EGU General Assembly 2022  

In 1963 Lorenz discovered what is usually known as “chaos”, that is the sensitive dependence of deterministic chaotic systems upon initial conditions. Since then, this concept has been strictly related to the notion of unpredictability pioneered by Lorenz. However, one of the most interesting and unknown facets of Lorenz ideas is that multiscale fluid flows could spontaneously lose their deterministic nature and become intrinsically random. This effect is radically different from chaos. Turbulent flows are the natural systems when Lorenz ideas can be touched by the hand. They can, indeed, be described via the Navier-Stokes equations, thus conforming to the class of deterministic dissipative systems, as well as, present rich dynamics originating from non-trivial energy fluxes in scale space, non-stationary forcings and geometrical constraints. This complexity appears via non-hyperbolic chaos, randomness, state-dependent persistence and predictability. All these features have prevented a full characterization of the underlying turbulent (stochastic) attractor, which will be the key object to unpin this complexity. 

Here we use a novel formalism to map unstable fixed points to singularities of turbulent flows and to trace the evolution of their structural characteristics when moving from small to large scales and vice versa, providing a full characterization of the attractor. We demonstrate that the properties of the dynamically invariant objects depend on the scale we are focusing on. Our results provide evidence that the large-scale properties of turbulent flows display universal statistical properties that are triggered by, but independent of specific physical properties at small scales. Given the changing nature of such attractors in time, space and scale spaces, we term them chameleon attractors.

How to cite: Alberti, T.: The geometry of scales: chameleon attractors, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1090, https://doi.org/10.5194/egusphere-egu22-1090, 2022.

Many systems in nature are characterized by the coexistence of different stable states for a given set of environmental parameters and external forcing. Examples for such behavior can be found in different fields of science ranging from mechanical or chemical systems to ecosystem and climate dynamics. As a consequence of the coexistence of a multitude of stable states, the final state of the system depends strongly on the initial condition.  Perturbations, applied to those natural systems can lead to critical transitions from one stable state to another. Such critical transitions are called tipping phenomena in climate science, regime shifts in ecology. They can happen in various ways: (1) due to bifurcations, i.e. changes in the dynamics when external forcing or parameters are varied extremely slow, (2) due to fluctuations which are always inevitable in natural systems, (3) due to rate-induced transitions, i.e. when external forcing changes on characteristic time scales comparable to the intrinsic time scale of the considered dynamical system and (4) due to shocks or extreme events. We discuss these critical transitions and their characteristics and illustrate them with examples from climate science and ecosystem dynamics. Moreover, we discuss the concept of resilience, which has been originally introduced by C.S. Holling in ecology, and formulate it in terms of dynamical systems theory. This formulation offers mathematical and numerical tools to use it as a measure of the persistence of a function of a dynamical system.

How to cite: Feudel, U.: Tipping phenomena and resilience of complex systems: Theory and applications to the earth system, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10567, https://doi.org/10.5194/egusphere-egu22-10567, 2022.

Variability in the tropical atmosphere is concentrated at wavenumber–frequency combinations where linear theory indicates wave modes can freely propagate, but with substantial power in between. This study demonstrates that such a power spectrum can arise from small-scale convection triggering large-scale waves via wave–wave interactions in a moderately turbulent fluid. Two key pieces of evidence are provided for this interpretation of tropical dynamics using a nonlinear rotating shallow-water model: a parameter sweep experiment in which the amplitude of an external forcing is gradually ramped up, and also an external forcing in which only symmetric or only antisymmetric modes are forced. These experiments do not support a commonly accepted mechanism involving the forcing projecting directly onto the wave modes with a strong response, yet still simulate a power spectrum resembling that observed, though the linear projection mechanism could still complement the mechanism proposed here in observations. Interpreting the observed tropical power spectrum using turbulence offers a simple explanation as to why power should be concentrated at the theoretical wave modes, and also provides a solid footing for the common assumption that the background spectrum is red, even as it clarifies why there is no expectation for a turbulent cascade with a specific, theoretically derived slope such as −5/3. However, it does explain why the cascade should be toward lower wavenumbers, that is an inverse energy cascade, similar to the midlatitudes even as compressible wave modes are important for tropical dynamics.
It also explains why  in satellite observations and reanalysis data, the symmetric component is stronger than the anti-symmetric component, as any bias in the small-scale forcing from isotropy, whether symmetric or antisymmetric, leads to symmetric bias in the large-scale spectrum regardless of the source of variability responsible for the onset of the asymmetry.


Shamir, O., C. Schwartz, C.I. Garfinkel, and N. Paldor, The power distribution between symmetric and anti-symmetric components of the tropical wavenumber-frequency spectrum, JAS, https://doi.org/10.1175/JAS-D-20-0283.1 .
Garfinkel, C.I., O. Shamir, I. Fouxon, and N. Paldor, Tropical background and wave spectra: contribution of wave-wave interactions in a moderately nonlinear turbulent flow, JAS, https://doi.org/10.1175/JAS-D-20-0284.1.
Shamir, O., C.I. Garfinkel, O. Adam, and N. Paldor, A note on the power distribution between symmetric and anti-symmetric components of the tropical Brightness Temperature spectrum in the wavenumber-frequency plane , JAS,doi: 10.1175/JAS-D-21-0099.1.

How to cite: Paldor, N., Garfinkel, C. I., and Shamir, O.: Tropical Background and Wave Spectra: Contribution of Wave–Wave Interactions in a Moderately Nonlinear Turbulent Flow, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1089, https://doi.org/10.5194/egusphere-egu22-1089, 2022.

How to cite: Sternberg, T. and Jackson, A.: Nonlinear subcritical and supercritical thermal convection in a sphere, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2192, https://doi.org/10.5194/egusphere-egu22-2192, 2022.

Ocean turbulence causes flows to split into smaller whirls or merge to make larger whirls, cascading energy to small or large scales respectively. Conventional ocean dynamics dictates that the kinetic energy in the ocean will cascade primarily to larger scales, via the inverse energy cascade, and has raised the question of how the kinetic energy in the ocean dissipates, which would necessarily require the transfer towards the molecular scales. However, so far no clear observational quantification of the energy cascade at the scales where these mechanisms are potentially active has been made. By using forcing-scale resolving third-order structure-function theory, which captures bidirectional energy fluxes and is applicable beyond inertial ranges, we analyse data from surface drifters, released in dense arrays in the Gulf of Mexico, to obtain the kinetic energy flux magnitude and directions along with the energy injection scales. We provide the first direct observational verification that the surface kinetic energy cascades to both small and large scales, with the forward cascade dominating at scales smaller than approximately 1-10km. Our results also show that there is a seasonality in these cascades, with winter months having a stronger injection of energy into the surface flows and a more energetic cascade to smaller scales. This work provides exciting new opportunities for further probing the energetics of ocean turbulence using non-gridded sparse observations, such as from drifters, gliders, or satellites.

How to cite: Xie, J.-H., Balwada, D., Marino, R., and Feraco, F.: Direct evidence of an oceanic dual kinetic energy cascade and its seasonality from surface drifters, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2238, https://doi.org/10.5194/egusphere-egu22-2238, 2022.

According to the classic energy cascade notion, large eddies as energy carrier are unstable to break up, through which energy is transferred from large scales till the smallest ones to dissipate the kinetic energy. A fundamental issue hereof is how to quantify the eddies of different sizes, else the energy cascade scenario remains illustrative. A possible remedy is the idea of dissipation element (DE) analysis, which is a topological approach based on extremal points. In this method, starting from each spatial point in a turbulent scalar field ϕ, a local minimum point and a local maximum point will inevitably be reached along the descending and ascending directions of the scalar gradient trajectory, respectively. The ensemble of spatial points whose gradient trajectories share the same pair of minimum and maximum points define a spatial region, called a DE. The entire filed can thus be partitioned into space-filling DEs. Typically, DE can be parameterized with l, the linear distance between the two extremal points, and ∆ϕ = ϕ_max – ϕ_min, the absolute value of the scalar quantity difference between the two extremal points. It needs to mention that dependence of the DE structure on the ϕ field is conformal with the physics that different variable fields are different structured, although related. In the past years, DE analysis has been implemented to understand the turbulence dynamics under different conditions. Since inside each DE, the monotonous change of the field variable (from ϕ_min  to ϕ_max  along the trajectory) depicts a laminar like structure in a local region, the space-filling DEs can be recognized as the smallest eddies.

In a more general sense, a newly defined multi-level DE structure has been developed. Introducing the size of the observation window S, extremal points are multi-level, based on which the DE structure can be extended to multi-level. At each S-level, the turbulent field can be decomposed into space-filling DEs, which makes it possible to understand to entire field from the properties of such individual units. In this sense, it is tentatively possible to define turbulent eddies of different scales as DEs at different S-levels. Conventional analyses based on “turbulent eddies” can be implemented using such idea. For instance, during energy cascade, eddy breakup corresponds to the splitting of DEs at higher levels (with larger S) to smaller ones at lower levels (with smaller S). Because of DE can be exactly defined, eddies can be quantified as well, but not just demonstrative. Such kind of multi-level DE structure is uniquely different from other existing approaches (e.g. vortex tube, PoD, Fourier analysis etc.) in the following senses. First, DEs at any S-level are quantitatively defined, rather than qualitatively visualized. Second, DEs at any S-level are space-filling.  The multi-level DE approach is generally applicable in turbulence analysis.

How to cite: Wang, L.: Quantification of “turbulent eddies” in energy cascade based on the multi-level dissipation element structure, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3335, https://doi.org/10.5194/egusphere-egu22-3335, 2022.

In his seminal work on turbulence, Kolmogorov made use of the stationary hypothesis to determine the Power Density Spectra of velocity field in turbulent flows. However to our knowledge, the constraints that stationary processes impose on the fluctuations of power have never been used in the context of turbulence. Here we recall that the Power Density Spectra of the fluctuations of the injected power, the dissipated power and the energy flux have to converge to a common value at vanishing frequency. Hence, we show that the intermittent GOY-shell model fulfills these constraints on the power as well as on the energy fluxes. We argue that they can be related to intermittency. Indeed, we find that the constraints on the power fluctuations imply a relation between scaling exponents, which is consistent with the GOY-shell model and in agreement with the She-Leveque formula. It also fixes the intermittent parameter of the log-normal model at a realistic value. The relevance of these results for real turbulence is drawn in the concluding remarks.

How to cite: Aumaitre, S. and Fauve, S.: Turbulent intermittency as a consequence of stationarity of the energy balance, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3918, https://doi.org/10.5194/egusphere-egu22-3918, 2022.

The turbulent energy cascade is one of the most recognizable characteristics of turbulent flow. Still, representing this tendency of large-scale anisotropic eddies to redistribute their energy content with decreasing scale, a phenomenon referred to as return to isotropy, remains a recalcitrant problem in the physics of turbulence. Atmospheric turbulence is characterised by large scale separation between production and viscous destruction of turbulent kinetic energy making it suitable for exploring such scale-wise redistribution of energy among velocity components.  Moreover, real-world atmospheric turbulence offers an unprecedentedly diverse source of inhomogeneity and large-scale anisotropy (caused by shear, buoyancy, terrain-induced pressure perturbations, closeness to the wall) while maintaining a high Reynolds number state. It may thus be assumed that relaxation through the energy cascade may be dependent on the anisotropy source, thus adding to the ways that atmospheric turbulence differs from canonical turbulent boundary-layers.

Here, we examine the scalewise return to isotropy for an unprecedented dataset of atmospheric turbulence measurements covering flat to mountainous terrain, stratification spanning convective to very stable conditions, surface roughness ranging over several orders of magnitude, various distances from the surface, and Reynolds numbers that far exceed the limits of direct numerical simulations and laboratory experiments.  The results indicate that irrespective of the complexity of the dataset examined, the return-to-isotropy trajectories that start from specific initial anisotropy at large scales show surprising scalewise universality in their trajectories towards isotropy. This novel finding suggests that the effects of boundary conditions, once accounted for in the starting anisotropy of the trajectory in the cascade, cease to be important at much smaller scales. It can therefore be surmised that large-scale anisotropy encodes the relevant information provided by the boundary conditions, adding to the body of evidence that the information on anisotropy is a missing variable in understanding and modelling atmospheric turbulence [1-3].

[1]  Stiperski I, and M Calaf. Dependence of near-surface similarity scaling on the anisotropy of atmospheric turbulence. Quarterly Journal of the Royal Meteorological, 144, 641-657, 2017.

[2]  Stiperski I, M Calaf and MW Rotach. Scaling, anisotropy, and complexity in near-surface atmospheric turbulence. Journal of Geophysical Research: Atmospheres, 124, 1428-1448, 2019.

[3] Stiperski I, GG Katul, M Calaf. Universal return to isotropy of inhomogeneous atmospheric boundary layer turbulence. Physical Review Letters, 126 (19), 194501, 2021

How to cite: Stiperski, I., Katul, G. G., and Calaf, M.: Scalewise Universal Relaxation to Isotropy of Inhomogeneous Atmospheric Boundary Layer Turbulence, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5934, https://doi.org/10.5194/egusphere-egu22-5934, 2022.

Due  to the extreme complexity of the oceanic dynamics, e.g., stratification, air-sea interaction,  waves, current, tide, etc., the corresponding turbulent cascade remains unknown. The third-order longitudinal structure-function is often employed to diagnose  the cascade direction and intensity, which is written as  S_LLL(r)=< Δ u_L³(r)>, where Δ u_L is the  velocity increment along the distance vector r, and r is the modulus of r. In the case of  three-dimension homogeneous and isotropic turbulence, S_LLL(r) is scaled as -4/5εr in the inertial range, where ε is the energy dissipation rate per unit.  In this work, S_LLL(r) is estimated for two experimental velocities that obtained in the Gulf of Mexico, namely Grand LAgrangian Deployment (GLAD) and the LAgrangian Submesoscale ExpeRiment (LASER). The experimental S_LLL(r) for both experiments shows a transition from negative values to a positive one roughly at r_T=10km, corresponding to a timescale  around τ_T=12-hour (e.g., τ_T=r_T/u_rms with u_rms ≈0.24m/s.  Power-law is evident for the scale on the range 0.01≤ r≤1km as S_LLL(r)∼ -r^1.45±0.10, and for the scale on the range 30≤ r≤300km as S_LLL(r)∼ r^1.45±0.10. Note that a weak stratification with depth of 10∼15m has been reported for the GLAD experiment, indicating a quasi-2D flow topography. The scaling ranges are above this stratification depth. Hence, the famous Kraichnan's 2D turbulence theory or the geostrophic turbulence proposed by Charney are expected to be applicable. However, due to the complexity of real oceanic flows, hypotheses behind these theories cannot be verified either directly or indirectly. To simplify the situation, we still consider here the sign of  S_LLL(r) as an indicator of the energy cascade. It thus suggests a possible forward energy cascade below the spatial scale r_T, and an inverse one above the scale  spatial r_T.  While, the scaling exponents 1.45 are deserved more studied in the future if more data is available.

Ref.

Charney, J. G. (1971). Geostrophic turbulence. J. Atmos. Sci., 28(6), 1087-1095.

Frisch, U., & Kolmogorov, A. N. (1995). Turbulence: the legacy of AN Kolmogorov. Cambridge University Press.

Alexakis, A., & Biferale, L. (2018). Cascades and transitions in turbulent flows. Phys. Rep., 767, 1-101.

Dong, S., Huang, Y., Yuan, X., & Lozano-Durán, A. (2020). The coherent structure of the kinetic energy transfer in shear turbulence. J. Fluid Mech., 892, A22.

Poje, A. C., Özgökmen, T. M., Bogucki, D. J., & Kirwan, A. D. (2017). Evidence of a forward energy cascade and Kolmogorov self-similarity in submesoscale ocean surface drifter observations. Phys. Fluids, 29(2), 020701.

How to cite: Ma, Y., Hu, J., and Huang, Y.: Turbulent Energy Cascade in the Gulf of Mexico, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7004, https://doi.org/10.5194/egusphere-egu22-7004, 2022.

Recently, multiscale statics is found to be relevant in description of the lithosphere deformation of the Tibetan Plateau (Jian et al, Phys. Rev. E, 2019). More precisely, a dual-power-law behavior is observed respectively on the spatial scale range of  50≤ r≤ 500km and 500≤ r ≤2000km, which coincidently agrees well with the one reported for the atmospheric movement (Nastrom et al., Nature, 1984). The corresponding high-order scaling exponents demonstrated a nonlinear shape, showing multifractality nature of the underlying dynamics. To diagnose further whether the lithosphere deformation is turbulent or not, the third-order longitudinal structure-function S_LLL(r)=< Δu_L(r)³> is estimated, where r is the modulus of the distance vector  r, and  Δu_L is the velocity component that paralleling with r.  Due to the finite sample size, the experimental S_LLL(r) is not reliable when r≤200km. The measured S_LLL(r) is scaled as  -r^4±0.2 on the spatial scale range of 500≤ r ≤ 2000km, indicating the existence of a turbulent cascade. Because of the complexity of the geodynamics, e.g., Coriolis force, mantle convection, India-Eurasia collision, to list a few, the exact force balance is remained unknown. Therefore, the full interpretation of the current observation is not feasible.

Ref.

A. Alexakis, &  L. Biferale (2018). Cascades and transitions in turbulent flows, Phys. Rep., 767, 1-101.

U. Frisch, (1995) Turbulence: The Legacy of A.N. Kolmogorov, Cambridge University Press

X. Jian, W. Zhang, Q. Deng & Y.X. Huang (2019) Turbulent lithosphere deformation in the Tibetan Plateau, Phys. Rev. E, 99:062122

G.D. Nastrom, K.S Gage & Jasperson (1984) Kinetic energy spectrum of large- and mesoscale atmospheric processes, Nature, 310:36

How to cite: Yan, T., Ma, Y., Hu, J., and Huang, Y.: Turbulent Cascade of  the Lithosphere Deformation in the Tibetan Plateau, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7115, https://doi.org/10.5194/egusphere-egu22-7115, 2022.

In this study, we analyse the non-linear transfer of kinetic energy in simulations of convection in a 3D rotating shell. Our aim is to understand the role of upscale transfer of kinetic energy and a potential inverse cascade for the formation of zonal jets and large vortices on the giant planets Jupiter and Saturn. We find that the main driving of the jets is associated with upscale transfer directly from the convection scale to the jets. This transfer of energy is mediated by Reynolds stresses, i.e. statistical correlations of velocity components of the small-scale flow.  Intermediate scales are mostly not involved, therefore strictly speaking the jets are not powered by an inverse energy cascade. To a much smaller degree, energy is transferred upscale from the convective scale to large vortices. However, these vortices also receive energy from the jets, likely due to an instability of the jet flow.  Concerning transport in the forward direction, we find as expected that the 3D convective motions transfer energy to the even smaller dissipation scales in a forward cascade.

How to cite: Böning, V., Wulff, P., Dietrich, W., Christensen, U. R., and Wicht, J.: Upscale and forward transfer of kinetic energy: Impact on giant planetary jet and vortex formation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7557, https://doi.org/10.5194/egusphere-egu22-7557, 2022.

Turbulence theory essentially describes energy and enstrophy flows crossing scales or a balance between input and output. A famous example is the Richardson-Kolmogorov forward energy cascade picture for three-dimensional homogeneous and isotropic turbulence. However, due to the complexity of turbulent systems, and the lack of an efficient method to describe the cascade quantitatively, the factual cascade features for most fluids are still unknown. In this work, an improved Filter-Space-Technique (FST) is proposed to extract the energy flux Π_E, and enstrophy flux Π_Ω between different scales for the ocean surface wind field which was remotely sensed by the China-France Oceanography Satellite (CFOSAT). With the improved FST method, Π_E and Π_Ω can be calculated for databases which contain gaps or with irregular boundary conditions. Moreover, the local information of the fluxes are preserved. A case study of the typhoon Maysak (2020) shows both inverse and forward cascades for the energy and enstrophy around the center of the typhoon, indicating a rich dynamical pattern. The global views of Π_E and Π_Ω for the wind field are studied for scales from 12.5 to 500 km. The results show that both Π_E and Π_Ω are hemispherically symmetric, with evident spatial and temporal variations for all the scales. More precisely, positive and negative Π_E  are found for the scales less and above 60 km, respectively. As for Π_Ω, the transition scale is around 150 km, forward and backward cascades are corresponding to the scales below and above this scale. In the physical space, stronger fluxes are occurring in midlatitudes than the ones in tropical regions, excepts for a narrow region around 10^oN, where strong fluxes are observed. In the temporal space, the fluxes in winter are stronger than the ones in summer. Our study provides an improved approach to derive the local energy and enstrophy fluxes with complex field observed data. The results presented in this work contribute to the fundamental understanding of ocean surface atmospheric motions in their multiscale dynamics, and also provide a benchmark for atmospheric models.

Ref. 

Alexakis, A., & Biferale, L. (2018). Cascades and transitions in turbulent flows. Phys. Rep., 767, 1-101.

Dong, S., Huang, Y.X., Yuan, X., Lozano-Durán, A. (2020). The coherent structure of the kinetic energy transfer in shear turbulence. J. Fluid Mech., 892, A22.

Frisch, U., Kolmogorov, A. N. (1995). Turbulence: the legacy of AN Kolmogorov. Cambridge University Press.

Gao, Y. , Schmitt, F.G., Hu,  J.Y. &  Huang, Y.X. (2021) Scaling analysis of the China France Oceanography Satellite along-track wind and wave data. J. Geophys. Res. Oceans, 126:e2020JC017119

How to cite: Gao, Y., Schmitt, F. G., Hu, J., and Huang, Y.: Scale-to-Scale Energy and Enstrophy Fluxes of Atmospheric Motions via CFOSAT, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8277, https://doi.org/10.5194/egusphere-egu22-8277, 2022.

In his seminal work "Weather Prediction by Numerical Process" in 1922, Lewis Fry Richardson proposed the famous cascade picture qualitatively for a turbulent flow that energy transferring from large to small scale  structures, until the viscosity one where the kinetic energy is converted  into heat. This picture has been recognized further as the forward energy  cascade.  But, it cannot be applied directly to the real atmospheric  or oceanic motions. Whatever, the global circulation model is indeed established within this framework by considering more complex situations, e.g., earth rotation, stratification, tide, mesoscale eddies, to list a few. In  this work, an improved Filter-Space-Technique (FST) is applied to a reanalysis product provided by the CMEMS global ocean eddy-resolving (1/12^o degree horizontal resolution).   The FST provides a global view of the  energy flux Π_E  that associated with the oceanic cascades for all resolved  scales, e.g., from mesoscale eddies to global circulations. For instance, at scale r=160 km (i.e., radius of the Gaussian filter kernel), a rich dynamic pattern is observed for an instantaneous flow filed. Both forward (Π_E>0, energy transferring from large scale to small scale structures) and inverse (Π_E<0, energy transferring from small scale to large scale structures) cascades are evident in the equator, western boundary current regions, Antarctic Circumpolar Current region, to name a few. While, the long-term averaged flux field show mainly a negative Π_E (inverse energy cascade) except for the equatorial region. Moreover, a high intensity negative flux is found for both the Loop Current and Kuroshio Current, indicating that the mesoscale eddies might be absorbed by the main flow.

Ref.

Charney, J. G. (1971). Geostrophic turbulence. J. Atmos. Sci., 28(6), 1087-1095.

Frisch, U.,  Kolmogorov, A. N. (1995). Turbulence: the legacy of AN Kolmogorov. Cambridge University Press.

Alexakis, A.,  Biferale, L. (2018). Cascades and transitions in turbulent flows. Phys. Rep., 767, 1-101.

Dong, S., Huang, Y.X., Yuan, X., & Lozano-Durán, A. (2020). The coherent structure of the kinetic energy transfer in shear turbulence. J. Fluid Mech., 892, A22.

How to cite: Song, J., Zhang, D., Peng, Y., Gao, Y., and Huang, Y.: Global view of oceanic cascades from the Global Circulation Model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8564, https://doi.org/10.5194/egusphere-egu22-8564, 2022.

Big whirls have little whirls that feed on their velocity,

and little whirls have lesser whirls and so on to viscosity.

These famous words written in 1922 by Lewis Fry Richardson have become inspiration for intensively developing scientific field studying scales of climate variability and their interactions. In spite of ever growing interest in this research area, the description of this session states: ”We still lack an efficient methodology to diagnose the scale-to-scale energy or other physical quantities fluxes to characterize the cascade quantitatively, e.g., strength, direction, etc. ”  In this contribution we would like to remind the methodology able to identify causal relations and information transfer between dynamical processes on different time scales and even to quantify the effect of such causal influences. Moreover, in macroscopic systems the information transfer is tied to the transfer of mass and energy [1].

The detection of cross-scale causal interactions [2] starts with a wavelet (or other scale-wise) decomposition of a multi-scale signal into quasi-oscillatory modes of a limited bandwidth, described using their instantaneous phases and amplitudes. Then their statistical associations are tested in order to search interactions across time scales. An information-theoretic formulation of the generalized, nonlinear Granger causality [3] uncovers causal influence and information transfer from large-scale modes of climate variability, characterized by time scales from years to almost a decade, to regional temperature variability on short time scales.  In particular, a climate oscillation with the period around 7-8 years has been identified as a factor influencing variability of surface air temperature (SAT) on shorter time scales.  Its influence on the amplitude of the SAT annual cycle was estimated in the range 0.7-1.4 °C, while its strongest effect was observed in the interannual variability of the winter SAT anomaly means where it reaches 4-5 °C in central European stations and reanalysis data [4].  In the dynamics of El Niño-Southern Oscillation (ENSO), three principal time scales - the annual cycle (AC), the quasibiennial (QB) mode(s) and the low-frequency (LF) variability – and their causal network have been identified [5]. Recent results show how the phases of ENSO QB and LF oscillations influence amplitudes of precipitation variability in east Asia in the annual and QB scales.

Support from the Czech Science Foundation (GA19-16066S) and the Czech Academy of Sciences (Praemium Academiae) is gratefully acknowledged.

[1] J. Hlinka et al., Chaos 27(3), 035811 (2017)

[2] M. Palus, Phys. Rev. Lett. 112, 078702 (2014)

[3] M. Palus, M. Vejmelka, Phys. Rev. E 75, 056211  (2007)

[4] N. Jajcay, J. Hlinka, S. Kravtsov, A. A. Tsonis, M. Palus, Geophys. Res. Lett. 43(2), 902–909 (2016)

[5] N. Jajcay, S. Kravtsov, G. Sugihara, A. A. Tsonis, and M. Palus, npj Climate and Atmospheric Science 1, 33 (2018).  doi:10.1038/s41612-018-0043-7, https://www.nature.com/articles/s41612-018-0043-7

How to cite: Palus, M.: Big whirls talking to smaller whirls: detecting cross-scale information flow, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9028, https://doi.org/10.5194/egusphere-egu22-9028, 2022.

How to cite: Chouksey, A., Carton, X., and Gula, J.: Study of Submesoscale Coherent Vortices (SCVs) in the Atlantic Ocean along different isopycnals, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9226, https://doi.org/10.5194/egusphere-egu22-9226, 2022.

In recent years a consensus has been reached regarding the direction of the energy cascade in the mesoscales in the Upper Tropospheric-Lower Stratospheric (UTLS) altitudes. Numerous measurements and model results confirm the existence of a predominantly forward spectral energy flux from low to high horizontal wavenumbers. However, the details to explain the observed -5/3 power law for Kinetic and Available Potential Energy (KE and APE) are still being debated.

In this study we performed simulations using the dry version of the Kühlungsborn Mechanistic general Circulation Model (KMCM) with high horizontal and vertical resolution for permanent January conditions. Horizontal diffusion schemes for horizontal momentum and sensible heat satisfy the Scale Invariance Criterion (SIC) using the Dynamic Smagorinsky Model (DSM). We investigated the simulated KE and APE spectra with regard to the scaling laws of Stratified Macro-Turbulence (SMT). Zonally and temporally averaged dissipation rates for KE & APE and SMT statistics correlate highly in subtropical mid-latitudes and the UTLS levels. Particularly the characteristic dimensionless numbers of Buoyancy Reynolds Number and turbulent-Rossby Number are pronounced in the regions, where the maximum of the forward spectral fluxes of nonlinear interactions are also found. During this process the spectral contribution of the negative buoyancy production term plays an important role by converting KE to APE. These findings are entirely in line with the spectral and statistical predictions of idealized Stratified Turbulence (ST) and confirms that the energy cascades that give rise to the simulated mesoscale shallowing are strongly nonlinear.

Furthermore level by level analyses of the horizontally averaged spectral tendencies and fluxes of both KE and APE reservoirs in this specific region revealed that there is a non-negligible spectral contribution by the energy deposition term of upward propagating Gravity Waves (GW). Further investigation indicate the dynamics of these resolved GWs look like a superposition of westward Inertia GWs that are subject to a Lindzen-type saturation condition. Their vertical propagation in UTLS heights is non-conservative above their generation level. These results associate directly for the first time ST and GW dynamics, which were thought to be distinct in character. Finally we present simulations with different diffusion schemes and show that the previously mentioned energy deposition contribution was only identified if both horizontal momentum and sensible heat diffusion schemes fulfill the SIC.

How to cite: Can, S.: Macro-Turbulent Energy Cascades in UpperTropospheric-Lower Stratospheric Mesoscales, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9270, https://doi.org/10.5194/egusphere-egu22-9270, 2022.

Western boundary currents are hotspots of the mesoscale oceanic variability and of energy transfers, channeled by topography, toward smaller scales and eventually down to dissipation. Here, we assess the main mesoscale eddies energy sinks in the Agulhas Current region, with an emphasize on the different paths of energy toward smaller scales, from a regional numerical simulation. 

We derive an eddy kinetic energy (EKE) budget in the framework of the vertical modes. This comprehensive method accounts for energy transfers between energy reservoirs and vertical modes, including transfers channeled by topography and by a turbulent vertical cascade. 

The variability is dominated by mesoscale eddies (barotropic and 1^st baroclinic modes) in the path of intense mean currents. Eddy-topography interactions result in a major mesoscale eddy energy sink (50 % of the total EKE sink). They represent energy transfers both toward higher baroclinic modes (27 % of the total EKE sink) and mean currents (23 % of the total EKE sink). Energy transfers toward higher baroclinic modes take different forms in the Northern Agulhas Current, where it corresponds to non-linear transfers to smaller vertical eddies on the slope (5 % of the total EKE sink), and in the Southern Agulhas Current, where it is dominated by a (linear) generation of internal-gravity waves over topography (22 % of the total EKE sink). The vertical turbulent cascade is significant in offshore regions, away from topography and intense mean currents. In these regions the direction of the turbulent vertical cascade is inverse - energy transferred from higher baroclinic modes toward mesoscale eddies - and it can locally amounts for most of the mesoscale eddies energy gain (up to 68 % of the local EKE source).

However, the Agulhas Current region remains a net source of mesoscale eddy energy due to the strong generation of eddies, modulated by the topography, especially in the Southern Agulhas Current. In the complex Agulhas Current system, which includes an intense mean oceanic current and mesoscale eddies field as well as strong topographic constraint and stratification gradients, the local generation of mesoscale eddies dominates the net EKE budget. It is in contrast with the paradigm of mesoscale eddies decay upon western boundaries, suggested as being due to topographically-channeled interactions triggering a direct energy cascade.

How to cite: Tedesco, P., Gula, J., Penven, P., and Ménesguen, C.: Mesoscale Eddy Kinetic Energy budgets and transfers between vertical modes in the Agulhas Current, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9329, https://doi.org/10.5194/egusphere-egu22-9329, 2022.

The relative dispersion of pairs of particles was first considered in a seminal article by Richardson (1926). The dispersion subsequently was subsequently linked to turbulence, and pair separation statistics can advantageously be used to deduce energy wavenumber spectra. Thus one can, for example, employ surface drifters to identify turbulent regimes at scales well below those resolved by satellite altimetry. The identification relies on knowing how dispersion evolves with a specific energy spectrum. The analytical predictions commonly used apply to infinite inertial ranges, i.e. assuming the same dispersive behavior over all scales. With finite inertial ranges, the metrics are less conclusive, and often are not even consistent with each other.

