directly, this way gets O-CNOPs and O-NFSVs faster which still obtain acceptable prediction performance. In addition, once the CNN model is trained completely, the cost of time for prediction will be saved. We illustrate the advantage by numerical simulations of a Lorenz 96 model.
Further more, based on above study, some comparison of the ensemble forecasting skill of O-CNOPs and O-NFSVs has been done, and there are three results for the reference: (1) in the early stage (1-6 days), the O-CNOPs method perform more skillfully, and in the later stage (6-12 days), the O-NFSVs method perform more skillfully; (2) within 1-5 days, if the development of analysis error is bigger than or close to the average value of the analysis error development of historical samples, the O-CNOPs method is preferred, else the O-NFSVs method is preferred; (3) within 0-3 days, if the development of energy is bigger than or close to the average value of the energy development of the historical samples, the O-CNOPs method is preferred, else the O-NFVS method is preferred. Next, further work is required to examine and explore more and deeper research using machine learning in ensemble forecasting studies of atmosphere and other systems.
How to cite: Ma, J. and Duan, W.: Preliminary application of machine learning in ensemble forecasting, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4017, https://doi.org/10.5194/egusphere-egu2020-4017, 2020.
EGU2020-11463 | Displays | NP5.2
Application of linear dynamical mode decomposition to surface air temperature in 20th centuryAndrey Gavrilov, Sergey Kravtsov, Dmitry Mukhin, Evgeny Loskutov, and Alexander Feigin
According to recent study [1], the current state-of-the-art climate models lack the substantial part of internal multidecadal climate signal which is observed in the 20th century surface air temperature reanalysis data as a global stadium wave (GSW). In the presented work we further investigate this phenomenon using the recently developed method [2] of empirical spatio-temporal data decomposition into linear dynamical modes (LDMs). The important property of LDMs is their ability to take into account the time scales of the system evolution (they are extracted from observed dataset by the Bayesian optimization technique) better than some other linear techniques, e.g. traditional empirical orthogonal function decomposition. Like any linear decomposition, it provides the time series of principal components and corresponding spatial patterns.
We modify the initially developed LDM decomposition to make it possible to take into account a prescribed external forcing (like CO2 emissions, sun activity etc.) and then find part of variability which may be considered as an internal climate dynamics decomposed into set of modes with different time scales, and hence may be helpful in GSW interpretation. The results of applying the method to the 20th century surface air temperature with different ways of forcing inclusion will be presented and discussed.
1. Kravtsov, S., Grimm, C., & Gu, S. (2018). Global-scale multidecadal variability missing in state-of-the-art climate models. Npj Climate and Atmospheric Science, 1(1), 34. https://doi.org/10.1038/s41612-018-0044-6
2. Gavrilov, A., Seleznev, A., Mukhin, D., Loskutov, E., Feigin, A., & Kurths, J. (2018). Linear dynamical modes as new variables for data-driven ENSO forecast. Climate Dynamics. https://doi.org/10.1007/s00382-018-4255-7
How to cite: Gavrilov, A., Kravtsov, S., Mukhin, D., Loskutov, E., and Feigin, A.: Application of linear dynamical mode decomposition to surface air temperature in 20th century, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11463, https://doi.org/10.5194/egusphere-egu2020-11463, 2020.
According to recent study [1], the current state-of-the-art climate models lack the substantial part of internal multidecadal climate signal which is observed in the 20th century surface air temperature reanalysis data as a global stadium wave (GSW). In the presented work we further investigate this phenomenon using the recently developed method [2] of empirical spatio-temporal data decomposition into linear dynamical modes (LDMs). The important property of LDMs is their ability to take into account the time scales of the system evolution (they are extracted from observed dataset by the Bayesian optimization technique) better than some other linear techniques, e.g. traditional empirical orthogonal function decomposition. Like any linear decomposition, it provides the time series of principal components and corresponding spatial patterns.
We modify the initially developed LDM decomposition to make it possible to take into account a prescribed external forcing (like CO2 emissions, sun activity etc.) and then find part of variability which may be considered as an internal climate dynamics decomposed into set of modes with different time scales, and hence may be helpful in GSW interpretation. The results of applying the method to the 20th century surface air temperature with different ways of forcing inclusion will be presented and discussed.
1. Kravtsov, S., Grimm, C., & Gu, S. (2018). Global-scale multidecadal variability missing in state-of-the-art climate models. Npj Climate and Atmospheric Science, 1(1), 34. https://doi.org/10.1038/s41612-018-0044-6
2. Gavrilov, A., Seleznev, A., Mukhin, D., Loskutov, E., Feigin, A., & Kurths, J. (2018). Linear dynamical modes as new variables for data-driven ENSO forecast. Climate Dynamics. https://doi.org/10.1007/s00382-018-4255-7
How to cite: Gavrilov, A., Kravtsov, S., Mukhin, D., Loskutov, E., and Feigin, A.: Application of linear dynamical mode decomposition to surface air temperature in 20th century, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11463, https://doi.org/10.5194/egusphere-egu2020-11463, 2020.
EGU2020-6339 | Displays | NP5.2
Applying Conditional Nonlinear Optimal Perturbation (CNOP) in the ensemble ENSO forecast systemQian Zhou, Yunfei Zhang, Junya Hu, and Wansuo Duan
Considering the effects of initial uncertainty on the ENSO forecast, ensemble forecasts method is applied in the latest version of ENSO forecast system in National Marine Environmental Forecasting Center (NMEFC, China). The currently operational ENSO forecasts system of NMEFC is established based on the CESM model, with initialization and data assimilation.
First, leading five Singular Vectors (SV) are obtained using the climatological SST empirical singular vector method, and a SV based ensemble forecasts system is . However, the SVs can only present the initial errors that have the fasted error growth rates in a linear assumption, while ENSO and its forecasting system both are nonlinear. So, Conditional Nonlinear Optimal Perturbations (CNOP), which is has the largest error growth at the prediction time in a nonlinear scenario, is used to replace the leading SV, while other 4 SVs are kept to construct a CNOP-SV based ensemble forecast system. The hindcasts of ENSO from 1982 to 2017 shows that, the ENSO prediction skills of both SV based and CNOP-SV based ENSO ensemble forecasts are improved when compared with the old forecasting system, moreover, the CNOP-SV based ensemble forecast system has a much larger spread, showing higher prediction skills.
How to cite: Zhou, Q., Zhang, Y., Hu, J., and Duan, W.: Applying Conditional Nonlinear Optimal Perturbation (CNOP) in the ensemble ENSO forecast system, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6339, https://doi.org/10.5194/egusphere-egu2020-6339, 2020.
Considering the effects of initial uncertainty on the ENSO forecast, ensemble forecasts method is applied in the latest version of ENSO forecast system in National Marine Environmental Forecasting Center (NMEFC, China). The currently operational ENSO forecasts system of NMEFC is established based on the CESM model, with initialization and data assimilation.
First, leading five Singular Vectors (SV) are obtained using the climatological SST empirical singular vector method, and a SV based ensemble forecasts system is . However, the SVs can only present the initial errors that have the fasted error growth rates in a linear assumption, while ENSO and its forecasting system both are nonlinear. So, Conditional Nonlinear Optimal Perturbations (CNOP), which is has the largest error growth at the prediction time in a nonlinear scenario, is used to replace the leading SV, while other 4 SVs are kept to construct a CNOP-SV based ensemble forecast system. The hindcasts of ENSO from 1982 to 2017 shows that, the ENSO prediction skills of both SV based and CNOP-SV based ENSO ensemble forecasts are improved when compared with the old forecasting system, moreover, the CNOP-SV based ensemble forecast system has a much larger spread, showing higher prediction skills.
How to cite: Zhou, Q., Zhang, Y., Hu, J., and Duan, W.: Applying Conditional Nonlinear Optimal Perturbation (CNOP) in the ensemble ENSO forecast system, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6339, https://doi.org/10.5194/egusphere-egu2020-6339, 2020.
EGU2020-6584 | Displays | NP5.2
Season-dependent predictability and error growth dynamics for La Nina predictionsJunya Hu, Wansuo Duan, and Qian Zhou
The “spring predictability barrier” (SPB) is a well-known characteristic of ENSO prediction, which has been widely studied for El Niño events. However, due to the nonlinearity of the coupled ocean–atmosphere system and the asymmetries between El Niño and La Niña, it is worthy to investigate the SPB for La Niña events and reveal their differences with El Niño. This study investigates the season-dependent predictability of sea surface temperature (SST) for La Niña events by exploring initial error growth in a perfect model scenario within the Community Earth System Model. The results show that for the prediction through the spring season, the prediction errors caused by initial errors have a season-dependent evolution and induce an SPB for La Niña events. Two types of initial errors that often yield the SPB phenomenon are identified: the first are type-1 initial errors showing positive SST errors in the central-eastern equatorial Pacific accompanied by a large positive error in the upper layers of the eastern equatorial Pacific. The second are type-2 errors presenting an SST pattern with positive errors in the southeastern equatorial Pacific and a west–east dipole pattern in the subsurface ocean. The type-1 errors exhibit an evolving mode similar to the growth phase of an El Niño-like event, while the type-2 initially experience a La Niña-like decay and then a transition to the growth phase of an El Niño-like event. Both types of initial errors cause positive prediction errors for Niño3 SST and under-predict the corresponding La Niña events. The resultant prediction errors of type-1 errors are owing to the growth of the initial errors in the upper layers of the eastern equatorial Pacific. For the type-2 errors, the prediction errors originate from the initial errors in the subsurface layers of the western equatorial Pacific. These two regions may represent the sensitive areas of targeted observation for La Niña prediction. In addition, the type-2 errors in the equatorial regions are enlarged by the recharge process from 10°N in the central Pacific during the eastward propagation. Therefore, the off-equatorial regions around 10°N in the central Pacific may represent another sensitive area of La Niña prediction. Additional observations may be prioritized in these identified sensitive areas to better predict La Niña events.
How to cite: Hu, J., Duan, W., and Zhou, Q.: Season-dependent predictability and error growth dynamics for La Nina predictions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6584, https://doi.org/10.5194/egusphere-egu2020-6584, 2020.
The “spring predictability barrier” (SPB) is a well-known characteristic of ENSO prediction, which has been widely studied for El Niño events. However, due to the nonlinearity of the coupled ocean–atmosphere system and the asymmetries between El Niño and La Niña, it is worthy to investigate the SPB for La Niña events and reveal their differences with El Niño. This study investigates the season-dependent predictability of sea surface temperature (SST) for La Niña events by exploring initial error growth in a perfect model scenario within the Community Earth System Model. The results show that for the prediction through the spring season, the prediction errors caused by initial errors have a season-dependent evolution and induce an SPB for La Niña events. Two types of initial errors that often yield the SPB phenomenon are identified: the first are type-1 initial errors showing positive SST errors in the central-eastern equatorial Pacific accompanied by a large positive error in the upper layers of the eastern equatorial Pacific. The second are type-2 errors presenting an SST pattern with positive errors in the southeastern equatorial Pacific and a west–east dipole pattern in the subsurface ocean. The type-1 errors exhibit an evolving mode similar to the growth phase of an El Niño-like event, while the type-2 initially experience a La Niña-like decay and then a transition to the growth phase of an El Niño-like event. Both types of initial errors cause positive prediction errors for Niño3 SST and under-predict the corresponding La Niña events. The resultant prediction errors of type-1 errors are owing to the growth of the initial errors in the upper layers of the eastern equatorial Pacific. For the type-2 errors, the prediction errors originate from the initial errors in the subsurface layers of the western equatorial Pacific. These two regions may represent the sensitive areas of targeted observation for La Niña prediction. In addition, the type-2 errors in the equatorial regions are enlarged by the recharge process from 10°N in the central Pacific during the eastward propagation. Therefore, the off-equatorial regions around 10°N in the central Pacific may represent another sensitive area of La Niña prediction. Additional observations may be prioritized in these identified sensitive areas to better predict La Niña events.
How to cite: Hu, J., Duan, W., and Zhou, Q.: Season-dependent predictability and error growth dynamics for La Nina predictions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6584, https://doi.org/10.5194/egusphere-egu2020-6584, 2020.
EGU2020-11277 | Displays | NP5.2
The Middle Pleistocene Transition: estimation of the interval stability by data-driven modelEvgeny Loskutov, Valery Vdovin, Andrey Gavrilov, Dmitry Mukhin, and Alexander Feigin
We investigate the Middle Pleistocene Transition (MPT) - a rapid change in the periodicity of the Pleistocene glacial cycles from 41 kyr to about 100 kyr, which occurred about a million years ago - using the data-driven model [1]. Here we estimate stability of the model using a novel concept of interval stability [2-4], referring to the behavior of the perturbed model during a finite time interval. In a few words we define the class of 'safe' perturbations after which the system (our data-driven model) returns back to the initial dynamical regime and 'unsafe' perturbation of minimal amplitude needed to disrupt the system.
We demonstrate that the MPT is likely associated with decreasing of the climate system's interval stability to rapid disturbances (millennial and shorter). This confirms the statement made in the paper [1] that the main factor in the onset of the long-period glacial cycles is strongly nonlinear oscillations induced by the short-scale variability.
- D. Mukhin, A. Gavrilov, E. Loskutov, J. Kurths, A. Feigin. Bayesian Data Analysis for Revealing Causes of the Middle Pleistocene Transition. Scientific Reports, 9 7328 (2019).
- P. Menck, J. Heitzig, N. Marwan, J. Kurths. How basin stability complements the linear-stability paradigm. Nature Phys, 9 89–92 (2013).
- V. Klinshov, V. Nekorkin, J. Kurths. Stability threshold approach for complex dynamical systems. New Journal Physics, 18 013004 (2016).
- V. Klinshov, S. Kirillov, J. Kurths, V. Nekorkin. Interval stability for complex systems. New Journal Physics, 18 013004 (2018).
How to cite: Loskutov, E., Vdovin, V., Gavrilov, A., Mukhin, D., and Feigin, A.: The Middle Pleistocene Transition: estimation of the interval stability by data-driven model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11277, https://doi.org/10.5194/egusphere-egu2020-11277, 2020.
We investigate the Middle Pleistocene Transition (MPT) - a rapid change in the periodicity of the Pleistocene glacial cycles from 41 kyr to about 100 kyr, which occurred about a million years ago - using the data-driven model [1]. Here we estimate stability of the model using a novel concept of interval stability [2-4], referring to the behavior of the perturbed model during a finite time interval. In a few words we define the class of 'safe' perturbations after which the system (our data-driven model) returns back to the initial dynamical regime and 'unsafe' perturbation of minimal amplitude needed to disrupt the system.
We demonstrate that the MPT is likely associated with decreasing of the climate system's interval stability to rapid disturbances (millennial and shorter). This confirms the statement made in the paper [1] that the main factor in the onset of the long-period glacial cycles is strongly nonlinear oscillations induced by the short-scale variability.
- D. Mukhin, A. Gavrilov, E. Loskutov, J. Kurths, A. Feigin. Bayesian Data Analysis for Revealing Causes of the Middle Pleistocene Transition. Scientific Reports, 9 7328 (2019).
- P. Menck, J. Heitzig, N. Marwan, J. Kurths. How basin stability complements the linear-stability paradigm. Nature Phys, 9 89–92 (2013).
- V. Klinshov, V. Nekorkin, J. Kurths. Stability threshold approach for complex dynamical systems. New Journal Physics, 18 013004 (2016).
- V. Klinshov, S. Kirillov, J. Kurths, V. Nekorkin. Interval stability for complex systems. New Journal Physics, 18 013004 (2018).
How to cite: Loskutov, E., Vdovin, V., Gavrilov, A., Mukhin, D., and Feigin, A.: The Middle Pleistocene Transition: estimation of the interval stability by data-driven model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11277, https://doi.org/10.5194/egusphere-egu2020-11277, 2020.
EGU2020-6633 | Displays | NP5.2
Target observation of mesoscale eddies in the oceanLin Jiang and Wansuo Duan
Previous studies show that the kinetic energy of mesoscale eddies (MEs) accounts for more than 80% of the global ocean energy. The theoretical study and numerical simulation of MEs will enable us to better understand the dynamics of ocean circulation. Weiss and Grooms (2017) found that assimilating uniform observations taken over MEs is much better than assimilating a subset of observations on a regular grid for improving prediction skill of SSH associated with ocean state. In the present study, we use a conditional nonlinear optimal perturbation (CNOP) approach to investigate the sensitivity of the ocean state sea surface height (SSH) predictions on MEs with a two-layer quasi-geostrophic model and show the optimal assimilating scheme. In the study, the CNOPs of SSH predictions are first computed. It is found that, if one regards the regions covered by the grid points with large values of CNOPs as sensitive area of SSH predictions, the sensitive areas are mainly located on MEs. Furthermore, the stronger the MEs, the more the MEs grid points covered by the sensitive area. Especially, these grid points associated with sensitive areas are not uniformly distributed over the MEs. It is obvious that the predictions of SSH are quite sensitive to the initialization of MEs (especially that of the particular region of large values of CNOPs for strong MEs, rather than of the uniformly distributed grid points over MEs). Therefore, an appropriate initialization of MEs is much helpful for improving the prediction accuracy of SSH. And the CNOPs of SSH prediction here may provide useful information on how to improve initialization of MEs.
How to cite: Jiang, L. and Duan, W.: Target observation of mesoscale eddies in the ocean, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6633, https://doi.org/10.5194/egusphere-egu2020-6633, 2020.
Previous studies show that the kinetic energy of mesoscale eddies (MEs) accounts for more than 80% of the global ocean energy. The theoretical study and numerical simulation of MEs will enable us to better understand the dynamics of ocean circulation. Weiss and Grooms (2017) found that assimilating uniform observations taken over MEs is much better than assimilating a subset of observations on a regular grid for improving prediction skill of SSH associated with ocean state. In the present study, we use a conditional nonlinear optimal perturbation (CNOP) approach to investigate the sensitivity of the ocean state sea surface height (SSH) predictions on MEs with a two-layer quasi-geostrophic model and show the optimal assimilating scheme. In the study, the CNOPs of SSH predictions are first computed. It is found that, if one regards the regions covered by the grid points with large values of CNOPs as sensitive area of SSH predictions, the sensitive areas are mainly located on MEs. Furthermore, the stronger the MEs, the more the MEs grid points covered by the sensitive area. Especially, these grid points associated with sensitive areas are not uniformly distributed over the MEs. It is obvious that the predictions of SSH are quite sensitive to the initialization of MEs (especially that of the particular region of large values of CNOPs for strong MEs, rather than of the uniformly distributed grid points over MEs). Therefore, an appropriate initialization of MEs is much helpful for improving the prediction accuracy of SSH. And the CNOPs of SSH prediction here may provide useful information on how to improve initialization of MEs.
How to cite: Jiang, L. and Duan, W.: Target observation of mesoscale eddies in the ocean, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6633, https://doi.org/10.5194/egusphere-egu2020-6633, 2020.
EGU2020-7649 | Displays | NP5.2
Natural time analysis: Estimation of the occurrence time of a major earthquake from the entropy changes of the preceding seismicity.Efthimios S Skordas, Nicholas V. Sarlis, Mary S Lazaridou-Varotsos, and Panayiotis A Varotsos
By analyzing the seismicity in the new time domain termed natural time [1], the entropy changes of seismicity before major earthquakes have been studied. It was found [2-5] that the key quantity is the entropy change ΔS under time reversal, which is minimized a few months before major earthquakes such as the M9.0 Tohoku earthquake [2] on 11 March 2011 and the M8.2 Chiapas earthquake [3] in Mexico on 7 September 2017; accompanied by an abrupt increase of its fluctuations [4,5]. Here we discuss how these fluctuations may lead to a procedure through which the occurrence time of an impending mainshock can be estimated [6].
References
1. Varotsos P.A., Sarlis N.V. and Skordas E.S., Natural Time Analysis: The new view of time. Precursory Seismic Electric Signals, Earthquakes and other Complex Time-Series (Springer-Verlag, Berlin Heidelberg) 2011.
2. N. V. Sarlis, E. S. Skordas, and P. A. Varotsos, "A remarkable change of the entropy of seismicity in natural time under time reversal before the super-giant M9 Tohoku earthquake on 11 March 2011", EPL (Europhysics Letters), 124 (2018), 29001.
3. N. V. Sarlis, E. S. Skordas P. A. Varotsos, A. Ramírez-Rojas, E. L. Flores-Márquez, "Natural time analysis: On the deadly Mexico M8.2 earthquake on 7 September 2017", Physica A 506 (2018), 625-634.
4. P. A. Varotsos, N. V. Sarlis and E. S. Skordas, "Tsallis Entropy Index q and the Complexity Measure of Seismicity in Natural Time under Time Reversal before the M9 Tohoku Earthquake in 2011", Entropy 20 (2018), 757.
5. A. Ramírez-Rojas, E. L. Flores-Márquez, N. V. Sarlis and P. A. Varotsos, "The Complexity Measures Associated with the Fluctuations of the Entropy in Natural Time before the Deadly México M8.2 Earthquake on 7 September 2017", Entropy 20 (2018), 477.
6. E. S. Skordas, N. V. Sarlis and P. A. Varotsos “Identifying the occurrence time of an impending major earthquake by means of the fluctuations of the entropy change under time reversal”, EPL (Europhysics Letters), in press.
How to cite: Skordas, E. S., Sarlis, N. V., Lazaridou-Varotsos, M. S., and Varotsos, P. A.: Natural time analysis: Estimation of the occurrence time of a major earthquake from the entropy changes of the preceding seismicity., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7649, https://doi.org/10.5194/egusphere-egu2020-7649, 2020.
By analyzing the seismicity in the new time domain termed natural time [1], the entropy changes of seismicity before major earthquakes have been studied. It was found [2-5] that the key quantity is the entropy change ΔS under time reversal, which is minimized a few months before major earthquakes such as the M9.0 Tohoku earthquake [2] on 11 March 2011 and the M8.2 Chiapas earthquake [3] in Mexico on 7 September 2017; accompanied by an abrupt increase of its fluctuations [4,5]. Here we discuss how these fluctuations may lead to a procedure through which the occurrence time of an impending mainshock can be estimated [6].
References
1. Varotsos P.A., Sarlis N.V. and Skordas E.S., Natural Time Analysis: The new view of time. Precursory Seismic Electric Signals, Earthquakes and other Complex Time-Series (Springer-Verlag, Berlin Heidelberg) 2011.
2. N. V. Sarlis, E. S. Skordas, and P. A. Varotsos, "A remarkable change of the entropy of seismicity in natural time under time reversal before the super-giant M9 Tohoku earthquake on 11 March 2011", EPL (Europhysics Letters), 124 (2018), 29001.
3. N. V. Sarlis, E. S. Skordas P. A. Varotsos, A. Ramírez-Rojas, E. L. Flores-Márquez, "Natural time analysis: On the deadly Mexico M8.2 earthquake on 7 September 2017", Physica A 506 (2018), 625-634.
4. P. A. Varotsos, N. V. Sarlis and E. S. Skordas, "Tsallis Entropy Index q and the Complexity Measure of Seismicity in Natural Time under Time Reversal before the M9 Tohoku Earthquake in 2011", Entropy 20 (2018), 757.
5. A. Ramírez-Rojas, E. L. Flores-Márquez, N. V. Sarlis and P. A. Varotsos, "The Complexity Measures Associated with the Fluctuations of the Entropy in Natural Time before the Deadly México M8.2 Earthquake on 7 September 2017", Entropy 20 (2018), 477.
6. E. S. Skordas, N. V. Sarlis and P. A. Varotsos “Identifying the occurrence time of an impending major earthquake by means of the fluctuations of the entropy change under time reversal”, EPL (Europhysics Letters), in press.
How to cite: Skordas, E. S., Sarlis, N. V., Lazaridou-Varotsos, M. S., and Varotsos, P. A.: Natural time analysis: Estimation of the occurrence time of a major earthquake from the entropy changes of the preceding seismicity., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7649, https://doi.org/10.5194/egusphere-egu2020-7649, 2020.
EGU2020-8787 | Displays | NP5.2
Bayesian recurrent neural network as a tool for reconstructing dynamical systems from multidimensional dataAlexander Feigin, Aleksei Seleznev, Dmitry Mukhin, Andrey Gavrilov, and Evgeny Loskutov
We suggest a new method for construction of data-driven dynamical models from observed multidimensional time series. The method is based on a recurrent neural network (RNN) with specific structure, which allows for the joint reconstruction of both a low-dimensional embedding for dynamical components in the data and an operator describing the low-dimensional evolution of the system. The key link of the method is a Bayesian optimization of both model structure and the hypothesis about the data generating law, which is needed for constructing the cost function for model learning. The form of the model we propose allows us to construct a stochastic dynamical system of moderate dimension that copies dynamical properties of the original high-dimensional system. An advantage of the proposed method is the data-adaptive properties of the RNN model: it is based on the adjustable nonlinear elements and has easily scalable structure. The combination of the RNN with the Bayesian optimization procedure efficiently provides the model with statistically significant nonlinearity and dimension.
The method developed for the model optimization aims to detect the long-term connections between system’s states – the memory of the system: the cost-function used for model learning is constructed taking into account this factor. In particular, in the case of absence of interaction between the dynamical component and noise, the method provides unbiased reconstruction of the hidden deterministic system. In the opposite case when the noise has strong impact on the dynamics, the method yield a model in the form of a nonlinear stochastic map determining the Markovian process with memory. Bayesian approach used for selecting both the optimal model’s structure and the appropriate cost function allows to obtain the statistically significant inferences about the dynamical signal in data as well as its interaction with the noise components.
Data driven model derived from the relatively short time series of the QG3 model – the high dimensional nonlinear system producing chaotic behavior – is shown be able to serve as a good simulator for the QG3 LFV components. The statistically significant recurrent states of the QG3 model, i.e. the well-known teleconnections in NH, are all reproduced by the model obtained. Moreover, statistics of the residence times of the model near these states is very close to the corresponding statistics of the original QG3 model. These results demonstrate that the method can be useful in modeling the variability of the real atmosphere.
The work was supported by the Russian Science Foundation (Grant No. 19-42-04121).
How to cite: Feigin, A., Seleznev, A., Mukhin, D., Gavrilov, A., and Loskutov, E.: Bayesian recurrent neural network as a tool for reconstructing dynamical systems from multidimensional data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8787, https://doi.org/10.5194/egusphere-egu2020-8787, 2020.
We suggest a new method for construction of data-driven dynamical models from observed multidimensional time series. The method is based on a recurrent neural network (RNN) with specific structure, which allows for the joint reconstruction of both a low-dimensional embedding for dynamical components in the data and an operator describing the low-dimensional evolution of the system. The key link of the method is a Bayesian optimization of both model structure and the hypothesis about the data generating law, which is needed for constructing the cost function for model learning. The form of the model we propose allows us to construct a stochastic dynamical system of moderate dimension that copies dynamical properties of the original high-dimensional system. An advantage of the proposed method is the data-adaptive properties of the RNN model: it is based on the adjustable nonlinear elements and has easily scalable structure. The combination of the RNN with the Bayesian optimization procedure efficiently provides the model with statistically significant nonlinearity and dimension.
The method developed for the model optimization aims to detect the long-term connections between system’s states – the memory of the system: the cost-function used for model learning is constructed taking into account this factor. In particular, in the case of absence of interaction between the dynamical component and noise, the method provides unbiased reconstruction of the hidden deterministic system. In the opposite case when the noise has strong impact on the dynamics, the method yield a model in the form of a nonlinear stochastic map determining the Markovian process with memory. Bayesian approach used for selecting both the optimal model’s structure and the appropriate cost function allows to obtain the statistically significant inferences about the dynamical signal in data as well as its interaction with the noise components.
Data driven model derived from the relatively short time series of the QG3 model – the high dimensional nonlinear system producing chaotic behavior – is shown be able to serve as a good simulator for the QG3 LFV components. The statistically significant recurrent states of the QG3 model, i.e. the well-known teleconnections in NH, are all reproduced by the model obtained. Moreover, statistics of the residence times of the model near these states is very close to the corresponding statistics of the original QG3 model. These results demonstrate that the method can be useful in modeling the variability of the real atmosphere.
The work was supported by the Russian Science Foundation (Grant No. 19-42-04121).
How to cite: Feigin, A., Seleznev, A., Mukhin, D., Gavrilov, A., and Loskutov, E.: Bayesian recurrent neural network as a tool for reconstructing dynamical systems from multidimensional data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8787, https://doi.org/10.5194/egusphere-egu2020-8787, 2020.
EGU2020-11974 | Displays | NP5.2 | Highlight
Evaluation of the impact of typhoon initialization on numerical weather forecasts.Jeong Ock Lim, Kyung-On Boo, HaeJin Kong, Sanghee Jun, Jeong-Hyun Park, and Hyun-Suk Kang
A typhoon is a high-impact weather phenomenon that causes serious damage to people and property when landing on the Korean peninsula. Therefore, accurate prediction of typhoon intensity and track is very important in establishing damage prevention measures.
KMA has applied its own typhoon initialization process (KMA bogusing) for Global Data Assimilation and Prediction System (GDPS) to produce realistic initial fields since 2010, when the Unified Model (UM) of UK Met Office (UKMO) was introduced as an operational model. If the typhoon intensity of the background is weaker than the observation, the KMA bogussing process generates horizontally spread mean sea level pressures by using TC warning center’s advisory and use it for data assimilation.
In June 2018, GDPS has been upgraded based on PS40 N1280 of UKMO with significantly increased its horizontal resolution from 17 km to 10 km. The new version of GDPS showed improved performance in TC intensity predictions. Since the model simulates tropical cyclone intensity strong enough, we investigated the impact of typhoon initialization on the predictability of the new version GDPS.
How to cite: Lim, J. O., Boo, K.-O., Kong, H., Jun, S., Park, J.-H., and Kang, H.-S.: Evaluation of the impact of typhoon initialization on numerical weather forecasts., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11974, https://doi.org/10.5194/egusphere-egu2020-11974, 2020.
A typhoon is a high-impact weather phenomenon that causes serious damage to people and property when landing on the Korean peninsula. Therefore, accurate prediction of typhoon intensity and track is very important in establishing damage prevention measures.
KMA has applied its own typhoon initialization process (KMA bogusing) for Global Data Assimilation and Prediction System (GDPS) to produce realistic initial fields since 2010, when the Unified Model (UM) of UK Met Office (UKMO) was introduced as an operational model. If the typhoon intensity of the background is weaker than the observation, the KMA bogussing process generates horizontally spread mean sea level pressures by using TC warning center’s advisory and use it for data assimilation.
In June 2018, GDPS has been upgraded based on PS40 N1280 of UKMO with significantly increased its horizontal resolution from 17 km to 10 km. The new version of GDPS showed improved performance in TC intensity predictions. Since the model simulates tropical cyclone intensity strong enough, we investigated the impact of typhoon initialization on the predictability of the new version GDPS.
How to cite: Lim, J. O., Boo, K.-O., Kong, H., Jun, S., Park, J.-H., and Kang, H.-S.: Evaluation of the impact of typhoon initialization on numerical weather forecasts., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11974, https://doi.org/10.5194/egusphere-egu2020-11974, 2020.
EGU2020-12376 | Displays | NP5.2
Targeted observations based on identified sensitive areas by CNOP to improve the thermal structures prediction in the summer Yellow Sea: preparatory work for the campaign in the fieldJingyi Liu, Wuhong Guo, Baolong Cui, Kun Liu, and Huiqin Hu
Targeted observation is an appealing procedure to improve oceanic model predictions by taking additional assimilation of collected measurements. However, studies on targeted observation in the oceanic field have been largely based on modeling efforts, and there is a need for field validating observations. Here, we report the preparatory work of a field campaign, which is designed based on the identified sensitive area by the Conditional Nonlinear Optimal Perturbation (CNOP) approach, to improve the short-range summer thermal structures prediction in the Yellow Sea (YS). We firstly simulated the hindcasting (2016-2018) temperature structures in the summertime, and found that the locations of the sensitive areas are generally consistent in space for each hindcast year. Then, we introduced the technique of multiple-assimilation and the definition of time-varying sensitive area, and designed observing strategies for the YS summer campaign. Observing System Simulation Experiments (OSSEs) were conducted prior to address the plan on field campaign in the Yellow Sea in August 2019. Results show that, reducing the initial errors in the sensitive area can lead to more improvement on thermal structures prediction than that in other area.
How to cite: Liu, J., Guo, W., Cui, B., Liu, K., and Hu, H.: Targeted observations based on identified sensitive areas by CNOP to improve the thermal structures prediction in the summer Yellow Sea: preparatory work for the campaign in the field, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12376, https://doi.org/10.5194/egusphere-egu2020-12376, 2020.
Targeted observation is an appealing procedure to improve oceanic model predictions by taking additional assimilation of collected measurements. However, studies on targeted observation in the oceanic field have been largely based on modeling efforts, and there is a need for field validating observations. Here, we report the preparatory work of a field campaign, which is designed based on the identified sensitive area by the Conditional Nonlinear Optimal Perturbation (CNOP) approach, to improve the short-range summer thermal structures prediction in the Yellow Sea (YS). We firstly simulated the hindcasting (2016-2018) temperature structures in the summertime, and found that the locations of the sensitive areas are generally consistent in space for each hindcast year. Then, we introduced the technique of multiple-assimilation and the definition of time-varying sensitive area, and designed observing strategies for the YS summer campaign. Observing System Simulation Experiments (OSSEs) were conducted prior to address the plan on field campaign in the Yellow Sea in August 2019. Results show that, reducing the initial errors in the sensitive area can lead to more improvement on thermal structures prediction than that in other area.
How to cite: Liu, J., Guo, W., Cui, B., Liu, K., and Hu, H.: Targeted observations based on identified sensitive areas by CNOP to improve the thermal structures prediction in the summer Yellow Sea: preparatory work for the campaign in the field, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12376, https://doi.org/10.5194/egusphere-egu2020-12376, 2020.
EGU2020-16961 | Displays | NP5.2
Applying causal discovery algorithm to find predictors for transformation process of wood combustion emissionVille Leinonen, Petri Tiitta, Olli Sippula, Hendryk Czech, Ari Leskinen, Juha Karvanen, Sini Isokääntä, and Santtu Mikkonen
Aerosols and their transformation process in atmosphere have significant effects on climate. Transformation process is a complex combination of physical and chemical reactions. Multiple oxidizing agents and other factors, such as radiation, affect the transformation process. Characterization of these factors and their strength is a problem, where advanced methods might help to gain more understanding.
In this work, we modeled transformation of wood combustion emission measured in the environmental chamber by using causal modeling (Pearl, 2009). The aim of the study was to use state-of-the-art causal discovery methods to search causal pathways between measured variables: precursors and particle products. The data used in the modelling are introduced in Tiitta et al. (2016).
In addition to wood combustion experiments, we simulated artificial datasets to understand abilities of the model. We wanted to evaluate the accuracy of our model to confirm the correct structure between variables and reproduce the measured transformation. This helps us to understand the model performance in real datasets.
We found that model could reproduce the measured evolution well. The structure between emission parts was not completely matching to prior assumption. Usually incorrect predictors in the modeled structure are highly correlated with correct causes.
References:
Pearl, J.: Causality : Models, Reasoning and Inference., Cambridge University Press., 2009.
Tiitta et al., Atmos. Chem. Phys., 16, 13251-13269, 2016.
How to cite: Leinonen, V., Tiitta, P., Sippula, O., Czech, H., Leskinen, A., Karvanen, J., Isokääntä, S., and Mikkonen, S.: Applying causal discovery algorithm to find predictors for transformation process of wood combustion emission, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16961, https://doi.org/10.5194/egusphere-egu2020-16961, 2020.
Aerosols and their transformation process in atmosphere have significant effects on climate. Transformation process is a complex combination of physical and chemical reactions. Multiple oxidizing agents and other factors, such as radiation, affect the transformation process. Characterization of these factors and their strength is a problem, where advanced methods might help to gain more understanding.
In this work, we modeled transformation of wood combustion emission measured in the environmental chamber by using causal modeling (Pearl, 2009). The aim of the study was to use state-of-the-art causal discovery methods to search causal pathways between measured variables: precursors and particle products. The data used in the modelling are introduced in Tiitta et al. (2016).
In addition to wood combustion experiments, we simulated artificial datasets to understand abilities of the model. We wanted to evaluate the accuracy of our model to confirm the correct structure between variables and reproduce the measured transformation. This helps us to understand the model performance in real datasets.
We found that model could reproduce the measured evolution well. The structure between emission parts was not completely matching to prior assumption. Usually incorrect predictors in the modeled structure are highly correlated with correct causes.
References:
Pearl, J.: Causality : Models, Reasoning and Inference., Cambridge University Press., 2009.
Tiitta et al., Atmos. Chem. Phys., 16, 13251-13269, 2016.
How to cite: Leinonen, V., Tiitta, P., Sippula, O., Czech, H., Leskinen, A., Karvanen, J., Isokääntä, S., and Mikkonen, S.: Applying causal discovery algorithm to find predictors for transformation process of wood combustion emission, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16961, https://doi.org/10.5194/egusphere-egu2020-16961, 2020.
EGU2020-20928 | Displays | NP5.2
The Transfer and Evolvement of Initial Temperature Perturbation in Ocean-Acoustic Coupled ProcessWuhong Guo, Baolong Cui, and Jingyi Liu
Focusing on the transfer and evolvement of initial perturbation from temperature of ocean to the underwater acoustic propagation,comparing with the remote sensing data,optimizing Ocean-Acoustic Coupled Model, the reliability of this model is verified. On this basis,global and regional error development experiments are carried out by adding perturbation on the initial temperature of a controlled test. The results show that after 5 days evolution of the initial temperature field,the global perturbation of the propagation loss is saturated, and the perturbation structure is basically consistent with the law of the dynamic ocean.For the target area in Kuroshio region, the initial perturbation in the upstream region is the fastest. This conclusion can provide the basis for the adaptive observation of ocean acoustics.
How to cite: Guo, W., Cui, B., and Liu, J.: The Transfer and Evolvement of Initial Temperature Perturbation in Ocean-Acoustic Coupled Process, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20928, https://doi.org/10.5194/egusphere-egu2020-20928, 2020.
Focusing on the transfer and evolvement of initial perturbation from temperature of ocean to the underwater acoustic propagation,comparing with the remote sensing data,optimizing Ocean-Acoustic Coupled Model, the reliability of this model is verified. On this basis,global and regional error development experiments are carried out by adding perturbation on the initial temperature of a controlled test. The results show that after 5 days evolution of the initial temperature field,the global perturbation of the propagation loss is saturated, and the perturbation structure is basically consistent with the law of the dynamic ocean.For the target area in Kuroshio region, the initial perturbation in the upstream region is the fastest. This conclusion can provide the basis for the adaptive observation of ocean acoustics.
How to cite: Guo, W., Cui, B., and Liu, J.: The Transfer and Evolvement of Initial Temperature Perturbation in Ocean-Acoustic Coupled Process, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20928, https://doi.org/10.5194/egusphere-egu2020-20928, 2020.
EGU2020-21445 | Displays | NP5.2
The Rapid Uncertainty Prediction of the Ocean-Acoustic Coupled ModelBaolong Cui and Wuhong Guo
Focusing on the rapid prediction of acoustic field uncertainty in environment with temporal and spatial sound speed perturbation, evolvement of sound speed structure over time is predicted based on the ocean-acoustic coupled model to obtain the uncertainty distribution of the vertical structure of sound speed. Further, a method combining the arbitrary polynomial chaos expansion with the empirical orthogonal function is proposed to reduce the dimensionality of uncertain parameters and to obtain the uncertainty distribution of the acoustic field. Simulations have shown that the computational complexity can be reduced by 2 orders of magnitude compared to the conventional polynomial chaos expansion while ensures the same precision. Moreover, the computational complexity is not influenced by the complexity of the sound speed profile. The acoustic field and uncertainty predicted in uncertain environment by proposed method also have been tested with the experimental data.
How to cite: Cui, B. and Guo, W.: The Rapid Uncertainty Prediction of the Ocean-Acoustic Coupled Model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21445, https://doi.org/10.5194/egusphere-egu2020-21445, 2020.
Focusing on the rapid prediction of acoustic field uncertainty in environment with temporal and spatial sound speed perturbation, evolvement of sound speed structure over time is predicted based on the ocean-acoustic coupled model to obtain the uncertainty distribution of the vertical structure of sound speed. Further, a method combining the arbitrary polynomial chaos expansion with the empirical orthogonal function is proposed to reduce the dimensionality of uncertain parameters and to obtain the uncertainty distribution of the acoustic field. Simulations have shown that the computational complexity can be reduced by 2 orders of magnitude compared to the conventional polynomial chaos expansion while ensures the same precision. Moreover, the computational complexity is not influenced by the complexity of the sound speed profile. The acoustic field and uncertainty predicted in uncertain environment by proposed method also have been tested with the experimental data.
How to cite: Cui, B. and Guo, W.: The Rapid Uncertainty Prediction of the Ocean-Acoustic Coupled Model, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21445, https://doi.org/10.5194/egusphere-egu2020-21445, 2020.
NP5.4 – Advances in statistical post-processing, blending and verification of deterministic and ensemble forecasts
EGU2020-2588 | Displays | NP5.4
Remember the past: A comparison of time-adaptive training schemes for non-homogeneous regressionMoritz N. Lang, Sebastian Lerch, Georg J. Mayr, Thorsten Simon, Reto Stauffer, and Achim Zeileis
Non-homogeneous regression is a frequently-used post-processing method for increasing the predictive skill of probabilistic ensemble weather forecasts. To adjust for seasonally varying error characteristics between ensemble forecasts and corresponding observations, different time-adaptive training schemes, including the classical sliding training window, have been developed for non-homogeneous regression. This study compares three such training approaches with the sliding-window approach for the application of post-processing near-surface air temperature forecasts across Central Europe. The predictive performance is evaluated conditional on three different groups of stations located in plains, in mountain foreland, and within mountainous terrain, as well as on a specific change in the ensemble forecast system of the European Centre for Medium-Range Weather Forecasts (ECMWF) used as input for the post-processing.
The results show that time-adaptive training schemes using data over multiple years stabilize the temporal evolution of the coefficient estimates, yielding an increased predictive performance for all station types tested compared to the classical sliding-window approach based on the most recent days only. While this may not be surprising under fully stable model conditions, it is shown that "remembering the past" from multiple years of training data is typically also superior to the classical sliding-window when the ensemble prediction system is affected by certain model changes. Thus, reducing the variance of the non-homogeneous regression estimates due to increased training data appears to be more important than reducing its bias by adapting rapidly to the most current training data only.
How to cite: Lang, M. N., Lerch, S., Mayr, G. J., Simon, T., Stauffer, R., and Zeileis, A.: Remember the past: A comparison of time-adaptive training schemes for non-homogeneous regression, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2588, https://doi.org/10.5194/egusphere-egu2020-2588, 2020.
Non-homogeneous regression is a frequently-used post-processing method for increasing the predictive skill of probabilistic ensemble weather forecasts. To adjust for seasonally varying error characteristics between ensemble forecasts and corresponding observations, different time-adaptive training schemes, including the classical sliding training window, have been developed for non-homogeneous regression. This study compares three such training approaches with the sliding-window approach for the application of post-processing near-surface air temperature forecasts across Central Europe. The predictive performance is evaluated conditional on three different groups of stations located in plains, in mountain foreland, and within mountainous terrain, as well as on a specific change in the ensemble forecast system of the European Centre for Medium-Range Weather Forecasts (ECMWF) used as input for the post-processing.
The results show that time-adaptive training schemes using data over multiple years stabilize the temporal evolution of the coefficient estimates, yielding an increased predictive performance for all station types tested compared to the classical sliding-window approach based on the most recent days only. While this may not be surprising under fully stable model conditions, it is shown that "remembering the past" from multiple years of training data is typically also superior to the classical sliding-window when the ensemble prediction system is affected by certain model changes. Thus, reducing the variance of the non-homogeneous regression estimates due to increased training data appears to be more important than reducing its bias by adapting rapidly to the most current training data only.
How to cite: Lang, M. N., Lerch, S., Mayr, G. J., Simon, T., Stauffer, R., and Zeileis, A.: Remember the past: A comparison of time-adaptive training schemes for non-homogeneous regression, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2588, https://doi.org/10.5194/egusphere-egu2020-2588, 2020.
EGU2020-17465 | Displays | NP5.4
Impact of the statistical method, training dataset, and spatial scale of post-processing to adjust ensemble forecasts of the height of new snowNousu Jari-Pekka, Matthieu Lafaysse, Guillaume Evin, Matthieu Vernay, Joseph Bellier, Bruno Joly, Maxime Taillardat, and Michaël Zamo
Forecasting the height of new snow (HS) is essential for avalanche hazard survey, road and ski resorts management, tourism attractiveness, etc. Meteo-France operates the PEARP-S2M probabilistic forecasting system including 35 members of the PEARP Numerical Weather Prediction system, the SAFRAN downscaling tool refining the elevation resolution in mountains, and the Crocus snowpack model representing the main physical processes in the snowpack (compaction, melting, etc.). It provides better HS forecasts than direct NWP diagnostics but exhibits significant biases and underdispersion. Therefore, a post-processing is required to be able to provide automatic forecasting products of HS from this system.
For that purpose, we compare the skill of two statistical methods (Nonhomogeneous Regression with a Censored Shifted Gamma distribution and Quantile Regression Forest), two predictor datasets for training (22-year reforecast with some discrepancies with the operational system or 3-year real time forecasts similar to the operational system) and two spatial scales of post-processing (local scale or 1000 km² regional scale).
The improvement relative to the raw forecasts is similar at both spatial scales. Thus, the regional validity of post-processing does not restrict the application at points with observations. The impact of the training dataset depends on lead time and on the evaluation criteria. The long-term reforecast improves the reliability of severe snowfall but leads to overdispersion due to a discrepancy with the initial perturbations used in the operational system. Finally, thanks to a larger number of predictors, the Quantile Regression Forest allows an improvement of forecasts for specific cases when the the rain-snow transition elevation is overestimated by the raw forecasts.
These conclusions help to choose an optimal post-processing configuration for automatic forecasts of the height of new snow and encourage the atmospheric modelling teams to develop long reforecasts as homogenous as possible with the operational systems.
How to cite: Jari-Pekka, N., Lafaysse, M., Evin, G., Vernay, M., Bellier, J., Joly, B., Taillardat, M., and Zamo, M.: Impact of the statistical method, training dataset, and spatial scale of post-processing to adjust ensemble forecasts of the height of new snow, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17465, https://doi.org/10.5194/egusphere-egu2020-17465, 2020.
Forecasting the height of new snow (HS) is essential for avalanche hazard survey, road and ski resorts management, tourism attractiveness, etc. Meteo-France operates the PEARP-S2M probabilistic forecasting system including 35 members of the PEARP Numerical Weather Prediction system, the SAFRAN downscaling tool refining the elevation resolution in mountains, and the Crocus snowpack model representing the main physical processes in the snowpack (compaction, melting, etc.). It provides better HS forecasts than direct NWP diagnostics but exhibits significant biases and underdispersion. Therefore, a post-processing is required to be able to provide automatic forecasting products of HS from this system.
For that purpose, we compare the skill of two statistical methods (Nonhomogeneous Regression with a Censored Shifted Gamma distribution and Quantile Regression Forest), two predictor datasets for training (22-year reforecast with some discrepancies with the operational system or 3-year real time forecasts similar to the operational system) and two spatial scales of post-processing (local scale or 1000 km² regional scale).
The improvement relative to the raw forecasts is similar at both spatial scales. Thus, the regional validity of post-processing does not restrict the application at points with observations. The impact of the training dataset depends on lead time and on the evaluation criteria. The long-term reforecast improves the reliability of severe snowfall but leads to overdispersion due to a discrepancy with the initial perturbations used in the operational system. Finally, thanks to a larger number of predictors, the Quantile Regression Forest allows an improvement of forecasts for specific cases when the the rain-snow transition elevation is overestimated by the raw forecasts.
These conclusions help to choose an optimal post-processing configuration for automatic forecasts of the height of new snow and encourage the atmospheric modelling teams to develop long reforecasts as homogenous as possible with the operational systems.
How to cite: Jari-Pekka, N., Lafaysse, M., Evin, G., Vernay, M., Bellier, J., Joly, B., Taillardat, M., and Zamo, M.: Impact of the statistical method, training dataset, and spatial scale of post-processing to adjust ensemble forecasts of the height of new snow, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17465, https://doi.org/10.5194/egusphere-egu2020-17465, 2020.
EGU2020-9698 | Displays | NP5.4
Vertical profiles of wind gust statistics from a regional reanalysis using multivariate extreme value theoryJulian Steinheuer and Petra Friederichs
How to cite: Steinheuer, J. and Friederichs, P.: Vertical profiles of wind gust statistics from a regional reanalysis using multivariate extreme value theory, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9698, https://doi.org/10.5194/egusphere-egu2020-9698, 2020.
How to cite: Steinheuer, J. and Friederichs, P.: Vertical profiles of wind gust statistics from a regional reanalysis using multivariate extreme value theory, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9698, https://doi.org/10.5194/egusphere-egu2020-9698, 2020.
EGU2020-11422 | Displays | NP5.4
Using neural networks for postprocessing of numerical weather predictions in complex terrainJonas Bhend, Christoph Spirig, Max Hürlimann, Lionel Moret, and Mark Liniger
Weather forecasts have been steadily improving in quality over the last decades. These ongoing improvements are due to advances in numerical weather prediction (NWP) and the advent of ever more powerful supercomputers that allow simulating future weather and its uncertainty with increasing resolution and using ensemble approaches. Such physics-based computer models, however, are not free of systematic errors. Statistical postprocessing can be used to calibrate NWP forecasts to further improve forecast quality and better exploit the available information. Here we present results from several explorative deep learning studies using artificial neural networks (ANN) to calibrate high resolution forecasts of temperature, precipitation, wind, and cloud cover in Switzerland. These first attempts at ANN-based postprocessing help us to understand the strengths and weaknesses of machine learning and are the basis to build more complex and comprehensive statistical models accounting for local effects in complex terrain such as the Swiss Alps. In all cases, ANN leads to significant improvements over the direct NWP output. While the improvement is comparable in magnitude with improvements achieved with conventional postprocessing approaches, ANN-based postprocessing is easier to generalize in space for a calibration of forecasts also at unobserved sites. In addition to the results of the postprocessing, we will also discuss the lessons learned so far in using machine learning for this particular problem.
How to cite: Bhend, J., Spirig, C., Hürlimann, M., Moret, L., and Liniger, M.: Using neural networks for postprocessing of numerical weather predictions in complex terrain, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11422, https://doi.org/10.5194/egusphere-egu2020-11422, 2020.
Weather forecasts have been steadily improving in quality over the last decades. These ongoing improvements are due to advances in numerical weather prediction (NWP) and the advent of ever more powerful supercomputers that allow simulating future weather and its uncertainty with increasing resolution and using ensemble approaches. Such physics-based computer models, however, are not free of systematic errors. Statistical postprocessing can be used to calibrate NWP forecasts to further improve forecast quality and better exploit the available information. Here we present results from several explorative deep learning studies using artificial neural networks (ANN) to calibrate high resolution forecasts of temperature, precipitation, wind, and cloud cover in Switzerland. These first attempts at ANN-based postprocessing help us to understand the strengths and weaknesses of machine learning and are the basis to build more complex and comprehensive statistical models accounting for local effects in complex terrain such as the Swiss Alps. In all cases, ANN leads to significant improvements over the direct NWP output. While the improvement is comparable in magnitude with improvements achieved with conventional postprocessing approaches, ANN-based postprocessing is easier to generalize in space for a calibration of forecasts also at unobserved sites. In addition to the results of the postprocessing, we will also discuss the lessons learned so far in using machine learning for this particular problem.
How to cite: Bhend, J., Spirig, C., Hürlimann, M., Moret, L., and Liniger, M.: Using neural networks for postprocessing of numerical weather predictions in complex terrain, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11422, https://doi.org/10.5194/egusphere-egu2020-11422, 2020.
EGU2020-16849 | Displays | NP5.4
Statistical post-processing of wind speed forecasts using convolutional neural networksMaurice Schmeits, Simon Veldkamp, and Kirien Whan
Current statistical post-processing methods for providing a probabilistic forecast are not capable of using full spatial patterns from the numerical weather prediction (NWP) model output. Recent developments in deep learning (notably convolutional neural networks) have made it possible to use large gridded input data sets. This could potentially be useful in statistical post-processing, since it allows us to use more spatial information.
In this study we consider wind speed forecasts for 48 hours ahead, as provided by KNMI's Harmonie-Arome model. Convolutional neural networks, fully connected neural networks and quantile regression forests are used to obtain probabilistic wind speed forecasts. Comparing these methods shows that convolutional neural networks are more skillful than the other methods, especially for medium to higher wind speeds.
How to cite: Schmeits, M., Veldkamp, S., and Whan, K.: Statistical post-processing of wind speed forecasts using convolutional neural networks, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16849, https://doi.org/10.5194/egusphere-egu2020-16849, 2020.
Current statistical post-processing methods for providing a probabilistic forecast are not capable of using full spatial patterns from the numerical weather prediction (NWP) model output. Recent developments in deep learning (notably convolutional neural networks) have made it possible to use large gridded input data sets. This could potentially be useful in statistical post-processing, since it allows us to use more spatial information.
In this study we consider wind speed forecasts for 48 hours ahead, as provided by KNMI's Harmonie-Arome model. Convolutional neural networks, fully connected neural networks and quantile regression forests are used to obtain probabilistic wind speed forecasts. Comparing these methods shows that convolutional neural networks are more skillful than the other methods, especially for medium to higher wind speeds.
How to cite: Schmeits, M., Veldkamp, S., and Whan, K.: Statistical post-processing of wind speed forecasts using convolutional neural networks, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-16849, https://doi.org/10.5194/egusphere-egu2020-16849, 2020.
EGU2020-18325 | Displays | NP5.4
ARPEGE cloud cover forecast post-processing with convolutional neural networkFlorian Dupuy, Olivier Mestre, and Léo Pfitzner
Cloud cover is a crucial information for many applications such as planning land observation missions from space. However, cloud cover remains a challenging variable to forecast, and Numerical Weather Prediction (NWP) models suffer from significant biases, hence justifying the use of statistical post-processing techniques. In our application, the ground truth is a gridded cloud cover product derived from satellite observations over Europe, and predictors are spatial fields of various variables produced by ARPEGE (Météo-France global NWP) at the corresponding lead time.
In this study, ARPEGE cloud cover is post-processed using a convolutional neural network (CNN). CNN is the most popular machine learning tool to deal with images. In our case, CNN allows to integrate spatial information contained in NWP outputs. We show that a simple U-Net architecture produces significant improvements over Europe. Compared to the raw ARPEGE forecasts, MAE drops from 25.1 % to 17.8 % and RMSE decreases from 37.0 % to 31.6 %. Considering specific needs for earth observation, special interest was put on forecasts with low cloud cover conditions (< 10 %). For this particular nebulosity class, we show that hit rate jumps from 40.6 to 70.7 (which is the order of magnitude of what can be achieved using classical machine learning algorithms such as random forests) while false alarm decreases from 38.2 to 29.9. This is an excellent result, since improving hit rates by means of random forests usually also results in a slight increase of false alarms.
How to cite: Dupuy, F., Mestre, O., and Pfitzner, L.: ARPEGE cloud cover forecast post-processing with convolutional neural network, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18325, https://doi.org/10.5194/egusphere-egu2020-18325, 2020.
Cloud cover is a crucial information for many applications such as planning land observation missions from space. However, cloud cover remains a challenging variable to forecast, and Numerical Weather Prediction (NWP) models suffer from significant biases, hence justifying the use of statistical post-processing techniques. In our application, the ground truth is a gridded cloud cover product derived from satellite observations over Europe, and predictors are spatial fields of various variables produced by ARPEGE (Météo-France global NWP) at the corresponding lead time.
In this study, ARPEGE cloud cover is post-processed using a convolutional neural network (CNN). CNN is the most popular machine learning tool to deal with images. In our case, CNN allows to integrate spatial information contained in NWP outputs. We show that a simple U-Net architecture produces significant improvements over Europe. Compared to the raw ARPEGE forecasts, MAE drops from 25.1 % to 17.8 % and RMSE decreases from 37.0 % to 31.6 %. Considering specific needs for earth observation, special interest was put on forecasts with low cloud cover conditions (< 10 %). For this particular nebulosity class, we show that hit rate jumps from 40.6 to 70.7 (which is the order of magnitude of what can be achieved using classical machine learning algorithms such as random forests) while false alarm decreases from 38.2 to 29.9. This is an excellent result, since improving hit rates by means of random forests usually also results in a slight increase of false alarms.
How to cite: Dupuy, F., Mestre, O., and Pfitzner, L.: ARPEGE cloud cover forecast post-processing with convolutional neural network, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18325, https://doi.org/10.5194/egusphere-egu2020-18325, 2020.
EGU2020-11478 | Displays | NP5.4
Regime-dependent statistical post-processing of wind speed forecastsSam Allen, Chris Ferro, and Frank Kwasniok
Raw output from deterministic numerical weather prediction models is typically subject to systematic biases. Although ensemble forecasts provide invaluable information regarding the uncertainty in a prediction, they themselves often misrepresent the weather that occurs. Given their widespread use, the need for high-quality wind speed forecasts is well-documented. Several statistical approaches have therefore been proposed to recalibrate ensembles of wind speed forecasts, including a heteroscedastic censored regression approach. An extension to this method that utilises the prevailing atmospheric flow is implemented here in a quasigeostrophic simulation study and on reforecast data. It is hoped that this regime-dependent framework can alleviate errors owing to changes in the synoptic-scale atmospheric state. When the wind speed strongly depends on the underlying weather regime, the resulting forecasts have the potential to provide substantial improvements in skill upon conventional post-processing techniques. This is particularly pertinent at longer lead times, where there is more improvement to be gained upon current methods, and in weather regimes associated with wind speeds that differ greatly from climatology. In order to realise this potential, however, an accurate prediction of the future atmospheric regime is required.
How to cite: Allen, S., Ferro, C., and Kwasniok, F.: Regime-dependent statistical post-processing of wind speed forecasts, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11478, https://doi.org/10.5194/egusphere-egu2020-11478, 2020.
Raw output from deterministic numerical weather prediction models is typically subject to systematic biases. Although ensemble forecasts provide invaluable information regarding the uncertainty in a prediction, they themselves often misrepresent the weather that occurs. Given their widespread use, the need for high-quality wind speed forecasts is well-documented. Several statistical approaches have therefore been proposed to recalibrate ensembles of wind speed forecasts, including a heteroscedastic censored regression approach. An extension to this method that utilises the prevailing atmospheric flow is implemented here in a quasigeostrophic simulation study and on reforecast data. It is hoped that this regime-dependent framework can alleviate errors owing to changes in the synoptic-scale atmospheric state. When the wind speed strongly depends on the underlying weather regime, the resulting forecasts have the potential to provide substantial improvements in skill upon conventional post-processing techniques. This is particularly pertinent at longer lead times, where there is more improvement to be gained upon current methods, and in weather regimes associated with wind speeds that differ greatly from climatology. In order to realise this potential, however, an accurate prediction of the future atmospheric regime is required.
How to cite: Allen, S., Ferro, C., and Kwasniok, F.: Regime-dependent statistical post-processing of wind speed forecasts, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11478, https://doi.org/10.5194/egusphere-egu2020-11478, 2020.
EGU2020-315 | Displays | NP5.4
The Sailor-diagram. An extension of the Taylor diagram to two-dimensional variables for verification of model data.Jon Saenz, Sheila Carreno-Madinabeitia, Ganix Esnaola, Santos J. González-Rojí, Gabriel Ibarra-Berastegi, and Alain Ulazia
A new diagram is proposed for the verification of vector quantities generated by individual or multiple models against a set of observations. It has been designed with the idea of extending the Taylor diagram to two-dimensional vector such as currents, wind velocity, or horizontal fluxes of water vapour, salinity, energy and other geophysical variables. The diagram is based on a principal component analysis of the two-dimensional structure of the mean squared error matrix between model and observations. This matrix is separated in two parts corresponding to the bias and the relative rotation of the empirical orthogonal functions of the data. We test the performance of this new diagram identifying the differences amongst a reference dataset and different model outputs using examples wind velocities, current, vertically integrated moisture transport and wave energy flux time series. An alternative setup is also proposed with an application to the time-averaged spatial field of surface wind velocity in the Northern and Southern Hemispheres according to different reanalyses and realizations of an ensemble of CMIP5 models. The examples of the use of the Sailor diagram show that it is a tool which helps identifying errors due to the bias or the orientation of the simulated vector time series or fields. An implementation of the algorithm in form of an R package (sailoR) is already publicly available from the CRAN repository, and besides the ability to plot the individual components of the error matrix, functions in the package also allow to easily retrieve the individual components of the mean squared error.
How to cite: Saenz, J., Carreno-Madinabeitia, S., Esnaola, G., González-Rojí, S. J., Ibarra-Berastegi, G., and Ulazia, A.: The Sailor-diagram. An extension of the Taylor diagram to two-dimensional variables for verification of model data., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-315, https://doi.org/10.5194/egusphere-egu2020-315, 2020.
A new diagram is proposed for the verification of vector quantities generated by individual or multiple models against a set of observations. It has been designed with the idea of extending the Taylor diagram to two-dimensional vector such as currents, wind velocity, or horizontal fluxes of water vapour, salinity, energy and other geophysical variables. The diagram is based on a principal component analysis of the two-dimensional structure of the mean squared error matrix between model and observations. This matrix is separated in two parts corresponding to the bias and the relative rotation of the empirical orthogonal functions of the data. We test the performance of this new diagram identifying the differences amongst a reference dataset and different model outputs using examples wind velocities, current, vertically integrated moisture transport and wave energy flux time series. An alternative setup is also proposed with an application to the time-averaged spatial field of surface wind velocity in the Northern and Southern Hemispheres according to different reanalyses and realizations of an ensemble of CMIP5 models. The examples of the use of the Sailor diagram show that it is a tool which helps identifying errors due to the bias or the orientation of the simulated vector time series or fields. An implementation of the algorithm in form of an R package (sailoR) is already publicly available from the CRAN repository, and besides the ability to plot the individual components of the error matrix, functions in the package also allow to easily retrieve the individual components of the mean squared error.
