Presentation type:
AS – Atmospheric Sciences

EGU23-4082 | ECS | Orals | MAL31 | AS Division Outstanding Early Career Scientist Award Lecture

Multiphase buffer theory: explanations of contrasts in atmospheric aerosol acidity and its applications 

Guangjie Zheng

Acidity is one central parameter in atmospheric multiphase reactions, and strongly influences the climate, ecological and health effects of aerosols. Yet, the drivers of aerosol pH remain to be fully resolved. Here we investigated into this issue with thermodynamic models and observations. We find that aerosol pH levels in populated continental regions are widely buffered by the conjugate acid-base pair NH4+/NH3, and in aerosols an individual buffering agent can adopt different buffer pH values. To explain these large shifts of buffer pH, we propose a multiphase buffer theory, and show that aerosol water content and mass concentration play a more important role in determining aerosol pH in ammonia-buffered regions than variations in particle chemical composition. These results imply that aerosol pH and atmospheric multiphase chemistry are strongly affected by the pervasive human influence on ammonia emissions and the nitrogen cycle in the Anthropocene. We further investigated into the applications of the multiphase buffer theory. Exemplary applications include to help explain the formation of severe hazes in China, to quantify the contribution of different factors in driving the aerosol pH variations, and to provide the framework to reconstruct long-term trends and spatial variations of aerosol pH, etc. Further investigations on its applications in aerosol and cloud chemistry studies are needed.

How to cite: Zheng, G.: Multiphase buffer theory: explanations of contrasts in atmospheric aerosol acidity and its applications, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4082, https://doi.org/10.5194/egusphere-egu23-4082, 2023.

EGU23-9284 | Orals | MAL31 | Vilhelm Bjerknes Medal Lecture

Kilometer-resolution climate models: prospects and challenges 

Christoph Schär

Currently major efforts are underway toward refining the horizontal grid spacing of climate models to about 1 km, using both global and regional models. Such resolutions have been used for about a decade in limited-area numerical weather prediction applications and have demonstrated significant improvements in the representation of convective precipitation events (thunderstorms and rain showers). There is the well-founded hope that these benefits carry over to climate models, as the approach enables replacing the parameterizations of moist convection and gravity-wave drag by explicit treatments.

In this presentation, we will review three areas of km-resolution climate modeling. First, consideration will be given to an ensemble of km-resolution simulations from the CORDEX-FPS program on convection-permitting climate modelling, with a computational domain covering the greater Alpine region. This addresses the occurrence of short-term heavy precipitation events including their impacts such as flash floods, hail, and lightning. Results demonstrate the benefits of high computational resolution, in particular for the representation of short-term heavy events of severe weather. Second, we will present recent results from the projects trCLIM / CONSTRAIN carried out over the tropical and subtropical Atlantic, with the goal to assess the potential of the methodology to constrain estimates of the equilibrium climate sensitivity. It will be argued that km-resolution is a highly promising approach for constraining uncertainties in global climate change projections, due to improvements in the representation of tropical and subtropical clouds that goes along with an improved representation of the intertropical convergence zone (ITCZ).

Third, technical aspects of developing km-resolution global models will be addressed. Developing this approach requires a concerted effort between climate and computer sciences. Key challenges are the exploitation of the next generation hardware architectures using accelerators (e.g. graphics processing units, GPUs), the development of suitable approaches to overcome the output avalanche, and the consistent maintenance of the rapidly-developing model source codes on a number of different compute architectures. Despite these challenges, it will be argued that km-resolution GCMs with a capacity to run at 1 SYPD (simulated year per day), might be much closer than commonly believed. However, as the computational load of CMIP-style simulations is tremendous, alternative ways to exploit these models will be needed.

How to cite: Schär, C.: Kilometer-resolution climate models: prospects and challenges, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9284, https://doi.org/10.5194/egusphere-egu23-9284, 2023.

AS1 – Meteorology

EGU23-13 | Orals | AS1.1

An Integrated Coupling Framework for Atmospheric Dynamics and Physics 

Linjiong Zhou and Lucas Harris

Atmospheric resolved-scale air flow (dynamics) and sub-grid parameterizations (physics) are two essential components of a weather or climate model. These two independent components are coupled and advanced using the same time step, either parallel or sequentially split. However, traditionally dynamics and physics are engineered in isolation and developed independently in models. As a result, many parts of the physics run at a physically-inappropriate time frequency or with heat transfers that are inconsistent with the dynamics, leading to errors. In addition, physical parameterizations should contain dynamical and non-dynamical processes. We believe there are compelling reasons that dynamical processes, if resolved, should be taken care of by the dynamical core.

Our study proposes a novel integrated dynamics-physics coupling framework (Zhou and Harris, 2022) within the GFDL (Geophysical Fluid Dynamics Laboratory) weather-to-seasonal prediction system SHiELD (System for High-resolution prediction on Earth-to-Local Domains; Harris et al., 2020) that promises to resolve the above issues. We will present our integrated coupling framework and the development of integrated physical parameterization for this framework in detail. The performance of forecast experiments using the modeling system SHiELD with this integrated coupling framework will be highlighted, focusing on large-scale circulation, cloud and precipitation, hurricane, and convective-storm predictions.

How to cite: Zhou, L. and Harris, L.: An Integrated Coupling Framework for Atmospheric Dynamics and Physics, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13, https://doi.org/10.5194/egusphere-egu23-13, 2023.

EGU23-415 | ECS | Orals | AS1.1

Ensemble Forecast Sensitivity to Observations Impact (EFSOI) of a high impact weather event using a convection permitting data assimilation system. 

Gimena Casaretto, Maria Eugenia Dillon, Yanina Garcia Skabar, Juan Ruiz, Paula Maldonado, and Maximiliano Sacco

The improvement of numerical weather forecasts is a key element to predict high-impact weather events, associated with deep moist convection. The observations that are assimilated into numerical weather prediction systems are conformed by numerous data sets and their impact should be objectively evaluated. This can be efficiently estimated by the Forecast Sensitivity to Observation Impact (FSOI) methodology. In this study, we explore the application of the ensemble formulation of FSOI (EFSOI) in a convective scale regional data assimilation system over Sierras de Córdoba (Argentina), a data-sparse region with complex terrain characterized by the periodic occurrence of extreme precipitation and flash floods events. To evaluate the observation networks that result beneficial and detrimental for the forecast, the Weather Research and Forecasting model coupled with the Local Ensemble Transform Kalman Filter was used with 40 members. Convective scale analyses were obtained every 5 minutes, assimilating reflectivity data from a C-band radar and conventional and non-conventional surface weather stations (CSWS and NSWS). The experiment  was initialized on December 13 at 23 UTC and ran for 5 hours, until December 14 03 UTC. The experiment conducted was a case study within the intensive observing period of the RELAMPAGO-CACTI field campaign that was carried out during the 2018-2019 austral warm season in the center of Argentina. An independent data assimilation cycle using more observations and a different configuration is used in the experiments as verifying truth for the computation of forecast errors in EFSOI.

Results showed that all the observation sources had, on average, a positive impact on the 30 minute forecasts with a positive impact rate above 50%. However, when observations impacts are analyzed by geographic location, different results are evidenced. Most of the surface stations that evidence a detrimental impact in forecasts are located in the northern part of the region, probably due to a misrepresentation of the thermodynamic environment. Regarding radar reflectivity observations, values of positive impact rate above 50% dominate over all the region, demonstrating that, in general, they reduce the forecast errors. The results suggest that the observations with values of reflectivity beneath 15 dBZ have a larger amount of beneficial observations in lower levels than in upper levels.

This methodology is an approximation to quantify the impact of reflectivity and surface observations on a convective permitting forecast over the region. The results of this (and future) work can help to identify observation data sources detrimental for the data assimilation system, suggesting data selection criteria to assess improvements in this regional convective-scale data assimilation system where nonconventional observations such as radar data plays an essential role.

How to cite: Casaretto, G., Dillon, M. E., Garcia Skabar, Y., Ruiz, J., Maldonado, P., and Sacco, M.: Ensemble Forecast Sensitivity to Observations Impact (EFSOI) of a high impact weather event using a convection permitting data assimilation system., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-415, https://doi.org/10.5194/egusphere-egu23-415, 2023.

This study explores the potential impact of global navigation satellite system (GNSS) radio occultation (RO) data on the performance of satellite radiance data assimilation for the tropical cyclone formation forecast over the western North Pacific. The forecast experiments of 32 tropical disturbances in September−October 2019 are performed through a regional model. Either assimilation of GNSS RO data, radiance data, or both of them can improve the forecast skill and environmental moisture of tropical cyclone formation. However, the interaction between radiance and GNSS RO data can further increase moisture throughout the forecast period, compared to the experiment with only radiance data assimilation. Moreover, the improved vorticity patterns are different between the experiments with GNSS RO data and with radiance data. When both the GNSS RO and radiance data are assimilated, the improved vorticity pattern tends to the pattern improved by GNSS RO data assimilation. This may be attributed to the anchoring effect of GNSS RO data on satellite radiance data assimilation. Although radiance data volume is much larger than GNSS RO data, the interaction between GNSS RO and radiance data in the data assimilation process can significantly improve forecast performance.

How to cite: Teng, H.-F., Kuo, Y.-H., and Done, J.: Impact of radio occultation data on satellite radiance data assimilation performance in tropical cyclone formation forecast over the western North Pacific, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1079, https://doi.org/10.5194/egusphere-egu23-1079, 2023.

EGU23-1128 | ECS | Posters virtual | AS1.1

Modeling of wind conditions in Warsaw 

Tomasz Strzyzewski and Adam Jaczewski

Airflow is one of the most important weather parameters in a city. It is important for the air quality, the city's heat balance, pedestrian comfort and the safety of high-rise buildings. Local flow at the scale of streets and districts is difficult or impossible to capture in regional weather models. Computational Fluid Dynamic models are the solution. In this paper, the OpenFoam model was used to model wind direction and speed in specific meteorological situations. The results were compared with measurement stations in Warsaw, and the model was improved on their basis. An averaged Navier Stokes turbulence model was used under steady-stable flow conditions. The Darcy-Forchheimer model was used to take vegetation into account. The poster presents the first results of analyzes related to the spatial distribution of wind direction and speed, delineates areas at risk of low air quality and compares it with the results from measuring stations. In addition to the basic model, a model containing ground thermals was also created to study the extent and intensity of the urban heat island and to study the phenomenon of smog during temperature inversion in selected meteorological conditions. A comparative analysis of both models was made. The first results show that it is possible quite accurately to map airflow in a city. It also indicates that some existing ventilation channels of the city have been blocked or limited due to new investments. The most important ventilation channel is the Vistula valley, which is 500-600 m wide in Warsaw. However, due to the terrain, its most important role is not fulfilled during prevailing westerly winds, and then the air quality decreases, especially at low wind speeds. In most cases, the northern districts are also generally better ventilated (spatial distribution of buildings, higher wind speeds) than the southern districts, but this is not always visible when assessing air quality. The immediate vicinity also influences the aspects of mechanical ventilation of the city and the way buildings are heated. Districts that theoretically should have better conditions for air exchange are often areas of single-family houses and independent boiler rooms. The city centre, despite tighter development, is heated by the municipal heating plant, and they are not direct emitters of pollution. Another aspect is vehicle traffic. In the city centre, more vehicle traffic is another pollutant emitter. For this reason, pollutants specific to heating and traffic were analysed separately. The general problem in high-resolution city-scale modelling is the use of adequate computational power. This initially precludes using CFD models in meteorological nowcasting and short-term modelling.

How to cite: Strzyzewski, T. and Jaczewski, A.: Modeling of wind conditions in Warsaw, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1128, https://doi.org/10.5194/egusphere-egu23-1128, 2023.

EGU23-1463 | ECS | Orals | AS1.1

Docker container in DWD's Seamless INtegrated FOrecastiNg sYstem (SINFONY) 

Matthias Zacharuk, Christian Welzbacher, Isabel Schnoor, Nils Rathmann, Christian Eser, Florian Prill, and Ulrich Blahak and the SINFONY

At Deutscher Wetterdienst (DWD), the SINFONY project has been set up to develop a seamless ensemble prediction system for convective-scale forecasting with forecast ranges of up to 12 hours. It combines Nowcasting (NWC) techniques with numerical weather prediction (NWP) in a seamless way. So far NWC and NWP run on two different IT-Infrastructure levels. Due to the data transfer between both infrastructures, this separation slows down SINFONY, makes it complex and prone to disturbances. These disadvantages are solved by applying the interconnected part of the SINFONY on one single architecture using a Docker Container.

With this aim in view a Docker-Container of the respective NWC components is created and executed on the infrastructure of NWP, the high performance linux computing cluster (HPC) of DWD. In test applications we already observed a speed up of roughly 20% by using the Container on the HPC-cluster instead of using NWC-Tools on the initial NWC IT-Architecture. The Container is already implemented in DWD’s experimental tool BACY for the assimilation cycle.

A major innovation of SINFONY is the rapid update cycle (RUC), an hourly refreshing NWP procedure with a Forecast range of 8 hours, which will be extended to 12 hours soon. The container will be implemented to the RUC and used for the subsequent combination of NWP and NWC forecasts.

In the presentation I will explain what a container is and discuss opportunities and risks of this technology. I will introduce how building the Container is integrated to the CICD procedures at DWD, how and where the Container is implemented to BACY and discuss latest results for the implementation to the RUC.

How to cite: Zacharuk, M., Welzbacher, C., Schnoor, I., Rathmann, N., Eser, C., Prill, F., and Blahak, U. and the SINFONY: Docker container in DWD's Seamless INtegrated FOrecastiNg sYstem (SINFONY), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1463, https://doi.org/10.5194/egusphere-egu23-1463, 2023.

EGU23-1510 | ECS | Orals | AS1.1

Comparison of Arctic sea-ice albedo between CARRA and ERA5 reanalyses and satellite based CLARA-A2 

Viivi Kallio-Myers, Yurii Batrak, and Bin Cheng

With the ongoing climate change, the Arctic region is experiencing rapid warming. This has a profound effect on the sea-ice cover and, as a result, on the surface albedo. Surface albedo has a large impact on the energy balance of the region: a decrease in surface albedo leads to increased absorption of solar radiation and thus higher temperatures, ultimately leading to the albedo decreasing further. Information on the surface albedo is therefore necessary for various applications and climate studies. Atmospheric reanalysis products answer this need, providing consistent multiyear datasets with good spatial coverage.

We have studied the Arctic sea-ice albedo in two reanalyses. First is ERA5, a global atmospheric reanalysis by the ECMWF (European Centre for Medium range Weather Forecasts). ERA5 has a horizontal resolution of 31 km, and sea-ice is modelled with a one-dimensional sea-ice parameterisation scheme.

The second reanalysis is CARRA (Copernicus Arctic Regional ReAnalysis), a regional atmospheric reanalysis covering a part of the Arctic with two overlapping domains: the western domain centred around Greenland and the eastern over the European Arctic. The horizontal resolution is 2.5 km, and similarly to ERA5, sea-ice is modelled with a one-dimensional thermodynamic sea-ice scheme.

We compare the surface albedo of these two reanalyses to the satellite-based black-sky surface albedo product of the CLARA-A2.1 dataset (CM SAF cLoud, Albedo and surface RAdiation dataset from AVHRR data). Comparisons are made for April to September, 2000-2015, for the sea areas of the CARRA domains. In addition to a general assessment, four different regions within the domains are studied separately.

How to cite: Kallio-Myers, V., Batrak, Y., and Cheng, B.: Comparison of Arctic sea-ice albedo between CARRA and ERA5 reanalyses and satellite based CLARA-A2, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1510, https://doi.org/10.5194/egusphere-egu23-1510, 2023.

EGU23-1687 | Orals | AS1.1

Winter jet stream wind speed changes in the eastern North Atlantic 

Joel Tenenbaum and Paul Williams

We have published [ https://doi.org/10.1002/qj.4342 ] recent results on winter jet stream wind speed changes in the eastern North Atlantic: there is no change for the past 40 years but a statistically significant increase for the past roughly 20 years (2002-2020).  The increase shows up in both the Global Aircraft Data Set (GADS) observations from flight data recorders and the ERA5 reanalysis.  The wind speeds seem to track the North Atlantic Oscillation (NAO).  We can consider four possibilities: ( 1 ) synoptic fluctuation; ( 2 ) improved aircraft routing, though inconsistent with NAO correlations; ( 3 ) greater number of automated aircraft observations; ( 4 ) actual secular change in the polar jet exit region of the atmosphere.  This type of study must deal with subtleties of North Atlantic track system that includes aircraft step climbs.  We will present newer results on the secular increase in automated aircraft observations and the effects of including more recent Northern Hemisphere winters (2021 through, possibly, 2023).

How to cite: Tenenbaum, J. and Williams, P.: Winter jet stream wind speed changes in the eastern North Atlantic, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1687, https://doi.org/10.5194/egusphere-egu23-1687, 2023.

EGU23-1830 | ECS | Posters on site | AS1.1

A statistical description method of global sub-grid topography for numerical models 

Yaqi Wang, Lanning Wang, Juan Feng, and Zhenya Song

Slope and aspect are important topographic elements for thermodynamics and dynamics of atmospheric circulation, especially for local radiation and topographic precipitation. We propose a simple realistic statistical method based on trigonometric function transformation to calculate sub-grid slope and aspect for describing the orographic characteristics of complex areas over the globe. It is found that the transformed conditional probability density function (PDF) conforms to the Gaussian distribution in most of the global areas (~98%), and this feature is not eliminated with the increasing of horizontal resolution. The reasonability of this method is tested over the Tibetan Plateau. The results show that the improvement ratio of surface solar radiation downward (SSRD) over the Tibetan Plateau improved significantly compared with the results from the grid average scheme, especially in autumn. The improvement of root mean square error (RMSE) is approximately 18.2 W/m2, and the improvement ratio reached 38.4%. The improvements of maximum and regional-averaged SSRD over the whole Tibetan Plateau were ~130 W/ m2 and ~44.3W/m2 respectively. Although we only consider the effect of sub-grid slope and aspect on solar shortwave radiation, which has a certain bias with the observation data, it is sufficient to prove the rationality of the statistical method compared with the unobstructed horizontal surfaces scheme (CTL). After that, we applied this sub-grid parameterization scheme for topographic vertical motion in CAM5 to revise the original vertical velocity by adding the topographic vertical motion and then resulting a significant improvement of simulation in precipitation over steep mountains.

How to cite: Wang, Y., Wang, L., Feng, J., and Song, Z.: A statistical description method of global sub-grid topography for numerical models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1830, https://doi.org/10.5194/egusphere-egu23-1830, 2023.

EGU23-2466 | ECS | Posters on site | AS1.1

Impact of changes in the cloud amount due to condensation processes on precipitation forecasting on the Korean Peninsula during the summer in the Korean Integrated Model 

Yeseo Park, Jeong-Ock Lim, Hyun-Joo Choi, Kyoungmi Cho, Seon-Kyun Baek, and Seong-Hoon Cheong

In numerical models, the amount of clouds affects atmospheric temperature through interaction with radiation. In the Korean Integrated Model (KIM), which has been in operation at the Korea Meteorological Administration since April 2020, the amount of clouds is determined from prognostic equation consisting of source and sink terms  by  physical processes such as planetary boundary layer (PBL) mixing, convection, advection, condensation, and evaporation. In the control KIM version, the temperature forcing used for calculating the rate of changes in time of saturation specific humidity which determines formation of cloud area due to condensation is calculated by considering those from all physical processes, such as radiation, cumulus convection, and turbulence, as well as cloud microphysical processes. However, we found the inconsistency between the cloud fraction and mixing ratio by using the methodology, so in this study, we modify the temperature forcing from all physical processes into that only due to the microphysical process. It is confirmed that the change in the amount of clouds changes the temperature and humidity of the atmosphere through the interaction between physical processes such as radiation, which also affects precipitation. 
In this study, to examine the effect of changes in cloud cover on precipitation in the Korean Peninsula, we perform one case study July 4, 2021 when precipitation in Gangwon occurs due to the convergence of air currents caused by east wind of high pressure in the eastern of Korea. Up to 172.5 mm of daily maximum precipitation was reported in the Gangwon region. In the 3-day forecast of the case, the control KIM  underestimates inland precipitation. But the trend of under-estimation is improved by increasing the amount of precipitation when the cloud amount is modified. The increase in precipitation mainly occurs in the large-scale precipitation due to the microphysical process. This is because the cloud amount generally increases in the Asian area including the Korean Peninsula, which makes the environment favor to the precipitation, by decreasing the temperature through the radiative cooling, in turn resulting the decrease in saturation vapor pressure. For the statistical evaluation of the precipitation performance, precipitation verification is also performed for one month in July, and it is found that ETS (Equivalent Threat Score) performance against the  reanalysis data on the Korean Peninsula is also improved.

How to cite: Park, Y., Lim, J.-O., Choi, H.-J., Cho, K., Baek, S.-K., and Cheong, S.-H.: Impact of changes in the cloud amount due to condensation processes on precipitation forecasting on the Korean Peninsula during the summer in the Korean Integrated Model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2466, https://doi.org/10.5194/egusphere-egu23-2466, 2023.

EGU23-2827 | Posters on site | AS1.1

Ensemble sensitivity localization 

Philipp Johannes Griewank, Tobias Necker, and Martin Weissmann

Ensemble sensitivity is a tool to quantitatively determine which initial conditions influence a forecast quantity of choice. This information can then be used to understand the sources and dynamics of forecast uncertainty, quantify the impact of observations (e.g., E-FSOI), and determine where to best deploy observations to improve the forecast (e.g., observation targetting and network design). The ensemble sensitivity is calculated from the covariances of the initial ensemble to the forecast ensemble. Unfortunately, these covariances are prone to sampling errors due to the limited ensemble size. The most common approach in data assimilation to mitigate sampling errors is to apply distance-based damping, i.e., localization. This poster explores how to localize the sensitivity correctly and how it differs from analysis localization. Using simplified problems, we highlight the benefits and drawbacks of sensitivity localization and discuss its usefulness to numerical weather prediction applications.

How to cite: Griewank, P. J., Necker, T., and Weissmann, M.: Ensemble sensitivity localization, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2827, https://doi.org/10.5194/egusphere-egu23-2827, 2023.

EGU23-2982 | Orals | AS1.1

Advancing Operational Modeling Systems at NOAA’s Environmental Modeling Center: Transitioning to Unified Forecast System Applications 

Ivanka Stajner, Brian Gross, Vijay Tallapragada, Jason Levit, Arun Chawla, Avichal Mehra, Daryl Kleist, and Fanglin Yang

National Oceanic and Atmospheric Administration’s (NOAA’s) Environmental Modeling Center (EMC) is a lead developer of Numerical Weather Prediction (NWP) systems that also transitions to operations and maintains more than 20 numerical prediction systems that are used across the National Weather Service (NWS), the broader NOAA, by other United States (U.S.) federal agencies, and various other stakeholders. These systems are developed through a close collaboration with partners from the academic, federal and commercial sectors. EMC maintains, enhances and transitions-to-operations numerical forecast systems for weather, ocean, climate, land surface and hydrology, hurricanes, and air quality for the U.S. and the global community and for the protection of life and property and the enhancement of the economy.

 

NOAA’s Next Generation Global Prediction System (NGGPS) Project initiated a major shift in the development of operational Earth system predictions with a goal to simplify the National Centers for Environmental Prediction (NCEP) Production Suite using the Unified Forecast System (UFS) framework (https://ufscommunity.org/). EMC has taken a lead in further development and consolidation of NCEP’s operational systems into UFS based applications.  The UFS is being designed as a community-based, comprehensive atmosphere-ocean-sea-ice-wave-aerosol-land coupled Earth modeling system with coupled data assimilation and ensemble capabilities, organized around applications spanning local to global domains and predictive time scales ranging from sub-hourly analyses to seasonal predictions.  Disparate operational applications that have been developed and maintained by EMC in support of various stakeholder requirements are being transitioned to the UFS framework. The transition started a few years ago and is planned to continue over the next few years. The resulting applications will consolidate NCEP’s Production Suite into far fewer applications that share a set of common scientific components and technical infrastructure.  This approach is expected to accelerate the transition of research into operations and simplify maintenance of operational systems.

 

This talk describes major development and operational implementation projects at EMC over the last few years and the plans for the next five years (2023-2027), how those fit within the broader strategic plans of NOAA, and how these projects link with other model-related projects internally within NOAA and with the broader U.S. and international modeling community.

How to cite: Stajner, I., Gross, B., Tallapragada, V., Levit, J., Chawla, A., Mehra, A., Kleist, D., and Yang, F.: Advancing Operational Modeling Systems at NOAA’s Environmental Modeling Center: Transitioning to Unified Forecast System Applications, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2982, https://doi.org/10.5194/egusphere-egu23-2982, 2023.

EGU23-3025 | Posters on site | AS1.1

Effects of increasing horizontal and vertical resolution in Korean Integrated Model (KIM) 

Ja-Rin Park, Hae-Jin Kong, Hyun Nam, and Suk-Jin Choi

Since the dynamical core of Korean Integrated Model (KIM) was developed in the 1st phase (2011~2019) of KIAPS, we have been aiming to develop a variable resolution prediction system covering short to medium range in the 2nd phase (2020.9~2026). As a first step towards moving to km-scale resolution, we have increased the model resolution from 12 km to 8 km horizontally and 91 to 137 layers vertically. For increasing the resolution horizontally, dynamics core configurations and terrain elevation data were newly set up. For vertically, vertical coordinates of 137 layers followed that of the European Center for Intermediate Forecasting (ECMWF) Integrated Forecasting System (IFS), which has been increased vertical resolution throughout the troposphere and stratosphere comparing to 91 layers.
This study discusses the forecast impact of high-resolution KIM in terms of objective verification scores against observations and analyses. The overall conclusion for horizontal high-resolution is that it shows slightly positive in southern hemisphere and mainly neutral for northern hemisphere, but also some negative in tropics. One of distinguished results is increasing horizontal resolution leads to cooling in the temperature in the lower and upper troposphere. The cooling in the lower tropospheric over the tropics seems to come from smaller time step that has to be for smaller dx, which results in enlarged low cloud formation and thus more radiative cooling. In case of the upper troposphere, the cooling results from outgoing long-wave radiative cooling by decreasing hydrometeors in physical response to smaller grid spacing. The increase of vertical resolution had an effect of neutral to slight positive in northern hemisphere but showed significant degradation in tropics. To achieve the consistency and improvement for high-resolution model, it is necessary to understand the physical processes related to time step and horizontal and vertical grid spacing.

 

Acknowledgement
One of the authors, S-J Choi, wishes to acknowledge this study was supported by 2023 New Professor Support Program of Natural Science Research Institute in Gangneung-Wonju National University).

How to cite: Park, J.-R., Kong, H.-J., Nam, H., and Choi, S.-J.: Effects of increasing horizontal and vertical resolution in Korean Integrated Model (KIM), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3025, https://doi.org/10.5194/egusphere-egu23-3025, 2023.

NOAA is collaborating with the US weather and climate science community to develop the next generation fully coupled earth system modeling capability for both research and operational forecast applications across different temporal and spatial scales.    In this presentation we explore the possibility of running the UFS at convection-permitting resolution for global medium-range weather forecasting.  A few sensitivity experiments were performed at a global uniform 3-km resolution with and without parameterized convection.  Results were compared with the 13-km control experiments to investigate the impact of model resolution and convection parameterization on precipitation and cloud-radiation interaction.   Aerosol indirect effect on clouds is also tested and evaluated within this framework to understand its sensitivity to model resolution and parameterized convection.  Aerosol indirect effect occurs when aerosols act as cloud condensation nuclei and ice nuclei within clouds and consequently alter cloud radiative properties and cloud lifetime.   Using the Thompson double-momentum microphysics scheme, the number concentrations of water friendly aerosol and ice friendly aerosol are either diagnosed from the MERRA2 aerosol climatology or predicted and advected with source and sink terms derived from the climatology. The relations between clouds, radiation and precipitation with and without the presence of aerosol indirect effects are analyzed for simulations made at both the control 13-km and experimental 3-km UFS model resolutions.  

How to cite: Yang, F., Chen, A., and Moorthi, S.: Prototyping Convection-Permitting Global Weather Forecast and the Representation of Aerosol-Cloud-Radiation Interaction in the NOAA Unified Forecast System, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3038, https://doi.org/10.5194/egusphere-egu23-3038, 2023.

EGU23-3183 | ECS | Posters on site | AS1.1

Integration of the WRF Model With Fine-Scale Land Use Data to Simulate Extreme Rainfall Events 

Nagaraju Gaddam, Abhinav Wadhwa, Likhitha Pentakota, Gowri Reghunath, and Pradeep P Mujumdar

Urbanization results in drastic land alteration in which natural land cover is replaced by impermeable surfaces such as compacted soils, buildings and associated infrastructures. While the impact of urbanization on extreme rainfall is captured in satellite data to a great extent, its signal is frequently less obvious in station-level data. Also, the lack of local meteorological data hinders the development of adequate mitigation measures to reduce the impact of extreme rainfall scenarios. To regenerate the local meteorological data, numerical model-based simulations using global boundary conditions are required at finer Spatio-temporal scales. To this end, integrated land surface models which can provide the maximum likelihood of observed rainfall can be of great significance, especially in urban complexes. Weather Research Forecasting (WRF) model is one such numerical model that can lay down a framework to provide short-range weather forecasts by fixing site-specific physics-based parametrization schemes. This study demonstrates the application of the WRF model to provide building-scale weather forecasts based on the finer-scale Urban Canopy Model (UCM) and Local Climate Zonation (LCZ). The numerical modelling framework is set up for Bangalore city, India. Bangalore city is categorized as one of the major urban complexes with a total built-up area of 77.5%. The World Urban Database Access Portal Tool (WUDAPT), which is based on random forest classification of the ground truth training samples, is used to develop the LCZ database for the WRF model. A single-layer UCM is developed to indicate the importance of structural and aerial characteristics of static datasets with appropriate land features. WRF model runs are carried out based on global boundary conditions to provide a 24hr forecast with 3km and 1km spatial domain for the study area at an urban scale. The overall accuracy of 92% (for the built-up area) and 85% (for water bodies) is obtained for LCZs developed using the random forest classification in WUDAPT. In comparison to default configurations of WRF, the forecasts of WUDAPT-based LCZs have shown an improvement at both spatial and temporal scales. The bias (particularly the spatial shift) observed using the default WRF is reduced drastically, and the forecasts are well-matched with the observed Telemetric Rain Gauge (TRG) station rainfall datasets. Assessment of the maximum likelihood of extreme rainfall forecasts can provide a platform for the development of an integrated WRF hydrological configuration in the future. Such frameworks will be greatly beneficial for obtaining more accurate rainfall and flood forecasts.

How to cite: Gaddam, N., Wadhwa, A., Pentakota, L., Reghunath, G., and P Mujumdar, P.: Integration of the WRF Model With Fine-Scale Land Use Data to Simulate Extreme Rainfall Events, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3183, https://doi.org/10.5194/egusphere-egu23-3183, 2023.

EGU23-3545 | ECS | Orals | AS1.1

The Role of Parameterized Momentum Flux on Biases in Tropical Cyclones and the Mean State in the Community Atmosphere Model 

Kyle Nardi, Colin Zarzycki, Vincent Larson, and George Bryan

With enhanced computational capacity, the treatment of subgrid processes in global Earth System Models (ESMs) has grown increasingly complex. Despite these enhancements, critical biases remain in the modeling of fundamental processes that govern both the mean climate and the development of extreme weather phenomena of high societal impact. Due to their potential to be better resolved in the next generation of ESMs, tropical cyclones (TCs) are extremes of particular interest. 

The importance of the parameterization of momentum flux within the boundary layer (PBL) for modeled TC structure has been established for numerical models run at a variety of spatial scales. However, few studies have specifically explored the modulation of TC structure by the PBL parameterization in a coarser-resolution ESM. In this study, we evaluate the role of the PBL scheme on modeled TC structure in the Community Atmosphere Model version 6 (CAM6), which is the atmospheric component of the Community Earth System Model version 2 (CESM2). CAM6 employs the Cloud Layers Unified by Binormals (CLUBB) scheme. To enhance generalizability of turbulent processes, we apply an experimental version of CLUBB (CLUBBX) with a prognostic formulation of momentum flux and a regime-specific formulation for the dissipation of turbulent eddies.  

We perform a sensitivity analysis, the Morris one-at-a-time (MOAT) method, to evaluate the influence of various tunable CLUBBX input parameters on process-based metrics that characterize TC structure in an idealized framework. We find that certain tunable CLUBBX parameters controlling vertical turbulent mixing in the PBL modulate key TC metrics like jet height, inflow angle, and surface heat flux. We further demonstrate that targeted perturbations to these influential parameters can reduce established ESM biases in modeled TC structure. 

However, in a global ESM, the accurate depiction of individual TCs should not come at the expense of the model’s depiction of the mean climate. Therefore, it is important to understand how the calibration of CAM6-CLUBBX impacts other aspects of the global and regional climate. We therefore repeat the MOAT sensitivity analysis on global ESM simulations to evaluate how these CLUBBX input parameters impact process-based climate metrics on regional and global scales. We leverage an ensemble approach with short, initialized runs (Betacast) to allow for computational tractability.  

We find that CLUBBX parameters that influence TC structure also influence various regionally and globally-averaged climate metrics, including thermodynamic profiles, cloud-radiative forcing, and surface wind stress, at short timescales (3 days). We further show that targeted perturbations to a handful of these influential input parameters can reduce global and regional biases in CAM6-CLUBBX at decadal timescales. We explore physical mechanisms for these demonstrated parameter sensitivities and discuss practical implications of targeted model tunings for long-term climate simulations. 

How to cite: Nardi, K., Zarzycki, C., Larson, V., and Bryan, G.: The Role of Parameterized Momentum Flux on Biases in Tropical Cyclones and the Mean State in the Community Atmosphere Model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3545, https://doi.org/10.5194/egusphere-egu23-3545, 2023.

EGU23-3553 | Posters on site | AS1.1

A positive definite solution for an EDMF PBL scheme that includes a moist adjustment process 

Jian-Wen Bao, Evelyn Grell, Sara Michelson, and Song-You Hong

The eddy diffusivity and mass flux (EDMF) scheme for simulating turbulent transport in the operational Global Forecast System (GFS) shows a behavior due to a physical and numerical inconsistency in the scheme's numerical procedure to obtain detrained cloud water due to the moist nonlocal mixing and its associated moist adjustment.  One-dimensional simulations show that such inconsistency leads to an unphysical distribution of thermal tendencies and detrained cloud water near the simulated planetary boundary layer (PBL) top.  To solve this problem, a new procedure to obtain a positive definite solution from the scheme is proposed to solve the EDMF equations in the scheme. We will show the impact of this new solution procedure on the GFS performance.

How to cite: Bao, J.-W., Grell, E., Michelson, S., and Hong, S.-Y.: A positive definite solution for an EDMF PBL scheme that includes a moist adjustment process, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3553, https://doi.org/10.5194/egusphere-egu23-3553, 2023.