We examine this using pair separation probability density functions (PDFs), obtained by integrating a Fokker-Planck equation with different diffusivity profiles. We consider time-based metrics, such as the relative dispersion, and separation-based metrics, such as the finite scale Lyapunov exponent (FSLE). As the latter cannot be calculated from a PDF, we introduce a new measure, the Cumulative Inverse Separation Time (CIST), which can. This behaves like the FSLE, but advantageously has analytical solutions in the inertial ranges. This allows establishing consistency between the time- and space-based metrics, something which has been lacking previously.

We focus on three dispersion regimes: non-local spreading (as in a 2D enstrophy inertial range), Richardson dispersion (as in the 3D and 2D energy inertial ranges) and diffusion (for uncorrelated pair motion). The time-based metrics are more successful with non-local dispersion, as the corresponding PDF applies from the initial time. Richardson dispersion is barely observed, because the self-similar PDF applies only asymptotically in time. In contrast, the separation-based CIST correctly captures the dependencies, even with a short (one decade) inertial range, and is superior to the traditional FSLE at large scales. Furthermore, the analytical solutions permit reconciling the CIST with the other measures, something which is generally not possible with the FSLE.

How to cite: LaCasce, J. and Meunier, T.: Relative Dispersion with Finite Inertial Ranges, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13450, https://doi.org/10.5194/egusphere-egu22-13450, 2022.

There are many regions where the duration of reliable scientific observations of key weather hazard variables, such as rainfall and wind speed, is of the order of just a few decades.  This length of dataset is often inadequate for the application of extreme value theory to rare events. Theoretical analysis of chaotic dynamical systems shows that extremes should be distributed according to the classical Pareto distribution, with explicit expressions for the scaling and shape parameter[1]. Discrepant results may be interpreted as indicating the need for a longer data time series.

Physicists acknowledge that history is just one realisation of what could have happened. One way of supplementing a brief duration observational dataset is to generate an ensemble of alternative realisations of history. Of special practical interest within this counterfactual ensemble are downward counterfactuals - where the outcome turned for the worse.  Extreme hazard events often cause surprise, which reflects an underlying degree of outcome cognitive bias. Downward counterfactual is a term originating in the cognitive psychological literature, which has been applied by Woo[2] to the search for extreme hazard events.  Most human counterfactual thoughts are upward, focusing on risk mitigation or prevention, rather than downward, focusing on potential rare Black Swan events. 

The insight gained from downward counterfactual analysis is illustrated with the example of rainfall and flooding in Cumbria, Northwest England.  Daily rainfall records at Honister Pass, Cumbria, from 1970 to 2004, were statistically analysed to estimate the return period for the rainfall of 301.4mm oberved on 20 November 2009.  This return period was estimated to be 396 years[3].  But six years later, on 5 December 2015, this was substantially exceeded by 341.4mm rainfall.

In 2009, there was only a moderate El Niňo.  Counterfactually, there might have been a strong El Niňo.  Indeed, in 2015 there was a very strong El Niňo. A downward counterfactual analysis of the heavy rainfall on 20 November 2009 would have included the possibility of a very strong El Niňo.  This is one of a number of exacerbating dynamical meteorological factors that might have elevated the rainfall.

Where the data duration is much shorter than the return period of extreme events, a downward counterfactual stochastic simulation of factors raising the hazard will provide important additional insight for geophysical hazard assessment.

How to cite: Woo, G.: Downward counterfactual insights into weather extremes, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-30, https://doi.org/10.5194/egusphere-egu22-30, 2022.

Global precipitation characteristics have been significantly altered due to the global warming. While, this is well-known, the sub-daily extreme precipitation events are more sensitive, as compared to the daily-scale. The future intensification of these sub-daily extremes worsen the risk of floods and droughts, thereby posing threat to the natural ecosystem and human society. The ability of general circulation models (GCMs) in simulating the sub-daily precipitation may be inferior, due to their coarser resolutions and complex parametrization schemes. In addition, the characteristics such as the intensity, frequency and duration of sub-daily precipitation may not be correctly simulated by the GCMs. Despite this fact, there are limited studies to investigate the credibility of sub-daily precipitation projections by GCMs, and the related uncertainty. Therefore, in order to investigate the reliability of GCMs in the projections of such extremes, we have used 20 Coupled Model Intercomparison Project phase 5 (CMIP5) models under RCP8.5 (Representative Concentration Pathway). The uncertainty is estimated in the projections of maximum wet spell length (WSL) i.e. maximum number of consecutive wet hours in four different meteorological seasons (DJF, MAM, JJA, and SON), for both near (2026-45) and far future (2081-99) time periods. The equatorial regions of Africa and South East Asia, showed higher model disagreement during every season. In contrast the equatorial regions of South America and South Asia showed significantly more disagreement during DJF and JJA season. Model uncertainty in each hemisphere is observed to be higher during their respective wet seasons. Though the model uncertainty in far future is varying when compared with that in near future, the uncertainty is not increasing globally. Also, the uncertainty is observed to have significantly decreased during MAM season in far future. The spatial contribution towards higher model uncertainty range, is less as compared to lower uncertainty range over the globe. While the magnitude of model uncertainty is varying with time, the latitudinal heterogeneity remains same in both the time period. 

Keywords: precipitation extremes, sub-daily, wet spell, GCM, projections, uncertainty, RCP 8.5

How to cite: Majhi, A., Dhanya, C. T., and Chakma, S.: Quantification of model uncertainty in the projection of sub-daily maximum wet spell length under RCP 8.5 climate change scenario, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-54, https://doi.org/10.5194/egusphere-egu22-54, 2022.

Due to the compounding nature of co-occurring weather extremes, these events can be highly detrimental to economies, damaging to infrastructure and result in loss of life. Previous work has established a connection between cold spells over North America and extreme wet and windy weather over Europe. This work attempts to identify a statistical link between the regional impact of wet and windy extremes over Europe based on the regional impact of cold spells over North America. We identify cold spells for 41 overlapping regions over North America for full winter (DJF) seasons between 1979 and 2020 using ERA5 data, employing 4 methodologies for the computation of onset dates. The impact of extreme precipitation and wind events over 6 regions of western and central Europe is analysed. Consistent across all methodologies, cold spells over eastern and mid USA are followed by significant wind extremes over Iberia, whilst cold spells over eastern Canada are followed by significant wind extremes over northern Europe and the British Isles. The regional impact of precipitation extremes shows much greater variance, though we find significant Iberian and southern European precipitation for cold spells over eastern USA, consistent with that found for wind extremes. The majority of extreme precipitation and some significant wind extremes also precede the peak of the cold spell. We show also that the frequency of extreme precipitation and wind events over Iberia increases by 1.5 to more than 2 times the climatological frequency, following cold spells in most North American regions.

How to cite: Leeding, R., Messori, G., and Riboldi, J.: The Regional Impact of Wet and Windy Extremes Over Europe, Following North American Cold Spells, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-258, https://doi.org/10.5194/egusphere-egu22-258, 2022.

Heatwaves cause widespread disruption to society and increased mortality across Europe. These events are often associated with persistent circulations, however, the maintenance mechanisms and characteristics of atmospheric persistence are comparatively poorly understood. We aim to help bridge the gap between qualitative meteorological arguments and mathematical theory relating to heatwaves by quantitatively identifying persistent atmospheric configurations. This will be achieved by calculating indicators associated with dynamical systems theory using ERA5 reanalysis data. We will then spatially compare these indicators with temperature anomalies to determine which regions of Europe are potentially sensitive to these quantities with regards to the occurrence of heatwaves, and if there are specific atmospheric configurations associated to these cases.

How to cite: Allwright, E. and Messori, G.: Relating atmospheric persistence to heatwaves in Europe, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-470, https://doi.org/10.5194/egusphere-egu22-470, 2022.

Unusual, long-lasting configurations of the North Atlantic jet stream affect the weather over Europe leading to persistent surface extremes. We study these persistent jet configurations in winter on intraseasonal and seasonal time scales using CMIP6 simulations, based on temporal averages of three jet indices: the jet latitude index, the jet speed index and the zonal jet index. We define these unusual configurations as long-lasting states, during which the jet stream is further south or further north, stronger or weaker, more split or more merged than usual. We estimate the probability of rare configurations, lasting at least 2 months, based on large deviation rate functions. The rate functions are asymmetric in case of the jet speed index, meaning that anomalously strong jet states are more persistent and more frequent than weak ones. Furthermore, we quantify the increased frequency of temperature and precipitation extremes over affected European regions. Here, we find a stronger link between jet events and precipitation extremes compared to temperature extremes. We observe the largest effects in case of precipitation extremes over the Mediterranean and Western Europe during anomalously strong jet configurations.

How to cite: Galfi, V. M. and Messori, G.: Persistent configurations of the North Atlantic jet stream from the perspective of large deviation theory, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-474, https://doi.org/10.5194/egusphere-egu22-474, 2022.

Detecting trends in regional large-scale circulation (LSC) is an important challenge as LSC is a key driver of local weather conditions. In this work, we investigate the past evolution of Western Europe LSC based on the 500 hPa geopotential height fields from 20CRv2c (1851-2010), ERA20C (1900-2010) and ERA5 (1950-2010) reanalyses. We focus on the evolution of large-scale circulation characteristics using three atmospheric descriptors that are based on analogy, by comparing daily geopotential height fields to each other. They characterize the stationarity of geopotential shape and how well a geopotential shape is reproduced in the climatology. A non-analogy descriptor is also employed to account for the intensity of the centers of action. We then combine the four atmospheric descriptors with an existing weather pattern classification over the period 1950-2019 to study the recent changes in the main atmospheric influences driving precipitation in the Northern French Alps. Even though LSC characteristics and trends are consistent among the three reanalyses after 1950, we find major differences between 20CRv2c and ERA20C from 1900 to 1950 in accordance with previous studies. Notably, ERA20C produces flatter geopotential shapes in the beginning of the 20th century and shows a reinforcement of the meridional pressure gradient that is not observed in 20CRv2c. Over the period 1950-2019, we show that winter Atlantic circulations (zonal flows) tend to be shifted northward and they become more similar to known Atlantic circulations. Mediterranean circulations tend to become more stationary, more similar to known Mediterranean circulations and associated with stronger centers of action in autumn, while an opposite behaviour is observed in winter. Finally, we discuss the responsibility of these LSC changes for extreme precipitation in the Northern French Alps. We show these changes in LSC characteristics are linked to more circulations that are likely to generate extreme precipitation in autumn.

How to cite: Blanc, A., Blanchet, J., and Creutin, J.-D.: Past Evolution of Western Europe Large-scale Circulation and Link to Extreme Precipitation Trend in the Northern French Alps, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1594, https://doi.org/10.5194/egusphere-egu22-1594, 2022.

Marine heatwaves (MHWs) are periods of extreme warm ocean temperatures that can have devastating impacts on marine
organisms and socio-economic systems. Despite recent advances in understanding the underlying processes of individual events, a
global view of the local oceanic and atmospheric drivers of MHWs is currently missing. Here, we use daily-mean output of
temperature tendency terms from a comprehensive fully coupled Earth system model to quantify the main local processes leading
to the buildup and decay of MHWs in the surface ocean. Our analysis reveals that net ocean heat uptake associated with more
shortwave heat absorption and less latent heat loss is the primary driver of the buildup of MHWs in the subtropics and mid-to-high
latitudes. Reduced vertical mixing from the nonlocal portion of the KPP boundary layer scheme partially dampens the temperature
increase. In contrast, ocean heat uptake is reduced during the MHW build-up in the tropics, where reduced vertical local mixing
and diffusion cause the warming. In the subsequent decay phase, ocean heat loss to the atmosphere dominates the temperature
decrease globally. The processes leading to the buildup and decay of MHWs are similar for short and long MHWs. Different types of
MHWs with distinct driver combinations are identified within the large variability among events. Our analysis contributes to a
better understanding of MHW drivers and processes and may therefore help to improve the prediction of high-impact marine
heatwaves.

How to cite: Vogt, L., Burger, F., Griffies, S., and Frölicher, T.: Local drivers of marine heatwaves: A global analysis with an Earth system model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1832, https://doi.org/10.5194/egusphere-egu22-1832, 2022.

The extratropical meridional energy transport in the atmosphere is fundamentally intermittent in nature, having extremes large enough to affect the net seasonal transport. Here, we investigate how these extreme transports are associated with the dynamics of the atmosphere at multiple scales, from planetary to synoptic. We use ERA5 reanalysis data to perform a wavenumber decomposition of meridional energy transport in the Northern Hemisphere mid-latitudes during winter and summer. We then relate extreme transport events to atmospheric circulation anomalies and dominant weather regimes, identified by clustering 500 hPa geopotential height fields. In general, planetary-scale waves determine the strength and meridional position of the synoptic-scale baroclinic activity with their phase and amplitude, but important differences emerge between seasons. During winter, large wavenumbers (k = 2 − 3) are key drivers of the meridional energy transport extremes, and planetary and synoptic-scale transport extremes virtually never co-occur. In summer, extremes are associated with higher wavenumbers (k = 4 − 6), identified as synoptic-scale motions. We link these waves and the transport extremes to recent results on exceptionally strong and persistent co-occurring summertime heat waves across the Northern Hemisphere mid-latitudes. We show that these events are typical, in terms of dominant regime patterns associated with extremely strong meridional energy transports.

Link to pre-print: https://wcd.copernicus.org/preprints/wcd-2021-85/

How to cite: Lembo, V., Fabiano, F., Galfi, V. M., Graversen, R., Lucarini, V., and Messori, G.: Meridional energy transport extremes and the general circulation of NH mid-latitudes: dominant weather regimes and preferred zonal wavenumbers, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1884, https://doi.org/10.5194/egusphere-egu22-1884, 2022.

Natural hazards cause a plethora of impacts on society, ranging from direct impacts such as loss of lives to cascading ones such as power outages and supply shortages. Despite the severe social and economic losses of extreme events, a comprehensive assessment of their impacts remains largely missing. Existing studies tend to focus on impacts that are relatively easy to measure (e.g. financial loss, number of deaths) and commonly break down impact assessments into specific sectors (e.g. forestry, agriculture). Thus, in the absence of multi-sector impact datasets, decision-makers have no baseline information for evaluating whether adaptation measures effectively reduce impacts. This can result in blind spots in adaptation.

In recent years, text data (e.g. newspapers, social media, and Wikipedia entries) have been used to elaborate impact datasets. However, the manual extraction of impact information by human experts is a time-consuming task. To develop comprehensive impact datasets, we propose using text-mining on text documents. We developed a tool termed TM-Impacts (text-mining of natural hazard impacts), which allows us to automatically extract information on impacts by applying natural language processing (NLP) and machine learning (ML) tools to text-corpora. TM-Impacts is built upon a previous prototype application (de Brito et al., 2020).

TM-Impacts consists of three complementary modules. The first focuses on using unsupervised topic modelling to identify the main topics covered in the text. These can include not only the disaster impacts but also information on response and recovery. The second module is based on the use of hand-crafted rules and pattern matching to extract information on specific impact types (e.g. traffic disruption, power outages). The final module builds upon the second one, and it uses the resulting labelled data to train supervised ML algorithms aiming to classify unlabeled text data into impact types.

We illustrate the application of TM-Impacts using the example of the 2021 flood in Germany. This event led to more than 180 fatalities and the disruption of critical infrastructure that continued for months after the event. We built a text corpus with more than 26,000 newspaper articles published in 200 different news outlets between July and November 2021. By using TM-Impacts, we were able to detect 20 different impact types, which were mapped at the NUTS 3 scale. We also identified temporal patterns. As expected, during the onset of the event, reporting on impacts tended to focus on deaths and missing people, whereas texts published in November focused on long term impacts such as the disruption of water supply.

In conclusion, we demonstrate that TM-Impacts allows scanning large amounts of text data to build multi-sector impact datasets with a great spatial and temporal stratification. We expect the use of text-mining to become widespread in assessing the impacts of natural hazards.

de Brito, M.M., Kuhlicke, C., Marx, A. (2020) Near-real-time drought impact assessment: A text mining approach on the 2018/19 drought in Germany. Environmental Research Letters. doi:org/10.1088/1748-9326/aba4ca

How to cite: Madruga de Brito, M., Sodoge, J., Kreibich, H., and Kuhlicke, C.: Text-mining of natural hazard impacts (TM-Impacts): an application to the 2021 flood in Germany, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2001, https://doi.org/10.5194/egusphere-egu22-2001, 2022.

Under continued global warming, extreme events such as heatwaves will continue to rise in frequency, intensity, duration, and spatial extent over the next decades. Younger generations are therefore expected to face more such events across their lifetimes compared to older generations. This raises important questions about solidarity and fairness across generations that have fueled a surge of climate protests led by young people in recent years, and that underpin questions of intergenerational equity raised in recent climate litigation. However, the standard scientific paradigm is to assess climate change in discrete time windows or at discrete levels of warming, a “period” approach that inhibits quantification of how much more extreme events a particular generation will experience over its lifetime compared to another. By developing a “cohort” perspective to quantify changes in lifetime exposure to climate extremes and compare across generations, we estimate that children born in 2020 will experience a two to sevenfold increase in extreme events, particularly heatwaves, under current climate policy pledges. Our results highlight a severe threat to the safety of young generations and call for drastic emission reductions to safeguard their future.

Thiery, W., Lange, S., Rogelj, J., Schleussner, C.-F., Gudmundsson, L., Seneviratne, S.I., Frieler, K., Emanuel, K., Geiger, T., Bresch, D.N., Zhao, F., Willner, S.N., Büchner, M., Volkholz, J., Andrijevic, M., Bauer, N., Chang, J., Ciais, P., Dury, M., François, L., Grillakis, M., Gosling, S.N., Hanasaki, N., Hickler, T., Huber, V., Ito, A., Jägermeyr, J., Khabarov, N., Koutroulis, A., Liu, W., Lutz, W., Mengel, M., Müller, C., Ostberg, S., Reyer, C.P.O., Stacke, T., Wada, Y., 2021, Intergenerational inequities in exposure to climate extremes, Science, 374(6564), 158-160.

How to cite: Thiery, W. and the The kids aren't alright team: Intergenerational inequities in exposure to climate extremes, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2050, https://doi.org/10.5194/egusphere-egu22-2050, 2022.

The Southeastern South American region (SESA) is one of the AR6 WGI reference regions which is used as an illustration of the interplay between climate variability drivers and regional response. Since most of the agricultural activities take place over this region, its climate variability has a strong impact on society. The region is sensitive to extreme precipitation and puts constraints on water resource management. In recent decades, positive rainfall trends have been detected especially during austral summer. Interactions between the El Nino Southern Oscillation (ENSO) and the Antarctic Oscillation (AAO) also known as the Southern Annual mode, have been well documented indicating the crucial role of ENSO in modulating the AAO phase. In this paper, we explore the interplay between ENSO and AAO and their effect on extreme precipitation over the SESA region during austral spring and summer. Statistical approaches based on extreme value theory (EVT) are applied to daily precipitation amounts to model extreme precipitation, identifying the relative impact of ENSO and AAO. We obtained return values for different phases of ENSO and AAO. We also perform dynamical analysis for sea level pressure and wind field to relate large-scale atmospheric circulation patterns with extreme precipitation.

How to cite: Hu, X., Decremer, D., Ferranti, L., Magnusson, L., Gong, D., Pappenberger, F., and Kantz, H.: The influence of ENSO and Antarctic Oscillation on extreme precipitation over southeastern South America., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3127, https://doi.org/10.5194/egusphere-egu22-3127, 2022.

The Extreme Event Attribution field aims at evaluating the impact of global warming linked to anthropogenic emissions on extreme events. This work performs an attribution to climate change of the storm Alex, an explosive extratropical cyclone [1] that hit especially Southern France and Northern Italy at the beginning of October 2020. We apply the analogues method on sea-level pressure maps [2] to identify 30 cyclones that match the dynamical structure of Alex for two periods, the counterfactual and the factual world, namely 1950-1985 and 1985-2021, using 6-hourly ERA5 data. Results show that in the factual period the anticyclonic circulation over the North Atlantic and the cyclonic circulation over Northern Africa are deeper than in the counterfactual. Precipitation differences depict a significant increase over North Italy and the Alps. 2-meter air temperature differences consist of a positive non-uniform pattern, with a significant increase over the Alps and east of Newfoundland. We also have computed two indices in the frame of dynamical systems theory for each period: the persistence, which characterizes the average time that the sea-level pressure pattern remains stationary, and the local dimension, which gives a measure of the predictability of the storm [3]. We found that in the factual world there is a significant increase in the persistence and a modest decrease in the local dimension with respect to the counterfactual. Hence, storms like Alex are more persistent and more predictable in present-like conditions. Cyclone tracking shows that the backward trajectories of the analogues in the factual world are more meridional than in the counterfactual one, while the response for the forward trajectories is less clear. This suggests that under current conditions patterns like Alex are more wavy than in the past. Finally, using the metrics to identify explosive cyclones in [1] , we found the same number of analogues that are explosive cyclones in both periods, although in the counterfactual world they come from lower latitudes and the deepening rates are significantly larger.

References

[1]  Reale, M., M. L. Liberato, P. Lionello, J. G. Pinto, S. Salon, and S. Ulbrich, A global climatology of explosive cyclones using a multi-tracking approach, Tellus A: Dynamic Meteorology and Oceanography, 71 (1), 1611,340, 2019.

[2] Yiou, P., AnaWEGE: a weather generator based on analogues of atmospheric circulation, Geosci. Model Dev., 7, 531–543, 2014.

[3] Faranda, D., G. Messori, and P. Yiou, Dynamical proxies of North Atlantic predictability and extremes, Sci Rep, 7, 41,278, 2017.

Acknowledgments

This work is part of the EU International Training Network (ITN) European weather extremes: drivers, predictability and impacts (EDIPI). This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement N° 956396. 

How to cite: Ginesta, M., Yiou, P., Messori, G., and Faranda, D.: A framework for attributing explosive cyclones to climate change: the case study of Alex storm 2020, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3133, https://doi.org/10.5194/egusphere-egu22-3133, 2022.

Rare events, such as heat waves, floods, or hurricanes, play a crucial role in climate dynamics mainly due to the large impact they have. Predicting the occurrence of such events is thus a major challenge. 

In this talk, we introduce the relevant mathematical object for predicting a future event: the committor function is the probability that an event will occur, conditioned on the current state of the system. Computing this quantity from observations is an extremely difficult task since rare events have a very low probability of occurring and may not even have been observed in measurements made to date. Similarly, direct simulation of such events with comprehensive climate models comes at a prohibitive computational cost. Hence, rare event algorithms have been devised to simulate rare events efficiently, avoiding the computation of long periods of typical fluctuations.

The effectiveness of these algorithms strongly relies on the knowledge of a measure of how close the event of interest is to occur, called the “score function”. The main difficulty is that the optimal score function is the committor function which is exactly the quantity to be computed. Therefore, it is very natural to consider an iterative procedure where the data produced by the algorithm is used to improve the score function, which in turn improves the algorithm, and so on.

In this presentation, we propose a data-driven approach for computing the committor function, based on a Markov chain approximation of the dynamics of the system (the analogue method). We first illustrate this approach for a paradigmatic toy model of multistability for atmospheric dynamics with six variables (the Charney-Devore model). Secondly, we apply this methodology to data generated from a climate model, in order to study and predict the occurrence of extreme heat waves. In both cases, we show that it is possible to obtain fairly precise estimates of the committor function, even when few observations are available.

In the second part of the talk, we show the advantage of coupling the analogue Markov chain with a rare event algorithm. Indeed, the committor learned with the analogue Markov chain can be used as a score function performing better than user-defined score functions, as we show for the Charney-Devore model. 

This new approach is promising for studying rare events in complex dynamics: the rare events can be simulated with a minimal prior knowledge and the results are much more precise than those obtained with a user-designed score function.

How to cite: Lucente, D., Rolland, J., Herbert, C., and Bouchet, F.: Advances in rare event simulations using data-based estimation of committor functions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4021, https://doi.org/10.5194/egusphere-egu22-4021, 2022.

• The occurrence of extreme weather events has increased during the two last decades.  European heat waves are responsible for social, economic and environmental damage and are projected to increase in magnitude, frequency and duration under global warming, heightening the  interest about the contribution of different drivers. 
• By using the ERA5 Re-analysis product, we performed a two-sided composite analysis to investigate a potential relation between North Atlantic sea surface temperatures (SSTs) and the near-surface air temperature (T2m) over the European continent. Here, we show that in the presence of cold North Atlantic SSTs during summer, the distribution of European T2m shifts towards positive anomalies a few days later, increasing the likelihood for heat waves. During these events a predominant wave number three pattern in addition to regionally confined Rossby wave activity  contribute to a trough-ridge pattern in the North Atlantic-European sector. Specifically, five of 17 European heat waves within the period of 1979 to 2019 could be related to a cold North Atlantic SST event a few days in advance. In the upstream analysis we identify eleven of 17 European heat waves co-existent with cold North Atlantic SSTs. 
• In order to confirm the crucial role of North Atlantic SSTs for European heat waves, we analysed output from a coupled climate model, HadGEM3, with three different horizontal resolutions. The high-resolution run revealed the closest resemblance to the ERA5 data, suggesting that mechanisms on the mesoscales (<50 km) play a role in the relationship between North Atlantic SSTs and European T2m. Results also highlight the importance of using a climate model with a high horizontal resolution for the purpose of studying the variability of European heat waves.
• Based upon our results, conducted with ERA5 Re-analysis and HadGEM3 data, North Atlantic SSTs provide potential predictive skill of European heat waves.

How to cite: Krüger, J., Kjellsson, J., Pilch Kedzierski, R., and Claus, M.: The relation between European heat waves and North Atlantic SSTs: a two-sided composite study, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5420, https://doi.org/10.5194/egusphere-egu22-5420, 2022.

Cold and snowy spells are compound extreme events with the potential of causing high socioeconomic impacts. Gaining insight on their dynamics in climate change scenarios could help anticipating the need for adaptation efforts. We focus on winter cold and snowy spells over Italy, reconstructing 32 major events in the past 60 years from documentary sources. Despite warmer winter temperatures,  very recent cold spells have been associated to abundant, and sometimes exceptional snowfall.
Our goal is to analyse the dynamical weather patterns associated to these events, and understand whether those patterns would be more or less recurrent in different emission scenarios using an intermediate complexity model (PlaSim). Our results, obtained by considering RCP2.6, RCP4.5 and RCP8.5 end-of-century CO2 concentrations, suggest that the likelihood of analogous synoptic configurations of these extreme cold spells would grow substantially under increased emissions.

This work was supported by the ANR-TERC grant BOREAS and by the Horizon 2020 research and innovation programme XAIDA (grant agreement No 101003469)

How to cite: Pons, F., D’Errico, M., Yiou, P., Tao, S., Nardini, C., Lunkeit, F., and Faranda, D.: Present and future synoptic circulation patterns associated with cold and snowy spells over Italy, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5511, https://doi.org/10.5194/egusphere-egu22-5511, 2022.

Extreme winter cold spells in Europe have huge societal impacts. Being able to simulate worst case scenarios of such events for present and future climates is hence crucial for adaptation. Rare event algorithms have been applied to simulate extreme heatwaves. They have emphasized the role of the atmospheric circulation in such extremes. The goal of this study is to test such algorithms to extreme cold spells.
We focus on cold spells that occur in France since 1950. The analysis is based on the ERA5 reanalysis. We select cold events that have occurred for different time scales (10 days, 1 month, 3 months). We identify record shattering cold events for time scales of 1 and 3 months (in 1956 and 1963). We find that, although the frequency of extreme cold spells decreases with time, their intensity is stationary.
We applied a stochastic weather generator approach with importance sampling, to simulate the worst cold spells that could occur every year since 1950, with lengths of 1 month and 3 months. We hence simulated ensembles of worst winter cold spells that are consistent with observations. Those worst cases are slightly colder than the record shattering events, and do not yield the trend that is observed on the mean temperature. The atmospheric circulation that prevails during those events is analyzed and compared to the observed circulation during the record breaking events.

How to cite: Cadiou, C. and Yiou, P.: Simulating extreme cold spells in France with empirical importance sampling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5734, https://doi.org/10.5194/egusphere-egu22-5734, 2022.

Marine heat waves (MHWs) and cold spells (MCSs) are anomalous ocean temperature events that occur in all oceans and seas with great ecological and economic impacts. The quantification of the relative importance of marine temperature extreme events is often done through the calculation of local metrics, the majority of them not considering explicitly the spatial extent of the events. Here, we propose a ranking methodology to evaluate the relative importance of marine temperature extreme events between 1982 and 2021 within the Mediterranean basin. We introduce a metric, generically termed activity, combining the number of events, duration, intensity and spatial extent of: i) summer MHWs and ii) winter MCSs. Results at the entire Mediterranean scale show that the former dominate in the last two decades while the latter are prevalent in the 1980s and 1990s. Summers with the highest MHW activity were 2018, 2003 and 2015 and winters with the strongest MCS activity took place in 1992, 1984 and 1983. The highest MHW activity occurred in the Gulf of Lion while the highest MCS activity took place preferably in the Aegean basin. According to our proposed definition, the three strongest MHWs almost double the duration, mean intensity, and activity of the three strongest MCSs. The long-term tendency of activity shows a rapid increase for summer MHWs and a linear decrease for winter MCSs in the Mediterranean over the last four decades.

We acknowledge the financing support from FCT – JPIOCEANS/0001/2019

How to cite: Simon, A., Plecha, S., Russo, A., Teles-Machado, A., Donat, M., and Trigo, R.: Hot and Cold Marine Extreme Events in the Mediterranean over the last four decades, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6141, https://doi.org/10.5194/egusphere-egu22-6141, 2022.

Concurrent weather extremes due to a meandering Jetstream can reduce crop productivity across multiple agricultural regions. However, future changes in associated synoptic climate patterns and their agricultural impacts remain unquantified. Here we investigate the ability of coupled climate crop model simulations to reproduce observed regional production impacts and production co-variabilities across major breadbasket regions of the world. We find that although climate models accurately reproduce atmospheric patterns, they underestimate associated surface anomalies in climate models and yield covariability in crop model simulations. Model estimates of future multiple breadbasket failures are therefore likely conservative, despite a projected future intensification of wave pattern-related extremes identified regionally. Our results suggest that climate risk assessments need to account for these high-impact but deeply-uncertain hazards.

How to cite: Kornhuber, K., Lesk, C., Schleussner, C., Jägermeyer, J., Pfleiderer, P., and Horton, R.: Preferred rossby waves and risks of synchronized heatwaves and harvest failures in observations and model projections, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6300, https://doi.org/10.5194/egusphere-egu22-6300, 2022.

The occurrence of cold spells over North America leads, on average, to a zonalisation and intensification of the North Atlantic jet stream and results in an enhanced risk of extreme wind and precipitation events over Europe. Cold spells enhance low-level baroclinicity at the entrance of the North Atlantic storm track and enhance extratropical cyclogenesis next to the East coast of the United States. However, the mechanisms by which this impact propagates from the entrance to the exit of the storm track, where Europe is, remain unclear.

We investigate from a regime perspective the two-way relationship between the occurrence of cold spells over the eastern coast of North America and the North Atlantic storm track. We stratify the occurrence of cold spells over two different regime classifications of the state of the North Atlantic storm track: the first one based on more classical k-means clustering of 500hPa geopotential height, the other based on dynamical system theory. The regimes have been further characterized using diagnostics acquired from dynamical meteorology, as the E vector or the wave activity flux, and display very different patterns of Rossby wave propagation. The analysis will highlight whether the occurrence of cold spells is able to cause shifts in storm track regimes. On the other hand, if the state of the storm track remains unchanged, this would suggest that other factors rather than cold spells modulate the connection to European wind and temperature extremes.

How to cite: Riboldi, J.: A storm-track regime perspective on the connection between cold spells over North America and wet/windy extremes over Europe, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6623, https://doi.org/10.5194/egusphere-egu22-6623, 2022.

Climate change has an influence on daily weather. It translates into a heightened public perception of any type of « weird » weather. For example, it has been shown that extreme weather events are seen as pointing towards the reality of climate change. These perceived attributions are not only related to heatwaves, but also to cold spells (Capstick and Pigeon (2014)), and floods (Taylor et al (2014)).

Extreme events however represent only a subset of the weather distribution experienced by the public. Another manifestation of « weird » weather is the succession of very different types of weather in a short period of time, e.g. two following days with a 10°C difference. While this is widely regarded as another manifestation of climate change by the general public, there are only a few studies exploring short timescale weather variability. For example, Cattiaux et al (2015) have found a projected increase in diurnal and interdiurnal variations of European summer temperatures in CMIP5 simulations.