How to cite: Saenz, J., Carreno-Madinabeitia, S., Esnaola, G., González-Rojí, S. J., Ibarra-Berastegi, G., and Ulazia, A.: The Sailor-diagram. An extension of the Taylor diagram to two-dimensional variables for verification of model data., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-315, https://doi.org/10.5194/egusphere-egu2020-315, 2020.
EGU2020-927 | Displays | NP5.4
Fidelity of CORDEX Evaluation runs under Non-stationary climateSwati Singh, Kaustubh Salvi, Subimal Ghosh, and Subhankar Karmakar
The downscaling approaches: Statistical and Dynamic, developed for regional climate predictions, have both advantages and limitations. The statistical downscaling is computationally inexpensive but suffers from the violation of the assumption of stationarity in statistical (predictor-predictand) relationship. The dynamical downscaling is assumed to take care of stationarity but suffers from the biases associated with various sources. Here we propose a joint approach of both the methods by applying statistical methods: bias correction & statistical downscaling to Coordinated Regional Climate Downscaling Experiment (CORDEX) evaluation runs. The evaluation runs are considered as perfect simulations of CORDEX Regional Climate Models (RCMs) with the boundary conditions by ERA-Interim reanalysis data. The statistical methods are also applied to ERA-Interim reanalysis data and compared with observation data for Indian Summer Monsoon characteristics. We evaluate the ability of statistical methods under the non-stationary environment by taking the difference of years close to extreme future runs (RCP8.5) as warmer years and preindustrial runs as cooler years. We find statistical downscaling of CORDEX evaluation runs shows skill in reproducing the signal of non-stationarity. The study can be extended methods by applying statistical downscaling to CORDEX RCMs with the CMIP5 boundary conditions.
How to cite: Singh, S., Salvi, K., Ghosh, S., and Karmakar, S.: Fidelity of CORDEX Evaluation runs under Non-stationary climate, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-927, https://doi.org/10.5194/egusphere-egu2020-927, 2020.
The downscaling approaches: Statistical and Dynamic, developed for regional climate predictions, have both advantages and limitations. The statistical downscaling is computationally inexpensive but suffers from the violation of the assumption of stationarity in statistical (predictor-predictand) relationship. The dynamical downscaling is assumed to take care of stationarity but suffers from the biases associated with various sources. Here we propose a joint approach of both the methods by applying statistical methods: bias correction & statistical downscaling to Coordinated Regional Climate Downscaling Experiment (CORDEX) evaluation runs. The evaluation runs are considered as perfect simulations of CORDEX Regional Climate Models (RCMs) with the boundary conditions by ERA-Interim reanalysis data. The statistical methods are also applied to ERA-Interim reanalysis data and compared with observation data for Indian Summer Monsoon characteristics. We evaluate the ability of statistical methods under the non-stationary environment by taking the difference of years close to extreme future runs (RCP8.5) as warmer years and preindustrial runs as cooler years. We find statistical downscaling of CORDEX evaluation runs shows skill in reproducing the signal of non-stationarity. The study can be extended methods by applying statistical downscaling to CORDEX RCMs with the CMIP5 boundary conditions.
How to cite: Singh, S., Salvi, K., Ghosh, S., and Karmakar, S.: Fidelity of CORDEX Evaluation runs under Non-stationary climate, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-927, https://doi.org/10.5194/egusphere-egu2020-927, 2020.
EGU2020-4039 | Displays | NP5.4
Model forecast error correction based on the Local Dynamical Analog method: an example application to the ENSO forecastZhaolu Hou, Bin Zuo, Shaoqing Zhang, Fei Huang, Ruiqiang Ding, Wansuo Duan, and Jianping Li
Numerical forecasts always have associated errors. Analogue correction methods combine numerical simulations with statistical analyses to reduce model forecast errors. However, identifying appropriate analogues remains a challenging task. Here, we use the Local Dynamical Analog (LDA) method to locate analogues and correct model forecast errors. As an example, an ENSO model forecast error correction experiment confirms that the LDA method locates more dynamical analogues of states of interest and better corrects forecast errors than do other methods. This is because the LDA method ensures similarity of the initial states and the evolution of both states. In addition, the LDA method can be applied using a scalar time series, which reduces the complexity of the dynamical system. Model forecast error correction using the LDA method provides a new approach to correcting state-dependent model errors and can be readily integrated with other advanced models.
How to cite: Hou, Z., Zuo, B., Zhang, S., Huang, F., Ding, R., Duan, W., and Li, J.: Model forecast error correction based on the Local Dynamical Analog method: an example application to the ENSO forecast, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4039, https://doi.org/10.5194/egusphere-egu2020-4039, 2020.
Numerical forecasts always have associated errors. Analogue correction methods combine numerical simulations with statistical analyses to reduce model forecast errors. However, identifying appropriate analogues remains a challenging task. Here, we use the Local Dynamical Analog (LDA) method to locate analogues and correct model forecast errors. As an example, an ENSO model forecast error correction experiment confirms that the LDA method locates more dynamical analogues of states of interest and better corrects forecast errors than do other methods. This is because the LDA method ensures similarity of the initial states and the evolution of both states. In addition, the LDA method can be applied using a scalar time series, which reduces the complexity of the dynamical system. Model forecast error correction using the LDA method provides a new approach to correcting state-dependent model errors and can be readily integrated with other advanced models.
How to cite: Hou, Z., Zuo, B., Zhang, S., Huang, F., Ding, R., Duan, W., and Li, J.: Model forecast error correction based on the Local Dynamical Analog method: an example application to the ENSO forecast, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4039, https://doi.org/10.5194/egusphere-egu2020-4039, 2020.
EGU2020-5664 | Displays | NP5.4
Correcting for Model Changes in Statistical Post-Processing - An approach based on Response TheoryJonathan Demaeyer and Stéphane Vannitsem
For most statistical post-processing schemes used to correct weather forecasts, changes to the forecast model induce a considerable reforcasting effort. We present a new approach based on response theory to cope with slight model change. In this framework, the model change is seen as a perturbation of the original forecast model. The response theory allows then to evaluate the variation induced on the averages involved in the statistical post-processing, provided that the magnitude of this perturbation is not too large.
This approach is studied in the context of a simple quasi-geostrophic model. It provides a proof-of-concept of the potential performances of response theory in a chaotic system. The parameters of the statistical post-processing used - an Error-in-Variables Model Output Statistics (EVMOS) - are appropriately corrected when facing a model change. The potential application in a more operational environment is also discussed.
How to cite: Demaeyer, J. and Vannitsem, S.: Correcting for Model Changes in Statistical Post-Processing - An approach based on Response Theory, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5664, https://doi.org/10.5194/egusphere-egu2020-5664, 2020.
For most statistical post-processing schemes used to correct weather forecasts, changes to the forecast model induce a considerable reforcasting effort. We present a new approach based on response theory to cope with slight model change. In this framework, the model change is seen as a perturbation of the original forecast model. The response theory allows then to evaluate the variation induced on the averages involved in the statistical post-processing, provided that the magnitude of this perturbation is not too large.
This approach is studied in the context of a simple quasi-geostrophic model. It provides a proof-of-concept of the potential performances of response theory in a chaotic system. The parameters of the statistical post-processing used - an Error-in-Variables Model Output Statistics (EVMOS) - are appropriately corrected when facing a model change. The potential application in a more operational environment is also discussed.
How to cite: Demaeyer, J. and Vannitsem, S.: Correcting for Model Changes in Statistical Post-Processing - An approach based on Response Theory, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5664, https://doi.org/10.5194/egusphere-egu2020-5664, 2020.
EGU2020-6242 | Displays | NP5.4
Probability and deterministic amount of precipitation on the multi-model ensembleJuwon Kim, Hae-Jin Kong, and Hyuncheol Shin
Multi-model ensemble using statistical post-processing is one of the methods to provide the impact of uncertainties of the Numerical Weather Prediction (NWP) models, with low cost and better accuracy for extreme weather forecasts. Extreme weather events such as heat/cold waves, windstorms, and heavy rainfall result in severe damage in human life and properties. However, the performance of the NWP models, particularly, heavy rain forecast is still low due to the intermittent and non-Gaussian properties. The light rain tends to be overestimated and the strong rain tends to be underestimated averagely on the NWP models. Thus the multi-model ensemble using statistical post-processing is activated to correct the discrepancies between the observation and the model intensity of precipitation.
The aim of this study is to provide the improvement of precipitation forecasts in probabilistic and deterministic aspects using a multi-model ensemble method with more weights on the less error and without any bias correction. Six types of models, namely, Local Data assimilation and Prediction System (LDPS), Local ENsemble System (LENS), Global Data assimilation and Prediction System (GDPS), Ensemble Prediction System-Global (EPSG) of Korea Meteorological Administration (KMA), the single and ensemble models of European Centre for Medium-Range Weather Forecasts (ECMWF), are used to blend. The preliminary results of the multi-model ensemble show similar results to the ECMWF ensemble mean in deterministic for 3-hourly accumulated precipitation over the East Asia and the middle of the performance among individual models in probabilistic over the South Korea. More details of the methodology, results, and improvements will be discussed in the presentation.
How to cite: Kim, J., Kong, H.-J., and Shin, H.: Probability and deterministic amount of precipitation on the multi-model ensemble, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6242, https://doi.org/10.5194/egusphere-egu2020-6242, 2020.
Multi-model ensemble using statistical post-processing is one of the methods to provide the impact of uncertainties of the Numerical Weather Prediction (NWP) models, with low cost and better accuracy for extreme weather forecasts. Extreme weather events such as heat/cold waves, windstorms, and heavy rainfall result in severe damage in human life and properties. However, the performance of the NWP models, particularly, heavy rain forecast is still low due to the intermittent and non-Gaussian properties. The light rain tends to be overestimated and the strong rain tends to be underestimated averagely on the NWP models. Thus the multi-model ensemble using statistical post-processing is activated to correct the discrepancies between the observation and the model intensity of precipitation.
The aim of this study is to provide the improvement of precipitation forecasts in probabilistic and deterministic aspects using a multi-model ensemble method with more weights on the less error and without any bias correction. Six types of models, namely, Local Data assimilation and Prediction System (LDPS), Local ENsemble System (LENS), Global Data assimilation and Prediction System (GDPS), Ensemble Prediction System-Global (EPSG) of Korea Meteorological Administration (KMA), the single and ensemble models of European Centre for Medium-Range Weather Forecasts (ECMWF), are used to blend. The preliminary results of the multi-model ensemble show similar results to the ECMWF ensemble mean in deterministic for 3-hourly accumulated precipitation over the East Asia and the middle of the performance among individual models in probabilistic over the South Korea. More details of the methodology, results, and improvements will be discussed in the presentation.
How to cite: Kim, J., Kong, H.-J., and Shin, H.: Probability and deterministic amount of precipitation on the multi-model ensemble, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6242, https://doi.org/10.5194/egusphere-egu2020-6242, 2020.
EGU2020-6811 | Displays | NP5.4
Evaluation of the analog-based method for the operational implementation in CroatiaIris Odak Plenkovic, Suzana Panezic, and Endi Keresturi
Even the state-of-the-art mesoscale models exhibit noteworthy errors, especially in the complex terrain. Therefore, it is useful to include post-processing methods in the forecasting system to further reduce starting model errors at locations where measurements are available.
The analog-based method (ABM) is a point-based post-processing approach which consists of two steps. The first step is to find the most similar past numerical weather predictions (analogs) over several variables (predictors) and the second is to form an analog ensemble (AnEn) out of the corresponding observations.
The ABM is thoroughly tested using the wind speed NWP input, focusing on the complex terrain. Since August 2019 it is used in a test operational mode at Croatian Meteorological and Hydrological Service. The setup includes 15 members wind speed, wind gusts and temperature ensemble predictions for approximately 50 stations using the 2-year training dataset. The preliminary results show that the ABM implementation is successful, reducing the error and improving the skill of the raw model. Additionally, it is found that the ABM predictions of wind speed and gusts optimally need more predictors than the temperature predictions. Finally, the forecasting system shows the best result in the coastal region for the temperature predictions, while the best results for the wind speed are achieved in the nearly flat continental terrain situated more inland.
How to cite: Odak Plenkovic, I., Panezic, S., and Keresturi, E.: Evaluation of the analog-based method for the operational implementation in Croatia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6811, https://doi.org/10.5194/egusphere-egu2020-6811, 2020.
Even the state-of-the-art mesoscale models exhibit noteworthy errors, especially in the complex terrain. Therefore, it is useful to include post-processing methods in the forecasting system to further reduce starting model errors at locations where measurements are available.
The analog-based method (ABM) is a point-based post-processing approach which consists of two steps. The first step is to find the most similar past numerical weather predictions (analogs) over several variables (predictors) and the second is to form an analog ensemble (AnEn) out of the corresponding observations.
The ABM is thoroughly tested using the wind speed NWP input, focusing on the complex terrain. Since August 2019 it is used in a test operational mode at Croatian Meteorological and Hydrological Service. The setup includes 15 members wind speed, wind gusts and temperature ensemble predictions for approximately 50 stations using the 2-year training dataset. The preliminary results show that the ABM implementation is successful, reducing the error and improving the skill of the raw model. Additionally, it is found that the ABM predictions of wind speed and gusts optimally need more predictors than the temperature predictions. Finally, the forecasting system shows the best result in the coastal region for the temperature predictions, while the best results for the wind speed are achieved in the nearly flat continental terrain situated more inland.
How to cite: Odak Plenkovic, I., Panezic, S., and Keresturi, E.: Evaluation of the analog-based method for the operational implementation in Croatia, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6811, https://doi.org/10.5194/egusphere-egu2020-6811, 2020.
EGU2020-7401 | Displays | NP5.4
A boosting algorithm for Generalized Extreme Value distributionsMadlen Peter, Alexander Pasternack, and Henning Rust
In weather and climate science statistical modeling is applied for manifold problems. Due to the increasing number of input variables, overfitting can easily deteriorate the performance for model predictions. In order to avoid this, it is often meaningful to apply model selection approaches. Since conventional approaches can be very time-consuming especially for many predictors, we are using the boosting approach, which combines model selection and parameter estimation. This iterative algorithm identifies and updates in each step only the most important coefficient, such that in the end most important predictor variables have non-zero coefficients and less relevant variables are ignored.
Boosting has been originally developed for classification problems but has also been extended and used for other applications; i.a. non-homogeneous gaussian regression. Based on the non-homogeneous boosting proposed by Messner et al. (2016), which is used to model mean and variance of a forecast distribution simultaneously, we have developed a boosting algorithm for a non-stationary Generalized Extreme Value distribution (GEV). Thus, it is possible to identify the most relevant predictor variables for location, scale and shape parameter concurrently. We apply this algorithm to various toy model simulations to assess the effect of this novel approach.
How to cite: Peter, M., Pasternack, A., and Rust, H.: A boosting algorithm for Generalized Extreme Value distributions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7401, https://doi.org/10.5194/egusphere-egu2020-7401, 2020.
In weather and climate science statistical modeling is applied for manifold problems. Due to the increasing number of input variables, overfitting can easily deteriorate the performance for model predictions. In order to avoid this, it is often meaningful to apply model selection approaches. Since conventional approaches can be very time-consuming especially for many predictors, we are using the boosting approach, which combines model selection and parameter estimation. This iterative algorithm identifies and updates in each step only the most important coefficient, such that in the end most important predictor variables have non-zero coefficients and less relevant variables are ignored.
Boosting has been originally developed for classification problems but has also been extended and used for other applications; i.a. non-homogeneous gaussian regression. Based on the non-homogeneous boosting proposed by Messner et al. (2016), which is used to model mean and variance of a forecast distribution simultaneously, we have developed a boosting algorithm for a non-stationary Generalized Extreme Value distribution (GEV). Thus, it is possible to identify the most relevant predictor variables for location, scale and shape parameter concurrently. We apply this algorithm to various toy model simulations to assess the effect of this novel approach.
How to cite: Peter, M., Pasternack, A., and Rust, H.: A boosting algorithm for Generalized Extreme Value distributions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7401, https://doi.org/10.5194/egusphere-egu2020-7401, 2020.
EGU2020-7804 | Displays | NP5.4
From research to applications – Examples of operational ensemble post-processing in France using machine learningMaxime Taillardat and Olivier Mestre
Statistical post-processing of ensemble forecasts, from simple linear regressions to more sophisticated techniques, is now a well-known procedure in order to correct biased and misdispersed ensemble weather predictions. However, practical applications in National Weather Services is still in its infancy compared to deterministic post-processing. This paper presents two different applications of ensemble post-processing using machine learning at an industrial scale. The first is a station-based post-processing of surface temperature in a medium resolution ensemble system. The second is a gridded post-processing of hourly rainfall amounts in a high resolution ensemble prediction system. The techniques used rely on quantile regression forests (QRF) and ensemble copula coupling (ECC), chosen for their robustness and simplicity of training whatever the variable subject to calibration.
Moreover, some variants of classical techniques used such as QRF or ECC have been developed in order to adjust to operational constraints. A forecast anomaly-based QRF is used for temperature for a better prediction of cold and heat waves. A variant of ECC for hourly rainfall is built, accounting for more realistic longer rainfall accumulations. It is shown that forecast quality as well as forecast value is improved compared to the raw ensemble. At last, comments about model size and computation time are made.
How to cite: Taillardat, M. and Mestre, O.: From research to applications – Examples of operational ensemble post-processing in France using machine learning, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7804, https://doi.org/10.5194/egusphere-egu2020-7804, 2020.
Statistical post-processing of ensemble forecasts, from simple linear regressions to more sophisticated techniques, is now a well-known procedure in order to correct biased and misdispersed ensemble weather predictions. However, practical applications in National Weather Services is still in its infancy compared to deterministic post-processing. This paper presents two different applications of ensemble post-processing using machine learning at an industrial scale. The first is a station-based post-processing of surface temperature in a medium resolution ensemble system. The second is a gridded post-processing of hourly rainfall amounts in a high resolution ensemble prediction system. The techniques used rely on quantile regression forests (QRF) and ensemble copula coupling (ECC), chosen for their robustness and simplicity of training whatever the variable subject to calibration.
Moreover, some variants of classical techniques used such as QRF or ECC have been developed in order to adjust to operational constraints. A forecast anomaly-based QRF is used for temperature for a better prediction of cold and heat waves. A variant of ECC for hourly rainfall is built, accounting for more realistic longer rainfall accumulations. It is shown that forecast quality as well as forecast value is improved compared to the raw ensemble. At last, comments about model size and computation time are made.
How to cite: Taillardat, M. and Mestre, O.: From research to applications – Examples of operational ensemble post-processing in France using machine learning, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7804, https://doi.org/10.5194/egusphere-egu2020-7804, 2020.
EGU2020-8724 | Displays | NP5.4
Will post-processing always improve my forecasts?Jon Olav Skøien, Peter Salamon, and Fredrik Wetterhall
Different statistical techniques are frequently employed to post-process the outcome of ensemble forecasting models. The main reason is to compensate for biases due to errors in model structure or initial conditions, and as a correction for under- or overdispersed ensembles.
Here we present analyses of the results from one these methods. We use the Ensemble Model Output Statistics method (EMOS; Gneiting et al., 2005) to post-process the ensemble output from a continental scale hydrological model - LISFLOOD (Van Der Knijff et al., 2010; De Roo et al., 2000). The model was calibrated at approximately 700 stations based on long term observations of runoff and meteorological variables. We use the same locations for calibration and verification of the 1-10 days forecasts of the model, based on ensemble and deterministic meteorological forecasts from ECMWF (51 ensemble members + 1 high-resolution), DWD (1 member) and COMSO-LEPS (16 ensemble members).
We calibrated the EMOS-parameters using the Continuous ranked probability score (CRPS). Whereas the post-processing improved the results for the first 1-2 days lead time, the improvement was less for increasing lead times of the verification period. As the post-processing is based on assumptions about the forecast errors, we will here present analyses of the ensemble output that can give some indications of what to expect from the post-processing.
Gneiting, T., Raftery, A. E., Westveld, A. H. and Goldman, T.: Calibrated Probabilistic Forecasting Using Ensemble Model Output Statistics and Minimum CRPS Estimation, Mon. Weather Rev., 133(5), 1098–1118, doi:10.1175/MWR2904.1, 2005.
Van Der Knijff, J. M., Younis, J. and De Roo, A. P. J.: LISFLOOD: a GIS‐based distributed model for river basin scale water balance and flood simulation, Int. J. Geogr. Inf. Sci., 24(2), 189–212, doi:10.1080/13658810802549154, 2010.
De Roo, A. P. J., Wesseling, C. G. and Van Deursen, W. P. A.: Physically based river basin modelling within a GIS: The LISFLOOD model, in Hydrological Processes, vol. 14, pp. 1981–1992, John Wiley & Sons Ltd. [online] Available from: http://www.scopus.com/inward/record.url?eid=2-s2.0-0034254644&partnerID=tZOtx3y1, 2000.
How to cite: Skøien, J. O., Salamon, P., and Wetterhall, F.: Will post-processing always improve my forecasts?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8724, https://doi.org/10.5194/egusphere-egu2020-8724, 2020.
Different statistical techniques are frequently employed to post-process the outcome of ensemble forecasting models. The main reason is to compensate for biases due to errors in model structure or initial conditions, and as a correction for under- or overdispersed ensembles.
Here we present analyses of the results from one these methods. We use the Ensemble Model Output Statistics method (EMOS; Gneiting et al., 2005) to post-process the ensemble output from a continental scale hydrological model - LISFLOOD (Van Der Knijff et al., 2010; De Roo et al., 2000). The model was calibrated at approximately 700 stations based on long term observations of runoff and meteorological variables. We use the same locations for calibration and verification of the 1-10 days forecasts of the model, based on ensemble and deterministic meteorological forecasts from ECMWF (51 ensemble members + 1 high-resolution), DWD (1 member) and COMSO-LEPS (16 ensemble members).
We calibrated the EMOS-parameters using the Continuous ranked probability score (CRPS). Whereas the post-processing improved the results for the first 1-2 days lead time, the improvement was less for increasing lead times of the verification period. As the post-processing is based on assumptions about the forecast errors, we will here present analyses of the ensemble output that can give some indications of what to expect from the post-processing.
Gneiting, T., Raftery, A. E., Westveld, A. H. and Goldman, T.: Calibrated Probabilistic Forecasting Using Ensemble Model Output Statistics and Minimum CRPS Estimation, Mon. Weather Rev., 133(5), 1098–1118, doi:10.1175/MWR2904.1, 2005.
Van Der Knijff, J. M., Younis, J. and De Roo, A. P. J.: LISFLOOD: a GIS‐based distributed model for river basin scale water balance and flood simulation, Int. J. Geogr. Inf. Sci., 24(2), 189–212, doi:10.1080/13658810802549154, 2010.
De Roo, A. P. J., Wesseling, C. G. and Van Deursen, W. P. A.: Physically based river basin modelling within a GIS: The LISFLOOD model, in Hydrological Processes, vol. 14, pp. 1981–1992, John Wiley & Sons Ltd. [online] Available from: http://www.scopus.com/inward/record.url?eid=2-s2.0-0034254644&partnerID=tZOtx3y1, 2000.
How to cite: Skøien, J. O., Salamon, P., and Wetterhall, F.: Will post-processing always improve my forecasts?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8724, https://doi.org/10.5194/egusphere-egu2020-8724, 2020.
EGU2020-13825 | Displays | NP5.4
Verification of post-processed seasonal predictionsAndré Düsterhus
Traditionally, verification of (ensemble) model predictions is done by comparing them to deterministic observations, e.g. with scores like the Continuous Ranked Probability Score (CRPS). While these approaches allow uncertain predictions basing on ensemble forecasts, it is open how to verify them against observations with non-parametric uncertainties.
This contribution focuses on statistically post-processed seasonal predictions of the Winter North Atlantic Oscillation (WNAO). The post-processing procedure creates in a first step for a dynamical ensemble prediction and for a statistical prediction basing on predictors two separate probability density functions (pdf). Afterwards these two distributions are combined to create a new statistical-dynamical prediction, which has been proven to be advantageous compared to the purely dynamical prediction. It will be demonstrated how this combination and with it the improvement of the prediction can be achieved before the focus will be set on the evaluation of those predictions at the hand of uncertain observations. Two new scores basing on the Earth Mover's Distance (EMD) and the Integrated Quadratic Distance (IQD) will be introduced and compared before it is shown how they can be used to effectively evaluate probabilistic predictions with uncertain observations.
Furthermore, a common approach (e.g. for correlation measures) is to compare predictions with observations over a longer time period. In this contribution a paradigm shift away from this approach towards comparing predictions for each single time step (like years) will be presented. This view give new insights into the performance of the predictions and allows to come to new understandings of the reasons for advantages or disadvantages of specific predictions.
How to cite: Düsterhus, A.: Verification of post-processed seasonal predictions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13825, https://doi.org/10.5194/egusphere-egu2020-13825, 2020.
Traditionally, verification of (ensemble) model predictions is done by comparing them to deterministic observations, e.g. with scores like the Continuous Ranked Probability Score (CRPS). While these approaches allow uncertain predictions basing on ensemble forecasts, it is open how to verify them against observations with non-parametric uncertainties.
This contribution focuses on statistically post-processed seasonal predictions of the Winter North Atlantic Oscillation (WNAO). The post-processing procedure creates in a first step for a dynamical ensemble prediction and for a statistical prediction basing on predictors two separate probability density functions (pdf). Afterwards these two distributions are combined to create a new statistical-dynamical prediction, which has been proven to be advantageous compared to the purely dynamical prediction. It will be demonstrated how this combination and with it the improvement of the prediction can be achieved before the focus will be set on the evaluation of those predictions at the hand of uncertain observations. Two new scores basing on the Earth Mover's Distance (EMD) and the Integrated Quadratic Distance (IQD) will be introduced and compared before it is shown how they can be used to effectively evaluate probabilistic predictions with uncertain observations.
Furthermore, a common approach (e.g. for correlation measures) is to compare predictions with observations over a longer time period. In this contribution a paradigm shift away from this approach towards comparing predictions for each single time step (like years) will be presented. This view give new insights into the performance of the predictions and allows to come to new understandings of the reasons for advantages or disadvantages of specific predictions.
How to cite: Düsterhus, A.: Verification of post-processed seasonal predictions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13825, https://doi.org/10.5194/egusphere-egu2020-13825, 2020.
EGU2020-17886 | Displays | NP5.4
Towards operational postprocessing of cloud cover at MeteoSwissStephan Hemri, Christoph Spirig, Jonas Bhend, Lionel Moret, and Mark Liniger
Over the last decades ensemble approaches have become state-of-the-art for the quantification of weather forecast uncertainty. Despite ongoing improvements, ensemble forecasts issued by numerical weather prediction models (NWPs) still tend to be biased and underdispersed. Statistical postprocessing has proven to be an appropriate tool to correct biases and underdispersion, and hence to improve forecast skill. Here we focus on multi-model postprocessing of cloud cover forecasts in Switzerland. In order to issue postprocessed forecasts at any point in space, ensemble model output statistics (EMOS) models are trained and verified against EUMETSAT CM SAF satellite data with a spatial resolution of around 2 km over Switzerland. Training with a minimal record length of the past 45 days of forecast and observation data already produced an EMOS model improving direct model output (DMO). Training on a 3 years record of the corresponding season further improved the performance. We evaluate how well postprocessing corrects the most severe forecast errors, like missing fog and low level stratus in winter. For such conditions, postprocessing of cloud cover benefits strongly from incorporating additional predictors into the postprocessing suite. A quasi-operational prototype has been set up and was used to explore meteogram-like visualizations of probabilistic cloud cover forecasts.
How to cite: Hemri, S., Spirig, C., Bhend, J., Moret, L., and Liniger, M.: Towards operational postprocessing of cloud cover at MeteoSwiss, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17886, https://doi.org/10.5194/egusphere-egu2020-17886, 2020.
Over the last decades ensemble approaches have become state-of-the-art for the quantification of weather forecast uncertainty. Despite ongoing improvements, ensemble forecasts issued by numerical weather prediction models (NWPs) still tend to be biased and underdispersed. Statistical postprocessing has proven to be an appropriate tool to correct biases and underdispersion, and hence to improve forecast skill. Here we focus on multi-model postprocessing of cloud cover forecasts in Switzerland. In order to issue postprocessed forecasts at any point in space, ensemble model output statistics (EMOS) models are trained and verified against EUMETSAT CM SAF satellite data with a spatial resolution of around 2 km over Switzerland. Training with a minimal record length of the past 45 days of forecast and observation data already produced an EMOS model improving direct model output (DMO). Training on a 3 years record of the corresponding season further improved the performance. We evaluate how well postprocessing corrects the most severe forecast errors, like missing fog and low level stratus in winter. For such conditions, postprocessing of cloud cover benefits strongly from incorporating additional predictors into the postprocessing suite. A quasi-operational prototype has been set up and was used to explore meteogram-like visualizations of probabilistic cloud cover forecasts.
How to cite: Hemri, S., Spirig, C., Bhend, J., Moret, L., and Liniger, M.: Towards operational postprocessing of cloud cover at MeteoSwiss, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17886, https://doi.org/10.5194/egusphere-egu2020-17886, 2020.
EGU2020-18784 | Displays | NP5.4
Calibration of direct normal irradiance (DNI) forecasts with quantile regressionJose L. Casado-Rubio, Isabel Martínez-Marco, and Carlos Yagüe
Direct normal irradiance (DNI) forecasts from two ensemble models, the global ECMWF-ENS and the limited area multimodel gSREPS, have been calibrated using the quantile regression method, taking DNI as the only input parameter to better understand the inner workings of the method. Forecasts for the southern part of Spain, with lead times up to 72 hours for ECMWF-ENS and 24 hours for gSREPS over a two-year period (from June 2017 to May 2019), have been used.
This study has focused on two particular aspects of the postprocess:
- The effect of quantile regression on the spread of the models. The results show that the spread of ECMWF-ENS greatly increases after the postprocess, which has a positive effect on the accuracy of the model, with an improvement of 20% in the continuous ranked probability score (CRPS) after the calibration. However, this increase is uniform over the whole period, affecting equally to situations with low or high spread, hence the postprocessed forecasts are not able to detect changes in predictability. On the other hand raw gSREPS forecasts behave better during episodes of both low or high predictability. The postprocess does not significantly change the spread and accuracy of gSREPS.
- The influence of the training sample. It has been found that DNI is a variable which can experience periods of low variability, particularly in regions like southern Spain, where long spells of sunny days are common. This has a sizeable impact on the performance of the quantile regression on certain days. Two study cases will be shown to illustrate this problem. Two possible solutions are proposed: use longer training periods (not always possible) or place restrictions on the value of the regression coefficients.
How to cite: Casado-Rubio, J. L., Martínez-Marco, I., and Yagüe, C.: Calibration of direct normal irradiance (DNI) forecasts with quantile regression, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18784, https://doi.org/10.5194/egusphere-egu2020-18784, 2020.
Direct normal irradiance (DNI) forecasts from two ensemble models, the global ECMWF-ENS and the limited area multimodel gSREPS, have been calibrated using the quantile regression method, taking DNI as the only input parameter to better understand the inner workings of the method. Forecasts for the southern part of Spain, with lead times up to 72 hours for ECMWF-ENS and 24 hours for gSREPS over a two-year period (from June 2017 to May 2019), have been used.
This study has focused on two particular aspects of the postprocess:
- The effect of quantile regression on the spread of the models. The results show that the spread of ECMWF-ENS greatly increases after the postprocess, which has a positive effect on the accuracy of the model, with an improvement of 20% in the continuous ranked probability score (CRPS) after the calibration. However, this increase is uniform over the whole period, affecting equally to situations with low or high spread, hence the postprocessed forecasts are not able to detect changes in predictability. On the other hand raw gSREPS forecasts behave better during episodes of both low or high predictability. The postprocess does not significantly change the spread and accuracy of gSREPS.
- The influence of the training sample. It has been found that DNI is a variable which can experience periods of low variability, particularly in regions like southern Spain, where long spells of sunny days are common. This has a sizeable impact on the performance of the quantile regression on certain days. Two study cases will be shown to illustrate this problem. Two possible solutions are proposed: use longer training periods (not always possible) or place restrictions on the value of the regression coefficients.
How to cite: Casado-Rubio, J. L., Martínez-Marco, I., and Yagüe, C.: Calibration of direct normal irradiance (DNI) forecasts with quantile regression, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18784, https://doi.org/10.5194/egusphere-egu2020-18784, 2020.
EGU2020-22298 | Displays | NP5.4
Towards operational post-processing of probabilistic temperature forecasts at MeteoSwissJan Rajczak, Regula Keller, Jonas Bhend, Christoph Spirig, Stephan Hemri, Lionel Moret, and Mark Liniger
MeteoSwiss is currently developing a post-processing suite for the territory of Switzerland. The system aims to provide optimized multi-variable (i.e. temperature, precipitation, wind and cloud cover), spatial and probabilistic predictions. The system will combine information in a seamless manner from the in-house short range and regional (COSMO-E/1) of 1 resp. 2 km resolution and the medium range ECMWF IFS NWP systems. At the example of probabilistic temperature forecasts, this contribution discusses recent advances and experiences at developing, applying and operationalizing non-homogenous Gaussian regression, also known as ensemble model output statistics (EMOS).
Over the complex terrain of Switzerland, postprocessing leads to a substantial improvement of temperature forecasts by up to 30% in terms of CRPS with respect to elevation-corrected direct model output (DMO) even by a basic EMOS only relying on DMO of temperature. Incorporating suitable predictors, such as the atmospheric boundary layer height, leads to a further gain in forecast quality. Results also show that combining high- (COSMO-E) and coarse-resolution (IFS) NWP output can not only provide a seamless medium-range forecast, but also further increase prediction skill during the time horizon when both models are available. Finally, we discuss first attempts to produce high-resolution spatial PP fields for arbitrary locations by exploiting a global EMOS framework with multiple static (e.g. geographic characteristics) and dynamic predictors derived from NWP data.
How to cite: Rajczak, J., Keller, R., Bhend, J., Spirig, C., Hemri, S., Moret, L., and Liniger, M.: Towards operational post-processing of probabilistic temperature forecasts at MeteoSwiss, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22298, https://doi.org/10.5194/egusphere-egu2020-22298, 2020.
MeteoSwiss is currently developing a post-processing suite for the territory of Switzerland. The system aims to provide optimized multi-variable (i.e. temperature, precipitation, wind and cloud cover), spatial and probabilistic predictions. The system will combine information in a seamless manner from the in-house short range and regional (COSMO-E/1) of 1 resp. 2 km resolution and the medium range ECMWF IFS NWP systems. At the example of probabilistic temperature forecasts, this contribution discusses recent advances and experiences at developing, applying and operationalizing non-homogenous Gaussian regression, also known as ensemble model output statistics (EMOS).
Over the complex terrain of Switzerland, postprocessing leads to a substantial improvement of temperature forecasts by up to 30% in terms of CRPS with respect to elevation-corrected direct model output (DMO) even by a basic EMOS only relying on DMO of temperature. Incorporating suitable predictors, such as the atmospheric boundary layer height, leads to a further gain in forecast quality. Results also show that combining high- (COSMO-E) and coarse-resolution (IFS) NWP output can not only provide a seamless medium-range forecast, but also further increase prediction skill during the time horizon when both models are available. Finally, we discuss first attempts to produce high-resolution spatial PP fields for arbitrary locations by exploiting a global EMOS framework with multiple static (e.g. geographic characteristics) and dynamic predictors derived from NWP data.
How to cite: Rajczak, J., Keller, R., Bhend, J., Spirig, C., Hemri, S., Moret, L., and Liniger, M.: Towards operational post-processing of probabilistic temperature forecasts at MeteoSwiss, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22298, https://doi.org/10.5194/egusphere-egu2020-22298, 2020.
EGU2020-22422 | Displays | NP5.4
Regime-dependent statistical post-processing of ensemble forecastsSam Allen, Christopher Ferro, and Frank Kwasniok
A number of realizations of one or more numerical weather prediction (NWP) models, initialised at a variety of initial conditions, compose an ensemble forecast. These forecasts exhibit systematic errors and biases that can be corrected by statistical post-processing. Post-processing yields calibrated forecasts by analysing the statistical relationship between historical forecasts and their corresponding observations. This article aims to extend post processing methodology to incorporate atmospheric circulation. The circulation, or flow, is largely responsible for the weather that we experience and it is hypothesized here that relationships between the NWP model and the atmosphere depend upon the prevailing flow. Numerous studies have focussed on the tendency of this flow to reduce to a set of recognisable arrangements, known as regimes, which recur and persist at fixed geographical locations. This dynamical phenomenon allows the circulation to be categorized into a small number of regime states. In a highly idealized model of the atmosphere, the Lorenz ‘96 system, ensemble forecasts are subjected to well-known post-processing techniques conditional on the system's underlying regime. Two different variables, one of the state variables and one related to the energy of the system, are forecasted and considerable improvements in forecast skill upon standard post-processing are seen when the distribution of the predictand varies depending on the regime. Advantages of this approach and its inherent challenges are discussed, along with potential extensions for operational forecasters.
How to cite: Allen, S., Ferro, C., and Kwasniok, F.: Regime-dependent statistical post-processing of ensemble forecasts, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22422, https://doi.org/10.5194/egusphere-egu2020-22422, 2020.
A number of realizations of one or more numerical weather prediction (NWP) models, initialised at a variety of initial conditions, compose an ensemble forecast. These forecasts exhibit systematic errors and biases that can be corrected by statistical post-processing. Post-processing yields calibrated forecasts by analysing the statistical relationship between historical forecasts and their corresponding observations. This article aims to extend post processing methodology to incorporate atmospheric circulation. The circulation, or flow, is largely responsible for the weather that we experience and it is hypothesized here that relationships between the NWP model and the atmosphere depend upon the prevailing flow. Numerous studies have focussed on the tendency of this flow to reduce to a set of recognisable arrangements, known as regimes, which recur and persist at fixed geographical locations. This dynamical phenomenon allows the circulation to be categorized into a small number of regime states. In a highly idealized model of the atmosphere, the Lorenz ‘96 system, ensemble forecasts are subjected to well-known post-processing techniques conditional on the system's underlying regime. Two different variables, one of the state variables and one related to the energy of the system, are forecasted and considerable improvements in forecast skill upon standard post-processing are seen when the distribution of the predictand varies depending on the regime. Advantages of this approach and its inherent challenges are discussed, along with potential extensions for operational forecasters.
How to cite: Allen, S., Ferro, C., and Kwasniok, F.: Regime-dependent statistical post-processing of ensemble forecasts, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22422, https://doi.org/10.5194/egusphere-egu2020-22422, 2020.
NP6.1 – Lagrangian methods for atmosphere and ocean science
EGU2020-1081 | Displays | NP6.1
Seasonality of surface stirring by geostrophic flows in the Bay of BengalNihar Paul and Jai Sukhatme
Stirring of passive tracers in the Bay of Bengal driven by altimetry derived daily geostrophic surface currents, is studied on subseasonal timescales. To begin with, Hovmöller plots, wavenumber-frequency diagrams and power spectra confirm the multiscale nature of the flow. Advection of latitudinal and longitudinal bands highlights the chaotic nature of stirring in the Bay via repeated straining and filamentation of the tracer field. An immediate finding is that stirring is local, i.e. of the scale of the eddies, and does not span the entire basin. Further, stirring rates are enhanced along the coast of the Bay and are relatively higher in the pre- and post-monsoonal seasons. Indeed, Finite Time Lyapunov Exponent (FTLE) and Finite Size Lyapunov Exponent (FSLE) maps in all the seasons are patchy with minima scattered through the interior of the Bay. Further, these maps bring out a seasonal cycle wherein rapid stirring progressively moves from the northern to southern Bay during pre- and post-monsoonal periods, respectively. The non-uniform stirring of the Bay is reflected in long tailed probability density functions of FTLEs, that become more stretched for longer time intervals. Quantitatively, advection for a week shows the mean FTLE lies between 0.13±0.07 day-1, while extremes reach almost 0.6 day-1 . Averaged over the Bay, Relative dispersion initially grows exponentially, followed by a power-law at scales between approximately 100 and 250 km, which finally transitions to an eddy-diffusive regime. Quantitatively, below 250 km, a scale dependent diffusion coefficient is extracted that behaves as a power-law with cluster size, while above 250 km, eddy-diffusivities range from 6 × 103 - 1.6 × 104 m2s-1 in different regions of the Bay. These estimates provide a useful guide for resolution dependent diffusivities in numerical models that hope to properly represent surface stirring in the Bay.
How to cite: Paul, N. and Sukhatme, J.: Seasonality of surface stirring by geostrophic flows in the Bay of Bengal, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1081, https://doi.org/10.5194/egusphere-egu2020-1081, 2020.
Stirring of passive tracers in the Bay of Bengal driven by altimetry derived daily geostrophic surface currents, is studied on subseasonal timescales. To begin with, Hovmöller plots, wavenumber-frequency diagrams and power spectra confirm the multiscale nature of the flow. Advection of latitudinal and longitudinal bands highlights the chaotic nature of stirring in the Bay via repeated straining and filamentation of the tracer field. An immediate finding is that stirring is local, i.e. of the scale of the eddies, and does not span the entire basin. Further, stirring rates are enhanced along the coast of the Bay and are relatively higher in the pre- and post-monsoonal seasons. Indeed, Finite Time Lyapunov Exponent (FTLE) and Finite Size Lyapunov Exponent (FSLE) maps in all the seasons are patchy with minima scattered through the interior of the Bay. Further, these maps bring out a seasonal cycle wherein rapid stirring progressively moves from the northern to southern Bay during pre- and post-monsoonal periods, respectively. The non-uniform stirring of the Bay is reflected in long tailed probability density functions of FTLEs, that become more stretched for longer time intervals. Quantitatively, advection for a week shows the mean FTLE lies between 0.13±0.07 day-1, while extremes reach almost 0.6 day-1 . Averaged over the Bay, Relative dispersion initially grows exponentially, followed by a power-law at scales between approximately 100 and 250 km, which finally transitions to an eddy-diffusive regime. Quantitatively, below 250 km, a scale dependent diffusion coefficient is extracted that behaves as a power-law with cluster size, while above 250 km, eddy-diffusivities range from 6 × 103 - 1.6 × 104 m2s-1 in different regions of the Bay. These estimates provide a useful guide for resolution dependent diffusivities in numerical models that hope to properly represent surface stirring in the Bay.
How to cite: Paul, N. and Sukhatme, J.: Seasonality of surface stirring by geostrophic flows in the Bay of Bengal, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1081, https://doi.org/10.5194/egusphere-egu2020-1081, 2020.
EGU2020-1459 | Displays | NP6.1
The spiralling North Atlantic Subtropical GyreKristofer Döös, Sara Berglund, Trevor Mcdougall, and Sjoerd Groeskamp
The North Atlantic Subtropical Gyre is shown to have a downward spiral flow beneath the mixed layer, where the water slowly gets denser, colder and fresher as it spins around the gyre. This path is traced with Lagrangian trajectories as they enter the Gyre in the Gulf Stream from the south until they exit through the North Atlantic Drift. The preliminary results indicate that these warm, saline waters from the south gradually becomes fresher, colder and denser due to mixing with waters originating from the North Atlantic. There are indications that there is also a diapycnal mixing, in the eastern part of the gyre due to mixing with the saline Mediterranean Waters, which would then be crucial for the Atlantic Meridional Overturning. The mixing in the rest of the gyre is dominated by isopycnic mixing, which transforms gradually the water into colder and fresher water as it spins down the gyre into the abyssal ocean before heading north.
How to cite: Döös, K., Berglund, S., Mcdougall, T., and Groeskamp, S.: The spiralling North Atlantic Subtropical Gyre, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1459, https://doi.org/10.5194/egusphere-egu2020-1459, 2020.
The North Atlantic Subtropical Gyre is shown to have a downward spiral flow beneath the mixed layer, where the water slowly gets denser, colder and fresher as it spins around the gyre. This path is traced with Lagrangian trajectories as they enter the Gyre in the Gulf Stream from the south until they exit through the North Atlantic Drift. The preliminary results indicate that these warm, saline waters from the south gradually becomes fresher, colder and denser due to mixing with waters originating from the North Atlantic. There are indications that there is also a diapycnal mixing, in the eastern part of the gyre due to mixing with the saline Mediterranean Waters, which would then be crucial for the Atlantic Meridional Overturning. The mixing in the rest of the gyre is dominated by isopycnic mixing, which transforms gradually the water into colder and fresher water as it spins down the gyre into the abyssal ocean before heading north.
How to cite: Döös, K., Berglund, S., Mcdougall, T., and Groeskamp, S.: The spiralling North Atlantic Subtropical Gyre, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-1459, https://doi.org/10.5194/egusphere-egu2020-1459, 2020.
EGU2020-2265 | Displays | NP6.1 | Highlight
Lagrangian analysis of atmospheric water balance over the Bay of BengalDipanjan Dey and Kristofer Döös
The origin of the atmospheric freshwater fluxes into the Bay of Bengal (BoB) are traced with Lagrangian water trajectories for both present and possible future climates. The water is traced backward from the precipitation at the sea surface to the evaporation regions. In the present-day simulation, the source is mostly from the Western Indian Ocean and near the Western Australian Coast. In the future climate scenario, simulated by EC-Earth, the origin of the moisture will not be the same as the present climate. In addition to it, the Bay of Bengal sourced water is also traced from the evaporation region to the precipitation locations. Most of the BoB originated moisture is precipitating within the neighbouring areas of the drainage basin and some part is transported into the Pacific Ocean. The Lagrangian model TRACMASS is currently running and a detailed analysis and results will be presented in the conference.
How to cite: Dey, D. and Döös, K.: Lagrangian analysis of atmospheric water balance over the Bay of Bengal, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2265, https://doi.org/10.5194/egusphere-egu2020-2265, 2020.
The origin of the atmospheric freshwater fluxes into the Bay of Bengal (BoB) are traced with Lagrangian water trajectories for both present and possible future climates. The water is traced backward from the precipitation at the sea surface to the evaporation regions. In the present-day simulation, the source is mostly from the Western Indian Ocean and near the Western Australian Coast. In the future climate scenario, simulated by EC-Earth, the origin of the moisture will not be the same as the present climate. In addition to it, the Bay of Bengal sourced water is also traced from the evaporation region to the precipitation locations. Most of the BoB originated moisture is precipitating within the neighbouring areas of the drainage basin and some part is transported into the Pacific Ocean. The Lagrangian model TRACMASS is currently running and a detailed analysis and results will be presented in the conference.
How to cite: Dey, D. and Döös, K.: Lagrangian analysis of atmospheric water balance over the Bay of Bengal, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2265, https://doi.org/10.5194/egusphere-egu2020-2265, 2020.
EGU2020-2569 | Displays | NP6.1
Forward and Backward Lagrangian Particle Tracking in Ensemble Flow FieldsSamah El Mohtar, Ibrahim Hoteit, Omar Knio, Leila Issa, and Issam Lakkis
Ocean ensemble data assimilation systems generate ensembles of independent velocity field realizations after every assimilation cycle. Lagrangian tracking of passive tracers within such a framework is challenging due to the exponential growth in the number of particles that arises from describing the behavior of velocity over time as a set of possible combinations of the different realizations. This contribution addresses the problem of efficiently advecting particles, forward and backward in time, in ensemble flow fields, whose statistics are prescribed by an underlying assimilated ensemble. To this end, a parallel adaptive binning procedure that conserves the zeroth, first and second moments of probability is introduced to control the growth in the number of particles. The adaptive binning process offers a tradeoff between speed and accuracy by limiting the number of particles to a desired maximum. To validate the proposed method, we conducted various forward and backward particle tracking experiments within a realistic high-resolution ensemble assimilation setting of the Red Sea, focusing on the effect of the maximum number of particles, the time step, the variance of the ensemble, the travel time, the source location, and history of transport.
How to cite: El Mohtar, S., Hoteit, I., Knio, O., Issa, L., and Lakkis, I.: Forward and Backward Lagrangian Particle Tracking in Ensemble Flow Fields, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2569, https://doi.org/10.5194/egusphere-egu2020-2569, 2020.
Ocean ensemble data assimilation systems generate ensembles of independent velocity field realizations after every assimilation cycle. Lagrangian tracking of passive tracers within such a framework is challenging due to the exponential growth in the number of particles that arises from describing the behavior of velocity over time as a set of possible combinations of the different realizations. This contribution addresses the problem of efficiently advecting particles, forward and backward in time, in ensemble flow fields, whose statistics are prescribed by an underlying assimilated ensemble. To this end, a parallel adaptive binning procedure that conserves the zeroth, first and second moments of probability is introduced to control the growth in the number of particles. The adaptive binning process offers a tradeoff between speed and accuracy by limiting the number of particles to a desired maximum. To validate the proposed method, we conducted various forward and backward particle tracking experiments within a realistic high-resolution ensemble assimilation setting of the Red Sea, focusing on the effect of the maximum number of particles, the time step, the variance of the ensemble, the travel time, the source location, and history of transport.
How to cite: El Mohtar, S., Hoteit, I., Knio, O., Issa, L., and Lakkis, I.: Forward and Backward Lagrangian Particle Tracking in Ensemble Flow Fields, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2569, https://doi.org/10.5194/egusphere-egu2020-2569, 2020.
EGU2020-2671 | Displays | NP6.1
Relative dispersion in a model of stratified upper-ocean turbulenceStefano Berti and Guillaume Lapeyre
Turbulence in the upper ocean in the submesoscale range (scales smaller than the deformation radius) plays an important role for the heat exchange with the atmosphere and for oceanic biogeochemistry. Its dynamical features are thought to strongly depend on the seasonal cycle and the associated mixed-layer instabilities. The latter are particularly relevant in winter and are responsible for the fomation of energetic small scales that are not confined in a thin layer close to the surface, as those arising from mesoscale-driven processes, but extend over the whole depth of the mixed layer. The knowledge of the transport properties of oceanic flows at depth, however, is still limited, due to the complexity of performing measurements below the surface. Improving this knowledge is essential to understand how the surface dynamics couple with those of the ocean interior.
By means of numerical simulations, here we explore the dispersion properties of turbulent flows in a quasi-geostrophic model system made of two coupled fluid layers (aimed to represent the mixed layer and the thermocline) with different stratification. Such a model has been previously shown to give rise to dynamics that compare well with observations of wintertime submesoscale flows. We examine the horizontal relative dispersion of Lagrangian tracers by means of both fixed-time and fixed-scale statistical indicators, at the surface and at depth, in the different dynamical regimes occurring in the presence, or not, of a mixed layer. The results indicate that, when mixed-layer instabilities are present, the dispersion regime is local (meaning governed by eddies of the same size as the particle separation distance) from the surface down to depths comparable with that of the interface with the thermocline. By contrasting this picture with what happens in the absence of a mixed layer, when dispersion quickly becomes nonlocal (i.e. dominated by the transport by the largest eddies) as a function of depth, we identify the origin of this behavior in the existence of fine-scale energetic structures due to mixed-layer instabilities. Finally, we discuss the effect of vertical shear on the tracer spreading process and address the correlation between the dispersion properties at the surface and in deeper layers, which is relevant to assess the possibility of inferring the dynamical features of deeper flows from the more accessible surface ones.
How to cite: Berti, S. and Lapeyre, G.: Relative dispersion in a model of stratified upper-ocean turbulence, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2671, https://doi.org/10.5194/egusphere-egu2020-2671, 2020.
Turbulence in the upper ocean in the submesoscale range (scales smaller than the deformation radius) plays an important role for the heat exchange with the atmosphere and for oceanic biogeochemistry. Its dynamical features are thought to strongly depend on the seasonal cycle and the associated mixed-layer instabilities. The latter are particularly relevant in winter and are responsible for the fomation of energetic small scales that are not confined in a thin layer close to the surface, as those arising from mesoscale-driven processes, but extend over the whole depth of the mixed layer. The knowledge of the transport properties of oceanic flows at depth, however, is still limited, due to the complexity of performing measurements below the surface. Improving this knowledge is essential to understand how the surface dynamics couple with those of the ocean interior.
By means of numerical simulations, here we explore the dispersion properties of turbulent flows in a quasi-geostrophic model system made of two coupled fluid layers (aimed to represent the mixed layer and the thermocline) with different stratification. Such a model has been previously shown to give rise to dynamics that compare well with observations of wintertime submesoscale flows. We examine the horizontal relative dispersion of Lagrangian tracers by means of both fixed-time and fixed-scale statistical indicators, at the surface and at depth, in the different dynamical regimes occurring in the presence, or not, of a mixed layer. The results indicate that, when mixed-layer instabilities are present, the dispersion regime is local (meaning governed by eddies of the same size as the particle separation distance) from the surface down to depths comparable with that of the interface with the thermocline. By contrasting this picture with what happens in the absence of a mixed layer, when dispersion quickly becomes nonlocal (i.e. dominated by the transport by the largest eddies) as a function of depth, we identify the origin of this behavior in the existence of fine-scale energetic structures due to mixed-layer instabilities. Finally, we discuss the effect of vertical shear on the tracer spreading process and address the correlation between the dispersion properties at the surface and in deeper layers, which is relevant to assess the possibility of inferring the dynamical features of deeper flows from the more accessible surface ones.
How to cite: Berti, S. and Lapeyre, G.: Relative dispersion in a model of stratified upper-ocean turbulence, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2671, https://doi.org/10.5194/egusphere-egu2020-2671, 2020.
EGU2020-6507 | Displays | NP6.1
Application systems of the FIO ocean forecasting system using Lagrangian methodsLiping Yin, Fangli Qiao, Chang Zhao, and Guansuo Wang
Lagrangian methods have been widely used and playing more and more essential roles in the analysis of ocean physical processes, pollution prediction, ecosystem protection and fisheries. Using the Lagrangian methods based on the high resolution coupled ocean model, we report several specific studies. The numerical modelling team from First Institute of Oceanography (FIO), Ministry of Natural Resources (MNR) of China, developed an ocean forecasting system based on the global (1/10°) wave-tide-circulation coupled model, as well as the regional model (1/24°) for China and adjacent seas. Basing on this system and its products, we developed the global ocean radionuclides model to investigate the long-term transport, distribution and evaluation of 137Cs in the ocean both from the Fukushima nuclear accident in March of 2011 and nuclear tests during the past 60 years; established the search and rescue system which has successfully applied in the rescue of the Phuket boat capsizing accident in July 2018; established the Enteromorpha prediction and tracking models for the protection of the marine environmental hazard from Enteromorpha, and to identify the origin area of this harmful green tide; developed the stock enhancement model of edible jellyfish to mimic the distribution of the human-released jellyfish and identify the connectivity between the releasing site and the fishing ground in Liaodong Bay of Bohai Sea, China. With the combination of the statistical methods, we established the near-term forecast and long-term projection system of the oil spill to forecast and evaluate the influence of the oil spill from the “Sanchi” collision accident on the ocean. All of these applications are verified and essential for protecting the oceans.
How to cite: Yin, L., Qiao, F., Zhao, C., and Wang, G.: Application systems of the FIO ocean forecasting system using Lagrangian methods, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6507, https://doi.org/10.5194/egusphere-egu2020-6507, 2020.
Lagrangian methods have been widely used and playing more and more essential roles in the analysis of ocean physical processes, pollution prediction, ecosystem protection and fisheries. Using the Lagrangian methods based on the high resolution coupled ocean model, we report several specific studies. The numerical modelling team from First Institute of Oceanography (FIO), Ministry of Natural Resources (MNR) of China, developed an ocean forecasting system based on the global (1/10°) wave-tide-circulation coupled model, as well as the regional model (1/24°) for China and adjacent seas. Basing on this system and its products, we developed the global ocean radionuclides model to investigate the long-term transport, distribution and evaluation of 137Cs in the ocean both from the Fukushima nuclear accident in March of 2011 and nuclear tests during the past 60 years; established the search and rescue system which has successfully applied in the rescue of the Phuket boat capsizing accident in July 2018; established the Enteromorpha prediction and tracking models for the protection of the marine environmental hazard from Enteromorpha, and to identify the origin area of this harmful green tide; developed the stock enhancement model of edible jellyfish to mimic the distribution of the human-released jellyfish and identify the connectivity between the releasing site and the fishing ground in Liaodong Bay of Bohai Sea, China. With the combination of the statistical methods, we established the near-term forecast and long-term projection system of the oil spill to forecast and evaluate the influence of the oil spill from the “Sanchi” collision accident on the ocean. All of these applications are verified and essential for protecting the oceans.
How to cite: Yin, L., Qiao, F., Zhao, C., and Wang, G.: Application systems of the FIO ocean forecasting system using Lagrangian methods, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6507, https://doi.org/10.5194/egusphere-egu2020-6507, 2020.
EGU2020-6984 | Displays | NP6.1
TRACMASS - A mass conserving trajectory code for ocean and atmosphere general circulation modelsAitor Aldama Campino, Kristofer Döös, Sara Berglund, Dipanjan Dey, Joakim Kjellsson, and Bror Jonsson
We present the latest version of the TRACMASS trajectory code, version 7.0. The new version includes new features such as water tracing in the atmosphere, parameterisation scheme for sub-grid scale turbulence, generalisation of the tracer handling, etc. The code has also become more user friendly and easier to get started with. Previous versions of TRACMASS only allowed temperature, salinity and potential density to be calculated along the trajectories, but the new version allows any tracer to be followed e.g. biogeochemical tracers or chemical compounds in the atmosphere. The new parameterisation of sub-grid turbulence will enhance the kinetic energy and dispersion of trajectories in the ocean so that results from eddy-permitting ocean models (dx ∼25km) resemble those from “eddy-resolving” models (dx ∼8km). We will demonstrate some use cases of these new capabilities for atmosphere and ocean sciences.
TRACMASS calculates Lagrangian trajectories offline for both the ocean and atmosphere by using already stored velocity fields, and optionally tracer fields. The velocity fields may be taken from ocean or atmosphere circulation models (e.g. NEMO, OpenIFS), reanalysis products (e.g. ERA-5) or observations (e.g. geostrophic currents from satellite altimetry). The fact that the numerical scheme in TRACMASS is mass conserving allows us to associate each trajectory with a mass transport and calculate the Lagrangian mass transport between different regions as well as construct Lagrangian stream functions.
A live demonstration on how to set up, configure and run the TRACMASS code will be given.
How to cite: Aldama Campino, A., Döös, K., Berglund, S., Dey, D., Kjellsson, J., and Jonsson, B.: TRACMASS - A mass conserving trajectory code for ocean and atmosphere general circulation models, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6984, https://doi.org/10.5194/egusphere-egu2020-6984, 2020.
We present the latest version of the TRACMASS trajectory code, version 7.0. The new version includes new features such as water tracing in the atmosphere, parameterisation scheme for sub-grid scale turbulence, generalisation of the tracer handling, etc. The code has also become more user friendly and easier to get started with. Previous versions of TRACMASS only allowed temperature, salinity and potential density to be calculated along the trajectories, but the new version allows any tracer to be followed e.g. biogeochemical tracers or chemical compounds in the atmosphere. The new parameterisation of sub-grid turbulence will enhance the kinetic energy and dispersion of trajectories in the ocean so that results from eddy-permitting ocean models (dx ∼25km) resemble those from “eddy-resolving” models (dx ∼8km). We will demonstrate some use cases of these new capabilities for atmosphere and ocean sciences.
TRACMASS calculates Lagrangian trajectories offline for both the ocean and atmosphere by using already stored velocity fields, and optionally tracer fields. The velocity fields may be taken from ocean or atmosphere circulation models (e.g. NEMO, OpenIFS), reanalysis products (e.g. ERA-5) or observations (e.g. geostrophic currents from satellite altimetry). The fact that the numerical scheme in TRACMASS is mass conserving allows us to associate each trajectory with a mass transport and calculate the Lagrangian mass transport between different regions as well as construct Lagrangian stream functions.
A live demonstration on how to set up, configure and run the TRACMASS code will be given.
How to cite: Aldama Campino, A., Döös, K., Berglund, S., Dey, D., Kjellsson, J., and Jonsson, B.: TRACMASS - A mass conserving trajectory code for ocean and atmosphere general circulation models, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6984, https://doi.org/10.5194/egusphere-egu2020-6984, 2020.
EGU2020-7357 | Displays | NP6.1
A Lagrangian strategy for in situ sampling the physical-biological coupling at fine scale : the PROTEVSMED-SWOT 2018 cruiseRoxane Tzortzis, Andrea M. Doglioli, Stéphanie Barrillon, Anne A. Petrenko, Francesco d'Ovidio, Lloyd Izard, Melilotus Thyssen, Ananda Pascual, Frédéric Cyr, Franck Dumas, and Gérald Gregori
The term "fine scales" is generally used to refer to the ocean processes occuring on horizontal scales smaller than 10 km and
characterized by a short lifetime (days/weeks). Fine scales have been predominantly studied with numerical simulations and
satellite observations which have highlighted their significant role on biological processes. Indeed, their short time scale is the
same as a lot of important processes in phytoplankton dynamics. Model simulations have shown that fine scales such as fronts
and filaments strongly influence the distribution of phytoplankton species. Nowadays, the combination of in situ measurements,
satellite observations and model simulations is a necessity to better understand these mechanisms. However these processes
are particularly challenging to sample in situ because of their size and their ephemeral nature.
The PROTEVSMED-SWOT cruise was performed in the Western Mediterranean Sea, in the southern region of the Balearic
Islands, onboard BHO Beautemps-Beaupré, between April 30 th and May 14 th , 2018. In order to study the influence of fine
scales on the distribution of phytoplankton species, a satellite-based adaptive Lagrangian sampling strategy has been deployed
in order to i) identify a fine scale structure of interest, ii) sample it at high spatial resolution the phytoplankton community, and
iii) follow the evolution of this structure and the related distribution of phytoplankton. The SPASSO software package uses
satellite altimetry, SST and surface Chl a concentration data to generate and provide near-real time daily maps of the dynamical
and biogeochemical structures present in the area. The sampling strategy was defined in order to cross a frontal zone separating
different types of water. Multidisciplinary in situ sensors (hull-mounted ADCP, a Seasoar towed fish and an automated flow
cytometer installed on the seawater supply of the Thermosalinograph) were used to sample at high spatial resolution physical
and biological variables. A particular attention was put in adapting the temporal sampling in different water masses to the
biological time scales in order to reconstruct the phytoplankton diurnal cycle.