EGU23-3703 | Orals | AS1.1

Facilitating the development of complex models with the Common Community Physics Package and its Single-Column Model 

Ligia Bernardet, Grant Firl, Dustin Swales, Man Zhang, Mike Kavulich, Samuel Trahan, Weiwei Li, Jimy Dudhia, and Mike Ek

The Common Community Physics Package (CCPP) is a collection of atmospheric physical parameterizations and a framework that couples the physics for use in Earth system models. The CCPP Framework was developed by the U.S. Developmental Testbed Center (DTC) and is now an integral part of the Unified Forecast System (UFS). The UFS is a community-based, coupled, comprehensive Earth modeling system designed to support research and be the source system for NOAA‘s multi-scale operational numerical weather prediction applications. The CCPP is also being used in the experimental U.S. Navy Environmental Prediction sysTem Utilizing the NUMA  corE (NEPTUNE, which employs a modified version of the Non-hydrostatic United Model for the Atmosphere dynamical core) and is currently being integrated into the Community Atmosphere Model (CAM) utilized in the National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM).

A primary goal for this effort is to facilitate research and development of physical parameterizations, while simultaneously offering capabilities for use in operational models. The CCPP Framework supports configurations ranging from process studies to operational numerical weather prediction as it enables host models to assemble the parameterizations in flexible suites. Framework capabilities include flexibility with respect to the order in which schemes are called, ability to group parameterizations for calls in different parts of the host model, and ability to call some parameterizations more often than others. Furthermore, the CCPP is distributed with a single-column model (SCM) that can be used to test innovations,  conduct hierarchical studies in which physics and dynamics are decoupled, and isolate processes to more easily identify issues associated with systematic model biases. The CCPP SCM can be driven using files in the DEPHY format (an internationally agreed-upon format for inputs and outputs of SCMs). This opens doors for collaborations using multiple initial and forcing datasets based on observational field campaigns. The CCPP SCM is also being updated to be forced by the UFS.

The CCPP v6.0.0 public release includes 23 primary parameterizations (and six supported suites), representing a wide range of meteorological and land-surface processes. Experimental versions of the CCPP also contain chemical schemes, making it possible to represent processes in which chemistry and meteorology are tightly coupled.

The CCPP is developed as open-source code and has received contributions from the wide community in the form of new schemes and innovations within existing schemes. In this presentation, we will provide an update on CCPP development and plans, as well as review existing resources for users and developers, such as the public releases, documentation, tutorial, and support mechanism. We will also provide information about the upcoming CCPP Visioning Workshop, indeed to be a forum for current and future CCPP users to learn about its capabilities and discuss requirements for new development. 

How to cite: Bernardet, L., Firl, G., Swales, D., Zhang, M., Kavulich, M., Trahan, S., Li, W., Dudhia, J., and Ek, M.: Facilitating the development of complex models with the Common Community Physics Package and its Single-Column Model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3703, https://doi.org/10.5194/egusphere-egu23-3703, 2023.

EGU23-3781 | ECS | Orals | AS1.1

Appropriately representing convective heating is critical for predicting catastrophic heavy rainfall in 2021 in Henan Province of China 

Mingyue Xu, Chun Zhao, Jun Gu, Jiawang Feng, Gudongze Li, and Jianping Guo

An unprecedented heavy rainfall event occurred in Henan Province of central China during 19-20 July 2021. To investigate the impacts of predicted large-scale circulation on the regional convection-permitting prediction of this event, two sets of nested experiments with different convective parameterizations (GF and MSKF) in the outer domain and at convection-permitting resolution in the inner domain are performed with the Weather Research and Forecasting (WRF) model. The analysis found the prediction of “21.7” rainstorm at convection-permitting resolution in the inner domain is largely affected by convective scheme in the outer domain. The large-scale circulation forcing from the outer domain with different convective schemes is significantly different, which ultimately affects the circulation and precipitation in the refined region through lateral boundary forcing. The difference in regional prediction at convection-permitting resolution can be mitigated by adjusting convective latent heat parameterization in the outer domain. This work highlights that appropriately parameterizing convective latent heat is the key to provide reasonable large-scale forcing for regionally predicting this catastrophic heavy rainfall event at convection-permitting resolution, which may also be applicable to other events and other regions.

How to cite: Xu, M., Zhao, C., Gu, J., Feng, J., Li, G., and Guo, J.: Appropriately representing convective heating is critical for predicting catastrophic heavy rainfall in 2021 in Henan Province of China, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3781, https://doi.org/10.5194/egusphere-egu23-3781, 2023.

The characteristic adjustment time scale τ is always defined as the time allowed for dissipation of Convective Available Potential Energy (CAPE) in convective parameterization schemes. Previous studies indicate that, in the cloud ensemble, τ is one of the most important parameters that have  the greatest influences on the global mean precipitation. Some research work has improved the Kain–Fritsch scheme in the regional model to realize the variable parameters. In the global model, some studies have used machine learning methods to optimize the parameters of the deep convection trigger function. However, changing constant parameters into variable parameters in the global model has not been explored. In our study, the Zhang-McFarlane (ZM) deep convection scheme is improved to realize the variable characteristic adjustment time scale parameter, so as to reduce the precipitation deviation in a global model. In the ZM deep convection scheme, τ is usually the default constant. While in this paper, we use CAPE to modulate τ and propose a calculation formula of τ. In the region where the mean precipitation amount bias is improved, the new scheme mainly increases the deep convective precipitation and reduces the large-scale and shallow convective precipitation. The modified scheme significantly improves the simulation of precipitation over the eastern equatorial Pacific Ocean and some steep terrain regions. The root mean square error of the mean precipitation amount over the eastern equatorial Pacific Ocean and the central Indo-Pacific Warm Pool in boreal summer is reduced after the new scheme is adopted in a global model with the horizontal resolution of 1° longitude and 1° latitude. Moreover, the simulations of precipitation over the Tibet Plateau and South America are also improved. The new scheme reduces the frequency of deep convective precipitation and increases the amount of deep convective precipitation each time.

How to cite: Wang, M. and Wang, L.: Simulation of Precipitation with a Variable Characteristic Adjustment Time Scale Parameter of Deep Convection in a Global AGCM, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4649, https://doi.org/10.5194/egusphere-egu23-4649, 2023.

EGU23-4730 | Posters on site | AS1.1

Status and plan of ensemble forecast system in Korea Meteorological Administration (KMA) 

Eun-Jung Kim, Hyun-Cheol Shin, Jong Im Park, Jong-Chul Ha, and Young-Cheol Kwon

The ensemble forecast system based on the Korea Integrated Model (KIM), which is developed for Korea’s own numerical weather prediction (NWP) model, has been in operation at Korean Meteorological Administration (KMA) since October 2021. KMA ensemble forecast system consists of 50 perturbation members (25 members for long-range forecast) and 1 control simulation. Four-dimensional LETKF (Local Ensemble Transform Kalman Filter) with additive and RTPS inflation scheme is used to make initial perturbation. 
Evaluation of forecast scores shows that our operational ensemble forecast system is generally more skillful compared to the deterministic simulation as forecast time is longer. Also, forecast with increased ensemble size produces better representation of atmospheric fields especially in higher latitudes. Details of results from operational ensemble system and impacts of increased ensemble size will be discussed with introducing a brief overview of our ensemble forecast system and development plan in future. 

How to cite: Kim, E.-J., Shin, H.-C., Park, J. I., Ha, J.-C., and Kwon, Y.-C.: Status and plan of ensemble forecast system in Korea Meteorological Administration (KMA), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4730, https://doi.org/10.5194/egusphere-egu23-4730, 2023.

EGU23-5548 | ECS | Orals | AS1.1

Exploitation of GNSS tropospheric gradients for severe weather Monitoring And Prediction (EGMAP): Project status and Initial results 

Rohith Muraleedharan Thundathil, Florian Zus, Galina Dick, and Jens Wickert

Data assimilation (DA) is a tool that is capable of combining observations and numerical weather models (NWMs) in an optimal manner. Current DA systems used by operational forecasting centres are constantly evolving and getting better than before. High-quality observations are very important for the accurate representation of variables in a weather model. In this study, we are incorporating Global Navigation Satellite System (GNSS) tropospheric gradients and Zenith Total Delays (ZTDs) into the Weather Research and Forecasting (WRF) model. WRF model has its operator already developed for the ZTDs and in this research, we are developing a new operator for the assimilation of tropospheric gradients. The assimilation of ZTDs, which are closely related to Integrated Water Vapor (IWV) above the GNSS station, has a positive impact on weather forecasts. On the other hand, tropospheric gradients are not yet assimilated by the weather agencies. Our research is based on a project titled “Exploitation of GNSS tropospheric gradients for severe weather Monitoring And Prediction” (EGMAP) focusing on the impact of GNSS tropospheric gradients and how it can be effectively used for operational forecasting of severe weather. EGMAP is funded by the German Research Foundation (DFG).

The observation operator currently in use for tropospheric gradients is based on a linear combination of ray-traced tropospheric delays (Zus et al., 2022). This observation operator is challenging to be implemented into an NWM DA system. We will thus rely on a more simple and fast observation operator which is based on the closed-form expression depending on the north–south and east–west horizontal gradients of atmospheric refractivity (Davis et al., 1993).

Initial testing of the operator is done on a 0.1 x 0.1-degree mesh configured over Central Europe in the WRF model with 50 vertical levels up to 50 hPa. The model configuration will be later upgraded to a convective-scale resolution after initial testing of the tropospheric gradient operator. Model forcing observations are derived from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) data at 0.25-degree resolution. Conventional observations are obtained from the European Centre for Medium-Range Weather Forecasts (ECMWF) and are the base dataset for the assimilation studies. The conventional datasets used for assimilation are restricted to surface stations (SYNOP observations) and radiosondes. Additionally, observations from roughly 100 GNSS stations are assimilated at each DA cycle. Three experiments are conducted: 1) Control run with only conventional data; 2) ZTD assimilation on top of the control run, and; 3) ZTD and tropospheric gradient assimilation on top of the control run. Initial DA tests are being performed with an automated rapid update cycle DA framework with 6 hourly intervals based on a deterministic three-Dimensional Variational (3DVar) DA system for the testing of ZTDs and tropospheric gradients. The DA system will be later upgraded to a probabilistic one based on the Hybrid 3DVar-Ensemble Transform Kalman Filter (-ETKF, Thundathil et al., 2021) and 4DEnVar. The EGMAP project status and initial results from the impact of GNSS-ZTDs and tropospheric gradients will be presented.

How to cite: Thundathil, R. M., Zus, F., Dick, G., and Wickert, J.: Exploitation of GNSS tropospheric gradients for severe weather Monitoring And Prediction (EGMAP): Project status and Initial results, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5548, https://doi.org/10.5194/egusphere-egu23-5548, 2023.

EGU23-6532 | Orals | AS1.1

Upper tropospheric convective outflow in ICON convection-permitting and parameterised set-up 

Edward Groot, Patrick Kuntze, Annette Miltenberger, and Holger Tost

The representation of upper tropospheric deep convective divergent outflow (UTDCDO) is compared between ICON-simulations with convection-permitting and convection parameterised set-ups (1 and 13 km resolution) for a convective event over Germany and the Alps on June 10th-11th 2019. Three hypotheses on those UTDCDO have been formulated using idealised Large Eddy Simulations and are now tested on ICON in a convection-permitting set-up: 1. Dimensionality affects the magnitude of UTDCDO in ICON; 2. Convective aggregation and organisation affects the magnitude of those convective outflows in ICON and 3. Convective momentum transport does not affect the magnitude of UTDCDO. A moving box is used to integrate mesoscale divergence, precipitation rate and convective momentum transport. Additionally, ellipse fitting is used to make estimates of convective organisation (dimensionality, area of convective precipitation, etc.).
Variability in UTDCDO at a given net latent heating rate is reduced in ICON with parameterised deep convection, compared to the convection-permitting set-up. Hints, but no conclusive results are found on the effect of dimensionality on the magnitude of UT divergent deep convective outflows. An impact of convective organisation and aggregation on UTDCDO is significant in the dataset: as a consequence of outflow collisions, UTDCDO increases sub-linearly with net latent heating. We also found a statistical relation between normalised UTDCDO and normalised convective momentum transport.  

How to cite: Groot, E., Kuntze, P., Miltenberger, A., and Tost, H.: Upper tropospheric convective outflow in ICON convection-permitting and parameterised set-up, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6532, https://doi.org/10.5194/egusphere-egu23-6532, 2023.

The sub-seasonal characteristics and prediction of rainfall over the Asian Monsoon Area during spring-summer transitional season (April-May-June) are investigated using a full set of hindcasts generated by the Dynamic Extended Range Forecast operational system version 2.0 (DERF2.0) of Beijing Climate Center, China Meteorological Administration. The onset and development of Asian summer monsoon and the seasonal migration of rain belt  over East Asia can be well depicted by the model hindcasts at various leads. However, there exist considerable differences between model results and observations, and model biases depend not only on lead time, but also on the stage of monsoon evolution. In general, forecast skill drops with  increasing lead time, but rises again after lead time becomes longer than 30 days, possibly associated with the effect of slowly-varying forcing or  atmospheric variability. An abrupt turning point of bias development appears around mid-May, when bias growths of wind and precipitation exhibit significant changes over the northwestern Pacific and South Asia, especially over the Bay of Bengal and the South China Sea. This abrupt bias change is  reasonably captured by the first two modes of multivariate empirical orthogonal function analysis, which reveals several important features associated  with the bias change. This analysis may provide useful information for further improving model performance in sub-seasonal rainfall prediction.

How to cite: Li, Q., Wang, J., and Yang, S.: Sub-seasonal Variations and Predictions of Precipitation over the Asian Monsoon Area with BCC_DERF2.0 in Spring-Summer Transition Season, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6653, https://doi.org/10.5194/egusphere-egu23-6653, 2023.

EGU23-7064 | ECS | Posters on site | AS1.1

Evaluation of Daily Temperature Extremes in the ECMWF ERA5 Reanalysis and Operational Weather Forecasts 

Francisco Lopes, Emanuel Dutra, and Souhail Boussetta

The daily maximum and minimum temperatures are among the most relevant meteorological variables in weather forecasts and climate monitoring. Their spatial and temporal evolution from synoptical to decadal scales are driven by numerous physical processes and climate feedbacks. Despite the significant improvements in weather forecasting over the last decades, forecasts of daily temperature extremes are still hampered by systematic errors. In this work we perform an integrated evaluation of the daily temperature extremes of the (i) ECMWF ERA5 reanalyses and (ii) ECMWF operational weather forecasts. The observations for the evaluation are taken from the Global Historical Climatology Network (GHCN) addressing: (i) the long-term assessment of the analysis produced by the ERA5 reanalysis, comprising a 40-year period (from 1980 to 2019); and (ii) the assessment of the ECMWF operational forecasts for a 5- year period (from 2017 to 2021). The evaluation carried out is global, however considering the GHCN station distribution and temporal availability, particular focus was given to four regions: Europe, Australia, East and West United States. The results identify a general underestimation of the daily maximum and overestimation of the daily minimum temperatures in both ERA5 analysis and operational forecasts, highlighting a known limitation of the ECMWF model in underestimating the diurnal temperature range. Our results also indicate a reduction of the errors in ERA5 when comparing the latest decade with the 1980’s, which is likely to be associated with an enhanced quality of the analysis due to a higher constrain emerging from the satellite data. The ERA5 analysis outperforms 1 day-ahead weather forecasts, which show some degree of improvement in the considered 5-year period, being associated with model upgrades.

 

This work was developed in the framework of the CoCO2 project. CoCO2 project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 958927.

How to cite: Lopes, F., Dutra, E., and Boussetta, S.: Evaluation of Daily Temperature Extremes in the ECMWF ERA5 Reanalysis and Operational Weather Forecasts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7064, https://doi.org/10.5194/egusphere-egu23-7064, 2023.

EGU23-7481 | ECS | Posters on site | AS1.1

Study of the 2 m temperature bias of the numerical weather forecasting model Arome over the French Alps 

Danaé Préaux, Ingrid Dombrowski-Etchevers, Isabelle Gouttevin, and Yann Seity

The Arome numerical weather prediction system is routinely used for weather forecasting over the mountains of the French Alps, Pyrénées and Corsica. However, its skills at temperature forecasting are altered by several 2 m temperature biases: (1) a cold bias at high altitude, (2) a low-altitude warm bias occurring in stably stratified layers and (3) a warm bias during snowfall situations.

Targeted numerical simulations (successive activation of some dynamic, physical and assimilation modifications) were carried out on the day of January 12, 2021, a problematic snowy situation in the Arve valley (Haute-Savoie, French Alps).

Over this period, the operational version of Arome has a mean absolute error (MAE) of 2.3°C in the valley. The increase of vertical resolution does not improve the performance of the model in the valley. The MAE is nevertheless decreased from 1.4 to 1.1°C in the mid-altitude range and from 1.5 to 1.2°C above 2000 m. Conversly, the use of a new surface scheme (ISBA-DIF) associated with a more complex snowpack model (ISBA-ES) allows to better represent the arrival of the warm front in the valley and reduces the error (to 1.8°C) whatever the altitude. The current surface scheme therefore seems too simplistic to correctly model soil-atmosphere interactions in the mountains. Forcing Arome with full-day data assimilation also reduces the bias in the valley (to 2.0°C). However, this experiment deteriorates the scores in the mid-altitude and high-altitude mountains. Furthermore, the situation has a poor initial state as biases are present even before the snow event starts. This may point towards deficiencies in the assimilation of in-situ data in mountain regions, that should be overcome in future work.

These results show that the warm bias during this snowy event has multiple origins. A carefull analysis of other situations will be needed to confirm and correct theses biases. 

How to cite: Préaux, D., Dombrowski-Etchevers, I., Gouttevin, I., and Seity, Y.: Study of the 2 m temperature bias of the numerical weather forecasting model Arome over the French Alps, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7481, https://doi.org/10.5194/egusphere-egu23-7481, 2023.

Infrasound waves generated by phenomena at the Earth’s surface can travel to these levels before returning to the surface and being detected. Observations like travel time, change in backazimuth angle, and trace velocity contain integrated information of all the levels the wave travelled through. These often include stratospheric and mesospheric levels which are otherwise poorly observed.
In this work we take a data assimilation technique, the Modulated Ensemble Transform Kalman Filter, which is commonly used in satellite data assimilation, and illustrate how it can be readily used for infrasound data assimilation. We highlight the similarities between the two problems, and the particular challenges in extracting information from summarised quantities. To our knowledge, this is the first work doing data assimilation with a full ray-tracing model as forward operator.

How to cite: Amezcua, J. and Näsholm, S. P.: Using satellite data assimilation techniques to combine infrasound observations and a full ray-tracing model to constrain atmospheric variables, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8665, https://doi.org/10.5194/egusphere-egu23-8665, 2023.

EGU23-8919 | Orals | AS1.1

PREVENIR: Japan-Argentina Cooperation Project for Heavy Rain and Urban Flood Disaster Prevention 

Takemasa Miyoshi, Celeste Saulo, Shigenori Otsuka, Juan Ruiz, Yanina G. Skabar, Arata Amemiya, Tomoo Ushio, Hirofumi Tomita, Tomoki Ushiyama, and Masaya Konishi

This presentation provides an overall summary of the project PREVENIR and recent activities about data assimilation and numerical weather prediction (NWP) research. PREVENIR is an international cooperation project between Argentina and Japan since 2022 for five years under the Science and Technology Research Partnership for Sustainable Development (SATREPS) program jointly funded by the Japan International Cooperation Agency (JICA) and the Japan Science and Technology Agency (JST). The main goal is to develop an impact-based early warning system for heavy rains and urban floods designed for two highly vulnerable urban basins in Argentina: one located in Buenos Aires Province and the other in Córdoba Province. PREVENIR takes advantage of leading research on simulations and Big Data Assimilation (BDA) with the Japan’s flagship supercomputer “Fugaku” and its predecessor “K” and develops a total package for disaster prevention, namely, monitoring, quantitative precipitation estimates (QPE), nowcasting, BDA and NWP, hydrological model prediction, warning communications, public education, and capacity building. Here, the Japanese leading institutions in the scientific research and operational services, i.e., RIKEN, Osaka University, the International Centre for Water Hazard and Risk Management (ICHARM), and the Japan Meteorological Agency (JMA) closely work with the Argentinian counterparts, i.e., the National Meteorological Service, the National Water Institute, and the National Research Council of Argentina under the strong support of JICA, JST, and Argentinian Foreign Affairs Ministry. Heavy rains and urban floods are important global issues under the changing climate. The total package for disaster prevention will be the first of its kind in Argentina and will provide useful tools and recommendations for the implementation of similar systems in other parts of the world.

How to cite: Miyoshi, T., Saulo, C., Otsuka, S., Ruiz, J., Skabar, Y. G., Amemiya, A., Ushio, T., Tomita, H., Ushiyama, T., and Konishi, M.: PREVENIR: Japan-Argentina Cooperation Project for Heavy Rain and Urban Flood Disaster Prevention, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8919, https://doi.org/10.5194/egusphere-egu23-8919, 2023.

EGU23-8950 | Posters on site | AS1.1

Exploring Domain Size for WRF High-Resolution Urban Rainfall Simulation 

Sichan Du, Lu Zhuo, Elizabeth J. Kendon, and Dawei Han

Abstract: With climate change, rainfall is expected to get more intense, leading to cities being increasingly at risk of urban flooding. Understanding local climate change over cities has therefore become a priority for the scientific community and city planners on building resilient cities and mitigating hydrometeorological disasters. Very high resolution (km-scale, ‘convection-permitting’) climate models are required to adequately represent cities and local rainfall extremes. Here we assess the Weather Research and Forecasting (WRF) model for simulating urban rainfall. Despite the wide application of WRF in rainfall simulations (including urban areas), there are limited investigations on the impact of the domain size and how to search for a suitable domain size over a particular city region.

To fill this knowledge gap, Newcastle upon Tyne is selected as the study area to simulate a summer heavy rainfall event with ERA5 (a fifth-generation dataset of global reanalysis developed by the European Centre for Medium-Range Weather Forecasts) as the input data and a radar product from the UK Met Office for validation. Accordingly, different domain sizes with the convection-permitting resolutions from 1 km to 4.5 km (increment: 0.5 km) are explored, and the hourly model outputs are compared with the radar observation data.

This study has proposed and tested a method to decide the most suitable domain size. By using eight assessment indexes (including pattern, cumulative time series, hourly time series, particular values (max/min/mean) as well as the seven statistical indicators of each data and overall data), there are two preliminary conclusions: 1) 200 km × 200 km is the best domain size for the single domain simulation; 2) For 200 km × 200 km or smaller domain sizes, higher resolution produces better results, but for 250 km × 250 km or large domain sizes, resolution sensitivity is opposite. Regarding next steps, the above procedure will be further investigated by applying it to more extreme rainfall case studies and to other cities in order to assess whether results here are generally applicable, and therefore the optimal domain configuration can be usefully applied to produce reliable urban rainfall simulations.

How to cite: Du, S., Zhuo, L., Kendon, E. J., and Han, D.: Exploring Domain Size for WRF High-Resolution Urban Rainfall Simulation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8950, https://doi.org/10.5194/egusphere-egu23-8950, 2023.

EGU23-9199 | ECS | Orals | AS1.1

ECMWF-OpenIFS Climate Sensitivity to Horizontal Resolution and Time Step 

Abhishek Savita, Joakim Kjellsson, Robin Pilch Kedzierski, Wonsun Park, Mojib Latif, and Sebastian Wahl

We explored the sensitivity of the atmosphere general circulation model OpenIFS to horizontal resolution and time step. We conducted a series of experiments at different horizontal resolutions (i.e., 100, 50, and 25 km) while maintaining the same time step (i.e., 15 minutes), and using different time steps (i.e., 60, 30 and 15 minutes) at 100 km horizontal resolution. We find that the zonal wind bias over the Southern Ocean has significantly reduces at high horizontal resolution (i.e., 25 km), and that this improvement is evident too when using a coarse resolution model with smaller time step (i.e., 15 min and 100 km horizontal resolution). There is also evidence of improvements in the mid-latitude westerly jet in the Northern Hemisphere too, which is also sensitive to both model time step and horizontal resolution. We have also found that the biases in wave speed and wave amplitude reduce when we shorten the model time step or increase the model horizontal resolution. Therefore, it is clear that the improvement in the highest horizontal resolution (i.e., 25 km) simulation is a combination of both the enhanced horizontal resolution and shorter time step. We speculate that the improvement in the surface zonal wind bias in the coarse resolution with shorter time step (i.e., 15 min and 100 km horizontal resolution) simulation is mostly due to shallow convection that is intensified at shorter time step. In addition, we have also noticed improvements in the surface-air temperature when a high resolution and a smaller time step; however, the precipitation bias is independent of the model’s horizontal resolution and time step.

We propose based on OpenIFS that by reducing the time step in a coarse resolution atmospheric model (at least in OpenIFS), one can alleviate the surface-wind biases in the extratropics that is important for e.g., climate modeling in the Southern Ocean sector.

How to cite: Savita, A., Kjellsson, J., Pilch Kedzierski, R., Park, W., Latif, M., and Wahl, S.: ECMWF-OpenIFS Climate Sensitivity to Horizontal Resolution and Time Step, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9199, https://doi.org/10.5194/egusphere-egu23-9199, 2023.

Significant problems in numerical weather prediction modeling systems appear when the horizontal grid-spacing is between 20 km and 1 km and when deep convection is important. These scales are usually termed “Gray Scales”.  Techniques have been developed so that the behavior of the convective parameterization changes with the horizontal grid spacing of the model; such parameterizations are said to become “scale-aware”. Commonly used techniques involve applying a scaling approach to smoothly transition from parameterized to resolved convection. These are similar to an elegantly simple mathematical method originally developed by Arakawa et al. (2011), which scales the convective tendencies in dependence on the convective area fraction. Here we show that the scaling approaches are flawed, since they fail to consider the fact that the impacts of deep convection on those scales are not limited to one grid box, and usually – because of the scaling -- leads to light precipitation covering too much area, as we have previously shown in HRRR simulations. Any scaling approach is especially flawed in areas of light forcing (such as daytime heating) and in the tropics, when the explicit microphysics parameterization is not yet producing precipitation. We will show examples of these problems and discuss possible solutions as applied to NOAA’s new RRFS storm-scale modeling system.

How to cite: Grell, G., Li, H., and Freitas, S.: Flaws of scale-aware techniques in convective parameterizations, as discovered in NOAA’s operational convection-allowing modeling systems: an attempt to improve them., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10514, https://doi.org/10.5194/egusphere-egu23-10514, 2023.

A squall line system that occurred on 9-10 April 2016 over southern China was used to investigate the impact of incremental analysis update (IAU) initialization under the replay configuration on its forecasts. The ERA5 global reanalysis and the forecast field of the regional Weather Research and Forecasting (WRF) Model were used to construct the analysis increment. The results showed that IAU initialization reduced the imbalance caused by the introduction of the low-resolution global reanalysis into the high-resolution regional WRF model and retained the microphysical information in the forecast field of the regional WRF model, which reduced the spin-up time. Compared with the cold start run initialized directly by the ERA5 reanalysis, the linear structure and precipitation distribution of the squall line system using IAU initialization were closer to those in the observations. Further analyses indicated that the improvement of the squall line forecasts using IAU initialization was mainly related to the faster development of cold pool caused by retaining the microphysical information in the forecast field of the regional WRF model and the more favorable stratification conditions corrected by the IAU increment.

How to cite: gao, Y. and wang, X.: Impact of incremental analysis update initialization under the replay configuration on forecasts of a squall line event in southern China, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11619, https://doi.org/10.5194/egusphere-egu23-11619, 2023.

EGU23-12177 | ECS | Orals | AS1.1

A multi-center exercise on the sensitivity of PAZ GNSS Polarimetric RO for NWP modeling 

Ramon Padullés, Estel Cardellach, Antía Paz, F. Joe Turk, Chi O. Ao, Kuo Nung Wang, Manuel de la Torre Juárez, Michael J. Murphy, Jennifer S. Haase, Katrin Lonitz, and Daisuke Hotta

A better understanding of the thermodynamics of heavy precipitation events is necessary towards improving weather and climate models and quantifying the impact of climate variability on precipitation. However, there are limited observations available to assess the thermodynamics model structure within heavy precipitation conditions.

In 2009, the Earth Observation Group at ICE-CSIC/IEEC conceived the polarimetric radio occultations (GNSS-PRO) technique with the aim to obtain simultaneous measurements of the vertical structure of precipitation and its associated thermodynamic state. Based on the standard GNSS radio occultation technique (GNSS-RO), polarimetric RO consists of an identical instrument working at two orthogonal linear polarizations (H,V) instead of the conventional circularly polarized antenna. This allows us to measure the differential phase delay at both ports, hypothesized to be positive in the presence of asymmetric hydrometeors (large raindrops, snowflakes, ice aggregates). This technique is being tested for the first time on the proof-of-concept mission Radio Occultations and Heavy Precipitation (ROHP) aboard PAZ satellite, operating since 2018. The results of the first 4 years of PRO observations already showed sensitivity to heavy precipitation and its associated cloud structures.

Such technique provides high quality thermodynamic observations of water vapor, temperature and pressure with high vertical resolution, along with the vertical measurements of the phase delay linked to the precipitation structure. This study focuses on comparing these observations with the simulations based on the outputs of several operational models and reanalysis for a set of selected cases. The main objectives of the study are: (1) To check if the models reproduce the main features of the actual data; (2) to assess whether different models/schemes result in different GNSS PRO observables, and whether these differences are larger than the measurement uncertainty; and (3) to examine the utility of PAZ GNSS PRO observations for model validation and diagnosis.

This effort provides insight on future methods to assimilate the PRO profile alongside other conventional (non-polarimetric) RO data, including work towards building a forward operator. The exercise includes comparisons with ECWMF operational model, ERA-5 reanalysis, the operational NWP at the Japan Meteorological Agency, and a near-real-time implementation of the WRF regional model over the northeastern Pacific produced at the Center for Western Weather and Water Extremes (CW3E) called West WRF, forced with ECMWF and GFS.

How to cite: Padullés, R., Cardellach, E., Paz, A., Turk, F. J., Ao, C. O., Wang, K. N., de la Torre Juárez, M., Murphy, M. J., Haase, J. S., Lonitz, K., and Hotta, D.: A multi-center exercise on the sensitivity of PAZ GNSS Polarimetric RO for NWP modeling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12177, https://doi.org/10.5194/egusphere-egu23-12177, 2023.

EGU23-12636 | ECS | Posters on site | AS1.1

Testing the AROME Hybrid 3DEnVar for convective-scale NWP over Austria 

Kaushambi Jyoti, Martin Weissmann, Philipp Griewank, and Florian Meier

Ensemble and hybrid ensemble-variational Data Assimilation (DA) methods incorporating ensemble-based flow-dependent error statistics into state estimation have emerged in recent decades. In a hybrid DA, the background error covariances are a combination of ensemble covariances and static climatology. The ensemble component provides flow-dependency and non-linear error growth critical for convective-scale models, and the static climatology mitigates the effects of a small ensemble size. Hybrid ensemble variational DA methods were recently implemented in the convective-scale NWP model AROME at Meteo-France.

We present our findings from testing Hybrid-3-Dimensional Variational Data Assimilation in convective-scale NWP model AROME over Austria. Given Austria's unique alpine orography, we investigate the impact of applying different weighting to flow-dependent covariances in hybrid DA for a summertime convection case over central Europe. In addition to the hybrid weights, we explore optimal ensemble size, the increase of ensemble size with a time-lagged approach as well as suitable localization settings. Finally, we compare our results to the 3-dimensional variational data assimilation (3DVar) operational model forecast of GeoSphere Austria and discuss the potential benefits, drawbacks, and challenges of using hybrid DA over traditional 3DVar.

Keywords: summertime convection; hybrid-3DEnVar; AROME NWP model; flow dependent background error covariance

How to cite: Jyoti, K., Weissmann, M., Griewank, P., and Meier, F.: Testing the AROME Hybrid 3DEnVar for convective-scale NWP over Austria, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12636, https://doi.org/10.5194/egusphere-egu23-12636, 2023.

EGU23-12877 | ECS | Orals | AS1.1

The influence of radiosonde observations on the sharpness and altitude of the tropopause 

Konstantin Krüger, Andreas Schäfler, George Craig, and Martin Weissmann

The shape, sharpness and altitude of the extratropical tropopause (TP) is strongly linked to the position and the strength of the subtropical and polar jet streams that determine the weather in the midlatitudes. However, current numerical weather prediction models fail to correctly represent the sharpness of the TP (i.e., the gradients of wind and temperature). In this study, we address the question if and how the assimilation of radiosonde observations influences the TP representation and whether it acts to sharpen or smooth near near-tropopause gradient.

We investigate the influence by comparing temperature, Brunt-Väisälä frequency (N²) and wind profiles of the observations (y), the model background (xb) and the analysis (xa) in tropopause-relative coordinates.

In total, we analyse more than 9000 radiosondes that were assimilated by the European Centre for Medium-Range Weather Forecast’s Integrated Forecast System (ECMWF IFS) over Canada, the Northern Atlantic and Europe during a one-month period in fall 2016. To test whether the diagnosed influence is caused by the assimilated radiosondes, we conducted a data denial experiment that excluded 500 radiosondes that were launched in the framework of the North Atlantic Waveguide and Downstream EXperiment (NAWDEX) field campaign. In observation space, we investigate the departures (i.e., the differences between y, xb and xa) in the control run (CTR) with all radiosondes considered and the denial run (DEN) without the NAWDEX radiosondes.

The observed minimum temperature at the TP is overestimated in the background forecast (warm bias, ~1 K). Above, in a layer 0.5-2 km, the temperature is underestimated (~0.5 K). Consequently, the sharpness of the TP which is diagnosed by the maximum of N² is also underestimated. We show that data assimilation is able to improve the temperature and to slightly strengthen the TP in the analysis, particularly in situations where the observed and model TP altitude fairly agree. In the data denial experiment we show that this influence exists in the CTR, but not in the DEN run, and thus can be attributed to the assimilation of the radiosonde data.

Regarding wind, we find an underestimation of the maximum wind at and below the TP (0.5-1 m s-1) and demonstrate that the assimilation of radiosonde winds is able to improve the wind profile across the TP. The bias and the positive influence are found to be stronger in situation of strong wind, i.e., the jet stream.

Although data assimilation is able to improve wind and temperature gradients across the tropopause by pulling the background closer to the observations, the individual analysis profiles still underestimate the sharpness of the tropopause. The misrepresented TP in models may impact the quality of weather and climate projections.

How to cite: Krüger, K., Schäfler, A., Craig, G., and Weissmann, M.: The influence of radiosonde observations on the sharpness and altitude of the tropopause, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12877, https://doi.org/10.5194/egusphere-egu23-12877, 2023.

EGU23-13110 | Orals | AS1.1

Recent progress and outlook for the ECMWF Integrated Forecasting System 

Gianpaolo Balsamo, Florence Rabier, Magdalena Balmaseda, Peter Bauer, Andy Brown, Peter Dueben, Steve English, Tony McNally, Florian Pappenberger, Irina Sandu, Jean-Noël Thepaut, and Nils Wedi

ECMWF recent improvements on scientific and technological fronts will be presented. In 2021 two new operational upgrades of the Integrated Forecasting System (IFS), cycles 47r2 and 47r3, have been introduced. In 2022 the ECMWF High-Performance Computing (HPC) facility has migrated from Reading, UK to a new data centre in Bologna, Italy, and on 18 October 2022 the operational system has been ported to a new supercomputer with enhanced capacity, that will pave the way for an increase in resolution in 2023 with the implementation of IFS cycle 48r1.