Here, we use the ERA5 reanalyses (1950-2020) over Europe to study observed diurnal and interdiurnal (2, 3, 5 and 7 days) variations of temperature. We focus on extremes (below the 5th percentile and above the 95th percentile of the distribution of temperature differences) for all seasons and independently for each season and calculate trends. While the general result is that, contrarily to popular beliefs, the diurnal and interdiurnal variations have not increased in the observational periods, we show regional differences over Europe and discuss potential explanations for these differences. 

References:
Capstick, S.B., Pidgeon, N.F. Public perception of cold weather events as evidence for and against climate change. Climatic Change 122, 695–708 (2014). https://doi.org/10.1007/s10584-013-1003-1
Cattiaux, J., Douville, H., Schoetter, R., Parey, S. and Yiou, P. (2015), Projected increase in diurnal and interdiurnal variations of European summer temperatures. Geophys. Res. Lett., 42: 899– 907. doi: 10.1002/2014GL062531.
Taylor, A., de Bruin, W.B. and Dessai, S. (2014), Climate Change Beliefs and Perceptions of Weather-Related Changes in the United Kingdom. Risk Analysis, 34: 1995-2004. https://doi.org/10.1111/risa.12234

How to cite: Jezequel, A. and Fararanda, D.: Is the weather getting "weirder"?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7381, https://doi.org/10.5194/egusphere-egu22-7381, 2022.

The Indian Summer Monsoon (ISM) and the East Asian Summer monsoon (EASM) are two integral components of the Asian Summer Monsoon system, largely influencing the agro-based economy of the densely populated southern and eastern parts of Asia. In our study, we use a complex network based approach to investigate the spatial coherence of extreme precipitation in the Asian Summer Monsoon region and gain a deep insight into the complex nature of the interaction between the ISM and the EASM. We identify two dominant modes of ISM-EASM interaction – (a) a southern mode connecting onset of the ISM over the Arabian Sea and southern India in June to the onset of Meiyu over south-eastern China, i.e., lower and middle reaches of the Yangtze river valley, and (b) a northern mode relating the occurrence and intensity of rainfall over the northern and central parts of India to that in northern China during July. Through determination of specific times of high synchronization of extreme precipitation, we distinctly identify the particular large-scale atmospheric circulation and moisture transport patterns associated with each mode. Thereafter, we investigate the role of the different components of the tropical intraseasonal oscillations, such as the Madden-Julian Oscillation and the boreal summer intraseasonal oscillation, in the intraseasonal variability of the relationship between the ISM and the EASM.

This work is funded by the CAFE project which 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., Su, Z., Boers, N., Kurths, J., Marwan, N., and Pappenberger, F.: Interrelation between the Indian and East Asian Summer Monsoon: A complex network-based approach, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8626, https://doi.org/10.5194/egusphere-egu22-8626, 2022.

The Pacific Northwest is characterized by a temperate climate with mild to warm summers, yet in late June 2021, the region was ravaged by extreme heat and ensuing wildfires. With local daily maximum temperatures 20 °C above the long term mean, the occurrence of such a brute heatwave makes it imperative to understand the underlying physical processes. Using the Community Earth System Model, we simulate this exceptional event and disentangle its thermodynamic and dynamic drivers. A factorial experimental design based on the ExtremeX framework is employed, in which the mid and upper-tropospheric circulation and soil moisture are either prescribed using reanalysis (ERA5) data, or calculated interactively. With this setup, the lower troposphere can always respond to land and ocean surface fluxes. Our results indicate that, despite widespread drought conditions in the analysis region (including the metropolitan areas of Portland, Seattle and Vancouver) and surroundings, the dynamic contribution far exceeded the effect of anomalous soil moisture. We further disentangle the soil moisture contribution into initial and event-driven, and find that precipitation in the first half of June 2021 prevented even higher near-surface temperatures by weakening the initial effect. Overall, the analysis highlights the role of the anticyclone that governed the large-scale circulation, and whose intensity during summertime and within 45°N–60 °N surpasses any other event in recent decades. As such, this heatwave presents an opportunity to investigate whether our Earth System Model of choice is capable of generating similarly extreme heat at large spatial scales on its own, i.e. with fully interactive winds. While the mean intensity of hot anticyclonic summer events over land (45°N–60 °N) is underestimated with respect to our reference simulation with prescribed circulation, the model portrays stronger variability with an interactive atmosphere and hence generates heatwaves that rival and even surpass the large-scale temperature anomalies of the Pacific Northwest 2021 event. Our investigation also points to strong temperature anomalies aloft, which we track back in time with a Lagrangian trajectory model driven by ERA5 data. By doing so, we find evidence for intense latent heating of the air that would later be part of the anticyclone, and mixed into the unusually deep atmospheric boundary layer. We further demonstrate that in the absence of anthropogenic climate change, an otherwise identical heatwave would not have reached such extreme temperatures. Altogether, this study shows that for the right atmospheric configuration and fuelled by our changing climate, unprecedented heat may be unleashed even in regions traditionally considered devoid of excessive heatwaves.

How to cite: Schumacher, D. L., Hauser, M., and Seneviratne, S. I.: Mechanisms and drivers of the 2021 Pacific Northwest heatwave, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9156, https://doi.org/10.5194/egusphere-egu22-9156, 2022.

Intense Mediterranean cyclones (IMC) are weather systems that have a high potential for destruction in the densely populated coastal areas around the Mediterranean sea and they cause high risk situations, such as flash floods and large-scale floods with significant impacts on human life and built environment. The aim of the study is to analyse and attribute future changes in IMC under different future forcings and to assess the effect of horizontal model resolution by comparing hydrostatic- versus convection-permitting models. Following a non-linear approach, we explore IMC events that are connected to anomalous atmospheric patterns. First, the analogs search is performed on ERA5 and historical simulations, so as to use the latter as a control run for future projections.  We then examine clusters and trends in the dates of analogs and study their predictability properties in the attractor space (e.g., local dimension and persistence). Then we explore how the trajectories of the precursors of the observed extreme event, emerging from the analog approach, may eventually lead to an IMC event in each available simulation. In this way, we can evaluate the probability of obtaining an observed event, given an initial condition. Finally, we evaluate the physical factors possibly connected to the change of probability of the event.

How to cite: Alvarez-Castro, M. C., Gualdi, S., Faranda, D., Ribera, P., Gallego, D., and Peña-Ortiz, C.: The response of intense Mediterranean cyclones to climate change, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9257, https://doi.org/10.5194/egusphere-egu22-9257, 2022.

Climate change is one of the most urgent challenges that humankind confronts nowadays. In order to mitigate its effects, the European Union aims to be climate-neutral, i.e. set the Greenhouse Gas (GHG) emissions to zero, by 2050. In this context, renewable energies (REs) play a key role: on the one hand their development and extensive usage can help to reduce the GHG emissions, on the other hand substantial local changes in atmospheric conditions could modify, for better or for worse, their efficiency. Extreme atmospheric events, in particular, can badly affect the efficiency of the RE infrastructures, preventing them from working or even damaging them. In this work, we focus on wind energy off shore, on the European panorama, with the purpose of estimate the behavior of extreme high winds, over the period 1950-2020, and their impact on wind energy availability. Indeed, the potential wind power production, according to the working regimes of a wind turbine, depends only on the wind speed and, over a certain wind speed threshold, called cut-off speed (25 m s^-1), the turbine stops working. By using 6-hourly ERA5 reanalysis data-set and convection permitting simulations, covering the European domain and a period from 1950 to 2020 and from 2000 to 2009 respectively, we analysed the 100 m wind speed over the cut-off threshold and its relation with the geopotential height at 500 hPa, in order to investigate the large-scale weather regimes related to these extreme events. We focused especially on five regions, where high winds flow more frequently: United Kingdom, Denmark, Greece, and the areas off the south of France and north of Spain. By using the Mann-Kendall test, we analysed the trends in the occurrence of extreme events, and we detected significant increasing trends in large areas of the regions selected, particularly during the winter period (DJF). Finally, considering only the events over the 99^th percentile, we found that they are often concurrently with storms, and, by means of the K-means clustering algorithm, we identified the different weather regimes at which they occur.

How to cite: Rapella, L., Faranda, D., and Gaetani, M.: Climate Change on Extreme Winds Already Affects Wind Energy Availability in Europe, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9634, https://doi.org/10.5194/egusphere-egu22-9634, 2022.

The intensity and frequency of persistent heat waves and droughts have increased over the last few decades. While some of the changes may be attributed to natural variability, it is a known reality that climate change contributes to these tendencies. According to the Fifth Assessment Report of the IPCC, these anomalies are projected to be accelerated and impact humans, ecology, agricultural events, and natural systems.

Understanding the spatiotemporal structure of heat waves is crucial to deciding what environmental change will affect the above-mentioned impacts. In this study, the temporal autocorrelation of near-surface temperature and 850 hPa geopotential height from daily ERA-5 reanalysis data is examined. The focus is on the period from 1979 to 2019. To explore this 41-year long dataset, spatio-temporal trend analysis is also conducted along with autocorrelation. The trends are inspected under 3, 5, and 7-day lag autocorrelations.

In this context, the summer of 2003 shows a very high autocorrelation of geopotential height over central Europe in this analysis, which is consistent with a persistent heat wave that resulted in a death toll. Along with the yearly analyzed data, the trends are calculated both as a whole and divided into intervals. The trend analysis yields high results that cluster around Northern Africa, the Middle East, Middle China, and Middle Russia in the summer season. Furthermore, in the winter season, Siberia, Middle Africa, and the northern part of South America reflect high trends.

How to cite: Gözlet, M. S., Kjellsson, J., Savita, A., and Latif, M.: Recent changes in persistence over Europe and the World in reanalysis dataset, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10586, https://doi.org/10.5194/egusphere-egu22-10586, 2022.

Under the ongoing climate change, extreme weather events are becoming more prolonged, intense, and frequent; and this trend is expected to continue in a future warmer climate. Several studies have found that the synoptic atmospheric circulation at the time of the event is the main contributing factor in most cases. Moreover, they are shaped by slower processes, including sea-surface temperature and soil moisture, in turn influenced by the history of preceding weather patterns, and by the background climate. The separation of influencing components is exploited by the storyline approach, where an atmosphere model is nudged toward the observed dynamics using different climate boundary conditions. Thus, the storyline approach focuses on the less uncertain thermodynamic influence of climate on extreme events, disregarding the somewhat controversial dynamical changes. This approach provides a very efficient way of making the impacts of climate change more tangible to experts and non-experts alike as events fresh in the people's memory are reproduced in different plausible climates with just moderate computational resources.

Spectral nudging experiments have been run with two coupled climate models, AWI-CM-1 and AWI-CM-3. In these simulations, the large-scale free-troposphere dynamics are constrained toward ERA5 data and the model is run for different boundary conditions. Here, the ocean and sea-ice state are consistently simulated, unlike previous studies which employed atmosphere-only models. Our setups reasonably reproduce daily to seasonal observed anomalies of relevant unconstrained parameters, including near-surface temperature, soil moisture or cloud cover. In particular, our configurations showed satisfactory skills in reproducing two different extreme events: the July 2019 European heat wave, and the July 2021 European extreme rainfall. Therefore, this methodology has been applied to study several extreme events in different climates. To do so, nudged simulations are branched off CMIP6 historical and scenario simulations of the same model. For the particular July 2021 extreme rainfall event, we have run five ensemble members for AWI-CM-1-1-MR for dynamical conditions from 1st January 2017 to 31st July 2021 in pre-industrial, present-day, +2K, and +4K climates. These simulations are complemented with similar experiments for AWI-CM-3. 

The most outstanding finding of these studies is a global warming amplification associated with some events, which exacerbates their exceptionality, especially in a high emission scenario.

How to cite: Sánchez Benítez, A., Jung, T., Athanase, M., Pithan, F., and Goessling, H.: Storylines of past and plausible future climates for recent extreme weather events with coupled climate models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11389, https://doi.org/10.5194/egusphere-egu22-11389, 2022.

Climate change exhibits one of its strongest and shocking effects through extreme precipitation events. Extreme convective precipitation events are getting more intense and more frequent and their attribution to global warming is confirmed by recent studies in many regions of the world. During October the 4^th and 5^th a Nord-Atlantic trough entering the western Mediterranean favored the formation of deep convective systems feeded by the wet and warm prefrontal flow. One of them built up over the Ligurian Gulf on the 4^th. Sustained by long-lasting interaction of large scale conditions and local forcings, the V-shape storm persisted over 24 hours locally accumulating more than 900 mm of rain. The event exceeded local and European precipitation records and caused landslides and flash-floods. In this study we try to objectively link the event to climate change through an extreme value theory analysis. This has been carried out through rain-gauge observations over Liguria, available continuously from 1960 for the fall season. The climate conditions of the event are compared to a pre-industrial period 1.2°C cooler than the present days. The Euro-CORDEX 12km resolution ensemble has been also used to confirm the event attribution to global warming. 

How to cite: Di Sante, F., Pichelli, E., Coppola, E., Vautard, R., Scussolini, P., Soubeyroux, J.-M., and Dubuisson, B.: Attribution of the fall 2021 extreme precipitation event over Italian region of Liguria, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12152, https://doi.org/10.5194/egusphere-egu22-12152, 2022.

A more accurate characterization of S2S extremes may result in great positive societal impact. Featurized S2S forecasts in the form of risk or extreme indices will aid in disaster response (especially for drought and flood events), inform disease outbreaks and heatwave onset, persistence, and decay. In this study, we identify a set of ECMWF-derived extreme weather indices that have spatio-temporal windows of opportunity for better-than-climatology skill. We report on the correlation between ECMWF-derived indices and ground-truth values.  The selected indices can be calculated directly form probabilistic daily forecasts, or alternatively, by training specialized ML-models to process ensembles in a multi-task learning setup. Our goal is to find better approaches to communicate S2S climate risk by deploying a set of ECMWF-derived climate forecast products.

How to cite: Patel, Z., Baloyi, G., Watson, C., Zaytar, A., Zadrozny, B., Civitarese, D., Makhanya, S., and Vos, E.: S2S Extreme Weather Featurization: A Global Skill Assessment Study, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12461, https://doi.org/10.5194/egusphere-egu22-12461, 2022.

How to cite: Minjares, M., Yiou, P., Serra, I., Barreiro, M., and Corral, Á.: Extreme Value Analysis of Madden-Julian Oscillation Events, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12484, https://doi.org/10.5194/egusphere-egu22-12484, 2022.

Record-breaking natural hazards occur regularly throughout the world, leading to a variety of impacts [1]. According to the WMO, since 1970 there were more than 11000 reported disasters attributed to these hazards globally, with just over 2 million deaths and US$ 3.64 trillion in losses [2]. From 1970 to 2019, weather, climate and water hazards accounted for 50% of all disasters, 45% of all reported deaths and 74% of all reported economic losses [2]. Droughts and heatwaves are both included in the top 4 disasters in terms of human losses [2], with uneven impacts throughout the world and a high likelihood that anthropogenic climate forcing will increase economic inequality between countries [3].

Nowadays there is strong evidence that droughts and heatwaves are at times synergetic and that their combined occurrence is largely caused by land-atmosphere feedbacks [4]. In fact, increasing trends of Compound Dry and Hot (CDH) events have been observed in both South America [5,6] and Europe [7,8], some of them with aggravated impacts. Specifically, the severe 2020 Pantanal extreme fire season (Brazil) resulted from the interplay between extreme and persistent temperatures (maximum temperatures 6 ºC above-average) and long-term soil dryness conditions [6]. Similarly, in the Iberian Peninsula, CDH events were shown to have an influence on the dramatic 2017 fire season [9] and also on crop losses [8]. Moreover, future climate projections suggest that CDH conditions are expected to become more common in a warming climate [4]. Therefore, it is very important to address weather events in a compound manner, identifying synergies, driving mechanisms and dominant atmospheric modes controlling single and combined hazards.

[1] IPCC, 2021: Climate Change 2021: The Physical Science Basis. Contribution of WGI to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte  V. et al., (eds.)]. Cambridge University Press. 

[2] WHO, 2021. Weather-related disasters increase over past 50 years, causing more damage but fewer deaths, https://public.wmo.int/en/media/press-release/weather-related-disasters-increase-over-past-50-years-causing-more-damage-fewer

[3] Diffenbaugh N.S., Burke M. (2019) Global warming has increased global economic inequality, PNAS, 116, 20, 9808-9813

[4] Zscheischler J. et al. (2018). Future climate risk from compound events. Nat. Clim. Change, 8, 469–477.

[5] Geirinhas J.L. et al. (2021). Recent increasing frequency of compound summer drought and heatwaves in Southeast Brazil. Environ. Res.  Lett., 16(3).

[6] Libonati R. et al (2022) Assessing the role of compound drought and heatwave events on unprecedented 2020 wildfires in the Pantanal, Environ. Res. Lett. 17 015005.

[7] Geirinhas J.L. et al. (2020) Heat-related mortality at the beginning of the twenty-first century in Rio de Janeiro, Brazil. Int. J. Biometeorol., 64, 1319–1332

[8] Russo A. et al. (2019) The synergy between drought and extremely hot summers in the Mediterranean. Environ. Res. Lett., 14, 014011

[9] Ribeiro A.F.S. et al. (2020) Risk of crop failure due to compound dry and hot extremes estimated with nested copulas. Biogeosciences, 17, 4815–4830

[10] Turco M. et al. (2019) Climate drivers of the 2017 devastating fires in Portugal. Sci. Rep., 9, 1

This work was supported by Fundação para a Ciência e a Tecnologia (Portugal) under projects PTDC/CTA-CLI/28902/2017, JPIOCEANS/0001/2019 and FCT- UIDB/50019/2020 –IDL.

How to cite: Russo, A., Libonati, R., Geirinhas, J. L., Ramos, A. M., Silva, P. S., Sousa, P. M., DaCamara, C. C., Miralles, D. G., and Trigo, R. M.: Complex interactions of extreme events in Southern Europe and Brazil: a compound event perspective, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12508, https://doi.org/10.5194/egusphere-egu22-12508, 2022.

Eddy saturation describes the nonlinear mechanism in geophysical flows whereby, when average conditions are considered, direct forcing of the zonal flow increases the eddy kinetic energy, while the energy associated with the zonal flow does not increase. We present a minimal baroclinic model that exhibits complete eddy saturation. Starting from Phillips’ classical quasi-geostrophic two-level model on the beta channel of the mid-latitudes, we derive a reduced order model comprising of six ordinary differential equations including parameterised eddies. This model features two physically realisable steady state solutions, one a purely zonal flow and one where, additionally, finite eddy motions are present. As the baroclinic forcing in the form of diabatic heating is increased, the zonal solution loses stability and the eddy solution becomes attracting. After this bifurcation, the zonal components of the solution are independent of the baroclinic forcing, and the excess of heat in the low latitudes is efficiently transported northwards by finite eddies, in the spirit of baroclinic adjustment.

How to cite: Kobras, M., Ambaum, M. H. P., and Lucarini, V.: Eddy saturation in a reduced two-level model of the atmosphere, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-230, https://doi.org/10.5194/egusphere-egu22-230, 2022.

One of the most fascinating, and surprising, aspects of stratified turbulence is the spontaneous formation of density staircases, consisting of layers with nearly constant density, separated by interfaces with large density gradients. Within a staircase, there are two key lengthscales: the layer depth, and the interface thickness. Density staircases appear in regions of the ocean where the overall stratification is stable, and can be induced experimentally by stirring a fluid with a stable salt gradient. Staircases also appear as a result of double diffusive convection, in both oceanic and astrophysical contexts. Turbulent transport through staircases is enhanced compared to non-layered regions, so understanding their dynamics is crucial for modelling salt and heat transport.

Progress has been made numerically and experimentally, but the fundamental aspects of the problem are not yet fully understood. One leading theory is the Phillips Effect: layering occurs due to the dependence of the turbulent density flux on the density gradient. If the flux is a decreasing function of the gradient for a finite range of gradients, then negative diffusion causes perturbations to grow into systems of layers and interfaces.

An important extension of the Phillips theory is by Balmforth, Llewellyn-Smith and Young [J. Fluid Mech., 335:329-358, 1998], who developed a k-ε style model of stirred stratified flow in terms of horizontally averaged energy and buoyancy fields. These fields obey turbulent diffusion equations, with fluxes depending on a mixing length. The parameterisation of this lengthscale is key to the model, as it must pick out both layer and interface scales. This phenomonological model parameterises terms based on dimensional arguments, and neglects diffusion for simplicity. This model produces clear density staircases, which undergo mergers where two interfaces combine to form one. Layers take up the interior of the domain, while edge regions on either side expand inwards at a rate of t^1/2 , removing layers from the outside in. Eventually the edge regions fill the entire domain, so the long time behaviour of the layers cannot be seen.

We present a similar model for stirred stratified layering derived directly from the Boussinesq equations, including molecular and viscous diffusion, so the model can be tailored to specific conditions to make realistic predictions. We show that the layered  region can evolve indefinitely through mergers, by taking fixed-buoyancy boundary conditions to prevent the expansion of the edge regions. We investigate the effects of diffusion on layer formation and evolution, finding that it acts to stabilise the system, both by decreasing the range of buoyancy gradients that are susceptible to the layering instability, and by decreasing the growth rates of perturbations. The lengthscale of the instability also increases, with larger viscosities and diffusivities producing deeper layers with less sharp interfaces.

This model can be used as a more general framework for layering phenomena. Extending to equations for energy, temperature and salinity can model double diffusive layering. More general parameterisations for the fluxes allow it to be adapted to other settings, including potential vorticity staircases in atmospheres and E×B staircases in plasmas.

How to cite: Pruzina, P., Hughes, D., and Pegler, S.: Nonlinear Multiscale Modelling of Layering in Turbulent Stratified Fluids, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-269, https://doi.org/10.5194/egusphere-egu22-269, 2022.

Unstable periodic orbits (UPOs) are a valuable tool for studying chaotic dynamical systems, as they allow one to distill their dynamical structure. We consider here the Lorenz 1963 model with the classic parameters' value. We investigate how a chaotic orbit can be approximated using a complete set of UPOs up to symbolic dynamics' period 14. At each instant, we rank the UPOs according to their proximity to the position of the orbit in the phase space. We study this process from two different perspectives. First, we find that longer period UPOs overwhelmingly provide the best local approximation to the trajectory. Second, we construct a finite-state Markov chain by studying the scattering of the orbit between the neighbourhood of the various UPOs. Each UPO and its neighbourhood are taken as a possible state of the system. Through the analysis of the subdominant eigenvectors of the corresponding stochastic matrix we provide a different interpretation of the mixing processes occurring in the system by taking advantage of the concept of quasi-invariant sets.

How to cite: Maiocchi, C. C., Lucarini, V., and Gritsun, A.: Decomposing the Dynamics of the Lorenz 1963 model using Unstable Periodic Orbits: Averages, Transitions, and Quasi-Invariant Sets, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1171, https://doi.org/10.5194/egusphere-egu22-1171, 2022.

On a synoptic time scale, the northern mid-latitudes weather is dominated by the influence of the eddy-driven jet stream and its variability. The usually zonal jet can become mostly meridional during so-called blocking events, increasing the persistence of cyclonic and anticyclonic structures and therefore triggering extremes of temperature or precipitations. During those events, the jet takes unusual latitudinal positions, either northerly or southerly of its mean position. Previous research proposed theoretically derived 1D models of the jet stream to represent the dynamics of such events. Here, we take a data-driven approach using ERA5 reanalysis data over the period 1979-2019 to investigate the variability of the eddy-driven jet latitudinal position and wind speed variability. We show that shifts of the jet latitudinal position occur on a daily time scale and are preceded by a strong decrease of the jet zonal wind speed 2-3 days prior to the shift. We also show that the dynamics of the jet zonal wind speed can be modelled by a non-linear oscillator with stochastic perturbations. We combine those two results to propose a simple 1D model capable of representing the statistics and dynamics of blocking events of the eddy-driven jet stream. The model is based on two stochastic coupled non-linear lattices representing the jet latitudinal position and zonal wind speed. Our model is able to reproduce temporal and spatial characteristics of the jet and we highlight a potential link between the propagation of solitary waves along the jet and the occurrence of blocking events.

How to cite: Noyelle, R., Faranda, D., and Yiou, P.: Modeling the Northern eddy-driven jet stream position and wind speed variability with stochastic coupled non-linear lattices, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1250, https://doi.org/10.5194/egusphere-egu22-1250, 2022.

We run a moist shallow water model with stochastic mesoscale forcing, to simulate the effects of mesoscale forcing on exciting large-scale flow structures. In previous work, we showed how the mesoscale forcing excites a classical -5/3 eddy kinetic energy upscale cascade to planetary scales where the linear tropical modes such as Rossby, Yanai, Intertial Gravity, and Kelvin waves form. In this work, we focus on the arising zonal mean flow.

We present results from ensembles of a few hundred simulations indicating multiple-equilibria in the tropical flow, once latent heat release passes a certain threshold in the first 1000 days. Runs up to one hundred thousand days confirm these results and show abrupt transitions in the dry and moist shallow-water turbulence lasting several thousand days. We will discuss the transient nature of the mean flow and suggest a possible new mechanism for the transition of the wind at the equator to super-rotation in a moist environment.

How to cite: Schröttle, J. and Harnik, N.: Spontaneous transitions between sub- and superrotation in dry and moist shallow-water turbulence on the sphere, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1307, https://doi.org/10.5194/egusphere-egu22-1307, 2022.

Glacial-interglacial cycles constitute large natural variations in Earth's climate. The Mid-Pleistocene Transition (MPT) marks a shift of the dominant periodicity of these climate cycles from ~40 to ~100 kyr. Ramping with frequency locking is a promising mechanism to explain the MPT, combining an increase in the internal period with lockings to an external forcing. We identify the strength of positive feedbacks as a key parameter to induce increases in the internal period and allow ramping with frequency locking. Using the calcifier-alkalinity model, we simulate changes in periodicity similar to the Mid-Pleistocene Transition through this mechanism. However, the periodicity shift occurs up to 10 Million years after the change in the feedback strength. This result puts into question the assumption that the cause for the MPT must have operated around the same time as the observed periodicity shift.

How to cite: Omta, A. W., Shackleton, J., Follows, M., and Thomas, P.: The Mid-Pleistocene Transition: A delayed response to an increasing positive feedback?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1514, https://doi.org/10.5194/egusphere-egu22-1514, 2022.

Heat waves result from large-scale stationary waves and have major impacts on the economy and mortality. However, the dynamical processes leading to and maintaining heat waves are still not well understood. Here we use a nonlinear stationary wave model (NSWM) to examine the role played by anomalous stationary waves and how they are forced during heat waves. We will discuss heat waves in Europe and Asia. We show that the NSWM can successfully reproduce the main features of the observed anomalous stationary waves in the upper troposphere. Our results indicate that the dynamics of heat waves are nonlinear, and transient momentum fluxes are the primary drivers of the observed anomalous stationary waves. We will also discuss the role of anomalous SSTs in influencing heat waves.

How to cite: Franzke, C. and Ma, Q.: The role of transient eddies and diabatic heating in the maintenance of heat waves: a nonlinear quasi-stationary wave perspective, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1571, https://doi.org/10.5194/egusphere-egu22-1571, 2022.

Recent observationally based studies indicate that the Atlantic Meridional Overturning Circulation (AMOC) and the Greenland Ice Sheet (GIS) may be approaching critical thresholds or tipping points, although the timing is uncertain. The connection between both Greenland meltwater fluxes and anthropogenic greenhouse gas emissions and their impact on the future state of the AMOC is also uncertain. Here we investigate the role of ocean vertical mixing within the interior and surface boundary layer (the K-Profile Parameterization (KPP)) on past millennial scale climate variability in a coupled climate model. Previous studies have demonstrated a sensitivity of the period of millennial scale ice age oscillations to the KPP scheme. Here we show that small changes in the profiles of vertical mixing under ice age boundary conditions can drive the AMOC through a Hopf bifurcation and result in the appearance of millennial-scale AMOC oscillations. This has implications on whether changes in tidal energy dissipation in the coastal and deep ocean are important for modelling past climate variability. More importantly, the same changes in ocean vertical mixing can impact the stability and hysteresis behaviour of the modern AMOC under freshwater input to the North Atlantic as well as leading to abrupt transitions in AMOC strength under a doubling of carbon dioxide concentrations in the atmosphere. We show how understanding the sensitivity of the AMOC to ocean vertical mixing parameterizations used in coupled Earth System models may be important for constraining future climate tipping points.

How to cite: Vettoretti, G., Jochum, M., and Ditlevsen, P.: Modelling Abrupt Transitions in Past Ocean Circulation to Constrain Future Tipping Points, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1988, https://doi.org/10.5194/egusphere-egu22-1988, 2022.

The directional dependencies of different climate indices are explored using the Liang-Kleeman information flow in order to disentangle the influence of certain regions over the globe on the development of low-frequency variability of others. Seven key indices (the sea-surface temperature in El-Niño 3.4 region, the Atlantic Multidecadal Oscillation, the North Atlantic Oscillation, the North Pacific America pattern, the Arctic Oscillation, the Pacifid Decadal Oscillation, the Tropical North Atlantic index), together with three local time series located in Western Europe (Belgium), are selected. The analysis is performed on time scales from a month to 5 years by using a sliding window as filtering procedure.

A few key new results on the remote influence emerge: (i) The Arctic Oscillation plays a key role at short time (monthly) scales on the dynamics of the North Pacific and North Atlantic; (ii) the North Atlantic Oscillation is playing a global role at long time scales (several years); (iii) the Pacific Decadal Oscillation is indeed slaved to other influences; (iv) the local observables over Western Europe influence the variability on the ocean basins on long time scales. These results further illustrate the power of the Liang-Kleeman information flow in disentangling the dynamical dependencies.

How to cite: Vannitsem, S. and Liang, X. S.: Dynamical dependencies at monthly and interannual time scales in the Climate system: Study of the North Pacific and Atlantic regions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1994, https://doi.org/10.5194/egusphere-egu22-1994, 2022.

The rise of the global sea-level due to the melting of the Greenland ice-sheet poses one of the biggest threats to human society in the 21st century (IPCC, 2021). The Greenland ice sheet has been hypothesized to exhibit multiple stable states with tipping point behavior when crossing specific thresholds of the global mean temperature (Robinson et al., 2012). In regards to the desultory efforts to reduce the global emissions it becomes more and more unlikely to reach the 1.5°C goal by the end of the century and a crossing of the tipping threshold for the Greenland ice sheet becomes inevitable. First early-warning signals of a possible transition have already been found (Boers&Rypdal, 2021). However, it is known that a short-term overshooting of a critical threshold is possible without prompting a change of the system state (Ritchie et al., 2021). Using a complex ice sheet model, we investigate the effects of different carbon-capture scenarios after crossing the tipping threshold for the Greenland ice sheet. We are able to sketch a stability diagram for a number of emission scenarios and show that temporarily overshooting the temperature threshold for Greenland might be quasi-irreversible for some of the emission scenarios.

IPCC, 2021: Summary for Policymakers. In: Climate Change 2021: The Physical Science Basis. Contribution of
Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-
Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M.
Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)].
Cambridge University Press. In Press.

Robinson, A., Calov, R. & Ganopolski, A. Multistability and critical thresholds of the Greenland ice sheet. Nature Clim Change 2, 429–432 (2012).

Boers, N. & Rypdal, M. Critical slowing down suggests that the western Greenland Ice Sheet is close to a tipping point. PNAS 118, (2021).

Ritchie, P. D. L., Clarke, J. J., Cox, P. M. & Huntingford, C. Overshooting tipping point thresholds in a changing climate. Nature 592, 517–523 (2021).

How to cite: Bochow, N.: Overshooting the tipping point threshold for the Greenland ice-sheet using a complex ice-sheet model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2353, https://doi.org/10.5194/egusphere-egu22-2353, 2022.

The Earth’s climate has experienced numerous abrupt and critical transitions during its long history. Such transitions are evidenced in precise, high-resolution records at different timescales. This type of evidence suggests the possibility of identifying a hierarchy of past critical events, which would yield a more complex perspective on climatic history of the than the classical saddle-node two-dimension representation of tipping points. Such a context allows defining a tipping, or dynamical, landscape (Lucarini and Bódai, 2020), similar to the epigenetic landscape of Waddington (1957).