Such a strategy was successful in sampling two different water masses separated by a narrow front and characterized by
different aboundances of several phytoplankton species and functional groups. Consequently, our results highlight the role of
the front on the physical and biological coupling confirming previous modelling and remote-sensing studies.
The new generation of altimetric satellite, SWOT, will provide a 2D sea surface height at an unprecedented resolution and
it will be a unique opportunity to better observe fine scale structures in the global ocean. Our methodology paves the way to
future in situ experiments that are planned in 2022 during the SWOT fast-sampling phase, few months after its launch.
How to cite: Tzortzis, R., Doglioli, A. M., Barrillon, S., Petrenko, A. A., d'Ovidio, F., Izard, L., Thyssen, M., Pascual, A., Cyr, F., Dumas, F., and Gregori, G.: A Lagrangian strategy for in situ sampling the physical-biological coupling at fine scale : the PROTEVSMED-SWOT 2018 cruise, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7357, https://doi.org/10.5194/egusphere-egu2020-7357, 2020.
The term "fine scales" is generally used to refer to the ocean processes occuring on horizontal scales smaller than 10 km and
characterized by a short lifetime (days/weeks). Fine scales have been predominantly studied with numerical simulations and
satellite observations which have highlighted their significant role on biological processes. Indeed, their short time scale is the
same as a lot of important processes in phytoplankton dynamics. Model simulations have shown that fine scales such as fronts
and filaments strongly influence the distribution of phytoplankton species. Nowadays, the combination of in situ measurements,
satellite observations and model simulations is a necessity to better understand these mechanisms. However these processes
are particularly challenging to sample in situ because of their size and their ephemeral nature.
The PROTEVSMED-SWOT cruise was performed in the Western Mediterranean Sea, in the southern region of the Balearic
Islands, onboard BHO Beautemps-Beaupré, between April 30 th and May 14 th , 2018. In order to study the influence of fine
scales on the distribution of phytoplankton species, a satellite-based adaptive Lagrangian sampling strategy has been deployed
in order to i) identify a fine scale structure of interest, ii) sample it at high spatial resolution the phytoplankton community, and
iii) follow the evolution of this structure and the related distribution of phytoplankton. The SPASSO software package uses
satellite altimetry, SST and surface Chl a concentration data to generate and provide near-real time daily maps of the dynamical
and biogeochemical structures present in the area. The sampling strategy was defined in order to cross a frontal zone separating
different types of water. Multidisciplinary in situ sensors (hull-mounted ADCP, a Seasoar towed fish and an automated flow
cytometer installed on the seawater supply of the Thermosalinograph) were used to sample at high spatial resolution physical
and biological variables. A particular attention was put in adapting the temporal sampling in different water masses to the
biological time scales in order to reconstruct the phytoplankton diurnal cycle.
Such a strategy was successful in sampling two different water masses separated by a narrow front and characterized by
different aboundances of several phytoplankton species and functional groups. Consequently, our results highlight the role of
the front on the physical and biological coupling confirming previous modelling and remote-sensing studies.
The new generation of altimetric satellite, SWOT, will provide a 2D sea surface height at an unprecedented resolution and
it will be a unique opportunity to better observe fine scale structures in the global ocean. Our methodology paves the way to
future in situ experiments that are planned in 2022 during the SWOT fast-sampling phase, few months after its launch.
How to cite: Tzortzis, R., Doglioli, A. M., Barrillon, S., Petrenko, A. A., d'Ovidio, F., Izard, L., Thyssen, M., Pascual, A., Cyr, F., Dumas, F., and Gregori, G.: A Lagrangian strategy for in situ sampling the physical-biological coupling at fine scale : the PROTEVSMED-SWOT 2018 cruise, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7357, https://doi.org/10.5194/egusphere-egu2020-7357, 2020.
EGU2020-8422 | Displays | NP6.1
A satellite-based Lagrangian perspective on Atlantic Water fractionation in the Nordic SeasLéon Chafik and Sara Broomé
The Arctic Ocean has been receiving more of the warm and saline Atlantic Water in the past decades. This water mass enters the Arctic Ocean via two Arctic gateways: the Barents Sea Opening and the Fram Strait. Here, we focus on the fractionation of Atlantic Water at these two gateways using a Lagrangian approach based on satellite-derived geostrophic velocities. Simulated particles are released at 70N at the inner and outer branch of the North Atlantic current system in the Nordic Seas. The trajectories toward the Fram Strait and Barents Sea Opening are found to be largely steered by the bottom topography and there is an indication of an anti-phase relationship in the number of particles reaching the gateways. There is, however, a significant cross-over of particles from the outer branch to the inner branch and into the Barents Sea, which is found to be related to high eddy kinetic energy between the branches. This cross-over may be important for Arctic climate variability.
How to cite: Chafik, L. and Broomé, S.: A satellite-based Lagrangian perspective on Atlantic Water fractionation in the Nordic Seas, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8422, https://doi.org/10.5194/egusphere-egu2020-8422, 2020.
The Arctic Ocean has been receiving more of the warm and saline Atlantic Water in the past decades. This water mass enters the Arctic Ocean via two Arctic gateways: the Barents Sea Opening and the Fram Strait. Here, we focus on the fractionation of Atlantic Water at these two gateways using a Lagrangian approach based on satellite-derived geostrophic velocities. Simulated particles are released at 70N at the inner and outer branch of the North Atlantic current system in the Nordic Seas. The trajectories toward the Fram Strait and Barents Sea Opening are found to be largely steered by the bottom topography and there is an indication of an anti-phase relationship in the number of particles reaching the gateways. There is, however, a significant cross-over of particles from the outer branch to the inner branch and into the Barents Sea, which is found to be related to high eddy kinetic energy between the branches. This cross-over may be important for Arctic climate variability.
How to cite: Chafik, L. and Broomé, S.: A satellite-based Lagrangian perspective on Atlantic Water fractionation in the Nordic Seas, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8422, https://doi.org/10.5194/egusphere-egu2020-8422, 2020.
EGU2020-8690 | Displays | NP6.1 | Highlight
Tracing the thermohaline Conveyor Belt circulation; from the Drake Passage to the Pacific OceanSara Berglund, Kristofer Döös, and Jonas Nycander
This study describes an important pathway of the thermohaline conveyor belt circulation and connects the geographical distribution of water masses with water mass transformation.
In the Southern Ocean, cold and fresh water up-wells to the surface and returns northward, entering the Pacific, Atlantic and Indian Ocean. This reflects an important part of the thermohaline conveyor belt circulation. As the water flows northward, it changes temperature and salinity, and thus density. These changes can be caused either by internal mixing or air-sea interactions.
In this study, Lagrangian trajectories are used to follow the pathway from Drake Passage to the warm Pacific Ocean. Trajectories are started in the Drake Passage, and are ended when they either reach 25$^\circ$C or return to the Drake Passage. The trajectories entering the Pacific Ocean follow the Antarctic circumpolar current and separate then into two pathways. The first enters the Pacific Ocean close to the South American coast and flows along the coast until it reaches 25$^\circ$C close to the equator. The second pathway, which corresponds to most of the total volume transport entering the Pacific, are subducted around 40$^\circ$S. The water then moves westward until it reaches Australia where it turns northward and ultimately joins the equatorial undercurrent.
Along these two pathways, the water changes temperature and salinity, going from cold and fresh to warm and saline. Preliminary results indicate that the water mass transformation for the first pathway are due to air-sea interactions, and internal mixing for the second.
How to cite: Berglund, S., Döös, K., and Nycander, J.: Tracing the thermohaline Conveyor Belt circulation; from the Drake Passage to the Pacific Ocean, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8690, https://doi.org/10.5194/egusphere-egu2020-8690, 2020.
This study describes an important pathway of the thermohaline conveyor belt circulation and connects the geographical distribution of water masses with water mass transformation.
In the Southern Ocean, cold and fresh water up-wells to the surface and returns northward, entering the Pacific, Atlantic and Indian Ocean. This reflects an important part of the thermohaline conveyor belt circulation. As the water flows northward, it changes temperature and salinity, and thus density. These changes can be caused either by internal mixing or air-sea interactions.
In this study, Lagrangian trajectories are used to follow the pathway from Drake Passage to the warm Pacific Ocean. Trajectories are started in the Drake Passage, and are ended when they either reach 25$^\circ$C or return to the Drake Passage. The trajectories entering the Pacific Ocean follow the Antarctic circumpolar current and separate then into two pathways. The first enters the Pacific Ocean close to the South American coast and flows along the coast until it reaches 25$^\circ$C close to the equator. The second pathway, which corresponds to most of the total volume transport entering the Pacific, are subducted around 40$^\circ$S. The water then moves westward until it reaches Australia where it turns northward and ultimately joins the equatorial undercurrent.
Along these two pathways, the water changes temperature and salinity, going from cold and fresh to warm and saline. Preliminary results indicate that the water mass transformation for the first pathway are due to air-sea interactions, and internal mixing for the second.
How to cite: Berglund, S., Döös, K., and Nycander, J.: Tracing the thermohaline Conveyor Belt circulation; from the Drake Passage to the Pacific Ocean, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8690, https://doi.org/10.5194/egusphere-egu2020-8690, 2020.
EGU2020-11496 | Displays | NP6.1
The effects of wind and waves on in-situ surface drift in the Baltic SeaNicole Delpeche-Ellmann, Andrea Giudici, and Tarmo Soomere
Wind and waves often have a strong influence on surface drift, especially in the strongly stratified Baltic Sea. However due to the limitations of wave models and analytical solutions, the quantification of the influence of the waves is a complicated problem. In this study we employ a more observational approach by utilizing one of the longest time series of in-situ surface drifters deployed in the Gulf of Finland, Baltic Sea for the period of 2011−2019. Analysis is performed both qualitatively and quantitatively to understand the effects of the wind and waves on surface drift. The forty-seven in-situ surface drifters utilized were designed to follow the uppermost 2 m layer of currents. In addition, a web-based software (DrifterTrack) was specifically developed for real time data monitoring, data collection, storage and access solution. The wind and wave data were obtained by wave buoys and meteorological stations located in the central part of the gulf.
Several hypothesis tests combined with statistical analysis of drifter trajectories, wind and wave data were utilized for the analysis. Qualitatively the drifter trajectories displayed a variety of shapes and maneuvers, hinting the complexity of the surface drift. Nevertheless, drifter trajectory maps showed for most years a predominance of surface drift towards the east which also coincides with the predominant wind and wave direction. Interestingly the results also suggest that when surface drift towards the west occurred it was generally quicker than the drift to the east. The average current speed was in the range of 0.05−0.15 m/s for approximately 45% of the occurrences. The drifter speed within the range of 0.3−0.5 m/s accounted for approximately 9% of the occurrences. The drifter speed was found to vary between 1.5−2.5 % of the wind speed. Hypothesis tests show that wave heights of >1 m (created by >10 m/s wind speed) have the most significant effect on the drifter speed within the range of 0.15−0.3 m/s. These tests also demonstrated that wind and waves effects are not the only forces influencing strong surface drift in the gulf. Several other processes (e.g. eddies, density gradients, upwellings, downwellings etc.) can substantially contribute to the surface drift.
How to cite: Delpeche-Ellmann, N., Giudici, A., and Soomere, T.: The effects of wind and waves on in-situ surface drift in the Baltic Sea, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11496, https://doi.org/10.5194/egusphere-egu2020-11496, 2020.
Wind and waves often have a strong influence on surface drift, especially in the strongly stratified Baltic Sea. However due to the limitations of wave models and analytical solutions, the quantification of the influence of the waves is a complicated problem. In this study we employ a more observational approach by utilizing one of the longest time series of in-situ surface drifters deployed in the Gulf of Finland, Baltic Sea for the period of 2011−2019. Analysis is performed both qualitatively and quantitatively to understand the effects of the wind and waves on surface drift. The forty-seven in-situ surface drifters utilized were designed to follow the uppermost 2 m layer of currents. In addition, a web-based software (DrifterTrack) was specifically developed for real time data monitoring, data collection, storage and access solution. The wind and wave data were obtained by wave buoys and meteorological stations located in the central part of the gulf.
Several hypothesis tests combined with statistical analysis of drifter trajectories, wind and wave data were utilized for the analysis. Qualitatively the drifter trajectories displayed a variety of shapes and maneuvers, hinting the complexity of the surface drift. Nevertheless, drifter trajectory maps showed for most years a predominance of surface drift towards the east which also coincides with the predominant wind and wave direction. Interestingly the results also suggest that when surface drift towards the west occurred it was generally quicker than the drift to the east. The average current speed was in the range of 0.05−0.15 m/s for approximately 45% of the occurrences. The drifter speed within the range of 0.3−0.5 m/s accounted for approximately 9% of the occurrences. The drifter speed was found to vary between 1.5−2.5 % of the wind speed. Hypothesis tests show that wave heights of >1 m (created by >10 m/s wind speed) have the most significant effect on the drifter speed within the range of 0.15−0.3 m/s. These tests also demonstrated that wind and waves effects are not the only forces influencing strong surface drift in the gulf. Several other processes (e.g. eddies, density gradients, upwellings, downwellings etc.) can substantially contribute to the surface drift.
How to cite: Delpeche-Ellmann, N., Giudici, A., and Soomere, T.: The effects of wind and waves on in-situ surface drift in the Baltic Sea, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11496, https://doi.org/10.5194/egusphere-egu2020-11496, 2020.
EGU2020-14732 | Displays | NP6.1
Relative dispersion in the Nordic Seas - new insights ten years laterInga Monika Koszalka and Joseph LaCasce
The POLEWARD experiment in the Nordic Seas (2007-2009) involved deployment of 150 drifters in the eastern Nordic Seas and has been the first large drifter pair experiment in the ocean (and one of the very few conducted up to date). The experiment yielded nearly 100 drifter pairs with initial separations 2km or less, which allowed us to elucidate several aspects of the relative dispersion (a proxy for tracer spreading and transport) at a basin scale, to quantify the role of mesoscale eddies in surface transport, and to further develop the relevant theoretical and analytical methods through a series of publications. Ten years ago however there were no modeling tools available to carry out a similar numerical Lagrangian study in this region resolving relevant scales of variability.
In this presentation, we will present an update on the relative dispersion of surface drifter pairs in the Nordic Seas, with over 400 pairs available. We will then compare the observed statistics to these derived from Lagrangian simulations (OpenDrift scheme) forced by output from a very high resolution regional ocean model (Regional Ocean Modeling System). The comparison is very favorable pointing to the ability of the ocean model to represent surface eddy stirring processes. We will also show analysis of the regional dispersion regimes using both drifter observations and model simulations, and consider the effect of including vertical motion in the Lagrangian simulations, which impacts their horizontal dispersion. We will also present statistics of the temperature differences on drifters pairs. These are underestimated by the model on daily time scales and deformation scales, which has implications for the model ability to simulate tracer processes on these scales.
How to cite: Koszalka, I. M. and LaCasce, J.: Relative dispersion in the Nordic Seas - new insights ten years later, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-14732, https://doi.org/10.5194/egusphere-egu2020-14732, 2020.
The POLEWARD experiment in the Nordic Seas (2007-2009) involved deployment of 150 drifters in the eastern Nordic Seas and has been the first large drifter pair experiment in the ocean (and one of the very few conducted up to date). The experiment yielded nearly 100 drifter pairs with initial separations 2km or less, which allowed us to elucidate several aspects of the relative dispersion (a proxy for tracer spreading and transport) at a basin scale, to quantify the role of mesoscale eddies in surface transport, and to further develop the relevant theoretical and analytical methods through a series of publications. Ten years ago however there were no modeling tools available to carry out a similar numerical Lagrangian study in this region resolving relevant scales of variability.
In this presentation, we will present an update on the relative dispersion of surface drifter pairs in the Nordic Seas, with over 400 pairs available. We will then compare the observed statistics to these derived from Lagrangian simulations (OpenDrift scheme) forced by output from a very high resolution regional ocean model (Regional Ocean Modeling System). The comparison is very favorable pointing to the ability of the ocean model to represent surface eddy stirring processes. We will also show analysis of the regional dispersion regimes using both drifter observations and model simulations, and consider the effect of including vertical motion in the Lagrangian simulations, which impacts their horizontal dispersion. We will also present statistics of the temperature differences on drifters pairs. These are underestimated by the model on daily time scales and deformation scales, which has implications for the model ability to simulate tracer processes on these scales.
How to cite: Koszalka, I. M. and LaCasce, J.: Relative dispersion in the Nordic Seas - new insights ten years later, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-14732, https://doi.org/10.5194/egusphere-egu2020-14732, 2020.
EGU2020-15825 | Displays | NP6.1
Impacts of meso and submesoscale dynamics on the horizontal dispersion of sinking particles from the surface to the deep oceanLu Wang, Jonathan Gula, Jeremy Collin, and Laurent Memery
Energetic eddy fields generated by meso and submesoscale dynamics induce tridimensional particle transport pathways, which complicate the interpretation of observed Particulate Organic Carbon (POC) fluxes using sediment traps. It is therefore of importance to understand how horizontal dispersion of particles is structured by these dynamics from surface to depth. In this modelling study, we use a Lagrangian method to backtrack sinking particles collected at various depths ranging from 500 m to 4700 m at the PAP (Porcupine Abyssal Plain) site. Particle trajectories are computed using high-resolution simulations of the Regional Ocean Modelling System (ROMS). Our results show that the horizontal distribution of particles with sinking velocities below 100 m d-1 presents a large small-scale heterogeneity. Mesoscale eddies act to define the general structure of particle patches while submesoscale features shape particle distributions through convergence/divergence processes. Distribution patterns of particles tracked from different depths suggest regime shifts of particle dispersion between subsurface layers. To identify and quantify these regimes, we perform 2d experiments at specific depths from 100 m to 4000 m and relate the Lagrangian statistics to the characteristics of the different dynamical regimes identified using vertical profiles of eddy energy and Finite Size Lyapunov Exponents (FSLE) approach.
How to cite: Wang, L., Gula, J., Collin, J., and Memery, L.: Impacts of meso and submesoscale dynamics on the horizontal dispersion of sinking particles from the surface to the deep ocean, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15825, https://doi.org/10.5194/egusphere-egu2020-15825, 2020.
Energetic eddy fields generated by meso and submesoscale dynamics induce tridimensional particle transport pathways, which complicate the interpretation of observed Particulate Organic Carbon (POC) fluxes using sediment traps. It is therefore of importance to understand how horizontal dispersion of particles is structured by these dynamics from surface to depth. In this modelling study, we use a Lagrangian method to backtrack sinking particles collected at various depths ranging from 500 m to 4700 m at the PAP (Porcupine Abyssal Plain) site. Particle trajectories are computed using high-resolution simulations of the Regional Ocean Modelling System (ROMS). Our results show that the horizontal distribution of particles with sinking velocities below 100 m d-1 presents a large small-scale heterogeneity. Mesoscale eddies act to define the general structure of particle patches while submesoscale features shape particle distributions through convergence/divergence processes. Distribution patterns of particles tracked from different depths suggest regime shifts of particle dispersion between subsurface layers. To identify and quantify these regimes, we perform 2d experiments at specific depths from 100 m to 4000 m and relate the Lagrangian statistics to the characteristics of the different dynamical regimes identified using vertical profiles of eddy energy and Finite Size Lyapunov Exponents (FSLE) approach.
How to cite: Wang, L., Gula, J., Collin, J., and Memery, L.: Impacts of meso and submesoscale dynamics on the horizontal dispersion of sinking particles from the surface to the deep ocean, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15825, https://doi.org/10.5194/egusphere-egu2020-15825, 2020.
EGU2020-17793 | Displays | NP6.1 | Highlight
Lagrangian modeling of the active dispersal of juvenile leatherback turtles in the North Atlantic OceanPhilippe Gaspar, Maxime Lalire, Pierrick Giffard, and Tony Candela
It has long been assumed that young sea turtles drift passively with ocean currents. As a consequence, simple Lagrangian models have often been used to investigate the dispersal of various sea turtle populations during their juvenile stage. However, evidence is growing that juvenile sea turtles do not drift purely passively with ocean currents but also display some swimming activity, generally directed towards favorable habitats.
We have thus developed a new Sea Turtle Active Movement Model (STAMM) in which simulated individuals disperse under the combined influence of oceanic currents and swimming movements triggered by the need to find suitable habitats, that is areas with suitable water temperatures and sufficient food. Preferred temperatures and food requirements are modeled to vary with the age (or size) of the simulated individuals.
STAMM is used here to investigate the active dispersal of juvenile leatherback turtles (Dermochelys coriacea) born in French Guiana, a major rookery for the Northwest Atlantic population. Our simulations reveal that:
- While currents broadly shape the dispersal area, habitat-driven movements profoundly structure the spatio-temporal distribution of juveniles within this area. Passive turtles can drift far North in deadly cold waters or concentrate in oligotrophic waters found at the center of the North Atlantic subtropical gyre. On the contrary, actively swimming juveniles tend to concentrate in favorable habitats along the northern boundary of the subtropical gyre and undertake seasonal north-south migrations allowing them to remain in suitable water temperatures.
- Active juveniles ultimately target rich areas of the Eastern Atlantic basin, in particular in the Bay of Biscay, off Galicia, Portugal and Mauritania, and in the western Mediterranean Sea where juvenile leatherbacks are actually observed. These zones are inaccessible to passive turtles.
- Arrival times of the active juveniles in these favorable zones are consistent with the observed sizes of individuals bycaught or stranded in these areas;
All together these results suggest that active habitat-driven swimming movements shall be systematically taken into account to produce realistic simulations of the spatial distribution of sea turtles during their pelagic juvenile stage. This is much needed to help develop effective conservation measures targeting this critical life stage.
How to cite: Gaspar, P., Lalire, M., Giffard, P., and Candela, T.: Lagrangian modeling of the active dispersal of juvenile leatherback turtles in the North Atlantic Ocean, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17793, https://doi.org/10.5194/egusphere-egu2020-17793, 2020.
It has long been assumed that young sea turtles drift passively with ocean currents. As a consequence, simple Lagrangian models have often been used to investigate the dispersal of various sea turtle populations during their juvenile stage. However, evidence is growing that juvenile sea turtles do not drift purely passively with ocean currents but also display some swimming activity, generally directed towards favorable habitats.
We have thus developed a new Sea Turtle Active Movement Model (STAMM) in which simulated individuals disperse under the combined influence of oceanic currents and swimming movements triggered by the need to find suitable habitats, that is areas with suitable water temperatures and sufficient food. Preferred temperatures and food requirements are modeled to vary with the age (or size) of the simulated individuals.
STAMM is used here to investigate the active dispersal of juvenile leatherback turtles (Dermochelys coriacea) born in French Guiana, a major rookery for the Northwest Atlantic population. Our simulations reveal that:
- While currents broadly shape the dispersal area, habitat-driven movements profoundly structure the spatio-temporal distribution of juveniles within this area. Passive turtles can drift far North in deadly cold waters or concentrate in oligotrophic waters found at the center of the North Atlantic subtropical gyre. On the contrary, actively swimming juveniles tend to concentrate in favorable habitats along the northern boundary of the subtropical gyre and undertake seasonal north-south migrations allowing them to remain in suitable water temperatures.
- Active juveniles ultimately target rich areas of the Eastern Atlantic basin, in particular in the Bay of Biscay, off Galicia, Portugal and Mauritania, and in the western Mediterranean Sea where juvenile leatherbacks are actually observed. These zones are inaccessible to passive turtles.
- Arrival times of the active juveniles in these favorable zones are consistent with the observed sizes of individuals bycaught or stranded in these areas;
All together these results suggest that active habitat-driven swimming movements shall be systematically taken into account to produce realistic simulations of the spatial distribution of sea turtles during their pelagic juvenile stage. This is much needed to help develop effective conservation measures targeting this critical life stage.
How to cite: Gaspar, P., Lalire, M., Giffard, P., and Candela, T.: Lagrangian modeling of the active dispersal of juvenile leatherback turtles in the North Atlantic Ocean, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17793, https://doi.org/10.5194/egusphere-egu2020-17793, 2020.
EGU2020-22374 | Displays | NP6.1
Progress on the development of innovative, floating, biodegradable radio- probes for atmospheric monitoring inside warm cloudsMiryam Paredes, Shahbozbek Abdunabiev, Marco Allegretti, Giovanni Perona, Daniela Tordella, Eros Pasero, Flavio Canavero, Andrea Merlone, and Chiara Musacchio
Characterization of clouds is still a challenging task for weather forecasting and climate modeling. This is because clouds depend on interdisciplinary natural processes, ranging from the micrometer scale, where particles and droplets collide, to the thousand-of-meters scale of airflow dynamics. Turbulence has an important role in cloud formation and rain initiation since it helps rain droplets to evolve through coalescence and collision processes. Unfortunately, the effects of turbulence mechanisms are not yet well understood and there remains a need for further clarification.
In an attempt to address these knowledge gaps, this work presents the advances of an experimental method for measuring in-situ the influence of turbulence in cloud formation and producing an infield cloud Lagrangian dataset by means of the development of ultra-light bio- compatible radio-probes. With a target weight of less than 20 grams, these innovative devices are carefully designed to float and passively track small-scale turbulence fluctuations in warm clouds and neighboring air. Each mini radio-probe embeds a set of compact size microprocessors, controllers and sensors for the measurement of atmospheric parameters inside clouds (e.g. velocity, acceleration, vorticity, pressure, temperature, humidity) after been released into the atmosphere. To reach a buoyancy force equal to the weight of the system, the bio balloons containing the electronics are appropriately filled with a mixture of helium gas and air. During the flight, the smart radio-probes acquire, pre-process, store, arrange and transmit the obtained data to different receiving and ground stations located on earth through a dedicated radio transmission link. Due to the radio-probes’ physical constrains and the environmental conditions that can be found inside warm clouds, a power-saving and long-range wireless communication technology has been selected and tested.
The development of the first operational prototypes for both, the radio-probes and the receiving stations, are presented together with results of the first measurement experiments both, in laboratory and field campaign.
How to cite: Paredes, M., Abdunabiev, S., Allegretti, M., Perona, G., Tordella, D., Pasero, E., Canavero, F., Merlone, A., and Musacchio, C.: Progress on the development of innovative, floating, biodegradable radio- probes for atmospheric monitoring inside warm clouds, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22374, https://doi.org/10.5194/egusphere-egu2020-22374, 2020.
Characterization of clouds is still a challenging task for weather forecasting and climate modeling. This is because clouds depend on interdisciplinary natural processes, ranging from the micrometer scale, where particles and droplets collide, to the thousand-of-meters scale of airflow dynamics. Turbulence has an important role in cloud formation and rain initiation since it helps rain droplets to evolve through coalescence and collision processes. Unfortunately, the effects of turbulence mechanisms are not yet well understood and there remains a need for further clarification.
In an attempt to address these knowledge gaps, this work presents the advances of an experimental method for measuring in-situ the influence of turbulence in cloud formation and producing an infield cloud Lagrangian dataset by means of the development of ultra-light bio- compatible radio-probes. With a target weight of less than 20 grams, these innovative devices are carefully designed to float and passively track small-scale turbulence fluctuations in warm clouds and neighboring air. Each mini radio-probe embeds a set of compact size microprocessors, controllers and sensors for the measurement of atmospheric parameters inside clouds (e.g. velocity, acceleration, vorticity, pressure, temperature, humidity) after been released into the atmosphere. To reach a buoyancy force equal to the weight of the system, the bio balloons containing the electronics are appropriately filled with a mixture of helium gas and air. During the flight, the smart radio-probes acquire, pre-process, store, arrange and transmit the obtained data to different receiving and ground stations located on earth through a dedicated radio transmission link. Due to the radio-probes’ physical constrains and the environmental conditions that can be found inside warm clouds, a power-saving and long-range wireless communication technology has been selected and tested.
The development of the first operational prototypes for both, the radio-probes and the receiving stations, are presented together with results of the first measurement experiments both, in laboratory and field campaign.
How to cite: Paredes, M., Abdunabiev, S., Allegretti, M., Perona, G., Tordella, D., Pasero, E., Canavero, F., Merlone, A., and Musacchio, C.: Progress on the development of innovative, floating, biodegradable radio- probes for atmospheric monitoring inside warm clouds, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22374, https://doi.org/10.5194/egusphere-egu2020-22374, 2020.
NP6.2 – Turbulence, magnetic reconnection, shocks and particle acceleration: nonlinear processes in space, laboratory and astrophysical plasmas
EGU2020-18202 | Displays | NP6.2
Modelling plasma turbulence observed by Parker Solar Probe during its first two orbits with hybrid-kinetic simulationsLuca Franci, Alice Giroul, David Burgess, Emanuele Papini, Christopher Chen, Daniele Del Sarto, Simone Landi, Andrea Verdini, and Petr Hellinger
We employ 2D and 3D high-resolution hybrid kinetic simulations of plasma turbulence to explore the physical conditions encountered by the Parker Solar Probe (PSP) spacecraft during its first two orbits, modelling the turbulent cascade self-consistently from large fluid scales down to kinetic scales.
By varying key parameters (e.g., the ion and electron plasma beta, the level of fluctuations with respect to the ambient magnetic field, the injection scale), we explore different plasma conditions. We identify a new kinetic-scale regime with respect to what has previously been found in both hybrid simulations and spacecraft observations of the solar wind and of the near-Earth environment, characterized among other things by a steeper magnetic field spectrum. Our simulations reproduce PSP observations and thus offer the opportunity to investigate the physical mechanism(s) behind such change in the turbulent cascade properties. We discuss our results in the framework of theoretical models of the nonlinear interaction of dispersive wave modes, field-particle interactions, and magnetic reconnection in low-beta plasmas.
We also analyse intermittency, magnetic compressibility, polarization of wave-like fluctuations, and statistics of magnetic reconnection events by means of iterative filters, a new method for the analysis of nonlinear nonstationary signals.
Together with our previous numerical results in quantitative agreement with MMS observations in the Earth’s magnetosheath, our new findings confirm the ability of the hybrid approach to model in-situ observations, which is fundamental for interpreting observational results and for planning future spacecraft missions.
How to cite: Franci, L., Giroul, A., Burgess, D., Papini, E., Chen, C., Del Sarto, D., Landi, S., Verdini, A., and Hellinger, P.: Modelling plasma turbulence observed by Parker Solar Probe during its first two orbits with hybrid-kinetic simulations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18202, https://doi.org/10.5194/egusphere-egu2020-18202, 2020.
We employ 2D and 3D high-resolution hybrid kinetic simulations of plasma turbulence to explore the physical conditions encountered by the Parker Solar Probe (PSP) spacecraft during its first two orbits, modelling the turbulent cascade self-consistently from large fluid scales down to kinetic scales.
By varying key parameters (e.g., the ion and electron plasma beta, the level of fluctuations with respect to the ambient magnetic field, the injection scale), we explore different plasma conditions. We identify a new kinetic-scale regime with respect to what has previously been found in both hybrid simulations and spacecraft observations of the solar wind and of the near-Earth environment, characterized among other things by a steeper magnetic field spectrum. Our simulations reproduce PSP observations and thus offer the opportunity to investigate the physical mechanism(s) behind such change in the turbulent cascade properties. We discuss our results in the framework of theoretical models of the nonlinear interaction of dispersive wave modes, field-particle interactions, and magnetic reconnection in low-beta plasmas.
We also analyse intermittency, magnetic compressibility, polarization of wave-like fluctuations, and statistics of magnetic reconnection events by means of iterative filters, a new method for the analysis of nonlinear nonstationary signals.
Together with our previous numerical results in quantitative agreement with MMS observations in the Earth’s magnetosheath, our new findings confirm the ability of the hybrid approach to model in-situ observations, which is fundamental for interpreting observational results and for planning future spacecraft missions.
How to cite: Franci, L., Giroul, A., Burgess, D., Papini, E., Chen, C., Del Sarto, D., Landi, S., Verdini, A., and Hellinger, P.: Modelling plasma turbulence observed by Parker Solar Probe during its first two orbits with hybrid-kinetic simulations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18202, https://doi.org/10.5194/egusphere-egu2020-18202, 2020.
EGU2020-2440 | Displays | NP6.2
What can Hall-MHD simulations tell us about the transition region in the solar wind proton density spectrum?Victor Montagud-Camps, František Němec, Jana Šafránková, Zdeněk Němeček, Roland Grappin, Andrea Verdini, and Alexander Pitňa
Similarly to the power density spectrum of magnetic field fluctuations in the solar wind, the spectrum of density fluctuations also shows multiple spectral slopes. Both of them present a spectral index varying between –3/2 and –5/3 in the inertial range and close to –2.8 between the proton and electron gyrofrequencies.
Despite these similarities, the spectrum of density fluctuations has a significant difference with respect to the magnetic and velocity fluctuations spectra: it shows a transition region between the inertial and the kinetic ranges with spectral index typically around –1.
We have combined the results of compressible Hall-MHD numerical simulations and measurements of the BMSW instrument onboard Spektr-R satellite to study the possible causes of the flattening in the density spectrum. Both numerical and experimental approaches point towards an important role played by Kinetic Alfvén Waves.
How to cite: Montagud-Camps, V., Němec, F., Šafránková, J., Němeček, Z., Grappin, R., Verdini, A., and Pitňa, A.: What can Hall-MHD simulations tell us about the transition region in the solar wind proton density spectrum?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2440, https://doi.org/10.5194/egusphere-egu2020-2440, 2020.
Similarly to the power density spectrum of magnetic field fluctuations in the solar wind, the spectrum of density fluctuations also shows multiple spectral slopes. Both of them present a spectral index varying between –3/2 and –5/3 in the inertial range and close to –2.8 between the proton and electron gyrofrequencies.
Despite these similarities, the spectrum of density fluctuations has a significant difference with respect to the magnetic and velocity fluctuations spectra: it shows a transition region between the inertial and the kinetic ranges with spectral index typically around –1.
We have combined the results of compressible Hall-MHD numerical simulations and measurements of the BMSW instrument onboard Spektr-R satellite to study the possible causes of the flattening in the density spectrum. Both numerical and experimental approaches point towards an important role played by Kinetic Alfvén Waves.
How to cite: Montagud-Camps, V., Němec, F., Šafránková, J., Němeček, Z., Grappin, R., Verdini, A., and Pitňa, A.: What can Hall-MHD simulations tell us about the transition region in the solar wind proton density spectrum?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2440, https://doi.org/10.5194/egusphere-egu2020-2440, 2020.
EGU2020-13249 | Displays | NP6.2
Statistical Research of the Intermittency and Cascade of Solar Wind Turbulence Based on Analysis of PSP MeasurementsYing Wang, Jiansen He, Die Duan, and Xingyu Zhu
By analyzing the turbulent magnetic field data from PSP, we find that: the solar wind turbulence in the inner heliosphere close to the Sun has formed the transition from multifractal intermittency at MHD scales to monofractal intermittency at kinetic scales. The order-dependent scaling exponent of the multi-order structure function shows a concave profile indicating the multifractal property at MHD scales, while its counterpart at kinetic scales shows a linear trend suggesting the monofractal property. We also find that, the closer to the sun, the more obvious the concave profile of the scaling exponent in the inertial range, which indicates that the multifractal characteristic of the magnetic field turbulence intermittency is also more evident when getting closer to the Sun.
Based on the Castaing description of the probability distribution function(PDF) of the disturbance difference, the key parameters(μ & λ^2) of the Castaing function are estimated as a function of scale. We find that: (1) when close to the sun (R~0.17 AU), the break point of μ is about 0.2 second, and the peak point of λ^2 is about 0.6 second, the two of which are about three times different in scale; (2) when far from the sun (R~0.8 AU), the break point of μ is about 1 second and the peak point of λ^2 is about 3 seconds, the two of which are also about three times different in scale. We also point out that the profiles (including the break/peak position) of both the parameters (μ & λ^2) along with the scale together determine the profile (including the spectral breaks) of the power spectrum.
Following the PP98 model function of incompressible MHD turbulent cascade rate (εZ), we first compared the cascade rate εZ with εB=<δB^3>/τ at the distance close to the sun, we find that the two trends over scales are in good agreement with one another. We therefore suggest that, to some extent (e.g. in the inertial region), εB=<δB^3>/τ can be used as a proxy of the cascade rate εZ. For the first time, by statistical analysis, we obtained that εB satisfies the following relation with the scale and the heliocentric distance: εB=((τ/τ0)^α)((r/r0)^β). In the inertial range, α changes from about -0.5 to about 0.5 as r increases from 0.17 AU to 0.81 AU, and β is about 6.4; in the kenetic range, when r increases from 0.17 AU to 0.25 AU, α keeps at about 2, and β is about 12.8. The εB(τ,r) expression given in this work, is believed to help understanding the transport and cascade processes of solar wind turbulence in the inner heliosphere.
Corresponding author:
Jiansen HE, jshept@pku.edu.cn
Acknowledgements:
We would like to thank the PSP team for providing the data of PSP to the public.
How to cite: Wang, Y., He, J., Duan, D., and Zhu, X.: Statistical Research of the Intermittency and Cascade of Solar Wind Turbulence Based on Analysis of PSP Measurements, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13249, https://doi.org/10.5194/egusphere-egu2020-13249, 2020.
By analyzing the turbulent magnetic field data from PSP, we find that: the solar wind turbulence in the inner heliosphere close to the Sun has formed the transition from multifractal intermittency at MHD scales to monofractal intermittency at kinetic scales. The order-dependent scaling exponent of the multi-order structure function shows a concave profile indicating the multifractal property at MHD scales, while its counterpart at kinetic scales shows a linear trend suggesting the monofractal property. We also find that, the closer to the sun, the more obvious the concave profile of the scaling exponent in the inertial range, which indicates that the multifractal characteristic of the magnetic field turbulence intermittency is also more evident when getting closer to the Sun.
Based on the Castaing description of the probability distribution function(PDF) of the disturbance difference, the key parameters(μ & λ^2) of the Castaing function are estimated as a function of scale. We find that: (1) when close to the sun (R~0.17 AU), the break point of μ is about 0.2 second, and the peak point of λ^2 is about 0.6 second, the two of which are about three times different in scale; (2) when far from the sun (R~0.8 AU), the break point of μ is about 1 second and the peak point of λ^2 is about 3 seconds, the two of which are also about three times different in scale. We also point out that the profiles (including the break/peak position) of both the parameters (μ & λ^2) along with the scale together determine the profile (including the spectral breaks) of the power spectrum.
Following the PP98 model function of incompressible MHD turbulent cascade rate (εZ), we first compared the cascade rate εZ with εB=<δB^3>/τ at the distance close to the sun, we find that the two trends over scales are in good agreement with one another. We therefore suggest that, to some extent (e.g. in the inertial region), εB=<δB^3>/τ can be used as a proxy of the cascade rate εZ. For the first time, by statistical analysis, we obtained that εB satisfies the following relation with the scale and the heliocentric distance: εB=((τ/τ0)^α)((r/r0)^β). In the inertial range, α changes from about -0.5 to about 0.5 as r increases from 0.17 AU to 0.81 AU, and β is about 6.4; in the kenetic range, when r increases from 0.17 AU to 0.25 AU, α keeps at about 2, and β is about 12.8. The εB(τ,r) expression given in this work, is believed to help understanding the transport and cascade processes of solar wind turbulence in the inner heliosphere.
Corresponding author:
Jiansen HE, jshept@pku.edu.cn
Acknowledgements:
We would like to thank the PSP team for providing the data of PSP to the public.
How to cite: Wang, Y., He, J., Duan, D., and Zhu, X.: Statistical Research of the Intermittency and Cascade of Solar Wind Turbulence Based on Analysis of PSP Measurements, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13249, https://doi.org/10.5194/egusphere-egu2020-13249, 2020.
EGU2020-18486 | Displays | NP6.2
Solar Wind Turbulence at Kinetic Scales in the inner HeliosphereOlga Alexandrova, Vamsee Jagarlamudi, Milan Maksimovic, Petr Hellinger, Yuri Shprits, and Andre Mangeney
We study magnetic fluctuations at sub-ion scales and down to sub-electron scales using Helios/SCM measurements in the inner Heliosphere and Cluster/STAFF data at the Earth's orbit. Using these data we test the generality of the kinetic spectrum and we show that it follows the ~k-8/3exp(-kld) law at different radial distances from the Sun (k being a wavenumber). We show as well that the dissipation scale ld correlates well with the electron Larmor radius ρe at 0.3 AU and at 1 AU. Then, in the time domain, at 1 AU, using the wavelet transform, we study the nature of magnetic fluctuations, which form the kinetic spectrum. It appears, that the spectrum is dominated by non-linear coherent structures in the form of magnetic vortices with the smallest resolved scale of the order of ρe. Finally, we comparer our results with measurements of the Parker Solar Probe/FIELDS and, hopefully, of the Solar Orbiter/RPW in the inner Heliosphere.
How to cite: Alexandrova, O., Jagarlamudi, V., Maksimovic, M., Hellinger, P., Shprits, Y., and Mangeney, A.: Solar Wind Turbulence at Kinetic Scales in the inner Heliosphere, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18486, https://doi.org/10.5194/egusphere-egu2020-18486, 2020.
We study magnetic fluctuations at sub-ion scales and down to sub-electron scales using Helios/SCM measurements in the inner Heliosphere and Cluster/STAFF data at the Earth's orbit. Using these data we test the generality of the kinetic spectrum and we show that it follows the ~k-8/3exp(-kld) law at different radial distances from the Sun (k being a wavenumber). We show as well that the dissipation scale ld correlates well with the electron Larmor radius ρe at 0.3 AU and at 1 AU. Then, in the time domain, at 1 AU, using the wavelet transform, we study the nature of magnetic fluctuations, which form the kinetic spectrum. It appears, that the spectrum is dominated by non-linear coherent structures in the form of magnetic vortices with the smallest resolved scale of the order of ρe. Finally, we comparer our results with measurements of the Parker Solar Probe/FIELDS and, hopefully, of the Solar Orbiter/RPW in the inner Heliosphere.
How to cite: Alexandrova, O., Jagarlamudi, V., Maksimovic, M., Hellinger, P., Shprits, Y., and Mangeney, A.: Solar Wind Turbulence at Kinetic Scales in the inner Heliosphere, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18486, https://doi.org/10.5194/egusphere-egu2020-18486, 2020.
EGU2020-18261 | Displays | NP6.2
Electric Field Turbulence in the Solar Wind from MHD down to Electron Scales: Artemis ObservationsChadi Salem, John Bonnell, Jordan Huang, Elizabeth Hanson, Christopher Chaston, Kristopher Klein, Luca Franci, Daniel Verscharen, and Vadim Roytershteyn
Recent observational and theoretical work on solar wind turbulence and dissipation suggests that kinetic-scale fluctuations are both heating and isotropizing the solar wind during transit to 1 AU. The nature of these fluctuations and associated heating processes are poorly understood. Whatever the dissipative process that links the fields and particles - Landau damping, cyclotron damping, stochastic heating, or energization through coherent structures - heating and acceleration of ions and electrons occurs because of electric field fluctuations. The dissipation due to the fluctuations depends intimately upon the temporal and spatial variations of those fluctuations in the plasma frame. In order to derive that distribution in the plasma frame, one must also use magnetic field and density fluctuations, in addition to electric field fluctuations, as measured in the spacecraft frame (s/c) to help constrain the type of fluctuation and dissipation mechanisms that are at play.
We present here an analysis of electromagnetic fluctuations in the solar wind from MHD scales down to electron scales based on data from the Artemis spacecraft at 1 AU. We focus on a few time intervals of pristine solar wind, covering a reasonable range of solar wind properties (temperature ratios and anisotropies; plasma beta; and solar wind speed). We analyze magnetic, electric field, and density fluctuations from the 0.01 Hz (well in the inertial range) up to 1 kHz. We compute parameters such as the electric to magnetic field ratio, the magnetic compressibility, magnetic helicity, compressibility and other relevant quantities in order to diagnose the nature of the fluctuations at those scales between the ion and electron cyclotron frequencies, extracting information on the dominant modes composing the fluctuations. We also use the linear Vlasov-Maxwell solver, PLUME, to determine the various relevant modes of the plasma with parameters from the observed solar wind intervals. We discuss the results and the relevant modes as well as the major differences between our results in the solar wind and results in the magnetosheath.
How to cite: Salem, C., Bonnell, J., Huang, J., Hanson, E., Chaston, C., Klein, K., Franci, L., Verscharen, D., and Roytershteyn, V.: Electric Field Turbulence in the Solar Wind from MHD down to Electron Scales: Artemis Observations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18261, https://doi.org/10.5194/egusphere-egu2020-18261, 2020.
Recent observational and theoretical work on solar wind turbulence and dissipation suggests that kinetic-scale fluctuations are both heating and isotropizing the solar wind during transit to 1 AU. The nature of these fluctuations and associated heating processes are poorly understood. Whatever the dissipative process that links the fields and particles - Landau damping, cyclotron damping, stochastic heating, or energization through coherent structures - heating and acceleration of ions and electrons occurs because of electric field fluctuations. The dissipation due to the fluctuations depends intimately upon the temporal and spatial variations of those fluctuations in the plasma frame. In order to derive that distribution in the plasma frame, one must also use magnetic field and density fluctuations, in addition to electric field fluctuations, as measured in the spacecraft frame (s/c) to help constrain the type of fluctuation and dissipation mechanisms that are at play.
We present here an analysis of electromagnetic fluctuations in the solar wind from MHD scales down to electron scales based on data from the Artemis spacecraft at 1 AU. We focus on a few time intervals of pristine solar wind, covering a reasonable range of solar wind properties (temperature ratios and anisotropies; plasma beta; and solar wind speed). We analyze magnetic, electric field, and density fluctuations from the 0.01 Hz (well in the inertial range) up to 1 kHz. We compute parameters such as the electric to magnetic field ratio, the magnetic compressibility, magnetic helicity, compressibility and other relevant quantities in order to diagnose the nature of the fluctuations at those scales between the ion and electron cyclotron frequencies, extracting information on the dominant modes composing the fluctuations. We also use the linear Vlasov-Maxwell solver, PLUME, to determine the various relevant modes of the plasma with parameters from the observed solar wind intervals. We discuss the results and the relevant modes as well as the major differences between our results in the solar wind and results in the magnetosheath.
How to cite: Salem, C., Bonnell, J., Huang, J., Hanson, E., Chaston, C., Klein, K., Franci, L., Verscharen, D., and Roytershteyn, V.: Electric Field Turbulence in the Solar Wind from MHD down to Electron Scales: Artemis Observations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18261, https://doi.org/10.5194/egusphere-egu2020-18261, 2020.
EGU2020-6815 | Displays | NP6.2
Sub-ion scale measurements of compressible turbulence in the solar wind MMS ObservationsOwen Roberts, Rumi Nakamura, Yasuhito Narita, Justin Holmes, Zoltan Voros, Christoph Lhotka, and Jessica Thwaites
Compressible plasma turbulence is investigated at sub ion scales using both the Fast Plasma Investigation instrument on the Magnetospheric MultiScale mission as well as using calibrated spacecraft potential. The data from FPI allow inertial and a small region of sub-ion scales to be investigated before the instrumental noise becomes significant near 3Hz. In this work we give a detailed description of the spacecraft potential and how it is calibrated such that it can be used the measure the electron density. The key advantage of using the calibrated spacecraft potential is that a much higher time resolution is possible when compared to the direct measurement. This allows a measurement down to 40Hz for a measurement of the electron density. This is an improvement of an additional decade in scale. Using a one hour interval of solar wind burst mode data the power spectrum of the density fluctuations is measured from the inertial range to the sub ion range. At inertial scales the density spectrum shows similarities with the magnetic field power spectrum with a characteristic Kolmogorov like power law. In between the ion inertial and kinetic scales there is a brief flattening in the spectra before steepening in the sub ion range to a spectral index comparable to the trace magnetic field fluctuations. The morphology if the density spectra can be explained by either a cascade of Alfv\'en waves and slow waves at large scales and kinetic Alfv\'en waves at sub ion scales, or by the presence of the hall effect. Using electric field measurements the two hypotheses are tested.
How to cite: Roberts, O., Nakamura, R., Narita, Y., Holmes, J., Voros, Z., Lhotka, C., and Thwaites, J.: Sub-ion scale measurements of compressible turbulence in the solar wind MMS Observations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6815, https://doi.org/10.5194/egusphere-egu2020-6815, 2020.
Compressible plasma turbulence is investigated at sub ion scales using both the Fast Plasma Investigation instrument on the Magnetospheric MultiScale mission as well as using calibrated spacecraft potential. The data from FPI allow inertial and a small region of sub-ion scales to be investigated before the instrumental noise becomes significant near 3Hz. In this work we give a detailed description of the spacecraft potential and how it is calibrated such that it can be used the measure the electron density. The key advantage of using the calibrated spacecraft potential is that a much higher time resolution is possible when compared to the direct measurement. This allows a measurement down to 40Hz for a measurement of the electron density. This is an improvement of an additional decade in scale. Using a one hour interval of solar wind burst mode data the power spectrum of the density fluctuations is measured from the inertial range to the sub ion range. At inertial scales the density spectrum shows similarities with the magnetic field power spectrum with a characteristic Kolmogorov like power law. In between the ion inertial and kinetic scales there is a brief flattening in the spectra before steepening in the sub ion range to a spectral index comparable to the trace magnetic field fluctuations. The morphology if the density spectra can be explained by either a cascade of Alfv\'en waves and slow waves at large scales and kinetic Alfv\'en waves at sub ion scales, or by the presence of the hall effect. Using electric field measurements the two hypotheses are tested.
How to cite: Roberts, O., Nakamura, R., Narita, Y., Holmes, J., Voros, Z., Lhotka, C., and Thwaites, J.: Sub-ion scale measurements of compressible turbulence in the solar wind MMS Observations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6815, https://doi.org/10.5194/egusphere-egu2020-6815, 2020.
EGU2020-6959 | Displays | NP6.2
Identification of magnetosonic modes in Galactic turbulenceHuirong Yan, Heshou Zhang, Alexey Chepurnov, and Kirit Makwana
The multiphase nature of astrophysical environment and diversity of driving mechanisms give rise to spatial variation of turbulence properties. Nevertheless, the employed model of magneto-hydrodynamic turbulence is often oversimplified being assumed to be only Alfvenic due to a lack of observational evidence. Here we report the employment of our novel method, the signature from polarization analysis (SPA), on unveiling the plasma modes in interstellar turbulence. The method is based on the statistical properties of the Stokes parameters (I,Q,U) of the synchrotron radiation polarization. The application of SPA on the synchrotron polarization data from the Galactic medium has for the first time revealed that interstellar turbulence is magnetized with different plasma modes composition, pinpointing the necessity to account for plasma property of turbulence, which is neither hydrodynamic nor purely Alfvenic, but depends on local physical conditions, particularly the driving process. A highly promising research field is foreseen to unroll with ample results anticipated from the advanced analysis of high resolution synchrotron polarization data and multiple wavelength comparison, that will shed light on the role of turbulence in various physical processes.
How to cite: Yan, H., Zhang, H., Chepurnov, A., and Makwana, K.: Identification of magnetosonic modes in Galactic turbulence, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6959, https://doi.org/10.5194/egusphere-egu2020-6959, 2020.
The multiphase nature of astrophysical environment and diversity of driving mechanisms give rise to spatial variation of turbulence properties. Nevertheless, the employed model of magneto-hydrodynamic turbulence is often oversimplified being assumed to be only Alfvenic due to a lack of observational evidence. Here we report the employment of our novel method, the signature from polarization analysis (SPA), on unveiling the plasma modes in interstellar turbulence. The method is based on the statistical properties of the Stokes parameters (I,Q,U) of the synchrotron radiation polarization. The application of SPA on the synchrotron polarization data from the Galactic medium has for the first time revealed that interstellar turbulence is magnetized with different plasma modes composition, pinpointing the necessity to account for plasma property of turbulence, which is neither hydrodynamic nor purely Alfvenic, but depends on local physical conditions, particularly the driving process. A highly promising research field is foreseen to unroll with ample results anticipated from the advanced analysis of high resolution synchrotron polarization data and multiple wavelength comparison, that will shed light on the role of turbulence in various physical processes.
How to cite: Yan, H., Zhang, H., Chepurnov, A., and Makwana, K.: Identification of magnetosonic modes in Galactic turbulence, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6959, https://doi.org/10.5194/egusphere-egu2020-6959, 2020.
EGU2020-12160 | Displays | NP6.2
Using machine learning to identify magnetic reconnection in two-dimensional simulationsAndong Hu, Jannis Teunissen, Manuela Sisti, Francesco Califano, Jérémy Dargent, Giorgio Pedrazzi, and Francesca Delli Ponti
How to cite: Hu, A., Teunissen, J., Sisti, M., Califano, F., Dargent, J., Pedrazzi, G., and Ponti, F. D.: Using machine learning to identify magnetic reconnection in two-dimensional simulations , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12160, https://doi.org/10.5194/egusphere-egu2020-12160, 2020.
How to cite: Hu, A., Teunissen, J., Sisti, M., Califano, F., Dargent, J., Pedrazzi, G., and Ponti, F. D.: Using machine learning to identify magnetic reconnection in two-dimensional simulations , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12160, https://doi.org/10.5194/egusphere-egu2020-12160, 2020.
EGU2020-6883 | Displays | NP6.2
Fast Magnetic Reconnection by Turbulence with High Landquist NumberLiping Yang, Hui Li, Fan Guo, Xiancan Li, Shengtai Li, Lei Zhang, Jiansen He, and Xueshang Feng
We report detailed numerical studies of magnetic reconnection in high-Lundquist-number, turbulent plasma by means of a three-dimensional (3D) resistive magnetohydrodynamics model. It is found that although turbulence is pre-existing, magnetic fields still restructure themselves to shape many X-points with evident mean inflow/outflow as well as the hierarchically generated magnetic flux ropes (plasmoids in 2D) with twist field lines. Moreover, the turbulence facilitates magnetic reconnections, and makes the normalized global reconnection rate reach ∼ 0.02 − 0.1, corresponding to turbulence level from very low to high and magnetic energy release from feeble to violent. The rate is nearly independent on the Lundquist number, and thus the fast turbulent reconnection occurs. A stochastic separation of the reconnected magnetic field lines with large opening angles follows a super-diffusion, indicating the broadening of outflow regions owing to the turbulence. These findings manifest that with the high Lundquist numbers (S ≥ 10^4), the 3D reconnection is turbulent and fast.
How to cite: Yang, L., Li, H., Guo, F., Li, X., Li, S., Zhang, L., He, J., and Feng, X.: Fast Magnetic Reconnection by Turbulence with High Landquist Number, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6883, https://doi.org/10.5194/egusphere-egu2020-6883, 2020.
We report detailed numerical studies of magnetic reconnection in high-Lundquist-number, turbulent plasma by means of a three-dimensional (3D) resistive magnetohydrodynamics model. It is found that although turbulence is pre-existing, magnetic fields still restructure themselves to shape many X-points with evident mean inflow/outflow as well as the hierarchically generated magnetic flux ropes (plasmoids in 2D) with twist field lines. Moreover, the turbulence facilitates magnetic reconnections, and makes the normalized global reconnection rate reach ∼ 0.02 − 0.1, corresponding to turbulence level from very low to high and magnetic energy release from feeble to violent. The rate is nearly independent on the Lundquist number, and thus the fast turbulent reconnection occurs. A stochastic separation of the reconnected magnetic field lines with large opening angles follows a super-diffusion, indicating the broadening of outflow regions owing to the turbulence. These findings manifest that with the high Lundquist numbers (S ≥ 10^4), the 3D reconnection is turbulent and fast.
How to cite: Yang, L., Li, H., Guo, F., Li, X., Li, S., Zhang, L., He, J., and Feng, X.: Fast Magnetic Reconnection by Turbulence with High Landquist Number, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6883, https://doi.org/10.5194/egusphere-egu2020-6883, 2020.
EGU2020-3234 | Displays | NP6.2
Flows in the MagnetotailRaymond Walker, Giovanni Lapenta, Mostafa El-Alaoui, Jean Berchem, Robert Richard, and David Schriver
Magnetic reconnection leads to fast streaming of electrons and ions away from the reconnection site. We have used an implicit particle-in-cell simulation (iPic3D) embedded within a global MHD simulation of the solar wind and magnetosphere interaction to investigate the evolution of electrons and ion flows in the magnetotail. We first ran the MHD simulation driven by solar wind observations and then used the MHD results to set the initial and boundary conditions for the PIC simulation. Then we let the PIC state evolve and investigated the electron and ion motion. Within a few seconds of the onset of reconnection, electrons near the reconnection site stream earthward at 500-700km/s while the ions move at less than 100 km/s. For electrons, magnetic trapping occurs very close to the reconnection site and they move mostly in the XGSM direction at the E×B/B2 velocity. Ion trapping occurs several Earth radii from the reconnection site about 100 s after the start of reconnection where both the electrons and ions move together at ~E×B/B2 velocity. Although the particles are moving at the E × B/B2 velocity, they are in a state defined by the kinetic physics not the state that exists in the MHD simulation.
How to cite: Walker, R., Lapenta, G., El-Alaoui, M., Berchem, J., Richard, R., and Schriver, D.: Flows in the Magnetotail, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3234, https://doi.org/10.5194/egusphere-egu2020-3234, 2020.
Magnetic reconnection leads to fast streaming of electrons and ions away from the reconnection site. We have used an implicit particle-in-cell simulation (iPic3D) embedded within a global MHD simulation of the solar wind and magnetosphere interaction to investigate the evolution of electrons and ion flows in the magnetotail. We first ran the MHD simulation driven by solar wind observations and then used the MHD results to set the initial and boundary conditions for the PIC simulation. Then we let the PIC state evolve and investigated the electron and ion motion. Within a few seconds of the onset of reconnection, electrons near the reconnection site stream earthward at 500-700km/s while the ions move at less than 100 km/s. For electrons, magnetic trapping occurs very close to the reconnection site and they move mostly in the XGSM direction at the E×B/B2 velocity. Ion trapping occurs several Earth radii from the reconnection site about 100 s after the start of reconnection where both the electrons and ions move together at ~E×B/B2 velocity. Although the particles are moving at the E × B/B2 velocity, they are in a state defined by the kinetic physics not the state that exists in the MHD simulation.
How to cite: Walker, R., Lapenta, G., El-Alaoui, M., Berchem, J., Richard, R., and Schriver, D.: Flows in the Magnetotail, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3234, https://doi.org/10.5194/egusphere-egu2020-3234, 2020.
EGU2020-22174 | Displays | NP6.2
Spontaneous whistler-cyclotron fluctuations of thermal and non-thermal electron distributions.Pablo S Moya, Daniel Hermosilla, Rodrigo López, Marian Lazar, and Stefaan Poedts
Observed particle distributions in space plasmas usually exhibit a variety of non-equilibrium features in the form of temperature anisotropies, suprathermal tails, field aligned beams, etc. The departure from thermal equilibrium provides a source for spontaneous emissions of electromagnetic fluctuations, such as whistler fluctuations at the electron scales. Analysis of these fluctuations provides relevant information about the plasma state and its macroscopic properties. Here we present a comparative analysis of spontaneous fluctuations in plasmas composed by thermal and non-thermal electron distributions. We compare 1.5D PIC simulations of a finite temperature isotropic magnetized electron–proton plasma modeled with Maxwellian and different kappa velocity distributions. Our results suggest a strong dependence between the shape of the velocity distribution function and the spontaneous magnetic fluctuations wave spectrum. This feature may be used as a proxy to identify the nature of electron populations in space plasmas at locations where direct in-situ measurements of particle fluxes are not available.
How to cite: Moya, P. S., Hermosilla, D., López, R., Lazar, M., and Poedts, S.: Spontaneous whistler-cyclotron fluctuations of thermal and non-thermal electron distributions., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22174, https://doi.org/10.5194/egusphere-egu2020-22174, 2020.
Observed particle distributions in space plasmas usually exhibit a variety of non-equilibrium features in the form of temperature anisotropies, suprathermal tails, field aligned beams, etc. The departure from thermal equilibrium provides a source for spontaneous emissions of electromagnetic fluctuations, such as whistler fluctuations at the electron scales. Analysis of these fluctuations provides relevant information about the plasma state and its macroscopic properties. Here we present a comparative analysis of spontaneous fluctuations in plasmas composed by thermal and non-thermal electron distributions. We compare 1.5D PIC simulations of a finite temperature isotropic magnetized electron–proton plasma modeled with Maxwellian and different kappa velocity distributions. Our results suggest a strong dependence between the shape of the velocity distribution function and the spontaneous magnetic fluctuations wave spectrum. This feature may be used as a proxy to identify the nature of electron populations in space plasmas at locations where direct in-situ measurements of particle fluxes are not available.
How to cite: Moya, P. S., Hermosilla, D., López, R., Lazar, M., and Poedts, S.: Spontaneous whistler-cyclotron fluctuations of thermal and non-thermal electron distributions., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22174, https://doi.org/10.5194/egusphere-egu2020-22174, 2020.
EGU2020-17128 | Displays | NP6.2
Direct Measurement of Excitation and Growth of Large Amplitude Cyclotron Waves by Reflected Ion Beams in Front of ShockJiansen He, Chuanpeng Hou, Xingyu Zhu, Qiaowen Luo, Daniel Verscharen, and Jinsong Zhao
Wave-particle interaction plays a critical role in producing the newborn waves/turbulence in the foreshock region in front of supercritical shock, which is prevalent in the heliosphere. It has been a long-lasting goal to catch and witness the excitation and growth of waves/turbulence by identifying the ongoing process of wave-particle interaction. This goal cannot be fulfilled until the arrival of the MMS’s era, during which we can simultaneously measure the electromagnetic fields and particle phase space densities with the unprecedented data quality. By surveying the data of burst mode, we are lucky to find some good examples illustrating the clear signals of wave activities in front of the shock. The active waves are diagnosed to be right-handed cyclotron waves, being highly circularly polarized and rotating right-handed about the background magnetic field vector. The waves are large amplitude with dB being greatly dominant over B0, or in other words, almost the whole magnetic field vector is involved in the circular rotation. Furthermore, we investigate the growth evolution of the large-amplitude cyclotron waves by calculating the spectrum of dJ.dE and its ratio to the electromagnetic energy spectrum. As far as we know, it is the first time to provide the spectrum of growth rate from in-situ measurements. Interestingly, we find that the contribution to the growth rate spectrum mainly comes from dJe,perp·dEperp rather than dJe,para·dEpara or dJi·dE. Although the eigen mode to couple the oscillating electromagnetic field is the electron bulk oscillation, the ultimate free energy to make the eigen mode unstable comes from the ion beams, which are reflected from the shock. The dynamics of 3D phase space densities for both ion and electron species are also studied in detail together with the fluctuating electromagnetic field, demonstrating the ongoing energy conversion during the wave-particle process.