IFS Cycle 47r2 was first introduced on 11 May 2021 and its key features included changing the vertical resolution of the Ensemble forecast system (ENS) from 91 to 137 levels, the same used in the high-resolution forecast (HRES). This was made possible by introducing single precision arithmetic in both the HRES and ENS forecast systems. The single precision itself is neutral but enabled the ENS change which led to significant forecast skill improvement. Five months later, ECMWF introduced Cycle 47r3 operationally on 12 October 2021. This included major changes to the model physics that had been under development for several years. A more consistent formulation of boundary layer turbulence, new deep convection closure and cloud microphysics changes have increased the realism of the water cycle.

The next science upgrade, cycle 48r1, will be implemented in 2023 on our new HPC system in Bologna. This will see an enhancement of the ENS horizontal resolution to the TCo1279 grid (approximately 9km), the same resolution currently used by the HRES. There will also be an increase of the data assimilation resolution used in the incremental 4D-Var minimisation, and the use a new object orientated approach to run the 4D-Var atmospheric data assimilation (OOPS). Other important changes in 48r1 include running a daily 100 members extended range ensembles, introducing a new multi-layer snowpack model, and improving the atmospheric energy and water conservation.

Looking further ahead, future higher resolution capabilities will be accelerated by the digital twin developments under the European Commission Destination Earth programme, which will build km-scale capability for a range of potential future HPC architectures. Major efforts have been invested in the code scalability of the Integrated Forecasting System to be able to run on GPUs and investigating alternative dynamical core options. Data assimilation will evolve towards a fully coupled approach to maximise the exploitation of observations and benefit all components of the Earth system (atmosphere, land, ocean) in a consistent way. Machine Learning (ML) will be exploited to enhance the performance and efficiency of our systems. 

Finally, our Copernicus partnership with the European Commission has just entered its second phase. Synergistic interactions between meteorology and composition will be pursued for the mutual benefit of both and preparatory steps for next ECMWF climate reanalysis, ERA6, and new seasonal forecasting system, SEAS6, have already started. Several major upgrades in ERA6 and SEAS6 will aim at mitigating against systematic model biases to produce climate records with significantly improved time consistency, and enhanced reliability for extended-range predictions.

How to cite: Balsamo, G., Rabier, F., Balmaseda, M., Bauer, P., Brown, A., Dueben, P., English, S., McNally, T., Pappenberger, F., Sandu, I., Thepaut, J.-N., and Wedi, N.: Recent progress and outlook for the ECMWF Integrated Forecasting System, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13110, https://doi.org/10.5194/egusphere-egu23-13110, 2023.

EGU23-13449 | ECS | Posters on site | AS1.1

Ensemble-based regional reanalysis system for Central Europe: Development framework and outlook 

Alexander Kelbch, Thomas Spangehl, Michael Borsche, Thomas Rösch, and Florian Imbery

The development of regional reanalyses aims at the provision of high-resolution data sets that are suitable for climate applications and climate services. As the desired high-resolution information can barely be provided by either synoptic or remote sensing observation data, a growing interest in high-quality regional reanalyses is recognisable. Particular demand arises from the renewable energy sector. Further quality gains are expected by using an ensemble approach, e.g. by making available the desired uncertainty information when moving towards higher resolution. 
Within the framework of the Innovation Programme for applied Researches and Developments (IAFE) at Germany's national meteorological service (DWD) our project aims to develop and evaluate an operational ensemble-based regional reanalysis system incorporating the current NWP model of DWD (ICON). One final goal of the project is to provide a basic framework for user-oriented verification.  
We first present the Basic Cycling Environment (BACY) being mainly characterized by its modularity, robustness, user-friendlyness as well as its high complexity. Thus, our future reanalysis system will be a certain BACY version with "frozen" specifications. To assess BACY specifications such as model resolution, number of ensemble members, domain size and choice of output variables NWP simulations will be performed and first simulation results will be presented.

How to cite: Kelbch, A., Spangehl, T., Borsche, M., Rösch, T., and Imbery, F.: Ensemble-based regional reanalysis system for Central Europe: Development framework and outlook, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13449, https://doi.org/10.5194/egusphere-egu23-13449, 2023.

EGU23-14259 | ECS | Orals | AS1.1

Forecast sensitivity to the assimilation of observational data - two case studies for Australia 

Cassandra Rogers and Chris Tingwell

Australian weather forecasts use Numerical Weather Prediction (NWP) model output. Forecast accuracy is improved by assimilating a range of observational data which includes Australian Bureau of Meteorology station data. The significant investment by the Bureau of Meteorology in the national observing network, and the constant evolution of observational technologies, requires an ongoing assessment of the scientific value of the network components. Examining an objective measure of the impact of each assimilated observing system on the quality of short-term NWP forecasts can potentially guide planning and investment decisions related to network efficiency and effectiveness. 

Traditional techniques for assessing the impact of observations in NWP are inflexible (i.e. they require dedicated trials) and computationally expensive, but a widely used technique, known as adjoint-based Forecast Sensitivity to Observations (FSO), can provide forecast impact information continuously, flexibly, and in near real-time. We use archived FSO data to assess the relative forecast impact of in-situ data for different instruments and variables. We use two case studies to examine the impact of 1) three upper-air measurement instruments - radiosondes, aircraft, and a wind profiler - through the atmosphere at Sydney Airport, and 2) Automatic Weather Station surface observations along the Great Barrier Reef. These studies aim to provide network planners with information that can guide observations rationalisation decisions. 

How to cite: Rogers, C. and Tingwell, C.: Forecast sensitivity to the assimilation of observational data - two case studies for Australia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14259, https://doi.org/10.5194/egusphere-egu23-14259, 2023.

EGU23-14671 | ECS | Orals | AS1.1

A feature based perspective on upscale error growth. 

Sören Schmidt, Michael Riemer, and Tobias Selz

Atmospheric predictability is fundamentally limited by the upscale growth of initial small-scale, small-amplitude errors. Studying upscale error growth mechanism is essential to better understand this fundamental limitation. Upscale error growth is frequently investigated by spectral analysis. By design, however, spectral analysis is non-local. A local investigation of error growth in different flow configurations is desirable, though, to study the well-known flow dependence of error growth. We thus take here a complementary approach to spectral analysis and identify local regions of prominent errors as “error features”.

We have developed an automated algorithm to identify error features in gridded data and track their spatial and temporal evolution. Errors are considered in terms of potential vorticity (PV) and near the tropopause, where they maximize. A previously derived PV-error tendency equation is evaluated to quantify the different contributions to error growth in previously published upscale error growth experiments with the global prediction Model ICON from the German Weather Service. Errors in these experiments grow from very small initial-condition uncertainty (three orders of magnitude smaller than current-day uncertainty) and due to differences in the seeding of a stochastic convection scheme.

Spatial composites centered on the centroid of error features indicate that features are primarily generated ahead of an upper-tropospheric trough. The environment surrounding the features at the time of their first detection is characterized by locally enhanced lower to mid tropospheric moisture, latent heat release, and upper tropospheric divergence. Subsequently, this moist-diabatic nature of the error environment becomes gradually less prominent. The evaluating of process specific error growth rates enables to quantify the upscale growth mechanics in more detail. For this purpose, we integrate the growth rates over the respective area associated with an error feature. Examination of the combined growth rates of all features reproduces the previously found three-phased multi-scale upscale growth paradigm: Errors are first generated on the small scale by differences in latent heat release, then projected onto the tropopause region by associated differences in upper tropospheric divergent outflow, and finally amplified by nonlinear Rossby wave dynamics. The growth rates from a single feature, however, can substantially differ from the mean picture. Some features, e.g., go through the described stages in a cyclic sequence, and the main focus of the presentation will be on the differences between fast and slowly amplifying error features.

How to cite: Schmidt, S., Riemer, M., and Selz, T.: A feature based perspective on upscale error growth., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14671, https://doi.org/10.5194/egusphere-egu23-14671, 2023.

Precipitation characteristics are expected to change in the future as a consequence of global climate change. For example, high-intensity precipitation is expected to become more frequent in some areas of the world. The short time scales and small spatial scales of intense precipitation events pose challenges for numerical weather prediction (NWP) models. Measurements of precipitation characteristics from in-situ and remote sensing instrumentation are often available at much higher time resolution than common NWP model output, and need to be aggregated for validation studies. Here we present a methodology to enable the comparison of precipitation observations and model output at the time scale of the model time steps. Our analysis is focused on an extreme, convective precipitation event during 30th July 2019 in Bergen, Norway (60.38ºN, 5.33ºE, 12 m a.s.l.). We use high-resolution measurements of precipitation characteristics from a Micro Rain Radar Metek MRR-2, an Ott Parsivel2 Disdrometer, and a TPS-3100 Hotplate Pluviometer. Model precipitation was extracted from the operational NWP model MetCoOp that uses a horizontal grid spacing of 2.5 km and 65 vertical levels as part of the HARMONIE AROME model configuration. Using DDH (Diagnostics par Domaines Horizontaux), a novel tool for extracting prognostic variables from the model at a time-step resolution, we extracted a detailed dataset from a NWP model reforecast at every time step (75s), for a 62.5 by 62.5 km subdomain centred around the measurement site. We characterised precipitation by investigating five parameters, namely rain rate, liquid water content, mean volume diameter, the normalised intercept parameter, and terminal fall velocity. The newly developed methodology enabled a direct comparison of the observed precipitation characteristics with corresponding parameters from the model prediction for the convective rainfall event. Despite a generally reasonable correspondence between all parameters in the model and observations, the model struggled with underestimation of rainfall intensity during the high-intensity periods. The onset and intensity of precipitation depended strongly on location for the investigated event. Higher time resolution provided more detailed insight into intensity, timing and spatial variability of the modelled precipitation compared to the more commonly used hourly interval. Our new methodology can be easily applied to other precipitation events, such as frontal rainfall events, and thus provide process-level understanding of precipitation characteristics simulated by high-resolution NWP models. 



How to cite: Steinslid, M., Sodemann, H., and Kähnert, M.: Enabling the comparison of high-resolution precipitation observations with numerical weather prediction model simulations at every model time-step, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14882, https://doi.org/10.5194/egusphere-egu23-14882, 2023.

EGU23-15208 | Posters on site | AS1.1

Methods of weather forecasting and navigation in the N-Atlantic in the Middle Ages tested with a modern NWP tool 

Haraldur Ólafsson, Philipp Weitzel, Iman Rousta, Benoît Soula, and Léo Jacopin

Weather forecasting in the Middle Ages was most likely mostly based on persistence, and there are indications that persistence and correlation between elements of the sensible weather, in particular fog, helped in navigation in the N-Atlantic during the Viking age.

Investigation of the weather in the CARRA dataset, produced by dynamic downscaling, reveals that the connection between wind directions and fog is different on the leg between Iceland and Greenland from what it is between Iceland and Norway.  Consequently, the same navigational rules could not be applied on both these legs, making navigation from Iceland to Greenland even more difficult than navigation from Norway to Iceland.  This, in addition to very high frequency of fog and of strong winds in the vicinity of Greenland, made sailing and navigation between Iceland and the Medieval Nordic settlements in Greenland exceptionally difficult.    

How to cite: Ólafsson, H., Weitzel, P., Rousta, I., Soula, B., and Jacopin, L.: Methods of weather forecasting and navigation in the N-Atlantic in the Middle Ages tested with a modern NWP tool, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15208, https://doi.org/10.5194/egusphere-egu23-15208, 2023.

Numerical weather prediction (NWP) models are frequently used tools in operational weather forecasting. The NWP bases on current weather observations and processing of this data using computational models to forecast possible weather conditions. The aim of the study was to determine the optimal configuration of the Weather Research and Forecasting (WRF) model , version 4.2 (Skamarock et al. 2008), for more effective weather forecasting for the area of Poland. For model evaluation, we used observations from the IMWM-NRI network (above 50 meteorological stations). Numerical simulations were run using GFS model data was obtained from NOAA's NCEP servers. The WRF model was configured for a 3 km horizontal resolution grid, using unique parameterization settings for this model. Validation of forecast data was performed using statistical measures recommended by the WMO, e.g. mean error, mean absolute error, mean squared error, showing the values of forecast error. In this study, the model settings were configured based of other papers for Europe (Stergiou et al. 2017, Mooney et al. 2013, Kioutsioukis et al. 2016, Garcia-Diez et al. 2015, Carvalho et al. 2014, Santos Alamillos 2013), especially from its central part (Wałaszek et al. 2014, Kryza et al. 2017). The results of the work present statistical summaries of optimal model parameterization schemes, depending on their verifiability. Model configuration characterized by the best performance will be further examined over a longer time period (in the study, the average MAE for air temperature was 0.8°C). The research was funded by National Science Center (project number: 2017/27/N/ST10/00565)

How to cite: Kendzierski, S.: Influence of resolution and parameterization of the WRF model on the verifiability of weather forecast, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15595, https://doi.org/10.5194/egusphere-egu23-15595, 2023.

EGU23-15927 | Orals | AS1.1

Potential of accumulated parameterisation tendencies from AROME-Arctic for stochastic parameterisation erturbation patterns 

Harald Sodemann, Marvin Kähnert, Teresa Maaria Remes, Petter Ekrem, Rafael Grote, and Inger-Lise Frogner

Stochastic parameterisations are an important way to represent uncertainty in the deterministic forecasting models underlying ensemble prediction systems. Current stochastic parameterisation approaches use random correlation patterns that are unrelated to the atmospheric flow to induce coherent perturbations to parameterisations. Here we replace these patterns by accumulated tendency fields from parameterized physical processes in the HARMONIE-AROME system. Our rationale is that by perturbing the parameterisations with a field that reflects where parameterisations are most active, rather than random, the model obtains a more targeted increase in the degrees-of-freedom to represent forecasting uncertainty.

Here we study a large marine cold-air outbreak over the Norwegian Sea. Strong heat fluxes persisted near the ice edge, and shallow convection dominated in the center of the model domain. Perturbation fields are diagnosed from individual tendency diagnostics implemented in AROME-Arctic within ALERTNESS. Total physical tendencies for the horizontal winds, for temperature and humidity are accumulated with a time filtering throughout the 66 h forecast period.

Accumulated tendencies show overlapping and differing centers of activity. Wind parameterisations are active near the ice edge, and with smaller scale variability over land areas. Temperature tendency patterns show activity more confined to the ice edge, and the coast of northern Scandinavia. Such spatially coherent patterns of parameterisation activity are meaningfully related to current weather. To exploit the relation between parameterisation activity and weather patterns for ensemble perturbation, we conduct sensitivity tests of cloud parameterisation parameters in a single-column model version MUSC and the full model version. First results illustrate our progress towards the use of diagnostic perturbation patterns for stochastically perturbed perturbations in the HarmonEPS system.

How to cite: Sodemann, H., Kähnert, M., Remes, T. M., Ekrem, P., Grote, R., and Frogner, I.-L.: Potential of accumulated parameterisation tendencies from AROME-Arctic for stochastic parameterisation erturbation patterns, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15927, https://doi.org/10.5194/egusphere-egu23-15927, 2023.

EGU23-16670 | Orals | AS1.1

EURO1k: A high-resolution European weather model developed by Meteomatics 

Julie Thérèse Pasquier, Johannes Rausch, Alexander Stauch, and Martin Fengler

Accurate and precise weather forecasting is essential for a wide range of applications and industries, from agriculture to transportation to renewable energy. However, current weather models often struggle to represent the weather accurately due to limitations in spatial resolution. Global models with broad resolution are unable to represent small-scale weather features, such as convective thunderstorms or local wind patterns, while regional high resolution models are highly dependent on boundary conditions and typically provide forecasts for a small domain. To fill this gap, Meteomatics has developed the EURO1k model, the first pan-European weather model with a 1km2 resolution.

 

The EURO1k model consists of approximately 20 million grid points and is run 24 times per day, with a forecast horizon of 24 hours. It is based on the WRF (Weather Research and Forecasting) model and uses global ECMWF-IFS model data for boundary conditions. In addition to standard data sources such as weather stations, radar and satellite data, and radiosondes, the EURO1k model also ingests data from a network of Meteodrones, small unmanned aircraft systems (UAS) developed by Meteomatics which collect vertical atmospheric profiles up to 6000m in altitude. The high resolution of the EURO1k model allows it to accurately represent small-scale weather patterns, resulting in highly accurate and precise forecasts. This is evident in verifications against weather station observations, which show a very good agreement between model output and a range of weather variables including wind, temperature, and radiation.

 

Statistical analyses of EURO1k model output against observations from 5000 weather stations in Europe demonstrate better accuracy compared to other global and regional models. This has important implications for industry and the public. The EURO1k model can improve the forecasting of extreme weather events, allowing for better preparation and response. It can also enhance the prediction of renewable energy production, which depends on weather conditions. This increases the cost efficiency of renewable energies and help to reduce CO2 emissions. And, most importantly, it provides a more accurate and reliable weather forecast for communities across Europe. Overall, the EURO1k model represents a major advance in numerical weather prediction, bringing improved understanding and forecasting of the weather to a wide range of users.

How to cite: Pasquier, J. T., Rausch, J., Stauch, A., and Fengler, M.: EURO1k: A high-resolution European weather model developed by Meteomatics, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16670, https://doi.org/10.5194/egusphere-egu23-16670, 2023.

EGU23-16972 | Orals | AS1.1

LiDAR-based data assimilation during offshore transient events 

Mostafa Bakhoday-Paskyabi, Hai Bui, and Mohammadreza Mohammadpour Penchah

Atmospheric conditions and instabilities affect directly the performance of modern large offshore wind farms and several offshore operations, particularly farther offshore in deep waters. However, our current knowledge regarding to the atmospheric processes over a wide range of spatiotemporal scales needs further improvements by the use of measurements, and sophisticated modelling of Marine Atmospheric Boundary Layer (MABL) processes relevant to the offshore wind energy. Processes like gravity waves, Open Convective Cells (OCCs), Low Level Jets (LLJs) affect both horizontal and vertical structures of MABL flow fields and the interactions between the ambient flow and offshore constructions. For example, LLJs are common physical processes over the Southern North Sea. These transient events occur during stably stratified atmosphere with jet cores at heights between 150 m and 300 m. Strong positive and negative shears are observed below and above the nose of LLJ (i.e a maxima in the vertical wind profile). Structure, timing, shape, and characteristics of LLJs influence the loads on turbines and the overall power generation of offshore wind parks. Therefore, precise modelling and measurement of these episodes are highly important.

While advanced measurement systems such as LiDAR provides important information on formation and characteristics of LLJs, such measurements are sparse in time and space. On the other hand, modelling tools are sensitive in prediction of LLJ characteristics such as LLJ’s height, spatial position, and timing, the choice of initial and boundary conditions, and planetary boundary layer schemes used in the Numerical Weather Prediction models (NWPs).  Predictive skills of these models can be enhanced through assimilation of available quality observational data with NWPs like Weather Research and Forecasting (WRF) model.

 

In this study, we use the WRF model to model wind variability for a geographical area covering the FINO1 offshore meteorological met-mast and Alpha Ventus offshore wind park (in the Southern North Sea). We first examine the performance of WRF, with an appropriate configuration, in forecasting few LLJ events. We then apply a LiDAR-based data assimilation (for sometimes during 2015) and study how different DA techniques (namely observational nudging and 3DVAR) can improve the accuracy of wind forecasting and reduce the model uncertainity during the LLJ events.

How to cite: Bakhoday-Paskyabi, M., Bui, H., and Mohammadpour Penchah, M.: LiDAR-based data assimilation during offshore transient events, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16972, https://doi.org/10.5194/egusphere-egu23-16972, 2023.

EGU23-16973 | Posters on site | AS1.1

Development of a New Microphysics Scheme with In-Cloud Processes for Weather Forecasting 

Songyou Hong, Haiqin Li, JIan-Wen Bao, and Jimy Dudhia

A new double-moment parameterization with in-cloud microphysical processes is developed for use in weather forecasting and climate studies. A main ingredient of the scheme utilizes a concept to represent the partial cloudiness effect on the microphysical processes, following the study of Kim and Hong (2018). The underlying assumption is that all the microphysical processes occur in a cloudy part of the grid box. Based on the long-term evaluation of the WRF Single-Moment (WSM) and WRF Double-Moment (WDM) schemes by WRF community, several revisions are made in microphysics terms, along with a newly introduced aerosol effect in ice processes. An aerosol-aware feature with prognostic aerosol emissions of sea salt, dust, anthropogenic and wildfire organic carbon for CCN is also designed. A mass-conserving Semi-Lagrangian sedimentation is re-configured for double-moment physics, which is superior to the conventional Eulerian algorithm in the context of the computational accuracy and numerical accuracy. The new scheme reproduces the storm structure in an idealized 2D testbed, accompanying better organized front-to-rear jets, cold pools, and convective updrafts, as compared to the results in the case of conventional microphysics. The wall-clock time is about a half in the US NOAA/GFS model, as compared to that of Thompson scheme.

How to cite: Hong, S., Li, H., Bao, J.-W., and Dudhia, J.: Development of a New Microphysics Scheme with In-Cloud Processes for Weather Forecasting, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16973, https://doi.org/10.5194/egusphere-egu23-16973, 2023.

EGU23-17383 | Orals | AS1.1

Automatic generation of a text forecast along a track 

Einar H. Guðmundsson, Ólafur Rögnvaldsson, and Karolina Stanislawska
Belgingur Ltd. has created a novel weather forecasting framework, called Weather On Demand – WOD, that can be deployed in the cloud and customised for any location world-wide at a very short notice.
 
A recent addition to the WOD system is a routing forecast option that generates a simple text forecast along a track provided by the end-user.
 
The process is such that a user provides a list of coordinates, where each coordinate pair is accompanied by a timestamp, via an API.

Points of interest are identified along the track. Most commonly these points are the locations of weather stations, as they are generally placed where weather conditions are of interest and the WOD system has additional machine learning interpolation mechanisms in development for weather stations. From this set, along with on-the-hour locations, a representative, refined, lower resolution track is assembled, for which high-resolution forecast data is pulled.

From that forecast data, the information most relevant to the user is highlighted. Any difficult conditions, as well as a segmented summary is generated in simple, succinct text, programmable in any language.

An ongoing extension of this feature is to develop a module that can create a simple text forecast for any user defined region.

The WOD software is maintained in Git and can be installed on suitable hardware in a matter of hours, bringing the full flexibility and power of the WRF modelling system at your fingertips.

How to cite: Guðmundsson, E. H., Rögnvaldsson, Ó., and Stanislawska, K.: Automatic generation of a text forecast along a track, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17383, https://doi.org/10.5194/egusphere-egu23-17383, 2023.

EGU23-17484 | Posters on site | AS1.1

Evaluating the Performance of WRF-Solar Model for 72-Hour Ahead Global Horizontal Irradiance Forecasting in West Africa: A Case Study of Ghana 

Windmanagda Sawadogo, Benjamin Fersch, Jan Bliefernicht, Stefanie Meilinger, and Harald Kunstmann

Accurate forecasting of solar irradiance is crucial for the integration of solar energy into the
power grid, power system planning, and the operation of solar power plants. The Weather
Research and Forecasting (WRF) model, with its solar radiation (WRF-Solar) extension, has
been used to forecast solar irradiance in various regions worldwide. However, the application
of the WRF-Solar model for global horizontal irradiance (GHI) forecasting in West Africa,
specifically in Ghana, has not been studied. This study aims to evaluate the performance of
the WRF-Solar model for GHI forecasting in Ghana, focusing on 3 health centers (Kologo,
Kumasi and Akwatia) for the year 2021. We applied a two one-way nested domain (D1=15
km and D2=3 km) to investigate the ability of the WRF solar model to forecast GHI up to 72
hours in advance under different atmospheric conditions. The initial and lateral boundary
conditions were taken from the ECMWF operational forecasts. In addition, the optical aerosol
depth (AOD) data at 550 nm from the Copernicus Atmosphere Monitoring Service (CAMS)
were considered. The study uses statistical metrics such as mean bias error (MBE), root mean
square error (RMSE), to evaluate the performance of the WRF-Solar model with the
observational data obtained from automatic weather stations in the three health centers in
Ghana. The results of this study will contribute to the understanding of the capabilities and
limitations of the WRF-Solar model for forecasting GHI in West Africa, particularly in
Ghana, and provide valuable information for stakeholders involved in solar energy generation
and grid integration towards optimized management of in the region.
Keywords: WRF-Solar; Global horizontal irradiance; Forecasting; West Africa; Ghana

How to cite: Sawadogo, W., Fersch, B., Bliefernicht, J., Meilinger, S., and Kunstmann, H.: Evaluating the Performance of WRF-Solar Model for 72-Hour Ahead Global Horizontal Irradiance Forecasting in West Africa: A Case Study of Ghana, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17484, https://doi.org/10.5194/egusphere-egu23-17484, 2023.

EGU23-17562 | Orals | AS1.1

Cut-cell Eta ensemble skill vs. ECMWF: Lessons learned 

Fedor Mesinger, Katarina Veljovic, Sin Chan Chou, Jorge L. Gomes, André A. Lyra, and Dušan Jovic

An experiment reported in Mesinger and Veljovic (JMSJ 2020) showed an
advantage of the Eta over its driver ECMWF ensemble members in placing 250 hPa jet
stream winds during a period of an upper tropospheric trough crossing the Rockies. A
byproduct of that experiment was that of the Eta ensemble switched to use sigma,
Eta/sigma, also achieving 250 hPa wind speed scores better than their driver members,
although to a lesser extent. Nevertheless, it follows that the Eta must include feature or
features additional to the eta coordinate responsible for this advantage over the
ECMWF.
An experiment we have done strongly suggests that the van Leer type vertical
advection of the Eta, implemented in 2007, is a significant contributor to this advantage.
In this experiment, having replaced a centered finite-difference Lorenz-Arakawa scheme
this finite-volume scheme enabled a successful simulation of an intense downslope
windstorm in the lee of the Andes.
While apparently a widespread opinion is that it is a disadvantage of terrain
intersecting coordinates that “vertical resolution in the boundary layer becomes reduced
at mountain tops as model grids are typically vertically stretched at higher altitudes,” a
very comprehensive 2006 NCEP parallel test gave just the opposite result. With
seemingly equal ABL schemes, the Eta showed a higher surface layer accuracy over
high topography than the NMM, using a hybrid terrain-following system (Mesinger, BLM
2022).
Hundreds of thousands of the Eta forecasts and experiments performed
demonstrate that the relaxation lateral boundary conditions almost universally used in
regional climate modeling (RCM)–in addition to conflicting with the properties of the
basic equations used–are unnecessary. Similarly, frequently applied in RCMs so-called
large scale or spectral nudging, being based on an ill-founded belief, should only be
detrimental if possible numerical issues of the limited area model used are addressed.
Note that this is confirmed by the results we refer to above.

How to cite: Mesinger, F., Veljovic, K., Chou, S. C., Gomes, J. L., Lyra, A. A., and Jovic, D.: Cut-cell Eta ensemble skill vs. ECMWF: Lessons learned, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17562, https://doi.org/10.5194/egusphere-egu23-17562, 2023.

EGU23-1129 | ECS | Posters virtual | AS1.2

High-resolution hail detection: probability of occurrence and size of hailstones based on weather radar data 

Krystian Specht, Jan Szturc, and Anna Jurczyk

The HAIL application was developed and implemented in the Institute of Meteorology and Water Management – National Research Institute (IMGW) as a component of the MeteoWarn system of detection and forecasting of dangerous weather phenomena. The application contains two algorithms: (i) hail detection and probability estimation; (ii) estimation of the maximum hail size that occurs in the event.

The probability of hail is determined using own hail detection algorithm based on fuzzy logic using the following weather radar products: the differential reflectivity (ZDR) and the exceedance of 0°C isotherm for echo top 40, 45, 50 dBZ (EHT40, EHT45, EHT50). Threshold have been introduced for the parameters to prevent false hail detection, above which hail is possible to occur. Additionally some other radar parameters: maximum reflectivity (CMAX), vertically integrated liquid water (VIL), constant altitude plan position indicator (CAPPI) on 4 km, and EHT are checked. The maximum hail size is calculated from the parameters: VIL, EHT50, and isotherm 0°C.

The developed algorithms were verified by observations in meteorological stations staffed by trained observers. The stations are limited to specific locations, but they are the most reliable and precise source of data about weather phenomena. Verification data for calibration are observations from synoptic stations and for hail size additionally observations from the European Severe Weather Database (ESWD). The results of the verification show good enough reliabilities of the two HAIL products. Validation based on the contingency table provided the following results: the probability of detection (POD) is 0.99, the false alarm ratio (FAR) is 0.02, and the critical success index (CSI) is 0.98. POD of no hail is 0.39, FAR is 0.38, and CSI is 0.31.

How to cite: Specht, K., Szturc, J., and Jurczyk, A.: High-resolution hail detection: probability of occurrence and size of hailstones based on weather radar data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1129, https://doi.org/10.5194/egusphere-egu23-1129, 2023.

EGU23-1345 | ECS | Orals | AS1.2

A Deep Learning-Based Bias Correction Method for Predicting Ocean Surface Waves in the Northwest Pacific Ocean 

Danyi Sun, Wenyu Huang, Yong Luo, Jingjia Luo, Jonathon S. Wright, Haohuan Fu, and Bin Wang

Ocean waves, especially extreme waves, are vital for air-sea interaction and shipping. However, current wave models still have significant biases, especially under extreme wind conditions. Based on a numerical wave model and a deep learning model, we accurately predict the significant wave height (SWH) of the Northwest Pacific Ocean. For each day in 2017-2021, we conducted a 3-day hindcast experiment using WAVEWATCH3 (WW3) to obtain the SWH forecasts at lead times of 24, 48, and 72hr, forced by GFS real-time forecast surface winds. The deep learning-based bias correction method is BU-Net by adding batch normalization layers to a U-Net, which could improve the accuracy. Due to the use of BU-Net, the mean Root Mean Squared Errors (RMSEs) of the SWH forecast from WW3 at lead times of 24, 48, and 72hr are reduced from 0.35m to 0.21m, 0.39m to 0.24m, and 0.43m to 0.30m, corresponding to drop percentages of 40%, 38%, and 30%, respectively. During typhoon passages, the drop percentages of RMSEs reach 45%, 42%, and 35% for three lead times. Therefore, combining numerical models and deep learning algorithms is very promising in ocean wave forecasting.

How to cite: Sun, D., Huang, W., Luo, Y., Luo, J., Wright, J. S., Fu, H., and Wang, B.: A Deep Learning-Based Bias Correction Method for Predicting Ocean Surface Waves in the Northwest Pacific Ocean, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1345, https://doi.org/10.5194/egusphere-egu23-1345, 2023.

EGU23-1777 | Orals | AS1.2

Improving the ensemble forecast of precipitation in Europe by combining a stochastic weather generator with dynamical models  

Meriem Krouma, Lauriane Batté, Linus Magnusson, Damien Specq, Constantin Ardilouze, and Pascal Yiou

Ensemble forecasts of precipitation with sub-seasonal lead times offer  useful information for decision makers when they sufficiently sample the possible outcomes of trajectories. In this study, we aim to improve  precipitation ensemble forecast systems using a stochastic weather generator (SWG) based on analogs of the atmospheric circulation. This approach is tested for sub-seasonal lead times (from 2 to 4 weeks). The SWG ensemble forecasts  yield promising probabilistic skill scores for lead times of 5-10 days for precipitation (Krouma et al, 2022) and for lead times of 40 days for temperature   (Yiou and Déandréis, 2019) . In this work, we adapt the parameters of the SWG to optimize the simulation of European precipitations from ensemble dynamical reforecasts of ECMWF and CNRM. We present the HC-SWG forecasting tool (HC refers to Hindcast and SWG to the stochastic weather generator) based on a combination of dynamical and stochastic models.

We start by computing analogs of Z500 from the ensemble member reforecast of ECMWF (11 members) and CNRM (10 members). Then, we generate an ensemble of 100 members for precipitation over Europe. We evaluate the ensemble forecast of the HC-SWG using skill scores such as the continuous probabilistic score CRPS and ROC curve.

We obtain reasonable forecast skill scores for lead times up to 35 days for different locations in Europe (Madrid, Toulouse, Orly, De Bilt and Berlin). We compare the HC-SWG forecast with other precipitation forecasts to further confirm the benefit of our method. We found that the HC-SWG shows improvement against the ECMWF precipitation forecast until 25 days.

 

How to cite: Krouma, M., Batté, L., Magnusson, L., Specq, D., Ardilouze, C., and Yiou, P.: Improving the ensemble forecast of precipitation in Europe by combining a stochastic weather generator with dynamical models , EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1777, https://doi.org/10.5194/egusphere-egu23-1777, 2023.

EGU23-4735 | Orals | AS1.2

GAN-based forecasting model via self-adaptive clustering approach 

Sojung An, Tae-Jin Oh, Inchae Na, Jiyeon Jang, Wooyeon Park, and Junghan Kim

Deep learning has been rapidly adopted in short-term precipitation prediction, such as simulating precipitation movement and predicting extreme weather events. Recently, generative adversarial neural networks (GANs) have been shown to be effective at dealing with field smoothing with increasing lead time. Several studies (Jing et al., 2019; Ravuri et al., 2021) demonstrated the potential of GAN by solving spatial smoothing problems and demonstrating reliable predictive performance. However, despite promising results from GANs, unbalanced datasets and human annotations can limit the predictive ability of deep learning and induce biased results. In addition, precipitation is a complex process that depends on various factors. Thus, approximating the model into a single latent space is a challenge, and furthermore, there is a risk of mode collapse. This study introduces an algorithm for predicting precipitation by clustering precipitation types using self-supervised learning (SSL) and estimating rainfall distribution according to precipitation types. First, we derive precipitation-type labels by self-clustering a generator that is a multi-layer ConvGRU. And then, we predict six-hour precipitation based on the gaussian distribution of each type. SSL improves the performance of precipitation forecasting based on type-specific representation learning through adaptive sampling in latent space. The proposed methodology was verified using hybrid surface rainfall (HSR) dataset at a spatial resolution of 500m with a resolution of 2,305 (longitude) × 2,881 (latitude) and a temporal resolution of 5 min. The images consist of 256×256 pixels from scaling down to a resolution of 4 km and are extracted at 30-minute intervals. Experimental results show that our method outperforms a state-of-the-art method on a six-hour prediction basis with a mean squared error and critical success index on unseen datasets. Also, the proposed algorithm can predict various precipitation types without spatial smoothing.

How to cite: An, S., Oh, T.-J., Na, I., Jang, J., Park, W., and Kim, J.: GAN-based forecasting model via self-adaptive clustering approach, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4735, https://doi.org/10.5194/egusphere-egu23-4735, 2023.

EGU23-5837 | Orals | AS1.2

Generating weather symbol data in IMPROVER 

Stephen Moseley, Ben Ayliffe, and Gavin Evans

The UK Met Office is developing an open-source probability-based post-processing system called IMPROVER (Integrated Model Post-Processing and Verification) to fully exploit our convection permitting, hourly cycling ensemble forecasts.  Post-processed MOGREPS-UK model forecasts are blended with deterministic UKV model forecasts and data from the coarser resolution global ensemble, MOGREPS-G, to produce seamless probabilistic forecasts from now out to 7 days ahead. For precipitation, an extrapolation nowcast is also blended in at the start.

A majority of the post-processing within IMPROVER is performed on gridded forecasts, with site-specific forecasts extracted as a final step, helping to ensure consistency. IMPROVER delivers a wide range of probabilistic products to both operational meteorologists and as input to automated forecast production. The system achieved operational acceptance in spring 2022 and will be used in operational products from spring 2023.