To illustrate a richer structure of critical transitions, we have analyzed 3 key high-resolution datasets covering the past 66 Ma and provided evidences of abrupt transitions detected with the augmented Kolmogorov-Smirnov test and a recurrence analysis (Bagniewski et al., 2021). These time series are the CENOGRID benthic d¹⁸O and d¹³C (Westerhold et al., 2020), the U1308 benthic d¹⁸O, d¹³C and the d¹⁸bulk carbonate (Hodell and Channell, 2016), and the NGRIP d¹⁸O (Rasmussen et al., 2014) records. The aim was to examine objectively the observed visual evidence of abrupt transitions and to identify among them the key thresholds indicating regime changes that differentiate among major clusters of variability. This identification is followed by establishing a hierarchy in the observed thresholds organized through a domino-like cascade of abrupt transitions that shaped the Earth’s climate system over the past 66 Ma.

This study is supported by the H2020-funded Tipping Points in the Earth System (TiPES) project.

References

Bagniewski, W., Ghil, M., and Rousseau, D. D.: Automatic detection of abrupt transitions in paleoclimate records, Chaos, 31, https://doi.org/10.1063/5.0062543, 2021.

Hodell, D. A. and Channell, J. E. T.: Mode transitions in Northern Hemisphere glaciation: co-evolution of millennial and orbital variability in Quaternary climate, Clim. Past, 12, 1805–1828, https://doi.org/10.5194/cp-12-1805-2016, 2016.

Lucarini, V. and Bódai, T.: Global stability properties of the climate: Melancholia states, invariant measures, and phase transitions, Nonlinearity, 33, R59–R92, https://doi.org/10.1088/1361-6544/ab86cc, 2020.

Rasmussen, S. O., Bigler, M., Blockley, S. P., et al.: A stratigraphic framework for abrupt climatic changes during the Last Glacial period based on three synchronized Greenland ice-core records: refining and extending the INTIMATE event stratigraphy, Quat. Sci. Rev., 106, 14–28, https://doi.org/10.1016/j.quascirev.2014.09.007, 2014.

Waddington, C. H.: The strategy of the genes., Allen & Unwin., London, 1957.

Westerhold, T., Marwan, N., Drury, A. J., et al.: An astronomically dated record of Earth’s climate and its predictability over the last 66 million years, Science, 369, 1383-+, https://doi.org/10.1126/science.aba6853, 2020.

How to cite: Rousseau, D.-D., Lucarini, V., Bagniewski, W., and Ghil, M.: Cascade of abrupt transitions in past climates, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2396, https://doi.org/10.5194/egusphere-egu22-2396, 2022.

The Atlantic Meridional Overturning Circulation (AMOC) transports warm, saline water towards the northern North Atlantic, contributing substantially to the meridional heat transport in the climate system. Measurements of the Atlantic freshwater divergence show that it may be in a bistable state and hence subject to collapsing under anthropogenic forcing. We aim at computing the probability of such a transition. We focus on timescales of the century and on temporary collapses of the AMOC. Using simulated data from an idealized stochastic AMOC model, where forcing and white noise are applied via a surface freshwater flux, we compute the transition probabilities versus noise and forcing amplitudes.

Such transitions are very rare and simulating long-enough trajectories in order to gather sufficient statistics is too expensive. Conversely, rare-events algorithms like TAMS (Trajectory-Adaptive Multilevel Sampling) encourage the transition without changing the statistics. In TAMS, N trajectories are simulated and evaluated with a score function; the poorest-performing trajectories are discarded, and the best ones are re-simulated.

The optimal score function is the committor function, defined as the probability that a trajectory reaches a zone A of the phase space before another zone B. Its exact computation is in general difficult and time-consuming. In this presentation, we compare data-driven methods to estimate the committor. Firstly, the Analogues Markov Chain method computes it from the transition matrix of a long re-simulated trajectory. The K-Nearest Neighbours method relies on an existing pool of states where the committor function is already known to estimate it everywhere. Finally, the Dynamical Modes Decomposition method is based on a Galerkin approximation of the Koopman operator. The latter is the most efficient one for the AMOC model when using adaptive dimensionality reduction of the phase space.

How to cite: Jacques-Dumas, V., Dijkstra, H., and van Westen, R.: Data-driven estimation of the committor function for an idealised AMOC model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2689, https://doi.org/10.5194/egusphere-egu22-2689, 2022.

How to cite: Romé, Y., Ivanovic, R., and Gregoire, L.: Mechanisms behind climate oscillations in last glacial maximum simulations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2784, https://doi.org/10.5194/egusphere-egu22-2784, 2022.

How to cite: Kypke, K. and Ditlevsen, P.: A minimal SDE model of D-O events with multiplicative noise, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3973, https://doi.org/10.5194/egusphere-egu22-3973, 2022.

Several climate sub-systems are believed to be at risk of undergoing abrupt, irreversible changes as a tipping point (TP) in Greenhouse gas concentrations is reached. Since the current generation of climate models is likely not accurate enough to reliably predict TPs, a hope is to anticipate them from observations via early-warning signals (EWS). EWS have been designed to identify generic changes in variability that occur before a well-defined TP is crossed.

Such well-defined, singular TPs are believed to arise from a single dominant positive feedback that destabilizes the system. However, one may ask whether the large number of spatio-temporal scales in the climate system, and associated second-order feedbacks, could not lead to a variety of more subtle, but discontinuous reorganizations of the spatial climate pattern before the eventual catastrophic tipping. Such intermediate TPs could hinder predictability and mask EWS.

We performed simulations with a global ocean model that shows a TP of the Atlantic meridional overturning circulation (AMOC) due to freshening of the surface waters resulting from increased ice melt. Using a large ensemble of equilibrium simulations, we map out the stability landscape of the ocean circulation in high detail. While in a classical hysteresis experiment only one regime of bistability is found, by very slow increases in forcing we observe an abundance of discontinuous, qualitative changes in the AMOC variability. These are used to initialize smaller-scale hysteresis experiments that reveal a variety of multistable regimes with at least 4 coexisting alternative attractors.

We argue that due to chaotic dynamics, non-autonomous instabilities, and complex geometries of the basins of attraction, the realized path to tipping can be highly sensitive to initial conditions and the trajectory of the control parameter. Further, we discuss the degree to which the equilibrium dynamics are reflected in the transient dynamics for different rates of forcing. The results have implications regarding the expected abruptness of TPs, as well as their predictability and the design of EWS.

How to cite: Lohmann, J.: Abundant multistability and intermediate tipping points in a global ocean model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4470, https://doi.org/10.5194/egusphere-egu22-4470, 2022.

The 'hothouse narrative' states that tipping cascades could lead humanity to a binary choice between a 'governed Earth' and a 'hothouse' with no midway alternative. To investigate this scenario, we construct a toy model of interacting tipping elements and ask the following questions: Given a continuous family of emission scenarios, are there discontinuities in the family of responses, as suggested by the 'hothouse narrative'? How realistic is this given knowledge provided by climate simulations and paleo-climate evidence? The relatively low complexity of our model allows us to easily run it for several thousand years and a large range of emissions scenarios, helping us highlight the fundamental role of the different time scales involved in answering our questions. On the one hand, we find that the near-linear relationship predicted by GCMs between global temperature and GHG emissions for the next century can break up at millennial time scales due to cascades involving slower tipping elements such as the ice sheets. This translates as a discontinuity in the family of responses of our model. On the other hand, we find that different emissions scenarios respecting the same carbon budget could potentially lead to different tipping cascades and thus qualitatively different outcomes.

How to cite: Couplet, V. and Crucifix, M.: Investigating the 'Hothouse narrative' with dynamical systems, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5197, https://doi.org/10.5194/egusphere-egu22-5197, 2022.

How to cite: van Westen, R. and Dijkstra, H.: Transition Probabilities of Wind-driven Ocean Flows, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5268, https://doi.org/10.5194/egusphere-egu22-5268, 2022.

How to cite: Wendling, V., Peugeot, C., Grippa, M., Kergoat, L., Mougin, E., Hiernaux, P., Rouché, N., Panthou, G., Rajot, J.-L., Pierre, C., Mora, O., Garcia-Mayor, A., Ba, A., Lawin, E., Bouzou-Moussa, I., Demarty, J., Etchanchu, J., Hector, B., Galle, S., and Lebel, T. and the TipHyc Project: Tipping points in hydrology: observed regional regime shift and System Dynamics modeling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5433, https://doi.org/10.5194/egusphere-egu22-5433, 2022.

The warning of tipping to an undesired state in a complex system, such as the climate, when a control parameter slowly approaching a critical value ($\lambda(t) \rightarrow \lambda_0$) relies on detecting early warning signals (EWS) in observations of the system. The primary EWS are increase in variance, due to loss of resilience, and increased autocorrelation due to critical slow down. They are statistical in nature, which implies that the reliability and statistical significance of the detection depends on the sample size in observations and the magnitude of the change away from the base value prior to the approach to the tipping point. Thus the possibility of providing useful early warning depends on the relative magnitude of several interdependent time scales in the problem. These are (a) the time before the critical value $\lambda_c$ is reached, (b) the (inverse) rate of approach to the bifurcation point (c) The size of the time window required to detect a significant change in the EWS and finally, (d) The escape time for noise-induced transition (prior to the bifurcation). Here we investigate under which conditions early warning of tipping can be provided. 

How to cite: Ditlevsen, P.: Conditions for detecting early warning of tipping., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5500, https://doi.org/10.5194/egusphere-egu22-5500, 2022.

Every year, the area of the Arctic sea-ice decreases in the boreal spring and summer and reaches its yearly minimum in the early autumn. The continuous satellite-based time series shows that the September area has decreased from 4.5 x 10⁶ km² in 1979, to 2.8 x 10⁶ km² in 2020. The decline has been approximately linear in global mean surface temperature, with a rate of loss of 2.7 x 10⁶ km² per degree C of global warming.

In the CMIP6 ensemble, however, we find that the majority of the models that reach an Arctic sea-ice free state in the SSP585 runs show an accelerated loss of sea-ice for the last degree of warming compared to the second last degree of warming, which implies an increased sensitivity of the sea-ice to temperature changes. 

Both in the observational and CMIP6 data, we find that the decline in September sea-ice area is approximately proportional to the area north of which the zonal average temperature in spring and summer is lower than a critical threshold T_c. The Arctic amplification implies that the zonally averaged temperatures increase relative to the global temperatures, and with rates increasing with latitude. Linear extrapolation of the zonally averaged temperatures predicts that, with further warming, the September sea-ice area will depend non-linearly on global temperature, the sensitivity will increase and the September sea-ice area may become less that 1 x 10⁶ km² for global warming between 0.5 and 1.4^oC above the current temperature. 

As a result of accelerated sea-ice loss, the average evolution of the sea-ice area among the CMIP6 models before the complete loss of the summer sea-ice shows an increase in the year-to-year fluctuations in minimum ice cover in the next decade. This implies exceptional accumulation of extreme events with very low or no sea-ice at all even before the final loss of the sea-ice. Likewise, an apparent short-term recovery of the sea-ice loss might be observable due to the increasing fluctuations. 

How to cite: Poltronieri, A., Bochow, N., and Rypdal, M.: Arctic summer sea-ice loss will accelerate in coming decades, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5725, https://doi.org/10.5194/egusphere-egu22-5725, 2022.

In the context of climate change, the word "commitment" was originally used to denote how much extra warming is to be expected eventually given a certain fixed concentration of CO2. The notion has evolved and now it is customary to encounter terms such as "constant emissions commitment", "sea level rise commitment" and "zero emissions commitment". All these notions refer to how much change with respect to the current climate state is expected at a given point in the future considering our current climate state and specified future anthropogenic emissions.

Here, we propose thinking about commitment as available options for future action that will allow future decision makers to avoid harmful futures. The definition requires the identification of unwanted outcomes e.g., too high temperature or too fast sea level rise and the specification of a range of possible future anthropogenic emission/intervention scenarios. Given an initial climate state, the measure of commitment is based on the diagnosis of which of those emission/intervention scenarios yield futures safe from the unwanted outcomes. This new definition of commitment explicitly captures the notion of legacy: It measures the range of options that the next generations have at their disposal to avoid harmful futures.

We illustrate the definition and methodology with a simple model featuring ice sheet tipping points and ocean carbonate chemical balance. After having introduced the model, we specify the considered future anthropogenic emission/intervention options available, along with the considered unwanted outcomes. We show how the safe options available for future generations would change in time if we were to follow some of the most standard emission scenarios used in the literature.

How to cite: Martinez Montero, M., Crucifix, M., Botta, N., and Brede, N.: Commitment as Lost Opportunities, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5928, https://doi.org/10.5194/egusphere-egu22-5928, 2022.

A new simple approach inspired by MacAyeal (1979) to explain the time-asymmetric ‘saw-toothed’ shape and 100,000-year quasi-period of glacial-interglacial cycles since the Middle Pleistocene Transition, is presented. Using a simple model with fast-slow dynamics, the global ice volume is taken to be a function of two independently varying parameters, the solar insolation and ‘alpha’, a secondary control parameter, the study of which is the focus this research. The steady state of the model is a partially folded surface in three-dimensional space where insolation, ‘alpha’, and global ice volume are orthogonal axes. The pleated surface allows for the gradual increase and sudden decrease in ice volume that is observed in the paleoclimate record. To derive a time series of global ice volume, the Euler integration method is used, producing a time series which replicates the ‘saw-toothed’ pattern of glacial cycles in the late Pleistocene. The second control parameter, ‘alpha’, is proposed to be related to internal dynamics of the climate system, such as ice sheet dynamics.

Reference

D. R.  MacAyeal, ‘A Catastrophe Model of the Paleoclimate Record’ , Journal of Glaciology , Volume 24 , Issue 90 , 1979 , pp. 245 – 257.

How to cite: Ajagun-Brauns, J. and Ditlevsen, P.: A fast-slow model for glacial cycles since the Mid-Pleistocene Transition, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5997, https://doi.org/10.5194/egusphere-egu22-5997, 2022.

The Atlantic Meridional Overturning Circulation (AMOC) is a vital part of the global climate that has been suggested to exhibit bi-stability. A collapse from its current strong state to the weak one would have significant consequences for the climate system. Early-warning signals (EWS) for such a transition have recently been found in observational fingerprints for the AMOC.

Some uncertainty in our understanding of the AMOC and its recent evolution is due to the varying quality of its representation in state-of-the-art models. In this work we examine the historical AMOC simulations in the 6th Coupled Model Intercomparison Project (CMIP6) by analyzing the AMOC strength in the models both directly and through the sea-surface temperature fingerprint. As well as examining the evolution of these AMOC time-series in the models, we calculate their associated EWS and use these to evaluate the models in terms of their representation of the AMOC.

How to cite: Blaschke, L., Ben-Yami, M., Boers, N., and Nian, D.: AMOC Early-Warning Signals in CMIP6, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5999, https://doi.org/10.5194/egusphere-egu22-5999, 2022.

The El Niño Southern Oscillation (ENSO) is the most important driver of interannual global climate variability and affects weather and climate in large parts of the world. Recently, we have developed a dynamical network approach for predicting the onset of El Niño events well before the spring predictability barrier. In the regarded climate network, the nodes are grid points in the Pacific, and the strengths of the links (teleconnections) between them are characterized by the cross-correlations of the atmospheric surface temperatures at the grid points. In the year before an El Niño event, the links between the eastern equatorial Pacific and the rest of the Pacific tend to strengthen such that the average link strength exceeds a certain threshold. This feature can be used to predict the onset of an El Niño with 73% probability and its absence with 90% probability. The p-value of the hindcasting and forecasting phase (1981-2021) for this performance based on random guessing with the climatological average is 4.6*10^-5.

To assess whether this predictive feature is also present in coupled general circulation models, we apply our algorithm to historical and control runs of CMIP5 and CMIP6. We find that the predictive performance present in observational data is absent or very low in GCMs. The lack of this feature may explain the difficulties of GCMs to overcome the spring barrier.

How to cite: Ludescher, J., Bunde, A., and Schellnhuber, H. J.: El Niño forecasting by climate networks: comparison of the forecasting performance in observational data and in historical and controls runs of CMIP5 and CMIP6, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6329, https://doi.org/10.5194/egusphere-egu22-6329, 2022.

The potential impact of tipping points for climate dynamics is now widely recognized. Furthermore, paleoclimate records suggest that abrupt climate changes have indeed occurred in Earth’s past, potentially on timescales which do not exceed a decade. Several tipping elements, involving various components of the climate system, such as the ocean circulation, sea-ice, continental ice sheets, vegetation, and their couplings, have been suggested. Yet, it remains virtually unknown whether the large-scale atmospheric circulation, the component of the climate system with shortest response time, may undergo bifurcations that could trigger abrupt climate change.

    In this talk I will discuss the possibility of abrupt transitions of the large-scale circulation in the tropics. Specifically, I will consider potential reversals of the mean zonal winds, from the weak easterlies observed in current climate to a "superrotation" state with prevailing westerly winds. The superrotating state exhibits a strongly reduced Hadley circulation.
    I will discuss positive feedback mechanisms and their relevance for the Earth across a hierarchy of models of increasing complexity. A low-dimensional model based on Rossby wave resonance exhibits bistability, and provides a simple criterion for the region of parameter space where this regime exists. We then study the nature of the transition to superrotation in a dry dynamical core, forced in an idealized manner. The main result is that there exists a parameter regime where the dry primitive equations support two coexisting states, with and without an equatorial jet. We will discuss the role of parameters such as the meridional temperature gradient and the boundary layer friction on the existence of this bifurcation.

How to cite: Herbert, C.: Bistability and hysteresis of the large-scale tropical circulation in idealized GCM simulations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6519, https://doi.org/10.5194/egusphere-egu22-6519, 2022.

It is theorized that the resilience of natural ecosystems – their ability to resist and recover from external perturbations – can be estimated from their natural variability. We test this hypothesis using a global set of recovery rates from large disturbances derived from satellite vegetation data, and find that the expected theoretical relationships between these empirical recovery rates and the lag-1 autocorrelation and variance indeed hold approximately. The spatial pattern of global vegetation resilience reveals a strong link to both precipitation availability and variability, implying that water plays a first-order role in controlling the resilience of global vegetation.

The resilience of vegetation is not, however, static – global changes in temperature, precipitation, and anthropogenic influence will all impact the ability of ecosystems to adapt to and recover from disturbances. We investigate the global spatial and temporal patterns of changes in resilience using the empirically confirmed metrics – lag-1 autocorrelation and variance – and find spatially heterogeneous long-term (1980s-) trends; recent trends (2000s-) in vegetation resilience are strongly negative across land-cover types and climate zones.

How to cite: Smith, T., Boers, N., and Traxl, D.: Global-scale Changes in Vegetation Resilience Mapped with Satellite Data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7029, https://doi.org/10.5194/egusphere-egu22-7029, 2022.

How to cite: Ratas, M. and van Leeuwen, P. J.: Information flow in complex high-dimensional systems, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7496, https://doi.org/10.5194/egusphere-egu22-7496, 2022.

Spatial organization is a well-known feature of vegetation in semi-arid regions. This phenomenon appears in various parts of the world where water is the limiting factor for plants growing. Those patterns can be reproduced by using reaction-diffusion equations. Rietkerk developed a vegetation patterns model where the joint effects of a local reaction and diffusion create heterogeneous solutions.

The existence of those solutions expands the range of precipitation conditions under which vegetation can prevail. The complete region in the bifurcation diagram where such stable patterns exist is called the Busse balloon.

To our knowledge, no full investigation of the Busse balloon in Rietkerk’s model is available. Here we address this gap and dissect this Busse balloon by analysing the patterned solution branches of the bifurcation diagram.

For a given domain length, those branches can be computed starting from the different zero modes at the edge of the Turing zone around the branch of homogeneous solutions. Then, we use a Newton-Raphson method to track each branch for precipitation changes. Two types of branches appear. What we call the main branches have a roughly constant wavenumber along the branch. What we call the “mixed state branches” originate at the transition between stability and instability along one main branch. The corresponding solutions appear as mixing the solutions of two main branches, which is why we call them that way. However, we show that the latter plays a minor role in the dynamics of the system.

The awareness of the various patterned branch sheds new light on the dynamics of wavenumber switching or R-tipping for patterned systems. More generally, this work gives new insights into the behaviour of patterned systems under changing environment.

How to cite: Vanderveken, L. and Crucifix, M.: Bifurcation diagram for vegetation patterns model: old ways for new insight, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7531, https://doi.org/10.5194/egusphere-egu22-7531, 2022.

Confirmation exists for the 1997 revolutionary date of 12.850 cal yr BP established for the Laacher See Eruption (LSE) and introduced to encourage US-research on the P/H-KISS impact with LSE as isochrone and impact volcanism proxy (Bujatti-Narbeshuber, 1997). Bayesian analysis by Wolbach et al. (2018) of 157 dated records of the YD-impact hypothesis of Firestone et al. (2007) confirms impact with 2.854 ± 0.056 ka BP. This now allows to introduce the much larger P/H-KISS paleoceanographic transition scenario relating also to Holocene up to the present global climate change. The Holocene era, because of the thermohaline damped flow scenario, is herein considered as permanent end of the ice age, suggested here as the climatic consequence of an ocean topography and threshold change. Decoded cave art navigation world maps with Pleistocene paleoceanography content from Altamira , La Pasiega and El Castillo document in each one of the three maps specific AMOC stable states for interstadial/ full stadial/ stadial paleoclimate. Each map-thermohaline stable state is differently relating to a geomorphological boundary condition that is the subaerial surface Topography of a large Mid Atlantic Plateau (MAP)-Island. It is modelled in the P/H-KISS scenario as primary Pleistocene thermohaline phase 0 geomorphological threshold. As physical boundary condition it is in interaction with the thermohaline gulfstream current (above /below/at threshold). This results in the 3 distinct AMOC equilibrium stages of interstadial/ full stadial /stadial, as Pleistocene criticality interconnected by their respective further transition thresholds. When the primary  geomorphological threshold is removed the result is the Holocene damped flow, a transition continuum of thermohaline phases 1, 2, 3. Geomorphological proof is first the MAP-Island, invariably shown on all three maps. Furthermore the MAP-Island is identified by its characteristic topography on decorated columns in Göbekli Tepe as a highly abstract island symbol with deeper political-territorial meanings. With paleo-astronomical precession dating on Pillar 43, the LSE 12.850 cal yr BP date was reproduced and the YD (P/H-KISS) impact series from comet fragments in the Taurid stream were decoded by M. Sweatman (2019).  The symbol sequence on Pillar 18, revealed here for the first time, is the (HI-T) = MAP-Island-Dual 90°-Transition-Tsunami Code of the two step Mid Atlantic Ridge MAR & MAP- Island isostatic submersion by the Taurid stream Koefels-comet oceanic-impact fragments: Paleoclimatology thus confirms and now extends the D. Paillard (1998) three equilibria ocean-box-climate-model with 3 thresholds for 3 transitions between the 3 thermohaline stable states of the ice age to the larger P/H-KISS transition scenario of paleo-climate change. It states that the above 3 AMOC states are exclusively based on the existence of the MAP-Island threshold. Isostatic MAR & MAP-Submergence brings their ice age ending collapse into the broad continuum of the Global warming Threshold Triad with thermohaline damped flow in a very long lasting Holocene interstadial.

*) Bujatti-Narbeshuber, M. - Pleistocene/Holocene (P/H) boundary oceanic Koefels-comet Impact Series Scenario (KISS) of 12.850 yr BP Global-warming Threshold Triad (GTT). -Climates: Past, Present and Future; Second European Palaeontological Congress Abstracts edited by D.K. Ferguson & H.A. Kollmann; Vienna, 1997.

How to cite: Dr. Bujatti-Narbeshuber, M.: Pleistocene/Holocene (P/H) boundary oceanic Koefels-comet Impact Series Scenario (KISS) of 12.850 yr BP Global-warming Threshold Triad (GTT)-Part II *), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8412, https://doi.org/10.5194/egusphere-egu22-8412, 2022.

This study suggests a stochastic model for time series of daily zonal (circumpolar) mean stratospheric temperature at a given pressure level. It can be seen as an extension of previous studies which have developed stochastic models for surface temperatures. The proposed model is a combination of a deterministic seasonality function and a Lévy-driven multidimensional Ornstein–Uhlenbeck process, which is a mean-reverting stochastic process. More specifically, the deseasonalized temperature model is an order 4 continuous-time autoregressive model, meaning that the stratospheric temperature is modeled to be directly dependent on the temperature over four preceding days, while the model’s longer-range memory stems from its recursive nature. This study is based on temperature data from the European Centre for Medium-Range Weather Forecasts ERA-Interim reanalysis model product. The residuals of the autoregressive model are well represented by normal inverse Gaussian-distributed random variables scaled with a time-dependent volatility function. A monthly variability in speed of mean reversion of stratospheric temperature is found, hence suggesting a generalization of the fourth-order continuous-time autoregressive model. A stochastic stratospheric temperature model, as proposed in this paper, can be used in geophysical analyses to improve the understanding of stratospheric dynamics. In particular, such characterizations of stratospheric temperature may be a step towards greater insight in modeling and prediction of large-scale middle atmospheric events, such as sudden stratospheric warming. Through stratosphere–troposphere coupling, the stratosphere is hence a source of extended tropospheric predictability at weekly to monthly timescales, which is of great importance in several societal and industry sectors.

How to cite: Eggen, M., Rognlien Dahl, K., Näsholm, S. P., and Mæland, S.: Stochastic Modeling of Stratospheric Temperature, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8745, https://doi.org/10.5194/egusphere-egu22-8745, 2022.

Given large regions of ice grounded below sea level associated with a retrograde bedrock, the West Antarctic Ice Sheet (WAIS) is believed to be a tipping element whose tipping point could be reached within this century under high emission scenarios. As the WAIS represents the largest and most uncertain source of future sea-level rise, characterising its stability is crucial for defining safe emission pathways and protecting livelihoods in coastal regions. In the present work, we investigate its potential to undergo an abrupt change due to a fold bifurcation. To this end, we use a high-order ice sheet model with 16km spatial resolution. Rather than applying a fixed forcing rate as in previous studies, we apply a forcing scheme that adaptively increases the local temperature while keeping the system near equilibrium, which allows us to obtain a rigorous value for the bifurcation tipping point. More importantly, we show how this threshold can become relevant for much lower warming levels than expected - even within the bounds of relatively conservative emission scenarios. Subsequently, we explain the underlying mechanisms leading the marine ice-sheet instability to possibly arise earlier than suggested by the bifurcation study. We finally question whether the tipping point of the WAIS can be understood as a fixed temperature value and if not, by which information it should be extended to provide an early warning signal.

How to cite: Swierczek-Jereczek, J., Montoya, M., Robinson, A., Alvarez-Solas, J., and Blasco, J.: Is West-Antarctica’s Tipping Point a Fixed Value?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8753, https://doi.org/10.5194/egusphere-egu22-8753, 2022.

Functional networks are powerful tools to study statistical interdependency structures in extended systems. They have been used to get insights into the structure and dynamics of complex systems in various areas of science. In particular, several studies have suggested the use of precursors based on percolation transitions in correlation networks to forecast El Niño events.

Our aim is to provide a better understanding of the potential of such percolation precursors for the prediction of episodic events in generic systems presenting chaotic oscillations. To this end, we study the behavior of the precursors in a spatially extended stochastic Vallis model, an asymmetric Lorenz-63 type model for the El Niño-Southern Oscillation (ENSO). Our results demonstrate the ability of the largest connected component of the network to anticipate abrupt changes associated with the system's oscillatory dynamics.

This research was conducted as part of the CAFE Innovative Training Network (http://www.cafes2se-itn.eu/) which 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: Ehstand, N., Donner, R. V., López, C., and Hernández-García, E.: Using complex networks to predict abrupt changes in oscillatory systems, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9237, https://doi.org/10.5194/egusphere-egu22-9237, 2022.

Since the pre-industrial era, global sea level has been rising along with greenhouse gas emissions. Part of the contribution to this sea-level change is the mass lost from continental ice sheets, i.e. the Greenland (GrIS) and Antarctic (AIS) ice sheets, which are shrinking at an accelerated rate. However, how they will respond to future warming is highly uncertain due to our lack of knowledge and associated uncertainty in modelling several physical processes, as well as in warming projections. A way to gain insight into future projections is to study past warm periods that are, to some extent, comparable to the present day (PD) in terms of external forcing. The mid-Pliocene warm period (mPWP, 3.3-3.0 million years ago) offers an ideal benchmark, as it is the most recent period with CO2 levels comparable to PD (350-450 ppmv), showing global mean temperatures 2.5-4.0 degrees higher. Eustatic sea-level reconstructions from that period estimate a sea level 15-20 meters higher than PD, implying ice sheets were much smaller in size. The GrIS was starting to form and the AIS was most likely constrained to land-based regions. The Pliocene Model Intercomparison Project, Phase 2 (PlioMIP2) has brought together over 15 climate outputs from 11 General Circulation models from different institutions. These models have simulated mPWP conditions under 400 ppmv of CO2 concentration over a topography generated from an updated bedrock configuration for that time period. Here we use these model outputs to force offline a higher-order ice sheet model for the Antarctic and Greenland domain. Our aim is to investigate how polar continental ice sheets respond to these different climatic fields to pinpoint their most significant climatic and topographical discrepancies. In addition, several sources of structural dependence, from different dynamic states (i.e. basal friction laws) to different initial boundary conditions (starting from no ice-sheet to the PD configuration) are investigated in this modelling framework to create a comprehensive output database for statistical analysis.

How to cite: Blasco, J., Tabone, I., Moreno-Parada, D., Alvarez-Solas, J., Robinson, A., and Montoya, M.: The Antarctic and Greenland response to PlioMIP2 mPWP climatic fields, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9322, https://doi.org/10.5194/egusphere-egu22-9322, 2022.

The Amazon rainforest has a major contribution to the bio-geochemical functioning of the Earth system and has been projected to be at risk of large-scale, potentially irreversible, dieback to a savanna state. Measuring the resilience of the Amazon rainforest empirically is critical to helping us understand the magnitude and frequency of disturbances that the rainforest can still recover from. Different means to quantify resilience in practice have been proposed. Here we determine the Amazon rainforest resilience based on a space-for-time replacement, and then estimating the average residence time in the forest state. This 'global' notion of resilience is different from local measures based on variance or autocorrelation and thus provides complementary information. We study the dependence of the exit-time-base resilience on total rainfall and, in order to study the evolution of the Amazon rainforest, we also estimate changes in their resilience over the years.

How to cite: Nian, D., Blaschke, L., Zheng, Y., and Boers, N.: Measuring Amazon rainforest resilience from remotely sensed data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9340, https://doi.org/10.5194/egusphere-egu22-9340, 2022.

Layer-counted paleoclimatic proxy records have non-negligible uncertainty arising from the dating process. Knowledge of this uncertainty is important for a rigorous propagation to further analyses; for example for identification and dating of abrupt transitions in climate or to provide a complete uncertainty quantification of early warning signals. This dating uncertainty can be quantified by assuming a probabilistic model for the age-depth relationship. We assume that the number of counted layers per unit of depth can be described using a Bayesian regression model with residuals following an autoregressive process. By synchronizing the chronologies with other archives one can constrain the uncertainties and correct potential biases in the dating process. This is done by matching the chronologies to tie-points obtained by analyzing different archives covering the same period in time. In practice, tie-points can be associated with a significant amount of uncertainty which also needs to be accounted for. We present a theoretically consistent approach which, under certain assumptions, allows for efficient sampling from synchronized age-depth models that match the tie-points under known uncertainty distributions. The model and associated methodology has been implemented into an R-package. 

How to cite: Myrvoll-Nilsen, E., Riechers, K., and Boers, N.: Synchronization of layer-counted archives using a statistical age-depth model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9504, https://doi.org/10.5194/egusphere-egu22-9504, 2022.

Tipping points in the Earth System could present challenges for society and ecosystems. The existence of tipping points also provides a major challenge for science, as the global warming thresholds at which they are triggered is highly uncertain. A theory of `Early Warning Signals' has been developed to 
warn of approaching tipping points. Although this theory uses generic features of a system approaching a Tipping Point, the conventional application of it relies on an implicit assumption that the system experiences white noise forcing. In the Earth system, this assumption is frequently invalid.
Here, we extend the theory of early warning signals to a system additively forced by an autocorrelated process. We do this by considering the spectral properties of both the system and also of the forcing.  We test our method on a simple dynamical system, before applying our method to a particular example from the Earth System: Amazon rainforest dieback. Using our new approach, we successfully forewarn of modelled rainforest collapse in a state-of-the-art CMIP6 Earth System Model.