How to cite: He, J., Hou, C., Zhu, X., Luo, Q., Verscharen, D., and Zhao, J.: Direct Measurement of Excitation and Growth of Large Amplitude Cyclotron Waves by Reflected Ion Beams in Front of Shock, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17128, https://doi.org/10.5194/egusphere-egu2020-17128, 2020.
Wave-particle interaction plays a critical role in producing the newborn waves/turbulence in the foreshock region in front of supercritical shock, which is prevalent in the heliosphere. It has been a long-lasting goal to catch and witness the excitation and growth of waves/turbulence by identifying the ongoing process of wave-particle interaction. This goal cannot be fulfilled until the arrival of the MMS’s era, during which we can simultaneously measure the electromagnetic fields and particle phase space densities with the unprecedented data quality. By surveying the data of burst mode, we are lucky to find some good examples illustrating the clear signals of wave activities in front of the shock. The active waves are diagnosed to be right-handed cyclotron waves, being highly circularly polarized and rotating right-handed about the background magnetic field vector. The waves are large amplitude with dB being greatly dominant over B0, or in other words, almost the whole magnetic field vector is involved in the circular rotation. Furthermore, we investigate the growth evolution of the large-amplitude cyclotron waves by calculating the spectrum of dJ.dE and its ratio to the electromagnetic energy spectrum. As far as we know, it is the first time to provide the spectrum of growth rate from in-situ measurements. Interestingly, we find that the contribution to the growth rate spectrum mainly comes from dJe,perp·dEperp rather than dJe,para·dEpara or dJi·dE. Although the eigen mode to couple the oscillating electromagnetic field is the electron bulk oscillation, the ultimate free energy to make the eigen mode unstable comes from the ion beams, which are reflected from the shock. The dynamics of 3D phase space densities for both ion and electron species are also studied in detail together with the fluctuating electromagnetic field, demonstrating the ongoing energy conversion during the wave-particle process.
How to cite: He, J., Hou, C., Zhu, X., Luo, Q., Verscharen, D., and Zhao, J.: Direct Measurement of Excitation and Growth of Large Amplitude Cyclotron Waves by Reflected Ion Beams in Front of Shock, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17128, https://doi.org/10.5194/egusphere-egu2020-17128, 2020.
EGU2020-13180 | Displays | NP6.2
The role of turbulence strength on the acceleration of transrelativistic electronsDomenico Trotta, Luca Franci, David Burgess, Petr Hellinger, and Joe Giacalone
Energetic particles are widely observed in many astrophysical systems, but the physical mechanisms responsible for their acceleration are not yet fully understood. We address the interaction of suprathermal, transrelativistic electrons with plasma turbulence at ion and sub-ion scales using a combination of hybrid particle-in-cell and test particle simulations. First, we present results of simulations with different turbulence amplitude. Two different mechanisms for electron energisation are identified: one is consistent with the picture of stochastic acceleration in turbulence, yielding to moderate electron energisation, while the other one involves electron trapping in turbulent structures, resulting in an efficient and fast electron energisation. The latter is observed to be active only for certain combinations of turbulence amplitude and electron initial energy. Furthermore, varying the injection scale, we explore the importance of the size of turbulent magnetic structures and of the nonlinear time associated to their dynamical evolution on electron acceleration. These results have important implications for electron acceleration in a wide range of space and astrophysical systems.
How to cite: Trotta, D., Franci, L., Burgess, D., Hellinger, P., and Giacalone, J.: The role of turbulence strength on the acceleration of transrelativistic electrons, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13180, https://doi.org/10.5194/egusphere-egu2020-13180, 2020.
Energetic particles are widely observed in many astrophysical systems, but the physical mechanisms responsible for their acceleration are not yet fully understood. We address the interaction of suprathermal, transrelativistic electrons with plasma turbulence at ion and sub-ion scales using a combination of hybrid particle-in-cell and test particle simulations. First, we present results of simulations with different turbulence amplitude. Two different mechanisms for electron energisation are identified: one is consistent with the picture of stochastic acceleration in turbulence, yielding to moderate electron energisation, while the other one involves electron trapping in turbulent structures, resulting in an efficient and fast electron energisation. The latter is observed to be active only for certain combinations of turbulence amplitude and electron initial energy. Furthermore, varying the injection scale, we explore the importance of the size of turbulent magnetic structures and of the nonlinear time associated to their dynamical evolution on electron acceleration. These results have important implications for electron acceleration in a wide range of space and astrophysical systems.
How to cite: Trotta, D., Franci, L., Burgess, D., Hellinger, P., and Giacalone, J.: The role of turbulence strength on the acceleration of transrelativistic electrons, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13180, https://doi.org/10.5194/egusphere-egu2020-13180, 2020.
EGU2020-11522 | Displays | NP6.2
Magnetoclinicity: Density variance effects in large-scale instability in magnetohydrodynamic turbulenceNobumitsu Yokoi
In the presence of strong compressibility an oblique configuration between the mean density gradient and magnetic field contributes to the electromotive force [1,2]. This effect can be called “magnetoclinicity” and may contribute to the formation of large-scale magnetic-field structure in compressible magnetohydrodynamic (MHD) turbulence. With the aid of the multiple-scale direct-interaction approximation (Multi-Scale DIA), a combination of the DIA and multiple-scale analysis, analytical expressions of the turbulent correlations (turbulent electromotive force, turbulent mass flux, turbulent heat flux, Reynolds stress, turbulent Maxwell stress, etc.) are obtained for the compressible MHD turbulence. Utilizing these analytical results, a large-scale instability of the strongly compressible MHD turbulence is investigated. An analysis into normal modes of the periodic plane waves is performed to get a dispersion relation of the instability modes [3]. It is shown that, depending on the mean density configuration, the inhomogeneity of the mean density variation coupled with the density variance <ρ'2> (ρ': density fluctuation, <...>: average) leads to a finite growth of the mean magnetic disturbance at large scales. This magnetoclinicity effect counter-balance to the turbulent magnetic diffusivity, and contribute to the formation of large-scale magnetic fields. This magnetoclinicity effect is expected to play essential roles in global structure formation in strongly compressible plasma turbulence.
Reference
[1] N. Yokoi, “Electromotive force in strongly compressible magnetohydrodynamic turbulence,” J. Plasma Physics, 84, 735840501, pp.1-26 (2018).
[2] N. Yokoi, “Mass and internal-energy transports in strongly compressible magnetohydrodynamic turbulence,” J. Plasma Physics, 84, 775840603, pp.1-30 (2018).
[3] S. Chandrasekhar, Hydrodynamic and Hydromagnetic Stability (Oxford University Press, 1961).
How to cite: Yokoi, N.: Magnetoclinicity: Density variance effects in large-scale instability in magnetohydrodynamic turbulence, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11522, https://doi.org/10.5194/egusphere-egu2020-11522, 2020.
In the presence of strong compressibility an oblique configuration between the mean density gradient and magnetic field contributes to the electromotive force [1,2]. This effect can be called “magnetoclinicity” and may contribute to the formation of large-scale magnetic-field structure in compressible magnetohydrodynamic (MHD) turbulence. With the aid of the multiple-scale direct-interaction approximation (Multi-Scale DIA), a combination of the DIA and multiple-scale analysis, analytical expressions of the turbulent correlations (turbulent electromotive force, turbulent mass flux, turbulent heat flux, Reynolds stress, turbulent Maxwell stress, etc.) are obtained for the compressible MHD turbulence. Utilizing these analytical results, a large-scale instability of the strongly compressible MHD turbulence is investigated. An analysis into normal modes of the periodic plane waves is performed to get a dispersion relation of the instability modes [3]. It is shown that, depending on the mean density configuration, the inhomogeneity of the mean density variation coupled with the density variance <ρ'2> (ρ': density fluctuation, <...>: average) leads to a finite growth of the mean magnetic disturbance at large scales. This magnetoclinicity effect counter-balance to the turbulent magnetic diffusivity, and contribute to the formation of large-scale magnetic fields. This magnetoclinicity effect is expected to play essential roles in global structure formation in strongly compressible plasma turbulence.
Reference
[1] N. Yokoi, “Electromotive force in strongly compressible magnetohydrodynamic turbulence,” J. Plasma Physics, 84, 735840501, pp.1-26 (2018).
[2] N. Yokoi, “Mass and internal-energy transports in strongly compressible magnetohydrodynamic turbulence,” J. Plasma Physics, 84, 775840603, pp.1-30 (2018).
[3] S. Chandrasekhar, Hydrodynamic and Hydromagnetic Stability (Oxford University Press, 1961).
How to cite: Yokoi, N.: Magnetoclinicity: Density variance effects in large-scale instability in magnetohydrodynamic turbulence, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11522, https://doi.org/10.5194/egusphere-egu2020-11522, 2020.
EGU2020-2738 | Displays | NP6.2
Solar wind temperature anisotropy and its influence on the spectrum of turbulenceAlexander Pitňa, Jana Šafránkova, and Zdeněk Němeček
Nearly collisionless solar wind plasma originating in the solar corona is a turbulent medium. The energy within large scale fluctuations is continuously transferred into smaller scales and it eventually reaches scales at which it is converted into a random particle motion, thus heating the plasma. Although the processes that take place within this complex system have been studied for decades, many questions remain unresolved. The power spectra of the fluctuating fields of the magnetic field, bulk velocity, and ion density were studied extensively; however, the spectrum of the thermal velocity is seldom reported and/or discussed. In this paper, we address the difficulty of estimating its power spectrum. We analyze high-cadence (31 ms) thermal velocity measurements of the BMSW instrument onboard the Spektr-R spacecraft and the SWE instrument onboard the Wind spacecraft. We discuss the role of the proton temperature anisotropy (parallel/perpendicular) and its influence on the shape of the power spectra in the inertial range of turbulence.
How to cite: Pitňa, A., Šafránkova, J., and Němeček, Z.: Solar wind temperature anisotropy and its influence on the spectrum of turbulence, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2738, https://doi.org/10.5194/egusphere-egu2020-2738, 2020.
Nearly collisionless solar wind plasma originating in the solar corona is a turbulent medium. The energy within large scale fluctuations is continuously transferred into smaller scales and it eventually reaches scales at which it is converted into a random particle motion, thus heating the plasma. Although the processes that take place within this complex system have been studied for decades, many questions remain unresolved. The power spectra of the fluctuating fields of the magnetic field, bulk velocity, and ion density were studied extensively; however, the spectrum of the thermal velocity is seldom reported and/or discussed. In this paper, we address the difficulty of estimating its power spectrum. We analyze high-cadence (31 ms) thermal velocity measurements of the BMSW instrument onboard the Spektr-R spacecraft and the SWE instrument onboard the Wind spacecraft. We discuss the role of the proton temperature anisotropy (parallel/perpendicular) and its influence on the shape of the power spectra in the inertial range of turbulence.
How to cite: Pitňa, A., Šafránkova, J., and Němeček, Z.: Solar wind temperature anisotropy and its influence on the spectrum of turbulence, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2738, https://doi.org/10.5194/egusphere-egu2020-2738, 2020.
EGU2020-2742 | Displays | NP6.2
Relations of velocity and magnetic field fluctuations in the minimum variance framesJana Šafránková, Zdeněk Němeček, František Němec, Daniel Verscharen, Tereza Ďurovcová, and Alexander Pitňa
The analysis of magnetic field and velocity fluctuations in corresponding minimum variance frames revealed that: (1) Minimum variance and mean magnetic field directions would be similar but these two directions are often perpendicular, especially in the high-beta environment, and a number of perpendicular cases decreases with the scale length; (2) Compressibility computed in the minimum variance frame generally increases with frequency but the increase is not monotonic; it exhibits two breaks observed for the magnetic field as well as for velocity fluctuations with approximately the same break frequencies. (3) We suggest that the first break can be connected with a change of pure Alfven to kinetic Alfven modes and the second break approximately coincides with the transition from the inertial to kinetic scales.
How to cite: Šafránková, J., Němeček, Z., Němec, F., Verscharen, D., Ďurovcová, T., and Pitňa, A.: Relations of velocity and magnetic field fluctuations in the minimum variance frames, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2742, https://doi.org/10.5194/egusphere-egu2020-2742, 2020.
The analysis of magnetic field and velocity fluctuations in corresponding minimum variance frames revealed that: (1) Minimum variance and mean magnetic field directions would be similar but these two directions are often perpendicular, especially in the high-beta environment, and a number of perpendicular cases decreases with the scale length; (2) Compressibility computed in the minimum variance frame generally increases with frequency but the increase is not monotonic; it exhibits two breaks observed for the magnetic field as well as for velocity fluctuations with approximately the same break frequencies. (3) We suggest that the first break can be connected with a change of pure Alfven to kinetic Alfven modes and the second break approximately coincides with the transition from the inertial to kinetic scales.
How to cite: Šafránková, J., Němeček, Z., Němec, F., Verscharen, D., Ďurovcová, T., and Pitňa, A.: Relations of velocity and magnetic field fluctuations in the minimum variance frames, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2742, https://doi.org/10.5194/egusphere-egu2020-2742, 2020.
EGU2020-12596 | Displays | NP6.2
Collisionless electron dynamics in the expanding solar windMaria Elena Innocenti, Elisabetta Boella, Anna Tenerani, and Marco Velli
Observations of solar wind electron properties, as displayed in the Tperp/Tpar vs βpar plane, appear to be constrained both in the Tperp/Tpar <1 and in the Tperp/Tpar >1 regimes by the electron firehose instability (EFI) and by the whistler instability respectively [Štverák 2008]. The onset mechanism of the EFI is established: solar wind expansion results in an electron thermal anisotropy, which in turns promotes the development of the instability that contributes to limit that same anisotropy [Innocenti 2019a]. However, if this were the only mechanism at work in the expanding solar wind, electron observations would pool at the EFI marginal instability line. Instead, they populate the “stable” interval bound by EFI and whistler marginal instability lines. It is not fully clear which role fully kinetic processes have in lifting the observed data points above the EFI marginal stability line and into the “stable” area. Other competing processes redistributing excess parallel energy into the perpendicular direction, such as collisions, may be at work as well [Yoon 2019].
We investigate this issue with Particle In Cell, Expanding Box Model simulations [Innocenti 2019b] of EFI developing self consistently in the expanding solar wind. Our results show that after the EFI marginal stability line is reached, further collisionless evolution brings our simulated data points in the “stable” area. We thus demonstrate that, at least under certain circumstances, purely collisionless processes may explain observed solar wind observations, without the need of invoking collisions as a way to channel excess parallel energy into the perpendicular direction.
Štverák, Štěpán, et al. "Electron temperature anisotropy constraints in the solar wind." Journal of Geophysical Research: Space Physics 113.A3 (2008).
Innocenti, Maria Elena, et al. "Onset and Evolution of the Oblique, Resonant Electron Firehose Instability in the Expanding Solar Wind Plasma." The Astrophysical Journal 883.2 (2019): 146.
Yoon, P. H., et al. "Solar Wind Temperature Isotropy." Physical review letters 123.14 (2019): 145101.
Innocenti, Maria Elena, Anna Tenerani, and Marco Velli. "A Semi-implicit Particle-in-cell Expanding Box Model Code for Fully Kinetic Simulations of the Expanding Solar Wind Plasma." The Astrophysical Journal 870.2 (2019): 66.
How to cite: Innocenti, M. E., Boella, E., Tenerani, A., and Velli, M.: Collisionless electron dynamics in the expanding solar wind, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12596, https://doi.org/10.5194/egusphere-egu2020-12596, 2020.
Observations of solar wind electron properties, as displayed in the Tperp/Tpar vs βpar plane, appear to be constrained both in the Tperp/Tpar <1 and in the Tperp/Tpar >1 regimes by the electron firehose instability (EFI) and by the whistler instability respectively [Štverák 2008]. The onset mechanism of the EFI is established: solar wind expansion results in an electron thermal anisotropy, which in turns promotes the development of the instability that contributes to limit that same anisotropy [Innocenti 2019a]. However, if this were the only mechanism at work in the expanding solar wind, electron observations would pool at the EFI marginal instability line. Instead, they populate the “stable” interval bound by EFI and whistler marginal instability lines. It is not fully clear which role fully kinetic processes have in lifting the observed data points above the EFI marginal stability line and into the “stable” area. Other competing processes redistributing excess parallel energy into the perpendicular direction, such as collisions, may be at work as well [Yoon 2019].
We investigate this issue with Particle In Cell, Expanding Box Model simulations [Innocenti 2019b] of EFI developing self consistently in the expanding solar wind. Our results show that after the EFI marginal stability line is reached, further collisionless evolution brings our simulated data points in the “stable” area. We thus demonstrate that, at least under certain circumstances, purely collisionless processes may explain observed solar wind observations, without the need of invoking collisions as a way to channel excess parallel energy into the perpendicular direction.
Štverák, Štěpán, et al. "Electron temperature anisotropy constraints in the solar wind." Journal of Geophysical Research: Space Physics 113.A3 (2008).
Innocenti, Maria Elena, et al. "Onset and Evolution of the Oblique, Resonant Electron Firehose Instability in the Expanding Solar Wind Plasma." The Astrophysical Journal 883.2 (2019): 146.
Yoon, P. H., et al. "Solar Wind Temperature Isotropy." Physical review letters 123.14 (2019): 145101.
Innocenti, Maria Elena, Anna Tenerani, and Marco Velli. "A Semi-implicit Particle-in-cell Expanding Box Model Code for Fully Kinetic Simulations of the Expanding Solar Wind Plasma." The Astrophysical Journal 870.2 (2019): 66.
How to cite: Innocenti, M. E., Boella, E., Tenerani, A., and Velli, M.: Collisionless electron dynamics in the expanding solar wind, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12596, https://doi.org/10.5194/egusphere-egu2020-12596, 2020.
EGU2020-8738 | Displays | NP6.2
Turbulent cascade in the solar wind on ion scalesPetr Hellinger, Andrea Verdini, Simone Landi, Luca Franci, Emanuele Papini, and Lorenzo Matteini
Magnetic power spectra in the solar wind typically exhibit a transition, steepening, on characteristic ion scales. This transition is not yet fully understood. Two basic phenomena are usually suspected: Hall physics and dissipation. We investigate properties of this transition using numerical simulations. We analyze results of two-dimensional hybrid simulations using a compressible version of von Kármán-Howarth equation for statistically homogeneous Hall MHD turbulence and compare these results to the predictions for the incompressible Hall MHD. The simulation results indicate that the transition between large, MHD and sub-ion scales is related to a combination of the Hall effect and ion heating/energization.
How to cite: Hellinger, P., Verdini, A., Landi, S., Franci, L., Papini, E., and Matteini, L.: Turbulent cascade in the solar wind on ion scales, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8738, https://doi.org/10.5194/egusphere-egu2020-8738, 2020.
Magnetic power spectra in the solar wind typically exhibit a transition, steepening, on characteristic ion scales. This transition is not yet fully understood. Two basic phenomena are usually suspected: Hall physics and dissipation. We investigate properties of this transition using numerical simulations. We analyze results of two-dimensional hybrid simulations using a compressible version of von Kármán-Howarth equation for statistically homogeneous Hall MHD turbulence and compare these results to the predictions for the incompressible Hall MHD. The simulation results indicate that the transition between large, MHD and sub-ion scales is related to a combination of the Hall effect and ion heating/energization.
How to cite: Hellinger, P., Verdini, A., Landi, S., Franci, L., Papini, E., and Matteini, L.: Turbulent cascade in the solar wind on ion scales, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8738, https://doi.org/10.5194/egusphere-egu2020-8738, 2020.
EGU2020-11410 | Displays | NP6.2
Mutual Iinformation exchange in solar wind density fluctuationsLuca Sorriso-Valvo, Francesco Carbone, and Daniele Telloni
The fluctuations of proton density in the slow solar wind are analyzed by means of joint Empirical Mode Decomposition (EMD) and Mutual Information (MI) analysis. The analysis reveal that, within the turbulent inertial range, the EMD modes associated with nearby scales have their phases correlated, as shown by the large information exchange. This is a qunatitative measure of the information flow occurring in the turbulent cascade. On the other hand, at scales smaller than the ion gyroscale, the information flow is lost, and the mutual information is low, suggesting that in the kinetic range the nonlinear interacions are no longer sustaining a turbulent energy cascade.
How to cite: Sorriso-Valvo, L., Carbone, F., and Telloni, D.: Mutual Iinformation exchange in solar wind density fluctuations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11410, https://doi.org/10.5194/egusphere-egu2020-11410, 2020.
The fluctuations of proton density in the slow solar wind are analyzed by means of joint Empirical Mode Decomposition (EMD) and Mutual Information (MI) analysis. The analysis reveal that, within the turbulent inertial range, the EMD modes associated with nearby scales have their phases correlated, as shown by the large information exchange. This is a qunatitative measure of the information flow occurring in the turbulent cascade. On the other hand, at scales smaller than the ion gyroscale, the information flow is lost, and the mutual information is low, suggesting that in the kinetic range the nonlinear interacions are no longer sustaining a turbulent energy cascade.
How to cite: Sorriso-Valvo, L., Carbone, F., and Telloni, D.: Mutual Iinformation exchange in solar wind density fluctuations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11410, https://doi.org/10.5194/egusphere-egu2020-11410, 2020.
EGU2020-12171 | Displays | NP6.2
Nature of Elsässer Variables in the slow solar wind turbulenceXin Wang, Chuanyi Tu, and Jiansen He
Elsässer Variables z± are widely considered as outward and inward propagating Alfvén waves in the solar wind turbulence study. It is believed that they can interact nonlinearly with each other to generate energy cascade. However, z− variations sometimes show a feature of convective structures or a combination of white noise and pseudo-structures. Here we present the amplitude of z± in σc (normalized cross helicity) - σr (normalized residual energy) plane in order to get some information on the nature of z±. Measurements from the WIND spacecraft in the slow solar wind during 2007-2009 are used for analysis. In each interval with length of 20 min, we calculate σc, σr, and consider the variance of z± as the amplitude of them for the given interval. We find that in the σc-σr plane, the level contours of the average z- amplitude present a feature of nearly horizontal stratification, which means that the amplitude of z- is independent of the value of σc, and is just related to σr. The horizontal-stratification feature suggests that z- could be convective structures. While the level contours of the average amplitude of z+ are approximately concentric semicircles, and the circle with larger radius corresponds to larger z+ amplitude. It indicates that z+ represents Alfvén waves. The nature of z± in the slow wind here will help us to understand more about the cascade process in the solar wind turbulence.
How to cite: Wang, X., Tu, C., and He, J.: Nature of Elsässer Variables in the slow solar wind turbulence, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12171, https://doi.org/10.5194/egusphere-egu2020-12171, 2020.
Elsässer Variables z± are widely considered as outward and inward propagating Alfvén waves in the solar wind turbulence study. It is believed that they can interact nonlinearly with each other to generate energy cascade. However, z− variations sometimes show a feature of convective structures or a combination of white noise and pseudo-structures. Here we present the amplitude of z± in σc (normalized cross helicity) - σr (normalized residual energy) plane in order to get some information on the nature of z±. Measurements from the WIND spacecraft in the slow solar wind during 2007-2009 are used for analysis. In each interval with length of 20 min, we calculate σc, σr, and consider the variance of z± as the amplitude of them for the given interval. We find that in the σc-σr plane, the level contours of the average z- amplitude present a feature of nearly horizontal stratification, which means that the amplitude of z- is independent of the value of σc, and is just related to σr. The horizontal-stratification feature suggests that z- could be convective structures. While the level contours of the average amplitude of z+ are approximately concentric semicircles, and the circle with larger radius corresponds to larger z+ amplitude. It indicates that z+ represents Alfvén waves. The nature of z± in the slow wind here will help us to understand more about the cascade process in the solar wind turbulence.
How to cite: Wang, X., Tu, C., and He, J.: Nature of Elsässer Variables in the slow solar wind turbulence, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12171, https://doi.org/10.5194/egusphere-egu2020-12171, 2020.
EGU2020-12022 | Displays | NP6.2
Isotropic Scaling Features Measured Locally in the Solar Wind Turbulence with Stationary Background FieldHonghong Wu, Chuanyi Tu, Xin Wang, Jiansen He, Liping Yang, and Linghua Wang
The scaling anisotropy is crucial to interpret the nonlinear interactions in solar wind turbulence. Previous observations provide diverse results and the structure functions analyses are also reported to be an approach to investigate the scaling anisotropy based on a local magnetic field. However, the determination of the sampling angle with respect to the local background magnetic field implicitly assumes that the observed time series are time stationary. If this assumed time-stationarity is compatible with the measurements has not been investigated. Here we utilize the second-order structure function method to study the scaling anisotropy with a time-stationary background field. We analyze 88 fast solar wind intervals each with time durations >=2 days measured by Wind spacecraft in the period 2005-2018. We calculate the local magnetic field as the average of the time series B(t') whose time-stationarity are fulfilled by our criterion φ<10o (φ is the angle between the two averaged magnetic field after cutting B(t') into two halves). We find for the first time the isotropic scaling feature of the magnetic-trace structure functions with scaling indices -0.63±0.08 and 0.70±0.04 respectively in the local parallel and perpendicular directions. The scaling for the velocity-trace structure functions is also isotropic and the indices are -0.47±0.10 and 0.51±0.09.
How to cite: Wu, H., Tu, C., Wang, X., He, J., Yang, L., and Wang, L.: Isotropic Scaling Features Measured Locally in the Solar Wind Turbulence with Stationary Background Field, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12022, https://doi.org/10.5194/egusphere-egu2020-12022, 2020.
The scaling anisotropy is crucial to interpret the nonlinear interactions in solar wind turbulence. Previous observations provide diverse results and the structure functions analyses are also reported to be an approach to investigate the scaling anisotropy based on a local magnetic field. However, the determination of the sampling angle with respect to the local background magnetic field implicitly assumes that the observed time series are time stationary. If this assumed time-stationarity is compatible with the measurements has not been investigated. Here we utilize the second-order structure function method to study the scaling anisotropy with a time-stationary background field. We analyze 88 fast solar wind intervals each with time durations >=2 days measured by Wind spacecraft in the period 2005-2018. We calculate the local magnetic field as the average of the time series B(t') whose time-stationarity are fulfilled by our criterion φ<10o (φ is the angle between the two averaged magnetic field after cutting B(t') into two halves). We find for the first time the isotropic scaling feature of the magnetic-trace structure functions with scaling indices -0.63±0.08 and 0.70±0.04 respectively in the local parallel and perpendicular directions. The scaling for the velocity-trace structure functions is also isotropic and the indices are -0.47±0.10 and 0.51±0.09.
How to cite: Wu, H., Tu, C., Wang, X., He, J., Yang, L., and Wang, L.: Isotropic Scaling Features Measured Locally in the Solar Wind Turbulence with Stationary Background Field, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12022, https://doi.org/10.5194/egusphere-egu2020-12022, 2020.
EGU2020-9805 | Displays | NP6.2
Comparison of semi-implicit and explicit particle in cell methods for the study of turbulence in space plasmasFrancesco Pucci, Tulasi N. Parashar, William H. Matthaeus, and Giovanni Lapenta
The plasma that permeates the solar wind, the solar corona, the Earth's magnetosheath and several
other space environments is in a turbulent state. The effect of turbulence on the dynamics of such systems
is very relevant, considering that it is invoked to explain plasma heating, and particle acceleration and transport
in those environments.
From a mathematical point of view, turbulence is a non linear phenomenon whose study, in the kinetic
description of plasmas, requires the solution of the non linear Vlasov-Maxwell system of equations.
Due to the complexity of the problem, the solutions are nowadays found mainly by means of numerical simulations.
The most widely used method for the solution of the Vlasov-Maxwell system is the Particle In Cell (PIC) method.
PIC methods can be divided into two major classes: explicit and implicit, depending on the algorithm used
for advancing the solution in time.
In this work, we compare two different PIC methods that use an explicit and a semi-implicit algorithm, respectively.
The explicit method is implemented in the code P3D[1], while the semi-implicit method in code iPic3D[2].
Both methods are fully kinetic, namely they retain the kinetic effects for both ions and electrons.
The two codes are tested against a classical set up of plasma turbulence in a 2D cartesian
geometry[3]. The system is initialized with a restricted number of modes at large scale and
evolves in time without forcing. The box size is of several tens of ion inertial length. The
grid size is of the order of the Debye length for the explicit scheme, to ensure numerical stability,
and is varied across the electron skin depth for the semi-implicit, by performing different simulations.
Several analyses are presented: global energy conversion, magnetic and electric spectra, scale dependent kurtosis,
temperature anisotropy for both species, proxies of dissipation such as J.E and PiD[4].
The weaknesses and strengths of the two methods in terms of description of the physical dynamics and of
computational time are presented, along with a convergence study of the semi-implicit to the explicit
method as the resolution of the former is varied.
[1] Zeiler, A., Biskamp, D., Drake, J. F., Rogers, B. N., Shay, M. A., & Scholer, M. (2002). Journal of Geophysical Research: Space Physics, 107(A9), SMP-6.
[2] Markidis, S., Lapenta, G., & Rizwan-uddin (2010). Mathematics and Computers in Simulation, 80(7), 1509-1519.
[3] Parashar, T. N., Matthaeus, W. H., & Shay, M. A. (2018). The Astrophysical Journal Letters, 864(1), L21.
[4] Yang, Y., Matthaeus, W. H., Parashar, T. N., Wu, P., Wan, M., Shi, Y., et al. (2017). Physical Review E, 95(6), 061201.
How to cite: Pucci, F., Parashar, T. N., Matthaeus, W. H., and Lapenta, G.: Comparison of semi-implicit and explicit particle in cell methods for the study of turbulence in space plasmas, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9805, https://doi.org/10.5194/egusphere-egu2020-9805, 2020.
The plasma that permeates the solar wind, the solar corona, the Earth's magnetosheath and several
other space environments is in a turbulent state. The effect of turbulence on the dynamics of such systems
is very relevant, considering that it is invoked to explain plasma heating, and particle acceleration and transport
in those environments.
From a mathematical point of view, turbulence is a non linear phenomenon whose study, in the kinetic
description of plasmas, requires the solution of the non linear Vlasov-Maxwell system of equations.
Due to the complexity of the problem, the solutions are nowadays found mainly by means of numerical simulations.
The most widely used method for the solution of the Vlasov-Maxwell system is the Particle In Cell (PIC) method.
PIC methods can be divided into two major classes: explicit and implicit, depending on the algorithm used
for advancing the solution in time.
In this work, we compare two different PIC methods that use an explicit and a semi-implicit algorithm, respectively.
The explicit method is implemented in the code P3D[1], while the semi-implicit method in code iPic3D[2].
Both methods are fully kinetic, namely they retain the kinetic effects for both ions and electrons.
The two codes are tested against a classical set up of plasma turbulence in a 2D cartesian
geometry[3]. The system is initialized with a restricted number of modes at large scale and
evolves in time without forcing. The box size is of several tens of ion inertial length. The
grid size is of the order of the Debye length for the explicit scheme, to ensure numerical stability,
and is varied across the electron skin depth for the semi-implicit, by performing different simulations.
Several analyses are presented: global energy conversion, magnetic and electric spectra, scale dependent kurtosis,
temperature anisotropy for both species, proxies of dissipation such as J.E and PiD[4].
The weaknesses and strengths of the two methods in terms of description of the physical dynamics and of
computational time are presented, along with a convergence study of the semi-implicit to the explicit
method as the resolution of the former is varied.
[1] Zeiler, A., Biskamp, D., Drake, J. F., Rogers, B. N., Shay, M. A., & Scholer, M. (2002). Journal of Geophysical Research: Space Physics, 107(A9), SMP-6.
[2] Markidis, S., Lapenta, G., & Rizwan-uddin (2010). Mathematics and Computers in Simulation, 80(7), 1509-1519.
[3] Parashar, T. N., Matthaeus, W. H., & Shay, M. A. (2018). The Astrophysical Journal Letters, 864(1), L21.
[4] Yang, Y., Matthaeus, W. H., Parashar, T. N., Wu, P., Wan, M., Shi, Y., et al. (2017). Physical Review E, 95(6), 061201.
How to cite: Pucci, F., Parashar, T. N., Matthaeus, W. H., and Lapenta, G.: Comparison of semi-implicit and explicit particle in cell methods for the study of turbulence in space plasmas, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9805, https://doi.org/10.5194/egusphere-egu2020-9805, 2020.
EGU2020-10074 | Displays | NP6.2
Particle energisation and energy transport in Multiscale MHD - Hybrid - Kinetic PIC models of magnetospheresGiovanni Lapenta, Jean Berchem, Raymond Walker, Mostafa El Alaoui, David Schriver, Robert Richard, and Pavel Travnicek
A grand challenge in physics is to understand how and where electrons and ions accelerate to high energy, often forming power law distributions. We report the result of a combined kinetic-fluid effort [1]. For Earth, a full kinetic model of sizeable chunks of the magnetosphere (e.g. the magnetopause up to the bow shock, or the magnetotail) of order 10-20 RE in size in each dimension is hosted within a MHD simulation that provides it with initial and boundary conditions. For Mercury, it is possible to treat the whole magnetosphere that in this case is spawn from a state derived from a hybrid code [2].
With this approach, we search for regions of most intense particle heating and acceleration, comparing the full kinetic (i.e. we treat both electrons and ions as particles) evolution with the evolution of the host global simulation: MHD for the Earth and hybrid for Mercury.
The results highlight some significant effects peculiar to kinetic models. First, of all full kinetic models provide a detailed view of the electron role in energy transfer, with a distinct role for the enthalpy, bulk and heat flux. Second, the full kinetic approach, allows for the development of modes and instabilities absent in global fluid or hybrid models [3].
How to cite: Lapenta, G., Berchem, J., Walker, R., El Alaoui, M., Schriver, D., Richard, R., and Travnicek, P.: Particle energisation and energy transport in Multiscale MHD - Hybrid - Kinetic PIC models of magnetospheres, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10074, https://doi.org/10.5194/egusphere-egu2020-10074, 2020.
A grand challenge in physics is to understand how and where electrons and ions accelerate to high energy, often forming power law distributions. We report the result of a combined kinetic-fluid effort [1]. For Earth, a full kinetic model of sizeable chunks of the magnetosphere (e.g. the magnetopause up to the bow shock, or the magnetotail) of order 10-20 RE in size in each dimension is hosted within a MHD simulation that provides it with initial and boundary conditions. For Mercury, it is possible to treat the whole magnetosphere that in this case is spawn from a state derived from a hybrid code [2].
With this approach, we search for regions of most intense particle heating and acceleration, comparing the full kinetic (i.e. we treat both electrons and ions as particles) evolution with the evolution of the host global simulation: MHD for the Earth and hybrid for Mercury.
The results highlight some significant effects peculiar to kinetic models. First, of all full kinetic models provide a detailed view of the electron role in energy transfer, with a distinct role for the enthalpy, bulk and heat flux. Second, the full kinetic approach, allows for the development of modes and instabilities absent in global fluid or hybrid models [3].
How to cite: Lapenta, G., Berchem, J., Walker, R., El Alaoui, M., Schriver, D., Richard, R., and Travnicek, P.: Particle energisation and energy transport in Multiscale MHD - Hybrid - Kinetic PIC models of magnetospheres, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10074, https://doi.org/10.5194/egusphere-egu2020-10074, 2020.
EGU2020-2841 | Displays | NP6.2
Observations of an Electron-only Magnetic Reconnection within a macroscopic Flux Rope in the MagnetotailHengyan Man, Meng Zhou, Yongyuan Yi, Zhihong Zhong, and Xiaohua Deng
It is widely accepted that flux ropes play important roles in the momentum and energy transport in space plasmas. Recent observations found that magnetic reconnection occurs at the interface between two counter flows around the center of flux ropes. In this presentation, we report a novel observation by MMS that reconnection occurs at the edge of a large-scale flux rope, the cross-section of which was about 2.5 Re. The flux rope was observed at the dusk side in Earth’s magnetotail and was highly oblique with its axis proximity along the XGSM direction. We found an electron-scale current sheet near the edge of this flux rope. The Hall magnetic and electric field, super-Alfvénic electron outflow, parallel electric field and positive energy dissipation were observed associated with the current sheet. All the above signatures indicate that MMS detected a reconnecting current sheet in the presence of a large guide field. Interestingly, ions were not coupled in this reconnection, akin to the electron-only reconnection observed in the magnetosheath turbulence. We suggest that the electron-scale current sheet was caused by the strong magnetic field perturbation inside the flux rope. This result will shed new lights for understanding the multi-scale coupling associated with flux ropes in space plasmas.
How to cite: Man, H., Zhou, M., Yi, Y., Zhong, Z., and Deng, X.: Observations of an Electron-only Magnetic Reconnection within a macroscopic Flux Rope in the Magnetotail, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2841, https://doi.org/10.5194/egusphere-egu2020-2841, 2020.
It is widely accepted that flux ropes play important roles in the momentum and energy transport in space plasmas. Recent observations found that magnetic reconnection occurs at the interface between two counter flows around the center of flux ropes. In this presentation, we report a novel observation by MMS that reconnection occurs at the edge of a large-scale flux rope, the cross-section of which was about 2.5 Re. The flux rope was observed at the dusk side in Earth’s magnetotail and was highly oblique with its axis proximity along the XGSM direction. We found an electron-scale current sheet near the edge of this flux rope. The Hall magnetic and electric field, super-Alfvénic electron outflow, parallel electric field and positive energy dissipation were observed associated with the current sheet. All the above signatures indicate that MMS detected a reconnecting current sheet in the presence of a large guide field. Interestingly, ions were not coupled in this reconnection, akin to the electron-only reconnection observed in the magnetosheath turbulence. We suggest that the electron-scale current sheet was caused by the strong magnetic field perturbation inside the flux rope. This result will shed new lights for understanding the multi-scale coupling associated with flux ropes in space plasmas.
How to cite: Man, H., Zhou, M., Yi, Y., Zhong, Z., and Deng, X.: Observations of an Electron-only Magnetic Reconnection within a macroscopic Flux Rope in the Magnetotail, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2841, https://doi.org/10.5194/egusphere-egu2020-2841, 2020.
EGU2020-8731 | Displays | NP6.2
Observations of Plasma Waves in the Multiple X-line Reconnection at the MagnetopauseZhihong Zhong, Daniel B. Graham, Yuri V. Khotyaintsev, Meng Zhou, Rongxin Tang, and Xiaohua Deng
Plasma waves are one of the important products of the magnetic reconnection process. Plasma waves can produce particle heating, diffusion, and anomalous effects, which can potentially affect magnetic reconnection. We investigate the evolution and properties of plasma waves during a multiple X-line reconnection event at the magnetopause using measurements from the Magnetospheric Multiscale (MMS) mission. Both whistler waves and large-amplitude electrostatic waves were observed around the reconnecting current sheet. In these regions, the electron velocity distribution functions consist of a combination of a cold beam at low energies with an anisotropic population or a loss-cone at high energies. The electrostatic waves corresponded to regions where the cold beams are accelerated, while the whistlers corresponded to regions with significant anisotropies or loss cones. When the cold beams were accelerated to higher energies, the whistlers disappeared since the anisotropy or loss-cone distributions became less apparent. These results present the detailed evolution of the plasma waves reflecting the electron dynamics during magnetic reconnection.
How to cite: Zhong, Z., Graham, D. B., Khotyaintsev, Y. V., Zhou, M., Tang, R., and Deng, X.: Observations of Plasma Waves in the Multiple X-line Reconnection at the Magnetopause, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8731, https://doi.org/10.5194/egusphere-egu2020-8731, 2020.
Plasma waves are one of the important products of the magnetic reconnection process. Plasma waves can produce particle heating, diffusion, and anomalous effects, which can potentially affect magnetic reconnection. We investigate the evolution and properties of plasma waves during a multiple X-line reconnection event at the magnetopause using measurements from the Magnetospheric Multiscale (MMS) mission. Both whistler waves and large-amplitude electrostatic waves were observed around the reconnecting current sheet. In these regions, the electron velocity distribution functions consist of a combination of a cold beam at low energies with an anisotropic population or a loss-cone at high energies. The electrostatic waves corresponded to regions where the cold beams are accelerated, while the whistlers corresponded to regions with significant anisotropies or loss cones. When the cold beams were accelerated to higher energies, the whistlers disappeared since the anisotropy or loss-cone distributions became less apparent. These results present the detailed evolution of the plasma waves reflecting the electron dynamics during magnetic reconnection.
How to cite: Zhong, Z., Graham, D. B., Khotyaintsev, Y. V., Zhou, M., Tang, R., and Deng, X.: Observations of Plasma Waves in the Multiple X-line Reconnection at the Magnetopause, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8731, https://doi.org/10.5194/egusphere-egu2020-8731, 2020.
EGU2020-9476 | Displays | NP6.2
Current structures and reconnection events analysis in hybrid-kinetic turbulence simulations using unsupervised machine learningManuela Sisti, Francesco Califano, Matteo Faganello, Giorgio Pedrazzi, Francesca Delli Ponti, Andong Hu, and Jannis Teunissen
How to cite: Sisti, M., Califano, F., Faganello, M., Pedrazzi, G., Delli Ponti, F., Hu, A., and Teunissen, J.: Current structures and reconnection events analysis in hybrid-kinetic turbulence simulations using unsupervised machine learning, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9476, https://doi.org/10.5194/egusphere-egu2020-9476, 2020.
How to cite: Sisti, M., Califano, F., Faganello, M., Pedrazzi, G., Delli Ponti, F., Hu, A., and Teunissen, J.: Current structures and reconnection events analysis in hybrid-kinetic turbulence simulations using unsupervised machine learning, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9476, https://doi.org/10.5194/egusphere-egu2020-9476, 2020.
EGU2020-12754 | Displays | NP6.2
Filamentary Currents in Turbulent Magnetic ReconnectionMeng Zhou, Xiaohua Deng, Zhihong Zhong, and Ye Pang
Magnetic reconnection and turbulence are the two most important energy conversion phenomena in plasma physics. Magnetic reconnection and turbulence are often intertwined. For example, reconnection occurs in thin current layers formed during cascades of turbulence, while reconnection in large-scale current sheet also evolves into turbulence. How energy is dissipated and how particles are accelerated in turbulent magnetic reconnection are outstanding questions in magnetic reconnection and turbulence. Here we report MMS observations of filamentary currents in turbulent outflows in the Earth's magnetotail. We found sub-ion-scale filamentary currents in high-speed outflows that evolved into turbulent states. The normal direction of these current filaments is mainly along the XGSM direction, which is distinct from the neutral sheet. Some filamentary currents were reconnecting, thereby further dissipating the magnetic energy far from the X line. We notice that turbulent reconnection is more efficient in energizing electrons than laminar reconnection. Coherent structures composed of these filaments may be important in accelerating particles during turbulent reconnection.
How to cite: Zhou, M., Deng, X., Zhong, Z., and Pang, Y.: Filamentary Currents in Turbulent Magnetic Reconnection, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12754, https://doi.org/10.5194/egusphere-egu2020-12754, 2020.
Magnetic reconnection and turbulence are the two most important energy conversion phenomena in plasma physics. Magnetic reconnection and turbulence are often intertwined. For example, reconnection occurs in thin current layers formed during cascades of turbulence, while reconnection in large-scale current sheet also evolves into turbulence. How energy is dissipated and how particles are accelerated in turbulent magnetic reconnection are outstanding questions in magnetic reconnection and turbulence. Here we report MMS observations of filamentary currents in turbulent outflows in the Earth's magnetotail. We found sub-ion-scale filamentary currents in high-speed outflows that evolved into turbulent states. The normal direction of these current filaments is mainly along the XGSM direction, which is distinct from the neutral sheet. Some filamentary currents were reconnecting, thereby further dissipating the magnetic energy far from the X line. We notice that turbulent reconnection is more efficient in energizing electrons than laminar reconnection. Coherent structures composed of these filaments may be important in accelerating particles during turbulent reconnection.
How to cite: Zhou, M., Deng, X., Zhong, Z., and Pang, Y.: Filamentary Currents in Turbulent Magnetic Reconnection, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12754, https://doi.org/10.5194/egusphere-egu2020-12754, 2020.
EGU2020-6983 | Displays | NP6.2
Evidence and analysis of ion/electron foreshocks for a curved shock in Subcritical regime: 2D self-consistent PIC simulationsPhilippe Savoini and Bertrand Lembege
Since early 2D PIC full self-consistent quasi-perpendicular simulations of the foreshock region [Savoini et Lembege, 2001] performed for a supercritical regime, different efforts have been invested later on to analyze the foreshock region. Previous 2D PIC simulations have succeeded in recovering both the local electron distribution [Savoini and Lembege, 2001] and the ion distribution [Savoini et al., 2013] in good agreement with the in-situ experimental data. These studies have retrieved both kinds of distributions and have analyzed in detail how these local distributions vary versus (i) the local angle ΘBn to the curved shock (defined between the normal of the shock front and the upstream interplanetary magnetic field) and (ii) the distance from the shock front, in order to identify in detail the different acceleration mechanisms at work at the curved front and supporting these local ion and electron distributions within the foreshock region [Savoini and Lembege, 2001, 2015; Savoini et al, 2013]. This last point can only be accessible to a self-consistent approach (where ion and electron scales are fully included) as in 2D PIC simulations.
Then, the present work is an extension of the previous analyses listed above for a curved (quasi-perpendicular) shock applied now in a subcritical regime. This work is performed thanks to a new 2D parallel PIC code (SMILEI) which is highly optimized and allows much higher statistics. The main characteristics of the curved front microstructures, its time dynamics, and preliminary results on local distribution functions obtained for both electrons and ions in this new Mach regime will be presented.
Savoini, P. and B. Lembege, « Two-dimensional simulations of a curved shock: Self-consistent formation of the electron foreshock », J. Geophys. Res., Vol. 106, A7, 12975-12992, 2001
Savoini P., B. Lembege and J. Stienlet, « On the origin of the quasi-perpendicular ion foreshock: Full-particle simulations”, J. Geophys. Res., V. 118, 1–14, doi:10.1002/jgra.50158, 2013
Savoini P. and B. Lembege, “Production of nongyrotropic and gyrotropic backstreaming ion distributions in the quasi-perpendicular ion foreshock region”, J. Geophys. Res., V. 120, 7154–7171, doi: 10.1002/2015JA021018, 2015.
How to cite: Savoini, P. and Lembege, B.: Evidence and analysis of ion/electron foreshocks for a curved shock in Subcritical regime: 2D self-consistent PIC simulations , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6983, https://doi.org/10.5194/egusphere-egu2020-6983, 2020.
Since early 2D PIC full self-consistent quasi-perpendicular simulations of the foreshock region [Savoini et Lembege, 2001] performed for a supercritical regime, different efforts have been invested later on to analyze the foreshock region. Previous 2D PIC simulations have succeeded in recovering both the local electron distribution [Savoini and Lembege, 2001] and the ion distribution [Savoini et al., 2013] in good agreement with the in-situ experimental data. These studies have retrieved both kinds of distributions and have analyzed in detail how these local distributions vary versus (i) the local angle ΘBn to the curved shock (defined between the normal of the shock front and the upstream interplanetary magnetic field) and (ii) the distance from the shock front, in order to identify in detail the different acceleration mechanisms at work at the curved front and supporting these local ion and electron distributions within the foreshock region [Savoini and Lembege, 2001, 2015; Savoini et al, 2013]. This last point can only be accessible to a self-consistent approach (where ion and electron scales are fully included) as in 2D PIC simulations.
Then, the present work is an extension of the previous analyses listed above for a curved (quasi-perpendicular) shock applied now in a subcritical regime. This work is performed thanks to a new 2D parallel PIC code (SMILEI) which is highly optimized and allows much higher statistics. The main characteristics of the curved front microstructures, its time dynamics, and preliminary results on local distribution functions obtained for both electrons and ions in this new Mach regime will be presented.
Savoini, P. and B. Lembege, « Two-dimensional simulations of a curved shock: Self-consistent formation of the electron foreshock », J. Geophys. Res., Vol. 106, A7, 12975-12992, 2001
Savoini P., B. Lembege and J. Stienlet, « On the origin of the quasi-perpendicular ion foreshock: Full-particle simulations”, J. Geophys. Res., V. 118, 1–14, doi:10.1002/jgra.50158, 2013
Savoini P. and B. Lembege, “Production of nongyrotropic and gyrotropic backstreaming ion distributions in the quasi-perpendicular ion foreshock region”, J. Geophys. Res., V. 120, 7154–7171, doi: 10.1002/2015JA021018, 2015.
How to cite: Savoini, P. and Lembege, B.: Evidence and analysis of ion/electron foreshocks for a curved shock in Subcritical regime: 2D self-consistent PIC simulations , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6983, https://doi.org/10.5194/egusphere-egu2020-6983, 2020.
EGU2020-18188 | Displays | NP6.2
In situ evidence of firehose instability in multiple magnetic reconnectionAlexandra Alexandrova, Alessandro Retinò, Andrey Divin, Lorenzo Matteini, Olivier Le Contel, Hugo Breuillard, Filomena Catapano, Giulia Cozzani, and Jan Deca
Energy conversion via reconnecting current sheets is common in space and astrophysical plasma. Frequently, current sheets disrupt at multiple reconnection sites, leading to the formation of plasmoid structures between the sites, which might affect energy conversion. We present in situ observations of multiple reconnection in the Earth’s magnetotail. The observed highly accelerated proton beams parallel to magnetic field and the ion-scale wave-like fluctuations of the whistler type imply the development of firehose instability between two active reconnection sites. The linear wave dispersion relation estimated for the measured plasma parameters, indicates a positive growth rate of the firehose-related electromagnetic fluctuations. The detailed time-space evolution of the plasmoid is obtained by reconstruction of observations with the 2.5D implicit particle-in-cell simulations. In course of time, plasma on the periphery of the plasmoid becomes anisotropic and as it overcomes the firehose marginal stability threshold, the corresponding magnetic field fluctuations arise. The results of observations and simulations suggest that the firehose instability operating between reconnection sites, converts plasma energy of the proton temperature anisotropy to the energy of magnetic field fluctuations, counteracting with the conversion of magnetic energy to the energy of plasma in reconnection sites.
How to cite: Alexandrova, A., Retinò, A., Divin, A., Matteini, L., Le Contel, O., Breuillard, H., Catapano, F., Cozzani, G., and Deca, J.: In situ evidence of firehose instability in multiple magnetic reconnection, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18188, https://doi.org/10.5194/egusphere-egu2020-18188, 2020.
Energy conversion via reconnecting current sheets is common in space and astrophysical plasma. Frequently, current sheets disrupt at multiple reconnection sites, leading to the formation of plasmoid structures between the sites, which might affect energy conversion. We present in situ observations of multiple reconnection in the Earth’s magnetotail. The observed highly accelerated proton beams parallel to magnetic field and the ion-scale wave-like fluctuations of the whistler type imply the development of firehose instability between two active reconnection sites. The linear wave dispersion relation estimated for the measured plasma parameters, indicates a positive growth rate of the firehose-related electromagnetic fluctuations. The detailed time-space evolution of the plasmoid is obtained by reconstruction of observations with the 2.5D implicit particle-in-cell simulations. In course of time, plasma on the periphery of the plasmoid becomes anisotropic and as it overcomes the firehose marginal stability threshold, the corresponding magnetic field fluctuations arise. The results of observations and simulations suggest that the firehose instability operating between reconnection sites, converts plasma energy of the proton temperature anisotropy to the energy of magnetic field fluctuations, counteracting with the conversion of magnetic energy to the energy of plasma in reconnection sites.
How to cite: Alexandrova, A., Retinò, A., Divin, A., Matteini, L., Le Contel, O., Breuillard, H., Catapano, F., Cozzani, G., and Deca, J.: In situ evidence of firehose instability in multiple magnetic reconnection, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18188, https://doi.org/10.5194/egusphere-egu2020-18188, 2020.
NP6.3 – Recent development in GFD and remote sensing. Nonlinear and turbulent processes under high wind conditions
EGU2020-7481 | Displays | NP6.3 | Highlight
Filed observations of spray production function during Tropical Cyclones Olwyn and VeronicaAlexander Babanin, Hongyu Ma, Xingkun Xu, and Fangli Qiao
Spray produced in Tropical Cyclones affects the dynamic and heat fluxes between the atmosphere and ocean, and thus can influence the Cyclone intensity in a number of ways. Measurements of the Sea Spray Generation Function (SSGF) in situ, however, are extremely challenging and correspondingly rare, and uncertainties in quantifying SSGF reach 1000 times.
In the presentation, measurements of the total volume of spray by means of a laser array in Tropical Cyclones Olwyn (2015) and Veronica (2019) in the Indian Ocean will be reported. They are used to develop a parameterisation of SSGF at wind speeds ranging from light to extreme. It is argued that the spray is produced by wind-over-the-waves, and therefore wave properties are also accounted for in the parameterisation.
How to cite: Babanin, A., Ma, H., Xu, X., and Qiao, F.: Filed observations of spray production function during Tropical Cyclones Olwyn and Veronica, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7481, https://doi.org/10.5194/egusphere-egu2020-7481, 2020.
Spray produced in Tropical Cyclones affects the dynamic and heat fluxes between the atmosphere and ocean, and thus can influence the Cyclone intensity in a number of ways. Measurements of the Sea Spray Generation Function (SSGF) in situ, however, are extremely challenging and correspondingly rare, and uncertainties in quantifying SSGF reach 1000 times.
In the presentation, measurements of the total volume of spray by means of a laser array in Tropical Cyclones Olwyn (2015) and Veronica (2019) in the Indian Ocean will be reported. They are used to develop a parameterisation of SSGF at wind speeds ranging from light to extreme. It is argued that the spray is produced by wind-over-the-waves, and therefore wave properties are also accounted for in the parameterisation.
How to cite: Babanin, A., Ma, H., Xu, X., and Qiao, F.: Filed observations of spray production function during Tropical Cyclones Olwyn and Veronica, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7481, https://doi.org/10.5194/egusphere-egu2020-7481, 2020.
EGU2020-4383 | Displays | NP6.3
Microphysics-Based Bulk Parameterizations of Enthalpy and Momentum Fluxes for Tropical CyclonesSydney Sroka and Kerry Emanuel
Despite the powerful influence that sea spray has on air-sea enthalpy and momentum fluxes, most state-of-the-art tropical cyclone forecast models do not incorporate the microphysics of sea spray evaporation into their boundary layer flux schemes. Since the air-sea enthalpy and momentum fluxes control a tropical cyclone’s intensification rate, increasing the accuracy of the associated bulk parameterizations is crucially important for improving forecast skill. New microphysics-based bulk parameterizations for enthalpy and momentum flux through the tropical cyclone boundary layer are developed from a set of prognostic evaporation equations and numerical simulations of evaporating, multiphase flow subject to extreme wind speeds. The microphysics-based parameterizations are computationally inexpensive and are functions of the local environmental conditions; these features allow forecast models to efficiently vary the air-sea enthalpy and momentum fluxes in space and time. By developing microphysics-based bulk parameterizations, the influence that sea spray exerts on tropical cyclone intensification can be more accurately simulated and intensity forecasts could be improved.
How to cite: Sroka, S. and Emanuel, K.: Microphysics-Based Bulk Parameterizations of Enthalpy and Momentum Fluxes for Tropical Cyclones, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4383, https://doi.org/10.5194/egusphere-egu2020-4383, 2020.
Despite the powerful influence that sea spray has on air-sea enthalpy and momentum fluxes, most state-of-the-art tropical cyclone forecast models do not incorporate the microphysics of sea spray evaporation into their boundary layer flux schemes. Since the air-sea enthalpy and momentum fluxes control a tropical cyclone’s intensification rate, increasing the accuracy of the associated bulk parameterizations is crucially important for improving forecast skill. New microphysics-based bulk parameterizations for enthalpy and momentum flux through the tropical cyclone boundary layer are developed from a set of prognostic evaporation equations and numerical simulations of evaporating, multiphase flow subject to extreme wind speeds. The microphysics-based parameterizations are computationally inexpensive and are functions of the local environmental conditions; these features allow forecast models to efficiently vary the air-sea enthalpy and momentum fluxes in space and time. By developing microphysics-based bulk parameterizations, the influence that sea spray exerts on tropical cyclone intensification can be more accurately simulated and intensity forecasts could be improved.
How to cite: Sroka, S. and Emanuel, K.: Microphysics-Based Bulk Parameterizations of Enthalpy and Momentum Fluxes for Tropical Cyclones, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4383, https://doi.org/10.5194/egusphere-egu2020-4383, 2020.
EGU2020-7249 | Displays | NP6.3
Investigation of droplet-mediated sensible and latent heat fluxes in a turbulent air flow over a waved water surface by direct numerical simulationOleg Druzhinin
The objective of the present study is to investigate sensible and latent heat transfer mediated by evaporating saline droplets in a turbulent air flow over a waved water surface by performing direct numerical simulation. Equations of the air-flow velocity, temperature and humidity are solved simultaneously with the two-way-coupled equations of individual droplets coordinates and velocities, temperatures and masses. Two different cases of air and water surface temperatures,Ta = 27 0C, Ts = 28 0C, and Ta = -10 0C, Ts = 0 0C, are considered and conditionally termed as "tropical cyclone" (TC) and "polar low" (PL) conditions, respectively. Droplets-mediated sensible and latent heat fluxes, QS and QL, are integrated along individual droplets Lagrangian trajectories and evaluated as distributions over droplet diameter at injection, d, and also obtained as Eulerian, ensemble-averaged fields. The results show that under TC-conditions, the sensible heat flux from droplets to air is negative whereas the latent heat flux is positive, and thus droplets cool and moisturize the carrier air. On the other hand, under PL-conditions, QS and QL are both positive, and QL – contribution is significantly reduced as compared to QS - contribution. Thus in this case, droplets warm up the air. In both cases, the droplet-mediated enthalpy flux, QS + QL , is positive, vanishes for sufficiently small droplets (with diameters d ≤ 150 μm) and further increases with d. The results also show that the net fluxes are reduced with increasing wave slope.
This work is supported by the Ministry of Education and Science of the Russian Federation (Task No. 0030-2019-0020). Numerical algorithms were developed under the support of RFBR (Nos. 18-05-60299, 18-55-50005, 18-05-00265, 20-05-00322). Postprocessing was performed under the support of the Russian Science Foundation (No. 19-17-00209).
How to cite: Druzhinin, O.: Investigation of droplet-mediated sensible and latent heat fluxes in a turbulent air flow over a waved water surface by direct numerical simulation , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7249, https://doi.org/10.5194/egusphere-egu2020-7249, 2020.
The objective of the present study is to investigate sensible and latent heat transfer mediated by evaporating saline droplets in a turbulent air flow over a waved water surface by performing direct numerical simulation. Equations of the air-flow velocity, temperature and humidity are solved simultaneously with the two-way-coupled equations of individual droplets coordinates and velocities, temperatures and masses. Two different cases of air and water surface temperatures,Ta = 27 0C, Ts = 28 0C, and Ta = -10 0C, Ts = 0 0C, are considered and conditionally termed as "tropical cyclone" (TC) and "polar low" (PL) conditions, respectively. Droplets-mediated sensible and latent heat fluxes, QS and QL, are integrated along individual droplets Lagrangian trajectories and evaluated as distributions over droplet diameter at injection, d, and also obtained as Eulerian, ensemble-averaged fields. The results show that under TC-conditions, the sensible heat flux from droplets to air is negative whereas the latent heat flux is positive, and thus droplets cool and moisturize the carrier air. On the other hand, under PL-conditions, QS and QL are both positive, and QL – contribution is significantly reduced as compared to QS - contribution. Thus in this case, droplets warm up the air. In both cases, the droplet-mediated enthalpy flux, QS + QL , is positive, vanishes for sufficiently small droplets (with diameters d ≤ 150 μm) and further increases with d. The results also show that the net fluxes are reduced with increasing wave slope.
This work is supported by the Ministry of Education and Science of the Russian Federation (Task No. 0030-2019-0020). Numerical algorithms were developed under the support of RFBR (Nos. 18-05-60299, 18-55-50005, 18-05-00265, 20-05-00322). Postprocessing was performed under the support of the Russian Science Foundation (No. 19-17-00209).
How to cite: Druzhinin, O.: Investigation of droplet-mediated sensible and latent heat fluxes in a turbulent air flow over a waved water surface by direct numerical simulation , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7249, https://doi.org/10.5194/egusphere-egu2020-7249, 2020.
EGU2020-15534 | Displays | NP6.3
On the momentum-, heat-, and moisture-exchange on the ocean surface under strong wind conditions.Elena Savenkova, Vladimir Kudryavtsev, and Bertran Chapron
We present results of the model treatment of momentum-, heat-, and moisture-exchange on the ocean surface under strong wind conditions. Despite the large amount of experimental and theoretical efforts, the mechanism and physics of the air-sea interaction at high wind conditions is still poor known and many open questions are still remained. (see e.g. Donelan et.al. 2004, Powell 2003, Kudryavtsev 2006, Jarosz 2007, Troitskaya et.al. 2011).
The model is based on extension of wind-over-wave couple model suggested by Kudryavtsev, Chapron and Makin (2014, hereinafter KCM2014). This model confirmed crucial role of wave breaking on surface drag and heat-, moister-transfer coefficients. Description of wave breaking crest roughness in KCM2014 is treated as Kolmogorov-type spectra resulting from the energy flux from the largest energetic breaking disturbances toward shorter scales. To extend KCM2014 model on high wind conditions, we introduced Kelvin- Helmholtz instability which is able to disrupt both the crests of short regular (non-breaking) waves, and the small-scale breaking crests roughness. It is suggested that at wind speed exceeding a critical value, spectral components of both regular wind waves and breaking crests roughness are subjected to Kelvin-Helmholtz instability and aerodynamically disrupted, and thus do not contribute to the total form drag. This effect results in decrease of the surface drag, that in turn, following KCM2014, leads to enhancement of exchange at the sea surface heat and moister transfer. As a consequence, ratio of the enthalpy to the drag coefficient increases and at wind speed above 25 m/s exceeds critical level introduced by (Emanuel, 1995). Comparison of model predictions with available data at high winds is encouraging, and suggests that accounting for the Kelvin- Helmholtz instability in the wind-over-wave coupled model provides realistic description of air-sea interaction under strong wind condition.