Weather symbols provide the general public with a simple, pictorial view of the weather for a time of interest and include sun and cloud conditions, mist and fog, hail and lightning, and three phases of precipitation, both as showers or continuous, and light or heavy. This talk describes how a deterministic most-likely weather type code is generated using a decision tree approach from probabilistic multi model IMPROVER data for 1 hour, 3 hour and daytime periods that are consistent with each other. Recent work to make these weather codes representative of a time-window, rather than an instant, will be discussed. We will present some verification, comparing IMPROVER weather symbols and the current operational Met Office symbols with SYNOP present weather reports.

How to cite: Moseley, S., Ayliffe, B., and Evans, G.: Generating weather symbol data in IMPROVER, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5837, https://doi.org/10.5194/egusphere-egu23-5837, 2023.

EGU23-7214 | Posters on site | AS1.2

Weather forecast downscaling for applications in smart agriculture 

Francesco Di Paola, Sabrina Gentile, Nicola Genzano, Elisabetta Ricciardelli, Filomena Romano, and Valerio Tramutoli

In the framework of the On Demand Services For Smart Agriculture (OD4SA) project, funded by PO FESR 2014-2020 from Regione Basilicata, Italy, a weather forecast service has been developed, for applications in smart agriculture and precision farming. It is based on the Weather Research and Forecasting (WRF) model and provides a daily 96-hour forecast of temperature and water vapor at 2 m altitude, wind speed and direction at 10 m altitude, atmospheric pressure, solar irradiance, and 1-hour accumulated rainfall, for the Southern Italy. Although encouraging advances in microscale modeling have been achieved in the last decade, the computational costs imposed by the state of the art do not allow for continuous operational forecasting at the sub-kilometer scale, useful for precision farming, especially in southern Italy that is characterized by a complex orography. To overcome this limit, an algorithm based on some Artificial Neural Networks (ANNs) has been developed, by using the WRF Large Eddy Simulation (LES) to build the training database at 240 m spatial resolution. Particular attention was paid to the analysis of the true spatial resolution of the WRF-LES outputs, to the definition of the ANNs topology and to the input selection, from over 250 inputs more than half has been discarded. The preliminary results show RMSE equal on average to 70% of those obtained by using the most common spatial interpolation methods.

How to cite: Di Paola, F., Gentile, S., Genzano, N., Ricciardelli, E., Romano, F., and Tramutoli, V.: Weather forecast downscaling for applications in smart agriculture, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7214, https://doi.org/10.5194/egusphere-egu23-7214, 2023.

EGU23-8628 | Posters on site | AS1.2

Discussion about bulk shear thresholds for severe weather environment that cause power outages and blow down towers of transmission and distribution lines in Southern Brazil 

Leonardo Calvetti, Luis Gabriel Cassol Machado, Cesar Beneti, Kerollyn Andrzejewski, Fabricio Pereira Harter, Marcelo Felix Alonso, and Sheila Radman Paz

Brazil has a country-wide interconnected grid of over 169,000 km of high voltage transmission lines. By 2026, an additional 20,000 km will expand the grid significantly. The main type of electrical energy transmission in Brazil is aerial for all sources of generation, including hydroelectric, wind and solar power plants, resulting in a network between the tropics to the subtropical regions up to -33 degrees latitude. In Southern Brazil there are 12.994.382 consumer units in the States, Rio Grande do Sul, Santa Catarina and Paraná.  One of the main causes of structural failures is associated with severe storms that produce loads that exceed the structural loading design criteria. In this work it has been investigating hindcast predictions with GFS and WRF for a high speed wind gust event that blew down towers in Southern Brazil during severe weather conditions between 2016 and 2022. It has analyzed eight high-impact events where towers or lines have failed or been shut down looking for convection parameters that indicate severe weather specifically for these impacts. In order to simulate a 48h forecast it was used the current operational GFS/GFDL V3 global model from NCEP/NOAA and 3-km resolution WRF runs. In seven of eight events the models were capable of simulating an environment conditions which meteorologists could elaborate an alert of high-impact severer weather for transmission lines and  could help the electric company's teams to execute a contingency plan.  Both GFS and WRF have indicated severe environments, but WRF has indicated better detailed areas of deep convection. In a sense of search thresholds that could be used in the future, some values of shear were found: 0-6km Shear 70-84 kt, 0-1 km Shear up to 40 kt, 0-3 km Shear up to 61 kt. The authors have not found specific thresholds for other variables such as the Convective available potential energy (CAPE) convective inhibition. The impact of the forecasts was analyzed according to the possible activities to be carried out by technicians in the prevention and repair of electrical systems and reduce the impact in outages.

How to cite: Calvetti, L., Cassol Machado, L. G., Beneti, C., Andrzejewski, K., Pereira Harter, F., Felix Alonso, M., and Radman Paz, S.: Discussion about bulk shear thresholds for severe weather environment that cause power outages and blow down towers of transmission and distribution lines in Southern Brazil, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8628, https://doi.org/10.5194/egusphere-egu23-8628, 2023.

EGU23-9531 | Orals | AS1.2

Latent diffusion models for generative nowcasting and uncertainty quantification of precipitation fields 

Jussi Leinonen, Ulrich Hamann, and Urs Germann

Deep generative modeling is able to generate highly realistic atmospheric fields, one prominent example being precipitation. So far, almost all studies have used generative adversarial networks (GANs) for this purpose, but recent progress in machine learning research has had a new class of methods called diffusion models replace GANs in many applications. Diffusion models have been often shown to be able to generate a wider variety of samples than GANs, suggesting that they might be able to better capture uncertainty in applications such as weather and climate where quantifying it is important.

In this presentation, we describe our research on using diffusion models for short-term prediction (nowcasting) of precipitation fields. We adapt the latent diffusion model used by Stable Diffusion (Rombach et al. 2022) to the this problem, predicting precipitation up to 3 hours ahead to the future at 5-min temporal resolution and 1-km horizontal resolution. Predictions can be produced as an ensemble where each member represent a possible future evolution of the precipitation field.

We show that our model:

  • generates highly realistic precipitation fields that are consistent with the past precipitation used as input.
  • outperforms the state-of-the-art GAN-based Deep Generative Models of Rainfall (DGMR) model by most relevant metrics.
  • performs particularly well at representing the uncertainty of its own predictions, as shown by uncertainty quantification methods developed for ensemble forecast verification.

Therefore, it appears that diffusion models are indeed suitable for generative modeling of precipitation fields with highly realistic representation of uncertainty. Our model architecture also permits multiple inputs data sources to be combined, in particular allowing seamless generative predictions to be made by exploiting observations and numerical weather predictions.

How to cite: Leinonen, J., Hamann, U., and Germann, U.: Latent diffusion models for generative nowcasting and uncertainty quantification of precipitation fields, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9531, https://doi.org/10.5194/egusphere-egu23-9531, 2023.

EGU23-9985 | Posters virtual | AS1.2

Predicting precipitation growth and decay with weather radar rainfall measurements 

Chen Li, Miguel Rico-Ramirez, Qin Wang, Weiru Liu, and Dawei Han

Recently, weather radar has been increasingly used to estimate precipitation for a variety of hydrological and meteorological applications, including real-time flood forecasting, severe weather monitoring and warning, and short-term precipitation forecasting. In very short range (0–6 h), many critical decisions are taken to ensure people’s safety. For example, the damage of a localized hazard of flood is high so that the warning of these severe weather is important. Forecasting precipitation in this time range the commonly relies on extrapolation-based nowcasting tools that exploit the persistence of the most recent weather radar observations. To obtain the best possible prediction skill in the 0–6-h range, one cannot solely rely on numerical weather prediction (NWP) but must also use the available observations in a more direct way. Weather radars are instruments capable to provide rainfall measurements with suitable spatial and temporal resolutions. The potential benefit of using radar rainfall in hydrology is huge, but practical hydrological applications of radar have been limited by the inherent uncertainties and errors in radar rainfall estimates. As radar nowcasts are essentially based on extrapolation from a series of consecutive radar scans, they are characterized by a high skill at the start of the forecast, but this decreases with lead time very rapidly, as extrapolation techniques generally do not account for growth and decay processes in the atmosphere (Golding 1998).

Machine learning algorithms can be trained with weather radar data to identify regions of precipitation growth and decay based on historical observations. Artificial neural networks (ANN) can be employed to learn the complex nonlinear dependence relating the growth and decay to the predictors, which are geographical location, motion vectors, temperature, precipitation and time (Foresti et al.2019). The precipitation motion field can be calculated by using the optical flow driven by weather radar data. Around 15-year of weather radar precipitation observations from Great Britain (GB) are used to derive precipitation growth and decay mainly due to orography. This paper will present the preliminary findings of predicting precipitation growth and decay in different regions in the UK.

 

How to cite: Li, C., Rico-Ramirez, M., Wang, Q., Liu, W., and Han, D.: Predicting precipitation growth and decay with weather radar rainfall measurements, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9985, https://doi.org/10.5194/egusphere-egu23-9985, 2023.

Although tropical cyclone (TC) forecasts can fairly well capture the TC track and primary rainfall distribution, limited skills are found in forecasting TC structural changes and asymmetric gusty winds. The barrier to further understanding TC structural change is due mainly to the lack of observation, and it is difficult to have systematic 2-D wind analyses. Here, we developed a deep learning model — Deep Learning 2-D Structure Analysis Model for Tropical Cyclones (DSAT-2D) — to produce TC wind analysis in high-temporal-spatial resolutions based on generative adversarial networks (GAN). We use IR1 satellite observation and ERA5 reanalysis data as the model input for the DSAT-2D. The ASCAT surface wind data were collected and used as the label data. Note, however, that the ASACT analysis tends to underestimate winds greater than 15 m/s. Thus, we proposed several methods to fix this issue before training the model. Furthermore, other innovative designs in the DSAT-2D model include: (i) we regrid all data in a polar coordinate to better handle the TC tangential and radial features, and (ii) we also set the target of the DSAT-2D model as the TC radial wind and tangential wind.

Experiment results demonstrate that the DSAT-2D model can capture the TC asymmetric wind structure while possessing the capability of increasing the maximum estimation frequency from approximately 12 hours (e.g., ASCAT data) to less than one hour. The DSAT-2D model may help understand the TC asymmetric wind evolution and improve TC forecasts. Future applications of assimilating this value-added information into the numerical weather prediction model will also be discussed.

How to cite: Cheng, Y.-Y. and Chen, B.-F.: An End-to-end Deep Learning Approach for Analyzing Tropical Cyclone 2-D Surface Winds Utilizing Satellite Data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10632, https://doi.org/10.5194/egusphere-egu23-10632, 2023.

EGU23-10645 | ECS | Orals | AS1.2

An Advanced Deep Learning Rainfall Forecasts Downscaling Method in Taiwan 

Rong-Cih Chang, Yung-Yun Cheng, and Buo-Fu Chen

Taiwan is a 35,808-km2 island with more than 100 peaks over 3,000 meters. The complex terrain in Taiwan makes forecasters more challenging to forecast rainfall in mesoscale and storm-scale. Besides, the spatial distribution of rainfall stations is quite uneven as well. Moreover, the forecast performance of both the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Global Forecast System (GFS) is limited by Taiwan's complex terrain, having certain systematic deviations in rainfall forecasts. For example, the ECMWF forecast has underestimated heavy rainfall and over-predicted light rain in Taiwan. Consequently, to correct model deviations and provide better rainfall forecast products, advanced statistical or artificial intelligence (AI) methods should be studied.

This research applies the U-net neural network to generate downscaling rainfall prediction. We collected precipitation forecast data from the ECMWF (9 km resolution) and the GFS (22 km resolution) during 2021 as the model input. The Quantitative Precipitation Estimation and Segregation Using Multiple Sensor (QPESUMS) radar data from CWB is used as the label data. QPESUMS data can effectively help describe the complete spatial distribution of rainfall. The testing data is from the 2022 whole year. An innovative design of the proposed model is a geographical attention layer (GAL) in the U-net. The GAL helps to learn the geospatial characteristics from the QPESUMS rainfall observation. Moreover, this study uses a scale-separated loss function for model optimization, for which the rainfall is divided into large-scale smoothing and small-scale disturbance fields.

Results show that this U-net downscaling model successfully learns the feature and corrects the systematic bias in both global models, such as shifts in the rainfall caused by topographical lift and local circulation. Furthermore, based on the overall statistics of 2021, the performance diagram shows that the AI model corrects the over-prediction of light rain, while the critical success index in heavy rain is improved by 25 to 30%. The ongoing work of this research will apply generative adversarial networks to break the limitation of learning wrong features from the original forecast input data.

How to cite: Chang, R.-C., Cheng, Y.-Y., and Chen, B.-F.: An Advanced Deep Learning Rainfall Forecasts Downscaling Method in Taiwan, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10645, https://doi.org/10.5194/egusphere-egu23-10645, 2023.

Daily to monthly variations of precipitation directly affect the propagation of an emerging drought. To cope with adverse impacts, a skillful sub-seasonal forecast of precipitation is essential to track the evolution of the emerging drought and provide actionable information for stakeholder and water resources managers. This study evaluates the predictive performances of the Subseasonal Experiment (SubX) models (ECCC-GEPS6, EMC-GEFSv12, ESRL-FIMr1p1, GMAO-GEOS_V2p1, and RSMAS-CCSM4) for the precipitation variations during two recent long-term drought events (2007−2010 and 2013−2016) over the Korean Peninsula. Sub-seasonal prediction skill of SubX models are quantitatively evaluated via multiple verification metrics for ensemble, deterministic, and categorical forecasts. Results show that during the emergence of multi-year droughts, the intensification and persistence of drought severity are generally better predicted by SubX models than the weakening and recovery of the drought severity in all forecast times (1−4 weeks). The multi-model ensemble approach shows the best prediction skill, and EMC-GEFSv12 which has the most ensemble member presents the better predictive performance than other models. In addition, results from the sensitivity test to ensemble member size show that multiple ensemble member can enhance the prediction skills significantly up to eight ensemble members. Overall results suggest that the forecast of SubX on multi-year Korean Peninsula droughts can provide actionable information that helps manage water resources in a timely manner.

How to cite: Park, C.-K. and Kam, J.: Evaluation of the sub-seasonal forecasting skill of SubX models for precipitation during recent multi-year droughts over the Korean Peninsula, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10752, https://doi.org/10.5194/egusphere-egu23-10752, 2023.

EGU23-10909 | Posters on site | AS1.2

Prediction skill of Asian Dust Generation in hindcast data of Asian Dust Seasonal Forecasting Model (GloSea5-ADAM) 

Misun Kang, Woojeong Lee, Pil-Hun Chang, Mi-Gyeong Kim, and Kyung-On Boo

This study investigated the prediction skill of the Asian dust seasonal forecasting model (GloSea5-ADAM) on the Asian dust and meteorological variables related to the dust generation using hindcasts of GloSea5-ADAM for the period of 1991~2016 for East Asia. GloSea5-ADAM incorporates the dust generation algorithm of the Asian Dust and Aerosol Model (ADAM) into the Global Seasonal Forecasting System version 5 (GloSea5). The Asian dust and meteorological variables (10 m wind speed, 1.5 m relative humidity, and 1.5 m air temperature) depending on the combination of the initial dates in the sub-seasonal scale were compared to that from synoptic observation and ERA5 reanalysis data. The evaluation criteria used Mean Bias Error (MBE), Root Mean Square Error (RMSE), and Anomaly Correlation Coefficient (ACC). The Asian dust and meteorological variables in the source region (35~44°N, 90~115°E) showed high ACC in the prediction scale within one month. The best performances for all variables showed when the use of the initial dates closest to the prediction month based on MBE, RMSE, and ACC. ACC was as high as 0.4 in Spring when using the closest two initial dates. In particular, the GloSea5-ADAM shows the best performance of Asian dust generation with an ACC of 0.60 in the occurrence frequency of Asian dust in March when using the closest initial dates for initial conditions. This result showed that the performances could be improved by adjusting the number of ensembles considering the combination of the initial date.

 

How to cite: Kang, M., Lee, W., Chang, P.-H., Kim, M.-G., and Boo, K.-O.: Prediction skill of Asian Dust Generation in hindcast data of Asian Dust Seasonal Forecasting Model (GloSea5-ADAM), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10909, https://doi.org/10.5194/egusphere-egu23-10909, 2023.

EGU23-11043 | ECS | Orals | AS1.2

Precipitation Nowcasting Based on an Optimized Deep Learning Model Trained with Heterogeneous Weather Data 

Dian-You Chen, Chia-Tung Chang, and Buo-Fu Chen

    Due to the threat of extreme rainfall associated with mesoscale convective systems and summer afternoon thunderstorms, very short-term quantitative precipitation forecasting during 0−3 h is critical in Taiwan. In this study, deep learning models are developed for high-resolution quantitative precipitation nowcasting in Taiwan up to 3 h ahead. The baseline model based on the convolutional recurrent neural network is trained with a dataset containing radar reflectivity and rain rates at a granularity of 10 min. As previous works tend to produce overprediction in low-rainfall regions, the currently proposed model is improved and further driven by highly related heterogeneous weather data, including visible channel satellite observation, environmental winds, and environmental thermo-dynamical profiles. Note that an innovative “PONI module” is added to the deep learning model to integrate a variety of heterogeneous data with various spatial and temporal characteristics. Moreover, model performance is evaluated from statistical and spatial rescaling perspectives represented by R =  Ravg + R', where R denotes original rainfall, Ravg and R' are spatial moving averages and the values deviated from Ravg, respectively. Statistical verification shows that the Ravg of the new model outperforms the previous model, while the performance of R' is comparable. The new model integrated with heterogeneous data selected upon domain knowledge can restrain the nowcasts that overestimate in low-rainfall regions. Last but not least, quasi-operational verifications against other state-of-the-art techniques in Taiwan Central Weather Bureau are presented as follows: (1) the CSI of the first-hour prediction from the deep learning model is comparable with QPESUMS-QPF and better than RWRF and iTeen. (2) 3h ahead prediction CSI of RWRF and iTeen are inferior to the performance of deep learning model owing to their misprediction of rainfall regions. The deep learning model can accurately predict medium and extreme amounts of precipitation at a fraction of the computational cost.

How to cite: Chen, D.-Y., Chang, C.-T., and Chen, B.-F.: Precipitation Nowcasting Based on an Optimized Deep Learning Model Trained with Heterogeneous Weather Data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11043, https://doi.org/10.5194/egusphere-egu23-11043, 2023.

So far, plenty of efforts have been pursued on the numerical weather prediction (NWP). However, systematic errors could never be ignored in the output applications. To supply the numerical forecasts with higher accuracies, statistical postprocessing is often expected to correct systemic biases and has been one of the key components of the forecasting suites. Based on the NWP models and taking advantages of the raw stepwise pattern projection method (SPPM), the neighborhood pattern projection method (NPPM) is newly proposed to postprocess the model outputs and to improve forecast skills of daily maximum and minimum temperatures (Tmax and Tmin) over East Asia for short-term timescales, as well as the Kalman filter based pattern projection method (KFPPM) for longer-term forecasts. For the short-term lead times of 1–7 days, the SPPM is slightly inferior to the benchmark of decaying averaging method, while its insufficiency decreases with increasing lead times. The NPPM shows manifest superiority for all lead times, with the mean absolute errors of Tmax and Tmin decreased by ~0.7° and ~0.9°C, respectively. Advantages of the SPPM and NPPM are both mainly concentrated on the high-altitude areas such as the Tibetan Plateau, where the raw model outputs show the most conspicuous biases. As for longer-term forecasts at the subseasonal timescale, the NPPM effectively calibrates the temperature forecasts at the early stage. However, with the growing lead times, it shows speedily decreasing skills and can no longer produce positive adjustments over the areas outside the plateaus. By contrast, the KFPPM consistently outperforms the other calibrations and reduces the forecast errors by almost 1.0°C and 0.5°C for Tmax and Tmin, respectively, both retaining superiorities to the random climatology benchmark till the lead time of 24 days. The optimization of KFPPM maintains throughout the whole range of the subseasonal timescale, showing most conspicuous improvements distributed over the Tibetan Plateau and its surroundings. Case experiments further demonstrate the above-mentioned features and imply the potential capability of the NPPM and KFPPM in improving forecast skills and disaster preventions for extreme temperature events. Besides, compared with the initial SPPM, they not only produces more powerful forecast calibrations, but also provides more pragmatic calculations and greater potential economic benefits in practical applications.

How to cite: Zhu, S., Lyu, Y., and Zhi, X.: Calibrations of Surface Air Temperature Forecasts at Short- and Long-term Timescales Based on Statistical Pattern Projection Methods, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11970, https://doi.org/10.5194/egusphere-egu23-11970, 2023.

EGU23-12127 | ECS | Orals | AS1.2

Exploiting radar polarimetry for nowcasting of convective hazards using deep learning 

Nathalie Rombeek, Jussi Leinonen, and Ulrich Hamann

Severe convective weather events, such as hail, lightning and heavy rainfall pose a great threat to humans and cause a considerable amount of economic damage. Nowcasting convective storms can provide precise and timely warnings and, thus, mitigate the impact of these storms. Dual-polarization weather radars are a crucial source of information for nowcasting severe convective events. These radars provide important information about the microphysics of the convective systems, on top of the rainfall rate and vertical structure of the reflectivity. Nevertheless, polarimetric variables, which can provide additional information about the size, shape and orientation of particles, are often not considered in nowcasting.

This work presents the importance of polarimetric variables as an additional data source for nowcasting thunderstorm hazards using machine learning, compared to using radar reflectivity alone. We add these data to the neural network architecture of Leinonen et al. 2022 (Seamless lightning nowcasting with recurrent-convolutional deep learning), which uses convolutional and recurrent layers and analyzes inputs from multiple data sources simultaneously. This network has a common framework, which enables nowcasting of hail, lightning and heavy rainfall for lead times up to 60 min with a 5 min resolution. The study area is covered by the Swiss operational radar network, which consists of five operational polarimetric C-band radars. In addition, we analyze the contribution of quality indices as an additional information source, which takes the uncertainty of the radar observations throughout the complex mountainous terrain and scanning strategy in Switzerland into account. Results indicate that including polarimetric variables and quality indices improves the accuracy of nowcasting convective storms.

How to cite: Rombeek, N., Leinonen, J., and Hamann, U.: Exploiting radar polarimetry for nowcasting of convective hazards using deep learning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12127, https://doi.org/10.5194/egusphere-egu23-12127, 2023.

EGU23-12517 | ECS | Posters on site | AS1.2

The combined impact of model uncertainty on flow-dependent spatial predictability of convective precipitation 

Takumi Matsunobu, Christian Keil, Matjaž Puh, Christoph Gebhardt, and Chiara Marsigli

Accurate precipitation forecasts at kilometre scales are still a key challenge for convective scale ensemble prediction systems. We assess the spatial forecast skill-spread relationship for summer convection in 2021 and address the impact of considering model uncertainties from two physics parametrisations -- microphysics and planetary boundary layer turbulence -- together with initial and lateral boundary conditions uncertainties. To investigate their flow dependence all analyses are done conditionally to strong and weak synoptic convective forcing cases.
It is found that the spatial skill-spread relationship is highly dependent on synoptic forcing and the current operational ensemble forecasts are spatially underdispersive especially during weak synoptic control, whereas a good agreement is found during strong synoptic control. Case studies during weak synoptic control demonstrate that perturbations in the planetary boundary layer contribute to improving forecast skill and increase spread at small scales while microphysical perturbations contribute to spread increase across all scales. Overall, the combination of both perturbations seems to combine their individual impacts and thus benefits the spatial skill-spread relationship at most times and scales.

How to cite: Matsunobu, T., Keil, C., Puh, M., Gebhardt, C., and Marsigli, C.: The combined impact of model uncertainty on flow-dependent spatial predictability of convective precipitation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12517, https://doi.org/10.5194/egusphere-egu23-12517, 2023.

EGU23-12665 | ECS | Posters on site | AS1.2

Development of Geostationary Satellite Atmospheric Motion Vectors Forecasting Algorithm by CNN Model 

Hwayon Choi, Yong-Sang Choi, and Gyuyeon Kim

Atmospheric motion vector (AMV) is an important factor that affects most meteorological phenomena in numerical weather prediction. Despite of its significance, the conventional algorithm of moisture tracking for AMV calculated with most of remote sensing data uses the cross-correlation coefficient (CCC) method, resulting in low-resolution (target-based) output and much of errors. In addition, forecasting AMVs is impossible in conventional method because it requires water vapor data 10 minutes from the current time to calculate current winds. For better moisture flow tracking, convolutional neural network (CNN) frames were used that track motion, which is called optical flow estimation in computer vision. The pixel-based high-resolution AMVs are calculated by using the water vapor channel images into the PWC-Net (CNNs for optical flow using pyramid, warping, and cost volume). For each pixel, linear regression is used to forecast AMVs. The performance of the AMVs calculated by CNN was validated by comparing those results and the Korean geostationary satellite GEO-KOMPSAT-2A (GK2A) AMVs with wind fields of ERA5 data at 100-1000 hPa. Experiments used infrared brightness temperature images of three water vapor channels at 6.2 µm, 7.0 µm, and 7.3 µm over Korean Peninsula for 2022. As to root-mean-square vector differences (RMSVDs), the tracking performance of this study was found to be more accurate than the GK2A AMVs ­— 1.3 to 21.93 m/s more accurate for the cloudy sky and 0.32 to 14.9 m/s more accurate for the clear sky above 400 hPa. The results using the CNN model showed better moisture tracking performance than the conventional method, especially for low altitudes. It also enables to obtain higher resolution AMVs with pixel-based tracking rather than conventional target-based tracking. Furthermore, the mean RMSVDs of forecasted AMVs are 1.97 m/s, 2.66 m/s, 3.32 m/s, and 5.28 m/s when the forecast lead time is 10 min, 20 min, 30 min, and 1 hr, respectively. Consequently, high-resolution AMV forecasts with accuracy, which could not be calculated by the conventional method, were obtained by CNN model, and can be used to advance the accuracy of weather forecasting.

 

KEYWORDS: Moisture Tracking; Optical Flow; Atmospheric Motion Vectors; Wind Forecasting; Remote Sensing

How to cite: Choi, H., Choi, Y.-S., and Kim, G.: Development of Geostationary Satellite Atmospheric Motion Vectors Forecasting Algorithm by CNN Model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12665, https://doi.org/10.5194/egusphere-egu23-12665, 2023.

EGU23-12924 | ECS | Orals | AS1.2

Short-term probabilistic forecast of cloudiness: a scale-dependent advection approach 

Alberto Carpentieri, Doris Folini, Daniele Nerini, Seppo Pulkkinen, Martin Wild, and Angela Meyer

Solar energy generation is highly volatile during the day due to the strong dependence on cloud dynamics, which limits its integration into the power grid (Smith et al., 2022). On the other hand, higher utilization of renewable energy is essential to tackle climate change. To increase the share of photovoltaic energy in the grid without jeopardizing grid stability, accurate forecasts are essential to ascertain the balance between energy demand and supply (David et al., 2021).

Photovoltaic energy production mainly depends on downwelling surface solar radiation (). SSR is accurately measured by pyranometers, but their spatial representativeness is limited to a few kilometers. By estimating the SSR from geostationary satellites, we can cover larger areas with high spatial and temporal resolutions, allowing us to track cloud motion.

Previous studies on probabilistic cloud motion focused on optical-flow methods without considering the temporal evolution of clouds as such. We address this issue by presenting a scale-dependent approach to forecast. Our approach is inspired by the works of Bowler et al., 2006 and Pulkkinen et al., 2019 on precipitation nowcasting. The novelty of our study is the utilization of different autoregressive models to forecast the temporal evolution of cloudiness of different spatial scales. Our work is motivated by the scale-dependent predictability of cloud growth and decay. By exploiting more than one autoregressive model, we can predict the noisy evolution of small scales independently of the more deterministic evolution of larger spatial scales.

Our preliminary results over Switzerland indicate that our model outperforms the probabilistic advection model based on Carriere et al., 2021 noise generation by reducing the continuously ranked probability score (CRPS) on the test set by 14%. Moreover, we demonstrate the advantage of cloudiness scale decomposition by comparing our model with the same approach without decomposition. We can reduce the CRPS by 6% and the RMSE by 5% by decomposing the images into multiple cascades

References

Bowler, N., C. Pierce, A. Seed, 2006, “STEPS: A probabilistic precipitation forecasting scheme which merges an extrapolation nowcast with downscaled NWP”, Quarterly Journal of the Royal Meteorological Society, 132, 620, pp. 2127–2155, doi:10.1256/qj.04.100.

Carriere, T., R. Amaro e Silva, F. Zhuang, Y. Saint-Drenan, P. Blanc, 2021, “A New Approach for Satellite-Based Probabilistic Solar Forecasting with Cloud Motion Vectors”, Energies, 14, doi:10.3390/en14164951.

David, M., M. Luis, P. Lauret, 2018, “Comparison of intraday probabilistic forecasting of solar irradiance using only endogenous data”, International Journal of Forecasting, 34, doi:10.1016/j.ijforecast.2018.02.003.

Pulkkinen, S., D. Nerini, A. Perez Hortal, C. Velasco-Forero, A. Seed, U. Germann, L. Foresti, 2019, “Systems: an open-source Python library for probabilistic precipitation nowcasting (v1.0)”, Geoscientific Model Development, 12, 10, pp. 4185–4219, doi:10.5194/gmd-12-4185-2019.

Smith, O., O. Cattell, E. Farcot, R. D. O’Dea, K. I. Hopcraft, 2022, “The effect of renewable energy incorporation on power grid stability and resilience”, Science Advances,  https://www.science.org/doi/abs/10.1126/sciadv.abj6734.

How to cite: Carpentieri, A., Folini, D., Nerini, D., Pulkkinen, S., Wild, M., and Meyer, A.: Short-term probabilistic forecast of cloudiness: a scale-dependent advection approach, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12924, https://doi.org/10.5194/egusphere-egu23-12924, 2023.

Quantitative precipitation nowcasting (QPN) is crucial for forecasting precipitation within the next several hours (generally up to 6) to prevent substantial socioeconomic damage. In general, ground radar data has been widely employed in QPN due to its high spatial-temporal resolution and more precise precipitation estimation than satellite. With the remarkable success of deep learning (DL), recent QPN studies have actively adopted DL using radar data. Although these studies yielded high skill scores in forecasting precipitation areas with a weak intensity (about 1 mm/h), they failed to effectively simulate the horizontal movement of precipitation areas and showed poor ability in forecasting precipitation with stronger intensities. In addition, despite the fact that the skill score is highly dependent on the characteristics of each precipitation event, there was a lack of evaluation over various precipitation cases. From the motivation that there can be room for improving QPN using the advanced DL model in video prediction, this study suggests the QPN model based on simple yet better video prediction (SimVP), which is a state-of-the-art DL model. We trained the SimVP model using radar data in South Korea from June to September (JJAS) for the period of 2019-2022, which includes the summer and early fall. In terms of the critical score index (CSI) with a lead time of 120 minutes (0.46, 0.23, and 0.09 for 1, 5, and 10 mm/h thresholds, respectively), the proposed model showed significant improvement over the existing DL models based on an evaluation from JJAS 2022. Considering different precipitation conditions, three case studies were conducted for heavy rainfall, typhoons, and fast-moving narrow convection events. The suggested model showed comparable or the highest CSI in 120 min with a 1 mm/h threshold in all cases, demonstrating robust performance (0.49, 0.69, and 0.29 for heavy rainfall, typhoon, and narrow convection, respectively). Qualitative evaluation of the proposed model also showed better results in terms of horizontal displacement movement and less underestimation than the other models. In addition, we further explored the possibility of real-time learning (RTL) with newly added radar data. By repeatedly optimizing DL model for currently facing precipitation events, RTL contributed to deep learning models predicting results more similar to actual radar patterns. It is expected that the proposed SimVP and RTL would serve as a new baseline for DL-based QPN due to their ease of implementation and enhanced performance. 

How to cite: Han, D., Choo, M., and Im, J.: A data-driven precipitation nowcasting framework using advanced deep learning model for video prediction and real-time learning approaches, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13644, https://doi.org/10.5194/egusphere-egu23-13644, 2023.

The accurate forecasting of the intensity of tropical cyclones (TCs) is able to effectively reduce the overall costs of disaster management. In this study, we proposed a deep learning-based model for TC forecasting with the lead time of 24, 48, and72 hours following the event, based on the fusion of geostationary satellite images and numerical forecast model output. A total of 268 TCs which developed in the Northwest Pacific from 2011 to 2019 were used in this study. The Communications system, the Ocean and Meteorological Satellite (COMS) Meteorological Imager (MI) data were used to extract the images of TCs, and the Climate Forecast System version 2 (CFSv2) provided by the National Center of Environmental Prediction (NCEP) was employed to extract atmosphere and ocean forecasting data. In this study, we suggested hybrid convolutional neural network (hybrid-CNN)-based TC forecasting models. It enables to efficiently consider not only the physical but also the spatial characteristics of variables. The Joint Typhoon Warning Center (JTWC) was used for validating the suggested model, and Korea Meteorological Administrator (KMA)-based operational TC predictions were utilized for evaluating the performance of the model. A hybrid-CNN-based prediction model obtained mean absolute errors (MAE) of 13.58, 16.48, and 21.64 kts and skill scores (SS) of 29%, 19%, and 1.6% for 24h, 48h, and 72h forecasts, respectively. Since the rapid intensification (RI) is one of the challenging tasks in the TC intensity prediction, the performance of suggested model for all RIs in 2019 were additionally evaluated. Compared to KMA-based predictions, the suggested models achieved average SS of 66%. Furthermore, using an explainable artificial intelligence (XAI) approach, it is possible to verify how the suggested model works for forecasting TC intensity and propose the feasibility of the suggested model in the meteorology field.

 

How to cite: Lee, J. and Im, J.: Deep learning-based tropical cyclone intensity prediction through synergistic fusion of geostationary satellite and numerical prediction model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14443, https://doi.org/10.5194/egusphere-egu23-14443, 2023.

EGU23-14544 | Orals | AS1.2

EUMETNET Nowcasting Programme 

Franziska Schmid, Anders Sivle, Solfrid Agersten, André Simon, and Aitor Atencia

One major task of the National Meteorological and Hydrological Services (NMHS) is the provision of consistent and integrated forecasting products from minutes to several days ahead (seamless forecasting). The former EUMETNET (European Meteorological Services’ Network) project ASIST (Application oriented analysis and very short-range forecast environment) which started in 2015 focused on the nowcasting and very short range forecasting. Then, it was extended to the EUMETNET Nowcasting Programme (E-NWC) which started in 2019 and will last until the end of 2023 with focus on nowcasting and also on seamless prediction.

In this presentation, the main objectives of the E-NWC Programme will be introduced. E-NWC supports NMHS in sharing expertise, experiences and best practices for developing and implementing nowcasting, very short-range forecasting and seamless prediction systems. Key activities lie in the exchange of information and experiences with the users during e.g. the every two years European Nowcasting Conference and the strong cooperation with the World Meteorological Organization (WMO) and EUMETSAT, and in summarizing the relevant findings in project reports and joint peer-reviewed papers. Highlights of this contribution comprehend a few results from studies and surveys carried out recently.