How to cite: Clarke, J., Huntingford, C., Ritchie, P., and Cox, P.: Early Warning Signals For Climate Tipping Points: Beyond White Noise, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10031, https://doi.org/10.5194/egusphere-egu22-10031, 2022.

The dynamics of systems with time-dependent forcing or coefficients has become a matter of considerable interest in the last couple of decades in general and in the last dozen years or so in the climate sciences in particular (Ghil, 2019; Ghil & Lucarini, 2020; Ghil, 2021; Tel et al., 2021; and references therein). We shall provide a general introduction to the topic and illustrate it with several paleoclimate-related examples (Crucifix, 2012; Riechers et al., 2022; Rousseau et al., 2022). Perspectives for further applications of the concepts and methods of the theory of pullback and random attractors and of their tipping points to paleoclimate will also be provided.

References

• Crucifix, M.: Oscillators and relaxation phenomena in Pleistocene climate theory, PTRSA, 370, 1140–1165, 2012.
• Ghil, M., 2019: A century of nonlinearity in the geosciences, Earth & Space Science, 6, 1007–1042, doi: 1029/2019EA000599.
• Ghil, M., 2020: Review article: Hilbert problems for the climate sciences in the 21st century – 20 years later, Nonlin. Processes Geophys., 27, 429–451, https://doi.org/10.5194/npg-27-429-2020.
• Ghil, M., and V. Lucarini, 2020: The physics of climate variability and climate change, Mod. Phys., 92(3), 035002, doi: 10.1103/RevModPhys.92.035002.
• Riechers, K., T. Mitsui, N. Boers, and M. Ghil, 2022: Orbital insolation variations, intrinsic climate variability, and Quaternary glaciations, Clim. Past Discuss. [preprint], https://doi.org/10.5194/cp-2021-136, in review.
• Rousseau, D.-D., W. Bagnewski, and M. Ghil, 2021: Abrupt climate changes and the astronomical theory: are they related?, Clim. Past, accepted, doi: 10.5194/cp-2021-103 .
• Tél, T., Bódai, T., Drótos, G., Haszpra, T., Herein, M., Kaszás, B. and Vincze, M., 2020. The theory of parallel climate realizations. Journal of Statistical Physics, 179(5), 1496–1530.

How to cite: Ghil, M.: Nonautonomous dynamics and its applications to paleoclimate, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10128, https://doi.org/10.5194/egusphere-egu22-10128, 2022.

The Paleocene-Eocene Thermal Maximum (PETM; 56 Ma) and Eocene Thermal Maximum 2 and 3 (ETM2; 54.06 Ma and ETM3; 52.87 Ma) were three of a series of abrupt climate and carbon cycle perturbations, characterized by massive carbon input into the ocean-atmosphere system and strong global warming. These abrupt events, termed hyperthermals, potentially represent ‘tipping points’ at moments in time when the resilience of the system was low and reinforced by strong internal feedbacks, such as the catastrophic release of carbon from submarine methane hydrates. Alternatively, external mechanisms such as volcanism may have played a pronounced external role during the PETM. Here, we evaluate if the hyperthermals indeed resulted from reduced Earth System resilience and tipping point behaviour through the mathematical analyses of climate and carbon cycle indicators, namely, oxygen and stable carbon isotope ratios of deep ocean foraminifer calcite, across the late Paleocene and early Eocene. Our combined analysis using Dynamic Indicators of Resilience (DIORs) and Convergent Cross Mapping (CCM) reveals a loss of resilience and an increase in the causal interaction between the carbon cycle and climate towards the PETM, ETM2, and ETM3. A novel, windowed CCM approach indicates a tight coupling between carbon and climate across the early Eocene, further supporting dominant climate forcing on carbon cycle dynamics. This indicates that the internal rather than external mechanisms were responsible for the hyperthermals, suggesting a secondary role for endogenic processes such as volcanism. Furthermore, the CCM analysis in conjunction with the absence of major positive feedbacks such as the presence of polar ice caps during early Eocene could be employed to stipulate that these hyperthermal events may be caused by the increase in coupling between the carbon cycle and climate systems, eventually pushing both systems towards a tipping point through increasing positive feedbacks.

How to cite: Setty, S., Cramwinckel, M., Leemput, I. V. D., Nes, E. H. V., Lourens, L. J., Sluijs, A., and Scheffer, M.: Loss of Earth System Resilience during Early Eocene Global Warming Events, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10628, https://doi.org/10.5194/egusphere-egu22-10628, 2022.

Millennial-scale climate variability, especially abrupt stadial-interstadial transitions, are a prominent feature of the last glacial as recorded in Greenland ice core records (Dansgaard-Oeschger events). Event abruptness and presence of statistical early warning signals before these transitions indicate that they involve repeated crossing of a tipping point of the climate system. However, only little information is available for periods before the last glacial period as Greenland ice cores and many other high-resolution records do not extent beyond the last glacial cycle. Given the lack of understanding of the triggering mechanism responsible for glacial millennial-scale variability with palaeoclimate data from the last glacial, it is essential to investigate this phenomenon during earlier glacial periods.

Here, we present a new highly resolved, precisely U-Th-dated speleothem oxygen isotope record from the Northern European Alps, a region which has been previously shown to resemble the glacial millennial-scale climate variability obtained from Greenland ice core records very well. Our new data covers the time interval from the ante-penultimate glacial to the penultimate glacial (MIS8-MIS6) with a high degree of replication. For both glacial periods, we find phases of pronounced millennial-scale variability but also several, ~10 ka long phases with the climate system being exclusively in stadial conditions. We compare our data with conceptual model results and investigate the occurrence and absence of abrupt climate transitions of the last 300,000 a.

How to cite: Skiba, V., Trüssel, M., Plessen, B., Spötl, C., Eichstädter, R., Schröder-Ritzrau, A., Braun, T., Mitsui, T., Frank, N., Boers, N., Marwan, N., and Fohlmeister, J.: Abrupt climate events recorded in speleothems from the ante penultimate glacial, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11671, https://doi.org/10.5194/egusphere-egu22-11671, 2022.

One of the key problems in climate science is to understand the asymptotic behaviour of a climate model, such as Equilibrium Climate Sensitivity (ECS), from finite time computations of transients of a model that may be complex and realistic. Typically, this is done by fitting to some simpler model and then extrapolating to an asymptotic state. But how do transients behave in the presence of tipping points? More precisely, how much warning can one get of an approaching tipping point? In this work we highlight an illustrative example showing how a good fit of a transient to a simpler model does not necessarily guarantee a good extrapolation, and discuss some other implicit assumptions that may arise when estimating quantities such as ECS.

How to cite: Ashwin, P., Bastiaansen, R., and von der Heydt, A.: Fitting and extrapolation of transient behaviour in the presence of tipping points, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12053, https://doi.org/10.5194/egusphere-egu22-12053, 2022.

Climate tipping points occur when change in a part of the climate system becomes self-perpetuating beyond a forcing threshold, leading to abrupt and/or irreversible impacts. Synthesizing paleoclimate, observational, and model-based studies, we provide a revised shortlist of global ‘core’ tipping elements and regional ‘impact’ tipping elements and their temperature thresholds. Current global warming of ~1.1°C above pre-industrial already lies within the lower end of some tipping point uncertainty ranges. Several more tipping points may be triggered in the Paris Agreement range of 1.5-2°C global warming, with many more likely at the 2-3°C of warming expected on current policy trajectories. In further work we use these estimates to test the potential for and impact of tipping cascades in response to global warming scenarios using a stylised model. This strengthens the evidence base for urgent action to mitigate climate change and to develop improved tipping point risk assessment, early warning capability, and adaptation strategies.

Preprint: https://doi.org/10.1002/essoar.10509769.1

How to cite: Armstrong McKay, D., Staal, A., Abrams, J., Winkelmann, R., Sakschewski, B., Loriani, S., Fetzer, I., Cornell, S., Rockström, J., and Lenton, T.: Updated assessment suggests >1.5°C global warming could trigger multiple climate tipping points, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12438, https://doi.org/10.5194/egusphere-egu22-12438, 2022.

Paleoclimate proxy records contain abrupt transitions that may represent former instances of the climate system crossing a tipping point (TP). Properly identifying these TPs in the Earth’s past helps determine critical thresholds in present-day climate and better understand the climate system’s underlying bifurcation mechanisms.

Information contained in paleoclimate proxy records is often ambiguous because of the complexity of the system, which includes both deterministic and stochastic processes. Furthermore, paleoclimate time series differ in their time spans and periodicities, and often have high levels of noise and a nonuniform resolution. These combined sources of uncertainty highlight the need for using advanced statistical methods for robustly identifying and comparing TPs.

A recently developed method that uses an augmented Kolmogorov-Smirnov test has been shown to be highly effective for transition detection in different types of records. Here, we apply this method to a set of high-quality paleoproxy records exhibiting centennial-to millennial-scale variability that have been compiled in the PaleoJump database. We thereby detect previously unrecognized transitions in these records and identify potential TPs. Furthermore, we investigate regime changes with recurrence analysis and spectral analysis.

This study is supported by the H2020-funded Tipping Points in the Earth System (TiPES) project.

How to cite: Bagniewski, W., Ghil, M., and Rousseau, D.-D.: Paleoclimatic tipping points and abrupt transitions: An application of advanced time series analysis methods, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12501, https://doi.org/10.5194/egusphere-egu22-12501, 2022.

The topology of the branched manifold associated with the Lorenz model’s random attractor (LORA) evolves in time. LORA’s time-evolving branched manifold robustly supports the point cloud associated with the system’s invariant measure at each instant in time. 

This manifold undergoes not only continuous deformations — with branches that bend, stretch or compress — but also discontinuous deformations, with branches that intersect at discrete times. These discontinuities in the system's invariant measure manifest themselves in the decrease or increase of the number of 1-holes, thus producing abrupt changes in the branched manifold’s topology.

Topological tipping points (TTPs) are defined as abrupt changes in the topology of a random attractor’s branched manifold. Branched Manifold Analysis through Homologies
(BraMAH) is a robust method that allows one to detect these fundamental changes. 
The existence of such TTPs is being confirmed by careful statistical analysis of LORA’s time-evolving branched manifold, following up on Charó et al. (Chaos, 2021, doi:10.1063/5.0059461). Research is being pursued on early warning signals for these TTPs, concentrating on local fluctuations in the system’s invariant measure.

How to cite: Charó, G. D., Ghil, M., and Sciamarella, D.: Early warning signals for topological tipping points, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12686, https://doi.org/10.5194/egusphere-egu22-12686, 2022.

Multiple proxy records from Greenland ice cores exhibit a series of concomitant abrupt climatic shifts during the last glacial. These so-called Dansgaard–Oeschger (DO) events comprise, among others, warming over Greenland, a sudden retreat of North Atlantic and Nordic Seas’ sea ice, and an atmospheric reorganisation of hemispheric extent. Typically DO events are followed by a phase of moderate cooling, before the climate abruptly transition back to its pre-event state. While the physics behind these dynamics are still subject to a vibrant debate, the idea that at least one of the involved climatic subsystems features bistability is widely accepted.

We assess the stability of Greenland temperatures and the Northern Hemisphere atmospheric circulation represented by δ¹⁸O and dust concentration records from the NGRIP ice core, respectively. We investigate the 27-59 ky b2k period of the combined record which covers 12 major DO events at high temporal resolution. Regarding the data as the realisation of a stochastic process we reconstruct the corresponding drift and diffusion by computing the Kramers–Moyal (KM) coefficients. In contrast to previous studies, we find the drift of the δ¹⁸O to be monostable, while analysis of the dust record yields a bistable drift. Furthermore, we find a non-vanishing 4^th-order KM coefficient for the δ¹⁸O, which indicates that the δ¹⁸O time series cannot be considered a standard type Langevin process. In a second step, we treat the joint (δ¹⁸O , dust) time series as a two dimensional stochastic process and compute the corresponding coefficients of the two dimensional KM expansion. This reveals the position of the fixed point of δ¹⁸O to be controlled by the value of the dust. In turn, the drift of the dust undergoes an imperfect supercritical pitchfork bifurcation when transitioning from low to high δ¹⁸O values.

How to cite: Riechers, K., Rydin, L., Hassanibesheli, F., Witthaut, D., Lind, P., and Boers, N.: Data-driven Reconstruction of Last Glacials' Climate Dynamics Suggests Monostable Greenland Temperatures and a Bistable Northern Hemisphere Atmosphere, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13023, https://doi.org/10.5194/egusphere-egu22-13023, 2022.

Many generations of climate general circulation models (GCMs) have suggested that a radical reorganisation (tipping) of the Atlantic Meridional Overturning Circulation is unlikely in the 21^st Century in response to the greenhouse gas emissions pathways considered by the Intergovernmental Panel on Climate Change (IPCC). Yet some studies suggest that GCMs as a class may represent an AMOC that is biased towards excessive stability. If this is the case then simply looking at AMOC response in the ensemble of current GCMs may give a misleading picture of the possible future pathways of the AMOC.

In this study we use a simple coupled climate model, including both the thermal and water cycle responses to greenhouse gas increase, to explore beyond the range of the current ensemble of ‘best estimate’ GCMs. What would the climate system need to look like in order for AMOC tipping to be a plausible outcome? We find that tipping behaviour would require key parameters controlling the response of the hydrological cycle to surface warming to be towards the edge of plausible ranges.

While AMOC tipping remains a ‘High Impact, Low Likelihood’ outcome, our results extend current knowledge by showing how AMOC tipping could occur in response to greenhouse gas forcing (as opposed to the common idealisation of ‘water hosing’ experiments). The results also show how monitoring key parameters of the climate system may over time allow the possibility of tipping to be more confidently assessed.

How to cite: Wood, R.: Climate storylines for AMOC tipping in response to increasing greenhouse gases, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13181, https://doi.org/10.5194/egusphere-egu22-13181, 2022.

Mesoscale eddy-permitting ocean models will be needed as a component of climate ensemble projections most likely for the next decade or more.   However, the kinetic energy and other measures of variability are typically an order of magnitude too weak at this nominal 0.25 degree lon-lat resolution.    This is predominantly due to excessive gridscale damping of momentum, needed for computational stability, which is believed to kill a large fraction of the energy source of the kinetic energy inverse cascade.   The KE inverse cascade is associated with the generation of intrinsic chaotic variability and ensemble spread, hence the estimation of potential predictability, but also with slower, larger-scale variability associated with climate.  The familiar Gent and McWilliams (1990) eddy parameterisation is problematic when applied to eddy-permitting models, where eddies are partially resolved, and it also tends to damp variability rather than energise it.   In response to this problem, several recent studies have focussed on the KE backscatter problem, which each attempt to increase the upscale transfer of KE, either deterministically or stochastically.

Stochastic parameterisation of sub-gridscale eddies has recently become a popular approach in ocean modelling, having been used in atmospheric modelling for many years, but there is still a diverse range of approaches for constraining either the underlying physics (how the forcing is applied) or the statistics (the spatiotemporal signature of the forcing).   This study explores some basic recipes for constructing the stochastic model from statistics of either observations or higher-resolution models.  The stochastic forcing, representing the sub-gridscale effects of eddies in our eddy-permitting simulations, is also applied adiabatically – to mimic the predominant behaviour of mesoscale eddies in the ocean interior and to preserve large-scale watermasses.   A theoretical challenge, which we explore, is to connect the applied, weakly imbalanced forcing, to a response in kinetic energy and upscale transfer.  This must also be applied without generating numerical instability.  

How to cite: Wilson, C., Hughes, C. W., Williams, S. D. P., and Blaker, A. T.: Adiabatic, Constrained, Stochastic Eddy Parameterisation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-750, https://doi.org/10.5194/egusphere-egu22-750, 2022.

The analysis of eddy-mean flow interaction provides key insights into the structures and dynamics of inhomogeneous and anisotropic flows such as atmospheric and oceanic jets. As the divergence of Eliassen-Palm (E-P) flux formally encapsulates the interaction, the community has had a long-standing interest in accurately diagnosing this term. Here, we revisit the E-P flux divergence with an emphasis on the Gulf Stream, using a 48-member, eddy-rich (1/12°) ensemble of the North Atlantic ocean partially coupled to identical atmospheric states amongst all members via an atmospheric boundary layer model. This dataset allows for an unique decomposition where we define the mean flow as the ensemble mean, and interpret it as the oceanic response to the atmospheric state. The eddies are subsequently defined as fluctuations about the ensemble mean. Our results highlight two points: i) the implementation of the Thickness-Weighted Averaged (TWA) framework for a realistic ocean simulation in diagnosing the E-P flux divergence, and ii) validity of the ergodic assumption where one treats the temporal mean equivalent to the ensemble mean, which is questionable for a temporally varying system such as the ocean and climate.

How to cite: Uchida, T., Jamet, Q., Dewar, W., Le Sommer, J., Penduff, T., and Balwada, D.: Diagnosing the thickness-weighted averaged eddy-mean flow interaction from an eddying North Atlantic ensemble, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-770, https://doi.org/10.5194/egusphere-egu22-770, 2022.

Understanding processes associated with eddy-mean flow interactions helps our interpretation of the ocean energetic balance, and guides the development of parameterizations. Here, we focus on the non-local nature of Kinetic Energy (KE) transfers between mean (MKE) and turbulent (EKE) reservoirs. Following previous studies, we interpret these transfers as non-local when the energy extraction from the mean flow does not locally sustain energy production of the turbulent flow, or vice versa. The novelty of our approach is to use ensemble statistics, rather than time averaging or coarse-graining methods, to define the mean and the turbulent flow. Based on KE budget considerations, we first rationalize the eddy-mean separation in the ensemble framework, and discuss the interpretation of a mean flow (<u>) driven by the prescribed (surface and boundary) forcing and a turbulent flow (u') driven by non-linear dynamics sensitive to initial conditions. Our results, based on the analysis of 120-day long, 20-member ensemble simulations of the Western Mediterranean basin run at 1/60^o, suggest that eddy-mean kinetic energy exchanges are largely non-local at small scales. Our main contribution is to recognize the prominent contribution of the cross energy term (<u>.u') to explain this non-locality, providing a strong constraint on the horizontal organization of eddy-mean flow KE exchanges since this term vanishes identically for perturbations (u') orthogonal to the mean flow ( Our results also highlight the prominent contribution of vertical turbulent fluxes for energy exchanges within the surface mixed layer. Analyzing the scale dependence of these non-local energy exchanges supports the local approximation usually made in the development of meso-scale, energy-aware parameterizations for non-eddying models, but points out to the necessity of accounting for these non-local effects in the meso-to-submeso scale range.

How to cite: Jamet, Q., Leroux, S., Dewar, W. K., Penduff, T., Le Sommer, J., Molines, J.-M., and Gula, J.: Non-local eddy-mean kinetic energy transfers in submesoscale-permitting ensemble simulations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1428, https://doi.org/10.5194/egusphere-egu22-1428, 2022.

Internal variability, unprovoked by external forcing, emerges in the hydrodynamics of the marginal seas. Ensemble ocean simulations are used to analyze the characteristics, scales, and intensities of such variability in the Bohai, Yellow Sea, and South China Sea. With the signal defined as the covariation in the ensemble, and the noises as the independent variations, a scale dependency of the Signal-to-Noise Ratio (S/N ratio) is found in the Bohai, Yellow Sea, and South China Sea. The external forcing and related signal are dominant for large scales, while most of the internal variability is generated for small scales. The intensities of internal variability of the Bohai and Yellow sea are about half of the intensities of South China Sea, likely because eddies are less energetic in the Bohai and Yellow Sea, which likely is the main source of noise in South China Sea.

In addition, we investigate the effect of tides on internal variability in the Bohai and Yellow Sea by three ensembles of numerical experiments with tidal forcing, with half tidal forcing, and without tidal forcing. When the tides are weakened or turned off, the S/N ratios are reduced in large and medium scales, more so in the Yellow Sea than in the Bohai. The increase in the S/N ratio is largest for large scales and for depth-averaged velocity. The reduction in tidal forcing results in an approximately 30% increase in S/N ratios in the Bohai at large scales. Thus, the absence of tidal forcing favours the emergence of unprovoked variability at large and medium scales but not at small scales. We suggest that the main mechanism for the increase of covarying variability when tides are active, is the additional mixing induced by the tides.

How to cite: Lin, L., von Storch, H., Chen, X., and Tang, S.: The Characteristics and Significance of Hydrodynamical Internal Variability in Modelling Dynamics in Marginal Seas, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1973, https://doi.org/10.5194/egusphere-egu22-1973, 2022.

Intrinsic chaotic variability in the oceans is an active field of research in modern oceanography, with important implications concerning the understanding and predictability of the ocean system. The focus is mainly on open ocean basins while very little attention is devoted to enclosed or semi-enclosed seas. The intrinsic variability of the Mediterranean Sea, in particular, has not yet been investigated. Here, results obtained with an eddy-resolving nonlinear multilayer ocean model are presented shedding light on relevant aspects of the intrinsic low-frequency variability of the Mediterranean Sea circulation.

An ensemble of multi-centennial ocean runs is performed to allow for a significant statistical analysis. The statistically stationary state obtained after long simulations shows a robust meridional structure consistent with the observed Mediterranean mean state. Among the various features emerging in the decadal and multidecadal temporal ranges are abrupt shifts in the water mass stratification structure. Differences and similarities with observed patterns are finally discussed. 

How to cite: Rubino, A., Pierini, S., Rubinetti, S., and Zanchettin, D.: Intrinsic low-frequency variability of the Mediterranean Sea circulation studied using a multilayer ocean model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2167, https://doi.org/10.5194/egusphere-egu22-2167, 2022.

An ensemble of North Atlantic simulations is analyzed, providing estimates of kinetic energy spectra.  A wavelet transform technique is used permitting comparisons to be made between spectra at different locations in this highly inhomogeneous environment.  We find a strong tendency towards anisotropy in the spectra, with meridional spectra typically stronger than zonal spectra.  This holds even in the gyre interior where conditions might be expected to be homogeneous.  The spectra show reasonable ranges consistent with a downscale enstrophy cascade, but also a persistent tendency to exhibit steeper slopes at smaller scales.  The only location where the presence of an upscale cascade is supported is the Gulf Stream extension.  This is amongst first attempts to quantify and compare spectra and their differences in the inhomogeneous setting of the North Atlantic.

How to cite: Dewar, W. K., Uchida, T., Jamet, Q., and Poje, A.: The Structure of North Atlantic Kinetic Energy Spectra, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2849, https://doi.org/10.5194/egusphere-egu22-2849, 2022.

Anthropogenic emissions of greenhouse gases, such as CO₂ and N₂O, warm the earth. This in turn modulates the atmospheric greenhouse gas concentrations. The underlying feedback mechanisms are complex and can be counterintuitive. Earth system models have recently matured to standard tools tailored to assess and understand these feedback mechanisms. Along comes the need to determine poorly-known model parameters. This is especially problematic for the ocean biogeochemical component where respective observational data, such as nutrient concentrations and phytoplankton growth, are rather sparse in time and space. In the present study, we illustrate common problems when attempting to estimate such parameters based on typical model evaluation metrics. We find very different parameter sets which are, on the one hand, equally consistent with (synthetic) historical observations while, on the other hand, they propose strikingly differing projections into a warming climate. By the example of simulated oxygen concentrations we propose a step forward by applying variance-based sensitivity analyses to map the respective parameter uncertainties onto their local manifestations - for both contemporary climate and climate projections. The mapping relates local uncertainties of projections to the uncertainty of specific model parameters. In a nutshell, we present a practical approach to the general question of where the present-day model fidelity may be indicative for reliable projections.

How to cite: Löptien, U. and Dietze, H.: Linking contemporary parametric model uncertainties to projections of biogeochemical cycles, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3044, https://doi.org/10.5194/egusphere-egu22-3044, 2022.

Marine biogeochemical (BGC) models are important tools in the hands of scientists and policymakers when assessing the impacts of climate change. Therefore, including an ocean BGC component in Earth System Modeling efforts is essential for climate simulation and predictions. However, current BGC models, used to simulate and thus better understand the marine ecosystem processes, are associated with large undefined uncertainties. Similar to other geoscientific models, complex biological and chemical processes are converted to simplified schemes in BGCs, a methodology known as parameterization. However, these parameter values can be poorly constrained and also involve unknown uncertainties. In turn, the uncertainty in the parameter values translates into uncertainty in the model outputs. Therefore, a systematic approach to properly quantify the uncertainties of the parameters is needed. In this study, we apply an ensemble data assimilation method to quantify the uncertainty arising from the parameterization within BGC models. We apply an ensemble Kalman filter provided by the parallel data assimilation framework (PDAF) into a one-dimensional vertical configuration of the biogeochemical model Regulated Ecosystem Model 2 (REcoM2) at two BGC time-series stations: the Bermuda Atlantic Time-series Study (BATS) and the Dynamique des Flux Atmosphériques en Méditerranée (DYFAMED). Satellite chlorophyll-a concentration data and in situ net primary production data are assimilated to estimate ten selected biogeochemical parameters and the model state. We present convergence and interdependence features of the estimated parameters in relation to the major biological processes and discuss their uncertainties. The major improvements on the parameters involved changes in phytoplankton photosynthesis rate, chlorophyll degradation, and grazing. In general, the change in the estimates of these parameters results in improvements in the model prediction and reduced prediction uncertainty. 

How to cite: Mamnun, N., Völker, C., Vrekoussis, M., and Nerger, L.: Uncertainty in ocean biogeochemical simulation: Application of ensemble data assimilation to a one-dimensional model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3668, https://doi.org/10.5194/egusphere-egu22-3668, 2022.

In this work, we aim to describe atmosphere-ocean coupling through a physically-based stochastic formulation. We adopt the framework of modelling under Location Uncertainty (LU) [Bauer2020a], which is based on a temporal-scale separation and a stochastic transport principle. One important characteristic of such random model is that it conserves the total energy of the resolved flow. This representation has been successfully tested for ocean-only models, such as the barotropic quasi-geostrophic (QG) model [Bauer2020b], the multi-layered QG model [Li2021], as well as the rotating shallow-water model [Brecht2021]. Here, we consider the ocean-atmosphere coupled QG model [Hogg2003]. The LU scheme has been tested for coarse-grid simulations, in which the spatial structure of ocean uncertainty is calibrated from eddy-resolving simulation data while the atmosphere component is parameterized from the ongoing simulation. In other words, the ocean dynamics has a data-driven stochastic component whereas the large-scale atmosphere dynamics is fully parameterized. Two major benefits of the resulting random model are provided on the coarse mesh: it enables us to reproduce the ocean eastward jet and its adjacent recirculation zones; it improves the prediction of intrinsic variability for both ocean and atmosphere components. These capabilities of the proposed stochastic coupled QG model are demonstrated through several statistical criteria and an energy transfers analysis.

References:

• [Bauer2020a] W. Bauer, P. Chandramouli, B. Chapron, L. Li, and E. Mémin. Deciphering the role of small-scale inhomogeneity on geophysical flow structuration: a stochastic approach. Journal of Physical Oceanography, 50(4):983-1003, 2020.
• [Bauer2020b] W. Bauer, P. Chandramouli, L. Li, and E. Mémin. Stochastic representation of mesoscale eddy effects in coarse-resolution barotropic models. Ocean Modelling, 151:101646, 2020.
• [Li2021] Li, L., 2021. Stochastic modelling and numerical simulation of ocean dynamics. PhD Thesis. Université Rennes 1.
• [Brecht2021] Rüdiger Brecht, Long Li, Werner Bauer and Etienne Mémin. Rotating Shallow Water Flow Under Location Uncertainty With a Structure-Preserving Discretization. Journal of Advances in Modeling Earth Systems, 13, 2021MS002492.
• [Hogg2003] A.M. Hogg, W.K. Dewar, P.D. Killworth, J.R. Blundell. A quasi-geostrophic coupled model (Q-GCM). Monthly Weather Review, 131:2261-2278, 2003.

How to cite: Li, L., Mémin, E., Chapron, B., and Lahaye, N.: Quasi-geostrophic coupled model under location uncertainty, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5287, https://doi.org/10.5194/egusphere-egu22-5287, 2022.

Over the last decade, the northeast Pacific experienced strong marine heatwaves (MHWs) that produced devastating marine ecological impacts and received major societal concerns. Here, we assess the link between the well-mixed greenhouse gas (GHG) forcing and the occurrence probabilities of the duration and intensity of the North Pacific MHWs. We investigate whether GHG forcing was necessary for the North Pacific MHWs to occur and whether it is a sufficient cause for such events to continue to repeatedly occur in the 21st Century. To begin with, we apply attribution technique on the long-term SST time series, and detect a region of systematically and externally-forced SST increase -- the long-term warming pool -- co-located with the past notably Blob-like SST anomalies. We further show that the anthropogenic signal has recently emerged from the natural variability of SST over the warming pool, which we attribute primarily to increased GHG concentrations, with anthropogenic aerosols playing a secondary role.

After we demonstrate that the GHG forcing has a dominant influence on the base climate state in the region, we pursue an event attribution analysis for MHWs on a more localized region. Extreme event attribution analysis reveals that GHG forcing is a necessary, but not sufficient, causation for the multi-year persistent MHW events in the current climate, such as that happened in 2014/2015 and 2019/2020. However, the occurrence of the 2019/2020 (2014/2015) MHW was extremely unlikely in the absence of GHG forcing. Thus, as GHG emissions continue to firmly rise, it is very likely that GHG forcings will become a sufficient cause for events of the magnitude of the 2019/2020 record event.

How to cite: Barkhordarian, A., Nielsen, D. M., and Baehr, J.: Greenhouse gas forcing a necessary, but not sufficient, causation for the northeast Pacific marine heatwaves, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6041, https://doi.org/10.5194/egusphere-egu22-6041, 2022.

It has been known for some time that the ocean basins are populated by what is known as ‘‘zonal jets’’, ‘‘deep zonal jets’’, or ‘‘striations’’. Since the oceanic flow is, at least weakly, chaotic, it is not known whether the positions of the jets are ‘‘deterministic’’, that is, entirely determined by external parameters. A number of theories have been proposed to explain them, some of them predicting zonal jets at fixed latitudes and others implying that the positions of the jets are random. To investigate how deterministic the zonal jets are in the eastern North Pacific, a ten-member ensemble of long-term integrations of a semi-global, eddy-resolving ocean general circulation model is analyzed.

The positions of the equatorial jets, even their variability, seem to obey deterministic dynamics and some of the jets in the tropics (5°–15°N) migrate poleward coherently (similarly between ensemble members). The jets in the subtropics (15°–45°N) systematically migrate equatorward but their positions are less coherent; the jets in the subpolar region (45°N–) are random and without systematic migration. Jets near the coast of North and South America tend to have shorter meridional wavelengths than interior ones and those in the northern hemisphere are fairly coherent whereas those in the southern hemisphere seem more random. There are a few quasi-barotropic jets which are anchored to steep bottom topographic features and which also appear to trap shallower counter-flows on their poleward and equatorward flanks.

How to cite: Furue, R., Nonaka, M., and Sasaki, H.: Zonal jets in the eastern North Pacific in an ensemble of eddy-resolving ocean general circulation model runs, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6754, https://doi.org/10.5194/egusphere-egu22-6754, 2022.