The work was supported by Russian Science Foundation grant No 17-77-30019.
How to cite: Savenkova, E., Kudryavtsev, V., and Chapron, B.: On the momentum-, heat-, and moisture-exchange on the ocean surface under strong wind conditions., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15534, https://doi.org/10.5194/egusphere-egu2020-15534, 2020.
We present results of the model treatment of momentum-, heat-, and moisture-exchange on the ocean surface under strong wind conditions. Despite the large amount of experimental and theoretical efforts, the mechanism and physics of the air-sea interaction at high wind conditions is still poor known and many open questions are still remained. (see e.g. Donelan et.al. 2004, Powell 2003, Kudryavtsev 2006, Jarosz 2007, Troitskaya et.al. 2011).
The model is based on extension of wind-over-wave couple model suggested by Kudryavtsev, Chapron and Makin (2014, hereinafter KCM2014). This model confirmed crucial role of wave breaking on surface drag and heat-, moister-transfer coefficients. Description of wave breaking crest roughness in KCM2014 is treated as Kolmogorov-type spectra resulting from the energy flux from the largest energetic breaking disturbances toward shorter scales. To extend KCM2014 model on high wind conditions, we introduced Kelvin- Helmholtz instability which is able to disrupt both the crests of short regular (non-breaking) waves, and the small-scale breaking crests roughness. It is suggested that at wind speed exceeding a critical value, spectral components of both regular wind waves and breaking crests roughness are subjected to Kelvin-Helmholtz instability and aerodynamically disrupted, and thus do not contribute to the total form drag. This effect results in decrease of the surface drag, that in turn, following KCM2014, leads to enhancement of exchange at the sea surface heat and moister transfer. As a consequence, ratio of the enthalpy to the drag coefficient increases and at wind speed above 25 m/s exceeds critical level introduced by (Emanuel, 1995). Comparison of model predictions with available data at high winds is encouraging, and suggests that accounting for the Kelvin- Helmholtz instability in the wind-over-wave coupled model provides realistic description of air-sea interaction under strong wind condition.
The work was supported by Russian Science Foundation grant No 17-77-30019.
How to cite: Savenkova, E., Kudryavtsev, V., and Chapron, B.: On the momentum-, heat-, and moisture-exchange on the ocean surface under strong wind conditions., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15534, https://doi.org/10.5194/egusphere-egu2020-15534, 2020.
EGU2020-17958 | Displays | NP6.3
TC observations from Synthetic Aperture Radar: short term perspectivesRomain Husson, Alexis Mouche, Nicolas Longepe, Henrick Berger, Olivier Archer, and François Soulat
More than 200 Sentinel-1 acquisitions over Tropical Cyclones (TC) eyes have been accumulated since 2016 thanks to the SHOC scheme (Satellite Hurricane Observation Campaign) operated in collaboration with ESA ground segment. These high-resolution observations have shown the great potential offered by S1 constellation in dual-polarization to monitor TC along their lifetime and to provide numerous observable parameters such as maximum sustained wind speed (up to 80 m/s) and TC structure (e.g. wind radii, eye geometry and position). Co-locations with the Stepped Frequency Microwave Radiometer (SFMR) confirm that, even for extreme cases, S1-derived ocean wind speeds are found in agreement and able to provide consistent measurements in the eyewall. Similarly, co-locations between SMOS and S1-wind degraded at a similar medium resolution are in good agreement. Also, Hurricane experts listed in their recommendations at the 40th WMO Hurricane Committee for USA/Caribbean region that “Special acquisitions plans during Irma, Jose and Maria having demonstrated the high value of kilometric-scale information provided by Sentinel-1 SAR data, HC40 recommends that these data are made available to help monitor critical aspects of the TC structure”.
Based on this demonstration, a new ESA-funded project called CYMS (CYclone Monitoring service with S-1) starts in February 2020, with the objective of scaling up the SHOC initiative for its potential integration as part of a Copernicus Service. One objective is the operational delivery of tailored S1-derived TC observations to tropical cyclone forecasters of all tropical cyclone Regional Specialized Meteorological Centres (RSMCs) and Tropical Cyclone Warning Centres (TCWCs). Besides, S1 TC observations will contribute to a new database for science applications.
In order to continuously keep improving the S1-derived TC observations, current limitations in the wind field retrieval are recalled and perspectives to overcome them are proposed. First, the presence of rain signatures over SAR images requires a fine pre-processing filtering of these non-wind related features in order not to interpret them as wind speed. Second, the current inversion using the co- and cross-polarized NRCS channels via a noise-dependent mixing can show some limitations for wind speed around 30m/s. Alternative schemes are proposed to mitigate this issue. Third, S1 wind directions are mostly influenced by the co-located atmospheric model which can show some significant shifts with respect to the actual situation. Pre-processing methods based on the exploitation of wind rolls signatures, ubiquitous under intense TC, are presented to improve the wind direction retrieval. Finally, improvements of the current cross-polarized Geophysical Model Function (GMF), MS1A, are proposed taking advantage of a more complete dataset of S1 TC observations since its first estimation in 2017.
Overall, the current and future developments for S1 wind field retrieval aim at integrating all valuable observations as inputs. Additional candidate parameters of interest are the Doppler Centroïd anomaly, which is related to the radial wind, and the Co-Cross Polarization Coherence (CCPC), which is related to both the wind speed and direction.
How to cite: Husson, R., Mouche, A., Longepe, N., Berger, H., Archer, O., and Soulat, F.: TC observations from Synthetic Aperture Radar: short term perspectives, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17958, https://doi.org/10.5194/egusphere-egu2020-17958, 2020.
More than 200 Sentinel-1 acquisitions over Tropical Cyclones (TC) eyes have been accumulated since 2016 thanks to the SHOC scheme (Satellite Hurricane Observation Campaign) operated in collaboration with ESA ground segment. These high-resolution observations have shown the great potential offered by S1 constellation in dual-polarization to monitor TC along their lifetime and to provide numerous observable parameters such as maximum sustained wind speed (up to 80 m/s) and TC structure (e.g. wind radii, eye geometry and position). Co-locations with the Stepped Frequency Microwave Radiometer (SFMR) confirm that, even for extreme cases, S1-derived ocean wind speeds are found in agreement and able to provide consistent measurements in the eyewall. Similarly, co-locations between SMOS and S1-wind degraded at a similar medium resolution are in good agreement. Also, Hurricane experts listed in their recommendations at the 40th WMO Hurricane Committee for USA/Caribbean region that “Special acquisitions plans during Irma, Jose and Maria having demonstrated the high value of kilometric-scale information provided by Sentinel-1 SAR data, HC40 recommends that these data are made available to help monitor critical aspects of the TC structure”.
Based on this demonstration, a new ESA-funded project called CYMS (CYclone Monitoring service with S-1) starts in February 2020, with the objective of scaling up the SHOC initiative for its potential integration as part of a Copernicus Service. One objective is the operational delivery of tailored S1-derived TC observations to tropical cyclone forecasters of all tropical cyclone Regional Specialized Meteorological Centres (RSMCs) and Tropical Cyclone Warning Centres (TCWCs). Besides, S1 TC observations will contribute to a new database for science applications.
In order to continuously keep improving the S1-derived TC observations, current limitations in the wind field retrieval are recalled and perspectives to overcome them are proposed. First, the presence of rain signatures over SAR images requires a fine pre-processing filtering of these non-wind related features in order not to interpret them as wind speed. Second, the current inversion using the co- and cross-polarized NRCS channels via a noise-dependent mixing can show some limitations for wind speed around 30m/s. Alternative schemes are proposed to mitigate this issue. Third, S1 wind directions are mostly influenced by the co-located atmospheric model which can show some significant shifts with respect to the actual situation. Pre-processing methods based on the exploitation of wind rolls signatures, ubiquitous under intense TC, are presented to improve the wind direction retrieval. Finally, improvements of the current cross-polarized Geophysical Model Function (GMF), MS1A, are proposed taking advantage of a more complete dataset of S1 TC observations since its first estimation in 2017.
Overall, the current and future developments for S1 wind field retrieval aim at integrating all valuable observations as inputs. Additional candidate parameters of interest are the Doppler Centroïd anomaly, which is related to the radial wind, and the Co-Cross Polarization Coherence (CCPC), which is related to both the wind speed and direction.
How to cite: Husson, R., Mouche, A., Longepe, N., Berger, H., Archer, O., and Soulat, F.: TC observations from Synthetic Aperture Radar: short term perspectives, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17958, https://doi.org/10.5194/egusphere-egu2020-17958, 2020.
EGU2020-19174 | Displays | NP6.3 | Highlight
An In-situ Reference for High and Extreme WindsAd Stoffelen, Alexis Mouche, Federica Polverari, Gerd-Jan van Zadelhoff, Joe Sapp, Marcos Portabella, Paul Chang, Wenming Lin, and Zorana Jelenek
A particularly pressing requirement in the Ocean Surface Vector Wind (OSVW) community is to obtain reliable extreme winds in hurricanes (> 30 m/s) from wind scatterometers, since extreme weather classification, surge and wave forecasts for societal warning are a high priority in nowcasting and in numerical weather prediction (NWP). A main goal of the EUMETSAT C-band High and Extreme-Force Speeds (CHEFS) study is therefore to consolidate an in-situ wind reference for assessing scatterometer high and extreme-force wind capabilities.
Scatterometers have proven to have very good performances when retrieving low to moderate winds. However, measuring high and extreme winds is still challenging as vicarious calibration is needed and calibrated in situ reference winds are scarce.
Moored buoy data are usually used as absolute reference to calibrate the scatterometer Geophysical Model Functions (GMF), however, for very high and extreme winds above 25 m/s, moored buoys may not be reliable. Moreover, controversy exists in the OSVW satellite community on the quality of moored buoys above 15 m/s rather than 25 m/s. Hence, the quality of buoy winds between 15 m/s and 25 m/s is thoroughly evaluated. The buoy wind performance, estimated with triple collocation analyses of buoy, ASCAT and ERA5 winds, shows that the quality of buoy wind vectors up to 25 m/s is within 2 m/s, indicating that buoy winds can indeed be used for wind scatterometer GMF calibration in the mentioned wind range.
The NOAA hurricane hunters fly into hurricanes to drop sondes, and thus obtain wind profiles in the lowest few kilometers of hurricanes, and operate dedicated microwave instrumentation on aircraft to obtain detailed wind patterns in hurricanes, such as the Stepped-Frequency Microwave Radiometer (SFMR). Ideally, local dropsonde winds may be statistically used to calibrate SFMR as they have similar spatial representation (“footprint”). SFMR, in turn, after spatial aggregation to scatterometer footprints, may be used to calibrate satellite scatterometers and radiometers in overflights.
The so-called WL150 algorithm is operationally used to estimate 10-m surface winds from dropsonde wind profiles. The measured radiosonde 10-m winds are a more direct calibration resource for the 10-m surface wind than WL150 estimates. However, an improved assessment of the position processing of the sonde near the surface, where its deceleration is maximum, is needed.
The air mass density needs to be considered to calibrate scatterometer winds in hurricanes, as these mainly occur at low pressures and hence low air mass density, i.e., so-called stress-equivalent winds should be used for comparison.
Finally, ASCAT winds show sensitivity to high winds, but lack good GMF calibration due to the lack of a consolidated in-situ wind reference. The saturation of the GMF at extreme winds is somehow compensated by the high calibration stability of the ASCAT instrument. As a result, further backscatter calibration refinements will support the retrieval of good-quality ASCAT winds in extreme conditions. In addition, GMF development and wind retrieval studies will be useful to improve high and extreme winds, in particular after a consolidated in-situ wind reference has been established.
How to cite: Stoffelen, A., Mouche, A., Polverari, F., van Zadelhoff, G.-J., Sapp, J., Portabella, M., Chang, P., Lin, W., and Jelenek, Z.: An In-situ Reference for High and Extreme Winds, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19174, https://doi.org/10.5194/egusphere-egu2020-19174, 2020.
A particularly pressing requirement in the Ocean Surface Vector Wind (OSVW) community is to obtain reliable extreme winds in hurricanes (> 30 m/s) from wind scatterometers, since extreme weather classification, surge and wave forecasts for societal warning are a high priority in nowcasting and in numerical weather prediction (NWP). A main goal of the EUMETSAT C-band High and Extreme-Force Speeds (CHEFS) study is therefore to consolidate an in-situ wind reference for assessing scatterometer high and extreme-force wind capabilities.
Scatterometers have proven to have very good performances when retrieving low to moderate winds. However, measuring high and extreme winds is still challenging as vicarious calibration is needed and calibrated in situ reference winds are scarce.
Moored buoy data are usually used as absolute reference to calibrate the scatterometer Geophysical Model Functions (GMF), however, for very high and extreme winds above 25 m/s, moored buoys may not be reliable. Moreover, controversy exists in the OSVW satellite community on the quality of moored buoys above 15 m/s rather than 25 m/s. Hence, the quality of buoy winds between 15 m/s and 25 m/s is thoroughly evaluated. The buoy wind performance, estimated with triple collocation analyses of buoy, ASCAT and ERA5 winds, shows that the quality of buoy wind vectors up to 25 m/s is within 2 m/s, indicating that buoy winds can indeed be used for wind scatterometer GMF calibration in the mentioned wind range.
The NOAA hurricane hunters fly into hurricanes to drop sondes, and thus obtain wind profiles in the lowest few kilometers of hurricanes, and operate dedicated microwave instrumentation on aircraft to obtain detailed wind patterns in hurricanes, such as the Stepped-Frequency Microwave Radiometer (SFMR). Ideally, local dropsonde winds may be statistically used to calibrate SFMR as they have similar spatial representation (“footprint”). SFMR, in turn, after spatial aggregation to scatterometer footprints, may be used to calibrate satellite scatterometers and radiometers in overflights.
The so-called WL150 algorithm is operationally used to estimate 10-m surface winds from dropsonde wind profiles. The measured radiosonde 10-m winds are a more direct calibration resource for the 10-m surface wind than WL150 estimates. However, an improved assessment of the position processing of the sonde near the surface, where its deceleration is maximum, is needed.
The air mass density needs to be considered to calibrate scatterometer winds in hurricanes, as these mainly occur at low pressures and hence low air mass density, i.e., so-called stress-equivalent winds should be used for comparison.
Finally, ASCAT winds show sensitivity to high winds, but lack good GMF calibration due to the lack of a consolidated in-situ wind reference. The saturation of the GMF at extreme winds is somehow compensated by the high calibration stability of the ASCAT instrument. As a result, further backscatter calibration refinements will support the retrieval of good-quality ASCAT winds in extreme conditions. In addition, GMF development and wind retrieval studies will be useful to improve high and extreme winds, in particular after a consolidated in-situ wind reference has been established.
How to cite: Stoffelen, A., Mouche, A., Polverari, F., van Zadelhoff, G.-J., Sapp, J., Portabella, M., Chang, P., Lin, W., and Jelenek, Z.: An In-situ Reference for High and Extreme Winds, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19174, https://doi.org/10.5194/egusphere-egu2020-19174, 2020.
EGU2020-7515 | Displays | NP6.3
The flood bore problem and the mushroom jet formation in the dam-break flowIgor Shugan, Yang-Yi Chen, and Cheng-Jung Hsu
Dam-break flows are not only an important practical problem in civil and hydraulic engineering, but also a fundamental problem of fluid mechanics. Due to property damage and the loss of numerous lives, it is critically important to have an exhaustive understanding of the landslide dam-break flow and sedimentation. The main objective of this study is a detailed analysis of the mechanisms of dam breaking flows through physical and theoretical modeling.
Our experimental work was focused on the initial stages of dam-break flow in the water channel, where a thin plate separating water at different levels is impulsively withdrawn in the vertical direction upwards, and as a result, a hydrodynamic bore is formed.
The theoretical model of the dam-break flow is based on Benney’s shallow water equations. We separately studied the regimes of a breaking and non-breaking bore front. On the hydrodynamic bore, the laws of conservation of mass, momentum and energy were required to be fulfilled,contrary to the classical solutions of Ritter and Stoker, in which the law of energy was not considered at all.
The non-breaking flow includes several zones: a shock wave and a shear vortex flow after it, a contact surface and a continuous discharge zone. The bore in our solution moves faster than the classical bore, which, in turn, propagates faster than the contact surface.
The breaking bore is characterised by the generation of a “mushroom jet” structure, including a pair of vortexes, oppositely directed, and a forerunner formed by the plunging jet directed forward. We found that the forerunner of the breaking bore has a speed significantly higher than the speed of the bore.
The experiments carried out in the wave flume of the Tainan Hydraulics Laboratory confirmed the theoretical predictions of the proposed dam breaking flow model for various initial conditions.
How to cite: Shugan, I., Chen, Y.-Y., and Hsu, C.-J.: The flood bore problem and the mushroom jet formation in the dam-break flow, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7515, https://doi.org/10.5194/egusphere-egu2020-7515, 2020.
Dam-break flows are not only an important practical problem in civil and hydraulic engineering, but also a fundamental problem of fluid mechanics. Due to property damage and the loss of numerous lives, it is critically important to have an exhaustive understanding of the landslide dam-break flow and sedimentation. The main objective of this study is a detailed analysis of the mechanisms of dam breaking flows through physical and theoretical modeling.
Our experimental work was focused on the initial stages of dam-break flow in the water channel, where a thin plate separating water at different levels is impulsively withdrawn in the vertical direction upwards, and as a result, a hydrodynamic bore is formed.
The theoretical model of the dam-break flow is based on Benney’s shallow water equations. We separately studied the regimes of a breaking and non-breaking bore front. On the hydrodynamic bore, the laws of conservation of mass, momentum and energy were required to be fulfilled,contrary to the classical solutions of Ritter and Stoker, in which the law of energy was not considered at all.
The non-breaking flow includes several zones: a shock wave and a shear vortex flow after it, a contact surface and a continuous discharge zone. The bore in our solution moves faster than the classical bore, which, in turn, propagates faster than the contact surface.
The breaking bore is characterised by the generation of a “mushroom jet” structure, including a pair of vortexes, oppositely directed, and a forerunner formed by the plunging jet directed forward. We found that the forerunner of the breaking bore has a speed significantly higher than the speed of the bore.
The experiments carried out in the wave flume of the Tainan Hydraulics Laboratory confirmed the theoretical predictions of the proposed dam breaking flow model for various initial conditions.
How to cite: Shugan, I., Chen, Y.-Y., and Hsu, C.-J.: The flood bore problem and the mushroom jet formation in the dam-break flow, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7515, https://doi.org/10.5194/egusphere-egu2020-7515, 2020.
EGU2020-5400 | Displays | NP6.3
Empirical Parameterization of the Wind-induced Drift CurrentsVladislav Polnikov and Hongyu Ma
Results of measurements of the drift currents induced by waves and wind at the wavy water surface are presented. The measurements were executed by means of surface floats in a large tank with the dimensions of 32.5x1x2 m3. Three cases were studied: (i) regular (narrow-band) mechanical waves; (ii) irregular (wide-band) mechanical waves; and (iii) wind waves.
The measured surface-drift currents induced by mechanical waves, Ud, are compared with the Stokes drift at the surface, USt, estimated by the well-known formula with the integral over a wave spectrum. In this case, it was found that ratio Ud / USt is varying in the range 0.5 – 0.93 and slightly growing with the decrease of wave steepness, having no visible dependence on the breaking intensity. These estimations are used to separate the wind-induced drift current, Udw, from the total drift at the presence of wind.
In the case of wind waves, the wind-induced part of the surface drift, Udw, is compared with the friction velocity, u*. In our measurements, the ratio Udw / u* varies systematically in the range 0.65 – 1.2. Taking into account the percentage of wave breaking, Br, the wave age, A, and the wave steepness, Ϭ = akp, it was found the parameterization: Udw = (Br + Ϭ A) u*, which corresponds to the observations with the mean error less than 10%. For the first time, this ratio provides the dependence of the surface wind drift on the surface wave parameters.
How to cite: Polnikov, V. and Ma, H.: Empirical Parameterization of the Wind-induced Drift Currents , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5400, https://doi.org/10.5194/egusphere-egu2020-5400, 2020.
Results of measurements of the drift currents induced by waves and wind at the wavy water surface are presented. The measurements were executed by means of surface floats in a large tank with the dimensions of 32.5x1x2 m3. Three cases were studied: (i) regular (narrow-band) mechanical waves; (ii) irregular (wide-band) mechanical waves; and (iii) wind waves.
The measured surface-drift currents induced by mechanical waves, Ud, are compared with the Stokes drift at the surface, USt, estimated by the well-known formula with the integral over a wave spectrum. In this case, it was found that ratio Ud / USt is varying in the range 0.5 – 0.93 and slightly growing with the decrease of wave steepness, having no visible dependence on the breaking intensity. These estimations are used to separate the wind-induced drift current, Udw, from the total drift at the presence of wind.
In the case of wind waves, the wind-induced part of the surface drift, Udw, is compared with the friction velocity, u*. In our measurements, the ratio Udw / u* varies systematically in the range 0.65 – 1.2. Taking into account the percentage of wave breaking, Br, the wave age, A, and the wave steepness, Ϭ = akp, it was found the parameterization: Udw = (Br + Ϭ A) u*, which corresponds to the observations with the mean error less than 10%. For the first time, this ratio provides the dependence of the surface wind drift on the surface wave parameters.
How to cite: Polnikov, V. and Ma, H.: Empirical Parameterization of the Wind-induced Drift Currents , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5400, https://doi.org/10.5194/egusphere-egu2020-5400, 2020.
EGU2020-3610 | Displays | NP6.3
Centrifugal Instability of a Geostrophic JetFrancis Poulin, Matthew Harris, and Kevin Lamb
Oceanic and Atmospheric jets with sufficiently strong anticyclonic vorticity are subject to centrifugal instabilities. This mechanism is relatively fast in comparison to barotropic and baroclinic instabilities and require non-conservative forces that mix the fluid properties. In this work, we present a novel approach to compute the linear stability characteristics of both barotropic and baroclinic jets. This enables us to compute the growth rates and spatial structures very accurately and efficiently. Subsequently, by integrating the fully nonlinear, non-hydrostatic dynamics using the spectrally accurate numerical model SPINS, we validate the predictions of the linear theory and then investigate the nonlinear equilibration that results. Depending on the Reynolds number of the flows, there are instances where a secondary instability occurs that eventually produces vortical structures, some of which are themselves subject to centrifugal instabilities. This idealized investigation quantifies the effects of centrifugal instabilities as an initial step to determine how to parameterize them.
How to cite: Poulin, F., Harris, M., and Lamb, K.: Centrifugal Instability of a Geostrophic Jet, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3610, https://doi.org/10.5194/egusphere-egu2020-3610, 2020.
Oceanic and Atmospheric jets with sufficiently strong anticyclonic vorticity are subject to centrifugal instabilities. This mechanism is relatively fast in comparison to barotropic and baroclinic instabilities and require non-conservative forces that mix the fluid properties. In this work, we present a novel approach to compute the linear stability characteristics of both barotropic and baroclinic jets. This enables us to compute the growth rates and spatial structures very accurately and efficiently. Subsequently, by integrating the fully nonlinear, non-hydrostatic dynamics using the spectrally accurate numerical model SPINS, we validate the predictions of the linear theory and then investigate the nonlinear equilibration that results. Depending on the Reynolds number of the flows, there are instances where a secondary instability occurs that eventually produces vortical structures, some of which are themselves subject to centrifugal instabilities. This idealized investigation quantifies the effects of centrifugal instabilities as an initial step to determine how to parameterize them.
How to cite: Poulin, F., Harris, M., and Lamb, K.: Centrifugal Instability of a Geostrophic Jet, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3610, https://doi.org/10.5194/egusphere-egu2020-3610, 2020.
EGU2020-3311 | Displays | NP6.3
Topological Waves in Astrophysical and Geophysical FlowsAntoine Venaille
Over the last decade, the concept of topological wave has spread over all fields of physics. These ideas were initially developed in condensed matter to describe peculiar electronic transport properties in exotic materials; it has now become clear that topological tools apply as well to classical systems, and thus to geophysical fluid dynamics. Topology predicts the emergence of unidirectional modes trapped along interfaces or boundaries, depending on broken discrete symmetries, and on the twisting of bulk eigenmodes. It guarantees the robustness of undirectional trapped modes against disorder, such as random topography or small scale turbulence. We will explain how to compute such topological features, discuss possible experimental realizations, and present three recent applications to geophysical flows :
- The emergence of equatorially trapped topological modes in Laplace tidal equations as a consequence of Coriolis force breaking time-reversal symmetry [1,2].
- The emergence of Lamb-like waves that connect acoustic wave bands to internal gravity waves bands in compressible-stratified fluids, as a consequence of gravity breaking miror symmetry, with potential applications in helioseismology [3] .
- A new manifestation of these topological features in geophysical ray tracing : when computing first order corrections to ray tracing, we find that rays or wave packets are deflected by an effective field corresponding to the so-called Berry curvature. To our knowledge, the effect of this Berry curvature had up to now been overlooked in geophysical context [4].
[1] P. Delplace, J.B. Marston, A. Venaille, Topological origin of equatorial waves, Science 2017
[2] C. Tauber, P. Delplace, A. Venaille, A bulk-interface correspondence for equatorial waves, Journal of Fluid Mechanics 2019
[3] M. Perrot, P. Delplace, A. Venaille, Topological transition in stratified fluids, Nature Physics 2019
[4] N. Perez, P. Delplace, A. Venaille Manifestation of Berry curvature in geophysical ray tracing, in prep. 2020
How to cite: Venaille, A.: Topological Waves in Astrophysical and Geophysical Flows, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3311, https://doi.org/10.5194/egusphere-egu2020-3311, 2020.
Over the last decade, the concept of topological wave has spread over all fields of physics. These ideas were initially developed in condensed matter to describe peculiar electronic transport properties in exotic materials; it has now become clear that topological tools apply as well to classical systems, and thus to geophysical fluid dynamics. Topology predicts the emergence of unidirectional modes trapped along interfaces or boundaries, depending on broken discrete symmetries, and on the twisting of bulk eigenmodes. It guarantees the robustness of undirectional trapped modes against disorder, such as random topography or small scale turbulence. We will explain how to compute such topological features, discuss possible experimental realizations, and present three recent applications to geophysical flows :
- The emergence of equatorially trapped topological modes in Laplace tidal equations as a consequence of Coriolis force breaking time-reversal symmetry [1,2].
- The emergence of Lamb-like waves that connect acoustic wave bands to internal gravity waves bands in compressible-stratified fluids, as a consequence of gravity breaking miror symmetry, with potential applications in helioseismology [3] .
- A new manifestation of these topological features in geophysical ray tracing : when computing first order corrections to ray tracing, we find that rays or wave packets are deflected by an effective field corresponding to the so-called Berry curvature. To our knowledge, the effect of this Berry curvature had up to now been overlooked in geophysical context [4].
[1] P. Delplace, J.B. Marston, A. Venaille, Topological origin of equatorial waves, Science 2017
[2] C. Tauber, P. Delplace, A. Venaille, A bulk-interface correspondence for equatorial waves, Journal of Fluid Mechanics 2019
[3] M. Perrot, P. Delplace, A. Venaille, Topological transition in stratified fluids, Nature Physics 2019
[4] N. Perez, P. Delplace, A. Venaille Manifestation of Berry curvature in geophysical ray tracing, in prep. 2020
How to cite: Venaille, A.: Topological Waves in Astrophysical and Geophysical Flows, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3311, https://doi.org/10.5194/egusphere-egu2020-3311, 2020.
EGU2020-9366 | Displays | NP6.3
Planetary geostrophic Boussinesq dynamics: barotropic flow, baroclinic instability and forced stationary wavesStamen Dolaptchiev, Ulrich Achatz, and Thomas Reitz
Motions on planetary spatial scales in the atmosphere are governed by
the planetary geostrophic equations. However, not much attention has
been paid to the interaction between the baroclinic and barotropic
flow within the planetary geostrophic scaling. This is the focus of
the present study by utilizing planetary geostrophic equations for a
Boussinesq fluid supplemented by an asymptotically derived evolution
equation for the barotropic flow. The latter is effected by meridional
momentum flux due to baroclinic flow and drag by the surface wind. The
barotropic wind on the other hand affects the baroclinic flow through
buoyancy advection. By relaxing towards a prescribed buoyancy profile
the model produces realistic major features of the zonally symmetric
wind and temperature fields. We show that there is considerable
cancelation between the barotropic and the baroclinic surface zonal
mean zonal wind. The linear and nonlinear model response to steady
diabatic zonally asymmetric forcing is investigated. The arising
stationary waves are interpreted in terms of analytical solutions. We
also study the problem of baroclinic instability on the sphere within
the present model.
Reference: Dolaptchiev, S. I., Achatz, U. and Th. Reitz, 2019: Planetary
geostrophic Boussinesq dynamics: barotropic flow, baroclinic
instability and forced stationary waves, Quart. J. Roy. Met. Soc., 145: 3751-3765.
How to cite: Dolaptchiev, S., Achatz, U., and Reitz, T.: Planetary geostrophic Boussinesq dynamics: barotropic flow, baroclinic instability and forced stationary waves, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9366, https://doi.org/10.5194/egusphere-egu2020-9366, 2020.
Motions on planetary spatial scales in the atmosphere are governed by
the planetary geostrophic equations. However, not much attention has
been paid to the interaction between the baroclinic and barotropic
flow within the planetary geostrophic scaling. This is the focus of
the present study by utilizing planetary geostrophic equations for a
Boussinesq fluid supplemented by an asymptotically derived evolution
equation for the barotropic flow. The latter is effected by meridional
momentum flux due to baroclinic flow and drag by the surface wind. The
barotropic wind on the other hand affects the baroclinic flow through
buoyancy advection. By relaxing towards a prescribed buoyancy profile
the model produces realistic major features of the zonally symmetric
wind and temperature fields. We show that there is considerable
cancelation between the barotropic and the baroclinic surface zonal
mean zonal wind. The linear and nonlinear model response to steady
diabatic zonally asymmetric forcing is investigated. The arising
stationary waves are interpreted in terms of analytical solutions. We
also study the problem of baroclinic instability on the sphere within
the present model.
Reference: Dolaptchiev, S. I., Achatz, U. and Th. Reitz, 2019: Planetary
geostrophic Boussinesq dynamics: barotropic flow, baroclinic
instability and forced stationary waves, Quart. J. Roy. Met. Soc., 145: 3751-3765.
How to cite: Dolaptchiev, S., Achatz, U., and Reitz, T.: Planetary geostrophic Boussinesq dynamics: barotropic flow, baroclinic instability and forced stationary waves, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9366, https://doi.org/10.5194/egusphere-egu2020-9366, 2020.
EGU2020-5004 | Displays | NP6.3 | Highlight
Climate impact of the Drake Passage opening: lessons from a minimalistic laboratory experimentMiklos Vincze, Tamás Bozóki, Mátyás Herein, Ion Dan Borcia, Costanza Rodda, József Pálfy, Anita Nyerges, and Uwe Harlander
The differentially heated rotating annulus is a widely studied experimental set-up designed to model mid-latitude circulation in the atmosphere and the ocean. By installing an insulating "meridional" barrier in this cylindrical tank, one can construct a minimal model of the large-scale flow phenomena in the Southern Ocean with a closed Drake Passage, imitating the situation before the Eocene-Oligocene transition (EOT) ca. 34 million years ago. We find that in this "closed" case a persistent azimuthal temperature gradient emerges whose magnitude scales linearly with the "meridional" temperature contrast. Furthermore, seemingly contradicting paleoclimatic data, the presence of the barrier appears to yield lower values of "sea surface temperature" in the tank than those in the "opened" control experiments (whereas the actual opening of the passage coincides with a major cooling event). This difference points to the importance of the role ice-albedo feedback plays in an EOT-like transition, an aspect that is not captured in the laboratory setting. This idea appears to be confirmed by numerical simulations conducted in a medium complexity GCM, where the comparison of "closed" on "opened" configurations could be made both with and without sea ice feedback. These runs indeed yielded opposite effects on sea-surface temperature and are therefore consistent with both the laboratory experiment and the paleoclimate data. This finding may well be relevant for the better understanding of the actual EOT dynamics.
How to cite: Vincze, M., Bozóki, T., Herein, M., Borcia, I. D., Rodda, C., Pálfy, J., Nyerges, A., and Harlander, U.: Climate impact of the Drake Passage opening: lessons from a minimalistic laboratory experiment, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5004, https://doi.org/10.5194/egusphere-egu2020-5004, 2020.
The differentially heated rotating annulus is a widely studied experimental set-up designed to model mid-latitude circulation in the atmosphere and the ocean. By installing an insulating "meridional" barrier in this cylindrical tank, one can construct a minimal model of the large-scale flow phenomena in the Southern Ocean with a closed Drake Passage, imitating the situation before the Eocene-Oligocene transition (EOT) ca. 34 million years ago. We find that in this "closed" case a persistent azimuthal temperature gradient emerges whose magnitude scales linearly with the "meridional" temperature contrast. Furthermore, seemingly contradicting paleoclimatic data, the presence of the barrier appears to yield lower values of "sea surface temperature" in the tank than those in the "opened" control experiments (whereas the actual opening of the passage coincides with a major cooling event). This difference points to the importance of the role ice-albedo feedback plays in an EOT-like transition, an aspect that is not captured in the laboratory setting. This idea appears to be confirmed by numerical simulations conducted in a medium complexity GCM, where the comparison of "closed" on "opened" configurations could be made both with and without sea ice feedback. These runs indeed yielded opposite effects on sea-surface temperature and are therefore consistent with both the laboratory experiment and the paleoclimate data. This finding may well be relevant for the better understanding of the actual EOT dynamics.
How to cite: Vincze, M., Bozóki, T., Herein, M., Borcia, I. D., Rodda, C., Pálfy, J., Nyerges, A., and Harlander, U.: Climate impact of the Drake Passage opening: lessons from a minimalistic laboratory experiment, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5004, https://doi.org/10.5194/egusphere-egu2020-5004, 2020.
EGU2020-20799 | Displays | NP6.3
A reduced-order model of the zonal jets problem in the Southern OceanElnaz Naghibi, Sergey Karabasov, and Igor Kamenkovich
We introduce a reduced-order model of the underlying dynamics of zonal jets in the Southern Ocean. The model is based on multi-scale decomposition in the vorticity equation and explains how large-scale forcing breaks down into mesoscale eddies and alternating zonal jets. In this reduced-order model, we average the vorticity equation both in time and in the zonal direction and utilize eddy viscosity parametrization for turbulence closure. For verification, we compare our results with two high-fidelity models: i) the quasi-geostrophic model of a shear-driven periodic channel flow and ii) primitive equation HYCOM (HYbrid Coordinate Ocean Model) simulations of the Southern Ocean.
How to cite: Naghibi, E., Karabasov, S., and Kamenkovich, I.: A reduced-order model of the zonal jets problem in the Southern Ocean, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20799, https://doi.org/10.5194/egusphere-egu2020-20799, 2020.
We introduce a reduced-order model of the underlying dynamics of zonal jets in the Southern Ocean. The model is based on multi-scale decomposition in the vorticity equation and explains how large-scale forcing breaks down into mesoscale eddies and alternating zonal jets. In this reduced-order model, we average the vorticity equation both in time and in the zonal direction and utilize eddy viscosity parametrization for turbulence closure. For verification, we compare our results with two high-fidelity models: i) the quasi-geostrophic model of a shear-driven periodic channel flow and ii) primitive equation HYCOM (HYbrid Coordinate Ocean Model) simulations of the Southern Ocean.
How to cite: Naghibi, E., Karabasov, S., and Kamenkovich, I.: A reduced-order model of the zonal jets problem in the Southern Ocean, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20799, https://doi.org/10.5194/egusphere-egu2020-20799, 2020.
EGU2020-21191 | Displays | NP6.3
Macroturbulence Response to Vertical Stratification Change Using Linear Response Function of an Idealized Dry AtmospherePak-Wah Chan, Pedram Hassanzadeh, and Zhiming Kuang
Rossby radius and Rhines scale are two popular scaling arguments for eddy length scale. They have not been tested in a well-controlled experiment with increased vertical stratification and unchanged jet. This is done using the linear response function of an idealized dry atmosphere calculated by Hassanzadeh and Kuang (2016). The resulting change in zonal wind is mostly less than 0.2m/s when temperature near surface is cooled by more than 2K. In such experiment, energy-containing zonal scale decreases, which is against the prediction of Rossby radius but consistent with the prediction of Rhines scale. Eddy kinetic energy decreases for all wavenumbers and latitudes, but eddy momentum flux strengthens locally around zonal wavenumber 8 and 40°S. This local strengthening is associated with a stronger Pearson correlation between u and v.
How to cite: Chan, P.-W., Hassanzadeh, P., and Kuang, Z.: Macroturbulence Response to Vertical Stratification Change Using Linear Response Function of an Idealized Dry Atmosphere, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21191, https://doi.org/10.5194/egusphere-egu2020-21191, 2020.
Rossby radius and Rhines scale are two popular scaling arguments for eddy length scale. They have not been tested in a well-controlled experiment with increased vertical stratification and unchanged jet. This is done using the linear response function of an idealized dry atmosphere calculated by Hassanzadeh and Kuang (2016). The resulting change in zonal wind is mostly less than 0.2m/s when temperature near surface is cooled by more than 2K. In such experiment, energy-containing zonal scale decreases, which is against the prediction of Rossby radius but consistent with the prediction of Rhines scale. Eddy kinetic energy decreases for all wavenumbers and latitudes, but eddy momentum flux strengthens locally around zonal wavenumber 8 and 40°S. This local strengthening is associated with a stronger Pearson correlation between u and v.
How to cite: Chan, P.-W., Hassanzadeh, P., and Kuang, Z.: Macroturbulence Response to Vertical Stratification Change Using Linear Response Function of an Idealized Dry Atmosphere, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21191, https://doi.org/10.5194/egusphere-egu2020-21191, 2020.
EGU2020-4709 | Displays | NP6.3
The spacing of streaks in wind waves from low to high windWu-ting Tsai and Guan-hung Lu
Quasi-streamwise vortices within aqueous shear layer beneath wind waves are found to contribute significantly to the scalar transfer across the air-water interface. These streamwise vortices manifest themselves by inducing distinct elongated high-speed streaks on the interface. The density of these streaks, which can be quantified by the transverse spacing of streaks, thus characterizes the interfacial scalar transfer contributed by the quasi-streamwise vortices. Thermal imageries of laboratory wind waves and flow fields obtained from numerical simulations of turbulent shear flows bounded by stress-driven flat boundary and wavy surface are utilized to study the characteristics of streak spacings and their dependence on wind speed. Consistent with previous studies, analyses of the thermal imageries of laboratory wind waves confirm that the streak spacings conform closely to a lognormal distribution, and the mean streak spacing d decreases as the wind speed increases. Revisiting the nondimensional mean spacing scaled by the viscous length, d+=du*/ν, where u* is the shear velocity of water and ν is the kinematic viscosity of water, however, reveals the different interpretations from the previous studies. For low to immediate wind-speed range,u*< 0.5 cm/s, the nondimensional mean spacing does not follow the scaling of d+≈ 100 observed in the turbulent wall layer; the scaled mean spacing d+< 100. This is also observed in numerical simulation of turbulent shear flow bounded by a stress-driven flat surface. For immediate wind-speed range, 0.5 cm/s < u*< 1.2 cm/s, within which surface waves become significant, the nondimensional mean streak spacings derived from the thermal imageries of wind waves remain to be less than the universal value of 100. The scaled mean streak spacing of simulated turbulent shear layer next to a stress-driven plane boundary, however, increases with the wind speed and approaches the value of 100 at this immediate wind-speed range. Imposing surface waves on the simulated turbulent shear flow significantly reduces the nondimensional streak spacing as observed on the wind-wave surfaces. Such reduction of streak spacings in finite-amplitude wind waves can be attributed to the additional wave stress arising in the oscillatory boundary layer, and the turning and stretching of turbulent vortices by the Lagrangian drift of progressive waves. At high wind speeds, u* > 1.2 cm/s, despite the occurrence of wave breaking, the scaled mean spacing approaches the universal value of 100 observed in the turbulent wall layer. This work was supported by the Taiwan Ministry of Science and Technology (MOST 107-2611-M-002 -014 -MY3).
How to cite: Tsai, W. and Lu, G.: The spacing of streaks in wind waves from low to high wind, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4709, https://doi.org/10.5194/egusphere-egu2020-4709, 2020.
Quasi-streamwise vortices within aqueous shear layer beneath wind waves are found to contribute significantly to the scalar transfer across the air-water interface. These streamwise vortices manifest themselves by inducing distinct elongated high-speed streaks on the interface. The density of these streaks, which can be quantified by the transverse spacing of streaks, thus characterizes the interfacial scalar transfer contributed by the quasi-streamwise vortices. Thermal imageries of laboratory wind waves and flow fields obtained from numerical simulations of turbulent shear flows bounded by stress-driven flat boundary and wavy surface are utilized to study the characteristics of streak spacings and their dependence on wind speed. Consistent with previous studies, analyses of the thermal imageries of laboratory wind waves confirm that the streak spacings conform closely to a lognormal distribution, and the mean streak spacing d decreases as the wind speed increases. Revisiting the nondimensional mean spacing scaled by the viscous length, d+=du*/ν, where u* is the shear velocity of water and ν is the kinematic viscosity of water, however, reveals the different interpretations from the previous studies. For low to immediate wind-speed range,u*< 0.5 cm/s, the nondimensional mean spacing does not follow the scaling of d+≈ 100 observed in the turbulent wall layer; the scaled mean spacing d+< 100. This is also observed in numerical simulation of turbulent shear flow bounded by a stress-driven flat surface. For immediate wind-speed range, 0.5 cm/s < u*< 1.2 cm/s, within which surface waves become significant, the nondimensional mean streak spacings derived from the thermal imageries of wind waves remain to be less than the universal value of 100. The scaled mean streak spacing of simulated turbulent shear layer next to a stress-driven plane boundary, however, increases with the wind speed and approaches the value of 100 at this immediate wind-speed range. Imposing surface waves on the simulated turbulent shear flow significantly reduces the nondimensional streak spacing as observed on the wind-wave surfaces. Such reduction of streak spacings in finite-amplitude wind waves can be attributed to the additional wave stress arising in the oscillatory boundary layer, and the turning and stretching of turbulent vortices by the Lagrangian drift of progressive waves. At high wind speeds, u* > 1.2 cm/s, despite the occurrence of wave breaking, the scaled mean spacing approaches the universal value of 100 observed in the turbulent wall layer. This work was supported by the Taiwan Ministry of Science and Technology (MOST 107-2611-M-002 -014 -MY3).
How to cite: Tsai, W. and Lu, G.: The spacing of streaks in wind waves from low to high wind, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4709, https://doi.org/10.5194/egusphere-egu2020-4709, 2020.
EGU2020-6571 | Displays | NP6.3
Spatial and statistical analysis of coherent vortical structures within a stress-driven free-surface turbulent shear flowPo-Chen Chen and Wu-ting Tsai
The water surface under high wind condition is characterized by elongated high-speed streaks and randomly emerged low-speed streaks, which are attributed to underneath coherent vortical motions. These vortical structures within aqueous turbulent boundary layer plays a critical role in turbulent exchange, their characteristics and statistics are therefore of interest in this study. Direct numerical simulation of an aqueous turbulent flow bounded by a stress-driven flat free surface was performed. Simulation results of cases with high wind condition (surface friction velocity = 1.22 cm/s) as well as weak wind condition (surface friction velocity = 0.71 cm/s) are analyzed. To identify the underlying vortical structures, an indicator of swirling strength derived from local velocity-gradient tensor is adopted. A formal classification scheme, based on the topological geometry of the vortex core, is then applied to classify the identified structures. Surface layers with the two wind conditions reveal similar results in statistics and spatial distribution of vortical structures. Two types of characteristic vortices which induce the surface streaks are extracted, including quasi-streamwise vortex and reversed horseshoe vortex (head pointing upstream), most inclining at about 10 to 20 degrees. Quasi-streamwise vortices are the dominant structure, and both high- and low-speed streaks are fringed with such vortices; they adjoin the surface streaks as counter-rotating arrays in either staggered or side-by-side spatial arrangement. The length of quasi-streamwise vortices, however, are significantly shorter than the corresponding surface streaks, only 10% of the extracted quasi-streamwise vortices are longer than 150 wall units. Reversed horseshoe vortices, associated with downwelling motions and surface convergence, are located beneath the high-speed streaks. In contrast to the turbulent boundary layer next to a flat wall, typical forward horseshoe vortices (head pointing downstream) associated with upwelling motions are barely found within the free-surface turbulent shear flow.
This work was supported by the Taiwan Ministry of Science and Technology (MOST 107-2611-M-002 -014 -MY3).
How to cite: Chen, P.-C. and Tsai, W.: Spatial and statistical analysis of coherent vortical structures within a stress-driven free-surface turbulent shear flow, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6571, https://doi.org/10.5194/egusphere-egu2020-6571, 2020.
The water surface under high wind condition is characterized by elongated high-speed streaks and randomly emerged low-speed streaks, which are attributed to underneath coherent vortical motions. These vortical structures within aqueous turbulent boundary layer plays a critical role in turbulent exchange, their characteristics and statistics are therefore of interest in this study. Direct numerical simulation of an aqueous turbulent flow bounded by a stress-driven flat free surface was performed. Simulation results of cases with high wind condition (surface friction velocity = 1.22 cm/s) as well as weak wind condition (surface friction velocity = 0.71 cm/s) are analyzed. To identify the underlying vortical structures, an indicator of swirling strength derived from local velocity-gradient tensor is adopted. A formal classification scheme, based on the topological geometry of the vortex core, is then applied to classify the identified structures. Surface layers with the two wind conditions reveal similar results in statistics and spatial distribution of vortical structures. Two types of characteristic vortices which induce the surface streaks are extracted, including quasi-streamwise vortex and reversed horseshoe vortex (head pointing upstream), most inclining at about 10 to 20 degrees. Quasi-streamwise vortices are the dominant structure, and both high- and low-speed streaks are fringed with such vortices; they adjoin the surface streaks as counter-rotating arrays in either staggered or side-by-side spatial arrangement. The length of quasi-streamwise vortices, however, are significantly shorter than the corresponding surface streaks, only 10% of the extracted quasi-streamwise vortices are longer than 150 wall units. Reversed horseshoe vortices, associated with downwelling motions and surface convergence, are located beneath the high-speed streaks. In contrast to the turbulent boundary layer next to a flat wall, typical forward horseshoe vortices (head pointing downstream) associated with upwelling motions are barely found within the free-surface turbulent shear flow.
This work was supported by the Taiwan Ministry of Science and Technology (MOST 107-2611-M-002 -014 -MY3).
How to cite: Chen, P.-C. and Tsai, W.: Spatial and statistical analysis of coherent vortical structures within a stress-driven free-surface turbulent shear flow, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6571, https://doi.org/10.5194/egusphere-egu2020-6571, 2020.
EGU2020-7591 | Displays | NP6.3
Non-linear resonant instability of short surface waves as the first stage “bag-breakup” process at the air-sea interface at high windsDmitry Kozlov and Yulia Troitskaya
The recent experimental study [1], [2] identify ‘‘bag breakup’’ fragmentation as the dominant mechanism by which spume droplets are generated at hurricane wind speeds. These droplets can significantly affect the exchanging processes in the air-ocean boundary layer. In order to estimate spray-mediated heat, momentum and mass fluxes we need not only reliable experimental data, but a theoretical model of this process. The “bag-breakup” fragmentation is a strongly non-linear process, and we focus only on its first stage which includes the small-scale elevation of the water surface.
Our model of the bag’s initiation is based on a weak nonlinear interaction of a longitudinal surface wave and two oblique waves propagating at equal and opposite angles to the flow as it was done in [3], [4]. All of these waves have the same critical layer where cross velocities of oblique waves become infinite making inviscid analysis invalid. So we took into account viscous effects. As a result, it has been established that for a piecewise continuous velocity profile explosive growth of wave amplitudes is possible at the wind speeds exceeding the critical one.
The present model let us find the dependency of “bag’s” transverse size on the wind speed and estimate its lifetime.
Acknowledgements
This work was supported by the RSF project 19-17-00209 and the RFBR projects 19-05-00249, 19-35-90053, 18-05-00265.
References:
How to cite: Kozlov, D. and Troitskaya, Y.: Non-linear resonant instability of short surface waves as the first stage “bag-breakup” process at the air-sea interface at high winds , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7591, https://doi.org/10.5194/egusphere-egu2020-7591, 2020.
The recent experimental study [1], [2] identify ‘‘bag breakup’’ fragmentation as the dominant mechanism by which spume droplets are generated at hurricane wind speeds. These droplets can significantly affect the exchanging processes in the air-ocean boundary layer. In order to estimate spray-mediated heat, momentum and mass fluxes we need not only reliable experimental data, but a theoretical model of this process. The “bag-breakup” fragmentation is a strongly non-linear process, and we focus only on its first stage which includes the small-scale elevation of the water surface.
Our model of the bag’s initiation is based on a weak nonlinear interaction of a longitudinal surface wave and two oblique waves propagating at equal and opposite angles to the flow as it was done in [3], [4]. All of these waves have the same critical layer where cross velocities of oblique waves become infinite making inviscid analysis invalid. So we took into account viscous effects. As a result, it has been established that for a piecewise continuous velocity profile explosive growth of wave amplitudes is possible at the wind speeds exceeding the critical one.
The present model let us find the dependency of “bag’s” transverse size on the wind speed and estimate its lifetime.
Acknowledgements
This work was supported by the RSF project 19-17-00209 and the RFBR projects 19-05-00249, 19-35-90053, 18-05-00265.
References:
How to cite: Kozlov, D. and Troitskaya, Y.: Non-linear resonant instability of short surface waves as the first stage “bag-breakup” process at the air-sea interface at high winds , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7591, https://doi.org/10.5194/egusphere-egu2020-7591, 2020.
EGU2020-8589 | Displays | NP6.3
Laboratory investigation of air-sea momentum transfer under severe wind conditionsMaksim Vdovin, Georgy Baydakov, Daniil Sergeev, and Yuliya Troitskaya
Wind-wave interaction at extreme wind speed is of special interest now in connection with the problem of explanation of the sea surface drag saturation at the wind speed exceeding 30 m/s. Now it is established that at hurricane wind speed the sea surface drag coefficient is significantly reduced in comparison with the parameterization obtained at moderate to strong wind conditions.
The subject of this work is investigation of aerodynamic resistance of the waved water surface under severe wind conditions (up to U10 ≈ 50 m/s). Laboratory experiments were carried out at the new high-speed wind-wave flume in the Large Thermally Stratified Tank (at the Institute of Applied Physics, Russia) built in 2019. The main difference between the new wind-wave flume and the old one is the absence of a pressure gradient along the main axis of the new flume. Aerodynamic resistance of the water surface was measured by the profile method with Pitot tube. A method for data processing taking into account the self-similarity of the air flow velocity profile in the aerodynamic tube was applied for retrieving wind friction velocity and surface drag coefficients. Simultaneously with the airflow velocity measurements, the wind-wave field parameters in the flume were investigated by system of wire gauges.
Analysis of the wind velocity profiles and wind-wave spectra showed tendency to decrease for surface drag coefficient for wind speed exceeding 25 m/s simultaneously with the mean square slope and significant wave height.
Acknowledgments
This work was carried out with the financial support of the RFBR according to the research project 18-55-50005, 20-05-00322, 18-35-20068, 18-05-00265. Data processing was carried out with the financial support of Russian Science Foundation grant 19-17-00209.
How to cite: Vdovin, M., Baydakov, G., Sergeev, D., and Troitskaya, Y.: Laboratory investigation of air-sea momentum transfer under severe wind conditions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8589, https://doi.org/10.5194/egusphere-egu2020-8589, 2020.
Wind-wave interaction at extreme wind speed is of special interest now in connection with the problem of explanation of the sea surface drag saturation at the wind speed exceeding 30 m/s. Now it is established that at hurricane wind speed the sea surface drag coefficient is significantly reduced in comparison with the parameterization obtained at moderate to strong wind conditions.
The subject of this work is investigation of aerodynamic resistance of the waved water surface under severe wind conditions (up to U10 ≈ 50 m/s). Laboratory experiments were carried out at the new high-speed wind-wave flume in the Large Thermally Stratified Tank (at the Institute of Applied Physics, Russia) built in 2019. The main difference between the new wind-wave flume and the old one is the absence of a pressure gradient along the main axis of the new flume. Aerodynamic resistance of the water surface was measured by the profile method with Pitot tube. A method for data processing taking into account the self-similarity of the air flow velocity profile in the aerodynamic tube was applied for retrieving wind friction velocity and surface drag coefficients. Simultaneously with the airflow velocity measurements, the wind-wave field parameters in the flume were investigated by system of wire gauges.
Analysis of the wind velocity profiles and wind-wave spectra showed tendency to decrease for surface drag coefficient for wind speed exceeding 25 m/s simultaneously with the mean square slope and significant wave height.
Acknowledgments
This work was carried out with the financial support of the RFBR according to the research project 18-55-50005, 20-05-00322, 18-35-20068, 18-05-00265. Data processing was carried out with the financial support of Russian Science Foundation grant 19-17-00209.
How to cite: Vdovin, M., Baydakov, G., Sergeev, D., and Troitskaya, Y.: Laboratory investigation of air-sea momentum transfer under severe wind conditions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8589, https://doi.org/10.5194/egusphere-egu2020-8589, 2020.
EGU2020-8767 | Displays | NP6.3
Quasi-three-dimensional simulation of crescent-shaped wavesAlexander Dosaev and Yuliya Troitskaya
Many features of nonlinear water wave dynamics can be explained within the assumption that the motion of fluid is strictly potential. At the same time, numerically solving exact equations of motion for a three-dimensional potential flow with a free surface (by means of, for example, boundary integral method) is still often considered too computationally expensive, and further simplifications are made, usually implying limitations on wave steepness. A quasi-three-dimensional model, put forward by V. P. Ruban [1], represents another approach at reducing computational cost. It is, in its essence, a two-dimensional model, formulated using conformal mapping of the flow domain, augmented by three-dimensional corrections. The model assumes narrow directional distribution of the wave field and is exact for two-dimensional waves. It was successfully applied by its author to study a nonlinear stage of of Benjamin-Feir instability and rogue waves formation.
The main aim of the present work is to explore the behaviour of the quasi-three-dimensional model outside the formal limits of its applicability. From the practical point of view, it is important that the model operates robustly even in the presence of waves propagating at large angles to the main direction (although we do not attempt to accurately describe their dynamics). We investigate linear stability of Stokes waves to three-dimensional perturbations and suggest a modification to the original model to eliminate a spurious zone of instability in the vicinity of the perpendicular direction on the perturbation wavenumber plane. We show that the quasi-three-dimensional model yields a qualitatively correct description of the instability zone generated by resonant 5-wave interactions. The values of the increment are reasonably close to those obtained from the exact equations of motion [2], despite the fact that the corresponding modes of instability consist of harmonics that are relatively far from the main direction. Resonant 5-wave interactions are known to manifest themselves in the formation of the so-called “horse-shoe” or “crescent-shaped” wave patterns, and the quasi-three-dimensional model exhibits a plausible dynamics leading to formation of crescent-shaped waves.
This research was supported by RFBR (grant No. 20-05-00322).
[1] Ruban, V. P. (2010). Conformal variables in the numerical simulations of long-crested rogue waves. The European Physical Journal Special Topics, 185(1), 17-33.
[2] McLean, J. W. (1982). Instabilities of finite-amplitude water waves. Journal of Fluid Mechanics, 114, 315-330.
How to cite: Dosaev, A. and Troitskaya, Y.: Quasi-three-dimensional simulation of crescent-shaped waves, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8767, https://doi.org/10.5194/egusphere-egu2020-8767, 2020.
Many features of nonlinear water wave dynamics can be explained within the assumption that the motion of fluid is strictly potential. At the same time, numerically solving exact equations of motion for a three-dimensional potential flow with a free surface (by means of, for example, boundary integral method) is still often considered too computationally expensive, and further simplifications are made, usually implying limitations on wave steepness. A quasi-three-dimensional model, put forward by V. P. Ruban [1], represents another approach at reducing computational cost. It is, in its essence, a two-dimensional model, formulated using conformal mapping of the flow domain, augmented by three-dimensional corrections. The model assumes narrow directional distribution of the wave field and is exact for two-dimensional waves. It was successfully applied by its author to study a nonlinear stage of of Benjamin-Feir instability and rogue waves formation.
The main aim of the present work is to explore the behaviour of the quasi-three-dimensional model outside the formal limits of its applicability. From the practical point of view, it is important that the model operates robustly even in the presence of waves propagating at large angles to the main direction (although we do not attempt to accurately describe their dynamics). We investigate linear stability of Stokes waves to three-dimensional perturbations and suggest a modification to the original model to eliminate a spurious zone of instability in the vicinity of the perpendicular direction on the perturbation wavenumber plane. We show that the quasi-three-dimensional model yields a qualitatively correct description of the instability zone generated by resonant 5-wave interactions. The values of the increment are reasonably close to those obtained from the exact equations of motion [2], despite the fact that the corresponding modes of instability consist of harmonics that are relatively far from the main direction. Resonant 5-wave interactions are known to manifest themselves in the formation of the so-called “horse-shoe” or “crescent-shaped” wave patterns, and the quasi-three-dimensional model exhibits a plausible dynamics leading to formation of crescent-shaped waves.
This research was supported by RFBR (grant No. 20-05-00322).
[1] Ruban, V. P. (2010). Conformal variables in the numerical simulations of long-crested rogue waves. The European Physical Journal Special Topics, 185(1), 17-33.
[2] McLean, J. W. (1982). Instabilities of finite-amplitude water waves. Journal of Fluid Mechanics, 114, 315-330.
How to cite: Dosaev, A. and Troitskaya, Y.: Quasi-three-dimensional simulation of crescent-shaped waves, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8767, https://doi.org/10.5194/egusphere-egu2020-8767, 2020.
EGU2020-9341 | Displays | NP6.3
Comparison between the sea-breeze circulation day and normal day Reynolds stress anisotropy in the lower atmospheric regionSayahnya Roy, Alexei Sentchev, François G. Schmitt, Patrick Augustin, and Marc Fourmentin
This study shows the comparison between the sea-breeze circulation (SBC) day and normal day turbulent characteristics and the Reynolds stress anisotropy in the lower atmospheric region. The Reynolds stress tensor is responsible for the dissipation and transport of mean kinetic energy. The variability of the turbulent kinetic energy due to the Reynolds stress anisotropy modulates the air quality. A 20 Hz Ultrasonic anemometer was deployed in the coastal area of northern France to measure the temporal wind variability for the duration of one year five months.
The SBC was detected by a change in wind direction from the West to the East during the day time. We found that the axial component of the turbulent kinetic energy is higher than the other two through an axisymmetric expansion, and energy ellipsoid has a cigar shape due to SBC. During this time the dominance of small scale zonal turbulent motions was observed. Also, the probability of a higher degree of wind anisotropy due to SBC generates large mean kinetic energy within the lower troposphere. Moreover, the production of larger negative turbulent kinetic energy due to SBC was evident.
How to cite: Roy, S., Sentchev, A., Schmitt, F. G., Augustin, P., and Fourmentin, M.: Comparison between the sea-breeze circulation day and normal day Reynolds stress anisotropy in the lower atmospheric region, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9341, https://doi.org/10.5194/egusphere-egu2020-9341, 2020.
This study shows the comparison between the sea-breeze circulation (SBC) day and normal day turbulent characteristics and the Reynolds stress anisotropy in the lower atmospheric region. The Reynolds stress tensor is responsible for the dissipation and transport of mean kinetic energy. The variability of the turbulent kinetic energy due to the Reynolds stress anisotropy modulates the air quality. A 20 Hz Ultrasonic anemometer was deployed in the coastal area of northern France to measure the temporal wind variability for the duration of one year five months.
The SBC was detected by a change in wind direction from the West to the East during the day time. We found that the axial component of the turbulent kinetic energy is higher than the other two through an axisymmetric expansion, and energy ellipsoid has a cigar shape due to SBC. During this time the dominance of small scale zonal turbulent motions was observed. Also, the probability of a higher degree of wind anisotropy due to SBC generates large mean kinetic energy within the lower troposphere. Moreover, the production of larger negative turbulent kinetic energy due to SBC was evident.
How to cite: Roy, S., Sentchev, A., Schmitt, F. G., Augustin, P., and Fourmentin, M.: Comparison between the sea-breeze circulation day and normal day Reynolds stress anisotropy in the lower atmospheric region, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9341, https://doi.org/10.5194/egusphere-egu2020-9341, 2020.
EGU2020-11860 | Displays | NP6.3
Laboratory simulation of the pancake ice influence on the wind wave interactionDaniil Sergeev, Yuliya Troitskaya, and Alexander Kandaurov
Recently, much attention has been paid to the study and numerical simulation of wind waves in the Arctic regions of the oceans. Their distinctive feature is the presence of ice cover of various types, which can significantly affect the processes of wind wave interaction, including momentum exchange. A detailed study of such processes under natural conditions is very difficult, especially for the forming ice (including pancake ice), therefore, laboratory simulation is preferable. Previously studies of the influence of floating ice on the evolution of waves that were generated by wavemakers were carried out only. In this paper we present preliminary results of studies performed on the AELOTRON circular wind wave flume of the University of Heidelberg, where the interaction of air flow with a water surface was simulated for the first time in the presence of forming ice of the pancake type. Synchronous measurements of wave characteristics were carried out using a laser wavegauge, as well as airflow velocity fields were measured with PIV-methods. Shims made of rubber with a diameter of 7 cm and a thickness of 1 cm with a density of about 0.8 kg /m3 were used as elements of artificial ice. The measurements were carried out in clean water and at three concentrations of artificial ice: maximum, 2/3 of the maximum, 1/3 of the maximum. Ice covered about half the surface at maximum concentration. The measurements were carried out in the range of equivalent wind speeds U10 from 7 to 16 m/s. The threshold character of excitation of long waves was obtained (the length is much greater than the average distance between the elements of ice). The higher the density, the higher the threshold for wind speed. According to the results of processing the velocity fields, the dependence of the aerodynamic drag coefficient on the equivalent wind speed was constructed. It is shown that the presence of ice weakly affects the momentum exchange for all concentrations and over the entire wind speed range.