How to cite: Schmid, F., Sivle, A., Agersten, S., Simon, A., and Atencia, A.: EUMETNET Nowcasting Programme, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14544, https://doi.org/10.5194/egusphere-egu23-14544, 2023.

On 26 November 2022, an extreme rainfall event occurred over Ischia Island (Italy). It triggered a mudflow that swept over Casamicciola Terme town and caused 12 victims. Based on available rainfall data from 4 rain-gauge stations over the island, the precipitation values registered during the event were higher than the annual maxima values of the previous 15 years. With regards to 1 and 24 hours, the rain-gauge stations measured values between 40.6 and 57.6 mm, and between 145.4 and 176.8 mm, respectively. Since one of the main challenges during these phenomena is predicting rainfall sufficiently in advance in order to allow water managers to take action (issue warnings or real-time control), this study investigates how much time before the peak - or threshold exceedance - a machine learning model is able to capture the peak - or threshold exceedance. A model that predicts rainfall intervals and the corresponding probability of occurrence for lead times from 10 minutes to 6 hours is proposed. The model employs cumulative rainfall depths from recording stations in an area of 50 km radius from the Ischia Island as inputs for a Feed Forward Neural Network to nowcast rainfall in the 4 rain-gauges over the study area. Based on almost 400 rain events observed during years 2009-2022, 24 machine learning models were independently trained for each rain-gauge and each of the 6 lead-times - 10, 30, 60, 120, 180 and 360 minutes. The performance of each model was evaluated and compared using different metrics, both continuous (RMSE and MAE) and categorical (POD and FAR). In addition, the Eulerian Persistence (EP) was considered as a benchmark model. The rainfall nowcasts showed encouraging results. Even though for convective rain events the potential lead-time is short, the models produced consistent nowcasts for lead-times up to 2 hours. With probabilities of almost 90%, the thresholds exceedance was forecasted up to 1 hour before. As expected, predictive accuracy and probabilities gradually decreased as the lead-time increased, according to physically based models. Moreover, the proposed models outperformed the benchmark EP for all the lead-times and performance criteria. Results confirmed that the use of cumulative rainfall depths for precipitation nowcasting made this approach a promising tool for nowcasting purposes, and his flexibility and conceptual simplicity resulted in a rapid, easily replicable and convenient nowcasting approach. To conclude, the proposed models enhanced a first identification of critical thresholds, which should be further analysed in order to achieve a better, complementary understanding of the occurring phenomenon. 

Keywords: Precipitation nowcasting; Multi-step predictions; Rain-gauge measurements; Pattern recognition; Feed forward neural networks; Cumulative rainfall fields.

How to cite: Pirone, D., Del Giudice, G., and Pianese, D.: Machine Learning models for probabilistic rainfall nowcasting applied to a case study in Italy: the extreme rainfall event on 26 November 2022 over Casamicciola town, Ischia Island., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14545, https://doi.org/10.5194/egusphere-egu23-14545, 2023.

EGU23-14709 | ECS | Orals | AS1.2

Improving Dual-Polarization Radar-based rainfall estimation using Long Short-Term Memory Neural Networks 

Jiun-Liang Lin, Chia-Yu Hsu, and Li-Chiu Chang

Extreme hydrological events, which are highly concerned by local governments, hydraulic units and hazard response centers due to their potential to bring heavy rainfall and cause serious floods, have frequently occurred and impacts on Taiwan urban area in recent years under the circumstance of climate change and global warming. The frequent occurrence of high intense storm always leads to flooding-related disasters within a short period, which makes rainfall monitoring a disaster prevention. Therefore, this study utilizes Long Short-Term Memory Neural Networks (LSTM) and Back Propagation Neural Networks (BPNN) to extract the characteristics of radar observations and forecast rainfall with time 1-step-ahead to 6-step-ahead (T+1~T+6) in Taiwan’s capital, Taipei City. The data collection was included in the Shulin dual-polarization radar (RCSL) observations, such as differential phase shift, specific differential phase, reflectivity and doppler radial wind field, and rain gauge data from May 2021 to November 2021 in the Taipei City. With a view to capturing the movement of hydrometeors continually changes within the time step, an algorithm which can calculate velocity and direction of specific hydrometeors on two-dimensional matrix were developed and applied to simulate location of the specific hydrometeors on n-step-ahead (T+n). Finally, the rainfall forecast can be achieved by using the simulated location of specific hydrometeors and its physical properties from radar observations as input data to fit rainfall from the gauge. This study aims to investigate the relationship between short-duration rainfall and radar observations by artificial neural network (ANN), and forecast the rainfall  within a short period.

 

Keywords: Dual-Polarization Radar; Rainfall Estimation; Artificial Intelligence (AI), Artificial neural network (ANN); Long Short-Term Memory Neural Networks(LSTM)

How to cite: Lin, J.-L., Hsu, C.-Y., and Chang, L.-C.: Improving Dual-Polarization Radar-based rainfall estimation using Long Short-Term Memory Neural Networks, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14709, https://doi.org/10.5194/egusphere-egu23-14709, 2023.

Reliable early forecasting of summer air temperature is important to effectively prepare and mitigate damage such as heat-related mortality and excessive electricity demand caused by heat waves and tropical nights. Numerical weather prediction (NWP) models have been used for operational forecasting of air temperature. However, NWP models have coarse spatial resolution due to massive computational resources arising from complex forecasting systems and unstable parameterization of NWP models, which make the uncertainty of prediction, consisting of systematic and random biases. Therefore, the objective of this study is to develop a novel deep learning-based statistical downscaling approach for the Global Data Assimilation and Prediction System (GDAPS) model’s summer air temperature forecasts over South Korea. This study developed the proposed statistical downscaling model through the decomposition into the temporal dynamics of daily air temperature forecast and spatial fluctuation by pixels. The daily temperature dynamic was estimated using a daily mean GDAPS temperature forecast with simple mean bias correction. The spatial fluctuation by pixels was obtained using the spatial anomaly of downscaled air temperature forecast by the U-Net model. The GDAPS model’s forecast data, present-day high spatial resolution satellite observations, and topography variables were used as input variables for training the U-Net model. The observations at weather stations were spatially interpolated using the regression-kriging, and then we used it as a target image for the U-Net model. The proposed U-net model was compared with the Local Data Assimilation and Prediction System (LDAPS), the dynamically downscaled model of the GDAPS, and the support vector regression (SVR)-based statistical downscaling model. For next-day Tmax and Tmin forecasts, the suggested U-net model showed better performance, having high coefficient of determination (R2) of 0.76 and 0.74 and root mean square error (RMSE) of 2.5 °C and 1.5 °C for next-day Tmax and Tmin forecasts, respectively. When analyzing the skill score (SS) values by stations of the U-Net model, it had remarkably high SS values at stations where the GDAPS had a high absolute value. For Tmax and Tmin forecasts with 1-7 days forecast lead time, the suggested model consistently provided better performance (higher spatial correlation and lower RMSE) than GDAPS and SVR. In addition, the U-net model showed a detailed spatial distribution most similar to that of the observations. These results demonstrated that the suggested model successfully corrected the bias of the GDAPS, improving not only the forecast accuracy but also the ability to capture the spatial distribution of Tmax and Tmin forecasts. Using the deep learning-based suggested model in this study, bias-corrected high spatial resolution air temperature forecasts with a relatively long forecast lead time in summer seasons can be successfully produced.

How to cite: Cho, D., Im, J., and Jung, S.: Deep learning-based statistical downscaling for short-term forecasting of summer air temperatures, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14894, https://doi.org/10.5194/egusphere-egu23-14894, 2023.

EGU23-14973 | ECS | Posters on site | AS1.2

Operational machine learning for the postprocessing of surface wind forecasts 

Daniele Nerini, Francesco Zanetta, Mathieu Schaer, Jonas Bhend, Christoph Spirig, Lionel Moret, and Mark A. Liniger

Forecasting winds at the local scale can be challenging due to the highly variable and complex nature of wind patterns, particularly in the case of complex terrain. In such cases, the accuracy of numerical weather prediction models (NWPs) is often limited by the quality of their initial conditions and their grid resolution. This is where the use of observational data through statistical postprocessing techniques can help to improve the quality of forecasts. 

Statistical postprocessing is nowadays an established component in operational weather forecasting that is used to improve the accuracy, resolution, and calibration of NWP ensemble forecasts with historical observations. In recent years, machine learning techniques have shown great potential in the field of postprocessing, thanks to their ability to deal with increasingly large volumes of data, and the capacity to capture complex relationships between forecasts and observations that are not explicitly represented in traditional postprocessing methods. 

To capitalize on machine learning for weather applications, and for it to gain acceptance and become a reliable technology for operational use, it is also crucial to consider the technical and engineering challenges that arise when implementing machine learning in a productive environment. MLOps, or Machine Learning Operations, is a set of practices that are used to manage and streamline the deployment, monitoring, and maintenance of machine learning models in production.  

We will present our recent experience with the development and operationalization of a statistical postprocessing system based on the use of neural networks to predict the probability distribution of forecasts of surface winds. Following MLOps best practices, our framework aims to improve the reproducibility and automation of most common tasks in a machine learning-based system, such as efficient data loading and manipulation, the monitoring and visualization of prediction quality, and the automation of model training and deployment pipelines. 

How to cite: Nerini, D., Zanetta, F., Schaer, M., Bhend, J., Spirig, C., Moret, L., and Liniger, M. A.: Operational machine learning for the postprocessing of surface wind forecasts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14973, https://doi.org/10.5194/egusphere-egu23-14973, 2023.

EGU23-15153 | Orals | AS1.2

Ensemble precipitation nowcasting by combination of generative and transformer deep learning models 

Gabriele Franch, Elena Tomasi, Virginia Poli, Chiara Cardinali, Marco Cristoforetti, and Pier Paolo Alberoni

This work introduces a novel deep-learning method for generating realistic ensembles nowcast of radar-based precipitation at a five-minute time resolution for the next 60 minutes and longer.

The proposed method is composed of a combination of two models: the first model is trained to compress and decompress the spatial domain into and from a discrete representation (tokens), while the second model evolves the compressed representation over time. Specifically, the compression and decompression model is based on a combination of a Quantized Variational Autoencoder with a Generative Adversarial Network, while the prediction over time leverages a Generative Pretrained Transformer (GPT) architecture.

This separation of concerns (discretized spatial compression/decompression and temporal extrapolation) adds several desirable features not present in more commonly used deep learning methods based on recurrent/convolutional deep learning architectures: 

  • transformer output probabilities can be leveraged to generate ensemble/probabilistic forecasts (without the need of injecting noise)
  • the discretized spatial representation can be used to characterize each token, adding interpretability and explainability to the model
  • the combination of transformer probabilities and token characterization can be used at inference time for forecasts conditioning based on external factors (e.g. NWP forecast output)

The presented architecture is trained and tested on a 7-year radar dataset of reflectivity composites of the Emilia-Romagna Region, Italy. The method is then applied at two different scales: regional, over Emilia-Romagna, and national, on the entire Italian domain, showing the adaptability of the approach to multiple spatial domains. We will present the performance of this model for both deterministic and ensemble settings by comparing it with respect to other commonly used extrapolation and deep learning methods.

How to cite: Franch, G., Tomasi, E., Poli, V., Cardinali, C., Cristoforetti, M., and Alberoni, P. P.: Ensemble precipitation nowcasting by combination of generative and transformer deep learning models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15153, https://doi.org/10.5194/egusphere-egu23-15153, 2023.

EGU23-15514 | Orals | AS1.2

Probabilistic Precipitation Nowcasting with Physically-Constrained GANs 

Matej Choma, Matej Murín, Jakub Bartel, Milly Troller, and Michal Najman

It is generally accepted that weather forecasts contain errors due to the chaotic nature of the atmosphere. Regression models, such as neural networks, are traditionally trained to minimize the pixel-wise difference between their predictions and ground truth. The major shortcoming of these models is that they express uncertainty about prediction with blurring, especially for longer prediction lead times. One way to tackle this issue is to use a generative adversarial network, which learns what real precipitation should look like during training. Coupled with a loss, such as Mean Squared or Mean Absolute Error, these networks can produce highly accurate and realistic nowcasts. As there is an inherent randomness in those networks, they allow to be sampled from, just like ensemble models, and various probabilistic metrics can be calculated from the samples. In this work, we have designed a physically-constrained generative adversarial network for radar reflectivity prediction. We compare this network to one without physical restraints and show that it predicts events with higher accuracy and shows much less variance among its samples. Furthermore, we explore fine-tuning the network to the prediction of severe weather events, as an accurate prediction of these benefits both automated warning systems and forecasters.

How to cite: Choma, M., Murín, M., Bartel, J., Troller, M., and Najman, M.: Probabilistic Precipitation Nowcasting with Physically-Constrained GANs, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15514, https://doi.org/10.5194/egusphere-egu23-15514, 2023.

EGU23-16271 | Posters virtual | AS1.2

Results of a GPS Zenith Total Delay data assimilation experiment over Italy 

Stefano Federico, Rosa Claudia Torcasio, Eugenio Realini, Giulio Tagliaferro, and Stefano Dietrich

The Mediterranean area is often struck by severe weather events and deep convective events because of the presence of the warm sea, the complex orography of the area, and the specific synoptic scale environment. This scenario is worsened by climate change because, as climate change is affecting many weather and climate extremes, and the frequency and intensity of heavy precipitation events have increased in most of the world.

Over the past years, the use of Numerical Weather Prediction (NWP) models, along with an increasing availability of computing power, led to an improvement of the forecast accuracy. However, NWPs have well-known difficulties in capturing the physical processes at small spatial and temporal scales which are involved in convective or severe weather events. 

In this work we study the impact of assimilating GPS-ZTD (Global Positioning System-Zenith Total Delay) on the precipitation forecast over Italy for the month of October 2019, characterized by several moderate to intense precipitation events. The Weather Research and Forecasting (WRF, version 4.1.3) is used with its 3DVar data assimilation system. The horizontal resolution is 3km while the vertical domain spans the whole troposphere and lower stratosphere.

A dense network of about 500 GPS receivers was used for data assimilation and verification of the atmospheric water content. The dataset was built collecting data from all the major national and regional GNSS permanent networks, achieving dense coverage over the whole area.

Results show that WRF underestimates the atmospheric water content for the period, and GPS-ZTD data assimilation reduced this underestimation by increasing the water content of the atmosphere. The GPS-ZTD data assimilation increases the precipitation forecast amount, and the model performance are improved up to 6h.

Results for a case study show that the GPS-ZTD data assimilation can improve the precipitation forecast in different ways: predicting rainfall missed by the model without data assimilation or better focusing the precipitation already predicted by the model without GPS-ZTD data assimilation on the impacted area, the main drawback being the prediction of false alarms.

 

How to cite: Federico, S., Torcasio, R. C., Realini, E., Tagliaferro, G., and Dietrich, S.: Results of a GPS Zenith Total Delay data assimilation experiment over Italy, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16271, https://doi.org/10.5194/egusphere-egu23-16271, 2023.

EGU23-360 | ECS | Orals | AS1.3

Factors influencing subseasonal predictability of Northern Eurasian cold spells 

Irene Erner, Alexey Karpechko, and Heikki Järvinen

The study focuses on identifying potential “windows of opportunity” for the enhanced predictability of extreme events, such as severe Northern Eurasian cold air outbreaks as these events have significant impacts on human health, energy use, agriculture and welfare.  The extended-range predictability of extreme events is closely related to the preceding large-scale circulation patterns and remote teleconnections. To assess the predictability of these events and attribute their causes we use ensemble hindcasts (i.e., reforecasts for dates in the past) from five prediction systems from the S2S database – namely, from the European Centre for Medium‐range Weather Forecasts (ECMWF), the United Kingdom Met Office (UKMO), Météo‐France (CNRM), Bureau of Meteorology (BoM), Japan Meteorological Agency (JMA). These models have long re-forecast periods and big ensemble sizes necessary to establish statistically robust results. Moreover, the comparison of the forecasts from these six models evaluates the ability of modern prediction systems to forecast extreme events well in advance and highlights the main sources of predictability. We subsample the hindcasts into two groups according to their skill to predict an extreme event beyond weather predictability horizon (lead time week 2 and 3) in order to study the systematic relationship between preceding conditions and the onset of extreme events. Next, we evaluate the flow configurations in the initial conditions: the state of the stratospheric polar vortex (SPV), the phase and amplitude of the Madden-Julian Oscillation (MJO) in the tropics, and the weather regimes over the North Atlantic and Europe. This analysis provides a systemic evaluation and understanding of the large-scale patterns that can potentially contribute to the onset of extreme events over Eurasia, therefore, extending their predictability. Our results show that in overall models tend to over-predict cold conditions after certain states of the remote drivers but there is case-to-case variability in the predictability of the individual events. Moreover, this study assesses and compares the results from several state-of-art predicting systems which provides useful information for model developers as well as for forecast users.

How to cite: Erner, I., Karpechko, A., and Järvinen, H.: Factors influencing subseasonal predictability of Northern Eurasian cold spells, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-360, https://doi.org/10.5194/egusphere-egu23-360, 2023.

EGU23-553 | ECS | Posters on site | AS1.3

The influence of the stratosphere on the North Atlantic storm track predictability in subseasonal-to-seasonal reforecasts 

Hilla Gerstman, Dominik Büeler, C. Ole Wulff, Michael Sprenger, and Daniela Domeisen

Extreme stratospheric polar vortex events, such as sudden stratospheric warmings (SSW) or extremely strong polar vortex (SPV) states, can have a prolonged downward impact, influencing surface weather for several weeks to months. These events often lead to changes in the midlatitude storm track position and associated cyclone frequency over the North Atlantic and Europe. Such changes can result in infrastructure damage and health impacts due to cyclone-associated extreme winds and the risk of flooding or heavy snowfall. However, there exists a strong inter-event variability in these downward impacts on the tropospheric storm track, leading to opposite predictions of the storm track response. Therefore, identifying the biases in the forecast of the downward impact of stratospheric polar vortex extremes can improve the predictability of extratropical winter storms on subseasonal-to-seasonal timescales, and has the potential to benefit society and stakeholders.

Using ECMWF reanalysis data and ECMWF reforecasts from the Subseasonal to Seasonal (S2S) Prediction Project database, we investigate the stratospheric influence on extratropical cyclones, identified with a cyclone detection algorithm. Following SSWs, there is an equatorward shift in cyclone frequency over the North Atlantic in reforecasts, and a poleward shift is observed after SPV events, consistent with the response in reanalysis. However, less than 70% of the reforecasts capture the sign of the cyclone frequency response over the North Atlantic during weeks 1-2 after SSWs, and less than 50% of the reforecasts capture the response during weeks 3-4. The cyclone forecasts following SPV events are generally more successful. We further discuss the differences in predictability of extratropical cyclones between the two types of stratospheric extremes.

The results provide new insights on the role of the stratosphere in subseasonal variability and predictability of extratropical cyclones during winter that can be used for forecasting their frequency and surface impacts.

How to cite: Gerstman, H., Büeler, D., Wulff, C. O., Sprenger, M., and Domeisen, D.: The influence of the stratosphere on the North Atlantic storm track predictability in subseasonal-to-seasonal reforecasts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-553, https://doi.org/10.5194/egusphere-egu23-553, 2023.

EGU23-861 | Orals | AS1.3

Boreal Summer Intraseasonal oscillation convective initiations in S2S models 

Daniel Simon and Neena Joseph Mani

Boreal summer Intraseasonal Oscillation (BSISO), with its 20–90 day periodicity characterised by northward propagation over the northern Indian Ocean and eastward propagation over the equatorial region, acts as a major source of predictability in the intraseasonal time scale. Predicting the initiation of BSISO over the equatorial Indian Ocean is of vital importance in the prediction of BSISO's northward advancement over the ISM domain. This study tries to investigate where we stand in terms of predicting the BSISO initiation and propagation, making use of the reforecasts available from the different operational forecasting centres part of the Sub-Seasonal-to-Seasonal (S2S) prediction project. The BSISO convective initiations over the Equatorial Indian Ocean are objectively identified using OLR MJO Index(OMI), and the ability of the models to simulate the initiation and propagation of BSISO is assessed. The BSISO propagation skill, quantified in 9 S2S models, ranges from 11 to 29 days, while the BSISO initiation skill, quantified in 4 out of 9 models, ranges from 11 to 16 days, which is systematically lower compared to the skill of the BSISO non-initiation stages. Two major regions of BSISO initiation were identified, one over the Western Equatorial Indian Ocean and another over the Eastern equatorial Indian Ocean. Over these identified initiation regions, observation show a buildup (reduction) of lower tropospheric moisture before (after) the BSISO initiation. Out of the 9 models considered, few capture either the buildup or reduction, while the majority of the models show biases in capturing the moisture buildup and reduction. Previous studies have emphasised the role of background moisture in the propagation of BSISO. The relationship between the background moisture gradient over the ISM domain and the BSISO propagation prediction skill is examined in the S2S models and a positive relationship is found.

How to cite: Simon, D. and Joseph Mani, N.: Boreal Summer Intraseasonal oscillation convective initiations in S2S models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-861, https://doi.org/10.5194/egusphere-egu23-861, 2023.

EGU23-953 | Posters on site | AS1.3

s2spy, a package to boost (sub) seasonal forecasting with artificial intelligence 

Yang Liu, Bart Schilperoort, Jannes van Ingen, Sem Vijverberg, Peter Kalverla, and Dim Coumou

Reliable (sub) seasonal (S2S) forecasts remain a huge scientific challenge. The lead-time is too long to benefit from the atmosphere’s inertial memory, but too short for the atmosphere’s boundary conditions to be felt strongly. Only for specific "windows of predictability" (i.e. specific regions, timescales and climatic background states), skillful forecasts are possible, in an otherwise largely unpredictable future. Due to a number of successes in S2S forecasting, the interest in machine learning (ML) is growing fast. However, we argue there is a need for more standardization, consensus on best practices, higher efficiency, and higher reproducibility. Typical S2S ML use-cases, such as (1) pure statistical forecasting based on observations, (2) transfer learning, and (3) post-processing of dynamical model ensembles, require a large coding and preprocessing effort. Such experiments are not trivial to set up, and without sufficient experience and expertise there is a large risk of improper cross-validation and/or improper and non-standard verification.

Within a 3-year project, we are developing a high-level Python package called s2spy. Our aim is to make ML workflows more transparent and easier to build, and to facilitate standardization and collaboration across the S2S community. s2spy also contributes to a higher reproducibility and works towards a wider acceptance of standards and best practices. We will present our vision and the capabilities of our package, show-casing that we can build a model from raw climate data up to verification and explanation in only a few lines of code.

How to cite: Liu, Y., Schilperoort, B., van Ingen, J., Vijverberg, S., Kalverla, P., and Coumou, D.: s2spy, a package to boost (sub) seasonal forecasting with artificial intelligence, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-953, https://doi.org/10.5194/egusphere-egu23-953, 2023.

EGU23-1102 | ECS | Orals | AS1.3

MJO-induced land-atmosphere feedbacks across East Africa 

Joshua Talib, Christopher Taylor, Bethan Harris, and Caroline Wainwright

Across East Africa, sub-seasonal rainfall variability predominantly depends on the phase of the Madden Julian Oscillation (MJO). Rainfall is enhanced during MJO phases 2 to 4, and suppressed during phases 6 to 8. Given that MJO-induced anomalous precipitation can persist beyond several days, a surface response is expected. Using earth observations and reanalysis data, in this presentation we will show how MJO-induced precipitation anomalies promote a surface response which feeds back onto local and regional atmospheric conditions.

              MJO-induced rainfall suppression across East Africa decreases surface soil moisture across the exit region of the Turkana jet. Reduced soil moisture increases surface sensible heat fluxes and elevates land surface temperatures. The drier and warmer surface reduces surface pressure and leads to an intensification of the Turkana jet. We conclude that on average approximately 11% of the anomalous jet speed is associated with surface-driven pressure fluctuations over the course of a single day. Since the Turkana jet controls moisture transport from low-lying regions of East Africa into Central Africa, we highlight that surface-induced jet variations impact rainfall totals across East Africa. Furthermore, due to the Turkana jet response to spatial variations in surface warming, we also identify that the magnitude of MJO-induced anomalous precipitation is influenced by surface conditions prior an MJO event. For example, when the surface over southern South Sudan is anomalously dry, MJO-induced precipitation suppression is greater. This presentation will highlight that to fully exploit predictability from the MJO, forecast models must correctly represent surface processes and land-atmosphere interactions. Future work evaluating sub-seasonal forecast models and improving the representation of land-atmosphere interactions will enhance the lead-time of early warning systems across East Africa.

How to cite: Talib, J., Taylor, C., Harris, B., and Wainwright, C.: MJO-induced land-atmosphere feedbacks across East Africa, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1102, https://doi.org/10.5194/egusphere-egu23-1102, 2023.

EGU23-1187 | Orals | AS1.3 | Highlight

Deep-learning-based monthly precipitation forecast for Europe 

Ramon Fuentes-Franco and Klaus Zimmermann

We implement deep neural networks to forecast monthly precipitation over Europe. This architecture conformed by several convolutional layers and fully connected layers uses four different variables (surface temperature, west-east wind at 200 hPa, precipitation and sea level pressure) coming from seven different operational forecast systems (1. ECCC 2. MeteoFrance  3. DWD  4. JMA 5. NCEP  6. ECMWF  7. CMCC). The neural network is trained using observations from E-OBS, a gridded land-only observational dataset covering the whole European continent. This convolutional neural network is trained using the period 1993-2012 and the validation period is 2013-2016, which is the range that is available for all operational forecast systems. 

Comparing with precipitation from observations we show that forecasted precipitation from this Deep-Learning model shows small biases in the whole European continent when forecasting monthly precipitation, especially over Sweden (with a small overestimation of less than 0.2 mm/day). With some higher negative biases over Southern Europe (<-1 mm/day). In turn, the representation of the mean precipitation over specific months and seasons was also assessed, showing that during the validation period this method is able to reproduce properly the spatial features of mean precipitation over Europe and its intensity.

How to cite: Fuentes-Franco, R. and Zimmermann, K.: Deep-learning-based monthly precipitation forecast for Europe, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1187, https://doi.org/10.5194/egusphere-egu23-1187, 2023.

EGU23-1286 | ECS | Orals | AS1.3

Wheat yields in Kazakhstan can successfully be forecasted using a statistical crop model 

Paula Romanovska, Bernhard Schauberger, and Christoph Gornott

The COVID-19 pandemic, recent extreme weather events around the globe and the invasion of Russian forces in Ukraine have led to a disrupted global food market. As the 12th largest global wheat exporter, Kazakhstan is fundamental for regional and global food security. Timely and reliable predictions of Kazakh wheat production could therefore improve food security planning and management in Central Asia and beyond.

In this session, we want to present a statistical weather-driven yield forecast model that is run with publicly available weather and yield data and requires low computational power, making it easily replicable. Decision makers in Kazakhstan have expressed high interest in using the forecast model as a replenishment to currently applied work-intensive forecasting methods. We stringently evaluated our model in a double out-of-sample validation and used it to forecast total national wheat production in a fully blind run for 2022.

Our results show that the model can successfully hindcast wheat yields at the oblast (regional) level up to two months before the harvest. The hindcast of wheat yields for 1993 to 2021 produces a median R2 of 0.69 for the full model run and R2 values of 0.60 and 0.37 for two levels of out-of-sample validations, respectively. Based on these yield estimates we provide a robust hindcast of the total wheat production for Kazakhstan with an R2 value of 0.86 (0.81 and 0.73 for two levels of out-of-sample validations). We forecast total wheat production in Kazakhstan for 2022 to be 12.4 million tonnes and thus 5 % above the production of the last year.

How to cite: Romanovska, P., Schauberger, B., and Gornott, C.: Wheat yields in Kazakhstan can successfully be forecasted using a statistical crop model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1286, https://doi.org/10.5194/egusphere-egu23-1286, 2023.

EGU23-1376 | ECS | Posters on site | AS1.3

New classification showing the stratospheric memory concept: towards a better seasonal prediction 

Alexis Mariaccia, Philippe Keckhut, and Alain Hauchecorne

A new method of classification based upon an empirical orthogonal functions (EOFs) analysis of zonal wind anomalies of the 70 winters from 1950 to 2020, extracted from ERA5, revealed that the winter stratosphere tends to follow four independent scenarios. The first three scenarios: the January, the February, and the Double modes, are all characterized by a perturbed evolution of the polar vortex due to significant sudden stratospheric warmings (SSWs) occurring in mid-winter, generally causing the reversing of zonal winds. Unsurprisingly, these modes contain the information of preferential important SSWs’ timings, events including minor and major SSWs, and final stratospheric warming’s timings. Thus, their patterns show that the mid-winter is often anti-correlated with the winter end. This result is consistent with the conclusion done in a recent study showing that the polar vortex on a given month is anti-correlated with its state 2-3 months earlier. While the last scenario illustrates an unperturbed polar vortex evolution during winter for which only the final stratospheric warming’s timing differs, either early and dynamical or late and radiative.

The study of the mean evolutions of wave-1 and wave-2 amplitude anomalies associated with these four scenarios reveals that they possess singular dynamic behavior, especially for the wave-1 activities, which are consistent with their mean evolutions of zonal mean zonal winds. Indeed, we found that the wave-1 activity drops systematically for each scenario when zonal winds weaken due to an important. In contrast, it is not the case for the wave-2 activity.

How to cite: Mariaccia, A., Keckhut, P., and Hauchecorne, A.: New classification showing the stratospheric memory concept: towards a better seasonal prediction, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1376, https://doi.org/10.5194/egusphere-egu23-1376, 2023.

EGU23-2752 | Posters on site | AS1.3

MJO-related China rainfall teleconnections in the MetUM 

Maria Joao Carvalho, Prince Xavier, and Kalli Furtado

During a Madden-Julian Oscillation (MJO) event, anomalous convection triggers a dynamical response with anomalous large-scale ascent and upper-tropospheric divergence outside the tropics creates interaction between the MJO and the extratropical weather, modes of global circulation and climate variability. The MJO is known to have an impact on China rainfall and regional circulation with enhanced/ suppressed rainfall in South China during the propagation of the MJO from the Indian Ocean into the western Pacific. As the MJO is considered a major source of predictability at subseasonal time scales, it is important to understand how climate models are representing the MJO and its remote effects. This study is aimed to investigate the modelled MJO and associated local effects in China precipitation using the Met Office Unified Model (MetUM). It was found that the response of the rainfall over South China is asymmetric, with the enhancement of rainfall during the Indian Ocean convective phases (phase 2) of the MJO being much stronger than the suppression during the west Pacific phases (phase 6). This response signal was mostly due to the increase in probability of extreme precipitation events rather than the increase in number of rainy days. Analysis of the modelled MJO and associated response shows, although the MJO is more realistically represented in the atmosphere-ocean coupled simulation, the atmosphere-only simulation showed more evidence of MJO-related remote effects in the rainfall patterns over China. The ocean-coupled simulation shows no significant response to the propagation of MJO-associated convection whereas the atmosphere-only simulation shows the correct pattern of enhancement and suppression of rainfall and associated regional circulation pattern changes. The differences found in the representation of remote effects between atmosphere-only and ocean-coupled simulations may be attributed to the air-sea interaction processes and to fundamentally different mean-state biases which affect not only the representation of the MJO but also the propagation of MJO-induced Rossby waves. 

How to cite: Carvalho, M. J., Xavier, P., and Furtado, K.: MJO-related China rainfall teleconnections in the MetUM, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2752, https://doi.org/10.5194/egusphere-egu23-2752, 2023.

EGU23-3039 | ECS | Orals | AS1.3

The Optimal Initial Condition of MJO Development 

Chun-Hao Chang and Kai-Chih Tseng

Madden-Julian Oscillation (MJO), an intraseasonal oscillation over the equatorial Indian ocean and Pacific, has profound impacts around the globe. Its extended-range life cycle (20-90 days) makes it the most important predictability source on subseasonal-to-seasonal timescales. While the mechanisms responsible for MJO's life cycle have been well  explored through the frameworks of moisture modes, and tropical wave dynamics, the mechanisms of initiation remain unsolved. By using linear inverse modeling (LIM) and incorporating different frameworks, this study investigates the processes resulting in MJO convection initiation. It is suggested that multi-scale interactions play a vital role in intraseasonal convection initiation over the Indian ocean. On intraseasonal timescales, the remnant of former MJO can create an environment favoring the convection development for the next event through modulating the prevailing circulations and moisture state (e.g., moisture advection). On shorter timescales (< 20 days), the optimal initial condition arises from the synoptic convergence/divergence of moisture flux, and the upper troposphere instability. 

How to cite: Chang, C.-H. and Tseng, K.-C.: The Optimal Initial Condition of MJO Development, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3039, https://doi.org/10.5194/egusphere-egu23-3039, 2023.

EGU23-5201 | ECS | Posters on site | AS1.3

How well in advance can we predict cold spells over France? 

Naveen Goutham, Hiba Omrani, Omar Himych, and Riwal Plougonven

France is committed to achieving climate neutrality by 2050. In this respect, the heating sector, one of the largest energy-consuming sectors in France, is undergoing rapid electrification. In 2022, electricity contributed to the heating of more than 40% of French dwellings. As a result, the French electricity demand is increasingly becoming thermosensitive. Accordingly, for every 1°C drop in temperature below the threshold (i.e., 15°C) during winter, the electricity demand increases by ~2.4 GW in France. With a notable share of French nuclear reactors reaching their end of service life, several recent episodes of widespread cold spells over France have raised concerns about energy security. Hence, anticipating cold spells well in advance is increasingly becoming important for the smooth operation of the energy sector. In this regard, we assess the predictability of several recent episodes of cold spells on seasonal timescales over France using the seasonal predictions from the European Centre for Medium-Range Weather Forecasts. Additionally, we test a recently developed statistical downscaling methodology in forecasting cold spells over France, using the forecasts of upper-level fields, which are better predicted than the surface fields. On comparing the dynamical and statistical predictions, we show that the statistical predictions, relying upon the information contained in the better-predicted upper-level fields, perform significantly better than the dynamical counterparts in predicting cold spells beyond a month.

How to cite: Goutham, N., Omrani, H., Himych, O., and Plougonven, R.: How well in advance can we predict cold spells over France?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5201, https://doi.org/10.5194/egusphere-egu23-5201, 2023.

EGU23-5397 | ECS | Orals | AS1.3 | Highlight

Factors influencing sub-seasonal forecast skill of Greenland Blockings 

Marisol Osman, Christian M. Grams, and Remo Beerli

Greenland blocking (GL) resembles the negative phase of the NAO and features a strong positive Z500 anomaly over Greenland and a zonally aligned negative anomaly stretching from the eastern North Atlantic into Northern Europe. The prevailing westerly flow is then deflected southward and extends into the Mediterranean. It causes melting events of the Greenland Ice Sheet which can impact global sea-level rise and has strong downstream impacts on Europe. It occurs year-round, although is more common in winter (11.7%) compared to summer (9.1%). GL is forecast with good ability by S2S models. This skill is driven by the performance in winter, when GL is persistent. In this study, we explore whether the skill of GL blocking can be linked to external meteorological drivers or the prevalence of specific meteorological features. Re-forecasts using the European Centre for Medium-Range Weather Forecasts for the 1999-2019 period are considered and compared against ERA Interim reanalysis over the same period. We focus on the factors affecting the skill, as depicted by the Brier Skill Score, from lead times 6 to 10 days, where the skill is 30% to 70% smaller than the skill at lead time 1 day.