Planetary flows and large scale circulation systems are characterised by an interaction between scales that range over several orders of magnitude, with contributions given by mesoscale and submesoscale dynamics. Resolving numerically  such interactions for realistic configuration is, however, far beyond reach. Any large-scale simulation must then rely on parameterizations of the effects of the small scales on  the large scales. In this work, a stochastic parameterization is proposed based on a decomposition of the flow in terms of a smooth-in-time large-scale contribution and a random fast-evolving uncorrelated small-scale part  accounting for  mesoscales and submesoscales unresolved eddies. This  approach, termed modelling under location uncertainty (LU) [4], relies on a stochastic version of Reynolds Transport Theorem to cast physically meaningful conservation principles in this scale-separated framework. Such a scheme has been successfully applied to several large-scale models of the  ocean dynamics [1, 2, 3, 5]. Here a LU version of the  hydrostatic primitive equations is  implemented within the  NEMO community code (https://www.nemo-ocean.eu) with a data-driven approach to establish the spatial correlation of the fast evolving scales. In comparison to a corresponding deterministic counterpart, this stochastic large-scale representation  is shown to improve, in terms of the eastward jet resolution and variabilities, the  flow prediction of an idealized wind forced double gyre circulation. The results are assessed through several statistical criterion as well as an energy transfer analysis [2,5].
[1] W. Bauer, P. Chandramouli, B. Chapron, L. Li, and E. Mémin. Deciphering the
role of small-scale inhomogeneity on geophysical flow structuration: a stochastic approach.
Journal of Physical Oceanography, 50(4):983-1003, 2020.
[2] W. Bauer, P. Chandramouli, L. Li, and E. Mémin. Stochastic representation of
mesoscale eddy effects in coarse-resolution barotropic models. Ocean Modelling, 151:101646,
2020.
[3] Rüdiger Brecht, Long Li, Werner Bauer and Etienne Mémin. Rotating Shallow
Water Flow Under Location Uncertainty With a Structure-Preserving Discretization. Journal of
Advances in Modeling Earth Systems, 13, 2021MS002492.
[4], E. Mémin Fluid flow dynamics under location uncertainty,(2014), Geophysical & Astrophysical Fluid Dynamics, 108, 2, 119–146.
[5] V. Resseguier, L. Li, G. Jouan, P. Dérian, E. Mémin, B. Chapron, (2021), New trends in ensemble forecast strategy: uncertainty quantification for coarse-grid computational fluid dynamics, Archives of Computational Methods in Engineering.

How to cite: Tucciarone, F., Li, L., and Memin, E.: Stochastic data-driven model of mesoscale and submesoscale eddies in gyre circulation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7907, https://doi.org/10.5194/egusphere-egu22-7907, 2022.

The multistability of the Atlantic Meridional Overturning Circulation (AMOC) challenges the predictability of long-term climate evolution. In light of an observed weakening in AMOC strength, it is crucial to study the probabilities of noise-induced transitions between the different competing flow regimes. From a dynamical systems perspective, the phase space of a multistable system can be characterised as a non-equilibrium potential landscape, with valleys corresponding to the different basins of attraction. Knowing the potential, one can infer the statistics and pathways of noise-induced transitions. Particularly, in the weak-noise limit, transition paths lead through special regions of the basin boundaries, called Melancholia states. Recent studies have applied these concepts to climate models of low and intermediate complexity. Here, we investigate the quasi-potential landscape of a three-box model of the AMOC, based on the popular model by Rooth. We analyse noise-induced transitions between the two stable circulation states and elucidate the role of the Melancholia state. Forcing the model with different noise laws, which represent fluctuations caused by different physical processes, we discuss how the properties of transitions change when considering non-Gaussian processes, specifically Lévy noise. Simulated transition rates are related to their theoretical values using the quasi-potential landscape. Our results yield a comprehensive picture of the dynamical properties of an inter-hemispheric three-box AMOC model under stochastic forcing. By relating the deterministic structure of this simple model to the statistics of critical transitions, we hope to build a basis for transferring this approach to more complex models of the AMOC.

How to cite: Börner, R., Lucarini, V., and Serdukova, L.: Dynamical Landscape and Noise-induced Transitions in a Box Model of the Atlantic Meridional Overturning Circulation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8332, https://doi.org/10.5194/egusphere-egu22-8332, 2022.

Mesoscale ocean eddies impact atmosphere-ocean gas exchange, carbon sequestration, and nutrient transport. Studies have attempted to identify trends in eddy activity using satellite altimetry; however, it is difficult to distinguish between robust trends and natural variability within the short observational record. Using a novel climate model that exploits the variable-resolution capabilities of unstructured meshes in the ocean component to concentrate computational resources in eddy-rich regions, we assess global mesoscale eddies and their long-term response to climate change at an unprecedented scale. The modeled results challenge the significance of some trends identified by observational studies, as well as the effectiveness of linear trends in assessing eddy kinetic energy (EKE) change. Some anticipated changes to ocean circulation, such as a poleward shift of major ocean currents and eddy saturation in the Southern Ocean, are reinforced by the modeled EKE changes. Several novel insights regarding the evolution of EKE in a warming world are also proposed, such as a decrease of EKE along the Gulf Stream in unison with weakening Atlantic meridional overturning circulation (AMOC); increasing Agulhas leakage; and accelerating, non-linear increases of EKE in the basins of the Kuroshio Current, Brazil and Malvinas Currents, and the Antarctic Circumpolar Current (ACC).

How to cite: Beech, N., Jung, T., Semmler, T., Rackow, T., Wang, Q., and Danilov, S.: Long-term evolution of eddying oceans in a warming world, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-741, https://doi.org/10.5194/egusphere-egu22-741, 2022.

This study explores the possible drivers of the recent Hadley circulation strengthening in the modern reanalyses. Predominantly, two recent generations of reanalyses provided by the European Centre for Medium-Range Weather Forecasts are used: the fifth-generation atmospheric reanalysis (ERA5) and the interim reanalysis (ERA-Interim). Some results are also evaluated against other long-term reanalyses. To assess the origins of the Hadley cell (HC) strength variability we employ the Kuo-Eliassen (KE) equation. ERA5 shows that both HCs were strengthening prior to 2000s, but they have been weakening or remained steady afterwards. Most of the long-term variability in the strength of the HCs is explained by the meridional gradient of diabatic (latent) heating, which is related to precipitation gradients. However, the strengthening of both HCs in ERA5 is larger than the strengthening expected from the observed zonal-mean precipitation gradient (via Global Precipitation Climatology Project, GPCP). This suggests that the HC strength trends in the recent decades in ERA5 can be explained partly as an artifact of the misrepresentation of latent heating and partly through (physical) long-term variability. To show that the latter is true, we analyze ERA5 preliminary data for the 1950-1978 period, other long-term (e.g. 20th century) reanalyses, and sea surface temperature observational data. This reveals that the changes in the HC strength can be a consequence of the Atlantic multidecadal variability (AMV) and related diabatic and frictional processes, which in turn drive the global HC variability. This work has implications for further understanding of the long-term variability of the Hadley circulation.

How to cite: Zaplotnik, Ž., Pikovnik, M., and Boljka, L.: Recent Hadley circulation strengthening: a trend or multidecadal variability?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3866, https://doi.org/10.5194/egusphere-egu22-3866, 2022.

The global atmospheric circulation determines the local weather and climate. To better understand this circulation and how it may change in a warming world, we separate the atmospheric energy transport by the spatial scale, the quasi-stationary and transient nature, and the latent and dry-static component in the ERA-5 reanalysis and climate-model simulations with EC-Earth. Different to previous studies that distinguish the scale by wave-numbers, here the meso, synoptic and planetary scales are separated at wavelengths below 2000km, between 2-8000km, and above the latter, respectively. The scale (wavelength) of most transient energy transport is around 5000km for all latitudes and is associated with baroclinic, synoptic-scale cyclones. Transient, synoptic-scale waves are the largest contributor to the energy transport at all latitudes outside the tropics, where the meridional overturning circulation is dominant. Planetary-scale waves are both of quasi-stationary and transient character, strongest at latitudes with much orography, and responsible for most of the inter-annual variability of the energy transport. The energy transport associated with mesoscale waves is negligible.

In a warming world, the moisture transport increases everywhere and in all components, however strongest for planetary waves, making dry areas dryer and moist areas moister, and supporting large and long-lasting events that favour floods and droughts. The total energy transport increases at latitudes smaller than 60 degrees, with the main contribution from quasi-stationary, planetary-scale waves, indicating that weather patterns become more persistent. The changing energy transport can be associated both with changing zonal gradients in temperature and with an atmospheric circulation that becomes more effective in transporting energy.

How to cite: Stoll, P., Graversen, R. G., Heiskanen, T. I. H., and Bintanja, R.: Changes in the global atmospheric energy transport separated by spatial scales in a warming world, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5121, https://doi.org/10.5194/egusphere-egu22-5121, 2022.

I use thermodynamics and an Earth system approach to determine how much kinetic energy the atmosphere is physically capable of generating at large scales from the solar radiative forcing.  The work done to generate and maintain large-scale atmospheric motion can be seen as the consequence of an atmospheric heat engine, which is driven by the difference in solar radiative heating between the tropics and the poles.  The resulting motion transports heat, which depletes this differential solar heating and the associated, large-scale temperature difference, which drives this energy conversion in the first place.  This interaction between the thermodynamic driver (temperature difference) and the resulting dynamics (heat transport) is critical for determining the maximum power that can be generated.  It leads to a maximum in the global mean generation rate of kinetic energy of about 1.7 W m^-2, which matches rates inferred from observations of about 2.1 - 2.5 W m^-2 very well.  This represents less than 1% of the total absorbed solar radiation that is converted into kinetic energy. Although it would seem that the atmosphere is extremely inefficient in generating motion, thermodynamics shows that the atmosphere works as hard as it can to generate the energy contained in the winds.  I then show that this view of atmospheric dynamics is essentially the same as a maximised generation rate of Available Potential Energy (APE) for the Lorenz energy cycle, and that it is also consistent with the outcome of the proposed principle of Maximum Entropy Production (MEP) while representing a more physically interpretable approach.  This supports the notion that Earth system processes evolve to and operate near their thermodynamic limit, which permits the use of this constraint to do climate science analytically with less empirical input.

How to cite: Kleidon, A.: How much kinetic energy can the large-scale atmospheric circulation at best generate?, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5417, https://doi.org/10.5194/egusphere-egu22-5417, 2022.

Ocean-atmosphere coupled models predict pronounced weakening of the Pacific Walker Circulation (PWC) with increasing CO₂ concentration due to enhanced tropospheric stability and reduced convective mass overturning. However, current observational results are inconsistent and do not confirm a clear weakening signal. The detection of the signature of increasing CO₂ is in part impeded by substantial internal variability and anthropogenic aerosol forcings. Here we explore the possibility of using a paleoclimatic analogue to understand the contemporary PWC sensitivity to CO₂ changes. We focus on the interval from mid-Piacenzian (MP, 3.3 – 3.0 Ma) to early Pleistocene (~2.4 Ma). The MP had elevated CO₂ concentrations (~400ppm) and geography, topology, and vegetation similar to today. Following the MP global CO₂ and temperature decreased, leading to the intensification of the Northern hemisphere glaciation. We seek to identify potential proxy constraints on model simulated PWC sensitivity to CO₂ forcing by focusing on changes in the hydroclimatology during this time interval. We developed several sets of isotope-tracking enabled CESM version 1.2 simulations, which utilize pre-Industrial and Pliocene boundary conditions, different CO₂ levels, and water tagging of 11 oceanographic regions to track the life cycles of various water species (H216O, H218O and HD16O). Preliminary results show that Pliocene boundary conditions have little impact on the relationship between the CO₂ forcing and the intensity of PWC. The precipitation δD contrast between the eastern and western tropical Pacific, scales well with the PWC strength, suggesting high potential for developing PWC strengths proxy with precipitation isotopic records from both sides of the tropical Pacific. Our ongoing work will further identify physical processes responsible for the simulated precipitation isotopic signals: i.e., whether they reflect changes in the moisture source, moisture transport, or moist convection at the destination. Additionally, prescribed-SST simulations will also be conducted to quantify the isotopic imprints of changing tropospheric instability from SST changes.

How to cite: Mayer, T., Feng, R., and Bhattacharya, T.: Water isotopic imprints of the Pliocene Pacific Walker Circulation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5439, https://doi.org/10.5194/egusphere-egu22-5439, 2022.

The Tibetan Plateau (TP), known as the “World Roof”, has significant influences on hydrological and atmospheric circulation at both regional and global scales. As a result, an adequate understanding of TP climate change is of great importance. In this study, the temporospatial variations of temperature extremes over the TP are investigated based on the station and gridded data provided by China Meteorological Administration (CMA) and the Mann-Kendall test. In addition, the typical large-scale circulations along with the temperature extremes are analyzed using the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis data. It is found that while the frequency of the temperature extremes is observed to have gone through significant variations from 1979 to 2018, the intensity of the temperature extremes has no significant change. On the one hand, the frequency of the warm days and nights is getting higher over the southeastern part and northwestern TP; on the other hand, most area of the eastern TP has witnessed a significant decreasing trend in the frequency of cold days and nights, together suggesting a warming TP. Moreover, the distribution of the long-term changes in the warm days and the cold nights resemble those of the multi-year tendencies of the maximum and minimum temperature. Furthermore, both warm days and nights occur with a significant anti-cyclone over the TP for continuous days, which might allow for more solar radiation arriving at the surface and also favors more adiabatic heating along with the sinking movement of the air parcels. Our results imply a possible linkage between the long-term climate change in the TP, the temperature extremes over the TP, and the large-scale circulations.

How to cite: Tian, Y., Zhong, D., and Kleidon, A.: The variations of temperature extremes over the wintertime Tibetan Plateau from 1979 to 2018, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5897, https://doi.org/10.5194/egusphere-egu22-5897, 2022.

Energy transport in the atmosphere is accomplished by systems of several length scales, from cyclones to Rossby waves. From recently developed Fourier and wavelet based methods it has been found that the planetary component of the latent heat transport affects the Arctic surface temperatures more than its dry-static counterpart and the synoptic scale component of the latent heat transport.  

However, both the Fourier and wavelet based methods require enormous amounts of data and are time consuming to process. The Fourier and wavelet decompositions are computed  from 6 hourly data, throughout the whole vertical column of the atmosphere. The data required are usually only available from reanalysis archives, or possibly from climate model experiments where a goal is to examine the decomposed energy transport. However, the vast CMIP5 and CMIP6 archives are out of reach for the exact computations of the Fourier and wavelet decompositions. Even if all the data were available in the CMIP archives, it would be a computationally, and storage-wise, intensive task to compute the Fourier and wavelet decompositions for a large selection of the CMIP experiments.

Here we suggest a deep-learning approach to approximate the decomposed energy transport from significantly less data than the original methods. The idea is to train a convolutional neural network (CNN) on ERA5 data, where we have already computed the Fourier decomposition of the energy transport. The CNN is trained on data at 850hPa in the atmosphere on a daily temporal resolution. The required data are only a small fraction of the data required to compute the exact Fourier decompositon of the energy transport. Once the CNN is trained, the model is tested on data from the EC-Earth climate model. For EC-Earth we have an ensemble of model runs where the energy transport is decomposed using the Fourier method, hence the CNN may be evaluated on the EC-Earth dataset.

The CNN based energy transport decomposition matches well with the classically computed energy transport from EC-Earth.The CNN captures the mean meridional transport well, and the projected changes from the 1950s to the 2090s in EC-Earth. Additionally the CNN model captures the day to day variability well, as regressions of temperature on the transport from the CNNcomputations and the classical Fourier decomposition are similar. Further we may investigate how the decomposed energy transport changes in a range of CMIP models and experiments

How to cite: Heiskanen, T. I. H. and Graversen, R.: Wave decomposition of energy transport using deep-learning, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7235, https://doi.org/10.5194/egusphere-egu22-7235, 2022.

Atmospheric spatial and temporal variability are closely related with the former being relatively well assessed compared to the latter. New opportunities for understanding the spatio-temporal variability spectrum are offered by coupled high-resolution climate models. However, the models still suffer from significant systematic errors (biases) calling for an approach that assesses circulation variability in relation to biases. Furthermore, biases in simulated variability are often of remote origin; for example, biases in the Atlantic sea-surface temperature in boreal winter may be responsible for changes in simulated variability over Asia.

We present a novel framework for the multivariate, multi-scale variability evaluation in relation to remote biases. Centennial simulations are carried out using a general circulation model PLASIM and a perfect-model framework. Biases in simulated circulation originate from regional errors in the surface forcing by prescribed sea surface temperature (SST). A reference simulation is forced with the monthly SST from ERA-20C reanalyses from January 1900 to December 2010. Sensitivity simulations are forced with the same SST with addition of regional perturbations that mimic the errors in the surface forcing of the atmosphere and lead to systematic errors in the simulated mean state and temporal variance. The erroneous SST is respectively located in tropical basins of Indian ocean, Western Pacific, Central Pacific, Eastern Pacific, and Atlantic, and in extra-tropical areas of North Pacific and North Atlantic.

The bias is the time-averaged difference between the reference and sensitivity simulations. Using the normal-mode function decomposition, the amplitude and phase of the bias can be related to deficiencies in spatial and temporal variance of the two main dynamical regimes: quasi-geostrophic regime and unbalanced circulation. The results show that biases are mainly established in the zonal-mean state and at planetary scales of balanced flow. In boreal winter, the biases at scales with zonal wavenumber k>0 are typically manifested in the barotropic Rossby wave train across the Northern Hemisphere. The structure of tropical biases is that of unbalanced flow, projecting predominantly on the Kelvin wave and the vertical baroclinic structure. The effects of biases on spatio-temporal variability are further investigated in spectral space.

How to cite: Zhao, Y.-B., Lunkeit, F., and Žagar, N.: Bias teleconnections: atmospheric variability associated with biases in remote regions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7317, https://doi.org/10.5194/egusphere-egu22-7317, 2022.

During the boreal summer monsoon, the temperature gradient between land and ocean in the Northern Hemisphere (NH) facilitates large transports of moist air masses towards the land regions, where their convergence causes precipitation. This is associated with an export of net energy (internal, potential, and latent energy) away from the land. On a global scale, there is a tight relationship between the location of the intertropical convergence zone (ITCZ) and the cross-equatorial atmospheric heat transport (AHT) on seasonal, interannual and climate time scales: a more northward cross-equatorial AHT is associated with a displacement of the ITCZ (as defined by precipitation) toward the equator. We further analyse the relationships between cross-equatorial AHT and common streamfunction-based measures of the ITCZ position and width found in the literature. However, it remains unclear whether links between energy transport and the monsoonal precipitation exist at the scale of monsoon regions.

To address this question, we combine data from the European Centre for Medium-Range Weather Forecast (ECMWF) reanalysis ERA5 and Global Precipitation Climatology Project (GPCP-version 2.3) rainfall data. In the annual cycle, the cross-equatorial northward AHT transport peaks in July and the annual net northward cross-equatorial AHT is -0.34 PW (negative sign denotes southward). A regression analysis confirms that the global ITCZ shifts southward when the cross-equatorial AHT is anomalously large, although we demonstrate this mainly happens over the Pacific Ocean. Outside of the Pacific sector, the relationship between cross-equatorial AHT and JJA precipitation is complex. For the West African monsoon region, greater northward cross-equatorial AHT is related to weaker rainfall along the Gulf of Guinea coast, while there is stronger rainfall in the Atlantic Ocean ITCZ. In the Indian sector, anomalous northward AHT is associated with a weak monsoon, marked by strong decreases in precipitation on the Western coast of India and the southern flank of the Himalayas.

In future work, the CMIP6 multi-model dataset will be analysed to examine future projection of AHT and its impact on monsoonal precipitation. The characteristics of the ITCZ will be explored using the same datasets.

How to cite: Awal, M. R., Turner, A., and Ferreira, D.: The relationship between atmospheric heat transport and monsoonal precipitation variability, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7957, https://doi.org/10.5194/egusphere-egu22-7957, 2022.

Oceanic mesoscale eddies contain most of the kinetic energy (KE) in the ocean and therefore play an important role in determining the ocean’s response to future climate scenarios. Oceanic wind-forced internal waves (IWs) are energetic fast motions that contribute substantially to the vertical mixing of water, thereby affecting biogeochemical and climate processes. We study the effects of wind-forced IWs on the KE pathways in high-resolution numerical simulations of an idealized wind-driven channel flow. Using spectral fluxes, we demonstrate that solutions with wind-forced IWs are characterized by a forward KE cascade, whereas solutions without exhibit an inverse KE cascade. We further decompose the flow field into ‘eddy’ and ‘internal wave’ motions using a Helmholtz decomposition and temporal filtering. This allows us to identify three key processes responsible for the reversal in the KE cascade: IW scattering, direct extraction, and stimulated cascade. Each process is quantified and discussed in detail.

How to cite: shaham, M. and Barkan, R.: Eddy-Internal wave decomposition and kinetic energy transfers in high-resolution turbulent channel flow with near-inertial waves, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8284, https://doi.org/10.5194/egusphere-egu22-8284, 2022.

In studying recent climate, changes to atmospheric circulation are often understood as a response to temperature changes. This work instead quantifies the contribution to temperature trends from the atmospheric dynamics, by analysing trends in the ERA5 zonal-mean temperature budget over the satellite era. The results are consistent with several previously highlighted trends in the circulation. In the winter hemisphere, the region of subtropical descent and heating associated with the Hadley cell strengthens on its poleward side, and the deep diabatic heating in the ITCZ intensifies and shifts northward in the northern hemisphere (NH) winter. In keeping with other studies, we find a weakening of the transient eddy heating associated with the NH summer storm tracks. At high northern latitudes, the climatological eddy heating is weakened at low levels; this signal is strongest in NH winter, consistent with the reduced baroclinicity associated with arctic warming. Our work also points towards emerging trends in the transition seasons, SON and MAM, and underlines the importance of circulation changes in understanding trends in atmospheric temperature.

How to cite: Thomas, R., Woollings, T., and Dunstone, N.: Diagnosing the effect of circulation trends on atmospheric temperature, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9166, https://doi.org/10.5194/egusphere-egu22-9166, 2022.

Planetary heat transport can be separated into the oceanic and atmospheric components and plays a major role in shaping the climate. In a climate in equilibrium, the net heat flux at the top of the atmosphere is constant and the rate of change in ocean heat content is negligible. In such conditions, anomalies in the ocean heat transport are accompanied by changes in the atmosphere of the same magnitude but opposite sign [Bjerknes, 1964], known as Bjerknes compensation (BJC). BJC remains a hypothesis since it has not been found in observations due to the length of time series and large errors compared to the observed heat transports. Nevertheless, BJC has a great number of applications in climate sciences, especially in climate predictability. Here we study the BJC in the IPSL-CM6A-LR model and contrast its properties in piControl and abrupt-4xCO2 experiments. In order to address this goal, we characterize the different time scales dependence and explore BJC dynamics linked to the Atlantic Meridional Overturning Circulation (AMOC) changes and Intertropical Convergence Zone (ICTZ) shifts. We improve the BJC diagnostics by introducing the Turner Angle between ocean and atmospheric anomalies:  this allows both to quantify the BJC strength and to distinguish the contributions of ocean and atmosphere. In the IPSL-CM6A-LR model, we found two regions of stronger BJC corresponding to the mid-latitudes storm track region and the Marginal Ice Zone. The strong forcing in abrupt-4xCO2 leads to an AMOC reduction of 60% compared to the control experiment and dampening of the centennial signal of heat transport, however, the role of BJC in AMOC recovery in this experiment remains unclear. The ocean dominates BJC at decadal and centennial timescales both in natural and forced experiments. BJC is associated with the co-variability between AMOC strength and ITCZ location. Other forms of heat compensation are found in this model, such as a Bjerknes-like compensation between Atlantic and Indo-Pacific centennial ocean heat transport in the South Hemisphere.  

How to cite: Povea Pérez, Y., Guilyardi, E., Ferster, B., and Fedorov, A.: Diagnosing differences in Bjerknes compensation in the IPSL-CM6A-LR model, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9501, https://doi.org/10.5194/egusphere-egu22-9501, 2022.

GCMs robustly project a delay in the timing of the global monsoon onset and tropical precipitation intensification with warming. However, a closer look at the response of different monsoon regions shows less consistency. To better understand how monsoons will respond to a warming climate, with a particular focus on the timing of monsoon onset, we use a hierarchy of climate models, starting from idealized aquaplanet simulations all the way to CMIP6 projections, to identify the robust and uncertain changes and investigate the underlying mechanisms. Our idealized work covers two sets of simulations: 1) aquaplanet runs with a uniform mixed layer depth (MLD) in a wide range of climates, from colder to warmer than the current climate, and 2) simulations with an idealized saturated zonally symmetric continent extending from 10^oN to the North Pole in a similar range of colder to warmer climates. Monsoon onset is determined using a change point detection method on the cumulative moisture flux convergence (MFC) (or net precipitation), which robustly links monsoon onset to changes in the large-scale monsoonal circulation. The idealized uniform MLD aquaplanet simulations show a robust progressive delay of monsoon onset, consistent with results reported in the literature. Analyses of the atmospheric energy budget suggest this delay is due to the increased atmospheric latent heat capacity with warming. Interestingly, this delay is not evident in the simulations with the idealized saturated continent. Mechanisms are explored by analyzing changes in the energetics and dynamics of the tropical circulation and related monsoonal precipitation. CMIP6 projections in different monsoon regions are investigated to determine if mechanisms exposed in the idealized simulations can shed some light on the differing monsoon onset responses in more complex climate models.

How to cite: Bordoni, S. and Hui, K.: Monsoon Onset Response to Warming in Idealized GCM and CMIP6 Simulations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10666, https://doi.org/10.5194/egusphere-egu22-10666, 2022.

Anthropogenic climate change in the Southern Hemisphere is driven by two forces, the greenhouse gas emissions and the stratospheric ozone levels. In the past, the combination of increasing greenhouse gas emissions and ozone depletion over Antarctica worked together leading to an increase in sea surface temperatures and a poleward shift of the storm tracks. With the ozone expected to recover by mid-century, however, the greenhouse gas and ozone forces will oppose each other and the changes observed previously will begin to weaken or reverse. The role the greenhouse gases and the ozone recovery play in the Southern Hemisphere climate system are examined using Community Climate System Model, version 4 (CCSM4) coupled ocean eddy-parameterized and eddy-resolving simulations. The greenhouse gas emissions and ozone levels are specified independently to represent the two extremes, peak greenhouse gas emissions and a recovered ozone. In the eddy-parameterized simulations, the ozone recovery signal is found to be stronger on average. In the case of the eddy-resolving simulations, however, the increase in greenhouse gases is stronger especially in eddy-rich regions like western boundary current regions and the Antarctic Circumpolar Current. The volume transport is also calculated for the Southern Hemisphere western boundary currents (Agulhas, Brazil, and East Australian Currents) and the two external forces are found to not play an important role in the mean transports, but the model resolution does. The eddy-parameterizing simulations yield a more accurate transport than the eddy-resolving simulations. The eddy-resolving simulations however, are able to resolve a more accurate eddy field in these highly active regions. The relationship between the sea surface temperatures in the western boundary currents and regional precipitation over nearby South Africa, South America, and Australia is then analyzed in greater detail.

How to cite: Daher, H. and Kirtman, B.: The impact of greenhouse gas and ozone forcing on the Southern Hemisphere climate system, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10915, https://doi.org/10.5194/egusphere-egu22-10915, 2022.

The poleward shift of the Hadley cell (HC) edge by global warming is widely documented. However, its reversibility to CO₂ removal remains unknown. By conducting a climate model experiment where CO₂ concentration is systematically increased and then decreased in time, this study shows that a poleward-shifted HC edge in warm climate returns equatorward as CO₂ concentration decreases. It is also shown that the rate significantly differs between the two hemispheres. While the southern HC edge monotonically changes with CO₂ concentration, the northern HC edge exhibits a super recovery, locating on the equatorward side of the present-climate HC edge when CO₂ concentration returns to the present level. Such a super recovery is associated with the hysteresis of the North Atlantic sea surface temperature. Our findings suggest that the HC edge change may result in the super recovery of subtropical dryness in the northern hemisphere except California.

How to cite: Choi, Y.-J., Kim, S.-Y., Son, S.-W., An, S., Yeh, S.-W., Kug, J.-S., Min, S.-K., and Shin, J.: Super recovery of the Hadley Cell edge to the CO2 removal, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10935, https://doi.org/10.5194/egusphere-egu22-10935, 2022.

Baroclinic instability in the mid-latitudes is a significant component of the climate system, as it is associated with the meridional transport of a large amount of energy and momentum. Hence, the ability of climate models to correctly predict the properties of atmospheric circulation in that latitudinal band is a very important requirement. This study aims to estimate the power content of the atmospheric phenomena typical of mid-latitudes, such as baroclinic perturbations, and to understand how seasonal forecasts can be practically used to assess energy transfer in the atmosphere. We compare the Southern Hemisphere mid-latitude winter variability of the long-range forecasting system SEAS5 with the ERA5 reanalysis. Both datasets are produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). The analysis is carried out by computing the Hayashi spectra of the 500-hPa geopotential height field. Both the reanalysis and the seasonal forecast show a series of peaks in the spectral region of eastward-traveling waves, which corresponds to the high frequency-high wavenumber domain. We quantify the amount of energy released from the atmosphere by calculating the Baroclinic Amplitude Index. Results suggest that the seasonal forecasts correctly reflect the variability of the geopotential height power spectra in the Southern Hemisphere, with some minor discrepancies related to the sub-daily variability, which is not correctly discriminated. However, the energy associated with the baroclinic activity is well represented by the seasonal forecast in the Southern Hemisphere, where the orographic effect is negligible compared to the Northern Hemisphere. This work is carried out as part of the European FOCUS-Africa project, which develops innovative and sustainable climate services in the Southern African Development Community (SADC) region.

How to cite: Trentini, L., Dal Gesso, S., Dell'Aquila, A., and Petitta, M.: Spectral analysis of the Southern Hemisphere atmospheric variability to assess the role of baroclinic instability in seasonal forecasts, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11288, https://doi.org/10.5194/egusphere-egu22-11288, 2022.

Oceanic mesoscale motions including eddies, meanders, fronts, and filaments comprise a dominant fraction of oceanic kinetic energy and contribute to the redistribution of tracers in the ocean such as heat, salt, and nutrients. This reservoir of mesoscale energy is regulated by the conversion of potential energy and transfers of kinetic energy across spatial scales. Whether and under what circumstances mesoscale turbulence precipitates forward or inverse cascades, and the rates of these cascades, remain difficult to directly observe and quantify despite their impacts on physical and biological processes. Here we use global observations to investigate the seasonality of surface kinetic energy and upper ocean potential energy. We apply spatial filters to along-track satellite measurements of sea surface height to diagnose surface eddy kinetic energy across 60-300 km scales. A geographic and scale dependent seasonal cycle appears throughout much of the mid-latitudes, with eddy kinetic energy at scales less than 60 km peaking 1-4 months before that at 60-300 km scales. Spatial patterns in this lag align with geographic regions where the conversion of potential to kinetic energy are seasonally varying. In mid-latitudes, the conversion rate peaks 0-2 months prior to kinetic energy at scales less than 60 km. The consistent geographic patterns between the seasonality of potential energy conversion and kinetic energy across spatial scale provide observational evidence for the inverse cascade, and demonstrate that some component of it is seasonally modulated. Implications for mesoscale parameterizations and numerical modeling are discussed.

How to cite: Steinberg, J., Cole, S., Drushka, K., and Abernathey, R.: Seasonality of the Mesoscale Inverse Cascade as Inferred from Global Scale-Dependent Eddy Energy Observations, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13178, https://doi.org/10.5194/egusphere-egu22-13178, 2022.

Precipitation changes are notoriously highly variable, and climate models misplace circulation features, making it difficult to evaluate if mechanisms of precipitation change are well reproduced in climate models. Several methods have been developed to detect externally forced precipitation change tracking circulation features rather than specific locations. For example, analysis of monthly ascending and descending regions in reanalysis show the increase of rainfall in ascending regions. Analysis of wet and dry regions in GPCP blended data shows that if the locations of wet and dry regions are tracked from month to month then trends over the past 3-4 decades can be attributed to a combination of human influences and the recovery from drying associated with the Mount Pinatubo eruption in wet regions. In response to volcanic eruptions, wet regions tend to dry and dry regions may get wetter, indicating a reduced moisture transport to the wettest regions of the tropics under strong volcanic forcing. However, this is also impacted by the hemispheric characteristics of the eruptions. 

How to cite: Hegerl, G., Ballinger, A., and Schurer, A.: Towards attributing change in tropical and subtropical precipitation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13547, https://doi.org/10.5194/egusphere-egu22-13547, 2022.

Atmospheric rivers (ARs) are filaments of extensive water vapor transport in the lower troposphere. They are important triggers of heavy rainfall events, contributing to more than 50% of the rainfall sums in some regions along the western coast of North America. ARs play a crucial role in the distribution of water, but can also cause natural and economical damage by facilitating heavy rainfall. Here, we investigate the large-scale spatio-temporal synchronization patterns of heavy rainfall triggered by ARs over the western coast and the continental regions of North America.