Investigation was supported by Russian Found Basic Research project # 18-05-60299 Arctic.
How to cite: Sergeev, D., Troitskaya, Y., and Kandaurov, A.: Laboratory simulation of the pancake ice influence on the wind wave interaction, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11860, https://doi.org/10.5194/egusphere-egu2020-11860, 2020.
Recently, much attention has been paid to the study and numerical simulation of wind waves in the Arctic regions of the oceans. Their distinctive feature is the presence of ice cover of various types, which can significantly affect the processes of wind wave interaction, including momentum exchange. A detailed study of such processes under natural conditions is very difficult, especially for the forming ice (including pancake ice), therefore, laboratory simulation is preferable. Previously studies of the influence of floating ice on the evolution of waves that were generated by wavemakers were carried out only. In this paper we present preliminary results of studies performed on the AELOTRON circular wind wave flume of the University of Heidelberg, where the interaction of air flow with a water surface was simulated for the first time in the presence of forming ice of the pancake type. Synchronous measurements of wave characteristics were carried out using a laser wavegauge, as well as airflow velocity fields were measured with PIV-methods. Shims made of rubber with a diameter of 7 cm and a thickness of 1 cm with a density of about 0.8 kg /m3 were used as elements of artificial ice. The measurements were carried out in clean water and at three concentrations of artificial ice: maximum, 2/3 of the maximum, 1/3 of the maximum. Ice covered about half the surface at maximum concentration. The measurements were carried out in the range of equivalent wind speeds U10 from 7 to 16 m/s. The threshold character of excitation of long waves was obtained (the length is much greater than the average distance between the elements of ice). The higher the density, the higher the threshold for wind speed. According to the results of processing the velocity fields, the dependence of the aerodynamic drag coefficient on the equivalent wind speed was constructed. It is shown that the presence of ice weakly affects the momentum exchange for all concentrations and over the entire wind speed range.
Investigation was supported by Russian Found Basic Research project # 18-05-60299 Arctic.
How to cite: Sergeev, D., Troitskaya, Y., and Kandaurov, A.: Laboratory simulation of the pancake ice influence on the wind wave interaction, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-11860, https://doi.org/10.5194/egusphere-egu2020-11860, 2020.
EGU2020-12916 | Displays | NP6.3
Momentum flux across breaking air-water interfaceNaohisa Takagaki, Naoya Suzuki, Keigo Matsuda, Satoru Komori, and Yuliya Troitskaya
It is important to measure the momentum flux across the air–water interface in the droplet- and bubble-laden turbulent flow at extremely high-wind speeds. Generally, the momentum flux is measured by a profile method, eddy correlation method, or momentum budget (balance) method at normal wind speeds. We assessed the usage of three measurement method at extremely high wind speeds in three wind-wave tanks, Kyoto, Kindai, and Kyushu Universities, JAPAN. Here, the Kyoto tank is 15 m long, 0.8 m wide, 0.8 m high and the maximum wind speed is 68 m/s. The Kyushu tank is 64 m long and the max. speed is 40 m/s. Moreover, we will show the preliminary results for the effects of the fetch on the momentum flux.
How to cite: Takagaki, N., Suzuki, N., Matsuda, K., Komori, S., and Troitskaya, Y.: Momentum flux across breaking air-water interface, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12916, https://doi.org/10.5194/egusphere-egu2020-12916, 2020.
It is important to measure the momentum flux across the air–water interface in the droplet- and bubble-laden turbulent flow at extremely high-wind speeds. Generally, the momentum flux is measured by a profile method, eddy correlation method, or momentum budget (balance) method at normal wind speeds. We assessed the usage of three measurement method at extremely high wind speeds in three wind-wave tanks, Kyoto, Kindai, and Kyushu Universities, JAPAN. Here, the Kyoto tank is 15 m long, 0.8 m wide, 0.8 m high and the maximum wind speed is 68 m/s. The Kyushu tank is 64 m long and the max. speed is 40 m/s. Moreover, we will show the preliminary results for the effects of the fetch on the momentum flux.
How to cite: Takagaki, N., Suzuki, N., Matsuda, K., Komori, S., and Troitskaya, Y.: Momentum flux across breaking air-water interface, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12916, https://doi.org/10.5194/egusphere-egu2020-12916, 2020.
EGU2020-15854 | Displays | NP6.3
On the features of the dynamics of the upper mixed layer of the ocean in the presence of shear flowsIrina Soustova, Daria Gladskikh, Yuliya Troitskaya, and Lev Ostrovsky
In the framework of the modernized RANS model of turbulent closure [1], the evolution in the pycnocline and shear flow in the upper mixed layer of the ocean is studied. For this purpose, one of the variants of the model situation is considered, which consists in studying the mutual transformation of the buoyancy frequency, shear flow, as well as the kinetic and potential turbulence energies determined at the initial time at different depths. It is shown that the kinetic energy of turbulence increases with time, and its maximum shifts to the maximum of the the horizontal shear flow. However, unlike the standard gradient scheme, in the beginning there is a mutual transformation of the kinetic and potential turbulence energies, after which they quickly reach a stationary equilibrium level (at large values of the Richardson numbers). A significant change in stratification, initially having a maximum at a certain depth, was also found in the process of establishing a stationary turbulence regime.
The work was financially supported by the Russian Foundation for Basic Research (projects № 18-05-00292, 18-35-00602).
References:
1. Ostrovsky, L.A., Troitskaya, Yu.I., The model of turbulent transport and the dynamics of turbulence in a stratified shear flow/ Izvestiya, Atmospheric and Oceanic Physics., 1987. v.3. pp. 1031–1040
How to cite: Soustova, I., Gladskikh, D., Troitskaya, Y., and Ostrovsky, L.: On the features of the dynamics of the upper mixed layer of the ocean in the presence of shear flows, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15854, https://doi.org/10.5194/egusphere-egu2020-15854, 2020.
In the framework of the modernized RANS model of turbulent closure [1], the evolution in the pycnocline and shear flow in the upper mixed layer of the ocean is studied. For this purpose, one of the variants of the model situation is considered, which consists in studying the mutual transformation of the buoyancy frequency, shear flow, as well as the kinetic and potential turbulence energies determined at the initial time at different depths. It is shown that the kinetic energy of turbulence increases with time, and its maximum shifts to the maximum of the the horizontal shear flow. However, unlike the standard gradient scheme, in the beginning there is a mutual transformation of the kinetic and potential turbulence energies, after which they quickly reach a stationary equilibrium level (at large values of the Richardson numbers). A significant change in stratification, initially having a maximum at a certain depth, was also found in the process of establishing a stationary turbulence regime.
The work was financially supported by the Russian Foundation for Basic Research (projects № 18-05-00292, 18-35-00602).
References:
1. Ostrovsky, L.A., Troitskaya, Yu.I., The model of turbulent transport and the dynamics of turbulence in a stratified shear flow/ Izvestiya, Atmospheric and Oceanic Physics., 1987. v.3. pp. 1031–1040
How to cite: Soustova, I., Gladskikh, D., Troitskaya, Y., and Ostrovsky, L.: On the features of the dynamics of the upper mixed layer of the ocean in the presence of shear flows, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15854, https://doi.org/10.5194/egusphere-egu2020-15854, 2020.
EGU2020-20860 | Displays | NP6.3
Investigation of the effect of wind speed fluctuation on the drag coefficientNaoya Suzuki, Takuji Waseda, and Naohisa Takagaki
The drag coefficient is generally expressed as functions only of the wind speed U10. However, there exists considerable disagreement among the observed values of the drag coefficient. In this study, we observed the wind stress at the coastal tower of Hiratsuka Offshore Experimental Tower of the University of Tokyo in Japan. The 3-axis sonic anemometer was installed on the top of the tower, which was 20 m above mean sea level. The observation periods were from September 15, 2015 to December 31, 2019. The eddy correlation method was used to calculate the friction velocity every 10 minutes. The variation of the drag coefficient plotted against the wind speed U10 has very large using the all period data. The variation of the drag coefficient was reduced by excluding large fluctuation of wind speed in time series within one hour. Furthermore, the sudden changes of the wind speed and direction was also found to affect the variation of the drag coefficient. These results show that the wind speed fluctuation influenced the variation of the drag coefficient. We also investigate the effect of waves on the drag coefficient.
How to cite: Suzuki, N., Waseda, T., and Takagaki, N.: Investigation of the effect of wind speed fluctuation on the drag coefficient, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20860, https://doi.org/10.5194/egusphere-egu2020-20860, 2020.
The drag coefficient is generally expressed as functions only of the wind speed U10. However, there exists considerable disagreement among the observed values of the drag coefficient. In this study, we observed the wind stress at the coastal tower of Hiratsuka Offshore Experimental Tower of the University of Tokyo in Japan. The 3-axis sonic anemometer was installed on the top of the tower, which was 20 m above mean sea level. The observation periods were from September 15, 2015 to December 31, 2019. The eddy correlation method was used to calculate the friction velocity every 10 minutes. The variation of the drag coefficient plotted against the wind speed U10 has very large using the all period data. The variation of the drag coefficient was reduced by excluding large fluctuation of wind speed in time series within one hour. Furthermore, the sudden changes of the wind speed and direction was also found to affect the variation of the drag coefficient. These results show that the wind speed fluctuation influenced the variation of the drag coefficient. We also investigate the effect of waves on the drag coefficient.
How to cite: Suzuki, N., Waseda, T., and Takagaki, N.: Investigation of the effect of wind speed fluctuation on the drag coefficient, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20860, https://doi.org/10.5194/egusphere-egu2020-20860, 2020.
EGU2020-21662 | Displays | NP6.3
Effects of momentum and enthalpy exchange on the typhoon intensity in the atmospheric boundary layer considering sea spray and rainfallHiroki Okachi and Tomohito Yamada
Typhoon intensity changes according to the momentum and enthalpy flux supplied from the boundary layer. MPI theory uses the ratio between a drag coefficient and an enthalpy exchange coefficient, which are indexes that indicate how much momentum or enthalpy is exchanged between the air and the sea. Each is a coefficient depending on wind speed, temperature and SST.
However, Lighthill (1999) is shown that latent heat exchange varies because sea spray generated from the sea surface evaporates in the boundary layer. In addition, Barenblatt (2005), inspired by Lighthill (1999), showed that the Karman constant changes according to the Froude number and the drag coefficient changes. Since both changes can change the MPI theory, it is necessary to quantitatively evaluate the effect of the droplets generated from the sea surface in order to grasp both accurately. In addition, it is necessary to consider the effects of rainfall in actual storms, which often involve rainfall.
In this study, to evaluate the flux exchange in the boundary layer quantitatively, we show the drag coefficient and the enthalpy exchange coefficient taking into account sea spray and rain. In addition, we show the results of observation of sea spray and rain using disdrometer and X-band radar.
How to cite: Okachi, H. and Yamada, T.: Effects of momentum and enthalpy exchange on the typhoon intensity in the atmospheric boundary layer considering sea spray and rainfall, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21662, https://doi.org/10.5194/egusphere-egu2020-21662, 2020.
Typhoon intensity changes according to the momentum and enthalpy flux supplied from the boundary layer. MPI theory uses the ratio between a drag coefficient and an enthalpy exchange coefficient, which are indexes that indicate how much momentum or enthalpy is exchanged between the air and the sea. Each is a coefficient depending on wind speed, temperature and SST.
However, Lighthill (1999) is shown that latent heat exchange varies because sea spray generated from the sea surface evaporates in the boundary layer. In addition, Barenblatt (2005), inspired by Lighthill (1999), showed that the Karman constant changes according to the Froude number and the drag coefficient changes. Since both changes can change the MPI theory, it is necessary to quantitatively evaluate the effect of the droplets generated from the sea surface in order to grasp both accurately. In addition, it is necessary to consider the effects of rainfall in actual storms, which often involve rainfall.
In this study, to evaluate the flux exchange in the boundary layer quantitatively, we show the drag coefficient and the enthalpy exchange coefficient taking into account sea spray and rain. In addition, we show the results of observation of sea spray and rain using disdrometer and X-band radar.
How to cite: Okachi, H. and Yamada, T.: Effects of momentum and enthalpy exchange on the typhoon intensity in the atmospheric boundary layer considering sea spray and rainfall, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21662, https://doi.org/10.5194/egusphere-egu2020-21662, 2020.
EGU2020-7775 | Displays | NP6.3
Direct numerical simulation of the droplet deformation in the external flow at various Reynolds and Weber numbersAnna Zotova, Yuliya Troitskaya, Daniil Sergeev, and Alexander Kandaurov
A lot of experimental works is devoted to studying behaviour of a droplet in the flow of the external medium. It is shown in [1] that mode of the deformation of droplet in the stationary flow is affected by the Weber number and the Reynolds number. The authors distinguish two types of the droplet deformation in the external flow: the dome-shaped deformation and the bowl-shaped one.
Using the Basilisk software package, direct numerical simulation of the process of deformation of liquid drop in the gas stream was carried out. We examined the problem of the following geometry: a drop of liquid with diameter of 5 mm was placed in the gas stream at the speed of 30 m/s. The density of liquid and gas correspond to the density of water and air, the viscosity of liquid is equal to the viscosity of water. The viscosity of gas and the surface tension at the interface between liquid and gas are determined by the set values of the Reynolds (50 - 3000) and the Weber (2 - 30) numbers. Two main modes of the drop deformation were observed: the dome-shaped deformation and the bowl-shaped one, there is a transitional deformation mode between them. The map of deformation modes is constructed for comparison with the experimental data available in the literature. It was found that the dependence of the Weber number corresponding to the transition from one deformation mode to another on the Reynolds number is well described by the power law proposed in the literature.
This work was supported by the RFBR projects 19-05-00249, 18-35-20068, 18-55-50005, 18-05-60299, 20-05-00322 (familiarization with the Basilisk software package) and the Grant of the President No. MK-3184.2019.5, work on comparison with experimental data was supported by the RSF project No. 18-77-00074, carrying out numerical experiment was supported by the RSF project No. 19-17-00209, A.N. Zotova is additionally supported by the Ministry of Education and Science of the Russian Federation (Government Task No. 0030-2019-0020). The authors are grateful to the FCEIA employee: UNR - CONICET (Rosario, Rep. Argentina) Dr. Ing. César Pairetti.
[1] Hsiang, L.-P., Faeth, G. M., Int. J. Multiphase Flow 21(4), 545-560 (1995).
How to cite: Zotova, A., Troitskaya, Y., Sergeev, D., and Kandaurov, A.: Direct numerical simulation of the droplet deformation in the external flow at various Reynolds and Weber numbers, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7775, https://doi.org/10.5194/egusphere-egu2020-7775, 2020.
A lot of experimental works is devoted to studying behaviour of a droplet in the flow of the external medium. It is shown in [1] that mode of the deformation of droplet in the stationary flow is affected by the Weber number and the Reynolds number. The authors distinguish two types of the droplet deformation in the external flow: the dome-shaped deformation and the bowl-shaped one.
Using the Basilisk software package, direct numerical simulation of the process of deformation of liquid drop in the gas stream was carried out. We examined the problem of the following geometry: a drop of liquid with diameter of 5 mm was placed in the gas stream at the speed of 30 m/s. The density of liquid and gas correspond to the density of water and air, the viscosity of liquid is equal to the viscosity of water. The viscosity of gas and the surface tension at the interface between liquid and gas are determined by the set values of the Reynolds (50 - 3000) and the Weber (2 - 30) numbers. Two main modes of the drop deformation were observed: the dome-shaped deformation and the bowl-shaped one, there is a transitional deformation mode between them. The map of deformation modes is constructed for comparison with the experimental data available in the literature. It was found that the dependence of the Weber number corresponding to the transition from one deformation mode to another on the Reynolds number is well described by the power law proposed in the literature.
This work was supported by the RFBR projects 19-05-00249, 18-35-20068, 18-55-50005, 18-05-60299, 20-05-00322 (familiarization with the Basilisk software package) and the Grant of the President No. MK-3184.2019.5, work on comparison with experimental data was supported by the RSF project No. 18-77-00074, carrying out numerical experiment was supported by the RSF project No. 19-17-00209, A.N. Zotova is additionally supported by the Ministry of Education and Science of the Russian Federation (Government Task No. 0030-2019-0020). The authors are grateful to the FCEIA employee: UNR - CONICET (Rosario, Rep. Argentina) Dr. Ing. César Pairetti.
[1] Hsiang, L.-P., Faeth, G. M., Int. J. Multiphase Flow 21(4), 545-560 (1995).
How to cite: Zotova, A., Troitskaya, Y., Sergeev, D., and Kandaurov, A.: Direct numerical simulation of the droplet deformation in the external flow at various Reynolds and Weber numbers, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7775, https://doi.org/10.5194/egusphere-egu2020-7775, 2020.
EGU2020-8111 | Displays | NP6.3
Wind waves modeling in the polar law weather conditionsAlexandra Kuznetsova, Evgeny Poplavsky, Nikita Rusakov, and Yuliya Troitskaya
Arctic storms pose a great danger to developing commercial and passenger shipping, coastal infrastructure, and also for oil production from offshore platforms. This is primarily due to high waves and extreme winds. Such episodes of adverse weather conditions due to their rapid development are poorly predicted by modern models. For this purpose, the representation of the event of polar law is studied in the wave model WAVEWATCH III.
Wind waves were simulated under conditions of polar depression on ice-free water. To simulate wind waves under conditions of polar depression, the Barents Sea was selected, where, according to the data of [1, 2], a large number of polar hurricanes are observed. Among the identified polar hurricanes, for example, in [3], a hurricane that took place on 05.02.2009, observed at coordinates 69 N 40 E is chosen. The preliminary results in the wave model are obtained without the ice influence consideration. The developed model was configured using the CFSR wind reanalysis data. The resulting distribution of significant wave heights is obtained. Then, to consider the attenuation by sea ice, the reanalysis data of the Arctic System Reanalysis Version 2 (ASRv2), which is based on Polar WRF with a resolution of 15 km for the Arctic region, is used. Modeling the destruction of ice by waves during an intense arctic storm will be implemented using WW3 models with an IS2 module.
The work is supported by RFBR grant 18-05-60299.
- Smirnova, J. E., Golubkin, P. A., Bobylev, L. P., Zabolotskikh, E. V., & Chapron, B. (2015). Polar low climatology over the Nordic and Barents seas based on satellite passive microwave data. Geophysical Research Letters, 42(13), 5603-5609.
- Smirnova, J., & Golubkin, P. (2017). Comparing polar lows in atmospheric reanalyses: Arctic System Reanalysis versus ERA-Interim. Monthly Weather Review, 145(6), 2375-2383.
- Noer, G., & Lien, T. (2010). Dates and Positions of Polar lows over the Nordic Seas between 2000 and 2010. Norwegian Meteorological Institute Rep.
How to cite: Kuznetsova, A., Poplavsky, E., Rusakov, N., and Troitskaya, Y.: Wind waves modeling in the polar law weather conditions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8111, https://doi.org/10.5194/egusphere-egu2020-8111, 2020.
Arctic storms pose a great danger to developing commercial and passenger shipping, coastal infrastructure, and also for oil production from offshore platforms. This is primarily due to high waves and extreme winds. Such episodes of adverse weather conditions due to their rapid development are poorly predicted by modern models. For this purpose, the representation of the event of polar law is studied in the wave model WAVEWATCH III.
Wind waves were simulated under conditions of polar depression on ice-free water. To simulate wind waves under conditions of polar depression, the Barents Sea was selected, where, according to the data of [1, 2], a large number of polar hurricanes are observed. Among the identified polar hurricanes, for example, in [3], a hurricane that took place on 05.02.2009, observed at coordinates 69 N 40 E is chosen. The preliminary results in the wave model are obtained without the ice influence consideration. The developed model was configured using the CFSR wind reanalysis data. The resulting distribution of significant wave heights is obtained. Then, to consider the attenuation by sea ice, the reanalysis data of the Arctic System Reanalysis Version 2 (ASRv2), which is based on Polar WRF with a resolution of 15 km for the Arctic region, is used. Modeling the destruction of ice by waves during an intense arctic storm will be implemented using WW3 models with an IS2 module.
The work is supported by RFBR grant 18-05-60299.
- Smirnova, J. E., Golubkin, P. A., Bobylev, L. P., Zabolotskikh, E. V., & Chapron, B. (2015). Polar low climatology over the Nordic and Barents seas based on satellite passive microwave data. Geophysical Research Letters, 42(13), 5603-5609.
- Smirnova, J., & Golubkin, P. (2017). Comparing polar lows in atmospheric reanalyses: Arctic System Reanalysis versus ERA-Interim. Monthly Weather Review, 145(6), 2375-2383.
- Noer, G., & Lien, T. (2010). Dates and Positions of Polar lows over the Nordic Seas between 2000 and 2010. Norwegian Meteorological Institute Rep.
How to cite: Kuznetsova, A., Poplavsky, E., Rusakov, N., and Troitskaya, Y.: Wind waves modeling in the polar law weather conditions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8111, https://doi.org/10.5194/egusphere-egu2020-8111, 2020.
EGU2020-15621 | Displays | NP6.3
Whitecap coverage measurements in laboratory modeling of wind-wave interactionAlexander Kandaurov, Yuliya Troitskaya, Daniil Sergeev, and Dmitry Kozlov
Whitecap coverage were retrieved from high-speed video recordings of the water surface obtained on the unique laboratory faculty Heidelberg Small-Scale Air-Sea Interaction Facility, the Aeolotron (annular wind-wave facility, 60 cm width, 2.4 m height, circumference of 27.3 m at the inner wall; water depth during experiments 1.0 m, water volume 18.0 m³, air space volume 24 m³; wind was generated by two axial fans mounted into the ceiling).
Records were made in the vertical direction (from top to bottom) in a shadowgraph configuration with backlight located under the channel. On the annular channel, regimes with an abrupt start of wind under an unperturbed surface condition were implemented, including the case of butanol presence in water simulating salinity. At the same time, the wave parameters varying depending on the time elapsed after the wind was turned on, made it possible to study the characteristics of the generation of spray at various effective fetches.
As a result of semi-automatic processing of image sequences using specially developed software that allows marking the moment and position of the bag-breakup formation on the videos, the dependences of the frequency of occurrence of these phenomena per unit surface area versus time after turning on the wind were obtained. From the same images, using the developed software for automatic detection of areas of wave breaking, the values of the whitecap coverage area were obtained. In this case, automatic image processing was performed using morphological analysis in combination with manual processing of part of the frames for tweaking the algorithm parameters: for each mode (water characteristics and wind speed), manual processing of several frames was performed, based on the results of which automatic algorithm parameters were selected to ensure that the resulting whitecap coverage corresponded. Since the same high-speed surface images were used to study the statistics of occurrence of events leading to the spray generation and the dependences of the whitecap coverage on time after turning on the wind for each regime were obtained, we were able to estimate the average number of fragmentation events per unit area of the collapse area.
The work was supported by the RFBR grant 18-35-20068 (conducting an experiment), President grant for young scientists MK-3184.2019.5 (software development) and the RSF grant No. 18-77-00074 (data processing).
How to cite: Kandaurov, A., Troitskaya, Y., Sergeev, D., and Kozlov, D.: Whitecap coverage measurements in laboratory modeling of wind-wave interaction, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15621, https://doi.org/10.5194/egusphere-egu2020-15621, 2020.
Whitecap coverage were retrieved from high-speed video recordings of the water surface obtained on the unique laboratory faculty Heidelberg Small-Scale Air-Sea Interaction Facility, the Aeolotron (annular wind-wave facility, 60 cm width, 2.4 m height, circumference of 27.3 m at the inner wall; water depth during experiments 1.0 m, water volume 18.0 m³, air space volume 24 m³; wind was generated by two axial fans mounted into the ceiling).
Records were made in the vertical direction (from top to bottom) in a shadowgraph configuration with backlight located under the channel. On the annular channel, regimes with an abrupt start of wind under an unperturbed surface condition were implemented, including the case of butanol presence in water simulating salinity. At the same time, the wave parameters varying depending on the time elapsed after the wind was turned on, made it possible to study the characteristics of the generation of spray at various effective fetches.
As a result of semi-automatic processing of image sequences using specially developed software that allows marking the moment and position of the bag-breakup formation on the videos, the dependences of the frequency of occurrence of these phenomena per unit surface area versus time after turning on the wind were obtained. From the same images, using the developed software for automatic detection of areas of wave breaking, the values of the whitecap coverage area were obtained. In this case, automatic image processing was performed using morphological analysis in combination with manual processing of part of the frames for tweaking the algorithm parameters: for each mode (water characteristics and wind speed), manual processing of several frames was performed, based on the results of which automatic algorithm parameters were selected to ensure that the resulting whitecap coverage corresponded. Since the same high-speed surface images were used to study the statistics of occurrence of events leading to the spray generation and the dependences of the whitecap coverage on time after turning on the wind for each regime were obtained, we were able to estimate the average number of fragmentation events per unit area of the collapse area.
The work was supported by the RFBR grant 18-35-20068 (conducting an experiment), President grant for young scientists MK-3184.2019.5 (software development) and the RSF grant No. 18-77-00074 (data processing).
How to cite: Kandaurov, A., Troitskaya, Y., Sergeev, D., and Kozlov, D.: Whitecap coverage measurements in laboratory modeling of wind-wave interaction, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-15621, https://doi.org/10.5194/egusphere-egu2020-15621, 2020.
EGU2020-10902 | Displays | NP6.3 | Highlight
On the modeling of thermohydrodynamic and biogeochemical processes in the inland water objectsDaria Gladskikh, Evgeny Mortikov, and Victor Stepanenko
Currently, one-dimensional and three-dimensional models are widely used to model thermohydrodynamic and biochemical processes in lakes and water rеreservoirs. One-dimensional models are highly computationally efficient and are used to parameterize land water bodies in climate models, however, when calculating large lakes and reservoirs with complex geometry, such models may incorrectly reproduce processes associated with horizontal heterogeneity. This becomes especially important for the prediction of water quality and euthrophication.
A three-dimensional model of thermohydrodynamics and biochemistry of an inland water obect is presented, which is based on the hydrostatic RANS model [1-3], and the parameterization of biochemical processes is implemented by analogy with the scheme for calculating biochemistry in the one-dimensional LAKE model [4]. Thus, the three-dimensional model is supplemented by a description of the transport of substances such as oxygen (O2), carbon dioxide (CO2), methane (CH4), as well as phyto- and zooplankton. The effect of turbulent diffusion and large-scale water movements on the distribution of a methane concentration field is studied.
To verify the calculation results, idealized numerical experiments and comparison with the measurement data on Lake Kuivajärvi (Finland) were used.
The work was supported by grants of the RF President’s Grant for Young Scientists (MK-1867.2020.5, MD-1850.2020.5) and by the RFBR (18-05-00292, 18-35-00602, 20-05-00776).
References:
[1] Mortikov E.V. Numerical simulation of the motion of an ice keel in stratified flow // Izv. Atmos. Ocean. Phys. 2016. 52. P. 108-115.
[2] Mortikov E.V., Glazunov A.V., Lykosov V.N. Numerical study of plane Couette flow: turbulence statistics and the structure of pressure-strain correlations // Russian Journal of Numerical Analysis and Mathematical Modelling. 2019. V. 34, N 2. P. 119-132.
[3] D.S. Gladskikh, V.M. Stepanenko, E.V. Mortikov, On the influence of the horizontal dimensions of inland waters on the thickness of the upper mixed layer. // Water Resourses. 2019. 18 pages. (submitted)
[4] Victor Stepanenko, Ivan Mammarella, Anne Ojala, Heli Miettinen, Vasily Lykosov, and Vesala Timo. LAKE 2.0: a model for temperature, methane, carbon dioxide and oxygen dynamics in lakes. Geoscientific Model Development, 9(5): 1977–2006, 2016.
How to cite: Gladskikh, D., Mortikov, E., and Stepanenko, V.: On the modeling of thermohydrodynamic and biogeochemical processes in the inland water objects, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10902, https://doi.org/10.5194/egusphere-egu2020-10902, 2020.
Currently, one-dimensional and three-dimensional models are widely used to model thermohydrodynamic and biochemical processes in lakes and water rеreservoirs. One-dimensional models are highly computationally efficient and are used to parameterize land water bodies in climate models, however, when calculating large lakes and reservoirs with complex geometry, such models may incorrectly reproduce processes associated with horizontal heterogeneity. This becomes especially important for the prediction of water quality and euthrophication.
A three-dimensional model of thermohydrodynamics and biochemistry of an inland water obect is presented, which is based on the hydrostatic RANS model [1-3], and the parameterization of biochemical processes is implemented by analogy with the scheme for calculating biochemistry in the one-dimensional LAKE model [4]. Thus, the three-dimensional model is supplemented by a description of the transport of substances such as oxygen (O2), carbon dioxide (CO2), methane (CH4), as well as phyto- and zooplankton. The effect of turbulent diffusion and large-scale water movements on the distribution of a methane concentration field is studied.
To verify the calculation results, idealized numerical experiments and comparison with the measurement data on Lake Kuivajärvi (Finland) were used.
The work was supported by grants of the RF President’s Grant for Young Scientists (MK-1867.2020.5, MD-1850.2020.5) and by the RFBR (18-05-00292, 18-35-00602, 20-05-00776).
References:
[1] Mortikov E.V. Numerical simulation of the motion of an ice keel in stratified flow // Izv. Atmos. Ocean. Phys. 2016. 52. P. 108-115.
[2] Mortikov E.V., Glazunov A.V., Lykosov V.N. Numerical study of plane Couette flow: turbulence statistics and the structure of pressure-strain correlations // Russian Journal of Numerical Analysis and Mathematical Modelling. 2019. V. 34, N 2. P. 119-132.
[3] D.S. Gladskikh, V.M. Stepanenko, E.V. Mortikov, On the influence of the horizontal dimensions of inland waters on the thickness of the upper mixed layer. // Water Resourses. 2019. 18 pages. (submitted)
[4] Victor Stepanenko, Ivan Mammarella, Anne Ojala, Heli Miettinen, Vasily Lykosov, and Vesala Timo. LAKE 2.0: a model for temperature, methane, carbon dioxide and oxygen dynamics in lakes. Geoscientific Model Development, 9(5): 1977–2006, 2016.
How to cite: Gladskikh, D., Mortikov, E., and Stepanenko, V.: On the modeling of thermohydrodynamic and biogeochemical processes in the inland water objects, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10902, https://doi.org/10.5194/egusphere-egu2020-10902, 2020.
EGU2020-8764 | Displays | NP6.3
Laboratory investigation of the effect of sea foam on the scattering of microwave radiationGeorgy Baydakov, Ermakova Olga, Vdovin Maxim, Sergeev Daniil, and Troitskaya Yuliya
This paper models the impact of the presence of foam on the short-wave component of surface waves and momentum exchange in the atmospheric boundary layer at high winds. First, physical experiments were carried out in a wind-wave flume in which foam can be artificially produced at the water surface. Tests were conducted under high wind-speed conditions where equivalent 10-m wind speed, U10, ranged 12–38 m/s, with measurements made of the airflow parameters, the frequency-wavenumber spectra of the surface waves, the foam coverage of the water surface, and the distribution of the foam bubbles.
Microwave measurements were performed using a coherent Doppler X-band scatterometer with a wavelength of 3.2 cm and a sequential reception of linearly polarized radiation. It was shown that the presence of foam reduces the NRCS of the agitated water surface. Foam formations are concentrated mainly on the ridges and front slopes of wind waves, which make the main contribution to the scattering of radio waves. This may explain the effect of reducing the total NRCS: foam, which has less reflective properties, masks the main diffusers on the water surface. The second mechanism is associated with the effect of foam on short waves, by analogy with surfactant films.
The effect of foam on the shape of the Doppler spectrum of a microwave signal scattered by the water surface was investigated. In the case of weak wind, the presence of foam on the surface leads to a decrease in the short-wave part of the spectrum of surface waves and, as a result, to a decrease in the scattered signal. In addition, a mirror component appears in the Doppler spectrum corresponding to the fundamental frequency of the wave. In the case of a stronger wind, the grouping of additional scatterers (foam) on the crests of the waves leads to a shift of the Doppler spectra to the high-frequency region.
The work was supported by the RFBR (grants 18-35-20068, 19-05-00366, 19-05-00249) and the RF President’s Grant for Young Scientists (MK-144.2019.5).
How to cite: Baydakov, G., Olga, E., Maxim, V., Daniil, S., and Yuliya, T.: Laboratory investigation of the effect of sea foam on the scattering of microwave radiation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8764, https://doi.org/10.5194/egusphere-egu2020-8764, 2020.
This paper models the impact of the presence of foam on the short-wave component of surface waves and momentum exchange in the atmospheric boundary layer at high winds. First, physical experiments were carried out in a wind-wave flume in which foam can be artificially produced at the water surface. Tests were conducted under high wind-speed conditions where equivalent 10-m wind speed, U10, ranged 12–38 m/s, with measurements made of the airflow parameters, the frequency-wavenumber spectra of the surface waves, the foam coverage of the water surface, and the distribution of the foam bubbles.
Microwave measurements were performed using a coherent Doppler X-band scatterometer with a wavelength of 3.2 cm and a sequential reception of linearly polarized radiation. It was shown that the presence of foam reduces the NRCS of the agitated water surface. Foam formations are concentrated mainly on the ridges and front slopes of wind waves, which make the main contribution to the scattering of radio waves. This may explain the effect of reducing the total NRCS: foam, which has less reflective properties, masks the main diffusers on the water surface. The second mechanism is associated with the effect of foam on short waves, by analogy with surfactant films.
The effect of foam on the shape of the Doppler spectrum of a microwave signal scattered by the water surface was investigated. In the case of weak wind, the presence of foam on the surface leads to a decrease in the short-wave part of the spectrum of surface waves and, as a result, to a decrease in the scattered signal. In addition, a mirror component appears in the Doppler spectrum corresponding to the fundamental frequency of the wave. In the case of a stronger wind, the grouping of additional scatterers (foam) on the crests of the waves leads to a shift of the Doppler spectra to the high-frequency region.
The work was supported by the RFBR (grants 18-35-20068, 19-05-00366, 19-05-00249) and the RF President’s Grant for Young Scientists (MK-144.2019.5).
How to cite: Baydakov, G., Olga, E., Maxim, V., Daniil, S., and Yuliya, T.: Laboratory investigation of the effect of sea foam on the scattering of microwave radiation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8764, https://doi.org/10.5194/egusphere-egu2020-8764, 2020.
EGU2020-9379 | Displays | NP6.3
Atmospheric boundary layer parameters retrieval from Stepped Frequency Microwave Radiometer measurements in tropical cyclonesNikita Rusakov, Evgeny Poplavsky, Olga Ermakova, Yuliya Troitskaya, Daniil Sergeev, and Galina Balandina
Active microwave sensing using satellite instruments has great advantages, since in this range the absorption by clouds and atmospheric gases is noticeably reduced, it allows for round-the-clock and all-weather monitoring of the ocean. One of the main problems is concerned with obtaining the dependency between the RCS of radar signal scattered by the wavy water surface and the parameters of the atmospheric boundary layer in hurricane conditions. To obtain this dependence, we used field measurements of wind speed in a hurricane from falling NOAA GPS-sondes and SAR images from the Sentinel-1 satellite. However, there is the problem of correct collocation of remote sensing data with field measurements of the atmospheric boundary layer parameters, since they are separated in time and space. In this regard, the amount of data suitable for analysis is very limited, which forces us to look for new data sources for processing. A six-channel SFMR radiometer is also installed on board of NOAA research aircraft that measures the emissivity of the ocean surface beneath the aircraft. Thus, it becomes possible to relate the radiometric measurements of SFMR with the parameters of the atmospheric boundary layer in a tropical cyclone obtained from wind velocity profiles, since they are carried out as close as possible in time and space. Using this relation, the SFMR data and the hurricane radar images were analyzed together and an alternative method was found for constructing the dependence of the RCS on the parameters of the boundary layer.
This work was supported by the RFBR projects No. 19-05-00249, 19-05-00366, 18-35-20068 (remote sensing data analysis) and RSF No. 19-17-00209 (GPS-sondes data assimilation and processing).
How to cite: Rusakov, N., Poplavsky, E., Ermakova, O., Troitskaya, Y., Sergeev, D., and Balandina, G.: Atmospheric boundary layer parameters retrieval from Stepped Frequency Microwave Radiometer measurements in tropical cyclones, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9379, https://doi.org/10.5194/egusphere-egu2020-9379, 2020.
Active microwave sensing using satellite instruments has great advantages, since in this range the absorption by clouds and atmospheric gases is noticeably reduced, it allows for round-the-clock and all-weather monitoring of the ocean. One of the main problems is concerned with obtaining the dependency between the RCS of radar signal scattered by the wavy water surface and the parameters of the atmospheric boundary layer in hurricane conditions. To obtain this dependence, we used field measurements of wind speed in a hurricane from falling NOAA GPS-sondes and SAR images from the Sentinel-1 satellite. However, there is the problem of correct collocation of remote sensing data with field measurements of the atmospheric boundary layer parameters, since they are separated in time and space. In this regard, the amount of data suitable for analysis is very limited, which forces us to look for new data sources for processing. A six-channel SFMR radiometer is also installed on board of NOAA research aircraft that measures the emissivity of the ocean surface beneath the aircraft. Thus, it becomes possible to relate the radiometric measurements of SFMR with the parameters of the atmospheric boundary layer in a tropical cyclone obtained from wind velocity profiles, since they are carried out as close as possible in time and space. Using this relation, the SFMR data and the hurricane radar images were analyzed together and an alternative method was found for constructing the dependence of the RCS on the parameters of the boundary layer.
This work was supported by the RFBR projects No. 19-05-00249, 19-05-00366, 18-35-20068 (remote sensing data analysis) and RSF No. 19-17-00209 (GPS-sondes data assimilation and processing).
How to cite: Rusakov, N., Poplavsky, E., Ermakova, O., Troitskaya, Y., Sergeev, D., and Balandina, G.: Atmospheric boundary layer parameters retrieval from Stepped Frequency Microwave Radiometer measurements in tropical cyclones, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9379, https://doi.org/10.5194/egusphere-egu2020-9379, 2020.
EGU2020-9628 | Displays | NP6.3
On the use of cross-polarized SAR and GPS-sonde measurements for wind speed retrieval in tropical cyclonesEvgeny Poplavsky, Nikita Rusakov, Olga Ermakova, Yuliya Troitskaya, Daniil Sergeev, and Galina Balandina
The current investigation is concerned with the study of the dependence of the scattered cross-polarized microwave signal from the Sentinel-1 satellite on the parameters of the marine atmospheric boundary layer based on data obtained from falling NOAA GPS-sondes under tropical cyclone conditions.
Field measurements and remote sensing data for hurricanes in the Atlantic and Pacific oceans were analyzed for the period 2016 - 2018. Based on the analysis of data measured by GPS-sondes, averaged wind speed profiles were obtained, while the parameters of the atmospheric boundary layer (drag coefficient and wind friction velocity) were retrieved using the self-similarity property of velocity profiles from measurements in the “wake” part.
Sentinel-1 SAR images were used as remote sensing data. Images with cross polarization have a high level of thermal noise (NESZ), which leads to errors when retrieving the NRCS. In this regard, preliminary image processing was performed in the SNAP application.
Using the obtained parameters of the atmospheric boundary layer, the data of GRS-sonde measurements and Sentinel-1 SAR images on cross polarization were collocated and the dependences of the NRCS on the parameters of the atmospheric boundary layer were obtained.
How to cite: Poplavsky, E., Rusakov, N., Ermakova, O., Troitskaya, Y., Sergeev, D., and Balandina, G.: On the use of cross-polarized SAR and GPS-sonde measurements for wind speed retrieval in tropical cyclones, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9628, https://doi.org/10.5194/egusphere-egu2020-9628, 2020.
The current investigation is concerned with the study of the dependence of the scattered cross-polarized microwave signal from the Sentinel-1 satellite on the parameters of the marine atmospheric boundary layer based on data obtained from falling NOAA GPS-sondes under tropical cyclone conditions.
Field measurements and remote sensing data for hurricanes in the Atlantic and Pacific oceans were analyzed for the period 2016 - 2018. Based on the analysis of data measured by GPS-sondes, averaged wind speed profiles were obtained, while the parameters of the atmospheric boundary layer (drag coefficient and wind friction velocity) were retrieved using the self-similarity property of velocity profiles from measurements in the “wake” part.
Sentinel-1 SAR images were used as remote sensing data. Images with cross polarization have a high level of thermal noise (NESZ), which leads to errors when retrieving the NRCS. In this regard, preliminary image processing was performed in the SNAP application.
Using the obtained parameters of the atmospheric boundary layer, the data of GRS-sonde measurements and Sentinel-1 SAR images on cross polarization were collocated and the dependences of the NRCS on the parameters of the atmospheric boundary layer were obtained.
How to cite: Poplavsky, E., Rusakov, N., Ermakova, O., Troitskaya, Y., Sergeev, D., and Balandina, G.: On the use of cross-polarized SAR and GPS-sonde measurements for wind speed retrieval in tropical cyclones, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9628, https://doi.org/10.5194/egusphere-egu2020-9628, 2020.
EGU2020-8799 | Displays | NP6.3
Exchange coefficients derived from GPS-sonde and SFMR measurements in hurricane conditionsOlga Ermakova, Nikita Rusakov, Evgeny Poplavsky, Yuliya Troitskaya, Daniil Sergeev, and Galina Balandina
Insufficient knowledge of the atmosphere layer momentum, heat and moisture transfer between the wavy water surface and marine atmospheric boundary layer under hurricane conditions lead to the uncertainties while using weather forecasting models and models of climate. In particular, there is a significant lack of data for heat and moisture exchange coefficients. In this regard, it is necessary to analyze and process the vertical profiles of wind speed and thermodynamic quantities. The present study is concerned with the analysis and processing of measurements from the NOAA falling GPS-sondes for hurricanes of categories 4 and 5 of 2003-2017, which represent an array of data on wind speed, temperature, altitude, coordinates, etc.
The proposed approach for describing a turbulent boundary layer formed in hurricane conditions is based on the use of the self-similarity properties of the velocity and enthalpy profiles in the atmospheric boundary layer, which includes a layer of constant flows, transferring into its “wake” part with height. Based on the proposed approach, the aerodynamic drag coefficients Cd and the enthalpy exchange coefficient Ck for a selected group of hurricanes were restored. As the value of Ck/Cd represents a determining factor in the formation of a hurricane, the dependence of this ratio on the wind speed was constructed.
This work was supported by the RFBR projects No 19-05-00249, 19-05-00366, 18-35-20068 (remote sensing data analysis) and RSF No 19-17-00209 (GPS-sonde data assimilation and processing).
How to cite: Ermakova, O., Rusakov, N., Poplavsky, E., Troitskaya, Y., Sergeev, D., and Balandina, G.: Exchange coefficients derived from GPS-sonde and SFMR measurements in hurricane conditions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8799, https://doi.org/10.5194/egusphere-egu2020-8799, 2020.
Insufficient knowledge of the atmosphere layer momentum, heat and moisture transfer between the wavy water surface and marine atmospheric boundary layer under hurricane conditions lead to the uncertainties while using weather forecasting models and models of climate. In particular, there is a significant lack of data for heat and moisture exchange coefficients. In this regard, it is necessary to analyze and process the vertical profiles of wind speed and thermodynamic quantities. The present study is concerned with the analysis and processing of measurements from the NOAA falling GPS-sondes for hurricanes of categories 4 and 5 of 2003-2017, which represent an array of data on wind speed, temperature, altitude, coordinates, etc.
The proposed approach for describing a turbulent boundary layer formed in hurricane conditions is based on the use of the self-similarity properties of the velocity and enthalpy profiles in the atmospheric boundary layer, which includes a layer of constant flows, transferring into its “wake” part with height. Based on the proposed approach, the aerodynamic drag coefficients Cd and the enthalpy exchange coefficient Ck for a selected group of hurricanes were restored. As the value of Ck/Cd represents a determining factor in the formation of a hurricane, the dependence of this ratio on the wind speed was constructed.
This work was supported by the RFBR projects No 19-05-00249, 19-05-00366, 18-35-20068 (remote sensing data analysis) and RSF No 19-17-00209 (GPS-sonde data assimilation and processing).
How to cite: Ermakova, O., Rusakov, N., Poplavsky, E., Troitskaya, Y., Sergeev, D., and Balandina, G.: Exchange coefficients derived from GPS-sonde and SFMR measurements in hurricane conditions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8799, https://doi.org/10.5194/egusphere-egu2020-8799, 2020.
EGU2020-7222 | Displays | NP6.3
Comparison of paradigmatic gravity wave models for ocean and atmosphereUwe Harlander
It appears that oceanographers and meteorologists have different pictures in their minds when they speak about internal waves. The reason might be that in both communities different paradigmatic gravity wave models based on different simplifying assumptions are in use. For the oceanographer, internal wave beams are rather common, a feature virtually unknown to the atmospheric scientist. In contrast, wave packets traveling upwards in the atmosphere is the standard picture for the meteorologist. The mathematical origin of such a different view is that for time harmonic waves, the underlying boundary value problem for internal waves in the ocean is hyperbolic but elliptic for atmospheric flows.
In the present paper we discuss the consequences that result from these two different types of boundary value problems. Wave focusing is a rather
generic process for hyperbolic problems and we argue that the latter should also be of interest to meteorologists in view of new findings that indeed
a significant part of the internal waves in the atmosphere travel downward. We further apply some of our findings to new laboratory data on inertial modes arguing that an additional shear flow leads to an elliptic boundary value problem and beam-like wave fields, typical for the inertial waves without a shear flow, become mode-like.
How to cite: Harlander, U.: Comparison of paradigmatic gravity wave models for ocean and atmosphere, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7222, https://doi.org/10.5194/egusphere-egu2020-7222, 2020.
It appears that oceanographers and meteorologists have different pictures in their minds when they speak about internal waves. The reason might be that in both communities different paradigmatic gravity wave models based on different simplifying assumptions are in use. For the oceanographer, internal wave beams are rather common, a feature virtually unknown to the atmospheric scientist. In contrast, wave packets traveling upwards in the atmosphere is the standard picture for the meteorologist. The mathematical origin of such a different view is that for time harmonic waves, the underlying boundary value problem for internal waves in the ocean is hyperbolic but elliptic for atmospheric flows.
In the present paper we discuss the consequences that result from these two different types of boundary value problems. Wave focusing is a rather
generic process for hyperbolic problems and we argue that the latter should also be of interest to meteorologists in view of new findings that indeed
a significant part of the internal waves in the atmosphere travel downward. We further apply some of our findings to new laboratory data on inertial modes arguing that an additional shear flow leads to an elliptic boundary value problem and beam-like wave fields, typical for the inertial waves without a shear flow, become mode-like.
How to cite: Harlander, U.: Comparison of paradigmatic gravity wave models for ocean and atmosphere, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7222, https://doi.org/10.5194/egusphere-egu2020-7222, 2020.
EGU2020-8302 | Displays | NP6.3
Experimental and numerical study of the resonant feature of internal gravity waves in the case of ‘dead water’ phenomenonKarim Medjdoub, Imre M. Jánosi, and Miklós Vincze
‘Dead water’ phenomenon, which is essentially a ship-wave in a stratified fluid is studied experimentally in a laboratory tank. Interfacial waves are excited by a moving ship model in a quasi-two-layer fluid, which leads to the development of a drag force that reaches the maximum at the largest wave amplitude in a critical ‘resonant’ towing speed, whose value depends on the structure of the vertical density profile. We utilize five ships of different lengths but of the same width and wet depth. The experimental analysis focuses on the variability of the interfacial wave amplitudes and wavelengths as a function of towing speed in different stratifications. Data evaluation is based on linear two- and three-layer theories of freely propagating interfacial waves and lee waves. We observe that although the internal waves have considerable amplitude, linear theory still gives a surprisingly adequate description of subcritical to supercritical transition and the associated amplification of internal waves.
How to cite: Medjdoub, K., Jánosi, I. M., and Vincze, M.: Experimental and numerical study of the resonant feature of internal gravity waves in the case of ‘dead water’ phenomenon , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8302, https://doi.org/10.5194/egusphere-egu2020-8302, 2020.
‘Dead water’ phenomenon, which is essentially a ship-wave in a stratified fluid is studied experimentally in a laboratory tank. Interfacial waves are excited by a moving ship model in a quasi-two-layer fluid, which leads to the development of a drag force that reaches the maximum at the largest wave amplitude in a critical ‘resonant’ towing speed, whose value depends on the structure of the vertical density profile. We utilize five ships of different lengths but of the same width and wet depth. The experimental analysis focuses on the variability of the interfacial wave amplitudes and wavelengths as a function of towing speed in different stratifications. Data evaluation is based on linear two- and three-layer theories of freely propagating interfacial waves and lee waves. We observe that although the internal waves have considerable amplitude, linear theory still gives a surprisingly adequate description of subcritical to supercritical transition and the associated amplification of internal waves.
How to cite: Medjdoub, K., Jánosi, I. M., and Vincze, M.: Experimental and numerical study of the resonant feature of internal gravity waves in the case of ‘dead water’ phenomenon , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8302, https://doi.org/10.5194/egusphere-egu2020-8302, 2020.
EGU2020-9872 | Displays | NP6.3
Instability of surface quasigeostrophic spatially periodic flowsMaksim Kalashnik, Michael Kurgansky, and Sergey Kostrykin
The surface quasigeostrophic (SQG) model is developed to describe the dynamics of flows with zero potential vorticity in the presence of one or two horizontal boundaries (Earth surface and tropopause). Within the framework of this model, the problems of linear and nonlinear stability of zonal spatially periodic flows are considered. To study the linear stability of flows with one boundary, two approaches are used. In the first approach, the solution is sought by decomposing into a trigonometric series, and the growth rate of the perturbations is found from the characteristic equation containing an infinite continued fraction. In the second approach, few-mode Galerkin approximations of the solution are constructed. It is shown that both approaches lead to the same dependence of the growth increment on the wavenumber of perturbations. The existence of instability with a preferred horizontal scale on the order of the wavelength of the main flow follows from this dependence. A similar result is obtained within the framework of the SQG model with two horizontal boundaries. The Galerkin method with three basis trigonometric functions is also used to study the nonlinear dynamics of perturbations, described by a system of three nonlinear differential equations similar to that describing the motion of a symmetric top in classical mechanics. An analysis of the solutions of this system shows that the exponential growth of disturbances at the linear stage is replaced by a stage of stable nonlinear oscillations (vacillations). The results of numerical integration of full nonlinear SQG equations confirm this analysis.
The work was supported by the Russian Foundation for Basic Research (Project 18-05-00414) and the Russian Science Foundation (Project 19-17-00248).
How to cite: Kalashnik, M., Kurgansky, M., and Kostrykin, S.: Instability of surface quasigeostrophic spatially periodic flows, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9872, https://doi.org/10.5194/egusphere-egu2020-9872, 2020.
The surface quasigeostrophic (SQG) model is developed to describe the dynamics of flows with zero potential vorticity in the presence of one or two horizontal boundaries (Earth surface and tropopause). Within the framework of this model, the problems of linear and nonlinear stability of zonal spatially periodic flows are considered. To study the linear stability of flows with one boundary, two approaches are used. In the first approach, the solution is sought by decomposing into a trigonometric series, and the growth rate of the perturbations is found from the characteristic equation containing an infinite continued fraction. In the second approach, few-mode Galerkin approximations of the solution are constructed. It is shown that both approaches lead to the same dependence of the growth increment on the wavenumber of perturbations. The existence of instability with a preferred horizontal scale on the order of the wavelength of the main flow follows from this dependence. A similar result is obtained within the framework of the SQG model with two horizontal boundaries. The Galerkin method with three basis trigonometric functions is also used to study the nonlinear dynamics of perturbations, described by a system of three nonlinear differential equations similar to that describing the motion of a symmetric top in classical mechanics. An analysis of the solutions of this system shows that the exponential growth of disturbances at the linear stage is replaced by a stage of stable nonlinear oscillations (vacillations). The results of numerical integration of full nonlinear SQG equations confirm this analysis.
The work was supported by the Russian Foundation for Basic Research (Project 18-05-00414) and the Russian Science Foundation (Project 19-17-00248).
How to cite: Kalashnik, M., Kurgansky, M., and Kostrykin, S.: Instability of surface quasigeostrophic spatially periodic flows, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9872, https://doi.org/10.5194/egusphere-egu2020-9872, 2020.
EGU2020-20956 | Displays | NP6.3
Complementary numerical and experimental study in the baroclinic annulus for the microgravity experiment AtmoFlowPeter Szabo, Florian Zaussinger, Peter Haun, Vadim Travnikov, Martin Meier, and Cristoph Egbers
The experimental investigation of large-scale flows on atmospheric circulation and climate such as Earth, Mars or even distant exoplanets are of great interest in geophysics. Gaining the fundamental knowledge of the origin of planetary waves or global cell formation is interesting from a meteorological point of view but up till now difficult to reproduce in laboratory scale. The limitation is based on the central force field which may be induced by the dielectrophoretic effect. However, the established radial force field is overpowered by the gravitational field unless experiments are conducted in a microgravity environment. The AtmoFlow project provides the possibility to study convective flow patterns in a spherical shell under microgravity conditions, planned after 2022, on the International Space Station (ISS) and is in fact the follow-up experiment of the GeoFlow project which served between 2008 and 2016 on the ISS.
Without losing the overall focus of complex planetary atmospheres, the AtmoFlow experiment is able to model the intake and outtake of energy (e.g. radiation) and the rotational forcing via rotating or co-rotating boundaries. The gap is filled with a Fluor-based fluid with physical properties sensitive to temperature and electric fields. With an electric potential applied between the spherical shells a central force field is established that is based on the above mentioned dielectrophoretic effect. By adjusting rotation, thermal forcing and strength of the applied electric potential the AtmoFlow experiment can simulate different planetary atmospheres to investigate local pattern formation or global planetary cells. An interferometry system similar to the one used in the GeoFlow experiment uses the Wollaston shearing technique (WSI) to record the evolving temperature fields.
To provide a benchmark solution for the experimentally recorded WSI interferograms a ground experiment is used to develop a validation method and to find the best postprocessing method for the AtmoFlow experiment. The ground experiment consists of a thermally forced baroclinic wave tank with a corresponding WSI setup and an infrared (IR) camera that are used to record the evolving temperature field. Here, we present first numerical simulations of the ground experiment that include the formation of the convective wave patterns and the numerical evaluated interferograms and IR pictures. The numerical calculated data will then be compared to the experimental recorded data to find a technique to best process the recorded WSI interferograms of the AtmoFlow project.
How to cite: Szabo, P., Zaussinger, F., Haun, P., Travnikov, V., Meier, M., and Egbers, C.: Complementary numerical and experimental study in the baroclinic annulus for the microgravity experiment AtmoFlow , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20956, https://doi.org/10.5194/egusphere-egu2020-20956, 2020.
The experimental investigation of large-scale flows on atmospheric circulation and climate such as Earth, Mars or even distant exoplanets are of great interest in geophysics. Gaining the fundamental knowledge of the origin of planetary waves or global cell formation is interesting from a meteorological point of view but up till now difficult to reproduce in laboratory scale. The limitation is based on the central force field which may be induced by the dielectrophoretic effect. However, the established radial force field is overpowered by the gravitational field unless experiments are conducted in a microgravity environment. The AtmoFlow project provides the possibility to study convective flow patterns in a spherical shell under microgravity conditions, planned after 2022, on the International Space Station (ISS) and is in fact the follow-up experiment of the GeoFlow project which served between 2008 and 2016 on the ISS.
Without losing the overall focus of complex planetary atmospheres, the AtmoFlow experiment is able to model the intake and outtake of energy (e.g. radiation) and the rotational forcing via rotating or co-rotating boundaries. The gap is filled with a Fluor-based fluid with physical properties sensitive to temperature and electric fields. With an electric potential applied between the spherical shells a central force field is established that is based on the above mentioned dielectrophoretic effect. By adjusting rotation, thermal forcing and strength of the applied electric potential the AtmoFlow experiment can simulate different planetary atmospheres to investigate local pattern formation or global planetary cells. An interferometry system similar to the one used in the GeoFlow experiment uses the Wollaston shearing technique (WSI) to record the evolving temperature fields.
To provide a benchmark solution for the experimentally recorded WSI interferograms a ground experiment is used to develop a validation method and to find the best postprocessing method for the AtmoFlow experiment. The ground experiment consists of a thermally forced baroclinic wave tank with a corresponding WSI setup and an infrared (IR) camera that are used to record the evolving temperature field. Here, we present first numerical simulations of the ground experiment that include the formation of the convective wave patterns and the numerical evaluated interferograms and IR pictures. The numerical calculated data will then be compared to the experimental recorded data to find a technique to best process the recorded WSI interferograms of the AtmoFlow project.
How to cite: Szabo, P., Zaussinger, F., Haun, P., Travnikov, V., Meier, M., and Egbers, C.: Complementary numerical and experimental study in the baroclinic annulus for the microgravity experiment AtmoFlow , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20956, https://doi.org/10.5194/egusphere-egu2020-20956, 2020.
EGU2020-4987 | Displays | NP6.3
A new method for the detection of incompressible turbulence as a deviation from the hydrostatic balance assumptionPetr Šácha and Petr Pišoft
This study aims at introducing a simple and physically consistent method for identification and analysis of turbulent layers in the free atmosphere that can supplement the traditional methods (Richardson number criterion, Thorpe scale). The method is based on differences between the observed and hydrostatically derived (with floating level of initialization) pressure. In the paper we derive the method analytically from the Navier Stokes equations and propose a methodology how to isolate information on turbulence from an internal gravity wave and atmospheric structure signal in the pressure differences. Finally we apply the methodology on high vertical-resolution radiosonde data to demonstrate the utility of the novel method by contrasting the results with traditional diagnostics.
How to cite: Šácha, P. and Pišoft, P.: A new method for the detection of incompressible turbulence as a deviation from the hydrostatic balance assumption, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4987, https://doi.org/10.5194/egusphere-egu2020-4987, 2020.
This study aims at introducing a simple and physically consistent method for identification and analysis of turbulent layers in the free atmosphere that can supplement the traditional methods (Richardson number criterion, Thorpe scale). The method is based on differences between the observed and hydrostatically derived (with floating level of initialization) pressure. In the paper we derive the method analytically from the Navier Stokes equations and propose a methodology how to isolate information on turbulence from an internal gravity wave and atmospheric structure signal in the pressure differences. Finally we apply the methodology on high vertical-resolution radiosonde data to demonstrate the utility of the novel method by contrasting the results with traditional diagnostics.
How to cite: Šácha, P. and Pišoft, P.: A new method for the detection of incompressible turbulence as a deviation from the hydrostatic balance assumption, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4987, https://doi.org/10.5194/egusphere-egu2020-4987, 2020.
EGU2020-7262 | Displays | NP6.3
Locating sources of variability in the transition to Structural Vacillation in the baroclinic annulusWolf-Gerrit Fruh, Peter Szabo, Christoph Egbers, and Harlander Uwe
The baroclinic rotating annulus is a classic experiment to investigate the transition from regular waves to complex flows. A well documented transition via Amplitude Vacillation leads to low-dimensional chaos through a sequence of canonical bifurcations. However, the transition to geostrophic turbulence is usually through a regime of 'Structural Vacillation' (SV) which retains the overall spatial structure of regular waves but includes small-scale variability. Even though the SV vacillation occurs with a clear time scale, the dynamics of SV cannot usually be described by low-dimensional dynamics. For example, attractor dimension estimations tend to fail: they may not show any scaling region or converge to an unrealistic values. Explanations of the origin of SV have variously invoked higher radial modes of the fundamental baroclinic waves, local secondary instabilities in the baroclinic waves caused by high thermal gradients (gravity waves) or velocity shear (barotropic instability), or instabilities within the side-wall (Stewartson) boundary layers.
The aim of this paper is to identify where within the fluid different signals of variability are located at different stages in the transition from a steady wave to pronounced SV. To this end, a set of experiments in a water-filled rotating annulus with a free surface (inner radius 45 mm, outer radius 120 mm, fluid depth 140 mm) was carried out covering a temperature difference between the heated outer wall and the cooler inner wall of between 6 and 9.5 K, and a range of rotation rates from 0.84 to 2.29 rad/s (Ta= 4.75 x 107 - 3.53 x 108 and Θ = 0.0617 - 0.629). The flow was observed through an infrared camera capturing the temperatures of the free surface. Images of the flow were recorded for a period of 15 minutes at a sampling rate of 1 Hz at the lower rotation rates and 2 Hz at the higher rotation rates.
The initial processing of the time series of temperature images involved normalisation of the temperatures followed by rotation of the images to a coordinate system co-rotating with the main baroclinic wave mode. The resulting images were separated into the time-mean wave field and the fluctuation field, resulting in a set of normalised temperature fluctuations at fixed points relative to the main baroclinic wave. Each of the time series was then used to calculate the power spectrum at that location. The low-frequency part of the spectra (up until half the tank rotation frequency) was used in a k-means cluster analysis to identify clusters of similar spectral shape and, from this, create a map of which spectral shape was found at which location in the flow field.
The results show isolated locations of a high frequency peak near the inner boundary at the onset of visible fluctuations. Further into the regime of clear structural vacillations, areas of pronounced variability at lower frequencies become visible at the lee shoulder of the cold jets in the fluid interior, followed by activity where the end of the cold jet interacts with the hot jet emanating from the outer boundary layer.
How to cite: Fruh, W.-G., Szabo, P., Egbers, C., and Uwe, H.: Locating sources of variability in the transition to Structural Vacillation in the baroclinic annulus, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7262, https://doi.org/10.5194/egusphere-egu2020-7262, 2020.