Results show that most of the GL blocking events associated with low skill occur in spring. In this season, the model fails in forecasting the transition from Scandinavian Blocking to Greenland Blocking, in opposition to the rest of the seasons, when this transition is well predicted. The analysis of the role of large-scale processes that affect GL skill reveals that half of the forecasts of GL events initialized up to 30 days after a sudden stratospheric warming shows poor skill. In addition, the forecasts of GL events initialized with an active MJO in phase 6 and 7 present good skill whereas those forecast GL events initialized during an active MJO in phase 2 to 4 show poor skill. This link between large-scale factors and skill offers potential guidance in operational forecasting.

How to cite: Osman, M., Grams, C. M., and Beerli, R.: Factors influencing sub-seasonal forecast skill of Greenland Blockings, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5397, https://doi.org/10.5194/egusphere-egu23-5397, 2023.

EGU23-5665 | ECS | Orals | AS1.3

The seasonal teleconnections of the Indian Ocean Dipole to the North Atlantic region 

Tim Hempel, Antje Weisheimer, and Tim Palmer

The Indian Ocean Dipole (IOD) is a major source of seasonal climate variability in the
Indian Ocean. This dipole has strong impacts on the Indian Ocean region and through
teleconnections can influence the seasonal climate of remote regions like the North Pacific
and North Atlantic. A prominent example of this teleconnection from the IOD occurred
in the winter 2019/2020, where the IOD was in a positive state. This influenced the state
and predictability of the Northern Hemisphere extratropics. Thus, a good understand-
ing of the mechanism that transports information from the Indian Ocean to the North
Atlantic is desirable. In this contribution we investigate the special teleconnection of the
winter 2019/2020 and analyse the transport mechanism.
In model experiments with the OpenIFS from ECMWF we show that the NAO in the
winter 2019/2020 is influenced by the IOD and analyse the teleconnection mechanisms.
We use hindcast ensemble model experiments of the DJF season 2019/2020 to analyse
the behaviour of the IOD and its impact on the NAO. In the uncoupled OpenIFS the Sea
Surface Temperature (SST) boundary conditions are perturbed in regions of importance
to the NAO (like the ENSO region and the Indian Ocean). With these perturbations we
identify the relative importance of individual ocean regions to the state of the NAO in
the winter of 2019/2020.
We contrast the experiments with the perturbed SST conditions to the operational ECMWF
System5 forecast and ERA5. Experiments with the 2019/2020 SST’s in the In-
dian Ocean (with other boundary conditions set to climatology) reproduce many of the
observed atmospheric 2019/2020 features. In contrast, experiments with SST’s in the
Pacific show very different patterns to the observed 2019/2020 ones.
We identify eddy-mean-flow interactions as a mechanism that connects and transports
information from the Indian Ocean to the North Atlantic. With Hoskins E-Vectors we
show that anomalous eddy activity during IOD events impacts the position and strength
of the Northern Hemisphere extratropical jet. This interaction provides a teleconnection
mechanism in addition to the Rossby-wavetrain discussed in other studies.

How to cite: Hempel, T., Weisheimer, A., and Palmer, T.: The seasonal teleconnections of the Indian Ocean Dipole to the North Atlantic region, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5665, https://doi.org/10.5194/egusphere-egu23-5665, 2023.

EGU23-5742 | Posters on site | AS1.3

S2S prediction of summer heatwaves in the Iberian Peninsula using convolutional networks 

Marie Drouard, Jorge Pérez-Aracil, David Barriopedro, Pablo G. Zaninelli, José M. Garrido-Perez, Dušan Fister, Sancho Salcedo-Sanz, and Ricardo García-Herrera

In this ongoing study we aim at using machine learning algorithms to better understand and improve southern Europe summer heatwave prediction on sub-seasonal to seasonal timescales (S2S). Summer heatwaves are extreme events that have large socio-economic impacts on mortality rate, crop yields, energy demand or water resources and southern Europe is particularly prone and vulnerable to such events.  

To do this, we train a convolutional network coupled with a multilayer perceptron to forecast with a 15-day and 1-month lead times the occurrence and intensity of heatwave in summer. This forecast model is trained with ERA5 data. The predictors fed to this model are monthly means of the SST, local soil moisture, outgoing longwave radiation, snow cover and sea-ice cover. The target is a monthly-mean heatwave index integrated over a sub-area of southern Europe. 

Here, we will present the initial results of this ongoing work and the next steps, focusing first on the Iberian Peninsula only. 

How to cite: Drouard, M., Pérez-Aracil, J., Barriopedro, D., Zaninelli, P. G., Garrido-Perez, J. M., Fister, D., Salcedo-Sanz, S., and García-Herrera, R.: S2S prediction of summer heatwaves in the Iberian Peninsula using convolutional networks, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5742, https://doi.org/10.5194/egusphere-egu23-5742, 2023.

EGU23-6161 | Orals | AS1.3

The Dynamics and Structure of the Baroclinic Annular Mode 

Edwin Gerber, Madeleine Youngs, and Olivier Pauluis

As first explored by Thompson and Barnes (2014), hemispheric mean storm activity (or related quantities, such as the meridional eddy heat flux) exhibits periodicity on 20-30 day time scales.  They characterized this variability with the so-called Baroclinic Annular Mode, or BAM, a ring of enhanced eddy activity which is present in both hemispheres, but most pronounced in the south, which is less perturbed by zonal asymmetries relative to the north.   The mechanism behind this internally generated periodicity, however, has remained elusive.  We probe the dynamics and structure of the BAM on two fronts.  To understand the mechanism, we develop a minimal model that captures the essential dynamics: 2 layer quasi-geostrophic flow in a channel. By varying the geometry of the channel and the thermal and frictional forcing, we tease out the parameters that control the period and amplitude of the BAM.  The resulting changes in the BAM support the general framework of the charge-discharge mechanism proposed by Thompson and Barnes, but demand a more detailed explanation for the coupling between eddies and the mean baroclinicity that generates enhanced variability on subseasonal time scales.  On a second front, we apply dynamical mode decomposition (DMD) to atmospheric reanalyses of the Southern Hemisphere to quantify the structure of the southern BAM.  DMD captures BAM variability, providing additional information on relationships between the eddy kinetic energy and other mean and eddy quantities.  It suggests that moisture plays a fundamental role in the relationship between the eddy activity and baroclinicity, and that changes in stratification are more important than horizontal temperature gradients in the dynamics.    In this sense, the underlying BAM dynamics of vacillation between eddy and potential energy are remarkably robust, active in our moist atmosphere and in dry quasi-geostrophic systems where only the meridional temperature gradient can capture the available energy.

How to cite: Gerber, E., Youngs, M., and Pauluis, O.: The Dynamics and Structure of the Baroclinic Annular Mode, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6161, https://doi.org/10.5194/egusphere-egu23-6161, 2023.

EGU23-6511 | Posters on site | AS1.3

Evaluating Western North Pacific Tropical Cyclone Forecast in the Subseasonal to Seasonal Prediction Project Database 

Xiaochun Wang, Duane Waliser, Frederic Vitart, Xianan Jiang, and Shakeel Asharaf

The Daily Tropical Cyclone Probability (DTCP), defined as the probability of tropical cyclone occurrence within 500 km of a location in one day, is proposed and used in evaluating subseasonal to seasonal (S2S) predictions from the S2S Prediction Project Database, from May 1 to Oct. 31, 1999, to 2010. The ensemble reforecasts are collected from eleven operational centers, the BoM, CMA, ECCC, ECMWF, HMCR, ISAC, JMA, KMA, METFR, NCEP, and UKMO.  In both observation and these eleven forecast models, the DTCP is modulated by the Boreal Summer Intraseasonal Oscillation (BSISO), depicted by the two indices, BSISO1 and BSISO2. During BSISO1 phases 1, 5, 6, 7, and 8, the DTCP in the northwestern Pacific region is ~3.5 times higher. Similarly, during phases 1, 2, 3, 4, and 8 of BSISO2, the DTCP is  ~2.5 times higher.  Among the eleven models, the ECMWF model best reproduces the climatological DTCP and its modulation by the BSISO in the western North  Pacific region, followed by NCEP, KMA, JMA  models. Using the DTCP metric, the highest debiased Brier Skill Score of the eleven models is from ECMWF, which has a slightly less skillful prediction than the reference climatological forecast with lead time 11 to 30 days. The skill of the eleven models is higher during the non-active phases of tropical cyclone activity than their skill during the active phases.  The updated results based on the real-time tropical cyclone forecasts of the S2S Prediction Project Database  from these eleven systems will also be discussed.

How to cite: Wang, X., Waliser, D., Vitart, F., Jiang, X., and Asharaf, S.: Evaluating Western North Pacific Tropical Cyclone Forecast in the Subseasonal to Seasonal Prediction Project Database, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6511, https://doi.org/10.5194/egusphere-egu23-6511, 2023.

EGU23-7102 | ECS | Orals | AS1.3

Tropical cyclone precipitation skill in S2S models 

Jorge L Garcia-Franco, Chia-Ying Lee, Suzana Camargo, Michael Tippett, Daehyun Kim, Andrea Molod, and Young-Kwon Lim

Tropical cyclone precipitation (TCP) contributes a significant fraction of total annual rainfall and also is a frequent cause of extreme precipitation in many parts of the tropics. The climatology of TCP in the S2S models is characterized by dry biases in the North Atlantic and wet biases in most other basins,  specially in the Southern Indian Ocean and Australia. 
Biases in total precipitation (P), TCP and their ratio (TCP/P) are mostly positive in the multi-model ensemble mean and change very little with lead time. in these models the frequency biases are the dominant contribution to TCP biases. However, in some models, there are positive biases in average precipitation per each TC which contribute significantly to TCP biases at equatorial latitudes.

The prediction skill of these reforecasts is evaluated using skill scores such as the ranked probability skill score for TCP and the Brier Skill score for genesis and occurrence. The implication of these results is discussed for their relevance to mean and extreme precipitation prediction skill using S2S models.

How to cite: Garcia-Franco, J. L., Lee, C.-Y., Camargo, S., Tippett, M., Kim, D., Molod, A., and Lim, Y.-K.: Tropical cyclone precipitation skill in S2S models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7102, https://doi.org/10.5194/egusphere-egu23-7102, 2023.

EGU23-7168 | Orals | AS1.3

European S2S streamflow forecasting: Towards a seamless communication 

Ilias Pechlivanidis and Louise Crochemore

Information at the sub-seasonal to seasonal (S2S) time scale can be of high socio-economic value to a variety of users whose decision-making depends on climate variability. The usability of S2S forecasts generated by Numerical Weather Prediction (NWP) systems has increased over the years not only due to their skill improvement but also due to their potential to bridge the medium-range and seasonal horizons. The skill of the sub-seasonal (4-6 weeks ahead) and seasonal (6-12 months ahead) NWP-based forecasts in space and time depends on different factors, including the representation of the physical process, the initialization frequency and the spatial resolution. However, the NWP model setups differ between the two time horizons, and this consequently intrinsic differences between the two forecast products. To date, it has been subjectively accepted that during the first time horizons, e.g. up to 6 weeks ahead, the sub-seasonal forecasts are more informative than the seasonal forecasts, and hence all efforts on generating a seamless product are implemented through a direct merging of the two products. This unfortunately masks the potential for tailored seamless products that extract the best S2S information available.

Here, we evaluate the S2S hydro-meteorological forecasts from the ECMWF sub-seasonal (ENS-ER) and seasonal (SEAS5) products, aiming to identify their skill complementarity in space and time and further seamlessly communicate them for improved decision-making. Both the ENS-ER and the SEAS5 precipitation and temperature forecasts were bias-adjusted prior to forcing the E-HYPE hydrological model. The investigation focuses on the period 1999-2015. Overall, results highlight both spatial and temporal complementarities between the two systems, which is very encouraging for a seamless communication. In particular, ENS-ER-based hydro-meteorological forecast skill patterns appear to be more homogeneous spatially, while SEAS5-based forecasts ensure skill at longer forecast horizons. This diagnostic analysis is a step forward in hydro-climate services, indicating the tipping points in all European river systems for switching from ENS-ER to SEAS5 forecasts.

How to cite: Pechlivanidis, I. and Crochemore, L.: European S2S streamflow forecasting: Towards a seamless communication, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7168, https://doi.org/10.5194/egusphere-egu23-7168, 2023.

EGU23-7750 | ECS | Orals | AS1.3

Probabilistic predictions of global fire activity 

Miguel Ángel Torres-Vázquez, Andrina Gincheva-Norcheva, Amar Halifa-Marín, Juan Pedro Montavez, and Marco Turco

Seasonal forecasts of meteorological drought can help decision-making for weather-driven wildfires (Turco et al., 2018). However, one of the main drawbacks of drought prediction lies in the uncertainty of monitoring precipitation in near-real time. In this contribution we assess the predictability of the Standardized Precipitation Index (SPI) on a global scale, combining 11 datasets (DROP; Turco et al., 2020) as observed initial conditions with empirical and dynamic predictions of precipitation. The empirical predictions are based on the ensemble-based streamflow prediction system (ESP, an ensemble-based reordering of historical data) and the dynamics on the new generation seasonal prediction model developed by ECMWF (System 5; S5). Although both systems show comparable quality, S5 performs better at longer forecast timescales, especially over tropical regions.

Subsequently, we investigate whether the S5 seasonal forecasts can predict area burned anomalies on a global scale. To do so, we link the seasonal climate predictions of S5 to an empirical climate-fire model, using standard regression techniques in the framework of generalised linear models. The seasonal climate predictions of S5 have shown high and significant performance (with a mean relative operating characteristic “ROC” area value of 0.87) over a large fraction of the burnable area (~47%).

In summary, given that all data are publicy available in near real time, our results provide a basis for the development of a global probabilistic seasonal drought and burned area forecast product.

References

Turco, M., Jerez, S., Doblas-Reyes, F. J., AghaKouchak, A., Llasat, M. C., & Provenzale, A. (2018). Skilful forecasting of global fire activity using seasonal climate predictions. Nature Communications, 9(1), 1–9.

Turco, M., Jerez, S., Donat, M. G., Toreti, A., Vicente-Serrano, S. M., & Doblas-Reyes, F. J. (2020). A global probabilistic dataset for monitoring meteorological droughts. Bulletin of the American Meteorological Society, 101(10), E1628–E1644.

Acknowledgements

We acknowledge funding through the project ONFIRE, grant PID2021-123193OB-I00,funded by MCIN/AEI/ 10.13039/501100011033.

How to cite: Torres-Vázquez, M. Á., Gincheva-Norcheva, A., Halifa-Marín, A., Montavez, J. P., and Turco, M.: Probabilistic predictions of global fire activity, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7750, https://doi.org/10.5194/egusphere-egu23-7750, 2023.

EGU23-8258 | Posters virtual | AS1.3

The Winter North Pacific Teleconnection in Response to ENSO and the MJO in Operational Subseasonal Forecasting Models Is Too Weak 

Chen Schwartz, Chaim Garfinkel, Wen Chen, Yanjie Li, Priyanka Yadav, and Daniela I.V. Domeisen

Teleconnection patterns associated with the Madden–Julian oscillation (MJO) and El Niño–Southern Oscillation (ENSO) impact weather and climate phenomena in the Pacific–North American region and beyond, and therefore accurately simulating these teleconnections is of importance for seasonal and subseasonal forecasts. Systematic biases in boreal midwinter ENSO and MJO teleconnections are found in eight subseasonal to seasonal (S2S) forecast models over the Pacific–North America region. All models simulate an anomalous 500-hPa geopotential height response that is too weak. This overly weak response is associated with overly weak subtropical upper-level convergence and a too-weak Rossby wave source in most models, and in several models there is also a biased subtropical Pacific jet, which affects the propagation of Rossby waves. In addition to this overly weak response, all models also simulate ENSO teleconnections that reach too far poleward toward Alaska and northeastern Russia. The net effect is that these models likely underestimate the impacts associated with the MJO and ENSO over western North America, and suffer from a reduction in skill from what could be achieved.

How to cite: Schwartz, C., Garfinkel, C., Chen, W., Li, Y., Yadav, P., and Domeisen, D. I. V.: The Winter North Pacific Teleconnection in Response to ENSO and the MJO in Operational Subseasonal Forecasting Models Is Too Weak, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8258, https://doi.org/10.5194/egusphere-egu23-8258, 2023.

Forecasts on sub-seasonal to seasonal (S2S) timescales have huge potential to improve early warning and anticipatory action ahead of high impact events. However, fully realising this potential predictability requires reliable forecasts that are communicated effectively so that they can support appropriate preparedness action. This study reflects on the African SWIFT (Science for Weather Information and Forecasting Techniques) S2S forecasting testbed which brought together researchers, forecast producers and forecast users from a range of African and UK institutions. The testbed used a co-production approach to pilot the provision of real-time bespoke S2S forecast products for applications. The S2S testbed supported decision-makers in a range of sectors and contexts. For example, informing food security decisions and hydropower energy planning in East Africa, supporting agricultural decision-making across West Africa, and, in health applications, increasing the lead-time for potential disease outbreaks.

 

This study critically reflects on the benefits and challenges of the co-production process within the S2S applications context. Specifically, while having direct access to the real-time S2S data allowed user-guided iterations to products to make them more actionable for their specific context. Some key lessons for effective co-production emerged. First, it is critical to ensure there is sufficient resource to support co-production, especially in the early co-exploration of needs. Second, all the groups in the co-production process require capacity building to effectively work in new knowledge systems. Third, evaluation should be ongoing and combine meteorological verification with decision-makers feedback. Ensuring the sustainability of project-initiated services within the testbed hinges on integrating the knowledge-exchanges between individuals in the co-production process into shaping sustainable pathways for improved operational S2S forecasting within African institutions.

How to cite: Hirons, L.: Using a co-production approach to support effective application of S2S forecasts in Africa, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9342, https://doi.org/10.5194/egusphere-egu23-9342, 2023.

Extreme precipitation events (EPE), especially those leading to floods and landslides, are devastating to society. Predicting these events in advance can help disaster managers to carry out plans of action to respond effectively to any oncoming adverse events. Sub-seasonal forecasts, which aim to predict the weather with 2 weeks to 2 months in advance, can help to provide valuable and actionable information to disaster managers. Given the potential usefulness to end users, it is vital to assess the skill of sub-seasonal forecasts in predicting EPEs. However, given that precipitation is known to be a difficult variable to predict, the lead time at which forecasts are skilful may be limited. This study, therefore, aims to assess at which lead time sub-seasonal forecasts of atmospheric drivers of EPEs are skilful.

The study investigates the skill of the European Centre for Medium-Range Weather Forecast (ECMWF) sub-seasonal reforecast in predicting EPE over Italy from 2001 to 2020. A total of 100 EPEs are used as case studies. The variables evaluated are total precipitation, mean sea level pressure, geopotential height at 500 hPa and specific humidity at 850 hPa. Variables are averaged over the 5 days surrounding the date of the EPE. ERA5 is used as the reference dataset. Both deterministic and probabilistic metrics are used to assess the skill of the reforecast.

Results show that the skill for precipitation is limited to the first two weeks. Nevertheless, the ECMWF sub-seasonal product is skilful in predicting the atmospheric fields associated with the selected EPEs, such as MSLP and geopotential height, showing both reliability and discrimination beyond two weeks.

How to cite: Scott, W., Gaetani, M., and Fosser, G.: Skill assessment of sub-seasonal forecasts of different atmospheric variables related to extreme precipitation events over Italy, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10052, https://doi.org/10.5194/egusphere-egu23-10052, 2023.

EGU23-10243 | ECS | Orals | AS1.3

Improved subseasonal prediction of South Asian monsoon rainfall using data-driven forecasts of oscillatory modes 

Eviatar Bach, Venkat Krishnamurthy, Jagadish Shukla, Safa Mote, A. Surjalal Sharma, Eugenia Kalnay, and Michael Ghil

Predicting the temporal and spatial patterns of South Asian monsoon rainfall within a season is of critical importance due to its impact on agriculture, water availability, and flooding. The monsoon intraseasonal oscillation (MISO) is a robust northward-propagating mode which determines the active and break phases of the monsoon, and much of the regional distribution of rainfall. However, dynamical atmospheric forecast models predict this mode poorly. Data-driven methods for MISO prediction have shown more skill, but only predict the rainfall portion corresponding to MISO.

Here, we combine state-of-the-art ensemble precipitation forecasts from a high-resolution atmospheric model with data-driven forecasts of MISO using a novel method. The ensemble members of the detailed atmospheric model are projected onto a lower-dimensional subspace corresponding to the MISO dynamics, and are then weighted according to their distance from the data-driven MISO forecast in this subspace. We thereby achieve significant improvements in rainfall forecasts over India, as well as the broader monsoon region, at 10–30 day lead times, an interval that is generally considered as a predictability gap. Our results demonstrate the potential of leveraging the predictability of intraseasonal oscillations to improve extended-range forecasts; more generally, they point towards a future of combining dynamical and data-driven forecasts for Earth system prediction.

How to cite: Bach, E., Krishnamurthy, V., Shukla, J., Mote, S., Sharma, A. S., Kalnay, E., and Ghil, M.: Improved subseasonal prediction of South Asian monsoon rainfall using data-driven forecasts of oscillatory modes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10243, https://doi.org/10.5194/egusphere-egu23-10243, 2023.

EGU23-11267 | ECS | Posters on site | AS1.3

Impact of flux type variable exchange method in the atmosphere-ocean coupled version of the Korean Integrated Model (KIM) system for extended medium-range weather forecast 

Namgu Yeo, Eun-Chul Chang, Hajoon Song, Junseong Park, Eunjeong Lee, and Myung-Seo Koo

Extended medium-range prediction targets a period of up to 30 days, which is a longer period than medium-range (up to 15 days) and shorter than seasonal (up to 3 months) forecast. The atmospheric response to the initial condition significantly impacts predictability in medium-range prediction while ocean response which is a slower change compared to the atmosphere is also an important factor in extended medium-range prediction. Thus, it is important to consider not only initial forcing but also air-sea interaction containing ocean response in extended medium-range prediction. The interactions in the earth system model can be considered among the atmosphere, ocean, sea-ice, and ocean wave by coupling of each components. The Korean Integrated Model (KIM) system, which is a global atmospheric forecast model, was developed by the Korea Institute of Atmospheric Prediction Systems. Recently, the ocean and sea-ice model components have been coupled with the KIM atmosphere system, and continuous efforts are being made to improve its performance. The air-sea interaction in an atmosphere-ocean coupled system can be considered by exchanging the variables that require interaction between components with a coupler. The bulk type exchange method basically transfers state variables such as temperature, pressure, and wind, which are used to get flux variables that contain interacting information among the atmosphere, ocean, and sea-ice. The bulk method is simple but the energy budget at the interface among the model components may become inconsistent due to the use of different formulas during calculation of the flux variables. In this study, exchange variables are changed by replacing atmospheric state variables with flux and momentum variables, which are the final form used in the ocean model. It is found that the corrected flux and momentum of the ocean surface resulting from the flux type exchange method change the ocean structure, particularly over the low latitude region. The atmosphere reacts to the changed ocean state, affecting not only the lower atmosphere but also the upper atmosphere. The results show that the flux type variable exchange method has advantages for considering air-sea interaction, which would improve the performance of extended medium-range weather forecast compared to the bulk type exchange method.

Keywords: extended medium-range forecast, coupled model, air-sea interaction, bulk type method

Acknowledgement

This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMI2022-01210.

 

 

How to cite: Yeo, N., Chang, E.-C., Song, H., Park, J., Lee, E., and Koo, M.-S.: Impact of flux type variable exchange method in the atmosphere-ocean coupled version of the Korean Integrated Model (KIM) system for extended medium-range weather forecast, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11267, https://doi.org/10.5194/egusphere-egu23-11267, 2023.

Rain-fed agriculture constitutes more than 95 % of cropland in Germany. It depends heavily on rainfall patterns and the water storage capacities of top soil layers. Intense summer droughts with long-lasting lack of precipitation leads to yield loss in wheat, corn and sugar beet production in the last years 2018, 2019, 2020 and 2022. Hence, these drought events increase the requirement of long-range forecasts for precipitation and soil moisture, which could provide useful predictions for agricultural applications.

Here a coupled modelling attempt is presented, that combines the extended-range ENS-forecasts from the European Centre for Medium-Range Weather Forecasts (ECWMF) with the soil-vegetation-atmosphere-transfer (SVAT) impact model AMBAV to simulate the top soil moisture for subseasonal forecasts on a downscaled 5x5 km grid in Germany. A quality assessment of forecast ensemble means from July 2022 to November 2022 has been done with the corresponding hindcasts for the preceding 20 years. The mean squared error skill score (MSESS) of weekly averages reveals a significant forecast skill up to 4-6 weeks for soil moisture in the upper 60 cm in comparison to an AMBAV analysis run based on gridded weather station data. In contrast, the precipitation forecast skill is much lower and achieve only adequate forecast skill with lead times up to two weeks. Due to the low variability and persistence of soil moisture values, it is proposed, that this storage variable is well suited for climate services like agricultural drought predicting systems on subseasonal time scales. It could offer guidance with sufficient reliability for medium-term management adjustments like irrigation planning or reduced fertilizer usage in case of expected severe drought periods. Overall, the results of this study show the potential of subseasonal soil moisture forecasts for agricultural applications. Further research is needed to verify these findings and to extend the forecast analysis period to the entire year. Then the impact modelling system might contribute to the adaptation of agriculture to climate change in Germany.

How to cite: Leppelt, T.: Quality assessment of subseasonal soil moisture forecasts for agricultural applications in Germany, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11833, https://doi.org/10.5194/egusphere-egu23-11833, 2023.

EGU23-12537 | ECS | Posters on site | AS1.3

A sub-seasonal to seasonal prediction system with MPI-ESM 

Vimal Koul, Sebastian Brune, Cristian Febre, Daniela I.V. Domeisen, and Johanna Baehr

Current sub-seasonal prediction systems are traditionally based on models developed for numerical weather prediction. We present a different approach wherein we develop a sub-seasonal prediction system using a coupled Earth system model, the Max-Planck-Institute Earth system model (MPI-ESM), developed primarily for the use in climate prediction. We present results from initialized sub-seasonal reforecasts for the time period 1993-2017 from a 1st generation (CMIP5) seasonal-turned-sub-seasonal prediction system based on MPI-ESM including different components of the Earth system: atmosphere, land surface, ocean, and marine ecosystems. With our system we find (1) that atmospheric variables can be predicted with a quality and prediction horizon similar to what is found within the range of current sub-seasonal to seasonal prediction systems, (2) that extreme events as diverse as heatwaves over land, storm severity over Europe, and sudden stratospheric warmings can be skilfully predicted one to a few weeks ahead, (3) that sea surface temperatures can be skilfully predicted in the majority of large marine ecosystems for several weeks ahead, and (4) that sea ice area in the majority of Arctic seas can be skillfully predicted several weeks ahead. Our findings indicate that a coupled Earth system model like MPI-ESM can already be seamlessly used for sub-seasonal to seasonal (to decadal) climate predictions of different domains of the Earth system. Ultimately these results ask for the seamless approach to be embedded into the development of future coupled Earth system models.

How to cite: Koul, V., Brune, S., Febre, C., Domeisen, D. I. V., and Baehr, J.: A sub-seasonal to seasonal prediction system with MPI-ESM, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12537, https://doi.org/10.5194/egusphere-egu23-12537, 2023.

EGU23-13445 | ECS | Orals | AS1.3

Optimal transport for the multi-model combination of sub-seasonal ensemble forecasts 

Camille Le Coz, Alexis Tantet, Rémi Flamary, and Riwal Plougonven

Combining ensemble forecasts from several models has been shown to improve the skill of S2S predictions. One of the most used method for such combination is the “pooled ensemble” method, i.e. the concatenation of the ensemble members from the different models. The members of the new multi-model ensemble can simply have the same weights or be given different weights based on the skills of the models. If one sees the ensemble forecasts as discrete probability distributions, then the “pooled ensemble” is their (weighted-)barycenter with respect to the L2 distance.
Here, we investigate whether a different metric when computing the barycenter may help improve the skill of S2S predictions. We consider in this work a second barycenter with respect to the Wasserstein distance. This distance is defined as the cost of the optimal transport between two distributions and has interesting properties in the distribution space, such as the possibility to preserve the temporal consistency of the ensemble members.
We compare the L2 and Wasserstein barycenters for the combination of two models from the S2S database, namely ECMWF and NCEP. Their performances are evaluated for the weekly 2m-temperature over seven winters in Europe (land) in terms of different scores. The weights of the models in the barycenters are estimated from the data using grid search with cross-validation. We show that the estimation of these weights is critical as it greatly impacts the score of the barycenters. Although the NCEP ensemble generally has poorer skills than the ECMWF one, the barycenter ensembles are able to improve on both single-model ensembles (although not for all scores). At the end, the best ensemble depends on the score and on the location. These results constitute a promising first step before implementing this methodology with more than two ensembles, and ensembles having less contrasting skills.

How to cite: Le Coz, C., Tantet, A., Flamary, R., and Plougonven, R.: Optimal transport for the multi-model combination of sub-seasonal ensemble forecasts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13445, https://doi.org/10.5194/egusphere-egu23-13445, 2023.

EGU23-14682 | ECS | Posters on site | AS1.3

Characteristics of Tropical cyclones in sub-seasonal forecasting with GloSea5: Predictability in extreme ENSO phases and a climate regime shift 

Taehyung Kim, Eunji Kim, Minkyu Lee, Dong-Hyun Cha, Sang-Min Lee, Johan Lee, and Kyung-On Boo

Tropical Cyclone (hereafter, TC), a most destructive weather phenomenon that causes enormous socio-economic damage, occurs around 25 times every year in the western North Pacific, of which Korea is directly or indirectly affected by about 3 to 4 TCs every year. Even if it is affected by a small number of TCs, the damage could be unimaginably large. To preemptively prepare and respond to TCs, predictability on the sub-seasonal to seasonal (S2S) time-scale, over two weeks to two months is being emphasized. In this study, the characteristics of TCs in sub-seasonal forecasting with the Global Seasonal Forecast System 5 (GloSea5) of the Korea Meteorological Administration (KMA) were assessed over the western North Pacific (WNP). The predictability of GloSea5 was examined for its ability to reproduce observed TC climatology as well as changes in TC genesis with the El Niño-Southern Oscillation (ENSO) and a 1998/1999 climate regime shift. GloSea5 showed skilful performance in simulating the frequency and genesis spatial distribution of TCs in climatology and both extreme ENSO phases. Synoptic fields related to TC genesis were also reasonably captured, despite some systematic biases in those. GloSea5 performed well in terms of characteristics of changes in TC genesis due to the climate regime shift. However, there were biases in TC frequency before the regime shift and in changes in TC-related environmental fields. This study implies that GloSea5, which has a good predictive skill for TC genesis over the WNP, can be used as an operational model for sub-seasonal TC forecasting, although it requires continuous improvements to reduce systematic errors

How to cite: Kim, T., Kim, E., Lee, M., Cha, D.-H., Lee, S.-M., Lee, J., and Boo, K.-O.: Characteristics of Tropical cyclones in sub-seasonal forecasting with GloSea5: Predictability in extreme ENSO phases and a climate regime shift, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14682, https://doi.org/10.5194/egusphere-egu23-14682, 2023.

EGU23-15043 | ECS | Orals | AS1.3

Investigating the Role of Weather Patterns in Crop Yield Variability and Predictability 

Chris Knight, Abdou Khouakhi, and Toby Waine

Climate change is causing disruptions in Earth's weather patterns, leading to an increase in the frequency and severity of extreme weather events such as droughts, floods, frost, and heatwaves. These events can impact food production and lead to challenges in meeting the food needs of a growing population. Previous research has documented the role of temperature and precipitation during the growing season in explaining crop yield variability. For example, droughts and extreme heat can reduce cereal production by 9-10%.

Current crop yield models use only a few meteorological variables to represent weather conditions. However, weather patterns or weather regimes, (i.e., persistent, and recurrent flow patterns of the large-scale atmospheric circulation) can provide a more comprehensive view of weather conditions, and can be used to predict and characterise extreme weather events and explain crop yield variation.

In this study, we first conducted a literature review to examine the links between extreme weather events, such as heat waves, and droughts with weather patterns and regimes. One of the main findings of that review was the need to define what extreme weather is in the context of agriculture. The new definition is based on studies that identified optimal and terminal weather conditions for winter wheat at specific phenological stages. Using this definition of extreme weather, we analyse historic yields in East Anglia, UK, forming statistically based relationships between low yield years with a set of classified weather patterns from the UK Met Office. We focused on the weather patterns frequency of occurrence and persistence with additional consideration given to potential microclimates as we compare the effects weather patterns have on a specific farm with a long-term data set to the effects of the larger region. Preliminary analyses shows that a small number of these weather patterns are associated with high impact weather events that cause yield limiting conditions or physical damage to the crop such as wind lodging.

It is hoped that further research will lead to the development of a next-generation crop yield variation model taking into account the weather patterns, which can provide longer-term predictions of regional crop yield variability to help agri-businesses, crop insurers and farmers to facilitate decision making, respond effectively to regional and global crop production shocks and food price spikes, and develop adaptation strategies to reduce the potential impact of extreme weather events.

How to cite: Knight, C., Khouakhi, A., and Waine, T.: Investigating the Role of Weather Patterns in Crop Yield Variability and Predictability, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15043, https://doi.org/10.5194/egusphere-egu23-15043, 2023.

EGU23-15077 | ECS | Posters on site | AS1.3

Subseasonal prediction of the July 2021 extreme rainfall event over Henan China in S2S forecasting systems 

Yuhan Yan, Congwen Zhu, and Boqi Liu

Unprecedented heavy rainfall reaches the warming Earth more frequently, creating the need for effective risk-warning alerts that utilize subseasonal-to-seasonal (S2S) forecasting to integrate information from nowcasting, weather, and seasonal predictions. A record-breaking flooding event occurred in Zhengzhou, Henan Province of China during 17–23 July 2021, causing 398 total of deaths and vast economic losses.

A number of studies have shown this super severe heavy flooding occurred under the background of multiscale circulation interactions and the impacts of remote tropical cyclones. Here, we evaluated the predictability of this extreme rainfall event and the impacts of tropical cyclones (TCs) using subseasonal-to-seasonal (S2S) operational models. Most S2S models can reasonably predict the wet-in-north and dry-in-south monthly rainfall pattern over China in July. Only four models captured the location, probability, and sudden intensification of the Zhengzhou rainfall extremes in advance of one week, largely due to their reasonable prediction of the variability of the western North Pacific subtropical high in mid-latitudes. Although the chance of exceeding the new record daily rainfall is only approx. 0.7% in mid-late July, they provide a high probability of this heavy weekly rainfall one week in advance. However, the S2S models still underestimated the super extremeness of this event. The prediction discrepancies came from the poor predictability of Typhoon IN-FA and its impact on the daily evolution of the extreme rainfall event, even within a few days forecast lead. Compared with the observation, the prediction bias of tropical disturbance changed the environmental monsoon airflow to induce the earlier warning of rainfall extremes prior to the formation of IN-FA. After the formation of IN-FA, the prediction bias of the typhoon’s moving speed distorted the typhoon location, which incorrectly predicted the moisture convergence center and underestimated their remote impacts on this heavy rainfall event. Future research should improve our awareness of the challenges that remain in the S2S forecasts.