For our work, we employ daily ERA5 rainfall estimates at a spatial resolution of 0.25°x0.25° latitude and longitude which we threshold at the 95^th percentile to obtain binary time series indicating the absence or presence of heavy rainfall. Subsequently, we separate periods with ARs and periods without ARs and investigate the differing spatial synchronization pattern of heavy rainfall. To establish that our results are not dependent on the chosen AR catalog, this is conducted in two different ways: first based on a recently published catalog by Gershunov et al. (2017) , and second based on a catalog constructed using the IPART algorithm (Xu et al, 2020). For both approaches, we subsequently utilize event synchronization and a complex network framework to reveal distinct spatial patterns of heavy rainfall events for periods with and without active ARs. Using composites of upper-level meridional wind, we attribute the formation of the rainfall synchronization patterns to well-known atmospheric circulation configurations, whose intensity scales with the strength of the ARs. Furthermore, we demonstrate that enhanced AR activity is going in hand with a suppressed seasonal shift of the characteristic meridional wind pattern. To verify and illustrate how small changes of the high-level meridional wind affect the distribution of heavy rainfall, we, additionally, perform a case study focusing on the boreal winter.

Our results indicate the strong sensitivity of the intensity, location, frequency, and pattern of synchronized heavy rainfall events related to ARs to small changes in the large-scale circulation.

How to cite: Wolf, F., Vallejo-Bernal, S. M., Boers, N., Marwan, N., Traxl, D., and Kurths, J.: Spatio-temporal synchronization of heavy rainfall events triggered by atmospheric rivers in North America, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2993, https://doi.org/10.5194/egusphere-egu22-2993, 2022.

In Denmark, about half of the agricultural land is artificially drained. These drainage systems have a significant effect on the hydrological system. Knowledge about the spatio-temporal distribution of drain flow is crucial to understand aspects such as groundwater recharge, streamflow partitioning and nutrient transport. Still, quantification of drain flow at regional and large scale remains a major challenge: Data on the distribution of the installed subsurface drainage system are scarce, as are measurements of drain flow. Large-scale simulations of drain with physically-based hydrological models are challenged by scale, as drain flow is controlled by small-scale variations in groundwater depth often beyond the model resolution. Purely data-driven models can struggle representing the complex controls behind drain flow.

Here, we suggest a metamodel approach to obtain a more accurate estimate of generated drain flow at high spatial resolution of 10 m, combining physically-based with data-driven models. Our variable of interest is drain fraction, defined as the ratio between drain flow and recharge per grid cell, which is an indicator for flow partitioning between drain and recharge to deeper groundwater.

First, we setup distributed, integrated groundwater models at 10 m grid resolution for 28 Danish field-scale drain catchments with observations of drain flow timeseries. A joint calibration of these field-scale models against observed drain flow resulted in an average KGE of above 0.5. Subsequently, the simulated drain fractions from the field-scale models were used to train a decision tree machine learning algorithm. This metamodel uses various mappable covariates (topography and geology-related) available at high resolution for all of Denmark. The metamodel then is used to predict drain fractions, within its limits of applicability, across relevant areas of Denmark with significant drain flow outside of the field-scale models.

Eventually, the predicted drain fractions are intended to inform national, large-scale physically based hydrological models: An improved representation of drain can, for example, make those models more fit to improve national targeted nitrate regulation.

How to cite: Schneider, R., Mahmood, H., Frederiksen, R. R., Højberg, A. L., and Stisen, S.: Prediction of drain flow fraction at high spatial resolution by combining physically based models and machine learning, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3694, https://doi.org/10.5194/egusphere-egu22-3694, 2022.

Soil environments are naturally governed by a multitude of interdependent chemical, biological, and physical processes that define their macro-state. In the context of farming these features are further complemented and affected by anthropogenic activities (ploughing, fertilizing, use of pesticides, etc.) that systematically aim to change soil and plant environments to enhance yield, but often with unforeseen detrimental effects (biodiversity loss, erosion, etc.). Assessing strategies for sustainable environmental management is therefore a highly challenging task that is often accompanied by incomplete knowledge of systemic feedback mechanisms and a lack of continuous and reliable data. 

To address this issue, we investigate the use of complexity metrics from information theory to gain insights about underlying patterns of multivariate soil systems and their potential implications for time series analysis. Here we apply existing methods for the processing and analysis of similar systems, we verify current theories about the dynamics and mechanisms of ecological processes in time and study innate interactions between separate components. Thereby, we will use available agricultural datasets that display a wide range of soil properties and explore several notions of complexity approaches, such as entropy measures (e.g., Permutation entropy, transfer entropy, Shannon entropy) and the Hurst exponent. Characteristic features will be highlighted that can be used to enhance time series prediction accuracy and systemic soil functions understanding.

How to cite: Corpaci, L. C., Raubitzek, S., and Mallinger, K.: Information theory approach for enhancing time series analysis and predictability of soil environments, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4076, https://doi.org/10.5194/egusphere-egu22-4076, 2022.

Abstract

Flood frequency curves are usually fitted to short time series of observations, leading to great uncertainties mainly for high return periods. However, reliable estimates are required for designing and assessing safety of hydraulic infrastructure, such as bridges and dams. Therefore, flood frequency analyses based on instrumental data collected at gauging stations can be improved by incorporating available information about historical floods before the beginning of the systematic period. This study presents how to identify and integrate all the information available, in order to improve flood frequency curve estimates. The Cuevas de Almanzora Dam located in southeast Spain is selected as case study.

The Cuevas de Almanzora Dam catchment has an area of 2122 km² with a mean annual precipitation of 316 mm. However, daily precipitation can be higher, such as 600 mm for the 1973 flood event. Flood data are available at a gauging station located in the River Almanzora upstream of the dam, with a draining catchment of 1850 km². The systematic period is 1963-2008 with information about 36 annual maximum floods. The largest flood in the 20^th century was recorded at the gauging station in 1973. A two-dimensional (2D) hydrodynamic model of the River Almanzora was calibrated with such information.

Historical information about floods has been collated from local newspapers, books, chronicles, research papers, photographs, national archives of historical floods, and municipal archives. The three largest floods in the River Almanzora between 1830 and 1963 were identified, extending the systematic period to a total period of 191 years. Information about water depths and flood extensions at different cross sections of the River Almanzora were collected. The 2D hydrodynamic model was used to estimate the peak discharges in such historical flood events.

After the end of the systematic period, the hydrograph of the great 2012 flood event was estimated from the data recorded at the Cuevas de Almanzora reservoir. A rainfall-runoff model was calibrated in the catchment with 1-h precipitation data to estimate the flood hydrograph at the gauging station.

The five historical floods that exceed the perception threshold in the period 1830-2020 were integrated with the annual maximum floods extracted from the systematic data, using five techniques to incorporate historical information in the flood frequency curve. The Generalized Extreme Value (GEV) and the Two-Component Extreme Value (TCEV) distribution functions were considered. The best fit was selected considering the accuracy and the uncertainty of estimates by a stochastic procedure. Flood quantiles for the highest return periods triple the estimates obtained by using only the systematic data.

The methodology proposed can improve the reliability of flood quantile estimates, mainly in arid regions where the lack of information about the rare greatest flood, which can exceed several times the mean magnitude of floods in the systematic period, can lead to strong underestimates for the highest return periods that are needed to design and assess the safety of hydraulic infrastructure.

Acknowledgments: This research has been supported by the project SAFERDAMS (PID2019-107027RB-I00) funded by the Spanish Ministry of Science and Innovation.

How to cite: Fernandez-Palomares, M. A. and Mediero, L.: Integrating historical information, systematic data, and rainfall-runoff modelling to improve flood frequency estimates, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4933, https://doi.org/10.5194/egusphere-egu22-4933, 2022.

Beach cast is a material deposited on beaches after being washed up by storm (or tidal movement). The composition of beach cast usually includes seagrass or algae fragments, wracks of land plants and other materials of natural origin, (anthropogenic) marine litter, including plastic debris and microplastics. Beach casts monitoring is of current interest for beach management and maintenance of the sandy shores for recreational purposes, tracing marine litter transport and dispersion, evaluating environmental contamination by microplastiсs.

Large patches of marine debris appear on beaches after stormy weather. However, little is known about the sea state that precedes the formation of beach casts. From an observer's point of view, beach casts occur at random locations along the coast at unpredictable times. They may even be washed back to the sea at some time later. This work aims to disclose characteristic features of temporal variations of surface wave field parameters, which lead to beach cast formation.

Results of incidental surveys of the northern coast of the Sambia Peninsula, stretching from west to east in the southeastern part of the Baltic Sea, were analyzed. The presence of beach cast (at one or more locations) was observed during 234 days of 2011-2021. Some of the observations were performed during or shortly after the ending of the beaching process. Field information was collated with a freely available re-analysis database on surface waves (http://marine.copernicus.eu). Surface wave spectrum parameters were picked up from the database at the geographical point corresponding to the coastal zone's open-sea limit. Elements of Bayesian analysis were applied to overcome the lack of information on the very time of the beach casts formation and/or the unknown duration of the beaching process.

The analysis shows the values of significant wave height, peak period, and wave direction, which occurred before the beach cast appearance more often than follows from the overall time statistics ("climate"). A separate analysis of only recently formed beach casts made it possible to determine the evolution of wave spectrum parameters during the beaching process. Data suggests that most of the beach cast events on this coast are preceded by waves caused by cyclone passages from the northern direction.

Data analysis is carried out by I.I., with the support of the Russian Science Foundation, grant No 21-77-00027. Beach surveys are carried out by E.E. voluntarily and with partial support from IO RAS state assignment.

How to cite: Isachenko, I. and Esiukova, E.: Analysis of wind wave statistics preceding beach cast events on the southeastern shore of the Baltic Sea (Kaliningrad region): preliminary results, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5690, https://doi.org/10.5194/egusphere-egu22-5690, 2022.

Process-based hydrological models seek to represent the dominant hydrological processes in a catchment. However, due to unavoidable incompleteness of knowledge, the construction of “fidelius” process-based models depends largely on expert judgment. We present a systematic approach that treats models as hierarchical assemblages of hypotheses (conservation principles, system architecture, process parameterization equations, and parameter specification), which enables investigating how the hierarchy of model development decisions impacts model fidelity. Each model development step provides information that progressively changes our uncertainty (increases, decreases, or alters) regarding the input-state-output behavior of the system. Following the principle of maximum entropy, we introduce the concept of “minimally restrictive process parameterization equations—MR-PPEs,” which enables us to enhance the flexibility with which system processes can be represented, and to thereby investigate the important role that the system architectural hypothesis (discretization of the system into subsystem elements) plays in determining model behavior. We illustrate and explore these concepts with synthetic and real-data studies, using models constructed from simple generic buckets as building blocks, thereby paving the way for more-detailed investigations using sophisticated process-based hydrological models. We also discuss how proposed MR-PPEs can bridge the gap between current process-based modeling and machine learning. Finally, we suggest the need for model calibration to evolve from a search over “parameter spaces” to a search over “function spaces.”

How to cite: Gharari, S., Gupta, H., Clark, M., Hrachowitz, M., Fenicia, F., Matgen, P., and Savenije, H.: Understanding the Information Content in the Hierarchy of Model Development Decisions: Learning From Data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6761, https://doi.org/10.5194/egusphere-egu22-6761, 2022.

The consequences of ever-increasing human interference with freshwater systems, e.g., through land-use and climate changes, are already felt in many regions of the world, e.g., by shifts in freshwater availability and partitioning between green (evapotranspiration) and blue (runoff) water fluxes around the world. In this study, we have developed a machine learning (ML) model for the possible prediction of green-blue water flux partitioning (WFP) under different climate, land-use, and other landscape and hydrological catchment conditions around the world. ML models have shown relatively high predictive performance compared to more traditional modelling methods for several tasks in geosciences. However, ML is also rightly criticized for providing theory-free “black-box” models that may fail in predictions under forthcoming non-stationary conditions. We here address the ML model interpretability gap using Shapley values, an explainable artificial intelligence technique. We also assess ML model predictability using a dissimilarity index (DI). For ML model training and testing, we use different parts of a total database compiled for 3482 hydrological catchments with available data for daily runoff over at least 25 years. The target variable of the ML model is the blue-water partitioning ratio between average runoff and average precipitation (and the complementary, water-balance determined green water partitioning ratio) for each catchment. The predictor variables are hydro-climatic, land-cover/use, and other catchment indices derived from precipitation and temperature time series, land cover maps, and topography data. As a basis for the ML modelling, we also investigate and quantify (through data averaging over moving sub-periods of different time lengths) a minimum temporal aggregation scale for water flux averaging (referred to as the flux equilibration time, T_eq) required to reach a stable temporal average runoff (and evapotranspiration) fraction of precipitation in each catchment; for 99% of catchments, T_eq is found to be ≤2 years, with longer T_eq emerging for catchments estimated to have higher ratio R_gw/R_avg, i.e., higher groundwater flow contribution (R_gw) to total average runoff (R_avg). The cubist model used for the ML modelling yields a Kling-Gupta efficiency of 0.86, while the Shapley values analysis indicates mean annual precipitation and temperature as the most important variables in determining the WFP, followed by average slope in each catchment. A DI threshold is further used to label new data points as inside or outside the ML model area of applicability (AoA). Comparison between test data points outside and inside the AoA reveals which catchment characteristics are mostly responsible for ML model loss of predictability. Predictability is lower for catchments with: larger T_eq and R_gw/R_avg; higher phase lag between peak precipitation and peak temperature over the year; lower forest and agricultural land fractions; and aridity index much higher or much lower than 1 (implying major water or energy limitation, respectively). Identifying such predictability limits is crucial for understanding, and facilitating user awareness of the applicability and forecasting ability of such data-driven ML modelling under different prevailing and changing future hydro-climatic, land-use, and groundwater conditions.

How to cite: Althoff, D. and Destouni, G.: Partitioning of green-blue water fluxes around the world: ML model explainability and predictability, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8321, https://doi.org/10.5194/egusphere-egu22-8321, 2022.

Discerning the dynamics of complex systems in a mathematically rigorous and physically consistent manner is as fascinating as intimidating of a challenge, stirring deeply and intrinsically with the most fundamental Physics, while at the same time percolating through the deepest meanders of everyday life.

The socio-natural coevolution in hydroclimate dynamics is an example of that, exhibiting a striking articulation between governing principles and free will, in a stochastic-dynamic resonance that goes way beyond a reductionist dichotomy between deterministic and probabilistic approaches and between physical principles and information technologies.

Subjacent to the conceptual and operational interdisciplinarity of that challenge, lies the simple formal elegance of a “lingua franca” for communication with Nature. This emerges from the innermost mathematical core of Information Physics articulating the wealth of insights and flavours from frontier natural, social and technical sciences in a coherent, integrated manner.

Communicating thus with Nature, we equip ourselves by developing formal innovative methodologies and technologies to better appreciate and discern complexity in articulation with expert knowledge. Thereby opening new pathways to assess and predict elusive non-recurrent phenomena such as irreversible geophysical transformations and extreme hydro-meteorological events in a coevolutionary climate.

Our novel advances will be shared across the formal, structural and functional theory of the Information Physics of Coevolutionary Complex Systems, along with the analysis, modelling and decision support in crucial matters afflicting our environment and society, with special emphasis onto hydroclimatic problems.

In an optic of operational empowerment, some of our flagship initiatives will be addressed such as Earth System Dynamic Intelligence and Quantum Information Technologies in the Earth Sciences (QITES) on a synergy among our information physical and quantum technological developments.

The articulation between these flagships leverages our proprietary synergistic quantum gravitational and electrodynamic QITES constellation from deep undersea to outer space to take the pulse of our planet, ranging from high resolution 4D sensing and computation to unveiling early warning signs of critical transitions and extreme events.

How to cite: Perdigão, R. A. P. and Hall, J.: Deciphering Hydroclimatic Complexity with Information Physics and Quantum Technologies, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8372, https://doi.org/10.5194/egusphere-egu22-8372, 2022.

The observed retreat of mountain glaciers on a global scale promotes the formation and growth of glacial lakes across newly exposed ice-free areas. In mainland Norway, this process drives the rise in glacial lake outburst floods (GLOFs), posing a considerable threat to people and infrastructure  downstream. Moreover, many glacial lakes are used as reservoirs for hydropower production and thus represent an important energy source, emphasizing the need for continuous monitoring of glacial lake life cycles.

Remote sensing is currently the most efficient technique for tracking changes in glacial lakes, understanding their responses to climate change and observing lakes prone to GLOFs. Recent advances in machine learning techniques have presented new opportunities to automatize glacial lake mapping over large areas. For the first time, this study presents a Norway-wide reconstruction of glacial lake changes through the last three decades using  machine learning algorithms and long-term satellite observations. It contrasts the performance of two classification methods - maximum likelihood  classification (MLC) and support vector machine (SVM) - to outline glacial lakes and study their evolution using the Landsat series and Sentinel-2 images.

This study zooms into the pros and cons of each classification method and satellite product through the prism of glacial lake processes occurring over  disparate temporal and spatial scales - from lake formation, growth and dissociation from the proximal glaciers to the aftermath of rapid GLOF events. Based on this analysis, I conclude that the recognition skills of supervised classification methods largely depend on the quality of satellite images and careful selection of training samples. Some of the factors that adversely affect the classification results are unfavourable weather conditions such as  cloud, snow and ice cover, image disturbances through atmospheric corrections and shadows on slopes that lead to misclassifications. Regardless of higher spatial and temporal resolution, Sentinel imagery has not revealed significant advantages over Landsat but has shown a potential for their  complementary use to continue glacial lake observations in the future. The performance of SVM is clearly superior to MLC, but it is difficult to use over  large spatial scales, at least in the form it is currently implemented in ENVI.

How to cite: Moghaddam, G., Andreassen, L. M., and Rogozhina, I.: Life cycles of glacial lakes in Norway: Insights from machine learning algorithms on Landsat series and Sentinel-2, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10119, https://doi.org/10.5194/egusphere-egu22-10119, 2022.

The fact that both the Lorenz 1963 and 1969 models suggest finite predictability is well-known. However, it is less known that mechanisms (i.e., sensitivities) within both models that lead to finite predictability are different. Additionally, the mathematical and physical relationship between these two models has not been fully documented. New analyses along with literature review are performed here to provide insights on the similarities and differences for these two models. The models represent different physical systems, one for convection and the other for barotropic vorticity. From theperspective of mathematical complexities, the Lorenz 1963 (L63) model is limited-scale and nonlinear; and the Lorenz 1969 (L69) model is closure-based, physically multiscale, mathematically linear, and numerically ill-conditioned. The former possesses a sensitive dependence of solutions on initial conditions, known as the butterfly effect, and the latter contains numerical sensitivities due to an ill-conditioned matrix with a large condition number (i.e., a large variance of growth rates).

Here, we illustrate that the existence of a saddle point at the origin is a common feature that produces instability in both systems. Within the chaotic regime of the L63 nonlinear model, unstable growth is constrained by nonlinearity, as well as dissipation, yielding time varying growth rates along an orbit, and, thus, a dependence of (finite) predictability on initial conditions. Within the L69 linear model, multiple unstable modes at various growth rates appear, and the growth of a specific unstable mode (i.e., the most unstable mode during a finite time interval) is constrained by imposing a saturation assumption, thereby yielding a time varying system growth rate. Both models have been interchangeably applied for qualitatively revealing the nature of finite predictability in weather and climate. However, only single type solutions were examined (i.e., chaotic and linearly unstable solutions for the L63 and L69 models, respectively), and the L69 system is ill-conditioned and easily captures numerical instability. Thus, an estimate of the predictability limit using either of the above models, with or without additional assumptions (e.g., saturation), should be interpreted with caution and should not be generalized as an upper limit for predictability of the atmosphere.

How to cite: Shen, B.-W., Pielke, Sr., R., and Zeng, X.: One Saddle Point and Two Types of Sensitivities Within the Lorenz 1963 and 1969 Models, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10890, https://doi.org/10.5194/egusphere-egu22-10890, 2022.

Soil moisture affects gross primary production through two pathways. First, directly through
drought stress and second, indirectly through temperature via evaporative cooling of the near-
surface atmospheric layer. Because it is not possible to disentangle these effects experimentally
at a biome level, Humphrey et al. (2021) has used Earth system model experiments in which soil
moisture is fixed to its seasonal cycle and evaluated the effects on gross primary production. In
contrast, we aim to use causal modeling to infer impacts directly from observation. To predict the
effects of soil moisture anomalies on gross primary production, we extend existing causal mod-
eling frameworks to cover situations where two variables influence one other. A major challenge
in applying causal modeling here lies in the bidirectional relationship between soil moisture and
temperature via evapotranspiration. On one hand, higher temperature leads to higher evapotran-
spiration and thus lower soil moisture. On the other hand, lower soil moisture leads to lower evap-
otranspiration and thus higher temperatures. Therefore, neither soil moisture nor temperature can
be adequately modeled as a function of the other. To address this challenge, we extend existing
causal modeling frameworks to account for these situations where the variables are not functions
of each other but are determined by equilibrium. We show that our method identifies the correct
links between variables in synthetic data. We further evaluate whether our new approach is con-
sistent with the results of Humphrey et al. (2021) based on idealized counterfactual experiments
using Earth system models. To this end, we use the control runs of the models to directly predict
the results of the idealized counterfactual experiment as proof-of-concept. Finally, we apply our
method to observations and determine the direct and indirect effect of soil moisture anomalies on
gross primary production.

References:
Vincent Humphrey, Alexis Berg, Philippe Ciais, Pierre Gentine, Martin Jung, Markus Reichstein,
Sonia I Seneviratne, and Christian Frankenberg. Soil moisture–atmosphere feedback dominates
land carbon uptake variability. Nature, 592(7852):65–69, 2021.

How to cite: Reimers, C., Winkler, A., Humphrey, V., and Reichstein, M.: Disentangling direct and indirect soil moisture effects onecosystem carbon uptake with Causal Modeling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11148, https://doi.org/10.5194/egusphere-egu22-11148, 2022.

The water environment is an important carrier of material processes, in which a large number of biochemical reactions and energy transmission processes occur. High-frequency water quality observation can help us understand the dynamics of solute transport in the water environment. The information-theoretic approaches to system dynamics are receiving more and more attention that it reveals the new laws and support board applications. Configuration entropy (H^*) is one of the derivative indexes that originated from information entropy, which was first introduced in 1994 to describe the disorder in random morphologies. It can reflect the complexity of the system under different space or time resolutions. Researchers have analyzed the characteristics of configuration entropy in some of the environment scenarios, such as spatial arrangement of rainfall. In this paper, we analyzed the space structure of river basin water quality dynamic system under the network topology of rivers, together with the time structure of water quality dynamic system. We calculated the configuration entropy of six water quality parameter data from four monitoring stations at Potomac River in two dimensions of time and space with topological treatment of river water system map. We arranged the high-frequency water quality time series according to different time slices to form a two-dimensional pixel image for calculating configuration entropy and the variation under different time resolutions. Results show that with the increasing length of time slice (from 1 day to 9 days), except pH and turbidity, the configuration entropy curve of other parameters has only one peak (1 day, 1.5 days, 2 days) to the valley (2.5 days and later), which confirms a hypothesis that the configuration entropy will not have a valley when the length of time grid is significantly greater than the width. When the length of the time slice is more than 2.5 days, even if the length of the time slice is increased, the overall shape of configuration entropy curve does not change significantly, suggesting that the configuration entropy of specific water quality parameters did not show temporal heterogeneity in a long-time period observation. We also assumed that temporal fractal phenomena exist in some water quality parameters consistent with previous studies. More analysis is in progress.

How to cite: Pang, T., Jiang, J., Wang, P., Zheng, Y., and Zheng, T.: Configuration entropy analysis of river water quality dynamics under fine time resolution and network topology, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12346, https://doi.org/10.5194/egusphere-egu22-12346, 2022.

Understanding the connections in the dynamics of water quality at different locations in a catchment is important for catchment studies and watershed management. Complex network science provides effective ways to uncover connections and patterns in catchment water quality dynamics. This study  investigates the spatial connections in each of five water quality indexes (Chloride, Dissolved oxygen, pH, Total nitrogen, and Total organic carbon) and flow rate in the Chesapeake Bay basin, USA.High-resolution data (five minutes) from 120 water quality monitoring stations are analyzed. 1) The clustering coefficient (CC) and degree distribution methods are employed to examine the connections and identify the type of the water quality networks. The results indicate that the networks of water quality parameters are  scale-free. The power-law (γ) values of for the networks of Chl, DO, flow rate, pH, TN, TOC are 0.74, 0.67, 0.37, 2.0, 0.57 and 1.2, respectively. 2) Monte Carlo simulation of degree distributions and clustering coefficients (CC) shown that all water quality parameters present a decrease in the CC along with the turn down of the threshold of correlation coefficient (R), but the R threshold for DO and flow rate was 0.9. Other water quality parameters showed a sharp decline in the range of correlation coefficient (R) of 0.3-0.6, show a gentle decrease, and then decrease sharply, with an inverse s-curve. 3) All the WQ parameters show stable patterns of CC versus R, for different sizes of networks, arrived by randomly reducing the number of nodes (i.e. stations) of the networks. This seems to indicate that the pattern is an internal systemically feature of the networks, regardless of the node selected for analysis. The variations of CC values for the different stations in the networks  with different R values also help identify the “heat area” of the whole catchment, which  has some nodes with stable large CC. For the different water quality parameters, the heat area is basically the same, except for pH and TN for which the area is much smaller. The present findings on the characteristics, patterns, and drivers of water quality dynamics in catchments have important implications for water quality studies, especially in large networks of monitoring stations.

How to cite: Wen, Q., Jiang, J., and Sivakumar, B.: A complex network perspective on catchment water quality dynamics: characteristics, pattern, and drivers, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12588, https://doi.org/10.5194/egusphere-egu22-12588, 2022.

Extreme drought has a strong socio-economic impact on the human environment, especially where surface and ground water supplies are significantly reduced due to reduced stream flow, reduced hydroelectric generation, and increased ground water pumping for agricultural and human consumption. This reduction will likely increase in the future as drought is expected to increase in the United States due to global warming and climate change. However, identifying drought is problematic due to the lack of standardized classification or reliable methods for drought prediction. Recently, machine learning techniques have been applied to drought indices to identify drought features and for risk assessment. For this work, we utilize unsupervised machine learning (ML) computational algorithms to identify drought characteristics with a new drought index based on vapor pressure deficit (VPD). The Standardized VPD Drought Index (SVDI) is used to cluster points with common features to characterize spatial and temporal drought characteristics. The SVDI is calculated with the NASA’s Land Surface Assimilation System (NLDAS) data from 1990-2010. Several ML cluster techniques (e.g. HMM, k_means, BIRCH, DBSCAN) are applied to the SVDI to identify known short and long term drought events. Optimized techniques will be applied to downscaled global climate models (e.g. CCSM4, GFDL-ESM2G, and HadGEM2-ES) based on the 8.5 Representative Concentration Pathway (RCP8.5). From the space-time clustering algorithm, we will extract the spatiotemporal information for each identified event as a means of determining the probability of each type of event under global warming in the future.

How to cite: Gamelin, B., Rao, V., Bessac, J., and Altinakar, M.: Machine Learning Methods with the Standardized VPD Drought Index to Identify and Assess Drought in the United States, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13100, https://doi.org/10.5194/egusphere-egu22-13100, 2022.

The public and scientific discourse on how to mitigate the COVID-19 pandemic is often focused on the impact of individual protective measures, in particular on vaccination. In view of changing virus variants and conditions, however, it seems not clear if vaccination or any other protective measure alone may suffice to contain the transmission of SARS-CoV-2. Accounting for both droplet and aerosol transmission, we investigated the effectiveness and synergies of vaccination and non-pharmaceutical interventions like masking, distancing & ventilation, testing & isolation, and contact reduction as a function of compliance in the population. For realistic conditions, we find that it would be difficult to contain highly contagious SARS-CoV-2 variants by any individual measure. Instead, we show how multiple synergetic measures have to be combined to reduce the effective reproduction number (Re) below unity for different basic reproduction numbers ranging from the SARS-CoV-2 ancestral strain up to measles-like values (R0 = 3 to 18).

Face masks are well-established and effective preventive measures against the transmission of respiratory viruses and diseases, but their effectiveness for mitigating SARS-CoV-2 transmission is still under debate. We show that variations in mask efficacy can be explained by different regimes of virus abundance (virus-limited vs. virus-rich) and are related to population-average infection probability and reproduction number. Under virus-limited conditions, both surgical and FFP2/N95 masks are effective at reducing the virus spread, and universal masking with correctly applied FFP2/N95 masks can reduce infection probabilities by factors up to 100 or more (source control and wearer protection).

Masks are particularly effective in combination with synergetic measures like ventilation and distancing, which can reduce the viral load in breathing air by factors up to 10 or more and help maintaining virus-limited conditions. Extensive experimental studies, measurement data, numerical calculations, and practical experience show that window ventilation supported by exhaust fans (i.e. mechanical extract ventilation) is a simple and highly effective measure to increase air quality in classrooms. This approach can be used against the aerosol transmission of SARS-CoV-2. Mechanical extract ventilation (MEV) is very well suited not only for combating the COVID19 pandemic but also for sustainably ventilating schools in an energy-saving, resource-efficient, and climate-friendly manner.  Distributed extract ducts or hoods can be flexibly reused, removed and stored, or combined with other devices (e.g. CO2 sensors), which is easy due to the modular approach and low-cost materials (www.ventilationmainz.de).

The scientific findings and approaches outlined above can be used to design, communicate, and implement efficient strategies for mitigating the COVID-19 pandemic.

References:

Cheng et al., Face masks effectively limit the probability of SARS-CoV-2 transmission, Science, 372, 1439, 2021, https://doi.org/10.1126/science.abg6296 

Klimach et al., The Max Planck Institute for Chemistry mechanical extract ventilation (MPIC-MEV) system against aerosol transmission of COVID-19, Zenodo, 2021, https://doi.org/10.5281/zenodo.5802048  

Su et al., Synergetic measures to contain highly transmissible variants of SARS-CoV-2, medRxiv, 2021, https://doi.org/10.1101/2021.11.24.21266824

How to cite: Pöschl, U., Cheng, Y., Helleis, F., Klimach, T., and Su, H.: Efficiency and synergy of simple protective measures against COVID-19: Masks, ventilation and more, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1024, https://doi.org/10.5194/egusphere-egu22-1024, 2022.

The time evolution of the Covid-19 death cases exhibits several distinct episodes since the start of the pandemic early in 2020. We propose an analysis of several Southern Europe regions that highlights how the beginning of each episode correlates with a strong increase in the concentrations level of pollution particulate matter smaller than 2.5 µm (PM2.5). Following the original PM2.5 spike, the evolution of the Covid-19 spread depends on the (partial) lockdowns and vaccinate races, thus the highest level of confidence in correlation can only be achieved when considering the beginning of each episode. The analysis is conducted for the 2020-2022 period at different locations: the Lombardy region (Italy), where we consider the mass concentrations measurements obtained by air quality monitoring stations (µg.m^-3), and the cities of Paris (France), Lisbon (Portugal) and Madrid (Spain) using in-situ measurements counting particles (cm^-3) in the 0.5-2.5 µm size range obtained with hundreds of mobile aerosol counters. The particle counting methodology is more suitable to evaluate the possible correlation between PM pollution and Covid-19 spread because we can better estimate the concentration of the submicronic particles compared with a mass concentration measurement methodology which would result in skewed results due to larger particles. Very fine particles of lesser than one micron go deeper inside the body and can even cross the alveolar-capillary barrier, subsequently attacking most of the organs through the bloodstream, potentially triggering a pejorative systemic inflammatory reaction. The rapidly increasing number of deaths attributed to the covid-19 starts between 2 weeks and one month after PM events that often occur in winter, which is coherent with the virus incubation time and its lethal outcome. We suggest that the pollution by the submicronic particles alters the pulmonary alveoli status and thus significantly increase the lungs susceptibility to the virus.

How to cite: Renard, J.-B., Delaunay, G., Poincelet, E., and Surcin, J.: Possible effect of the particulate matter (PM) pollution on the Covid-19 spread in southern Europe, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1890, https://doi.org/10.5194/egusphere-egu22-1890, 2022.