The baroclinic rotating annulus is a classic experiment to investigate the transition from regular waves to complex flows. A well documented transition via Amplitude Vacillation leads to low-dimensional chaos through a sequence of canonical bifurcations. However, the transition to geostrophic turbulence is usually through a regime of 'Structural Vacillation' (SV) which retains the overall spatial structure of regular waves but includes small-scale variability. Even though the SV vacillation occurs with a clear time scale, the dynamics of SV cannot usually be described by low-dimensional dynamics. For example, attractor dimension estimations tend to fail: they may not show any scaling region or converge to an unrealistic values. Explanations of the origin of SV have variously invoked higher radial modes of the fundamental baroclinic waves, local secondary instabilities in the baroclinic waves caused by high thermal gradients (gravity waves) or velocity shear (barotropic instability), or instabilities within the side-wall (Stewartson) boundary layers.
The aim of this paper is to identify where within the fluid different signals of variability are located at different stages in the transition from a steady wave to pronounced SV. To this end, a set of experiments in a water-filled rotating annulus with a free surface (inner radius 45 mm, outer radius 120 mm, fluid depth 140 mm) was carried out covering a temperature difference between the heated outer wall and the cooler inner wall of between 6 and 9.5 K, and a range of rotation rates from 0.84 to 2.29 rad/s (Ta= 4.75 x 107 - 3.53 x 108 and Θ = 0.0617 - 0.629). The flow was observed through an infrared camera capturing the temperatures of the free surface. Images of the flow were recorded for a period of 15 minutes at a sampling rate of 1 Hz at the lower rotation rates and 2 Hz at the higher rotation rates.
The initial processing of the time series of temperature images involved normalisation of the temperatures followed by rotation of the images to a coordinate system co-rotating with the main baroclinic wave mode. The resulting images were separated into the time-mean wave field and the fluctuation field, resulting in a set of normalised temperature fluctuations at fixed points relative to the main baroclinic wave. Each of the time series was then used to calculate the power spectrum at that location. The low-frequency part of the spectra (up until half the tank rotation frequency) was used in a k-means cluster analysis to identify clusters of similar spectral shape and, from this, create a map of which spectral shape was found at which location in the flow field.
The results show isolated locations of a high frequency peak near the inner boundary at the onset of visible fluctuations. Further into the regime of clear structural vacillations, areas of pronounced variability at lower frequencies become visible at the lee shoulder of the cold jets in the fluid interior, followed by activity where the end of the cold jet interacts with the hot jet emanating from the outer boundary layer.
How to cite: Fruh, W.-G., Szabo, P., Egbers, C., and Uwe, H.: Locating sources of variability in the transition to Structural Vacillation in the baroclinic annulus, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7262, https://doi.org/10.5194/egusphere-egu2020-7262, 2020.
EGU2020-4137 | Displays | NP6.3
Barotropic instability of a zonal jet on the sphere: From non-divergence through quasi-geostrophy to shallow waterOfer Shamir, Nathan Paldor, and Chaim Garfinkel
Two common approximations to the full Shallow Water Equations (SWEs) are non-divergence and quasi-geostrophy, and the degree to which these approximations lead to biases in numerical solutions are explored using the testbed of barotropic instability. Specifically, we examine the linear stability of strong polar and equatorial jets and compare the growth rates obtained from the SWEs along with those obtained from the Non-Divergent barotropic vorticity (ND) equation and the Quasi-Geostrophic (QG) equation. The main result of this paper is that the depth over which a layer is barotropically unstable is a crucial parameter in controlling the growth rate of small-amplitude perturbations and this dependence is completely lost in the ND equation and is overly weak in the QG system. Only for depths of 30 km or more are the growth rates predicted by the ND and QG systems a good approximation to those of the SWEs, and such a convergence for deep layers can be explained using theoretical considerations. However, for smaller depths, the growth rates predicted by the SWEs become smaller than those of the ND and QG systems and for depths of between 5 and 10 km they can be smaller by more than 50%. For polar jets, and for depths below 2 km the mean height in geostrophic balance with the strong zonal jet becomes negative and hence the barotropic instability problem is ill-defined. While in the SWEs an equatorial jet becomes stable for layer depths smaller than ~3-4 km, in the QG and ND approximation it is unstable for layer depths down to 1 km. These results may have implications for the importance of barotropic instability in Earth's upper stratosphere and perhaps also other planets such as Venus.
How to cite: Shamir, O., Paldor, N., and Garfinkel, C.: Barotropic instability of a zonal jet on the sphere: From non-divergence through quasi-geostrophy to shallow water, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4137, https://doi.org/10.5194/egusphere-egu2020-4137, 2020.
Two common approximations to the full Shallow Water Equations (SWEs) are non-divergence and quasi-geostrophy, and the degree to which these approximations lead to biases in numerical solutions are explored using the testbed of barotropic instability. Specifically, we examine the linear stability of strong polar and equatorial jets and compare the growth rates obtained from the SWEs along with those obtained from the Non-Divergent barotropic vorticity (ND) equation and the Quasi-Geostrophic (QG) equation. The main result of this paper is that the depth over which a layer is barotropically unstable is a crucial parameter in controlling the growth rate of small-amplitude perturbations and this dependence is completely lost in the ND equation and is overly weak in the QG system. Only for depths of 30 km or more are the growth rates predicted by the ND and QG systems a good approximation to those of the SWEs, and such a convergence for deep layers can be explained using theoretical considerations. However, for smaller depths, the growth rates predicted by the SWEs become smaller than those of the ND and QG systems and for depths of between 5 and 10 km they can be smaller by more than 50%. For polar jets, and for depths below 2 km the mean height in geostrophic balance with the strong zonal jet becomes negative and hence the barotropic instability problem is ill-defined. While in the SWEs an equatorial jet becomes stable for layer depths smaller than ~3-4 km, in the QG and ND approximation it is unstable for layer depths down to 1 km. These results may have implications for the importance of barotropic instability in Earth's upper stratosphere and perhaps also other planets such as Venus.
How to cite: Shamir, O., Paldor, N., and Garfinkel, C.: Barotropic instability of a zonal jet on the sphere: From non-divergence through quasi-geostrophy to shallow water, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4137, https://doi.org/10.5194/egusphere-egu2020-4137, 2020.
EGU2020-17693 | Displays | NP6.3
Analytical solution technique in k-omega and k-epsilon turbulence parameterizations and their implementation in the OGCMAnatoly Gusev and Vladimir Zalesny
The main purpose of the work is to improve the ocean general circulation model (OGCM) by including new parameterizations of heat, salt and momentum vertical turbulent exchange, which significantly affects quality of reproducing the ocean circulation and thermohaline structure using the OGCMs based on the primitive equation system. The main instrument of the research is the σ-model of the oceanic and marine circulation INMOM (Institute of Numerical Mathematics Ocean Model) developed at the Marchuk Institute of Numerical Mathematics of RAS. The basic equation set in the incompressibility, hydrostatics and Boussinesq approximations is supplemented with the equations for the k-ω and k-ε vertical turbulent exchange parameterizations, which are solved using the splitting with respect to the physical processes. The total equations are split into the stages describing transport-diffusion of the turbulent characteristics and their generation-dissipation. At the generation-dissipation stage, the equations for turbulent characteristics can be solved analytically. This approach allows one to solve the turbulence equations with the time step used in the OGCM. To estimate quality of these two vertical turbulent exchange parameterizations, the joint circulation of the North Atlantic and Arctic Ocean is numerically simulated and the upper ocean layer characteristics are studied. It is shown that the structure of large-scale fields in the North Atlantic and Arctic Ocean is sensitive to the choice between these two vertical turbulence models. In particular, application of the k-ε parameterization is accompanied by a noticeably higher rate of water involvement within the seasonal pycnocline in the developed turbulence zone than that resulting from application of the k-ω model.
The investigation is carried out in the INM RAS and MHI RAS under support of the Russian Science Foundation (grant No 17-77-30001).
References
Moshonkin, S., Zalesny, V. and Gusev, A., 2018, Journal of Marine Science and Engineering, 6(95), https://doi.org/10.3390/jmse6030095
Zalesny, V.B., Moshonkin, S.N., Perov, V.L. and Gusev, A.V., 2019, Physical Oceanography, 26(6), 455-466, https://doi.org/10.22449/1573-160X-2019-6-455-466
How to cite: Gusev, A. and Zalesny, V.: Analytical solution technique in k-omega and k-epsilon turbulence parameterizations and their implementation in the OGCM, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17693, https://doi.org/10.5194/egusphere-egu2020-17693, 2020.
The main purpose of the work is to improve the ocean general circulation model (OGCM) by including new parameterizations of heat, salt and momentum vertical turbulent exchange, which significantly affects quality of reproducing the ocean circulation and thermohaline structure using the OGCMs based on the primitive equation system. The main instrument of the research is the σ-model of the oceanic and marine circulation INMOM (Institute of Numerical Mathematics Ocean Model) developed at the Marchuk Institute of Numerical Mathematics of RAS. The basic equation set in the incompressibility, hydrostatics and Boussinesq approximations is supplemented with the equations for the k-ω and k-ε vertical turbulent exchange parameterizations, which are solved using the splitting with respect to the physical processes. The total equations are split into the stages describing transport-diffusion of the turbulent characteristics and their generation-dissipation. At the generation-dissipation stage, the equations for turbulent characteristics can be solved analytically. This approach allows one to solve the turbulence equations with the time step used in the OGCM. To estimate quality of these two vertical turbulent exchange parameterizations, the joint circulation of the North Atlantic and Arctic Ocean is numerically simulated and the upper ocean layer characteristics are studied. It is shown that the structure of large-scale fields in the North Atlantic and Arctic Ocean is sensitive to the choice between these two vertical turbulence models. In particular, application of the k-ε parameterization is accompanied by a noticeably higher rate of water involvement within the seasonal pycnocline in the developed turbulence zone than that resulting from application of the k-ω model.
The investigation is carried out in the INM RAS and MHI RAS under support of the Russian Science Foundation (grant No 17-77-30001).
References
Moshonkin, S., Zalesny, V. and Gusev, A., 2018, Journal of Marine Science and Engineering, 6(95), https://doi.org/10.3390/jmse6030095
Zalesny, V.B., Moshonkin, S.N., Perov, V.L. and Gusev, A.V., 2019, Physical Oceanography, 26(6), 455-466, https://doi.org/10.22449/1573-160X-2019-6-455-466
How to cite: Gusev, A. and Zalesny, V.: Analytical solution technique in k-omega and k-epsilon turbulence parameterizations and their implementation in the OGCM, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-17693, https://doi.org/10.5194/egusphere-egu2020-17693, 2020.
NP7.1 – Nonlinear Waves and Fracturing
EGU2020-4439 | Displays | NP7.1 | Highlight | NP Division Outstanding ECS Lecture
Soliton turbulence in weakly nonlinear and weakly dispersive mediaEkaterina Didenkulova
A short review on weakly nonlinear and weakly dispersive dynamics of soliton ensembles, the so-called soliton turbulence is given. Such processes take place in shallow water waves, internal waves in the atmosphere and the ocean, solid mechanics and astrophysical plasma; they are described by the integrable models of Korteweg – de Vries equation type (modified Korteweg – de Vries equation, Gardner equation). Here, soliton turbulence means an ensemble of solitons with random parameters. The property of solitons to interact elastically with each other gives rise to an obvious association with the gas of elastically colliding particles. Strictly speaking, soliton turbulence (soliton gas) is a deterministic dynamical system due to the integrability of equations describing the evolution of waves (solitons). However, due to the great complexity of its behavior (due to the large number of participating solitons and nonlinear nature of their interactions), the dynamics of the system can be considered random and, accordingly, may be investigated using methods typical for such problems.
Firstly, pair soliton collisions have been analyzed as an elementary act of the soliton turbulence for further understanding of their impact on multi-soliton dynamics. Different types of solitons have been considered: “thick” or “top-table” solitons, algebraic solitons, solitons of different polarities. From the point of view of the turbulence theory, the interactions of waves (particles) should be described by the statistical moments of the wave field. These moments, with the exception of the first two, are not invariants of the equation and are not preserved within the time. It was shown that the interaction of solitons of the same polarity leads to a decrease in the third and fourth moments characterizing the skewness and kurtosis. However, the interaction of solitons of different polarity leads to an increase in these moments of the soliton field.
Then, the study of collision patterns of breathers (localized oscillating packets) with each other and with solitons has been carried out. The determination of conditions leading to an extreme scenario, as well as statistical properties, probability and features of large wave manifestation has been provided.
As a result of numerical modeling of the multi-soliton fields’ dynamics, the appearance of anomalously large waves in bipolar soliton fields has been demonstrated. Though most of the soliton collisions occur between the pairs of solitons, which may result in maximum two-fold wave amplification, multiple collisions also happen (they make about 10% of the total number of collisions). The long-term simulation of the soliton gas dynamics has shown a significant decrease in skewness and significant increase in kurtosis, confirming the fact of abnormally large waves’ (so-called “freak/rogue waves”) occurrence.
The reported study was funded by RFBR according to the research projects 19-35-60022 and 18-02-00042.
How to cite: Didenkulova, E.: Soliton turbulence in weakly nonlinear and weakly dispersive media, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4439, https://doi.org/10.5194/egusphere-egu2020-4439, 2020.
A short review on weakly nonlinear and weakly dispersive dynamics of soliton ensembles, the so-called soliton turbulence is given. Such processes take place in shallow water waves, internal waves in the atmosphere and the ocean, solid mechanics and astrophysical plasma; they are described by the integrable models of Korteweg – de Vries equation type (modified Korteweg – de Vries equation, Gardner equation). Here, soliton turbulence means an ensemble of solitons with random parameters. The property of solitons to interact elastically with each other gives rise to an obvious association with the gas of elastically colliding particles. Strictly speaking, soliton turbulence (soliton gas) is a deterministic dynamical system due to the integrability of equations describing the evolution of waves (solitons). However, due to the great complexity of its behavior (due to the large number of participating solitons and nonlinear nature of their interactions), the dynamics of the system can be considered random and, accordingly, may be investigated using methods typical for such problems.
Firstly, pair soliton collisions have been analyzed as an elementary act of the soliton turbulence for further understanding of their impact on multi-soliton dynamics. Different types of solitons have been considered: “thick” or “top-table” solitons, algebraic solitons, solitons of different polarities. From the point of view of the turbulence theory, the interactions of waves (particles) should be described by the statistical moments of the wave field. These moments, with the exception of the first two, are not invariants of the equation and are not preserved within the time. It was shown that the interaction of solitons of the same polarity leads to a decrease in the third and fourth moments characterizing the skewness and kurtosis. However, the interaction of solitons of different polarity leads to an increase in these moments of the soliton field.
Then, the study of collision patterns of breathers (localized oscillating packets) with each other and with solitons has been carried out. The determination of conditions leading to an extreme scenario, as well as statistical properties, probability and features of large wave manifestation has been provided.
As a result of numerical modeling of the multi-soliton fields’ dynamics, the appearance of anomalously large waves in bipolar soliton fields has been demonstrated. Though most of the soliton collisions occur between the pairs of solitons, which may result in maximum two-fold wave amplification, multiple collisions also happen (they make about 10% of the total number of collisions). The long-term simulation of the soliton gas dynamics has shown a significant decrease in skewness and significant increase in kurtosis, confirming the fact of abnormally large waves’ (so-called “freak/rogue waves”) occurrence.
The reported study was funded by RFBR according to the research projects 19-35-60022 and 18-02-00042.
How to cite: Didenkulova, E.: Soliton turbulence in weakly nonlinear and weakly dispersive media, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4439, https://doi.org/10.5194/egusphere-egu2020-4439, 2020.
EGU2020-2741 | Displays | NP7.1
Simulation of the dynamics of blocky media based on the Cosserat continuum theory using high-performance computationsVladimir Sadovskii and Oxana Sadovskaya
The method of numerical simulation based on the theory of an orthotropic elastic-plastic Cosserat continuum with a plasticity condition, that takes into account both the shear and rotational nature of irreversible deformation, is applied to the analysis of plastic deformation of structurally inhomogeneous materials. Within the assumption of a blocky structure of a material with elastic blocks interacting through compliant plastic interlayers, this condition limits the tangential components of the asymmetric stress tensor, which characterize shears, as well as the couple stresses, which limit values lead to an irreversible change in the curvature of deformed state of the continuum. The equations of translational and rotational motion together with the constitutive relations of the model are formulated as a variational inequality that correctly describes both the state of elastic-plastic deformation under active loading and the state of elastic unloading, [1]. For numerical implementation of mathematical model, the parallel computational algorithm and author’s software package for multiprocessor computer systems of the cluster architecture are used. With the help of the developed computational technology, [2], the problem of squeezing a rectangular block-type rock massif of a masonry by a rough non-deformable plate making a uniformly accelerated rotation is analysed. The influence of the yield strengths of compliant interlayers during shear and bending on the stress-strain state of the massif is investigated. The fields of displacements, stresses, couple stresses, angle of rotation, plastic energy dissipation of the structural elements are studied numerically. A detailed analysis of numerical solutions shows that the couple stresses and the associated curvatures have small effect on the final macroscale deformed state of the massif, which is characterized by the main quantities – displacements and corresponding stresses. The distribution of couple stresses takes a cellular structure, reflecting the heterogeneity of a material and the change in heterogeneity in the process of loading. Therefore, unlike conventional stresses, they should be associated with a mesoscale level of deformation of a structurally inhomogeneous material. Chaotic distribution of the energy of plastic dissipation due to a change in curvature in the entire volume of a medium confirms the hypothesis that the plasticization of a material at the meso-level is due to the rotational degrees of freedom of the particles.
This work was supported by the Russian Foundation for Basic Research, Government of Krasnoyarsk Territory, Krasnoyarsk Regional Fund of Science to the research project No. 18-41-242001.
References
- Sadovskaya O., Sadovskii V. Mathematical Modeling in Mechanics of Granular Materials. Ser.: Advanced Structured Materials, vol. 21. Springer, Heidelberg – New York – Dordrecht – London, 2012. 390 p.
- Sadovskii V.M., Sadovskaya O.V. Modeling of elastic waves in a blocky medium based on equations of the Cosserat continuum // Wave Motion. 2015. V. 52. P. 138–150.
How to cite: Sadovskii, V. and Sadovskaya, O.: Simulation of the dynamics of blocky media based on the Cosserat continuum theory using high-performance computations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2741, https://doi.org/10.5194/egusphere-egu2020-2741, 2020.
The method of numerical simulation based on the theory of an orthotropic elastic-plastic Cosserat continuum with a plasticity condition, that takes into account both the shear and rotational nature of irreversible deformation, is applied to the analysis of plastic deformation of structurally inhomogeneous materials. Within the assumption of a blocky structure of a material with elastic blocks interacting through compliant plastic interlayers, this condition limits the tangential components of the asymmetric stress tensor, which characterize shears, as well as the couple stresses, which limit values lead to an irreversible change in the curvature of deformed state of the continuum. The equations of translational and rotational motion together with the constitutive relations of the model are formulated as a variational inequality that correctly describes both the state of elastic-plastic deformation under active loading and the state of elastic unloading, [1]. For numerical implementation of mathematical model, the parallel computational algorithm and author’s software package for multiprocessor computer systems of the cluster architecture are used. With the help of the developed computational technology, [2], the problem of squeezing a rectangular block-type rock massif of a masonry by a rough non-deformable plate making a uniformly accelerated rotation is analysed. The influence of the yield strengths of compliant interlayers during shear and bending on the stress-strain state of the massif is investigated. The fields of displacements, stresses, couple stresses, angle of rotation, plastic energy dissipation of the structural elements are studied numerically. A detailed analysis of numerical solutions shows that the couple stresses and the associated curvatures have small effect on the final macroscale deformed state of the massif, which is characterized by the main quantities – displacements and corresponding stresses. The distribution of couple stresses takes a cellular structure, reflecting the heterogeneity of a material and the change in heterogeneity in the process of loading. Therefore, unlike conventional stresses, they should be associated with a mesoscale level of deformation of a structurally inhomogeneous material. Chaotic distribution of the energy of plastic dissipation due to a change in curvature in the entire volume of a medium confirms the hypothesis that the plasticization of a material at the meso-level is due to the rotational degrees of freedom of the particles.
This work was supported by the Russian Foundation for Basic Research, Government of Krasnoyarsk Territory, Krasnoyarsk Regional Fund of Science to the research project No. 18-41-242001.
References
- Sadovskaya O., Sadovskii V. Mathematical Modeling in Mechanics of Granular Materials. Ser.: Advanced Structured Materials, vol. 21. Springer, Heidelberg – New York – Dordrecht – London, 2012. 390 p.
- Sadovskii V.M., Sadovskaya O.V. Modeling of elastic waves in a blocky medium based on equations of the Cosserat continuum // Wave Motion. 2015. V. 52. P. 138–150.
How to cite: Sadovskii, V. and Sadovskaya, O.: Simulation of the dynamics of blocky media based on the Cosserat continuum theory using high-performance computations, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2741, https://doi.org/10.5194/egusphere-egu2020-2741, 2020.
EGU2020-3229 | Displays | NP7.1
Study on dynamic strength of sandstone based on SHPB numerical experimentationWengang Zhang, Fansheng Meng, and Qi Wang
It is unavoidable that in rock engineering practices such as mining and tunnel constructions rocks are subjected to dynamic loading impacts including blasting, seismic loading, rock burst, and so on. The mechanical parameters for rock strength obtained via traditional static tests are not capable of characterizing the dynamic strength of rock mass. Therefore, the conventionally adopted tests cannot be further applied to guide the design of rock engineering subjected to dynamic loadings. Therefore the determination of the dynamic strength is essential for practical engineering. In this study, sandstone is chosen as the experimental sample for Split Hopkinson Pressure Bar (SHPB) numerical simulation by FLAC3D. The validation demonstrated that rocks are prone to fail under dynamic loading impacts. Extensive simulations are also carried out to investigate the development of rock dynamic strength and evolution process of energy accumulation and release in rock mass for samples of various sizes subjected to different levels of dynamic loading and axial loading. The simulation results may provide design guidance for the safety protection of rock engineering subjected to dynamic impacts.
How to cite: Zhang, W., Meng, F., and Wang, Q.: Study on dynamic strength of sandstone based on SHPB numerical experimentation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3229, https://doi.org/10.5194/egusphere-egu2020-3229, 2020.
It is unavoidable that in rock engineering practices such as mining and tunnel constructions rocks are subjected to dynamic loading impacts including blasting, seismic loading, rock burst, and so on. The mechanical parameters for rock strength obtained via traditional static tests are not capable of characterizing the dynamic strength of rock mass. Therefore, the conventionally adopted tests cannot be further applied to guide the design of rock engineering subjected to dynamic loadings. Therefore the determination of the dynamic strength is essential for practical engineering. In this study, sandstone is chosen as the experimental sample for Split Hopkinson Pressure Bar (SHPB) numerical simulation by FLAC3D. The validation demonstrated that rocks are prone to fail under dynamic loading impacts. Extensive simulations are also carried out to investigate the development of rock dynamic strength and evolution process of energy accumulation and release in rock mass for samples of various sizes subjected to different levels of dynamic loading and axial loading. The simulation results may provide design guidance for the safety protection of rock engineering subjected to dynamic impacts.
How to cite: Zhang, W., Meng, F., and Wang, Q.: Study on dynamic strength of sandstone based on SHPB numerical experimentation, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3229, https://doi.org/10.5194/egusphere-egu2020-3229, 2020.
EGU2020-5882 | Displays | NP7.1
Self-consistency between input and output data for models describing elastic properties of fractured media: does conventional models satisfy this criterion?Andrey V. Radostin and Vladimir Yu. Zaitsev
Models that adequately describe the effect of crack-like defects on the elastic moduli of solids are one of the key "ingredients" needed to obtain diagnostic conclusions about the structural features of the material. The change in the velocities of longitudinal and shear elastic waves depending on the pressure is one of the most popular methods of measuring the connection of these moduli with the cracks present in the material. For commonly considered models with an isotropic crack orientation (which makes the medium on average isotropic), the measurement of these two velocities is sufficient to determine two independent moduli (for example, the shear and bulk moduli) through which other characteristics of interest can be expressed. In this case, the applied pressure, gradually closing the cracks, is a control parameter that regulates the concentration of cracks.
It is quite natural when constructing models to obtain expressions relating the elastic moduli with the crack concentration (the latter cannot be to directly monitored when the applied pressure is varied). In this regard, some additional considerations are used about the relationship of crack concentration to pressure, which allows one to relate the model expressions with the moduli measured during the pressure variation. Assuming some approximations relating the pressure and concentration with free fitting parameters in the model, it is possible to achieve the best agreement of model with the experimental dependences on pressure. This approach looks natural and is conventionally used, resulting in apparently satisfactory agreement between the model predictions and the measurement data.
Here we show that this apparent agreement is often achieved at the expense of strong violation of self-consistency between the input data fed into the model and the output of the model. This violation is far from obvious in conventional approaches based on the use of an auxiliary (and not directly measurable) relationship between concentration and pressure. To find out the fact of either violation or fulfillment of the condition of self-consistency, here we describe such a form of the model, in which its input parameters can be expressed in terms of experimentally measured values (in contrast to the crack concentration that cannot be monitored as a function of pressure). In the proposed description of the fractured material, the cracks are characterized by the shear- and normal compliances, the ratio of which is not a priori fixed and can be extracted from the experimental data.The proposed procedure of interpretation of experimental pressure dependences allows one to explicitly verify the model self-consistency and assess the elastic properties of real cracks that is many cases appear to be strongly different from the properties intrinsic to the standard penny-shape-crack model.
The reported study was supported by RFBR, project number 19-05-00536.
How to cite: Radostin, A. V. and Zaitsev, V. Yu.: Self-consistency between input and output data for models describing elastic properties of fractured media: does conventional models satisfy this criterion?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5882, https://doi.org/10.5194/egusphere-egu2020-5882, 2020.
Models that adequately describe the effect of crack-like defects on the elastic moduli of solids are one of the key "ingredients" needed to obtain diagnostic conclusions about the structural features of the material. The change in the velocities of longitudinal and shear elastic waves depending on the pressure is one of the most popular methods of measuring the connection of these moduli with the cracks present in the material. For commonly considered models with an isotropic crack orientation (which makes the medium on average isotropic), the measurement of these two velocities is sufficient to determine two independent moduli (for example, the shear and bulk moduli) through which other characteristics of interest can be expressed. In this case, the applied pressure, gradually closing the cracks, is a control parameter that regulates the concentration of cracks.
It is quite natural when constructing models to obtain expressions relating the elastic moduli with the crack concentration (the latter cannot be to directly monitored when the applied pressure is varied). In this regard, some additional considerations are used about the relationship of crack concentration to pressure, which allows one to relate the model expressions with the moduli measured during the pressure variation. Assuming some approximations relating the pressure and concentration with free fitting parameters in the model, it is possible to achieve the best agreement of model with the experimental dependences on pressure. This approach looks natural and is conventionally used, resulting in apparently satisfactory agreement between the model predictions and the measurement data.
Here we show that this apparent agreement is often achieved at the expense of strong violation of self-consistency between the input data fed into the model and the output of the model. This violation is far from obvious in conventional approaches based on the use of an auxiliary (and not directly measurable) relationship between concentration and pressure. To find out the fact of either violation or fulfillment of the condition of self-consistency, here we describe such a form of the model, in which its input parameters can be expressed in terms of experimentally measured values (in contrast to the crack concentration that cannot be monitored as a function of pressure). In the proposed description of the fractured material, the cracks are characterized by the shear- and normal compliances, the ratio of which is not a priori fixed and can be extracted from the experimental data.The proposed procedure of interpretation of experimental pressure dependences allows one to explicitly verify the model self-consistency and assess the elastic properties of real cracks that is many cases appear to be strongly different from the properties intrinsic to the standard penny-shape-crack model.
The reported study was supported by RFBR, project number 19-05-00536.
How to cite: Radostin, A. V. and Zaitsev, V. Yu.: Self-consistency between input and output data for models describing elastic properties of fractured media: does conventional models satisfy this criterion?, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5882, https://doi.org/10.5194/egusphere-egu2020-5882, 2020.
EGU2020-12195 | Displays | NP7.1
Experimental and CDEM Analysis on Crack Propagation Mechanism of Rock-Like Material Containing Flaws Under Uniaxial and Biaxial CompressionYong Li, Weishen Zhu, Chao Wei, Weibing Cai, Guannan Wu, Zhiheng Wang, and Weiqiu Kong
Abstract: Uniaxial and biaxial tests are performed to investigate the evolution mechanism of crack propagation and coalescence through developing newly cement mortar materials with horizontal and inclined pre-existing flaws. Additionally, a new numerical method-CDEM (Continuous discrete element method) is employed to analyze the evolution laws of stress field of crack tips under hydraulic coupling. The results reveal that the maximum principal stress of the wing crack tip gradually decreases with increase of internal water pressure, and the initiation stress, initiation angle and peak strength show decreasing trend. The results of crack propagation and coalescence obtained by numerical simulation is consistent with laboratory results. With the water pressure increases, prior to the occurrence of wing cracks, the coplanar cracks firstly initiate around inclined flaws. Under the coupling action of uniaxial compression and internal water pressure, the lateral pressure would limit the initiation of the wing cracks, while the increasing water pressure weakens the inhibition of lateral pressure on wing cracks.
How to cite: Li, Y., Zhu, W., Wei, C., Cai, W., Wu, G., Wang, Z., and Kong, W.: Experimental and CDEM Analysis on Crack Propagation Mechanism of Rock-Like Material Containing Flaws Under Uniaxial and Biaxial Compression, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12195, https://doi.org/10.5194/egusphere-egu2020-12195, 2020.
Abstract: Uniaxial and biaxial tests are performed to investigate the evolution mechanism of crack propagation and coalescence through developing newly cement mortar materials with horizontal and inclined pre-existing flaws. Additionally, a new numerical method-CDEM (Continuous discrete element method) is employed to analyze the evolution laws of stress field of crack tips under hydraulic coupling. The results reveal that the maximum principal stress of the wing crack tip gradually decreases with increase of internal water pressure, and the initiation stress, initiation angle and peak strength show decreasing trend. The results of crack propagation and coalescence obtained by numerical simulation is consistent with laboratory results. With the water pressure increases, prior to the occurrence of wing cracks, the coplanar cracks firstly initiate around inclined flaws. Under the coupling action of uniaxial compression and internal water pressure, the lateral pressure would limit the initiation of the wing cracks, while the increasing water pressure weakens the inhibition of lateral pressure on wing cracks.
How to cite: Li, Y., Zhu, W., Wei, C., Cai, W., Wu, G., Wang, Z., and Kong, W.: Experimental and CDEM Analysis on Crack Propagation Mechanism of Rock-Like Material Containing Flaws Under Uniaxial and Biaxial Compression, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12195, https://doi.org/10.5194/egusphere-egu2020-12195, 2020.
EGU2020-9960 | Displays | NP7.1
Analysis of the laboratory hydraulic fracturing curves.Helen Novikova and Mariia Trimonova
In this study, the data obtained during a series of laboratory experiments on hydraulic fracturing were analyzed. The main goal was to determine the time of the fracture closure, the pressure of the fracture closure, and the permeability of the sample, where the fracture was formed and propagated.
A special laboratory setup was used to conduct the experiments. The design of this setup allows to provide a three-axis load on the model sample, which makes the conditions of the laboratory experiment on hydraulic fracturing closer to the real conditions in the field. To produce the fracture, viscous fluid was injected under constant rate through the preliminary created cased borehole with perforations.
As results of the experiments, the curves of the fluid injection pressure variations with time were obtained. Their analysis was carried out using the G-function technique developed by Nordgren [1] and Nolte [2]. It is based on the plotting and analyzing of the behavior of the following dependencies: the injection pressure, first derivative of the pressure and the semi-logarithmic derivative of the pressure with respect to G-function. The curves processing allows to estimate the time of the fractures closure, with the help of which the fracture closure pressure was determined. The obtained pressure values were compared with the minimum stresses known from the experimental conditions.
Additionally, the permeability of the model reservoir sample was calculated using a technique developed by Horner [3] and improved by Nolte et al. [4]. The approach is based on an assumption that the fracture in the formation has been already closed, and a radial regime of fluid flow has been established. The obtained results were compared with the actual permeability, which was determined in the preliminary laboratory experiment.
Acknowledgements
The reported study was funded by RFBR, project number 20-35-80018, and state task 0146-2019-0007.
References
- Nordgren, R. P. [1972] Propagation of a vertical Hydraulic Fracture. SPE 45th Annual Fall Meeting, Houston, SPE-3009-PA.
- Nolte, K. G. [1979] Determination of Fracture Parameters from Fracturing Pressure Decline. The 54th Annual Fall Technical Conference and Exhibition of the Society of Petroleum Engineers of AIME, Las Vegas, SPE-8341-MS.
- Horner, D. R. [1951] Pressure Build-Up in Wells. 3rd World Petroleum Congress, Netherlands, WPC-4135.
- Nolte, K. G., Maniere, J. L., Owens, K. A. [1997] After-Closure Analysis of Fracture Calibration Tests. SPE Annual Technical Conference and Exhibition, San Antonio, Texas, SPE-38676-MS.
How to cite: Novikova, H. and Trimonova, M.: Analysis of the laboratory hydraulic fracturing curves., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9960, https://doi.org/10.5194/egusphere-egu2020-9960, 2020.
In this study, the data obtained during a series of laboratory experiments on hydraulic fracturing were analyzed. The main goal was to determine the time of the fracture closure, the pressure of the fracture closure, and the permeability of the sample, where the fracture was formed and propagated.
A special laboratory setup was used to conduct the experiments. The design of this setup allows to provide a three-axis load on the model sample, which makes the conditions of the laboratory experiment on hydraulic fracturing closer to the real conditions in the field. To produce the fracture, viscous fluid was injected under constant rate through the preliminary created cased borehole with perforations.
As results of the experiments, the curves of the fluid injection pressure variations with time were obtained. Their analysis was carried out using the G-function technique developed by Nordgren [1] and Nolte [2]. It is based on the plotting and analyzing of the behavior of the following dependencies: the injection pressure, first derivative of the pressure and the semi-logarithmic derivative of the pressure with respect to G-function. The curves processing allows to estimate the time of the fractures closure, with the help of which the fracture closure pressure was determined. The obtained pressure values were compared with the minimum stresses known from the experimental conditions.
Additionally, the permeability of the model reservoir sample was calculated using a technique developed by Horner [3] and improved by Nolte et al. [4]. The approach is based on an assumption that the fracture in the formation has been already closed, and a radial regime of fluid flow has been established. The obtained results were compared with the actual permeability, which was determined in the preliminary laboratory experiment.
Acknowledgements
The reported study was funded by RFBR, project number 20-35-80018, and state task 0146-2019-0007.
References
- Nordgren, R. P. [1972] Propagation of a vertical Hydraulic Fracture. SPE 45th Annual Fall Meeting, Houston, SPE-3009-PA.
- Nolte, K. G. [1979] Determination of Fracture Parameters from Fracturing Pressure Decline. The 54th Annual Fall Technical Conference and Exhibition of the Society of Petroleum Engineers of AIME, Las Vegas, SPE-8341-MS.
- Horner, D. R. [1951] Pressure Build-Up in Wells. 3rd World Petroleum Congress, Netherlands, WPC-4135.
- Nolte, K. G., Maniere, J. L., Owens, K. A. [1997] After-Closure Analysis of Fracture Calibration Tests. SPE Annual Technical Conference and Exhibition, San Antonio, Texas, SPE-38676-MS.
How to cite: Novikova, H. and Trimonova, M.: Analysis of the laboratory hydraulic fracturing curves., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9960, https://doi.org/10.5194/egusphere-egu2020-9960, 2020.
EGU2020-6008 | Displays | NP7.1
Analysis of seismicity caused by fluid injectionVasily Riga and Sergey Turuntaev
Induced seismicity associated with fluid injection into the subsurface is an important issue worldwide. Sometimes the fluid injection into a fault leads to aseismic creep of the fault or to microseismic events, but other times it results in more significant seismicity. In our work, we analyze the influence of various parameters of the fault and the rock, as well as the geometry of the model on induced seismicity. A case of well injecting water near a single fault was considered. To describe the slip process, several versions of the rate-and-state friction law was used. It was analyzed, how the model parameters, such as the position of the well relative to the fault, the permeability of the rock, the frictional properties of the fault affect the fault displacements. The problem of the poroelastic effect influence on the fault motion was also considered. Conditions that are favorable for the occurrence of noticeable seismicity were obtained. Difference in the fault behavior with one-parameter and two-parameter rate-and-state friction law were also considered.
How to cite: Riga, V. and Turuntaev, S.: Analysis of seismicity caused by fluid injection, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6008, https://doi.org/10.5194/egusphere-egu2020-6008, 2020.
Induced seismicity associated with fluid injection into the subsurface is an important issue worldwide. Sometimes the fluid injection into a fault leads to aseismic creep of the fault or to microseismic events, but other times it results in more significant seismicity. In our work, we analyze the influence of various parameters of the fault and the rock, as well as the geometry of the model on induced seismicity. A case of well injecting water near a single fault was considered. To describe the slip process, several versions of the rate-and-state friction law was used. It was analyzed, how the model parameters, such as the position of the well relative to the fault, the permeability of the rock, the frictional properties of the fault affect the fault displacements. The problem of the poroelastic effect influence on the fault motion was also considered. Conditions that are favorable for the occurrence of noticeable seismicity were obtained. Difference in the fault behavior with one-parameter and two-parameter rate-and-state friction law were also considered.
How to cite: Riga, V. and Turuntaev, S.: Analysis of seismicity caused by fluid injection, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6008, https://doi.org/10.5194/egusphere-egu2020-6008, 2020.
EGU2020-2754 | Displays | NP7.1
Analysis of seismic efficiency of the electromagnetic pulse source "Yenisei"Oxana Sadovskaya, Vladimir Sadovskii, and Evgenii Efimov
We developed a computational technology for numerical modeling of wave fields generated by seismic sources in blocky-layered geological media, and applied it to the analysis of efficiency of the electromagnetic pulse source of new generation "Yenisei", created recently by international geotechnical company "Geotech Seismic Services". To describe wave processes, we worked out new mathematical models of the dynamics of elastic, viscoelastic and elastic-plastic media, of porous and granular materials taking into account the increase in stiffness of such materials as pores collapse, [1]. Algorithms of numerical implementation of governing equations were realized for the cluster-type supercomputers, based on the method of two-cyclic splitting with respect to spatial variables. The conducted computational experiments have demonstrated that the proposed technology allows reproducing the system of waves near the region of excitation of seismic oscillations in 3D setting with a high degree of details and accuracy, [2]. We analysed frequencies and amplitudes of waves generated in the near-surface soils, and showed that our computational results are in a good agreement with seismic parameters of a real electromagnetic pulse source. We studied seismic efficiency of the pulse source as the ratio of the energy passing through the reflecting surface in the depth of layered massif to the energy of pulse effect on the surface. Besides, the energy of surface waves, which is obviously useless for the excitation of reflected waves, was estimated. To compare the energy efficiency of pulse sources with seismic sources of periodic action (vibrators), the problem of cyclic loading through the platform was solved numerically by the same method and the same geometric scheme. The seismic efficiency of vibrator was calculated by the maximum value of the energy fluxes during large time interval. Judging by computations, the pulse seismic sources are not inferior to the sources of vibratory type by seismic efficiency in the range of low frequencies. However, it is necessary to take into account that they differ sharply by the level of expended energy, because the energy of a pulse source, needed for generation of incident wave of a given amplitude, is many times lower than the energy of a vibrator.
The reported study was supported by the Russian Foundation for Basic Research, Government of Krasnoyarsk Territory, Krasnoyarsk Regional Fund of Science to the research project No. 18-41-242001: "Analysis of wavy seismic fields generated by the electromagnetic pulse source "Yenisei" in heterogeneous soil massifs during geological exploration in the conditions of northern regions of Eastern Siberia".
References
- Sadovskaya O., Sadovskii V. Mathematical Modeling in Mechanics of Granular Materials. Ser.: Advanced Structured Materials, vol. 21. Springer, Heidelberg – New York – Dordrecht – London, 2012. 390 p.
- Sadovskii V.M., Sadovskaya O.V., Efimov E.A. Analysis of seismic waves exited in near-surface soils by means of the electromagnetic pulse source "Yenisei". Materials Physics and Mechanics. 2019. V. 42, No. 5. P. 544–557.
How to cite: Sadovskaya, O., Sadovskii, V., and Efimov, E.: Analysis of seismic efficiency of the electromagnetic pulse source "Yenisei", EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2754, https://doi.org/10.5194/egusphere-egu2020-2754, 2020.
We developed a computational technology for numerical modeling of wave fields generated by seismic sources in blocky-layered geological media, and applied it to the analysis of efficiency of the electromagnetic pulse source of new generation "Yenisei", created recently by international geotechnical company "Geotech Seismic Services". To describe wave processes, we worked out new mathematical models of the dynamics of elastic, viscoelastic and elastic-plastic media, of porous and granular materials taking into account the increase in stiffness of such materials as pores collapse, [1]. Algorithms of numerical implementation of governing equations were realized for the cluster-type supercomputers, based on the method of two-cyclic splitting with respect to spatial variables. The conducted computational experiments have demonstrated that the proposed technology allows reproducing the system of waves near the region of excitation of seismic oscillations in 3D setting with a high degree of details and accuracy, [2]. We analysed frequencies and amplitudes of waves generated in the near-surface soils, and showed that our computational results are in a good agreement with seismic parameters of a real electromagnetic pulse source. We studied seismic efficiency of the pulse source as the ratio of the energy passing through the reflecting surface in the depth of layered massif to the energy of pulse effect on the surface. Besides, the energy of surface waves, which is obviously useless for the excitation of reflected waves, was estimated. To compare the energy efficiency of pulse sources with seismic sources of periodic action (vibrators), the problem of cyclic loading through the platform was solved numerically by the same method and the same geometric scheme. The seismic efficiency of vibrator was calculated by the maximum value of the energy fluxes during large time interval. Judging by computations, the pulse seismic sources are not inferior to the sources of vibratory type by seismic efficiency in the range of low frequencies. However, it is necessary to take into account that they differ sharply by the level of expended energy, because the energy of a pulse source, needed for generation of incident wave of a given amplitude, is many times lower than the energy of a vibrator.
The reported study was supported by the Russian Foundation for Basic Research, Government of Krasnoyarsk Territory, Krasnoyarsk Regional Fund of Science to the research project No. 18-41-242001: "Analysis of wavy seismic fields generated by the electromagnetic pulse source "Yenisei" in heterogeneous soil massifs during geological exploration in the conditions of northern regions of Eastern Siberia".
References
- Sadovskaya O., Sadovskii V. Mathematical Modeling in Mechanics of Granular Materials. Ser.: Advanced Structured Materials, vol. 21. Springer, Heidelberg – New York – Dordrecht – London, 2012. 390 p.
- Sadovskii V.M., Sadovskaya O.V., Efimov E.A. Analysis of seismic waves exited in near-surface soils by means of the electromagnetic pulse source "Yenisei". Materials Physics and Mechanics. 2019. V. 42, No. 5. P. 544–557.
How to cite: Sadovskaya, O., Sadovskii, V., and Efimov, E.: Analysis of seismic efficiency of the electromagnetic pulse source "Yenisei", EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2754, https://doi.org/10.5194/egusphere-egu2020-2754, 2020.
EGU2020-3837 | Displays | NP7.1
Probable reasons of Rock Sample Apparent Permeability Loss over Time in Long-term MeasurementsNikolay Baryshnikov, Evgeniy Zenchenko, and Sergey Turuntaev
In the last few years, tight oil production has increased significantly. This is why the study of the filtration properties of low-permeable rocks (permeability near 1 mD) has acquired particular significance. Such rocks can be subject to considerable compaction during development, which manifests itself in the non-linear permeability loss in time at constant net confining stress. In the laboratory, the compaction (or creep) of porous rock samples under constant stress conditions was observed by many researchers for experiment durations ranging from several hours to several weeks. Conducting such lengthy flow experiments accompanies by a number of challenges. First of all, it is necessary to exclude factors not related to the deformation of the sample. In this study we analyzed possible causes of time trends observed under constant net confining stresses in long-term measurements of low-permeable sample permeabilities. Experimental study of flow in a limestone core sample was conducted. During the experiment with duration of 40 days, the fluid pumping was carried out in several stages with different constant values of the confining pressure and the pore pressure gradient. As a result, the permeability of the sample decreased by 10 times. It was shown that such significant decrease in the permeability in time can be caused by clogging of the sample pore space. The additional experiment with sequential pumping of single-phase gas and liquid through the sample showed that when pumping gas, the sample permeability remained almost constant most of the time. We propose that gas bubbles contained in the flow of liquid can act as a dispersed phase that clogs pores. The estimations show that even very low particle concentrations at large time periods lead to significant decrease in the permeability. The possibility of clogging of the core sample pore space must be considered when conducting the long-term experiments on study of the permeability by the steady-state method.
How to cite: Baryshnikov, N., Zenchenko, E., and Turuntaev, S.: Probable reasons of Rock Sample Apparent Permeability Loss over Time in Long-term Measurements , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3837, https://doi.org/10.5194/egusphere-egu2020-3837, 2020.
In the last few years, tight oil production has increased significantly. This is why the study of the filtration properties of low-permeable rocks (permeability near 1 mD) has acquired particular significance. Such rocks can be subject to considerable compaction during development, which manifests itself in the non-linear permeability loss in time at constant net confining stress. In the laboratory, the compaction (or creep) of porous rock samples under constant stress conditions was observed by many researchers for experiment durations ranging from several hours to several weeks. Conducting such lengthy flow experiments accompanies by a number of challenges. First of all, it is necessary to exclude factors not related to the deformation of the sample. In this study we analyzed possible causes of time trends observed under constant net confining stresses in long-term measurements of low-permeable sample permeabilities. Experimental study of flow in a limestone core sample was conducted. During the experiment with duration of 40 days, the fluid pumping was carried out in several stages with different constant values of the confining pressure and the pore pressure gradient. As a result, the permeability of the sample decreased by 10 times. It was shown that such significant decrease in the permeability in time can be caused by clogging of the sample pore space. The additional experiment with sequential pumping of single-phase gas and liquid through the sample showed that when pumping gas, the sample permeability remained almost constant most of the time. We propose that gas bubbles contained in the flow of liquid can act as a dispersed phase that clogs pores. The estimations show that even very low particle concentrations at large time periods lead to significant decrease in the permeability. The possibility of clogging of the core sample pore space must be considered when conducting the long-term experiments on study of the permeability by the steady-state method.
How to cite: Baryshnikov, N., Zenchenko, E., and Turuntaev, S.: Probable reasons of Rock Sample Apparent Permeability Loss over Time in Long-term Measurements , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3837, https://doi.org/10.5194/egusphere-egu2020-3837, 2020.
EGU2020-3993 | Displays | NP7.1
Modular Korteweg - de Vries equation: Riemann, cnoidal and solitary wavesEfim Pelinovsky, Anna Kokorina, Alexey Slunyaev, and Elena Tobisch
The review paper by Oleg Rudenko [1] suggests several examples of elastic systems with so-called modular nonlinearities. In this study we consider the modular Korteweg - de Vries (KdV) equation in the form u_t + 6 u u_x + u_{xxx} = 0. This equation is not integrable by means of the Inverse Scattering Transform in the general case, but sign-defined functions which never change the sign satisfy the integrable KdV equation, and hence possess an exact solution. Firstly, we consider the dispersionless limit of the modular KdV equation and analyze the evolution of a simple nonlinear wave (Riemann wave) and its Fourier transform including the asymptotics when the wave tends to break [2]. Then, we study the structure of travelling waves. If the waves propagate on a pedestal and do not cross the zero level u = 0, they coincide with the well-known travelling wave solutions of the classic KdV equation in the form of cnoidal and solitary waves. If the pedestal is zero, the structure of sign-varying travelling waves is expressed through Jacobi elliptic functions. The interaction of solitary waves of different polarities is studied numerically using an implicit pseudo-spectral method. The simulation has revealed the inelastic character of the collision; in the course of the interaction the solitons can alter their amplitudes (the small soliton decreases and the large one grows) and emit small-amplitude waves. The inelastic effects are most pronounced when the solitons’ amplitudes are close. When their amplitudes differ significantly, the maximum wave height which is attained during the absorb-emit interaction tends to the sum of the heights of the solitons with the polarity inherited from the large soliton, as predicted in the frameworks of different long-wave integrable models in [3, 4]. As a result of the collision the solitons may experience non-classic phase shifts as they both jump back.
[1] O.V. Rudenko. Physics – Uspekhi, Vol. 56(7), 683-690 (2013).
[2] E. Tobisch, and E. Pelinovsky. Appl. Math. Lett., Vol. 97, 1-5 (2019).
[3] A.V. Slunyaev, and E.N. Pelinovsky. Phys. Rev. Lett., Vol. 117, 214501 (2016).
[4] A. Slunyaev. Stud. Appl. Math., Vol. 142, 385-413 (2019).
How to cite: Pelinovsky, E., Kokorina, A., Slunyaev, A., and Tobisch, E.: Modular Korteweg - de Vries equation: Riemann, cnoidal and solitary waves, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3993, https://doi.org/10.5194/egusphere-egu2020-3993, 2020.
The review paper by Oleg Rudenko [1] suggests several examples of elastic systems with so-called modular nonlinearities. In this study we consider the modular Korteweg - de Vries (KdV) equation in the form u_t + 6 u u_x + u_{xxx} = 0. This equation is not integrable by means of the Inverse Scattering Transform in the general case, but sign-defined functions which never change the sign satisfy the integrable KdV equation, and hence possess an exact solution. Firstly, we consider the dispersionless limit of the modular KdV equation and analyze the evolution of a simple nonlinear wave (Riemann wave) and its Fourier transform including the asymptotics when the wave tends to break [2]. Then, we study the structure of travelling waves. If the waves propagate on a pedestal and do not cross the zero level u = 0, they coincide with the well-known travelling wave solutions of the classic KdV equation in the form of cnoidal and solitary waves. If the pedestal is zero, the structure of sign-varying travelling waves is expressed through Jacobi elliptic functions. The interaction of solitary waves of different polarities is studied numerically using an implicit pseudo-spectral method. The simulation has revealed the inelastic character of the collision; in the course of the interaction the solitons can alter their amplitudes (the small soliton decreases and the large one grows) and emit small-amplitude waves. The inelastic effects are most pronounced when the solitons’ amplitudes are close. When their amplitudes differ significantly, the maximum wave height which is attained during the absorb-emit interaction tends to the sum of the heights of the solitons with the polarity inherited from the large soliton, as predicted in the frameworks of different long-wave integrable models in [3, 4]. As a result of the collision the solitons may experience non-classic phase shifts as they both jump back.
[1] O.V. Rudenko. Physics – Uspekhi, Vol. 56(7), 683-690 (2013).
[2] E. Tobisch, and E. Pelinovsky. Appl. Math. Lett., Vol. 97, 1-5 (2019).
[3] A.V. Slunyaev, and E.N. Pelinovsky. Phys. Rev. Lett., Vol. 117, 214501 (2016).
[4] A. Slunyaev. Stud. Appl. Math., Vol. 142, 385-413 (2019).
How to cite: Pelinovsky, E., Kokorina, A., Slunyaev, A., and Tobisch, E.: Modular Korteweg - de Vries equation: Riemann, cnoidal and solitary waves, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3993, https://doi.org/10.5194/egusphere-egu2020-3993, 2020.
EGU2020-21399 | Displays | NP7.1
Stability of fragmented and blocky solidsIgor Shufrin, Elena Pasternak, and Arcady Dyskin
Fragmented geomaterials are discontinuous solids assembled of blocks, which are not joined together by any binder. The integrity of these solids is provided by interlocking of the interfaces between the fragments and compression applied at the boundary of the assembly. The main distinctive feature of these solids is the ability of separate fragments to move and rotate independently within the geometric constraints imposed by the neighbouring elements. Under application of external loads the fragments partially lose contact – the blocks get detached in a part of their contact area – that reduces the stiffness of entire blocky structure. The compression applied at the boundaries of the structure restores these contacts and brings shifted blocks back to their place. At the same time, this external compression can cause instability of the assembly, in particular when applied over heavily detached interfaces. This instability mechanism is highly non-linear due to the rotation of the fragments that produce elbowing effect and increases the compression.
In order to assess the stability of fragmented solids, we carried out a series of experiments on the fragmented beams assembled of prismatic blocks and topologically interlocked osteomorphic blocks. The beams were axially prestressed and loaded in the transverse direction. We observed that the blocky beams can exhibit negative stiffness in the certain testing regimes. The block rotations observed during bending decrease the bending stiffness of the beam through the partial detachments between the fragments, while increasing the axial force due to the elbowing effect, which allows the beam to sustain additional bending deformations without increase in the external loading. This apparent negative stiffness is controlled by the combination of the prestress levels and rigidity of the axial beam constraints. We also verified these results through finite element simulations and analytical modelling.
Acknowledgements: This research was supported by the ISRAEL SCIENCE FOUNDATION (grant No. 1345/19).
How to cite: Shufrin, I., Pasternak, E., and Dyskin, A.: Stability of fragmented and blocky solids, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21399, https://doi.org/10.5194/egusphere-egu2020-21399, 2020.
Fragmented geomaterials are discontinuous solids assembled of blocks, which are not joined together by any binder. The integrity of these solids is provided by interlocking of the interfaces between the fragments and compression applied at the boundary of the assembly. The main distinctive feature of these solids is the ability of separate fragments to move and rotate independently within the geometric constraints imposed by the neighbouring elements. Under application of external loads the fragments partially lose contact – the blocks get detached in a part of their contact area – that reduces the stiffness of entire blocky structure. The compression applied at the boundaries of the structure restores these contacts and brings shifted blocks back to their place. At the same time, this external compression can cause instability of the assembly, in particular when applied over heavily detached interfaces. This instability mechanism is highly non-linear due to the rotation of the fragments that produce elbowing effect and increases the compression.
In order to assess the stability of fragmented solids, we carried out a series of experiments on the fragmented beams assembled of prismatic blocks and topologically interlocked osteomorphic blocks. The beams were axially prestressed and loaded in the transverse direction. We observed that the blocky beams can exhibit negative stiffness in the certain testing regimes. The block rotations observed during bending decrease the bending stiffness of the beam through the partial detachments between the fragments, while increasing the axial force due to the elbowing effect, which allows the beam to sustain additional bending deformations without increase in the external loading. This apparent negative stiffness is controlled by the combination of the prestress levels and rigidity of the axial beam constraints. We also verified these results through finite element simulations and analytical modelling.
Acknowledgements: This research was supported by the ISRAEL SCIENCE FOUNDATION (grant No. 1345/19).
How to cite: Shufrin, I., Pasternak, E., and Dyskin, A.: Stability of fragmented and blocky solids, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21399, https://doi.org/10.5194/egusphere-egu2020-21399, 2020.
In this study, surface contact involving sections with symmetric and asymmetric friction (different magnitudes of friction are encountered when moving in opposite direction) is considered. The asymmetric friction phenomenon considered here is created when blocks of anisotropic material with symmetric axis inclined to the contact area moves in a constraint environment. Bafekrpour et al. (2015) have shown this arrangement can create high levels of asymmetric friction by coupling shear and normal forces. We consider a spring- blocks model of the type proposed by Burridge and Knopoff (1967): multiple blocks – some blocks with asymmetric friction property and others with symmetric friction property – connected by springs. Each of these blocks are connected by a spring to a driving block. Two types motion for the driving block are considered: moving at constant velocity and constant velocity with an oscillation. Parametric analysis has been conducted to compare the difference in dynamics when comparing surface interaction involving only symmetric friction blocks to different combinations of asymmetric and symmetric friction blocks. We show that threshold for instability/motion can be controlled by the proportion of asymmetric friction section present in the system and the magnitude of friction involved in the asymmetric friction section. The characteristic of the system’s motion is also shown to be affected by the arrangement asymmetric and symmetric friction sections.
Bafekrpour, E., A.V. Dyskin, E. Pasternak, A. Molotnikov and Y. Estrin (2015), Internally architectured materials with directionally asymmetric friction. Scientific Reports, 5, Article 10732.
Burridge, R. and L. Knopoff, 1967. Model and theoretical seismicity. Bulletin of the Seismological Society of America, 57(3) 341-371.
How to cite: Wong, R. X.: Asymmetric friction effects in surface interaction, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22426, https://doi.org/10.5194/egusphere-egu2020-22426, 2020.
In this study, surface contact involving sections with symmetric and asymmetric friction (different magnitudes of friction are encountered when moving in opposite direction) is considered. The asymmetric friction phenomenon considered here is created when blocks of anisotropic material with symmetric axis inclined to the contact area moves in a constraint environment. Bafekrpour et al. (2015) have shown this arrangement can create high levels of asymmetric friction by coupling shear and normal forces. We consider a spring- blocks model of the type proposed by Burridge and Knopoff (1967): multiple blocks – some blocks with asymmetric friction property and others with symmetric friction property – connected by springs. Each of these blocks are connected by a spring to a driving block. Two types motion for the driving block are considered: moving at constant velocity and constant velocity with an oscillation. Parametric analysis has been conducted to compare the difference in dynamics when comparing surface interaction involving only symmetric friction blocks to different combinations of asymmetric and symmetric friction blocks. We show that threshold for instability/motion can be controlled by the proportion of asymmetric friction section present in the system and the magnitude of friction involved in the asymmetric friction section. The characteristic of the system’s motion is also shown to be affected by the arrangement asymmetric and symmetric friction sections.
Bafekrpour, E., A.V. Dyskin, E. Pasternak, A. Molotnikov and Y. Estrin (2015), Internally architectured materials with directionally asymmetric friction. Scientific Reports, 5, Article 10732.
Burridge, R. and L. Knopoff, 1967. Model and theoretical seismicity. Bulletin of the Seismological Society of America, 57(3) 341-371.
How to cite: Wong, R. X.: Asymmetric friction effects in surface interaction, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22426, https://doi.org/10.5194/egusphere-egu2020-22426, 2020.
EGU2020-22252 | Displays | NP7.1
Self-similar solution analysis of hydraulic fracture growth with bottom hole pressure restrictionGrigory Paderin
Nowadays hydraulic fracturing is an essential part of the development of low-permeability oil and gas fields. Moreover, the well productivity dynamics is radically depends on the effectiveness of fracturing treatment. One of the main hydraulic fracturing design problem is create a long fracture without crack height growth into the intervals saturated with non-target fluid (e.g. water). The obtaining self-similar solution to this problem in the framework of the Pserudo3D [1-3] model is considered in the presented study.
The presented crack propagation analysis shows that in the case of constant bottom hole pressure the automodel solution of one variable could be derived. A study on the dependence of the solution on pressure, time, hydraulic fluid properties and leak off is also conducted.
REFERENCES
[1] J.I. Adachi, E. Detournay, and A. P. Peirce // Analysis of the classical pseudo-3D model for hydraulic fracture with equilibrium height growth across stress barriers. International Journal of Rock Mechanics and Mining Sciences. 2010. 47 (4): 625–639.
[2] X. Weng, O. Kresse, C. Cohen, R. Wu, and H. Gu // Modeling of hydraulic-fracture-network propagation in a naturally fractured formation. SPE Production & Operations 2011. 26 (4): 368–380. doi:10.2118/140253-PA.
[3] G.V. Paderin // Proxy Pseudo3D model: the optimum of speed and accuracy in hydraulic fracturing simulation. IOP Conference Series: Earth and Environmental Science. 2018.
How to cite: Paderin, G.: Self-similar solution analysis of hydraulic fracture growth with bottom hole pressure restriction, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22252, https://doi.org/10.5194/egusphere-egu2020-22252, 2020.
Nowadays hydraulic fracturing is an essential part of the development of low-permeability oil and gas fields. Moreover, the well productivity dynamics is radically depends on the effectiveness of fracturing treatment. One of the main hydraulic fracturing design problem is create a long fracture without crack height growth into the intervals saturated with non-target fluid (e.g. water). The obtaining self-similar solution to this problem in the framework of the Pserudo3D [1-3] model is considered in the presented study.
The presented crack propagation analysis shows that in the case of constant bottom hole pressure the automodel solution of one variable could be derived. A study on the dependence of the solution on pressure, time, hydraulic fluid properties and leak off is also conducted.
REFERENCES
[1] J.I. Adachi, E. Detournay, and A. P. Peirce // Analysis of the classical pseudo-3D model for hydraulic fracture with equilibrium height growth across stress barriers. International Journal of Rock Mechanics and Mining Sciences. 2010. 47 (4): 625–639.
[2] X. Weng, O. Kresse, C. Cohen, R. Wu, and H. Gu // Modeling of hydraulic-fracture-network propagation in a naturally fractured formation. SPE Production & Operations 2011. 26 (4): 368–380. doi:10.2118/140253-PA.
[3] G.V. Paderin // Proxy Pseudo3D model: the optimum of speed and accuracy in hydraulic fracturing simulation. IOP Conference Series: Earth and Environmental Science. 2018.
How to cite: Paderin, G.: Self-similar solution analysis of hydraulic fracture growth with bottom hole pressure restriction, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-22252, https://doi.org/10.5194/egusphere-egu2020-22252, 2020.
EGU2020-4046 | Displays | NP7.1
The effect of seismic-like induced cyclic loading on damage response of sandstone and graniteRashid Geranmayeh Vaneghi, Arcady V. Dyskin, Klaus Thoeni, Mostafa Sharifzadeh, and Mohammad Sarmadivaleh
The detailed study of rock response to cyclic loading induced by natural phenomena, such as seismic and volcanic activities, and man-made explosions and excavation is necessary for failure prediction and hazard mitigation. The effect of the maximum stress level, loading amplitude, and frequency of stress cycles on the fatigue life and failure mechanisms of two microstructurally different rocks of granite/granodiorite and sandstone is investigated. Test data obtained from comprehensive experiments conducted on these rock types incorporated with the results of previous studies show that the fatigue life time of both rock types increases with a decrease in either maximum stress level or stress amplitude. Nevertheless, the fatigue strength threshold of hard rocks like granite is generally lower than that of soft rocks like sandstone. The study also shows that the low-frequency cyclic loading has more damaging effect on both rock types than the high frequency loading. This investigation demonstrates that the failure mechanism of rocks under cyclic loading is characterized by the development of more tensile microcracks compared to the monotonic loading and the opening and extension of the axial tensile microfractures are more evident at higher maximum stresses or loading amplitudes or at lower loading frequencies. The results presented in this study will contribute to a deeper understanding of the fatigue responses of sandstone and granite to seismic-generated loading–unloading processes under different conditions of stress cycles.