How to cite: Yan, Y., Zhu, C., and Liu, B.: Subseasonal prediction of the July 2021 extreme rainfall event over Henan China in S2S forecasting systems, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15077, https://doi.org/10.5194/egusphere-egu23-15077, 2023.

EGU23-15594 | ECS | Posters virtual | AS1.3

Hunting for “Windows of Opportunity” in Forecasts Across Timescales? Cross it 

Ángel G. Muñoz, Francisco Doblas-Reyes, Laurel DiSera, Markus Donat, Nube González-Reviriego, Albert Soret, Marta Terrado, and Verónica Torralba

Stakeholders in all socio-economic sectors require reliable forecasts at multiple timescales as part of their decision-making processes. Although basing decisions mostly on a particular timescale (e.g., weather, subseasonal, seasonal) is the present status quo, this approach tends to lead to missing opportunities for more comprehensive risk-management systems (Goddard et al. 2014).

 

While today a variety of forecasts are produced targeting distinct timescales in a routine way, these products are generally presented to the users in different websites and bulletins, often without an assessment of how consistent the predictions are across timescales. Since different models and strategies are used at different timescales by both national and international seasonal and subseasonal forecasting centers (Kirtman et al. 2014, Kirtman et al. 2017, Vitart et al. 2017), and skill is different at those timescales, it is key to guarantee that a physically consistent “bridging” between the forecasts exists, and that the cross-timescale predictions are overall skilful and actionable, so decision makers can conduct their work.

 

Here, we propose and explore a new methodology –that we call the Xit (“cross-it”) operator– based on the Liang-Kleeman information flow (e.g., Tawia Hagan et al. 2019) and wavelet spectra and entropy (e.g., Zunino et al. 2007), to “bridge” forecasts at different timescales in a smooth and physically-consistent manner.

 

In summary, the Xit operator (1) conducts a wavelet spectral analysis (e.g., Ng and Chan 2013, Zunino et al. 2007) and (2) a non-stationary time-frequency causality analysis (e.g., Tawia Hagan et al. 2019, Liang 2015) on forecasts at different timescales to assess cross-timescale coherence and physical consistency in terms of various sources of predictability. In principle, the approach permits to identify which “intrinsic” periods/scales (i) in the timescale continuum (t) are more suitable for the bridging to occur, and/or which ones can produce more skillful forecasts, by pointing to particular target times—i.e., potential windows of opportunity (Mariotti et al. 2020)—in the forecast period where wavelet entropy (uncertainty) is lower.

 

While the first component of the Xit operator, i.e., the wavelet spectral and entropy analysis (Zunino et al. 2007), is designed to identify the optimal time-frequency bands for cross-timescale bridging, the fact that two forecast systems (e.g., a subseasonal and a seasonal) exhibit significant wavelet coherence does not imply that bridging those systems will provide physically-consistent predictions. The second component of the Xit operator, i.e., the non-stationary causality analysis (Tawia Hagan et al. 2019), is thus designed to assess physical consistency of the bridging by analyzing the causal link between different climate drivers (acting at different timescales) and the forecast variable of interest.

How to cite: Muñoz, Á. G., Doblas-Reyes, F., DiSera, L., Donat, M., González-Reviriego, N., Soret, A., Terrado, M., and Torralba, V.: Hunting for “Windows of Opportunity” in Forecasts Across Timescales? Cross it, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15594, https://doi.org/10.5194/egusphere-egu23-15594, 2023.

EGU23-16178 | ECS | Posters virtual | AS1.3

Subseasonal forecasting of temperature and precipitation over India using a machine learning approach 

Prajwal Jadhav, Sreejith Op, and Sabeerali Thelliyil

Subseasonal forecasting is forecasting of the weather parameters, mainly temperature and precipitation, two weeks to two months in advance. Sub-seasonal variability accounts for a substantial portion of the summer rainfall over India. Prediction of sub-seasonal climate is of immense societal importance in agriculture planning, water management, emergency planning, etc. Using various weather parameters and ECMWF dynamical model forecasts as predictors, this study tries to investigate the weekly forecast of temperature and precipitation at 2-week, 3-week, and 4-week forecast horizon over India using a computationally inexpensive machine learning model-MultiLLR, which prunes out irrelevant predictors and integrates remaining predictors linearly for each target date. The model’s predictions calculated over the years 2019-2022 are as skilful as IMD’s Extended Range Forecasting System (ERFS). The skill of the model is better in the coastal region than in the inland part of India.

How to cite: Jadhav, P., Op, S., and Thelliyil, S.: Subseasonal forecasting of temperature and precipitation over India using a machine learning approach, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16178, https://doi.org/10.5194/egusphere-egu23-16178, 2023.

EGU23-16412 | ECS | Posters on site | AS1.3

The 2020-2023 La Niña: Did Cross-timescale Interference Fuel this Multi-year Event? 

Laurel DiSera and Ángel G. Muñoz

Beginning July 2020, the Niño 3.4 index crossed below the threshold to La Niña conditions and remained below a -0.4 sea surface temperature anomaly through the spring of 2023, impacting agriculture, livelihoods, and communities around the world. What caused this prolonged La Niña event and why was it sustained? How did the interaction between the different modes of climate variability influence the event? The internal dynamics of ENSO, the Indian Ocean Dipole, and the Madden-Julian Oscillation are studied here through a non-linear approach utilizing compositing techniques and both linear and non-linear wave superposition to identify what caused and prolonged the 2020-2023 La Niña event.

How to cite: DiSera, L. and Muñoz, Á. G.: The 2020-2023 La Niña: Did Cross-timescale Interference Fuel this Multi-year Event?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16412, https://doi.org/10.5194/egusphere-egu23-16412, 2023.

EGU23-16731 | ECS | Posters on site | AS1.3

Projected Future Changes in Equatorial Wave Spectrum in CMIP6 

Hagar Bartana, Chaim Garfinkel, Ofer Shamir, and Jian Rao

Changes of tropical wave-modes due to climate change will impact the predictability of the tropical atmosphere, and may impact extratropical weather as well. The simulations of convectively coupled equatorial waves and the Madden-Julian Oscillation (MJO) are considered in 13 state-of-the-art models from phase 6 of the Coupled Model Intercomparison Project (CMIP6).  We look at the wave-modes using frequency-wavenumber power spectra of the models and observations for Outgoing Longwave Radiation and zonal winds at 250 hPa. We analyze the spectra of the historical simulations and end of 21st century projections for the SSP245 and SSP585 scenarios.  The models simulate a spectrum quantitatively resembling that observed, though systematic biases exist. Most models project a future increase in power spectra for the MJO, while nearly all project a robust increase for Kelvin waves (KW) and weaker power values for most other wavenumber-frequency combinations. Models with a more realistic MJO in their control climate tend to simulate a stronger future intensification. In addition to strengthening, KW also shift toward higher phase speeds. The net effect is a more organized tropical circulation on intraseasonal timescales, which may contribute to higher intrinsic predictability in the tropics and to stronger teleconnections in the extratropics. In addition, those projected changes might be due to extratropical forcings, and more specifically due to changes in the North Pacific subtropical jet.

How to cite: Bartana, H., Garfinkel, C., Shamir, O., and Rao, J.: Projected Future Changes in Equatorial Wave Spectrum in CMIP6, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16731, https://doi.org/10.5194/egusphere-egu23-16731, 2023.

EGU23-604 | ECS | Posters on site | CL4.3

Boreal Spring Southern Hemisphere Climate Mode and Global Monsoon 

Shikhar Srivastava, Arindam Chakraborty, and Raghu Murtugudde

The global climatic pattern is governed by the dominant mode of variability in the tropics and the extratropic and their interaction. The extratropical atmosphere is much more vigorous than the tropics owing to sharp meridional temperature gradients in the mid-latitude. Especially on the decadal timescales, large signals are seen over the extratropical region than in the tropics. Here, we propose that during boreal spring, the second leading mode of climate variability in the Southern Hemisphere, has a decadal pattern. This mode is independent of the Southern Annular Mode (SAM), which represents the most dominant mode of climate variability in the Southern Hemisphere. The boreal spring climate of the Southern Hemisphere interacts with the tropics and significantly impacts the global climate, which is reflected in the global Monsoon rainfall. During the positive phase of the decadal mode, the global Monsoon rainfall is coherently suppressed. We propose a new finding highlighting that the Southern Hemisphere's extratropical forcing can significantly impact the tropical Pacific through subtropical pathways on the decadal to multidecadal timescale. The impact of such decadal climate variability is enormous and global and can add a new paradigm to the pursuit of improving decadal predictions of the global climate.

How to cite: Srivastava, S., Chakraborty, A., and Murtugudde, R.: Boreal Spring Southern Hemisphere Climate Mode and Global Monsoon, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-604, https://doi.org/10.5194/egusphere-egu23-604, 2023.

As a dominant pattern of the North Pacific sea surface temperature decadal variability, the Pacific Decadal Oscillation (PDO) has remarkable influences on the marine and terrestrial ecosystems. However, the PDO is highly unpredictable. Here, we assess the performance of the Coupled Model Intercomparison Project Phase 6 (CMIP6) models in simulating the PDO, with an emphasis on the evaluation of CMIP6 models in reproducing a recently detected early warning signal based on climate network analysis for the PDO regime shift. Results show that the skill of CMIP6 historical simulations remains at a low level, with a skill limited in reproducing PDO’s spatial pattern and nearly no skill in reproducing the PDO index. However, if the warning signal for the PDO regime shift by climate network analysis is considered as a test-bed, we find that even in historical simulations, a few models can represent the corresponding relationship between the warning signal and the PDO regime shift, regardless of the chronological accuracy. By further conducting initialization, the performance of the model simulations is improved according to the evaluation of the hindcasts from two ensemble members of the Decadal Climate Prediction Project (NorCPM1 and BCC-CSM2-MR). Particularly, we find that the NorCPM1 model can capture the early warning signals for the late-1970s and late-1990s regime shifts 5–7 years in advance, indicating that the early warning sig- nal somewhat can be captured by some CMIP6 models. A further investigation on the underlying mechanisms of the early warning signal would be crucial for the improvement of model simulations in the North Pacific.

How to cite: Ma, Y.: On the Pacific Decadal Oscillation Simulations in CMIP6 Models: A New Test‐Bed from Climate Network Analysis, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5325, https://doi.org/10.5194/egusphere-egu23-5325, 2023.

Climate extremes can impact societies in various ways: from nuances in daily lives to full humanitarian crises. Droughts  are usually slow onset extremes but can be highly disruptive and affect millions of people every year. Warm temperature extremes (e.g. heat waves) can exacerbate droughts and their impacts and trigger a faster drought evolution. Combined drought and heat waves can lead to devastating consequences. For example, 2022 was a very active year in terms of drought or combined drought and heat waves, affecting particularly hard several regions of the world (e.g. Europe, China, southern South America and East Africa). In a context of risk management and civil protection, the use of operationally available seasonal climate forecasts can provide actionable information to reduce the risks and the impacts of these events on societies with different levels of development and adaptive capacities. 

 

Within the Copernicus Emergency Management Service (CEMS), the European and Global Drought Observatories (EDO and GDO, respectively) provide real time drought and temperature extreme monitoring products freely available and displayed through two dedicated web services. Recent efforts have been targeting the optimal integration and use of multi-system forecasting products to enhance the early warning component of the service. This contribution provides an overview of first results in terms of  initial multi-model skill assessment of forecasts available through the Copernicus Climate Change Service (C3S). It also discusses future avenues to improve skill in regions with limited predictability, for example by applying physically-based sampling techniques.    

How to cite: Acosta Navarro, J. C. and Toreti, A.: Seasonal forecasting of drought and temperature extremes as part of the Copernicus Emergency Management Service (CEMS), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5602, https://doi.org/10.5194/egusphere-egu23-5602, 2023.

EGU23-6000 | ECS | Orals | CL4.3

Seasonal forecasting of the European North West Shelf: Quantifying the persistence of the physical marine environment 

Jamie Atkins, Jonathan Tinker, Jennifer Graham, Adam Scaife, and Paul Halloran

The European North West shelf seas (NWS) support economic and environmental interests of several adjacent populous countries. Forecasts of physical marine variables on the NWS for upcoming months – an important decision-making timescale – would be useful for many industries. However, currently there is no operational seasonal forecasting product deemed sufficient for capturing the high variability associated with shallow, dynamic shelf waters. Here, we identify the dominant sources of seasonal predictability on the shelf and quantify the extent to which empirical persistence relationships can produce skilful seasonal forecasts of the NWS at the lowest level complexity. We find that relatively skilful forecasts of the typically well-mixed Winter and Spring seasons are achievable via persistence methods at a one-month lead time. In addition, incorporating observed climate modes of variability, such as the North Atlantic Oscillation (NAO), can significantly boost persistence for some locations and seasons, but this is dependent on the strength of the climate mode index. However, even where high persistence skill is demonstrated, there are sizeable regions exhibiting poor predictability and skilful persistence forecasts are typically limited to ≈ one-month lead times. Summer and Autumn forecasts are generally less skilful owing largely to the effects of seasonal stratification which emphasises the influence of atmospheric variability on sea surface conditions. As such, we also begin incorporating knowledge of future atmospheric conditions to forecasting strategies. We assess the ability of an existing global coupled ocean-atmosphere seasonal forecasting system to exceed persistence skill and highlight areas where additional downscaling efforts may be needed.

How to cite: Atkins, J., Tinker, J., Graham, J., Scaife, A., and Halloran, P.: Seasonal forecasting of the European North West Shelf: Quantifying the persistence of the physical marine environment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6000, https://doi.org/10.5194/egusphere-egu23-6000, 2023.

EGU23-7676 | Orals | CL4.3

Decadal Climate Variability and Predictability with a High-resolution Eddy-resolving Model 

Wei Zhang, Ben Kirtman, Leo Siqueira, and Amy Clement

Current global climate models typically fail to fully resolve mesoscale ocean features (with length scales on the order of 10 km), such as the western boundary currents, potentially limiting climate predictability over decadal timescales. This study incorporates high-resolution eddy-resolving ocean (HR: 0.1°) in a suite of CESM model experiments that capture these important mesoscale ocean features with increased fidelity. Compared with eddy-parametrized ocean (LR: 1°) experiments, HR experiments show more realistic climatology and variability of sea surface temperature (SST) over the western boundary currents and eddy-rich regions. In the North Atlantic, the inclusion of mesoscale ocean processes produces a more realistic Gulf Stream and improves both localized rainfall patterns and large-scale teleconnections. We identify enhanced decadal SST predictability in HR over the western North Atlantic, which can be explained by the strong vertical connectivity between SST and sub-surface ocean temperature. SST is better connected with slower processes deep down in HR, making SST more persistent (and predictable). Moreover, we detect a better representation of the air-sea interactions between SST and low-level atmosphere over the Gulf Stream, thus improving low-frequency rainfall variations and extremes over the Southeast US. The results further imply that high-resolution GCMs with increased ocean model resolution may be needed in future climate prediction systems.

How to cite: Zhang, W., Kirtman, B., Siqueira, L., and Clement, A.: Decadal Climate Variability and Predictability with a High-resolution Eddy-resolving Model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7676, https://doi.org/10.5194/egusphere-egu23-7676, 2023.

Earth system predictability on decadal timescales can arise from both low frequency internal variability as well as from anthropogenically forced long-term changes. However, on these timescales, the chaotic nature of the climate system makes skillful predictions difficult to achieve even if we include information from climate change projections. Furthermore, it is difficult to separate the contributions from internal variability and external forcing to predictability. One way to improve skill is through identifying and harnessing initial conditions with more predictable evolution, so-called state-dependent predictability. We explore a neural network approach to identify these opportunistic initial states in the CESM2 large ensemble and subsequently explore how predictability may manifest in a future climate, influenced by both forced warming and internal variability. We use an interpretable neural network to demonstrate that internal variability will continue to play an important role in future climate predictions, especially for states of increased predictability.

How to cite: Gordon, E. and Barnes, E.: An interpretable neural network approach to identifying sources of predictability in the future climate, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8000, https://doi.org/10.5194/egusphere-egu23-8000, 2023.

EGU23-8296 | ECS | Orals | CL4.3 | Highlight

Better late than never: arrival of decadal predictions to the climate services arena 

Balakrishnan Solaraju-Murali, Dragana Bojovic, Nube Gonzalez-Reviriego, Andria Nicodemou, Marta Terrado, Louis-Philippe Caron, and Francisco J. Doblas-Reyes

Decadal prediction represents a source of near-term climate information that has the potential to support climate-related decisions in key socio-economic sectors that are influenced by climate variability and change. While the research to illustrate the ability of decadal predictions in forecasting the varying climate conditions on a multi-annual timescale is rapidly evolving, the development of climate services based on such forecasts is still in its early stages. This study showcases the potential value of decadal predictions in the development of climate services. We summarize the lessons learnt from coproducing a forecast product that provides tailored and user-friendly information about multi-year drought conditions for the coming five years over global wheat harvesting regions. The interaction between the user and climate service provider that was established at an early stage and lasted throughout the forecast product development process proved fundamental to provide useful and ultimately actionable information to the stakeholders concerned with food production and security. This study also provides insights on the potential reasons behind the delayed entry of decadal predictions in the climate services discourse and practice, which were obtained from surveying climate scientists and discussing with decadal prediction experts.

How to cite: Solaraju-Murali, B., Bojovic, D., Gonzalez-Reviriego, N., Nicodemou, A., Terrado, M., Caron, L.-P., and Doblas-Reyes, F. J.: Better late than never: arrival of decadal predictions to the climate services arena, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8296, https://doi.org/10.5194/egusphere-egu23-8296, 2023.

EGU23-8750 | Orals | CL4.3

A simple coupled assimilation approach for improved initialization of decadal climate predictions 

Tim Kruschke, Mehdi Pasha Karami, David Docquier, Frederik Schenk, Ramon Fuentes Franco, Ulrika Willén, Shiyu Wang, Klaus Wyser, Uwe Fladrich, and Torben Koenigk

We introduce a simple data assimilation approach applied to the coupled global climate model EC-Earth3.3.1, aiming at producing initial conditions for decadal climate hindcasts and forecasts. We rely on a small selection of assimilated variables, which are available in a consistent manner for a long period, providing good spatial coverage for large parts of the globe, that is sea-surface temperatures (SST) and near-surface winds.

Given that these variables play a role directly at or very close to the ocean-atmosphere interface, we assume a comparably strong cross-component impact of the data assimilation. Starting from five different free-running CMIP6-historical simulations in 1900, we first apply surface restoring in the model’s ocean component towards monthly means of HadISST1. After integrating this five-member ensemble with only assimilating SST for the period 1900-1949, we start additionally assimilating (nudging) 6-hourly near-surface winds (vorticity and divergence) taken from the ERA5 reanalysis from 1950 onwards. To mitigate the risk of model drifts after initializing the decadal predictions and to account for known instationary biases of the model, we assimilate anomalies of all variables that are calculated based on a 30-year running mean.

By assimilating near-surface data over several decades before entering the actual period targeted by the decadal hindcasts/forecasts for CMIP6-DCPP, we expect the coupled model to be able to ingest a significant share of observed climate evolution also in deeper ocean layers. This would then potentially serve as a source of predictive skill on interannual-to-decadal timescales.

We show that the presented assimilation approach is able to force the coupled model’s evolution well in phase with observed climate variability, positively affecting not only near-surface levels of the atmosphere and ocean but also deeper layers of the ocean and higher levels of the atmosphere as well as Arctic sea-ice variability. However, we also present certain problematic features of our approach. Two examples are significantly strengthened low-frequency variability of the AMOC and a wind bias resulting into generally reduced evaporation over ocean areas.

How to cite: Kruschke, T., Karami, M. P., Docquier, D., Schenk, F., Fuentes Franco, R., Willén, U., Wang, S., Wyser, K., Fladrich, U., and Koenigk, T.: A simple coupled assimilation approach for improved initialization of decadal climate predictions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8750, https://doi.org/10.5194/egusphere-egu23-8750, 2023.

The interdisciplinary research project "BayTreeNet" examines the reactions of forest ecosystems to climate dynamics. To establish a relationship between tree growth and climate, it is important to know that in the mid-latitudes, local climate phenomena often show a strong dependence on the large-scale climate weather types (WT), which significantly determine the climate of a region through frequency and intensity. Different WT show various weather conditions at different locations, especially in the topographically diverse region of Bavaria. The meaning of every WT is the physical basis for the climate-growth relationships established in the dendroecology sub-project to investigate the response of forests to individual WT at different forest sites. Complementary steps allow interpretation of results for the past (20th century) and projection into the future (21st century). One hypothesis is that forest sites in Bavaria are affected by a significant influence of climate change in the 21st century and the associated change in WT.

The automated classification of large-scale weather patterns is presented by Self-Organizing-Maps (SOM) developed by Kohonen, which enables visualization and reduction of high-dimensional data. The poster presents the SOM-setting which was used to classify the WT and the results of past environmental conditions (1990-2019) for different WT in Europe based on ERA5 data. Morover, it shows a future projection until 2100 for European WT and their respective environmental conditions. The projections are based on a novel GCM selection technique for two scenarios (ssp1-2.6 and ssp5-8.5) to obtain a range of the most likely conditions.

How to cite: Wehrmann, S. and Mölg, T.: GCM-based future projections of European weather types obtained by Self‑Organizing-Maps and a novel GCM selection technique, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8934, https://doi.org/10.5194/egusphere-egu23-8934, 2023.

EGU23-9520 | Orals | CL4.3

Estimating the significance of the added skill from initializations: The case of decadal predictions 

Bo Christiansen, Shuting Yang, and Dominic Matte

A considerable part of the skill in decadal forecasts often come from the forcings which are present in both initialized and un-initialized model experiments. This makes the added value from initialization difficult to assess. We investigate statistical tests to quantify if initialized forecasts provide skill over the un-initialized experiments. We consider three correlation based statistics previous used in the literature. The distributions of these statistics under the null-hypothesis that initialization has no added values are calculated by a surrogate data method. We present some simple examples and study the statistical power of the tests. We find that there can be large differences in both the values and the power for the different statistics. In general the simple statistic defined as the difference between the skill of the initialized and uninitialized experiments behaves best. However, for all statistics the risk of rejecting the true null-hypothesis is too high compared to the nominal value.

We compare the three tests on initialized decadal predictions (hindcasts) of near-surface temperature performed with a climate model and find evidence for a significant effect of initializations for small lead-times. In contrast, we find only little evidence for a significant effect of initializations for lead-times larger than 3 years when the experience from the simple experiments is included in the estimation.

How to cite: Christiansen, B., Yang, S., and Matte, D.: Estimating the significance of the added skill from initializations: The case of decadal predictions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9520, https://doi.org/10.5194/egusphere-egu23-9520, 2023.

EGU23-9986 | Posters on site | CL4.3

Probabilistic nonlinear lagged teleconnections of the sea surface temperature field 

Carlos Pires and Abdel Hannachi

The monthly anomaly sea surface temperature field over the global ocean exhibit probabilistic dependencies between remote points and lagged times, which are explained eventually by some oceanic or atmospheric bridge of information transfer. Despite much of the bivariate SST dependencies appear to be linear, others are characterized by robust and statistically significant nonlinear correlations. In order to enhance that, we present a general method of extracting bivariate (X,Y) dependencies, seeking for pairs of polynomials P(X) and Q(Y) which are maximally correlated. The method relies on a Canonical correlation Analysis (CCA) between sets of standardized monomials of X and Y, up to a certain (low) degree (e.g. 4). Polynomial coefficients are obtained from the leading CCA eigenvector. Polynomials are calibrated and validated over independent periods, being afterwards subjected to marginal Gaussian anamorphoses. The bivariate non-Gaussianity in the space of marginally Gaussianized polynomials remains residual because of the correlation concentration and maximization. Consequently, the bivariate Gaussian pdf or in alternative, a copula pdf in the space of maximally correlated polynomials can accurately approximate the bivariate dependency. That probabilistic model is then used to determine conditional pdfs, cdfs and probabilities of extremes.

The method is applied to various (X,Y) pairs. In the first example, X is an optimized polynomial of the El-Niño 3.4 index while Y is that index lagged to the future. For lags between 6 and 18 months, the nonlinear El-Niño forecast clearly surpasses the linear one, contributing to lower the El-Niño seasonal predictability barrier. In the second example, we relate El-Niño (X) with the lagged Atlantic multidecadal oscillation index (Y). Nonlinear, robust correlations appear, both for positive and negative lags up to 5 years putting in evidence Pacific-Atlantic basin oceanic teleconnections.

The above probabilistic (polynomial based) model appears to be a good candidate tool for the statistical (seasonal up to decadal) forecast of regime probabilities (e.g. dry/wet) and extremes, given certain antecedent precursors.

This work was funded by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020- IDL and the project JPIOCEANS/0001/2019 (ROADMAP: ’The Role of ocean dynamics and Ocean–Atmosphere interactions in Driving cliMAte variations and future Projections of impact–relevant extreme events’). Acknowledgements are also due to the International Meteorological Institute (IMI) at Stockholm University.

How to cite: Pires, C. and Hannachi, A.: Probabilistic nonlinear lagged teleconnections of the sea surface temperature field, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9986, https://doi.org/10.5194/egusphere-egu23-9986, 2023.

EGU23-13375 | ECS | Orals | CL4.3

Role of the subpolar North Atlantic region in skillful climate predictions for high northern latitudes: A pacemaker experiment 

Annika Drews, Torben Schmith, Shuting Yang, Steffen Olsen, Tian Tian, Marion Devilliers, Yiguo Wang, and Noel Keenlyside
Recent studies have suggested that the Atlantic water pathway connecting the subpolar North Atlantic (SPNA) with the Nordic Seas and Arctic Ocean may lead to skillful predictions of sea surface temperature and salinity anomalies in the eastern Nordic Seas. To investigate the role of the SPNA for such anomalies downstream, we designed a pacemaker experiment, using two decadal climate prediction systems based on EC-Earth3 and NorCPM. We focus on the subpolar extreme cold anomaly in 2015 and its subsequent development, a feature not well captured and predicted. The pacemaker experiment follows the protocol of the CMIP6 DCPP-A retrospective forecasts or hindcasts initialized November 1, 2014, but the models are forced to follow the observed ocean temperature and salinity anomalies in the SPNA from ocean reanalysis from November 2014 through to December 2019. Two sets of 10-year hindcasts are performed with 10 members for EC-Earth3 and 30 members for NorCPM. We here detail and discuss the design of this pacemaker experiment and present results, comparing with the initialized CMIP6 DCPP-A experiment assessing differences in decadal prediction skill outside the SPNA. We conclude that the pacemaker experiments show improved skill compared to the standard decadal predictions for the eastern Norwegian Sea, and therefore the SPNA is key for successful decadal predictions in the region.

How to cite: Drews, A., Schmith, T., Yang, S., Olsen, S., Tian, T., Devilliers, M., Wang, Y., and Keenlyside, N.: Role of the subpolar North Atlantic region in skillful climate predictions for high northern latitudes: A pacemaker experiment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13375, https://doi.org/10.5194/egusphere-egu23-13375, 2023.

EGU23-13639 | Orals | CL4.3

Seasonal prediction of UK mean and extreme winds 

Julia Lockwood, Nicky Stringer, Katie Hodge, Philip Bett, Jeff Knight, Doug Smith, Adam Scaife, Matthew Patterson, Nick Dunstone, and Hazel Thornton

For several years the Met Office has produced a seasonal outlook for the UK every month, which is issued to the UK Government and contingency planners.  The outlook gives predictions of the probability of having average, low, or high seasonal mean UK temperature and precipitation for the coming three-months.  In recent years, there has been increasing demand from sectors such as energy and insurance to include similar probabilistic predictions of UK wind speed: both for the seasonal mean and for measures of extreme winds such as storm numbers.  In this presentation we show the skill of the Met Office’s GloSea system in predicting seasonal (three-month average) UK mean wind and a measure of UK storminess throughout the year, and discuss the drivers of predictability.  Skill in predicting the UK mean wind speed and storminess peaks in winter (December–February), owing to predictability of the North Atlantic oscillation.  In summer (June–August), there is evidence that a significant proportion of variability in UK winds is driven by a Rossby wave train which the model has little skill in predicting. Nevertheless there are signs that the wave is potentially predictable and skill may be improved by reducing model errors.

How to cite: Lockwood, J., Stringer, N., Hodge, K., Bett, P., Knight, J., Smith, D., Scaife, A., Patterson, M., Dunstone, N., and Thornton, H.: Seasonal prediction of UK mean and extreme winds, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13639, https://doi.org/10.5194/egusphere-egu23-13639, 2023.

EGU23-13736 | ECS | Posters on site | CL4.3

Decadal predictability of European temperature extremes. 

Eirini Tsartsali, Panos Athanasiadis, Stefano Tibaldi, and Silvio Gualdi

Accurate predictions of climate variations at the decadal timescale are of great interest for decision-making, planning and adaptation strategies for different socio-economic sectors. Notably, decadal predictions have rapidly evolved during the last 15 years and are now produced operationally worldwide. The majority of the studies assessing the skill of decadal prediction systems focus on time-mean anomalies of standard meteorological variables, such as annual mean near-surface air temperature and precipitation. However, the predictability of extreme events frequency may differ substantially from the predictability of multi-year annual or seasonal means. Predicting the frequency of extreme events at different timescales is of major importance, since they are associated with severe impacts on various natural and human systems. In the current study we evaluate the capability of state-of-the-art decadal prediction systems to predict the frequency of temperature extremes in Europe. More specifically, we assess the skill of a multi-model ensemble from the Decadal Climate Prediction Project (DCPP, 163 ensemble members from 12 models in total) to forecast the number of days belonging to heatwaves episodes during summer (June–August). We find statistically significant predictive skill over Europe, except for the United Kingdom and a large part of the Scandinavian Peninsula, most of which is associated with the long-term warming trend. We are progressing with the evaluation of other statistical aspects of extreme events, including warm and cold episodes during winter, and we are also investigating whether there is predictive skill beyond that stemming from the external forcing.  

How to cite: Tsartsali, E., Athanasiadis, P., Tibaldi, S., and Gualdi, S.: Decadal predictability of European temperature extremes., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13736, https://doi.org/10.5194/egusphere-egu23-13736, 2023.

EGU23-13789 | Posters on site | CL4.3

Do oceanic observations (still) matter in initializing decadal climate predictions over the North Atlantic ocean? 

Sebastian Brune, Vimal Koul, and Johanna Baehr

Earth system models are now regularly being used in inter-annual to decadal climate prediction. Such prediction systems based on CMIP5-generation Earth system models had demonstrated an overall positive impact of initialization, i.e. deriving initial conditions of retrospective forecasts from a separate data assimilation experiment, on decadal prediction skill. This view is now being increasingly challenged in the context of improvements both in CMIP6-generation Earth system models and CMIP6-evaluation of external forcing as well as in the context of ongoing transient climate change. In this study we re-evaluate the impact of atmospheric and oceanic initialization on decadal prediction skill of North Atlantic upper ocean heat content (0-700m) in a CMIP6-generation decadal prediction system based on the Max Planck Institute Earth system model (MPI-ESM). We compare the impact of initial conditions derived through full-field atmospheric nudging with those derived through an additional assimilation of observed oceanic temperature and salinity profiles using an ensemble Kalman filter. Our experiments suggest that assimilation of observed oceanic temperature and salinity profiles into the model reduces the warm bias in the subpolar North Atlantic heat content, and improves the modelled variability of the Atlantic meridional overturning circulation and ocean heat transport. These improvements enable a proper initialization of model variables which leads to an improved decadal prediction of surface temperatures. Our results reveal an important role of subsurface oceanic observations in decadal prediction of surface temperatures in the subpolar North Atlantic even in CMIP6-generation decadal prediction system.

How to cite: Brune, S., Koul, V., and Baehr, J.: Do oceanic observations (still) matter in initializing decadal climate predictions over the North Atlantic ocean?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13789, https://doi.org/10.5194/egusphere-egu23-13789, 2023.

EGU23-14755 | ECS | Posters on site | CL4.3

A low-dimensional dynamical systems approach to climate ensemble design and interpretation 

Francisco de Melo Viríssimo and David Stainforth

Earth System Models (ESMs) are complex, highly nonlinear, multi-component systems described by large number of differential equations. They are used to study the evolution of climate and its dynamics, and to make projection of future climate at both regional and global levels – which underpins climate change impact assessments such as the IPCC report. These projections are subject to several sorts of uncertainty due to high internal variability in the system dynamics, which are usually quantified via ensembles of simulations.

Due to their multi component nature of such ESMs, the emerging dynamics also contain different temporal scales, meaning that climate ensembles come in a variety of shapes and sizes. However, our ability to run such ensembles is usually constrained by the computational resources available, as they are very expensive to run. Hence, choices on the ensemble design must be made, which conciliate the computational capability with the sort of information one is looking for.

One alternative to gain information is to use low-dimensional climate-like systems, which consists of simplified, coupled versions of atmosphere, ocean, and other components, and hence capture some of the different time scales present in ESMs. This approach allows one to run very large ensembles, and hence to explore all sorts of model uncertainty with only modest computational usage.

In this talk, we discuss this approach in detail, and illustrate its applicability with a few results. Particular attention will be given to the issues of micro and macro initial condition uncertainty, and parametric uncertainty – including external, anthropogenic-like forcing. The ability of large ensembles to constrain decadal to centennial projections will be also explored.

How to cite: de Melo Viríssimo, F. and Stainforth, D.: A low-dimensional dynamical systems approach to climate ensemble design and interpretation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14755, https://doi.org/10.5194/egusphere-egu23-14755, 2023.

EGU23-15829 | ECS | Posters on site | CL4.3

Near term climate change in Emilia-Romagna (Italy) using CMIP6 decadal climate predictions 

Valeria Todaro, Marco D'Oria, Daniele Secci, Andrea Zanini, and Maria Giovanna Tanda

Ongoing climate change makes both short- and long-term adaptation and mitigation strategies urgently needed. While many long-term climate models have been developed and investigated in recent years, little attention has been paid to short-term simulations. The first attempts to perform multi-model initialized decadal forecasts were presented in the fifth Coupled Model Intercomparison Project 5 (CMIP5). Near-term climate prediction models are new socially relevant tools to support the decision makers delivering climate adaptation solutions on an annual or decadal scale. Recent improvements in decadal models were coordinated in CMIP6 and the World Climate Research Program (WCRP) Grand Challenge on Near Term Climate Prediction, as part of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (AR6, IPCC). The Decadal Climate Prediction Project (DCPP) provides decadal climate forecasts based on advanced techniques for the reanalysis of climate data, initialization methods, ensemble generation and data analysis. The initialization allows to consider the predictability of the internal climate variability reducing the prediction errors compared to those of the long-term projections, whose simulations do not take into account the phasing between the internal variability of the model and the observations. The aim of this work is to assess the near-future climate change in the Emilia-Romagna region in northern Italy until 2031. The hydrological variables analyzed are the daily precipitation and maximum and minimum temperature. An ensemble of models, with the highest resolution available, is used to handle the uncertainty in the predictions. Initially, to assess the reliability of the selected climate models, the hindcast data of the DCPP are checked against observations. Then, the DCPP predictions are used to investigate the variability of precipitation and temperature in the near future over the investigated area. Some climate features that are referenced to have an important impact on human health and activities are evaluated, such as drought indices and heat waves.

How to cite: Todaro, V., D'Oria, M., Secci, D., Zanini, A., and Tanda, M. G.: Near term climate change in Emilia-Romagna (Italy) using CMIP6 decadal climate predictions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15829, https://doi.org/10.5194/egusphere-egu23-15829, 2023.