In the past two years, numerous advances have been made in the ability to predict the progress of COVID19 epidemics.  Basic forecasting of the health state of a population with respect to a given disease is based on the well-known family of SIR models (Susceptible Infected Recovered). The models used in epidemiology were based on deterministic behavior, so the epidemiological picture tomorrow depends exclusively on the numbers recorded today. The forecasting shortcomings of the deterministic SEIR models previously used in epidemiology were difficult to highlight before the advent of COVID19  because epidemiology was mostly not concerned with real-time forecasting.  From the first wave of COVID19 infections, the limitations of using deterministic models were immediately evident: to use them, one should know the exact status of the population and this knowledge was limited by the ability to process swabs. Futhermore, there is an intrinsic variability of the dynamics which depends on age, sex, characteristics of the virus, variants and vaccination status. 

Our main contribution was to define a SEIR model that assumes these parameters as constants could not be used for reliable predictions of COVID19 pandemis and that more realistic forecasts can be obtained by adding fluctuations in the model. The fluctuations in the dynamics of the virus induced by these factors do not just add variaiblity around the deterministic solution of the SIR models, the also introduce another timing of the pandemics which influence the epidemic peak. With our model we have found that even with a basic reprdocution number R_t less than 1 local epidemic peaks can occur that resume over a certain period of time. 

Introducing noise and uncertainty allows  to define a range of possible scenarios, instead of making a single prediction. This is what happens when we replace the deterministic approach, with a probabilistic approach. The probabilistic models used to predict the progress of the Covid-19 epidemic are conceptually very similar to those used by climatologists, to imagine future environmental scenarios based on the actions taken in the present.  As human beings we can intervene in both systems. Based on the choices we will make and the fluctuations of the systems, we can predict different responses. In the context of the emergency that we faced, the collaboration between different scientific fields was therefore fundamental, which, by comparing themselves, were able to provide more accurate answers. Furthermore, a close collaboration has arisen between epidemiologists and climatologists. A beautiful synergy that can give a great help to society in a difficult moment.

References

-Faranda, Castillo, Hulme, Jezequel, Lamb, Sato & Thompson (2020). Chaos: An Interdisciplinary Journal of Nonlinear Science, 30(5), 051107.

-Alberti & Faranda (2020).  Communications in Nonlinear Science and Numerical Simulation, 90, 105372.

-Faranda & Alberti (2020). Chaos: An Interdisciplinary Journal of Nonlinear Science, 30(11), 111101.

-Faranda, Alberti, Arutkin, Lembo, Lucarini. (2021).  Chaos: An Interdisciplinary Journal of Nonlinear Science, 31(4), 041105.

-Arutkin, Faranda, Alberti, & Vallée. (2021). Chaos: An Interdisciplinary Journal of Nonlinear Science, 31(10), 101107.

How to cite: Faranda, D.: How concepts and ideas from Statistical and Climate physics improve epidemiological modelling of the COVID 19 pandemics, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2801, https://doi.org/10.5194/egusphere-egu22-2801, 2022.

Recurrent epidemic outbreaks such as the seasonal flu and the ongoing COVID-19 are disastrous events to our societies both in terms of fatalities, social and educational structures, and financial losses. The difficulty to control COVID-19 spread in the last two years has brought evidence that basic mechanisms of transmission for such pathogens are still poorly understood.

             Three different routes of virus transmission are known: direct contact (e.g. through handshakes) and indirect contact through fomites; ballistic droplets produced by speaking, sneezing or coughing; and airborne transmission through aerosols which can also be produced by normal breathing. The latter route, which has long been ignored, even by the World Health Organization during the COVID-19 pandemics, now appears to play the predominant role in the spread of airborne diseases (e.g. Chen et al., 2020).

             Further scientific research thus needs to be conducted to better understand the mechanistic processes that lead to inactivate airborne viruses, as well as the environmental conditions which favour these processes. In addition to modelling and epidemiological studies, chamber experiments, where viruses are exposed to various types of humidity, temperature and/or UV dose, offer to simulate everyday life conditions for virus transmission. However, the current standard instrumental solutions for virus aerosolization to the chamber and sampling from it use high fluid forces and recirculation which can cause infectivity losses (Alsved et al., 2020) and also do not compare to the relevant production of airborne aerosol in the respiratory tract.

             In this study, we utilized two of the softest aerosolization and sampling techniques: the sparging liquid aerosol generator (SLAG, CH Technologies Inc., Westwood, NJ, USA), which forms aerosol from a liquid suspension by bubble bursting, thus mimicking natural aerosol formation in wet environments (e.g. the respiratory system but also lakes, sea, toilets, etc…); and the viable virus aerosol sampler (BioSpot-VIVAS, Aerosol Devices Inc., Fort Collins, CO, USA), which grows particle via water vapour condensation to gently collect them down to a few nanometres in size. We characterized these systems with particle sizers and biological analysers using non-pathogenic viruses such as bacteriophages suspended in surrogate lung fluid and artificial saliva. We compared the size distribution of produced aerosol from these suspensions against similar distributions generated with standard nebulizers, and assess the ability of these devices to produce aerosol that much more resembles that produced in human exhaled air. We also assess the conservation of viral infectivity with the VIVAS vs. conventional biosamplers.

Acknowledgment

We acknowledge the IVEA project in the framework of SINERGIA grant (Swiss National Science Foundation)

References

Alsved, M., Bourouiba, L., Duchaine, C., Löndahl, J., Marr, L. C., Parker, S. T., Prussin, A. J., and Thomas, R. J. (2020): Natural sources and experimental generation of bioaerosols: Challenges and perspectives, Aerosol Science and Technology, 54, 547–571.

Chen, W., Zhang, N., Wei, J., Yen, H.-L., and Li, Y. (2020): Short-range airborne route dominates exposure of respiratory infection during close contact, Building and Environment, 176, 106859.

How to cite: Motos, G., Violaki, K., Schaub, A., David, S., Kohn, T., and Nenes, A.: Improving the conservation of virus infectivity during airborne exposure experiments, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3690, https://doi.org/10.5194/egusphere-egu22-3690, 2022.

COVID-19 effects on measurements of the Earth Magnetic Field in the urbanized area of Brest (Brittany, France)

Jean-François OEHLER¹, Sylvain LUCAS¹, Alexandre LEON¹, André LUSVEN¹, Gildas DELACHIENNE¹

¹Shom (Service Hydrographique et Océanographique de la Marine), Brest, France

Since September 2019, Shom’s Magnetic Station (SMS) has been deployed in the north neighbourhoods of the medium-sized city of Brest (Brittany, France, about 210,000 inhabitants). SMS continuously measures the intensity of the Earth Magnetic Field (EMF) with an absolute Overhauser sensor. The main goal of SMS is to derive local external variations of the EMF mainly due to solar activity. These variations consist of low and high parasitic frequencies in magnetic data and need to be corrected. Magnetic mobile stations or permanent observatories are usually installed in isolated areas, far from human activities and electromagnetic effects. It is clearly not the case for SMS, mainly for practical reasons of security, maintenance and data accessibility. However, despite its location in an urbanized area, SMS stays the far western reference station for processing marine magnetic data collected along the Atlantic and Channel coasts of France.

The corona pandemic has had unexpected consequences on the quality of measurements collected by SMS. For example, during the French first lockdown between March and May 2020, the noise level significantly decreased of about 50%. Average standard deviations computed on 1 Hz-time series over 1 min. periods fell from about 1.5 nT to 0.8 nT. This more stable behavior of SMS is clearly correlated with the drop of human activities and traffic in the city of Brest.

Keywords: Shom’s Magnetic Station (SMS), Earth Magnetic Field, COVID19.

How to cite: Oehler, J.-F., Leon, A., Lucas, S., Lusven, A., and Delachienne, G.: COVID-19 effects on measurements of the Earth Magnetic Field in the urbanized area of Brest, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3936, https://doi.org/10.5194/egusphere-egu22-3936, 2022.

Economic activities and the associated emissions have significantly declined during the 2019 novel coronavirus (COVID-19) pandemic, which has created a natural experiment to assess the impact of the emitted precursor control policy on ozone (O₃) pollution. In this study, we utilized comprehensive satellite, ground-level observations, and source-oriented chemical transport modeling to investigate the O₃ variations during the COVID-19 pandemic in China. Here, we found that the significant elevated O₃ in the North China Plain (40%) and Yangtze River Delta (35%) were mainly attributed to the enhanced atmospheric oxidation capacity (AOC) in these regions, associated with the meteorology and emission reduction during lockdown. Besides, O₃ formation regimes shifted from VOC-limited regimes to NO_x-limited and transition regimes with the decline of NO_x during lockdown. We suggest that future O₃ control policies should comprehensively consider the effects of AOC on the O₃ elevation and coordinated regulations of the O₃ precursor emissions.

How to cite: Wang, P., Zhu, S., and Zhang, H.: Comprehensive Insights Into O3 Changes During the COVID-19 From O3 Formation Regime and Atmospheric Oxidation Capacity, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4170, https://doi.org/10.5194/egusphere-egu22-4170, 2022.

In the last few decades, Nature-based Solutions (NBS) has become widely considered a sustainable development strategy for the development of urban environments. Assessing the performances of NBS is significant for understanding their efficiency in addressing a large range of natural and societal challenges, such as climate change, ecosystem services and human health. With the rapid onset of the COVID-19 pandemic, the inner relationship between humans and nature becomes apparent. However, the current catchment management mainly focuses on reducing hydro-meteorological and/or climatological risks and improving urban climate resilience. This single-dimensional management seems insufficient when facing epidemics, and multi-dimensional management (e.g., reduce zoonosis) is necessary. With this respect, policymakers pay more attention to NBS. Hence, it is significant to increase the connectivity of the landscape to improve the ecosystem services and reduce the health risks from COVID-19 with the help of NBS.

This study takes the Guyancourt catchment as an example. The selected catchment is located in the Southwest suburb of Paris, with a total area of around 5.2 km². The ArcGIS software is used to assess the patterns of structural landscape connectivity, and the heterogeneous spatial distribution of current green spaces over the catchment is quantified with the help of the scale-independent indicator of fractal dimension. To quantify opportunities to increase landscape connectivity over the catchment, a least-cost path approach to map potential NBS links urban green spaces through vacant parcels, alleys, and smaller green spaces. Finally, to prioritise these potential NBS in multiscale, a new scale-independent indicator within the Universal Multifractal framework is proposed in this study.

The results indicated that NBS can effectively improve the connectivity of the landscape and has the potential to reduce the physical and mental risks caused by COVID-19. Overall, this study proposed a scale-independent approach for enhancing the multiscale connectivity of the NBS network in urban areas and providing quantitative suggestions for on-site redevelopment.

How to cite: Qiu, Y., Tchiguirinskaia, I., and Schertzer, D.: Nature-based Solutions in actions: improving landscape connectivity during the COVID-19, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5126, https://doi.org/10.5194/egusphere-egu22-5126, 2022.

The Coronavirus (COVID-19) epidemic, which was first reported in December 2019 in Wuhan, China, has been becoming one of the most important public health issues worldwide. Previous studies have shown the importance of weather variables and air pollution in the transmission or prognosis of infectious diseases, including, but not limited to, influenza and severe acute respiratory syndrome (SARS). In the early stage of the COVID-19 epidemic, there was intense debate and inconsistent results on whether environmental factors were associated with the spread and prognosis of COVID-19. Therefore, our team conducted a series studies to explore the associations between atmospheric parameters (temperature, humidity, UV radiation, particulate matters and nitrogen dioxygen) and the COVID-19 (transmission ability and prognosis) at the early stage of the COVID-19 epidemic with data in early 2020 in China and worldwide. Our results showed that meteorological conditions (temperature, humidity and UV radiation) had no significant associations with cumulative incidence rate or R₀ of COVID-19 based on data from 224 Chinese cities, or based on data of 202 locations of 8 countries before March 9, 2020, suggesting that the spread ability of COVID-19 among public population would not significantly change with increasing temperature or UV radiation or changes of humidity. Moreover, we found that particulate matter pollution significantly associated with case fatality rate (CFR) of COVID-19 in 49 Chinese cities based on data before April 12, 2020, indicating that air pollution might exacerbate negative prognosis of COVID-19. Our studies provided an environmental perspective for the prevention and treatment of COVID-19.

How to cite: Meng, X., Yao, Y., Wang, W., and Kan, H.: The associations between environmental factors and COVID-19: early evidence from China, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5150, https://doi.org/10.5194/egusphere-egu22-5150, 2022.

The COVID-19 lockdowns worldwide provided a prospect to evaluate the impacts of restricted movements and emissions on air quality. In this study, we analyze the data obtained from the ground-based observation stations for six air pollutants (PM₁₀, PM_2.5, CO, NO₂, O₃ and SO₂) and meteorological parameters from March 25th to May 31st in 22 cities representative of five regions of India and from March 16th to May 14th in 21 districts of Finland from 2017 to 2020. The NO₂ concentrations dropped significantly during all phases apart from East India's exception during phase 1. O₃ concentrations for all four phases in West India reduced significantly, with the highest during Phase 2 (~38%). The PM_2.5 concentration nearly halved across India during all phases except South India, where a very marginal reduction (2%) was observed during Phase 4. SO₂ (~31%) and CO (~41%) concentrations also reduced noticeably in South India and North India during all the phases. The air temperature rose by ~10% (average) during all the phases across India when compared to 2017-2019. In Finland, NO₂ concentration reduced substantially in 2020. Apart from Phase 1, the concentrations of PM₁₀ and PM_2.5 reduced markedly in all the Phases across Finland. Also, O₃ and SO₂ concentrations stayed within the permissible limits in the study period for all four years but were highest in 2017 in Finland, while the sulfurous compounds (OSCs) levels increased during all the phases across Finland. The changes in the mobility patterns were also assessed and were observed to have reduced significantly during the lockdown. The benefits in the overall mortality due to the reduction in the concentrations of PM_2.5 have also been estimated for India and Finland. Therefore, this research illustrates the effectiveness of lockdown and provides timely policy suggestions to the regulators to implement interventions to improve air quality.

How to cite: Sharma, S., Heibati, B., Suneja, J., and Kota, S. H.: The Effects of COVID-19 Lockdown on Air Quality and Health in India and Finland, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9213, https://doi.org/10.5194/egusphere-egu22-9213, 2022.

Since 2020, countries around the world have implemented various interventions in response to a global public health crisis. The interventions included restrictions on mobility, promotion of working from home and the limiting of local and international travel. These, along with other behavioural changes from people in response to the crisis affected various sources of air pollution, not least the transport sector. Whilst the method through which these changes were implemented is not something to be repeated, understanding the effects of the changes will help direct policy for further improving air quality. 

We analysed NO_x, O₃ and PM_2.5 data from many 100s of air quality monitoring sites in urban areas around the world, and examined 2020 in relation to the previous 5 years. The data were examined alongside mobility metrics to contextualise the magnitude of changes and were viewed through the lens of World Health Organisation guidelines as a metric to link air quality changes with human health. Interestingly, reductions in polluting activities did not lead to wholesale improvements in air quality by all metrics due to the more complex processes involved with tropospheric O₃ production.

How to cite: Drysdale, W., Stapleton, C., and Lee, J.: Changes in Global Urban Air Quality due to Large Scale Disruptions of Activity, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9812, https://doi.org/10.5194/egusphere-egu22-9812, 2022.

Defining optimal COVID-19 mitigation strategies remains at the top of public health agendas around the world. It requires a better understanding and refined modeling of the intrinsic dynamics of the epidemic. The common root of most models of epidemics is a cascade paradigm that dates to their emergence with Bernoulli and d’Alembert, which predated Richardson’s famous quatrain on the cascade of atmospheric dynamics. However, unlike other cascade processes, the characteristic times of a cascade of contacts that spread infection and the corresponding rates are believed to be independent on the cascade level. This assumption prevents having cascades of scaling contamination.

In this presentation, we theoretically argue and empirically demonstrate that the intrinsic dynamics of the COVID-19 epidemic during the phases of growth and decline, is a cascade with a rather universal scaling, the statistics of which differ significantly from those of an exponential process. This result first confirms the possibility of having a higher prevalence of intrinsic dynamics, resulting in slower but potentially longer phases of growth and decline. It also shows that a fairly simple transformation connects the two phases. It thus explains the frequent deviations of epidemic models rather aligned with exponential growth and it makes it possible to distinguish an epidemic decline from a change of scaling in the observed growth rates. The resulting variability across spatiotemporal scales is a major feature that requires alternative approaches with practical consequences for data analysis and modelling. We illustrate some of these consequences using the now famous database from the Johns Hopkins University Center for Systems Science and Engineering.

Due to the significant increase over time of available data, we are no longer limited to deterministic calculus. The non-negligible fluctuations with respect to a power-law can be easily explained within the framework of stochastic multiplicative cascades. These processes are exponentials of a stochastic generators Γ(t), whose stochastic differentiation remains quite close to the deterministic one, basically adding a supplementary term σdt to the differential of the generator. When the generator Γ(t) is Gaussian, σ is the “quadratic variation”. Extensions to Lévy stable generators, which are strongly non-Gaussian, have also been considered. To study the stochastic nature of the cascade generator, as well as how it respects the above-mentioned symmetry between the phases of growth and decline, we use the universal multifractals. They provide the appropriate framework for joint scaling analysis of vector-valued time series and for introducing location and other dependencies. This corresponds to enlarging the domain, on which the process and its generator are defined, as well as their co-domain, on which they are valued. These clarifications should make it possible to improve epidemic models and their statistical analysis.

More fundamentally, this study points out to a new class of stochastic multiplicative cascade models of epidemics in space and time, therefore not limited to compartments. By their generality, these results pave the way for a renewed approach to epidemics, and more generally growth phenomena, towards more resilient development and management of our urban systems.

How to cite: Tchiguirinskaia, I. and Schertzer, D.: Scaling Dynamics of Growth Phenomena: from Epidemics to the Resilience of Urban Systems, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11475, https://doi.org/10.5194/egusphere-egu22-11475, 2022.

There have been a series of sessions on the generic theme of “Covid-19 and Geosciences” on the occasion of AGU, AOGS and EGU conferences, since 2020 including during the first lockdown that required a very fast adaptation to unprecedented health measures. We think it is interesting and useful to have an overview of these sessions and try to capture what could be the lessons to learn.

To our knowledge, the very first such session was the Great e-Debate “Epidemics, Urban Systems and Geosciences” (https://hmco.enpc.fr/news-and-events/great-e-debate-epidemics-urban-systems-and-geosciences-invitations-and-replays/). It was virtually organised with the help of the UNESCO UniTwin CS-DC (Complex Systems Digital Campus) thanks to its expertise in organising e-conferences long before the pandemic and the first health measures. This would not have been possible without the strong personal involvement of its chair Paul Bourgine. It was held on Monday 4th May on the occasion of the 2020 EGU conference, which became virtual under the title “EGU2020: Sharing Geoscience Online” (4-8 May 2020). The Great e-Debate did not succeed in being granted as an official session of this conference, despite the fact that the technology used (Blue Button) by the Great e-Debate was much more advanced. Nevertheless, it was clearly an extension of the EGU session ITS2.10 / NP3.3: “Urban Geoscience Complexity: Transdisciplinarity for the Urban Transition”. 

Thanks to a later venue (7-11 December 2020) and the existence of a GeoHealth section of the AGU, the organisation of several regular sessions for the 2020 Fall Meeting was easier. For EGU 2021 (19-30 April 2021), a sub-part of the  inter- transdisciplinary sessions ITS1 “Geosciences and health during the Covid pandemic”, a Union Session US “Post-Covid Geosciences” and a Townhall meeting TM10 “Covid-19 and other epidemics: engagement of the geoscience communities” were organised. A brief of the special session SS02 “Covid-19 and Geoscience” of the (virtual) 18th Annual Meeting of AOGS (1-6 August 2021) is included in the proceedings of this conference (in press). 

We will review materials generated by these sessions that rather show a shift from a focus on the broad range of scientific responses to the pandemic, to which geoscientists could contribute with their specific expertise (from data collection to theoretical modelling), to an expression of concerns about the broad impacts on the geophysical communities that appear to be increasingly long-term and constitute a major transformation of community functioning (e.g., again data collection, knowledge transfer).

How to cite: Schertzer, D., Dimri, V., and Fraedrich, K.: Geophysicists facing Covid-19, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11584, https://doi.org/10.5194/egusphere-egu22-11584, 2022.

The COVID-19 pandemic has brought forth the question of the need for draconian interventions before concrete evidence for their need and efficacy is presented. Such interventions could be critical if necessary for avoiding threats, or a threat in themselves if harms caused by the intervention are significant.

The interdisciplinary nature of such issues as well as the unpredictability of various local responses considering their potential for global impact further complicate the question.

The study aims to review the available evidence and discuss the problem of weighting the predictability of interventions vis-à-vis their intended results against the limits of knowability regarding complex non-linear systems and thus the predictability in non-interventionist approaches.

How to cite: Chiotinis, M., Dimitriadis, P., Illiopoulou, T., Mamassis, N., and Koutsoyiannis, D.: To act or not to act. Predictability of intervention and non-intervention in health and environment, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11747, https://doi.org/10.5194/egusphere-egu22-11747, 2022.

How to cite: Alberti, T. and Faranda, D.: COVID-19 waves: intrinsic and extrinsic spatio-temporal dynamics over Italy, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12302, https://doi.org/10.5194/egusphere-egu22-12302, 2022.

Black carbon (BC) not only warms the atmosphere but also affects human health. The nationwide lockdown due to the COVID-19 pandemic led to a major reduction in human activity during the past thirty years. Here, the concentration of BC in the urban, urban-industry, suburb, and rural areas of a megacity Hangzhou were monitored using a multi-wavelength Aethalometer to estimate the impact of the COVID-19 lockdown on BC emissions. The citywide BC decreased by 44% from 2.30 μg/m³ to 1.29 μg/m³ following the COVID-19 lockdown period. The source apportionment based on the Aethalometer model shows that vehicle emission reduction responded to BC decline in the urban area and biomass burning in rural areas around the megacity had a regional contribution of BC. We highlight that the emission controls of vehicles in urban areas and biomass burning in rural areas should be more efficient in reducing BC in the megacity Hangzhou.

How to cite: Li, W. and Xu, L.: Responses of concentration and sources of black carbon in a megacity during the COVID-19 pandemic, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12907, https://doi.org/10.5194/egusphere-egu22-12907, 2022.

How to cite: Ghil, M.: Time-dependent forcing in the geosciences and in epidemiology, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13522, https://doi.org/10.5194/egusphere-egu22-13522, 2022.

Standard epidemic models based on compartmental differential equations are investigated under continuous parameter change as external forcing. We show that seasonal modulation of the contact parameter superimposed upon a monotonic decay needs a different description from that of the standard chaotic dynamics. The concept of snapshot attractors and their natural distribution has been adopted from the field of the latest climate change research. This shows the importance of the finite-time chaotic effect and ensemble interpretation while investigating the spread of a disease. By defining statistical measures over the ensemble, we can interpret the internal variability of the
epidemic as the onset of complex dynamics—even for those values of contact parameters where originally regular behaviour is expected. We argue that anomalous outbreaks of the infectious class cannot die out until transient chaos is presented in the system. Nevertheless, this fact becomes apparent by using an ensemble approach rather than a single trajectory representation. These findings are applicable generally in explicitly time-dependent epidemic systems regardless of parameter values and time scales.

How to cite: Kovács, T.: How can contemporary climate research help understand epidemic dynamics? -- Ensemble approach and snapshot attractors, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-13534, https://doi.org/10.5194/egusphere-egu22-13534, 2022.

As the climate warms, the hydrological cycle is expected to intensify. Also, in response to climate warming, hydrologic sensitivity is a major concern for the coming decades. Here, we aim to understand the relationship between hydroclimate and temperature variability during the past. The periods selected for investigation are the Mid-Miocene Climate Optimum (MMCO), the Eemian Interglacial (EI) Stage, the Last Glacial Maximum, the Heinrich and Dansgaard–Oeschger Events, the Bølling-Allerød, the Younger Dryas, the 8.2 ka event, the Medieval Climate Anomaly, and the Little Ice Age. In general, the proxy records suggest that the hydrological cycle is intensified under warmer climate conditions and weakened over colder periods. However, the spatial signals are not uniform worldwide. For instance, during the MMCO and EI, the global temperature was higher than the pre-industrial time; some regions were wetter, (northern Eurasia and Sahara Arabian desert), while others were more arid (Argentina, Bolivia, and Africa). Therefore, the hypothesis “a warmer climate is a wetter climate” could be considered as a simplified pattern of regional changes as a result of global warming. The reason is that the water cycle response is spatiotemporally not similar. Due to its wide distribution, hydroclimate variability is difficult to quantify on a regional, continental, and global scale. In this context, investigation of paleo-hydroclimatic changes, specifically during the warm periods, could provide relevant insights into the present and future climate.

How to cite: Pratap, S. and Markonis, Y.: Evaluation of hydrological cycle intensification in response to temperature variability, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1157, https://doi.org/10.5194/egusphere-egu22-1157, 2022.

How to cite: Thompson, D. W. and Li, J.: Widespread changes in surface temperature persistence under climate change, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1326, https://doi.org/10.5194/egusphere-egu22-1326, 2022.

The agreement between simulated and reconstructed multidecadal to centennial climate variability has improved over the past decades. However, significant disagreements still exist, especially at regional scale. In the Southern Ocean, both reconstructions and climate models display large variability at those timescales but models fail in reproducing some key elements such as the centennial variability in the strength of the westerly winds inferred from various types of proxy data. Data assimilation combines in an optimal way information from proxy data and climate models. It can help in identifying the cause of such model-data mismatch by improving the reconstructions as well as by testing the compatibility of those reconstructions with model physics or between different types of proxy data. Two examples will be discussed here. The first one focuses on the shift in the westerly winds between the 14^th and 16^th century, showing that it is clear in reconstructions based on classical statistical methods and on data assimilation but it is not simulated in models without data assimilation. In the second example, we will discuss the deep ocean convection and open ocean formation in the Southern Ocean that induce large multi-decadal to centennial variability in some global models while it is totally absent in many others. We will check how data assimilation can be used to test the validity of the simulations and to determine which model behavior is the most realistic. 

How to cite: Goosse, H., Dalaiden, Q., and Lyu, Z.: Analyzing centennial variability in the Southern Ocean using data assimilation, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1530, https://doi.org/10.5194/egusphere-egu22-1530, 2022.

Himalayan mountain region lying in the northern part of Indian sub-continent is among those zones which bears the most ecologically sensitive environments and is also a repository of biodiversity, fresh water storage and ecosystem services. Over the last three decades, land transformation related to exploitative land uses is among the main drivers of changing snow cover, vegetation cover and productivity in western Himalayas region. In a region where field-based research is challenging due to heterogenous relief and high altitude, quantifying the changes in temperature pattern using Remote Sensing Techniques can provide essential information regarding variating trends in different elements relating to temperature. This paper studies the trend analysis of changing temperature patterns using SWAT data (1979–2014) over Uttarakhand Himalayas and its association with altitudinal gradient. This paper investigates the trends in maximum (T_max), minimum (T_min) & mean (T_mean) temperatures in the annual, seasonal and monthly time-scales for 55 stations in the 5 regions of Uttarakhand’s Western Himalayan region which are categorized on the basis of elevation, from year 1979-2014. Statistical approaches are used to examine the effect of change in pattern of temperature upon the phenology of vegetation in the region under study, fresh water ecosystems, agricultural productivity, decreasing snow line & increasing tree line, change in duration of the seasons etc.

How to cite: Palni, S., Parashar, D., and Pandey, A.: Trend analysis of Changing Temperature over the Time Period of 1979 to 2014 in Uttarakhand, Western Himalaya, India, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1585, https://doi.org/10.5194/egusphere-egu22-1585, 2022.

Understanding the interaction between ocean circulation and ice sheet dynamics is fundamental to study the rapid Quaternary climate changes that punctuate major glacial-interglacial periods. Compared to the surface and deep compartments of the Atlantic Meridional Overturning Circulation (AMOC), intermediate water depths during key time periods, such as Heinrich Stadials (HSs), remain poorly documented, especially in the Northeast Atlantic.

In this study, we use benthic foraminiferal assemblage data from an upper slope sediment core from the Northern Bay of Biscay to reconstruct paleoenvironmental and paleohydrological changes at ~1000m water depth, from ~35 to 14 kyr cal BP. Our results show a strong response of benthic communities to hydrodynamic changes (related to AMOC) and to instabilities of the European Ice Sheet during the last three HSs. Benthic foraminifera provide species-specific responses to the induced physico-chemical changes, in coherence with the various geochemical and sedimentological proxies documented in the area. The three HSs are characterized by the low abundance of species indicative of high-energy environments (Cibicides lobatulus and Trifarina angulosa) and the simultaneous presence of Cibicidoides pachyderma (meso-oligotrophic species) and Globobulimina spp. (anoxia-tolerant species).   This species composition suggests a slowing of the intermediate circulation during the three HSs. Nevertheless, HS1 is very distinct from HS2 and HS3 by the high presence of high-organic flux indicator species (Cassidulina carinata and Bolivina spp.) during its early phase (Early HS1). This result confirms that EIS meltwaters were much less charged in organic material derived from the continent during HS2 and HS3 than during HS1 due to the scarcer vegetation cover and partially frozen soils. Finally, benthic foraminifera depict clearly the rapid "re-ventilation" during Mid-HS2, corresponding to a response to regional glacial instabilities.

How to cite: Depuydt, P., Mojtahid, M., Barras, C., Bouhdayad, F., and Toucanne, S.: Links between intermediate ocean circulation and cryosphere dynamics during Heinrich Stadials in the NE Atlantic: a foraminiferal perspective, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1792, https://doi.org/10.5194/egusphere-egu22-1792, 2022.

How to cite: Ellerhoff, B., Kirschner, M. J., Ziegler, E., Holloway, M. D., Sime, L., and Rehfeld, K.: State-dependent effects of natural forcing on global and local climate variability, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3459, https://doi.org/10.5194/egusphere-egu22-3459, 2022.

The stochastic energy balance models (SEBMs) pioneered by  Hasselmann and  Mitchell [1] have long been known to climate scientists to be important aids to gaining both qualitative insight and quantitative information about global mean temperatures.  SEBMs are now much more widely visible, after the award of last year’s Nobel Prize to Hasselmann, shared with Manabe and Parisi [1].

The earliest univariate SEBMs were, however, built around the simplest linear and Markovian stochastic process, and researchers have very intentionally exploited their equivalence to the Langevin equation of 1908. Although multivariate SEBMs have now been extensively studied [1,2] and provide one important route to incorporating non-Markovian memory effects into climate dynamics, my presentation will discuss the continuing value of univariate SEBMs, especially when coupled to other models. I  will also highlight how we and others (e.g. [4,5]) are going beyond the first SEBMs to incorporate more general models of temporal dependence, motivated by evidence of non-Markovian, and in particular long-ranged, memory in the climate system.  This effort has brought new and interesting challenges, both in mathematical methods and physical interpretation.

I will highlight our recent paper [3] on using a Hasselmann-type EBM to study the economic impacts of climate change and variability and our other ongoing work [6, and its updated version, 7] on  generalised (and in particular fractional) Hasselmann univariate SEBMs. I will compare our model [6,7] with Lovejoy and co-workers' FEBE [5], and discuss what the requirements are in order for such non-Markovian SEBMs to exhibit fluctuation-dissipation relations, which have been debated in the  SEBM field since the early work of Leith in the 1970s.

[1] Scientific background on the Nobel prize in physics 2021, Nobel Committee, Royal Swedish Academy of Sciences.

[2] Franzke and O’Kane, eds. Nonlinear and Stochastic Climate Dynamics, CUP, 2017.

[3] Calel et al, Nature Communications, 2020.

[4] Rypdal et al, Climate, 2018.

[5] Lovejoy et al, QJRMS, 2021.

[6] Watkins et al, On Generalized Langevin Dynamics and the Modelling of Global Mean Temperature, 2021, https://link.springer.com/chapter/10.1007%2F978-3-030-67318-5_29

[7] Watkins et al, arXiv: https://arxiv.org/abs/2007.06464v2.

How to cite: Watkins, N. W., Calel, R., Chapman, S., Chechkin, A., Ford, I., Klages, R., and Stainforth, D.: Beyond Hasselmann and Leith: The challenge of non-Markovian and fractional stochastic climate modelling, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3962, https://doi.org/10.5194/egusphere-egu22-3962, 2022.

Extratropical cyclones are a major source of natural hazards in the mid latitudes as wind and precipitation extremes are associat