How to cite: Geranmayeh Vaneghi, R., V. Dyskin, A., Thoeni, K., Sharifzadeh, M., and Sarmadivaleh, M.: The effect of seismic-like induced cyclic loading on damage response of sandstone and granite, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4046, https://doi.org/10.5194/egusphere-egu2020-4046, 2020.
The detailed study of rock response to cyclic loading induced by natural phenomena, such as seismic and volcanic activities, and man-made explosions and excavation is necessary for failure prediction and hazard mitigation. The effect of the maximum stress level, loading amplitude, and frequency of stress cycles on the fatigue life and failure mechanisms of two microstructurally different rocks of granite/granodiorite and sandstone is investigated. Test data obtained from comprehensive experiments conducted on these rock types incorporated with the results of previous studies show that the fatigue life time of both rock types increases with a decrease in either maximum stress level or stress amplitude. Nevertheless, the fatigue strength threshold of hard rocks like granite is generally lower than that of soft rocks like sandstone. The study also shows that the low-frequency cyclic loading has more damaging effect on both rock types than the high frequency loading. This investigation demonstrates that the failure mechanism of rocks under cyclic loading is characterized by the development of more tensile microcracks compared to the monotonic loading and the opening and extension of the axial tensile microfractures are more evident at higher maximum stresses or loading amplitudes or at lower loading frequencies. The results presented in this study will contribute to a deeper understanding of the fatigue responses of sandstone and granite to seismic-generated loading–unloading processes under different conditions of stress cycles.
How to cite: Geranmayeh Vaneghi, R., V. Dyskin, A., Thoeni, K., Sharifzadeh, M., and Sarmadivaleh, M.: The effect of seismic-like induced cyclic loading on damage response of sandstone and granite, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4046, https://doi.org/10.5194/egusphere-egu2020-4046, 2020.
EGU2020-10275 | Displays | NP7.1
Interaction of a hydraulic fracture with parallel pre-existing fracturesHaijun Wang, Shuyang Yu, Xuhua Ren, Lei Tang, Arcady Dyskin, and Elena Pasternak
Formation and growth of hydraulic fractures can be strongly affected by pre-existing fractures in the rock mass. Until now the main attention was directed towards the investigation of the interaction between the hydraulic fracture and the pre-existing fractures intersecting its path, as they could significantly hamper its formation and growth, alter the geometry and produce additional leak-off. Less attention was paid to the interaction of the hydraulic fracture with parallel and coplanar pre-existing fractures, yet their interaction and coalescence can lead to unwelcome increase in the hydraulic fracture dimensions, change the direction of growth and in some cases result in undesirable effects such as environmental damage.
In order to investigate the hydraulic fracture interaction with parallel pre-existing fractures we conducted a series of tests on transparent rectangular samples with two artificial cracks. One of the crack was loaded with pressurised fluid. The types of interaction were classified and the conditions of fracture coalescence formulated. The results will contribute to the understanding of hydraulic fracture propagation in fractured rock masses and mitigating environmental damage.
Acknowledgements. Wang acknowledge support from the Natural Scinece Foundation of Jiangsu (BK20171130). The AVD and EP acknowledge support from the Australian Research Council through project DP190103260. AVD acknowledges the support from the School of Civil and Transportation, Faculty of Engineering, Beijing University of Civil Engineering and Architecture. Wang acknowledge support from the National Natural Science Fund (51409170,U1765204)
How to cite: Wang, H., Yu, S., Ren, X., Tang, L., Dyskin, A., and Pasternak, E.: Interaction of a hydraulic fracture with parallel pre-existing fractures, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10275, https://doi.org/10.5194/egusphere-egu2020-10275, 2020.
Formation and growth of hydraulic fractures can be strongly affected by pre-existing fractures in the rock mass. Until now the main attention was directed towards the investigation of the interaction between the hydraulic fracture and the pre-existing fractures intersecting its path, as they could significantly hamper its formation and growth, alter the geometry and produce additional leak-off. Less attention was paid to the interaction of the hydraulic fracture with parallel and coplanar pre-existing fractures, yet their interaction and coalescence can lead to unwelcome increase in the hydraulic fracture dimensions, change the direction of growth and in some cases result in undesirable effects such as environmental damage.
In order to investigate the hydraulic fracture interaction with parallel pre-existing fractures we conducted a series of tests on transparent rectangular samples with two artificial cracks. One of the crack was loaded with pressurised fluid. The types of interaction were classified and the conditions of fracture coalescence formulated. The results will contribute to the understanding of hydraulic fracture propagation in fractured rock masses and mitigating environmental damage.
Acknowledgements. Wang acknowledge support from the Natural Scinece Foundation of Jiangsu (BK20171130). The AVD and EP acknowledge support from the Australian Research Council through project DP190103260. AVD acknowledges the support from the School of Civil and Transportation, Faculty of Engineering, Beijing University of Civil Engineering and Architecture. Wang acknowledge support from the National Natural Science Fund (51409170,U1765204)
How to cite: Wang, H., Yu, S., Ren, X., Tang, L., Dyskin, A., and Pasternak, E.: Interaction of a hydraulic fracture with parallel pre-existing fractures, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10275, https://doi.org/10.5194/egusphere-egu2020-10275, 2020.
EGU2020-19507 | Displays | NP7.1
Hydraulic fracture oscillations in response to strong impulseElena Pasternak and Arcady Dyskin
Hydraulic fractures and the natural fractures in rock masses are closed by the in-situ compressive stress such that their opposite faces are in contact either with each other or with the proppant in hydraulic fractures or with gouge in the natural fractures. Subsequently, a pressure increase can produce negligible deformation in already closed fractures as compared to the deformation associated with the opening caused by sufficiently large tensile stress. This suggests a simple model of closed fracture as a bilinear spring with a certain stiffness in tension and a very high (potentially infinite) stiffness in compression. Therefore the oscillations of fractures can be reduced to the oscillations of a bilinear oscillator or impact oscillator [1] when the compressive stiffness considerably exceeds the tensile one. We use the simplest model of the impact oscillator with preload representing the action of the in-situ compressive stress. Based on this model, two sets of multiple resonances are identified and the reaction to impulsive load is determined. The harmonics of free oscillations are calculated. The knowledge of the first two harmonics is sufficient to recover the tensile stiffness and hence identify the geometric parameters of the fracture. The results of the research contribute to the development of the methods of fracture reconstruction and the hydraulic fracture monitoring.
- Dyskin, A.V., E. Pasternak and E. Pelinovsky, 2012. Periodic motions and resonances of impact oscillators. Journal of Sound and Vibration 331(12) 2856-2873. ISBN/ISSN 0022-460X, 04/06/2012.
Acknowledgements. The authors acknowledge support from the Australian Research Council through project DP190103260. AVD acknowledges the support from the School of Civil and Transportation, Faculty of Engineering, Beijing University of Civil Engineering and Architecture.
How to cite: Pasternak, E. and Dyskin, A.: Hydraulic fracture oscillations in response to strong impulse, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19507, https://doi.org/10.5194/egusphere-egu2020-19507, 2020.
Hydraulic fractures and the natural fractures in rock masses are closed by the in-situ compressive stress such that their opposite faces are in contact either with each other or with the proppant in hydraulic fractures or with gouge in the natural fractures. Subsequently, a pressure increase can produce negligible deformation in already closed fractures as compared to the deformation associated with the opening caused by sufficiently large tensile stress. This suggests a simple model of closed fracture as a bilinear spring with a certain stiffness in tension and a very high (potentially infinite) stiffness in compression. Therefore the oscillations of fractures can be reduced to the oscillations of a bilinear oscillator or impact oscillator [1] when the compressive stiffness considerably exceeds the tensile one. We use the simplest model of the impact oscillator with preload representing the action of the in-situ compressive stress. Based on this model, two sets of multiple resonances are identified and the reaction to impulsive load is determined. The harmonics of free oscillations are calculated. The knowledge of the first two harmonics is sufficient to recover the tensile stiffness and hence identify the geometric parameters of the fracture. The results of the research contribute to the development of the methods of fracture reconstruction and the hydraulic fracture monitoring.
- Dyskin, A.V., E. Pasternak and E. Pelinovsky, 2012. Periodic motions and resonances of impact oscillators. Journal of Sound and Vibration 331(12) 2856-2873. ISBN/ISSN 0022-460X, 04/06/2012.
Acknowledgements. The authors acknowledge support from the Australian Research Council through project DP190103260. AVD acknowledges the support from the School of Civil and Transportation, Faculty of Engineering, Beijing University of Civil Engineering and Architecture.
How to cite: Pasternak, E. and Dyskin, A.: Hydraulic fracture oscillations in response to strong impulse, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19507, https://doi.org/10.5194/egusphere-egu2020-19507, 2020.
EGU2020-19431 | Displays | NP7.1
Intra-sonic propagation of sliding zones in a faultArcady Dyskin and Elena Pasternak
Seismic events associated with pre-existing faults are traditionally assumed to be caused by rupture propagation, that is in-plane shear crack propagation. However what appears to be a shear crack is a sliding zone over a fault; it grows by overcoming friction (either in direct contact or in the gouge) rather than rock rupture. When modelling frictional sliding, two important factors need to be considered: (1) the elasticity of the surrounding rocks which causes self-oscillations resulting in the movement resembling stick-slip even in constant friction; (2) the rotation of real gouge particles which being non-spherical lead, in the presence of compression, to the effect of negative shear stiffness. The latter effectively works to transfer the elastic energy stored in the compressed rock into the energy of the sliding zone propagation.
This presentation introduces 1D models accounting for these factors. Both lead to the so-called telegraph equation which is a wave equation with a non-derivative term referring to the fact that the movement is considered against a stationary solid. The equation with respect to displacement corresponds to the case of apparent negative stiffness, while the equation with respect to the displacement rate corresponds to the pure frictional sliding. The rock elasticity leads to the sliding zone propagation speed equal to the p-wave velocity making the propagation speed intra-sonic [1]. The rate-dependent friction can slightly reduce the speed. It is interesting that the sliding zone propagation is related to p-wave rather than s- or Raylegh waves as one would anticipate. The results of this research contribute to the understanding of the mechanics of seismicity.
- Karachevtseva, I, A.V. Dyskin and E. Pasternak, 2017. Generation and propagation of stick-slip waves over a fault with rate-independent friction. Nonlinear Processes in Geophysics (NPG), 24, 343-349.
Acknowledgements. AVD acknowledges the support from the School of Civil and Transportation, Faculty of Engineering, Beijing University of Civil Engineering and Architecture.
How to cite: Dyskin, A. and Pasternak, E.: Intra-sonic propagation of sliding zones in a fault, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19431, https://doi.org/10.5194/egusphere-egu2020-19431, 2020.
Seismic events associated with pre-existing faults are traditionally assumed to be caused by rupture propagation, that is in-plane shear crack propagation. However what appears to be a shear crack is a sliding zone over a fault; it grows by overcoming friction (either in direct contact or in the gouge) rather than rock rupture. When modelling frictional sliding, two important factors need to be considered: (1) the elasticity of the surrounding rocks which causes self-oscillations resulting in the movement resembling stick-slip even in constant friction; (2) the rotation of real gouge particles which being non-spherical lead, in the presence of compression, to the effect of negative shear stiffness. The latter effectively works to transfer the elastic energy stored in the compressed rock into the energy of the sliding zone propagation.
This presentation introduces 1D models accounting for these factors. Both lead to the so-called telegraph equation which is a wave equation with a non-derivative term referring to the fact that the movement is considered against a stationary solid. The equation with respect to displacement corresponds to the case of apparent negative stiffness, while the equation with respect to the displacement rate corresponds to the pure frictional sliding. The rock elasticity leads to the sliding zone propagation speed equal to the p-wave velocity making the propagation speed intra-sonic [1]. The rate-dependent friction can slightly reduce the speed. It is interesting that the sliding zone propagation is related to p-wave rather than s- or Raylegh waves as one would anticipate. The results of this research contribute to the understanding of the mechanics of seismicity.
- Karachevtseva, I, A.V. Dyskin and E. Pasternak, 2017. Generation and propagation of stick-slip waves over a fault with rate-independent friction. Nonlinear Processes in Geophysics (NPG), 24, 343-349.
Acknowledgements. AVD acknowledges the support from the School of Civil and Transportation, Faculty of Engineering, Beijing University of Civil Engineering and Architecture.
How to cite: Dyskin, A. and Pasternak, E.: Intra-sonic propagation of sliding zones in a fault, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-19431, https://doi.org/10.5194/egusphere-egu2020-19431, 2020.
EGU2020-9064 | Displays | NP7.1
Rotational waves in fragmented and blocky geomaterialsJunxian He, Elena Pasternak, Arcady Dyskin, and Igor Shufrin
An important mechanism of oscillation and wave propagation in fragmented and blocky geomaterials such as rock masses and the Earth’s crust is the movement and rotation of the fragments/blocks as rigid bodies with deformation mainly residing at the interfaces. There are cases when the gouge in the interfaces is very weak and soft such that the resistance to parting the fragments is provided by the ambient compression which prevents the fragments/blocks from parting but allows their mutual rotation.
In order to investigate this type of block movement we performed a series of vibration tests on blocky beams of different heights under horizontal vibrations of the base. The fragmented/blocky geomaterial was modelled using osteomorphic blocks. The osteomorphic blocks have a special shape that ensures topological interlocking. The assembly is an engineered material with internal architecture which captures the fragmented and blocky nature of geomaterials [1]. The observations using the DIC technique confirm that the blocks undergo relative rotational movement. The associated rotational waves travel within the assembly transferring the energy within the blocks. This is an extension of our previous analysis that established the formation of stationary points in fragmented bodies [2]. There is energy exchange between the assembly and the loading device. The energy calculations show that the energy fluctuates around a constant value. The spectrum of block oscillations exhibits the main peak corresponding to the driving frequency as well as secondary peaks that correspond to the multiples of the driving frequency. This is in line with our previous results on bilinear oscillators [3]. The results contribute to the understanding of wave propagation in blocky/fragmented rock mass and the Earth’s crust.
- Pasternak, E., A.V. Dyskin and Y. Estrin, 2006. Deformations in transform faults with rotating crustal blocks. PAGEOPH, 163, 2011-2030.
- Dyskin, A.V., E. Pasternak and I. Shufrin, 2014. Structure of resonances and formation of stationary points in symmetrical chains of bilinear oscillators. Journal of Sound and Vibration 333, 6590–6606.
- Dyskin, A.V., E. Pasternak and E. Pelinovsky, 2012. Periodic motions and resonances of impact oscillators. Journal of Sound and Vibration 331(12) 2856-2873. ISBN/ISSN 0022-460X, 04/06/2012.
Acknowledgements. The authors acknowledge support from the Australian Research Council through project DP190103260. The authors acknowledge the UWA workshop in developing and manufacturing the experimental setup. In the experiments some setup fixtures previously developed by M. Khudyakov were used. AVD acknowledges the support from the School of Civil and Transportation, Faculty of Engineering, Beijing University of Civil Engineering and Architecture.
How to cite: He, J., Pasternak, E., Dyskin, A., and Shufrin, I.: Rotational waves in fragmented and blocky geomaterials, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9064, https://doi.org/10.5194/egusphere-egu2020-9064, 2020.
An important mechanism of oscillation and wave propagation in fragmented and blocky geomaterials such as rock masses and the Earth’s crust is the movement and rotation of the fragments/blocks as rigid bodies with deformation mainly residing at the interfaces. There are cases when the gouge in the interfaces is very weak and soft such that the resistance to parting the fragments is provided by the ambient compression which prevents the fragments/blocks from parting but allows their mutual rotation.
In order to investigate this type of block movement we performed a series of vibration tests on blocky beams of different heights under horizontal vibrations of the base. The fragmented/blocky geomaterial was modelled using osteomorphic blocks. The osteomorphic blocks have a special shape that ensures topological interlocking. The assembly is an engineered material with internal architecture which captures the fragmented and blocky nature of geomaterials [1]. The observations using the DIC technique confirm that the blocks undergo relative rotational movement. The associated rotational waves travel within the assembly transferring the energy within the blocks. This is an extension of our previous analysis that established the formation of stationary points in fragmented bodies [2]. There is energy exchange between the assembly and the loading device. The energy calculations show that the energy fluctuates around a constant value. The spectrum of block oscillations exhibits the main peak corresponding to the driving frequency as well as secondary peaks that correspond to the multiples of the driving frequency. This is in line with our previous results on bilinear oscillators [3]. The results contribute to the understanding of wave propagation in blocky/fragmented rock mass and the Earth’s crust.
- Pasternak, E., A.V. Dyskin and Y. Estrin, 2006. Deformations in transform faults with rotating crustal blocks. PAGEOPH, 163, 2011-2030.
- Dyskin, A.V., E. Pasternak and I. Shufrin, 2014. Structure of resonances and formation of stationary points in symmetrical chains of bilinear oscillators. Journal of Sound and Vibration 333, 6590–6606.
- Dyskin, A.V., E. Pasternak and E. Pelinovsky, 2012. Periodic motions and resonances of impact oscillators. Journal of Sound and Vibration 331(12) 2856-2873. ISBN/ISSN 0022-460X, 04/06/2012.
Acknowledgements. The authors acknowledge support from the Australian Research Council through project DP190103260. The authors acknowledge the UWA workshop in developing and manufacturing the experimental setup. In the experiments some setup fixtures previously developed by M. Khudyakov were used. AVD acknowledges the support from the School of Civil and Transportation, Faculty of Engineering, Beijing University of Civil Engineering and Architecture.
How to cite: He, J., Pasternak, E., Dyskin, A., and Shufrin, I.: Rotational waves in fragmented and blocky geomaterials, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9064, https://doi.org/10.5194/egusphere-egu2020-9064, 2020.
EGU2020-20936 | Displays | NP7.1
Seismic events associated with catastrophic fracture propagation in rock under compressionHongyu Wang, Arcady Dyskin, Elena Pasternak, and Phil Dight
Fracture growth produced by compressive stress is typically restricted to the sizes of the pre-existing defect seeding the fracture. However the biaxial compression acting near a free surface (e.g. a wall of an opening or at a large scale, the Earth’s surface) can change the fracture growth mechanism. Our experiments demonstrate that in the presence of the second, intermediate principal stress (the minor principal stress is nearly zero in the vicinity of free surface) leads to extensive fracture propagation. Furthermore, the interaction of the propagating fracture with the free surface makes the growth unstable (catastrophic). This produces a seismic event and can lead to such a dangerous and hazardous dynamic rock failure such as skin rockburst.
Our previous experiments on brittle transparent samples with an internal initial crack under biaxial compression showed that a small magnitude of the intermediate principal stress, around 5% of the major principal stress, is sufficient to ensure extensive fracture propagation [1- 3]. The catastrophic fracture propagation is then induced by the interaction between the fracture and the free surface as the presence of the free surface imposes additional tensile stresses on the growing fracture. The type of the associated seismic event is the Compensated Linear Vector Dipole (CLVD) source. We present a simple model that allows the determination of the conditions of unstable fracture propagation and the energy of the associated seismic event. The results of this research contribute to the understanding of the nature of seismic events and the mechanics of skin rockburst.
- Wang, H., Dyskin, A.V. Pasternak, E Dight, P Sarmadivaleh, M. 2018. Effect of the intermediate principal stress on 3-D crack growth. Engineering Fracture Mechanics, 204, 404-420.
- Wang, H., Dyskin, A.V. and Pasternak, E. (2019) Comparative analysis of mechanisms of 3-D brittle crack growth in compression, Engineering Fracture Mechanics220, 106656.
- Wang, H., Dyskin, A. Pasternak, E., Dight, P. and Sarmadivaleh, M. (2019) Experimental and numerical study into 3D crack growth from a spherical pore in biaxial compression, Rock Mechanics and Rock Engineering, doi.org/10.1007/s00603-019-01899-1.
Acknowledgements. AVD and EP acknowledge support from the Australian Research Council through project DP190103260. The first author acknowledges financial support from the Australian Centre for Geomechanics. The authors are grateful to Mr. Frank EE How Tan for his assistance with specimen preparation. AVD acknowledges the support from the School of Civil and Transportation, Faculty of Engineering, Beijing University of Civil Engineering and Architecture.
How to cite: Wang, H., Dyskin, A., Pasternak, E., and Dight, P.: Seismic events associated with catastrophic fracture propagation in rock under compression, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20936, https://doi.org/10.5194/egusphere-egu2020-20936, 2020.
Fracture growth produced by compressive stress is typically restricted to the sizes of the pre-existing defect seeding the fracture. However the biaxial compression acting near a free surface (e.g. a wall of an opening or at a large scale, the Earth’s surface) can change the fracture growth mechanism. Our experiments demonstrate that in the presence of the second, intermediate principal stress (the minor principal stress is nearly zero in the vicinity of free surface) leads to extensive fracture propagation. Furthermore, the interaction of the propagating fracture with the free surface makes the growth unstable (catastrophic). This produces a seismic event and can lead to such a dangerous and hazardous dynamic rock failure such as skin rockburst.
Our previous experiments on brittle transparent samples with an internal initial crack under biaxial compression showed that a small magnitude of the intermediate principal stress, around 5% of the major principal stress, is sufficient to ensure extensive fracture propagation [1- 3]. The catastrophic fracture propagation is then induced by the interaction between the fracture and the free surface as the presence of the free surface imposes additional tensile stresses on the growing fracture. The type of the associated seismic event is the Compensated Linear Vector Dipole (CLVD) source. We present a simple model that allows the determination of the conditions of unstable fracture propagation and the energy of the associated seismic event. The results of this research contribute to the understanding of the nature of seismic events and the mechanics of skin rockburst.
- Wang, H., Dyskin, A.V. Pasternak, E Dight, P Sarmadivaleh, M. 2018. Effect of the intermediate principal stress on 3-D crack growth. Engineering Fracture Mechanics, 204, 404-420.
- Wang, H., Dyskin, A.V. and Pasternak, E. (2019) Comparative analysis of mechanisms of 3-D brittle crack growth in compression, Engineering Fracture Mechanics220, 106656.
- Wang, H., Dyskin, A. Pasternak, E., Dight, P. and Sarmadivaleh, M. (2019) Experimental and numerical study into 3D crack growth from a spherical pore in biaxial compression, Rock Mechanics and Rock Engineering, doi.org/10.1007/s00603-019-01899-1.
Acknowledgements. AVD and EP acknowledge support from the Australian Research Council through project DP190103260. The first author acknowledges financial support from the Australian Centre for Geomechanics. The authors are grateful to Mr. Frank EE How Tan for his assistance with specimen preparation. AVD acknowledges the support from the School of Civil and Transportation, Faculty of Engineering, Beijing University of Civil Engineering and Architecture.
How to cite: Wang, H., Dyskin, A., Pasternak, E., and Dight, P.: Seismic events associated with catastrophic fracture propagation in rock under compression, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20936, https://doi.org/10.5194/egusphere-egu2020-20936, 2020.
EGU2020-20594 | Displays | NP7.1
3D Simulation of Fracture Propagation in Complex Reservoirs Rocks at MicroscaleVictor Nachev, Andrey Kazak, and Sergey Turuntaev
The hydraulic fracturing (HF) is one of the most commonly used methods for improving oil recovery. Improvement of HF efficiency requires the generation of an extensive network of secondary (non-main) fractures in the reservoir rock. This work aims to study the fracture propagation at the microscale for determining the optimal stress-strain states sustaining the most extensive network of secondary fractures. The solution accounts for rock microstructure at various scales, elastic strength parameters and elastic-plastic type of rock behavior during fracture propagation. The object of investigation is Berezov formation that features low permeability (< 1 mD) and pore dimensions down to tens of nanometers. Microstructural characterization employed computed tomography (CT) before and after geomechanical tests, quantitative evaluation of minerals by scanning electron microscopy (QEMSCAN) and energy dispersive spectroscopy. Geomechanical characterization included multi-stage compressive strength tests, Brazilian tensile strength testing. Data processing included the segmentation of micro-CT data, the 2D-QEMSCAN to 3D- micro-CT registration. For the digital rock model, the preparation we built the mesh, then populated the model with mechanical properties, defined the contact behavior between mineral grains and set boundary conditions. Using an advanced commercial mechanical simulator, we modeled fracture propagation at the microscale, obtained the simulations of fracture initiation and propagation in a 3D-homogeneous porous matrix, 2D stress-strain state of the heterogeneous material with nine minerals and fracture evolution through intergranular contacts. We found the appearance of a plasticity region in the heterogeneous matrix associated with fracture propagation. The research results allow improving the efficiency of HF operations at unconventional reservoirs and increasing production from isolated pore systems by creating an extensive secondary-fracture network.
How to cite: Nachev, V., Kazak, A., and Turuntaev, S.: 3D Simulation of Fracture Propagation in Complex Reservoirs Rocks at Microscale, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20594, https://doi.org/10.5194/egusphere-egu2020-20594, 2020.
The hydraulic fracturing (HF) is one of the most commonly used methods for improving oil recovery. Improvement of HF efficiency requires the generation of an extensive network of secondary (non-main) fractures in the reservoir rock. This work aims to study the fracture propagation at the microscale for determining the optimal stress-strain states sustaining the most extensive network of secondary fractures. The solution accounts for rock microstructure at various scales, elastic strength parameters and elastic-plastic type of rock behavior during fracture propagation. The object of investigation is Berezov formation that features low permeability (< 1 mD) and pore dimensions down to tens of nanometers. Microstructural characterization employed computed tomography (CT) before and after geomechanical tests, quantitative evaluation of minerals by scanning electron microscopy (QEMSCAN) and energy dispersive spectroscopy. Geomechanical characterization included multi-stage compressive strength tests, Brazilian tensile strength testing. Data processing included the segmentation of micro-CT data, the 2D-QEMSCAN to 3D- micro-CT registration. For the digital rock model, the preparation we built the mesh, then populated the model with mechanical properties, defined the contact behavior between mineral grains and set boundary conditions. Using an advanced commercial mechanical simulator, we modeled fracture propagation at the microscale, obtained the simulations of fracture initiation and propagation in a 3D-homogeneous porous matrix, 2D stress-strain state of the heterogeneous material with nine minerals and fracture evolution through intergranular contacts. We found the appearance of a plasticity region in the heterogeneous matrix associated with fracture propagation. The research results allow improving the efficiency of HF operations at unconventional reservoirs and increasing production from isolated pore systems by creating an extensive secondary-fracture network.
How to cite: Nachev, V., Kazak, A., and Turuntaev, S.: 3D Simulation of Fracture Propagation in Complex Reservoirs Rocks at Microscale, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20594, https://doi.org/10.5194/egusphere-egu2020-20594, 2020.
EGU2020-13081 | Displays | NP7.1
Dynamic Stress Concentration Around Shallow-Buried Circle Cavity Under Transient P Wave Loads in Different ConditionsMing Tao, Linqi Huang, Xibing Li, and Shaofeng Wang
Based on the large-arc assumption, an analytical model is established and solved by using the complex variable function method to illustrate the dynamic stress concentration around a shallow-buried cavity under transient loads. The jump points in the dynamic stress concentration factor (DSCF) curve that do not in line with the overall trend is filtered out to obtain more reasonable results. The convergence speed of the Graf addition formula is examined, as well as the effects of the incidence angle, frequency, and burial depth on the DSCF around the cavity. Examples show that a larger arc radius and a higher incident frequency correspond to slower convergence of the Graf addition formula. There are differences between the DSCF distributions of high-frequency incidents (such as blasting waves) and low-frequency incidents (such as seismic waves). There are three tensile-stress zones and three compressive-stress zones approximately equally spaced around the cavity in the low-frequency case, and there are two tensile-stress zones and two compressive-stress zones in the high-frequency case. Regarding the variation of the DSCFs with respect to the cavity depth, incidence angle and position of wave peak there are significant differences between the high- and low-frequency cases.
How to cite: Tao, M., Huang, L., Li, X., and Wang, S.: Dynamic Stress Concentration Around Shallow-Buried Circle Cavity Under Transient P Wave Loads in Different Conditions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13081, https://doi.org/10.5194/egusphere-egu2020-13081, 2020.
Based on the large-arc assumption, an analytical model is established and solved by using the complex variable function method to illustrate the dynamic stress concentration around a shallow-buried cavity under transient loads. The jump points in the dynamic stress concentration factor (DSCF) curve that do not in line with the overall trend is filtered out to obtain more reasonable results. The convergence speed of the Graf addition formula is examined, as well as the effects of the incidence angle, frequency, and burial depth on the DSCF around the cavity. Examples show that a larger arc radius and a higher incident frequency correspond to slower convergence of the Graf addition formula. There are differences between the DSCF distributions of high-frequency incidents (such as blasting waves) and low-frequency incidents (such as seismic waves). There are three tensile-stress zones and three compressive-stress zones approximately equally spaced around the cavity in the low-frequency case, and there are two tensile-stress zones and two compressive-stress zones in the high-frequency case. Regarding the variation of the DSCFs with respect to the cavity depth, incidence angle and position of wave peak there are significant differences between the high- and low-frequency cases.
How to cite: Tao, M., Huang, L., Li, X., and Wang, S.: Dynamic Stress Concentration Around Shallow-Buried Circle Cavity Under Transient P Wave Loads in Different Conditions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13081, https://doi.org/10.5194/egusphere-egu2020-13081, 2020.
EGU2020-20233 | Displays | NP7.1
Hydraulic fracture propagation in high porosity mediaAliya Tairova, Georgy Belyakov, Nikita Iudochkin, and Aleksandr Molokoedov
In the present work, a foam rubber sheet installed between two transparent thick flat glasses was used as a physical model of a permeable oil reservoir. The elastic properties of foam rubber and its coefficient of friction on glass are supposed to be measured in separate experiments. In the center of the foam sheet there is a round hole, which is a model of the end face of the well in the oil reservoir. Before the experiment, cuts are made from the hole in opposite directions and to a certain length, simulating a previously closed crack. Using a vacuum pump it is possible to change the pressure of glasses per layer and thereby simulate the increase in "rock pressure" on a productive oil reservoir . A fluid is pumped through the hole in the end of the well. Under the action of fluid filtration, the surface of the walls along the cut of the foam layer are moved apart, forming a gap.The dependence of the pressure gradient on the length of the crack formed was obtained. The overall picture of the growth of hydraulic fracturing is recorded by camera. Continuous physical observations of the formation of a fracture in time allow subsequently predict the optimal fracture geometry.
The reported study was funded by RFBR, project number №. 20-35-80028 and state task 0146-2019-0007
How to cite: Tairova, A., Belyakov, G., Iudochkin, N., and Molokoedov, A.: Hydraulic fracture propagation in high porosity media, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20233, https://doi.org/10.5194/egusphere-egu2020-20233, 2020.
In the present work, a foam rubber sheet installed between two transparent thick flat glasses was used as a physical model of a permeable oil reservoir. The elastic properties of foam rubber and its coefficient of friction on glass are supposed to be measured in separate experiments. In the center of the foam sheet there is a round hole, which is a model of the end face of the well in the oil reservoir. Before the experiment, cuts are made from the hole in opposite directions and to a certain length, simulating a previously closed crack. Using a vacuum pump it is possible to change the pressure of glasses per layer and thereby simulate the increase in "rock pressure" on a productive oil reservoir . A fluid is pumped through the hole in the end of the well. Under the action of fluid filtration, the surface of the walls along the cut of the foam layer are moved apart, forming a gap.The dependence of the pressure gradient on the length of the crack formed was obtained. The overall picture of the growth of hydraulic fracturing is recorded by camera. Continuous physical observations of the formation of a fracture in time allow subsequently predict the optimal fracture geometry.
The reported study was funded by RFBR, project number №. 20-35-80028 and state task 0146-2019-0007
How to cite: Tairova, A., Belyakov, G., Iudochkin, N., and Molokoedov, A.: Hydraulic fracture propagation in high porosity media, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20233, https://doi.org/10.5194/egusphere-egu2020-20233, 2020.
EGU2020-7956 | Displays | NP7.1
Laboratory study of hydraulic refracturing possibilitySergey Turuntaev, Evgeny Zenchenko, Petr Zenchenko, Maria Trimonova, and Nikolai Baryshnikov
The results of laboratory experiments will be considered, that are carried out in a laboratory setup that differs from the standard ones in the shape and size of the test samples. The setup consists from two disks and wide ring between them, which form a high-pressure chamber, and it is capable to produce true 3D stresses in the samples. Laboratory experiments are performed on saturated artificial porous samples created according to similarity criteria using gypsum with Portland cement added as a model material. The samples are created directly in the high-pressure chamber and have the forms of disks with diameters of 430 mm and heights of 70 mm. This sample is saturated with water gypsum solution and loaded with vertical and two horizontal stresses using special chambers. In the upper, lower and lateral parts of the installation there are pressure sensors, ultrasonic transducers and generators. The first fracture was created by viscous fluid (mineral oil) injection through a cased borehole preliminary created in the center of the sample. After the first fracturing, the principal maximal and minimal stress axis orientations were changed, and refracturing was carried out. We failed to create two fractures oriented along the borehole, but we succeeded in creation one fracture perpendicular to the borehole and the second fracture along the borehole. Comparison of the ultrasonic wave amplitude changes during the fracturing with the fracturing pressure variations allowed us to distinct the fracture propagation and the fracture fill-up by the fracturing fluid. It was also found that for an adequate calculation of the minimum compressive stresses from the characteristic parameters of the pressure change in the well, it is necessary to take into account the plastic properties of the rock, the diffusion of the fluid pore pressure in the vicinity of the well and the hydraulic fracture, the lag of the filling of the fracture with the fluid.
How to cite: Turuntaev, S., Zenchenko, E., Zenchenko, P., Trimonova, M., and Baryshnikov, N.: Laboratory study of hydraulic refracturing possibility, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7956, https://doi.org/10.5194/egusphere-egu2020-7956, 2020.
The results of laboratory experiments will be considered, that are carried out in a laboratory setup that differs from the standard ones in the shape and size of the test samples. The setup consists from two disks and wide ring between them, which form a high-pressure chamber, and it is capable to produce true 3D stresses in the samples. Laboratory experiments are performed on saturated artificial porous samples created according to similarity criteria using gypsum with Portland cement added as a model material. The samples are created directly in the high-pressure chamber and have the forms of disks with diameters of 430 mm and heights of 70 mm. This sample is saturated with water gypsum solution and loaded with vertical and two horizontal stresses using special chambers. In the upper, lower and lateral parts of the installation there are pressure sensors, ultrasonic transducers and generators. The first fracture was created by viscous fluid (mineral oil) injection through a cased borehole preliminary created in the center of the sample. After the first fracturing, the principal maximal and minimal stress axis orientations were changed, and refracturing was carried out. We failed to create two fractures oriented along the borehole, but we succeeded in creation one fracture perpendicular to the borehole and the second fracture along the borehole. Comparison of the ultrasonic wave amplitude changes during the fracturing with the fracturing pressure variations allowed us to distinct the fracture propagation and the fracture fill-up by the fracturing fluid. It was also found that for an adequate calculation of the minimum compressive stresses from the characteristic parameters of the pressure change in the well, it is necessary to take into account the plastic properties of the rock, the diffusion of the fluid pore pressure in the vicinity of the well and the hydraulic fracture, the lag of the filling of the fracture with the fluid.
How to cite: Turuntaev, S., Zenchenko, E., Zenchenko, P., Trimonova, M., and Baryshnikov, N.: Laboratory study of hydraulic refracturing possibility, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-7956, https://doi.org/10.5194/egusphere-egu2020-7956, 2020.
NP7.2 – Wave-current interactions
EGU2020-929 | Displays | NP7.2
Experimental and Numerical Study on Liquid Sloshing Dynamics with Single Vertical Porous Baffle in a Sway Excited Ship TankSahaj k v and Nasar Thuvanismail
Liquid motion in partially filled tanks may cause large structural loads if the period of tank motion is close to the natural period of fluid inside the tank. This phenomenon is called sloshing. Sloshing means any motion of a free liquid surface inside a container. The effect of severe sloshing motion on global seagoing vessels is an important factor in safety design of such containers. In order to examine the sloshing effects, a shake table experiments were conducted for different water fill depth of aspect ratio 0.163, 0.325 and 0.488. The parametric studies were carried out to show the liquid sloshing effects in terms of slosh frequencies, maximum free surface elevation and hydrodynamic forces acting on the tank wall. Sloshing oscillation for the excitation frequency f1, f2, f3, f4 and f5 are observed and analysed. The excitation frequencies is varied between 0.4566 Hz to 1.9757 Hz and constant amplitudes of 7.5mm was adopted. The movement of fluid in a rectangular tank has been studied using experimental approach and different baffle configurations were adopted for analysing the sloshing oscillation, natural frequencies and variation in wave deflection. The adopted porosities in the present study is 15% – 25 %. Porous screen is placed inside the tank at L/2 location and study is extended for single porous screen for better wave energy absorption. Capacitance wave probes have been placed at tank ends to record the free surface water elevation. Load cells are used to measure the sloshing force inside the tank. Linear variable displacement transducers is used to measure the displacement of shake table. In the present study single porous screen under the action of wave were analysed to understand the wave control performance due to porosity parameters. A boundary element model is developed to calculate problems of wave interaction with a porous screen structure. The numerical results from the present boundary element methods (BEM) are compared with series of experiments conducted in a rectangular tank with various baffle porosities and submerged depths.
How to cite: k v, S. and Thuvanismail, N.: Experimental and Numerical Study on Liquid Sloshing Dynamics with Single Vertical Porous Baffle in a Sway Excited Ship Tank, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-929, https://doi.org/10.5194/egusphere-egu2020-929, 2020.
Liquid motion in partially filled tanks may cause large structural loads if the period of tank motion is close to the natural period of fluid inside the tank. This phenomenon is called sloshing. Sloshing means any motion of a free liquid surface inside a container. The effect of severe sloshing motion on global seagoing vessels is an important factor in safety design of such containers. In order to examine the sloshing effects, a shake table experiments were conducted for different water fill depth of aspect ratio 0.163, 0.325 and 0.488. The parametric studies were carried out to show the liquid sloshing effects in terms of slosh frequencies, maximum free surface elevation and hydrodynamic forces acting on the tank wall. Sloshing oscillation for the excitation frequency f1, f2, f3, f4 and f5 are observed and analysed. The excitation frequencies is varied between 0.4566 Hz to 1.9757 Hz and constant amplitudes of 7.5mm was adopted. The movement of fluid in a rectangular tank has been studied using experimental approach and different baffle configurations were adopted for analysing the sloshing oscillation, natural frequencies and variation in wave deflection. The adopted porosities in the present study is 15% – 25 %. Porous screen is placed inside the tank at L/2 location and study is extended for single porous screen for better wave energy absorption. Capacitance wave probes have been placed at tank ends to record the free surface water elevation. Load cells are used to measure the sloshing force inside the tank. Linear variable displacement transducers is used to measure the displacement of shake table. In the present study single porous screen under the action of wave were analysed to understand the wave control performance due to porosity parameters. A boundary element model is developed to calculate problems of wave interaction with a porous screen structure. The numerical results from the present boundary element methods (BEM) are compared with series of experiments conducted in a rectangular tank with various baffle porosities and submerged depths.
How to cite: k v, S. and Thuvanismail, N.: Experimental and Numerical Study on Liquid Sloshing Dynamics with Single Vertical Porous Baffle in a Sway Excited Ship Tank, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-929, https://doi.org/10.5194/egusphere-egu2020-929, 2020.
EGU2020-2322 | Displays | NP7.2
Experimental study of dispersion and modulational instability of surface gravity waves on constant vorticity currentsTon van den Bremer, James Steer, Dimitris Stagonas, Eugeny Buldakov, and Alistair Borthwick
We examine experimentally the dispersion and stability of weakly nonlinear waves on opposing linearly vertically sheared current profiles (with constant vorticity). Measurements are compared against predictions from the unidirectional 1D+1 constant vorticity nonlinear Schrödinger equation (the vor-NLSE) derived by Thomas et al. (Phys. Fluids, vol. 24, no. 12, 2012, 127102). The shear rate is negative in opposing currents when the magnitude of the current in the laboratory reference frame is negative (i.e. opposing the direction of wave propagation) and reduces with depth, as is most commonly encountered in nature. Compared to a uniform current with the same surface velocity, negative shear has the effect of increasing wavelength and enhancing stability. In experiments with a regular low-steepness wave, the dispersion relationship between wavelength and frequency is examined on five opposing current profiles with shear rates from 0 to -0,87 s-1 For all current profiles, the linear constant vorticity dispersion relation predicts the wavenumber to within the 95% confidence bounds associated with estimates of shear rate and surface current velocity. The effect of shear on modulational instability was determined by the spectral evolution of a carrier wave seeded with spectral sidebands on opposing current profiles with shear rates between 0 and -0.48 s-1. Numerical solutions of the vor-NLSE are consistently found to predict sideband growth to within two standard deviations across repeated experiments, performing considerably better than its uniform-current NLSE counterpart. Similarly, the amplification of experimental wave envelopes is predicted well by numerical solutions of the vor-NLSE, and significantly over-predicted by the uniform-current NLSE.
How to cite: van den Bremer, T., Steer, J., Stagonas, D., Buldakov, E., and Borthwick, A.: Experimental study of dispersion and modulational instability of surface gravity waves on constant vorticity currents, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2322, https://doi.org/10.5194/egusphere-egu2020-2322, 2020.
We examine experimentally the dispersion and stability of weakly nonlinear waves on opposing linearly vertically sheared current profiles (with constant vorticity). Measurements are compared against predictions from the unidirectional 1D+1 constant vorticity nonlinear Schrödinger equation (the vor-NLSE) derived by Thomas et al. (Phys. Fluids, vol. 24, no. 12, 2012, 127102). The shear rate is negative in opposing currents when the magnitude of the current in the laboratory reference frame is negative (i.e. opposing the direction of wave propagation) and reduces with depth, as is most commonly encountered in nature. Compared to a uniform current with the same surface velocity, negative shear has the effect of increasing wavelength and enhancing stability. In experiments with a regular low-steepness wave, the dispersion relationship between wavelength and frequency is examined on five opposing current profiles with shear rates from 0 to -0,87 s-1 For all current profiles, the linear constant vorticity dispersion relation predicts the wavenumber to within the 95% confidence bounds associated with estimates of shear rate and surface current velocity. The effect of shear on modulational instability was determined by the spectral evolution of a carrier wave seeded with spectral sidebands on opposing current profiles with shear rates between 0 and -0.48 s-1. Numerical solutions of the vor-NLSE are consistently found to predict sideband growth to within two standard deviations across repeated experiments, performing considerably better than its uniform-current NLSE counterpart. Similarly, the amplification of experimental wave envelopes is predicted well by numerical solutions of the vor-NLSE, and significantly over-predicted by the uniform-current NLSE.
How to cite: van den Bremer, T., Steer, J., Stagonas, D., Buldakov, E., and Borthwick, A.: Experimental study of dispersion and modulational instability of surface gravity waves on constant vorticity currents, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2322, https://doi.org/10.5194/egusphere-egu2020-2322, 2020.
EGU2020-3878 | Displays | NP7.2
Head-collision of nonlinear waves in a shallow basin: wave field and bottom pressureArtem Rodin, Natalia Rodina, Andrey Kurkin, Julien Touboul, and Efim Pelinovsky
The collision of solitary waves has been studied analytically and numerically in numerated papers for last 50 years. In the weakly nonlinear theory, the soliton interaction is inelastic. Here we study more general class of the head-collision of nonlinear waves of various shape (Riemann waves of both polarities, shock waves and solitons) in the shallow water within nonlinear shallow-water theory, Serre-Green-Naghdi and Euler equations. The structure of wave field and induced bottom pressure at the moment of wave interaction is analysed analytically and numerically. It is shown that such an interaction leads to a phase shift and shape deformation in the moment of interaction. Estimates of the height of the Riemann waves as well solitons of moderate amplitudes at the moment of interaction are in agreement with theoretical predictions. The phase shift in the interaction of non-breaking waves is small enough, but becomes noticeable in the case of the shock waves motion. The approximated analytical solution for the wave field and bottom pressure distribution is obtained analytically within Serre-Green-Naghdi system. Computed bottom pressure in dispersive theories has two-bell shape for large amplitude solitary waves in quality agreement with theoretical analysis.
How to cite: Rodin, A., Rodina, N., Kurkin, A., Touboul, J., and Pelinovsky, E.: Head-collision of nonlinear waves in a shallow basin: wave field and bottom pressure, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3878, https://doi.org/10.5194/egusphere-egu2020-3878, 2020.
The collision of solitary waves has been studied analytically and numerically in numerated papers for last 50 years. In the weakly nonlinear theory, the soliton interaction is inelastic. Here we study more general class of the head-collision of nonlinear waves of various shape (Riemann waves of both polarities, shock waves and solitons) in the shallow water within nonlinear shallow-water theory, Serre-Green-Naghdi and Euler equations. The structure of wave field and induced bottom pressure at the moment of wave interaction is analysed analytically and numerically. It is shown that such an interaction leads to a phase shift and shape deformation in the moment of interaction. Estimates of the height of the Riemann waves as well solitons of moderate amplitudes at the moment of interaction are in agreement with theoretical predictions. The phase shift in the interaction of non-breaking waves is small enough, but becomes noticeable in the case of the shock waves motion. The approximated analytical solution for the wave field and bottom pressure distribution is obtained analytically within Serre-Green-Naghdi system. Computed bottom pressure in dispersive theories has two-bell shape for large amplitude solitary waves in quality agreement with theoretical analysis.
How to cite: Rodin, A., Rodina, N., Kurkin, A., Touboul, J., and Pelinovsky, E.: Head-collision of nonlinear waves in a shallow basin: wave field and bottom pressure, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3878, https://doi.org/10.5194/egusphere-egu2020-3878, 2020.
EGU2020-6887 | Displays | NP7.2
Explicit solution of the scattering problem involving a vertical flexible membraneSrinivasa Rao Manam, Ashok Kumar, and Gunasundari Chandrasekar
The problem of normally incident water wave scattering by a flexible membrane is completely solved. The physical problem in a half-plane is reduced to a couple of equivalent quarter-plane problems by allowing incident waves from either direction of the membrane. In the same way, quarter-plane boundary value problems are posed for solid wave potentials that are solutions of the scattering problem involving a rigid structure of the same geometric configuration. Then, two novel integral relations are introduced to establish a link between the required solution wave potentials and few resolvable solid wave potentials. Explicit expressions for the scattering quantities such as the reflection and the transmission wave amplitudes are obtained. Also, the deflection of the flexible vertical membrane and the solution potentials are determined analytically. Numerical results for the scattering quantities and the membrane deflection are presented.
How to cite: Manam, S. R., Kumar, A., and Chandrasekar, G.: Explicit solution of the scattering problem involving a vertical flexible membrane, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6887, https://doi.org/10.5194/egusphere-egu2020-6887, 2020.
The problem of normally incident water wave scattering by a flexible membrane is completely solved. The physical problem in a half-plane is reduced to a couple of equivalent quarter-plane problems by allowing incident waves from either direction of the membrane. In the same way, quarter-plane boundary value problems are posed for solid wave potentials that are solutions of the scattering problem involving a rigid structure of the same geometric configuration. Then, two novel integral relations are introduced to establish a link between the required solution wave potentials and few resolvable solid wave potentials. Explicit expressions for the scattering quantities such as the reflection and the transmission wave amplitudes are obtained. Also, the deflection of the flexible vertical membrane and the solution potentials are determined analytically. Numerical results for the scattering quantities and the membrane deflection are presented.
How to cite: Manam, S. R., Kumar, A., and Chandrasekar, G.: Explicit solution of the scattering problem involving a vertical flexible membrane, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6887, https://doi.org/10.5194/egusphere-egu2020-6887, 2020.
EGU2020-18933 | Displays | NP7.2
A new model for the three-dimensional propagation of water waves in the presence of vertically sheared, horizontally varying currentsJulien Touboul and Kostas Belibassakis
In coastal areas, steep bathymetries and strong currents are often observed. Among several causes, the presence of cliffs, rocky beds, or human structures may cause strong variations of the sea bed, while oceanic circulation, tides, wind action or wave breaking can be responsible for the generation of strong currents. For both coastal safety and engineering purposes, there are many interests in providing efficient models predicting the nonlinear, phase resolved behavior of water waves in such areas. The difficulty is known to be important, and many models achieving that goal are described in the related literature.
Recently, it was established that beneath the influence of vertically uniform currents, the vorticity involved in depth varying mean flows could have significant impact on the propagation of water waves (Rey et al. 2014). This gave rise to new derivations of equations aimed to describe this interaction. First, an extended mild slope equation was obtained (Touboul et al. 2016). Then, the now classical coupled mode theory was introduced in the system to obtain a set of coupled equations, which could be compared to the system derived by Belibassakis et al (2011) but considering currents which may present constant shear with depth (Belibassakis et al. 2017, Belibassakis et al., 2019). In these works, the currents were assumed to vary linearly with depth, presenting a constant shear. However, this approach was recently extended to more general configurations (Belibassakis & Touboul, 2019; Touboul & Belibassakis, 2019).
In this work, we extend this model to three dimensional configurations. It is emphasized that the model is able to describe rotational waves, as expected, for example, when water waves propagate with a non-zero angle with respect to the current direction (see e.g. Ellingsen, 2016).
[1] Rey, V., Charland, J., Touboul, J., Wave – current interaction in the presence of a 3d bathymetry: deep water wave focusing in opposite current conditions. Phys. Fluids 26, 096601, 2014.
[2] Touboul J., Charland J., Rey V., Belibassakis K., Extended Mild-Slope equation for surface waves interacting with a vertically sheared current, Coastal Engineering, 116, 77–88, 2016.
[3] Belibassakis, K.A., Gerostathis, Th., Athanassoulis, G.A. A coupled-mode model for water wave scattering by horizontal, non-homogeneous current in general bottom topography, Applied Ocean Res. 33, 384– 397, 2011.
[4] Belibassakis K.A., Simon B., Touboul J., Rey V., A coupled-mode model for water wave scattering by vertically sheared currents in variable bathymetry regions, Wave Motion, vol.74, 73-92, 2017.
[5] Belibassakis K., Touboul J., Laffitte E., Rey V., A mild-slope system for Bragg scattering of water waves by sinusoidal bathymetry in the presence of vertically sheared currents, J. Mar. Sci. Eng., Vol.7(1), 9, 2019.
[6] Belibassakis K.A., Touboul J. A nonlinear coupled-mode model for waves propagating in
vertically sheared currents in variable bathymetry-collinear waves and currents, Fluids, 4(2),
61, 2019.
[7] J. Touboul & K. Belibassakis, A novel method for water waves propagating in the presence of vortical mean flows over variable bathymetry, J. Ocean Eng. and Mar. Energy, https://doi.org/10.1007/s40722-019-00151-w, 2019.
[8] Ellingsen, S.A., Oblique waves on a vertically sheared current are rotational, Eur. J. Mech. B-Fluid 56, 156–160, 2016.
How to cite: Touboul, J. and Belibassakis, K.: A new model for the three-dimensional propagation of water waves in the presence of vertically sheared, horizontally varying currents, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18933, https://doi.org/10.5194/egusphere-egu2020-18933, 2020.
In coastal areas, steep bathymetries and strong currents are often observed. Among several causes, the presence of cliffs, rocky beds, or human structures may cause strong variations of the sea bed, while oceanic circulation, tides, wind action or wave breaking can be responsible for the generation of strong currents. For both coastal safety and engineering purposes, there are many interests in providing efficient models predicting the nonlinear, phase resolved behavior of water waves in such areas. The difficulty is known to be important, and many models achieving that goal are described in the related literature.
Recently, it was established that beneath the influence of vertically uniform currents, the vorticity involved in depth varying mean flows could have significant impact on the propagation of water waves (Rey et al. 2014). This gave rise to new derivations of equations aimed to describe this interaction. First, an extended mild slope equation was obtained (Touboul et al. 2016). Then, the now classical coupled mode theory was introduced in the system to obtain a set of coupled equations, which could be compared to the system derived by Belibassakis et al (2011) but considering currents which may present constant shear with depth (Belibassakis et al. 2017, Belibassakis et al., 2019). In these works, the currents were assumed to vary linearly with depth, presenting a constant shear. However, this approach was recently extended to more general configurations (Belibassakis & Touboul, 2019; Touboul & Belibassakis, 2019).
In this work, we extend this model to three dimensional configurations. It is emphasized that the model is able to describe rotational waves, as expected, for example, when water waves propagate with a non-zero angle with respect to the current direction (see e.g. Ellingsen, 2016).
[1] Rey, V., Charland, J., Touboul, J., Wave – current interaction in the presence of a 3d bathymetry: deep water wave focusing in opposite current conditions. Phys. Fluids 26, 096601, 2014.
[2] Touboul J., Charland J., Rey V., Belibassakis K., Extended Mild-Slope equation for surface waves interacting with a vertically sheared current, Coastal Engineering, 116, 77–88, 2016.
[3] Belibassakis, K.A., Gerostathis, Th., Athanassoulis, G.A. A coupled-mode model for water wave scattering by horizontal, non-homogeneous current in general bottom topography, Applied Ocean Res. 33, 384– 397, 2011.
[4] Belibassakis K.A., Simon B., Touboul J., Rey V., A coupled-mode model for water wave scattering by vertically sheared currents in variable bathymetry regions, Wave Motion, vol.74, 73-92, 2017.
[5] Belibassakis K., Touboul J., Laffitte E., Rey V., A mild-slope system for Bragg scattering of water waves by sinusoidal bathymetry in the presence of vertically sheared currents, J. Mar. Sci. Eng., Vol.7(1), 9, 2019.
[6] Belibassakis K.A., Touboul J. A nonlinear coupled-mode model for waves propagating in
vertically sheared currents in variable bathymetry-collinear waves and currents, Fluids, 4(2),
61, 2019.
[7] J. Touboul & K. Belibassakis, A novel method for water waves propagating in the presence of vortical mean flows over variable bathymetry, J. Ocean Eng. and Mar. Energy, https://doi.org/10.1007/s40722-019-00151-w, 2019.
[8] Ellingsen, S.A., Oblique waves on a vertically sheared current are rotational, Eur. J. Mech. B-Fluid 56, 156–160, 2016.
How to cite: Touboul, J. and Belibassakis, K.: A new model for the three-dimensional propagation of water waves in the presence of vertically sheared, horizontally varying currents, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18933, https://doi.org/10.5194/egusphere-egu2020-18933, 2020.
EGU2020-20307 | Displays | NP7.2 | Highlight
Wave-current Interactions in the Aghulas current: Impact on ship behaviorClément Le Goff, Alexey Mironov, and Bertrand Chapron
Ocean waves Interacting with large scale ocean currents is a frequent cause of sea-state variability [Ardhuin et al 2017, Quilfen et al 2018, Quilfen and Chapron 2019]. Such situations can lead to sea-state hazards, crucial for shipping security. The Great Agulhas current system is an area of very intensive maritime traffic, where dangerous localized sea-state amplification by the current has quite regularly been reported.
In absence of wind and wave-induced motions, the heading and drift of every ship along its trajectory can be estimated from the near-surface oceanic current map. This first guess can then be compared with real ship parameters obtained from satellite-collected ship Automatic Identification System (AIS) messages. During Southwestern storm-swell wave conditions, with wind and waves aligned against the current, some ships experience pronounced navigation difficulties, slowing down up to 2 m/s, and frequently maneuvering to keep their heading perpendicular to dominant waves. Superposed multiple individual ship trajectories can then help map anomalous areas, and to relate them to localized strong wave-current effects such as large refraction of waves by the oceanic current.
[Ardhuin et al 2017] : Ardhuin, F., S. T. Gille, D. Menemenlis,C. B. Rocha, N. Rascle, B. Chapron, J. Gula, and J. Molemaker (2017), Small-scale open ocean
currents have large effects on wind wave heights, J. Geophys. Res. Oceans, 122, 4500–4517, doi:10.1002/2016JC012413.
[Quilfen et al 2018] :Quilfen Yves, Yurovskaya M., Chapron Bertrand, Ardhuin Fabrice (2018). Storm waves focusing and steepening in the Agulhas current: Satellite observations and modeling. Remote Sensing Of Environment, 216, 561-571. Publisher's official version :
[Quilfen and Chapron, 2019] : Quilfen, Y., & Chapron, B. (2019). Ocean surface wave-current signatures from satellite altimeter measurements.
Geophysical Research Letters, 46.
How to cite: Le Goff, C., Mironov, A., and Chapron, B.: Wave-current Interactions in the Aghulas current: Impact on ship behavior, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20307, https://doi.org/10.5194/egusphere-egu2020-20307, 2020.
Ocean waves Interacting with large scale ocean currents is a frequent cause of sea-state variability [Ardhuin et al 2017, Quilfen et al 2018, Quilfen and Chapron 2019]. Such situations can lead to sea-state hazards, crucial for shipping security. The Great Agulhas current system is an area of very intensive maritime traffic, where dangerous localized sea-state amplification by the current has quite regularly been reported.
In absence of wind and wave-induced motions, the heading and drift of every ship along its trajectory can be estimated from the near-surface oceanic current map. This first guess can then be compared with real ship parameters obtained from satellite-collected ship Automatic Identification System (AIS) messages. During Southwestern storm-swell wave conditions, with wind and waves aligned against the current, some ships experience pronounced navigation difficulties, slowing down up to 2 m/s, and frequently maneuvering to keep their heading perpendicular to dominant waves. Superposed multiple individual ship trajectories can then help map anomalous areas, and to relate them to localized strong wave-current effects such as large refraction of waves by the oceanic current.
[Ardhuin et al 2017] : Ardhuin, F., S. T. Gille, D. Menemenlis,C. B. Rocha, N. Rascle, B. Chapron, J. Gula, and J. Molemaker (2017), Small-scale open ocean
currents have large effects on wind wave heights, J. Geophys. Res. Oceans, 122, 4500–4517, doi:10.1002/2016JC012413.
[Quilfen et al 2018] :Quilfen Yves, Yurovskaya M., Chapron Bertrand, Ardhuin Fabrice (2018). Storm waves focusing and steepening in the Agulhas current: Satellite observations and modeling. Remote Sensing Of Environment, 216, 561-571. Publisher's official version :
[Quilfen and Chapron, 2019] : Quilfen, Y., & Chapron, B. (2019). Ocean surface wave-current signatures from satellite altimeter measurements.
Geophysical Research Letters, 46.
How to cite: Le Goff, C., Mironov, A., and Chapron, B.: Wave-current Interactions in the Aghulas current: Impact on ship behavior, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20307, https://doi.org/10.5194/egusphere-egu2020-20307, 2020.
EGU2020-20406 | Displays | NP7.2
Langmuir circulation due to shear flow over wavy topographyAndreas H Akselsen, Andreas Brostrøm, and Simen Ådnøy Ellingsen
Langmuir circulations (LC) in their traditional form are large rolling fluid flow pattern created by the interplay of surface waves and a near-surface shear current, typically both created by the wind. A celebrated theory by Craik and Leibovich (1976) describes two kinematic mechanisms which cause instabilities which grow into Langmuir rolls, both involving only the shear of the flow and the kinematic driving of flow undulations by a wavy surface, but containing no direct reference to the wind as a driving force. The same kinematic processes are present also in boundary layer flow over a wavy bottom topography in almost perfect analogy.
We present a theory of Langmuir-like circulations created by boundary layer flow over a topography in the form of a regular pattern of two monochromatic waves crossing at an oblique angle. Thus, the Craik-Leibovich instability sometimes referred to as CL1 is triggered and the close analogy with surface waves allows us to follow the general procedure of Craik (1970).
A flow of arbitrary shear profile is assumed over the bottom topography. In the opposite limits of transient inviscid flow and steady-state viscous flow simple equations for the stream function in cross-current plane can be derived and easily solved numerically. For the special case of a power-law velocity profile, explicit leading-order solutions are available. This allows us to quickly map out the circulation response to different parameters: wavelength, crossing angle and wave amplitude. The study is supplemented with direct numerical simulations which verify the manifestation of Langmuir-like circulations over wavy geometries with a no-slip boundary condition.
References
Craik, A.D.D., A wave-interaction model for the generation of windrows. J. Fluid Mech. (1970) 41, 801-821.
Craik, A.D.D. & Leibovich, S. A rational model for Langmuir circulations. J. Fluid Mech. (1976) 73, 401-426.
How to cite: Akselsen, A. H., Brostrøm, A., and Ellingsen, S. Å.: Langmuir circulation due to shear flow over wavy topography, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20406, https://doi.org/10.5194/egusphere-egu2020-20406, 2020.
Langmuir circulations (LC) in their traditional form are large rolling fluid flow pattern created by the interplay of surface waves and a near-surface shear current, typically both created by the wind. A celebrated theory by Craik and Leibovich (1976) describes two kinematic mechanisms which cause instabilities which grow into Langmuir rolls, both involving only the shear of the flow and the kinematic driving of flow undulations by a wavy surface, but containing no direct reference to the wind as a driving force. The same kinematic processes are present also in boundary layer flow over a wavy bottom topography in almost perfect analogy.
We present a theory of Langmuir-like circulations created by boundary layer flow over a topography in the form of a regular pattern of two monochromatic waves crossing at an oblique angle. Thus, the Craik-Leibovich instability sometimes referred to as CL1 is triggered and the close analogy with surface waves allows us to follow the general procedure of Craik (1970).
A flow of arbitrary shear profile is assumed over the bottom topography. In the opposite limits of transient inviscid flow and steady-state viscous flow simple equations for the stream function in cross-current plane can be derived and easily solved numerically. For the special case of a power-law velocity profile, explicit leading-order solutions are available. This allows us to quickly map out the circulation response to different parameters: wavelength, crossing angle and wave amplitude. The study is supplemented with direct numerical simulations which verify the manifestation of Langmuir-like circulations over wavy geometries with a no-slip boundary condition.
References
Craik, A.D.D., A wave-interaction model for the generation of windrows. J. Fluid Mech. (1970) 41, 801-821.
Craik, A.D.D. & Leibovich, S. A rational model for Langmuir circulations. J. Fluid Mech. (1976) 73, 401-426.
How to cite: Akselsen, A. H., Brostrøm, A., and Ellingsen, S. Å.: Langmuir circulation due to shear flow over wavy topography, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20406, https://doi.org/10.5194/egusphere-egu2020-20406, 2020.