EGU23-16034 | ECS | Posters on site | CL4.3

Seasonal forecast of the Sudden Stratospheric Warming occurrence 

Mikhail Vokhmyanin, Timo Asikainen, Antti Salminen, and Kalevi Mursula

The polar vortex in the wintertime Northern Hemisphere can sometimes experience a dramatic breakdown after an associated warming of the stratosphere during so-called Sudden Stratospheric Warmings (SSWs). These events are known to influence the ground weather in Northern Eurasia and large parts of North America. SSWs are primarily generated by enhanced planetary waves propagating from the troposphere to the stratosphere where they decelerate the vortex and lead to its breakdown. According to the Holton-Tan mechanism, the easterly direction of equatorial stratospheric QBO (Quasi-Biennial Oscillation) winds weakens the northern polar vortex by guiding more waves poleward. Recently, we found that during easterly QBO the occurrence rate of SSWs is modulated by the geomagnetic activity. We used the aa-index which is a good proxy for the energetic electron precipitations (EEP) responsible for the indirect effect on ozone. Our model shows that the breaking of the polar vortex is very likely to occur if the geomagnetic activity is weak. On the other hand, during westerly QBO, solar irradiance modulates the SSW occurrence: more SSWs happen under high solar activity.

How to cite: Vokhmyanin, M., Asikainen, T., Salminen, A., and Mursula, K.: Seasonal forecast of the Sudden Stratospheric Warming occurrence, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16034, https://doi.org/10.5194/egusphere-egu23-16034, 2023.

The state-of-the-art climate models suffer from significant sea surface temperature (SST) biases in the tropical Indian Ocean (TIO), greatly damaging the climate prediction and projection. In this study, we investigate the multidecadal atmospheric bias teleconnections caused by the TIO SST biases and their impacts on the simulated atmospheric variability. A set of century long simulations forced with idealized SST perturbations, resembling various persistent TIO SST biases in coupled climate models, are conducted with an intermediate complexity climate model. Bias analysis is performed using the normal-mode function decomposition which can differentiate between balanced and unbalanced flow regimes across spatial scales. The results show that the long-term atmospheric circulation biases caused by the TIO SST biases have the Matsuno-Gill-type pattern in the tropics and Rossby wavetrain distribution in the extratropics, similar to the steady state response to tropical heating. The teleconnection between the tropical and extratropical biases is set up by the Rossby wavetrain emanating from the subtropics. Over 90% of the total bias energy is stored in the zonal modes k≤6, and the Kelvin modes take 50-65% of the total unbalanced bias energy. The spatial and temporal variabilities have different responses to positive SST biases. In the unbalanced regime, variability changes are confined in the tropics, but the spatial variability increases whereas the temporal variability decreases. In the balanced regime, the spatial variability generally increases in the tropics and decreases in the extratropics, whereas the temporal variability decreases globally. Variability responses in the tropics are confined in the Indo-west Pacific region, and those in the extratropics are strong in the Pacific-North America region and the Europe. In the experiment with only negative SST biases, spatial and temporal variabilities increase in both regimes. In addition, the comparison between experiments indicates that the responses of the circulation and its variability are not sensitive to the structure and location of the TIO SST biases.

How to cite: Zhao, Y.-B., Žagar, N., Lunkeit, F., and Blender, R.: Long-term atmospheric bias teleconnection and the associated spatio-temporal variability originating from the tropical Indian Ocean sea surface temperature errors, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16899, https://doi.org/10.5194/egusphere-egu23-16899, 2023.

EGU23-946 | ECS | Orals | NP5.1

Combining Bayesian Neural Networks with explainable AI techniques for trustworthy probabilistic post-processing 

Mariana Clare, Zied Ben Bouallegue, Matthew Chantry, Martin Leutbecher, and Thomas Haiden

The large data volumes available in weather forecasting make post-processing an attractive field for applying machine learning. In turn, novel statistical machine learning methods that can be used to generate uncertainty information from a deterministic forecast are of great interest to forecast users, especially given the computational cost of running high resolution ensembles. In this work, we show how one such method, a Bayesian Neural Network (BNN), can be used to post-process a single global high resolution forecast for 2m temperature. This methodology improves both the accuracy of the forecast and adds uncertainty information, by predicting the distribution of the forecast error relative to its own analysis.

Here we assess both model and data uncertainty using two different BNN approaches. In the first approach, the BNN’s parameters are defined to be distributions rather than deterministic parameters, thereby generating an ensemble of models that can be used to quantify model uncertainty. In the second approach, the BNN remains deterministic but predicts a distribution rather than a deterministic output thereby quantifying data uncertainty. Our BNN results are benchmarked against simpler statistical methods, as well as statistics from the ECMWF operational ensemble.

Finally, in order to add trustworthiness to the BNN predictions, we apply an explainable AI technique (Layerwise Relevance Propagation) so as to understand whether the variables on which the BNN bases its prediction are physically reasonable or whether it is instead learning spurious correlations.

How to cite: Clare, M., Ben Bouallegue, Z., Chantry, M., Leutbecher, M., and Haiden, T.: Combining Bayesian Neural Networks with explainable AI techniques for trustworthy probabilistic post-processing, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-946, https://doi.org/10.5194/egusphere-egu23-946, 2023.

EGU23-1365 | Posters virtual | NP5.1

Improving post-processing of East African precipitation forecasts using a generative machine learning model 

Bobby Antonio, Andrew McRae, Dave MacLeod, Fenwick Cooper, John Marsham, Laurence Aitchison, Tim Palmer, and Peter Watson

Existing weather models are known to have poor skill over Africa, where there are regular threats of drought and floods that present significant risks to people's lives and livelihoods. Improved precipitation forecasts could help mitigate the negative effects of these extreme weather events, as well as providing significant financial benefits to the region. Building on work that successfully applied a state-of-the-art machine learning method (a conditional Generative Adversarial Network, cGAN) to postprocess precipitation forecasts in the UK, we present a novel way to improve precipitation forecasts in East Africa. We address the challenge of realistically representing tropical convective rainfall in this region, which is poorly simulated in conventional forecast models. We use a cGAN to postprocess ECMWF high resolution forecasts at 0.1 degree resolution and 6-18h lead times, using the iMERG dataset as ground truth, and investigate how well this model can correct bias, produce reliable probability distributions and create samples of rainfall with realistic spatial structure. We will also present performance in extreme rainfall events. This has the potential to enable cost effective improvements to early warning systems in the affected areas.

How to cite: Antonio, B., McRae, A., MacLeod, D., Cooper, F., Marsham, J., Aitchison, L., Palmer, T., and Watson, P.: Improving post-processing of East African precipitation forecasts using a generative machine learning model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1365, https://doi.org/10.5194/egusphere-egu23-1365, 2023.

EGU23-2592 | ECS | Orals | NP5.1

U-Net based Methods for the Postprocessing of Precipitation Ensemble Forecasting 

Romain Pic, Clément Dombry, Maxime Taillardat, and Philippe Naveau

Most Numerical Weather Prediction (NWP) systems use statistical postprocessing methods to correct for bias and underdispersion errors made by ensemble forecasting. This underdispersion leads to an underestimation of extreme events. Thus, many statistical postprocessing methods have been used to take into consideration the extremal behavior of meteorological phenomena such as precipitation. State-of-the-art techniques are based on Machine Learning combined with knowledge from Extreme Value Theory in order to improve forecasts. However, some of the best techniques do not consider the spatial dependency between locations. For example, Taillardat et al. (2019) trains a different Quantile Regression Forest at each location of interest and Rasp & Lerch (2018) uses neural networks with an embedding for the station's information in order to train a global model.
The dataset used corresponds to 3-h precipitation amounts produced by the radar-based observations of ANTILOPE and the 17-members ensemble forecast system called PEAROME. The dataset spans over the south of France with a grid resolution of 0.025 degrees. Our method uses a U-Net-like neural network in order to take into account the spatial structure of the data and the output of our model is a parameterized law at each grid point. Among the choices available in the literature, we focused on the Extended Generalized Pareto Distribution  and the truncated logistic with a point mass in 0. The model is trained by minimizing the scoring rules such as the Continuous Ranked Probability Score, the Log-Score or weighted versions of the aforementioned scoring rules. The method developed here is then compared to the raw ensemble as well as state-of-the-art techniques through scoring rules, skill scores and ROC curves.

References :

  • L. Pacchiardi, R. Adewoyin, P. Dueben, and R. Dutta. Probabilistic forecasting with generative networks via scoring rule minimization. Dec. 2021. arXiv:2112.08217
  • M. Taillardat, A.-L. Fougères, P. Naveau, and O. Mestre. Forest-based and semiparametric methods for the postprocessing of rainfall ensemble forecasting. Weather and Forecasting, 34(3):617–634, jun 2019. doi: 10.1175/waf-d-18-0149.1.

How to cite: Pic, R., Dombry, C., Taillardat, M., and Naveau, P.: U-Net based Methods for the Postprocessing of Precipitation Ensemble Forecasting, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2592, https://doi.org/10.5194/egusphere-egu23-2592, 2023.

EGU23-2628 | ECS | Posters on site | NP5.1

Seasonal Weather Forecast Biases Dependence on Static and Dynamic Environmental Variables in the Alpine Region 

Sameer Balaji Uttarwar, Anna Napoli, Diego Avesani, and Bruno Majone

Global seasonal weather forecasts have inherent biases compared to observational datasets over mountainous regions. This can be attributed to the model's inaccurate representation of local and global environmental processes on the Earth. In this context, the objective of this study is to assess the variation of seasonal weather forecast biases with respect to static and dynamic environmental variables over the Trentino-South Tyrol region (north-eastern Italian Alps), characterized by complex terrain.

The research employs the latest fifth-generation seasonal weather forecast system (SEAS5) dataset produced by the European Center for Medium-Range Weather Forecast (ECMWF), available at a horizontal grid resolution of 0.125° x 0.125° with 25 ensemble members in a re-forecast period from 1981 to 2016. The reference dataset is a high-resolution gridded observation (250 m x 250 m) over the region of interest. The spatiotemporal variation of monthly weather (i.e., precipitation and temperature) forecast biases over the region is inferred using several statistical indicators at observational dataset grid resolution. The static and dynamic environmental variables (i.e., respectively, terrain characteristics and large-scale atmospheric circulation indices) are used univariately to interpret their relationship with monthly weather forecast biases using the linear regression technique. A statistically significant linear relation between monthly weather forecast biases and terrain characteristics, as well as large-scale atmospheric circulation indices, has been found depending on seasonality and ensemble members.

Given significant univariate linear correlation, a simple linear bias reduction model is developed and assessed by implementing a random subsampling technique in which the regression parameters are simulated by splitting the data into calibration (70%) and validation (30%). The results reveal a reduction in the monthly weather forecast bias over the region.

This study demonstrates that the local and global environmental variables should be explicitly considered in the bias correction and downscaling of the seasonal weather forecasts over complex terrain.

How to cite: Uttarwar, S. B., Napoli, A., Avesani, D., and Majone, B.: Seasonal Weather Forecast Biases Dependence on Static and Dynamic Environmental Variables in the Alpine Region, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2628, https://doi.org/10.5194/egusphere-egu23-2628, 2023.

This work investigates several statistical tests in the context of probabilistic weather forecasting and ensemble postprocessing. The tests are commonly used for comparing predictive performance of e.g. two statistical postprocessing models.  

In the first part of the analysis a case study is conducted on temperature data consisting of observations and ensemble forecasts. The tests are applied to compare the performance of two probabilistic temperature forecasts at different stations, for different lead times, investigating several standard verification metrics to measure prediction performance. The analysis shows that the tests generally behave consistently in the context of temperature forecasts. However, for certain scenarios some tests might be be preferred over the others. In general, the combination of the original Diebold-Mariano test with the continuous ranked probability score (CRPS) to assess forecast accuracy leads to the most consistent and reliable results.

The second part of the analysis uses simulated data to investigate the general behaviour of the tests in different postprocessing scenarios as well as their size and power properties. Again, the original Diebold-Mariano test appears to perform most reliably and shows no noticeable inconsistent behaviour for different simulation settings.

How to cite: Möller, A. and Grupe, F.: Investigating properties of statistical tests for comparing predictive performance with application to probabilistic weather forecasting, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2701, https://doi.org/10.5194/egusphere-egu23-2701, 2023.

EGU23-2902 | ECS | Posters virtual | NP5.1

D-Vine Copula based Postprocessing of Wind Speed Ensemble Forecasts 

David Jobst, Annette Möller, and Jürgen Groß

Statistical postprocessing of ensemble forecasts has become a common practice in research to correct biases and errors in calibration. Meanwhile, machine learning methods such as quantile regression forests or neural networks are often suggested as promising candidates in literature. However, interpretation of these methods is not always straightforward. 
Therefore, we propose the D-vine (drawable-vine) copula based postprocessing, where for the construction of a multivariate conditional copula the graphical D-vine model serves as building plan. The conditional copula is based on this tracetable model using bivariate copulas, which allow to describe linear as well as non-linear relationships between the response variable and its covariates. Additionally, our highly data-driven model selects the covariates based on their predictive strength and thus provides a natural variable selection mechanism, facilitating interpretability of the model. Finally, (non-crossing) quantiles from the obtained conditional distribution can be utilized as postprocessed ensemble forecasts. 
In a case study for the postprocessing of 10 m surface wind speed ensemble forecasts with 24 hour lead time we compare local and global D-vine copula based models to the zero-truncated ensemble model output statistics (tEMOS) for different sets of predictor variables at 60 surface weather stations in Germany. Furthermore, we investigate different types of training periods for both methods. We observe that the D-vine based postprocessing yields a comparable performance with respect to tEMOS models if wind speed ensemble variables are included only and a significant improvement if additional meteorological and station specific weather variables are integrated. The case study indicates that training periods capturing seasonal patterns are performing best for both models. Additionally, we provide a criterion for calculating the variable importance in D-vine copulas and utilize it to outline which predictor variables are the most important for the correction of 10 m surface wind speed ensemble forecasts.

How to cite: Jobst, D., Möller, A., and Groß, J.: D-Vine Copula based Postprocessing of Wind Speed Ensemble Forecasts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2902, https://doi.org/10.5194/egusphere-egu23-2902, 2023.

EGU23-5821 | ECS | Posters on site | NP5.1

A multivariate approach to combine general circulation models using graph cuts 

Lucas Schmutz, Soulivanh Thao, Mathieu Vrac, and Gregoire Mariethoz

General circulation models (GCMs) are of extreme importance to making future climate projections. Those are used extensively by policymakers to manage responses to anthropogenic global warming and climate change.

To extract a robust global signal and evaluate uncertainties, individual models are often assembled in Multi-Model Ensembles (MMEs). Various approaches to combine individual models have been developed, such as the Multi-Model Mean (MMM) or its weighted variants.

Recently, Thao et al. (2022) proposed a model comparison approach based on graph cuts. Graph cut optimization was developed in the field of computer vision to efficiently approximate a solution for low-level computer vision tasks such as image segmentation (Boykov et al., 2001). Applied to MMEs, it allows selecting for each gridpoint the best-performing model and produces a patchwork of models that maximizes performances while avoiding spatial discontinuities. Thus, it considers the local performance of individual models in contrast with approaches such as MMM or similar methods that use global weights.

Here we propose a new multivariate combination approach of MMEs based on graph cuts. Compared to the existing univariate method, our approach ensures that the relationships between variables, that are present in GCMs, are locally preserved while providing coherent spatial fields. Moreover, we measure the local performance of models using the Hellinger distance between multi-decadal distributions. This allows a combination of models that is not only indicative of the average behavior (e.g. mean temperature or mean precipitation) but of the entire multivariate distribution, including more extreme values that have a high societal and environmental impact.

REFERENCES 

Boykov, Y., Veksler, O., & Zabih, R. (2001). Fast approximate energy minimization via graph cuts. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(11), 1222–1239. https://doi.org/10.1109/34.969114

Thao, S., Garvik, M., Mariethoz, G., & Vrac, M. (2022). Combining global climate models using graph cuts. Climate Dynamics, February. https://doi.org/10.1007/s00382-022-06213-4

How to cite: Schmutz, L., Thao, S., Vrac, M., and Mariethoz, G.: A multivariate approach to combine general circulation models using graph cuts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5821, https://doi.org/10.5194/egusphere-egu23-5821, 2023.

EGU23-8594 | ECS | Posters on site | NP5.1

Joint Generalized Neural Models and Censored Spatial Copulas for Probabilistic Rainfall Forecasting 

David Huk, Rilwan Adewoyin, and Ritabrata Dutta

This work develops a novel method for generating conditional probabilistic rainfall forecasts with temporal and spatial dependence. A two-step procedure is employed. Firstly, marginal location-specific distributions are modelled independently of one another. Secondly, a spatial dependency structure is learned in order to make these marginal distributions spatially coherent.
To learn marginal distributions over rainfall values, we propose a class of models termed Joint Generalised Neural Models (JGNMs). These models expand the linear part of generalised linear models with a deep neural network allowing them to take into account non-linear trends of the data while learning the parameters for a distribution over the outcome space.
In order to understand the spatial dependency structure of the data, a model based on censored copulas is presented. It is designed for the particularities of rainfall data and incorporates the spatial aspect into our approach. Uniting our two contributions, namely the JGNM and the Censored Spatial Copulas into a single model, we get a probabilistic model capable of generating possible scenarios on short to long-term timescales, able to be evaluated at any given location, seen or unseen. We show an application of it to a precipitation downscaling problem on a large UK rainfall dataset and compare it to existing methods.

How to cite: Huk, D., Adewoyin, R., and Dutta, R.: Joint Generalized Neural Models and Censored Spatial Copulas for Probabilistic Rainfall Forecasting, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8594, https://doi.org/10.5194/egusphere-egu23-8594, 2023.

EGU23-8824 | ECS | Posters on site | NP5.1

Evaluating probabilistic forecasts of extremes using continuous ranked probability score distributions 

Maxime Taillardat, Anne-Laure Fougères, Philippe Naveau, and Raphaël De Fondeville

Verifying probabilistic forecasts for extreme events is a highly active research area because popular media and public opinions are naturally focused on extreme events, and biased conclusions are readily made. In this context, classical verification methods tailored for extreme events, such as thresholded and weighted scoring rules, have undesirable properties that cannot be mitigated, and the well-known continuous ranked probability score (CRPS) is no exception.

Here, we define a formal framework for assessing the behavior of forecast evaluation procedures with respect to extreme events, which we use to demonstrate that assessment based on the expectation of a proper score is not suitable for extremes. Alternatively, we propose studying the properties of the CRPS as a random variable by using extreme value theory to address extreme event verification. An index is introduced to compare calibrated forecasts, which summarizes the ability of probabilistic forecasts for predicting extremes. The strengths and limitations of this method are discussed using both theoretical arguments and simulations.

How to cite: Taillardat, M., Fougères, A.-L., Naveau, P., and De Fondeville, R.: Evaluating probabilistic forecasts of extremes using continuous ranked probability score distributions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8824, https://doi.org/10.5194/egusphere-egu23-8824, 2023.

The ERA5 global reanalysis has been compared against a high-resolution regional reanalysis (COSMO-REA6) by means of scale-separation diagnostics based on 2d Haar discrete wavelet transforms. The presented method builds upon existing methods and enables the assessment of bias, error and skill for individual spatial scales, separately. A new skill score (evaluated against random chance) and the Symmetric Bounded Efficiency are introduced. These are compared to the Nash-Sutcliffe and the Kling-Gupta Efficiencies, evaluated on different scales, and the benefits of symmetric statistics are illustrated. As expected, the wavelet statistics show that the coarser resolution ERA5 products underestimate small-to-medium scale precipitation compared to COSMO-REA6. The newly introduced skill score shows that the ERA5 control member (EA-HRES), despite its higher variability, exhibits better skill in representing small-to-medium scales with respect to the smoother ensemble members. The Symmetric Bounded Efficiency is suitable for the intercomparison of reanalyses, since it is invariant with respect to the order of comparison.

How to cite: Casati, B., Lussana, C., and Crespi, A.: Scale-separation diagnostics and the Symmetric Bounded Efficiency for the inter-comparison of precipitation reanalyses, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9083, https://doi.org/10.5194/egusphere-egu23-9083, 2023.

EGU23-9328 | Orals | NP5.1

The EUPPBench postprocessing benchmark 

Jonas Bhend, Jonathan Demaeyer, Sebastian Lerch, Cristina Primo, Bert Van Schaeybroeck, Aitor Atencia, Zied Ben Bouallègue, Jieyu Chen, Markus Dabernig, Gavin Evans, Jana Faganeli Pucer, Ben Hooper, Nina Horat, David Jobst, Janko Merše, Peter Mlakar, Annette Möller, Olivier Mestre, Maxime Taillardat, and Stéphane Vannitsem

Statistical postprocessing of forecasts from numerical weather prediction systems is an important component of modern weather forecasting systems. A growing variety of postprocessing methods has been proposed, but a comprehensive, community-driven comparison of their relative performance is yet to be established. Important reasons for this lack include the absence of a fair intercomparison protocol, and, the difficulty of constructing a common comprehensive dataset that can be used to perform such intercomparison. Here we introduce the first version of the EUPPBench, a dataset of time-aligned medium-range forecasts and observations over Central Europe, with the aim to facilitate and standardize the intercomparison of postprocessing methods. This dataset is publicly available [1], includes station and gridded data, ensemble forecasts for training (20 years) and validation (2 years) based on the ECMWF system. The initial dataset is the basis of an ongoing activity to establish a benchmarking platform for postprocessing of medium-range weather forecasts. We showcase a first benchmark of several methods for the adjustment of near-surface temperature forecasts and outline the future plans for the benchmark activity. 

 

[1] https://github.com/EUPP-benchmark/climetlab-eumetnet-postprocessing-benchmark

How to cite: Bhend, J., Demaeyer, J., Lerch, S., Primo, C., Van Schaeybroeck, B., Atencia, A., Ben Bouallègue, Z., Chen, J., Dabernig, M., Evans, G., Faganeli Pucer, J., Hooper, B., Horat, N., Jobst, D., Merše, J., Mlakar, P., Möller, A., Mestre, O., Taillardat, M., and Vannitsem, S.: The EUPPBench postprocessing benchmark, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9328, https://doi.org/10.5194/egusphere-egu23-9328, 2023.

The established benefits of post-processing the results of multi-model ensembles, even by simple averaging, suggest a more radical approach: The models should be combined more frequently in run-time so as to form a single “supermodel”.  Simple nudging of models to one another, as frequently as the models might assimilate data from observations, combines model fusion with a reasonable degree of model autonomy.

Key to the success of the supermodeling approach is the phenomenon of chaos synchronization, known in the field of nonlinear dynamics, wherein two chaotic systems synchronize when connected through only a few of their variables, despite sensitive dependence on initial conditions. Synchronization gives rise to consensus among models. The nudging coefficients can be trained so that that consensus agrees with observations, because the effective dynamics of the trained supermodel, regarded as a single dynamical system, matches the dynamics of nature. Yet the number of independent nudging coefficients that must be trained is far less than the number of trainable parameters in a typical climate model.

It is expected that supermodeling will be especially useful for improving the representation of localized structures, such as blocking patterns, which will wash out if de-synchronized output fields of different models are combined by averaging.  We confirm a hypothesis that such coherent structures will synchronize even when the underlying fields do not, because the internal synchronization within each structure re-enforces synchronization between models: A configuration of CAM4 and CAM5 models, of different resolution, connected by nudging, exhibits correlated blocking activity even when the flows do not otherwise synchronize.  

We further explore the basis for correlated blocking activity in a pair of coupled quasi-geostrophic channel models. The local synchronization error is lower in a region of the channels where blocks form than elsewhere in the channels. Blocking correlations emerge as a vestige of “chimera synchronization”, the phenomenon in which complete synchronization of two spatially extended systems is intermittent in space as well as time. Such partial synchronization of different models in the regions of blocks - and of other structures such as jets, fronts, and large-scale convection - would be particularly useful for projecting climate-change patterns in extreme events associated with those structures.

How to cite: Duane, G., Schevenhoven, F., and Weiss, J.: Synchronization of Blocking Patterns in Diifferent Models, Connected So As to Form a “Supermodel” of Future Climate, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10153, https://doi.org/10.5194/egusphere-egu23-10153, 2023.

EGU23-11230 | Posters on site | NP5.1

Mathematical Properties of Continuous Ranked Probability Score Forecasting 

Clément Dombry, Romain Pic, Philippe Naveau, and Maxime Taillardat

The theoretical advances on the properties of scoring rules over the past decades have broaden the use of scoring rules in probabilistic forecasting. In meteorological forecasting, statistical postprocessing techniques are essential to improve the forecasts made by deterministic physical models. Numerous state-of-the-art statistical postprocessing techniques are based on distributional regression evaluated with the Continuous Ranked Probability Score (CRPS). However, theoretical properties of such minimization of the CRPS have mostly considered the unconditional framework (i.e. without covariables) and infinite sample sizes. We circumvent these limitations and study the rate of convergence in terms of CRPS of distributional regression methods. We find the optimal minimax rate of convergence for a given class of distributions. Moreover, we show that the nearest neighbor method and the kernel method for distributional regression reach the optimal rate of convergence in dimension larger than 2 and in any dimension, respectively.
Associated article: https://doi.org/10.1016/j.ijforecast.2022.11.001

How to cite: Dombry, C., Pic, R., Naveau, P., and Taillardat, M.: Mathematical Properties of Continuous Ranked Probability Score Forecasting, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11230, https://doi.org/10.5194/egusphere-egu23-11230, 2023.

It is often stated that the goal of probabilistic forecasting is to issue predictive distributions that are as sharp as possible, subject to being calibrated. To assess the calibration of ensemble forecasts, it is customary to employ rank histograms. Rank histograms not only assess whether or not an ensemble prediction system is calibrated, but they also reveal what (if any) systematic biases are present in the forecasts. This information can readily be relayed back to forecasters, helping to improve future predictions. Such is the utility of rank histograms, several extensions have been proposed to evaluate the calibration of probabilistic forecasts for multivariate outcomes. These extensions typically introduce a so-called pre-rank function that condenses the multivariate forecasts and observations into univariate objects, from which a standard rank histogram can be constructed. Several different approaches to construct multivariate rank histograms have been proposed, each of which differs in the choice of pre-rank function. Existing pre-rank functions typically aim to preserve as much information as possible when condensing the multivariate forecasts and observations into univariate objects. Although this is sensible when testing for multivariate calibration, the resulting rank histograms are often difficult to interpret, and are therefore rarely used in practice.        
We argue that the principal utility of these histogram-based diagnostic tools is that they provide forecasters with additional information regarding the deficiencies that exist in their forecasts, in turn allowing them to address these shortcomings more readily; interpretation is therefore a key requirement. We demonstrate that there are very few restrictions on the choice of pre-rank function when constructing multivariate rank histograms, meaning forecasters need not restrict themselves to the few proposed already, but can instead choose a pre-rank function on a case-by-case basis, depending on what information they want to extract from their forecasts. We illustrate this by introducing a range of possible pre-rank functions when assessing the calibration of probabilistic spatial field forecasts. The pre-rank functions that we introduce are easy to interpret, easy to implement, and they provide complementary information. Several pre-rank functions can therefore be employed to achieve a more complete understanding of the multivariate forecast performance. Finally, having chosen suitable pre-rank functions, tests for univariate calibration based on rank histograms can readily be applied to the multivariate rank histograms. We illustrate this here using e-values, which provide a theoretically attractive way to sequentially test for the calibration of probabilistic forecasts.

How to cite: Allen, S. and Ziegel, J.: Assessing the calibration of multivariate ensemble forecasts: E-values and the choice of pre-rank function, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11660, https://doi.org/10.5194/egusphere-egu23-11660, 2023.

EGU23-12232 | ECS | Posters on site | NP5.1

Impacts of uni- and multivariate bias adjustment methods on simulations of hydrological signatures in high latitude catchments 

Faranak Tootoonchi, Andrijana Todorović, Thomas Grabs, and Claudia Teutschbein

Climate models are used to generate future hydroclimatic projections for exploring how climate change may affect water resources. Their outputs, however, feature systematic errors due to parametrization and simplification of processes at the spatiotemporal scales required for impact studies. To minimize the adverse effects of such biases, an additional bias adjustment step is typically required.

Over the past decade, adjustment methods with different levels of complexity have been developed that consider one or several variables at a time, consequently adjusting one or multiple features of climate model simulations. Despite attempts in developing such methods and the growing use of some, the selection of methods for accurate simulation of streamflow remains subjective and still highly debated. In this study, we seek to answer whether sophisticated multivariate bias adjustment methods outperform simple univariate methods in the simulation of streamflow signatures.

To this end, we systematically investigated the ability of two simple univariate and two advanced multivariate methods to accurately represent various hydrological signatures relevant for water resources management in high latitudes. We offer practical guidelines for choosing the most suitable bias adjustment methods based on the objective of each study (i.e., hydrologic signatures of interest) and the hydroclimatic regime of the study catchments.

How to cite: Tootoonchi, F., Todorović, A., Grabs, T., and Teutschbein, C.: Impacts of uni- and multivariate bias adjustment methods on simulations of hydrological signatures in high latitude catchments, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12232, https://doi.org/10.5194/egusphere-egu23-12232, 2023.

Spatial sampling remains a conundrum for verification. The observations that are required are rarely on a grid, nor are they homogenously spaced. They are often located where there are people, easy access and do not sample the variable in a representative way. In an aggregate sense, scores derived from such observation locations, will give areas with greater observation density more weight in the aggregate if the variations in network density are not accounted for. Furthermore the performance in some parts of the domain may not be represented at all if there are no observations there. Gridded analyses on the other hand often provide complete coverage, and offer great ease of use, but adjacent grid boxes are not independent. Given this relative wealth of coverage and uniform sampling, we tend to use all available grid points for computing aggregate scores for an area or region, despite knowing that this is likely to produce too-narrow confidence intervals and inflate any statistical significance that may be present. 

In this presentation a variety of approaches, both empirical and statistical, are explored to establish what we ought to include when computing aggregate scores. Three different empirical sampling approaches are compared to selections from statistical coverage or network design algorithms. The empirical options include what is termed “strict” sub-sampling, whereby a sample is taken from the full grid and the reduction in sample size is explored by systematically continually taking a sub-sample from the sub-sample. The second is a systematic reduction in sample size from the original grid whereby each sample is drawn from the original grid, taken every other grid point, then every 3rd grid point, every 4th etc. The third is a mean computed from N random draws of reducing sample size. These empirical options do not respect land or sea locations. They are purely intended at looking at the behaviour and stability of the sample score. The coverage design algorithms provide a methodology for deriving homogeneous samples for irregularly spaced surface networks over land, and regularly spaced sampling of grids over the ocean, to achieve an optimal blend of sampling for regions that cover both land and sea.  These sample sizes and sample scores are compared to a statistically computed effective sample size. 

Some interesting and surprising results emerge. One of which is that as little as 1% of the total number of grid points may be sufficient for measuring the performance of the forecast on a grid, though the proportion of the total will always be dependent on (to varying degrees) the variable, the threshold or event of interest, the metric or score, and the characteristics of the geographical region of interest. 

How to cite: Mittermaier, M. and Gilleland, E.: Exploring empirical and statistical approaches for determining an appropriate sample size for aggregate scores, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12242, https://doi.org/10.5194/egusphere-egu23-12242, 2023.

EGU23-12316 | Posters on site | NP5.1

On the reliability of bivariate forecasts 

Zied Ben Bouallegue

Reliability is a key attribute of an ensemble forecast. Typically, this means that one expects that the ensemble spread reflects the potential error of the corresponding ensemble mean forecast. In the realistic case of an unperfect forecast, reliability deficiencies can be diagnosed with tools such as the reliability diagram and the rank histogram. Along with the computation of scores, the use of these diagnostic tools is common practice in ensemble forecast verification when assessing univariate forecasts. But what does reliability mean in practical terms when assessing multivariate forecasts? Here the concept of reliability is revisited in the simplest of the multivariate cases: the bivariate forecast. As a result, we propose a set of new diagnostic tools with an emphasis on the cross-variable reliability aspect. Real case examples are used for illustration and discussion.

How to cite: Ben Bouallegue, Z.: On the reliability of bivariate forecasts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12316, https://doi.org/10.5194/egusphere-egu23-12316, 2023.

EGU23-13327 | ECS | Posters on site | NP5.1

Towards a machine learning based multimodel for precipitation forecast over the italian peninsula 

Luca Monaco, Roberto Cremonini, and Francesco Laio

Direct model output forecasts by Numerical Weather Prediction models (NWPs) present some limitations caused by errors mostly due to sensitivity to initial conditions, sensitivity to boundary conditions and deficiencies in parametrization schemes (i.e. orography).
These sources of error are unavoidable, and atmospheric chaotic dynamics make prediction errors spread rapidly in time in the course of the forecast, inducing both systematic and random errors.
Nonetheless, in the last 50 years, NWPs had a significant decrease in the impact of these sources of errors, even in the long-term forecast, thanks for instance to an ever-increasing computational capability, but their relevance is still not neglectable.
Moreover, different NWPs present specific different pros and cons which are findable empirically. For instance, in the case of precipitation forecast in north-west Italy, low-resolution models (e.g. ECMWF-IFS) are more reliable in terms of space and time in predicting the average precipitation, while high-resolution models (e.g. COSMO-2I) tend to forecast better the maximum precipitation. Research purposes apart, actual limitations must be seen in an operational context, where weather forecasts’ skillfulness and associated uncertainty are information of the utmost importance to the forecaster and in general to the user of a certain forecasts system.

To tackle these limitations of NWPs and the need for an uncertainty-quantified meteorological forecast, we propose a machine learning-based multimodel post-processing technique for precipitation forecast. We focus on precipitation since it is the most important variable in the issue of spatially localized weather alert notice by the Italian Civil Protection system and at the same time it is one of the most challenging variables to forecast. 
We use a Convolutional Neural Network (CNN) to obtain deterministic and probabilistic forecast grids over 24h up to 48h focusing on North-West Italy, using several high and low-resolution deterministic NWPs as input and using high-resolution rain-gauge corrected radar observations for the training. The effect of the usage of different convolutional parameters (e.g. stride, padding) is taken into account. The deterministic output grid is chosen as the grid with the lowest mean square error obtained during the training, and it is compared with the linear regression of the input NWPs and with every single model. The probabilistic output grid is generated by considering the statistical ensemble of the twenty grids with the lowest mean square error obtained during the training, and it is compared with the logistic regression of the input NWPs and with ECMWF-EPS as a benchmark, both at different precipitation thresholds.

How to cite: Monaco, L., Cremonini, R., and Laio, F.: Towards a machine learning based multimodel for precipitation forecast over the italian peninsula, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13327, https://doi.org/10.5194/egusphere-egu23-13327, 2023.

In recent years neural networks have successfully been applied to probabilistic post-processing of numerical weather prediction forecasts. In the Bernstein Quantile Networks (BQN) method predictive quantile distributions are specified by Bernstein polynomials and their coefficients linked to input features through flexible neural networks. However, precipitation presents an additional challenge due to its mixed distributed nature with a considerable proportion of dry events for short accumulation periods. In this presentation, it is demonstrated how the BQN method can be modified to mixed distributed variables like precipitation by introducing a latent variable and treating zero precipitation cases as censored data. The method is tested on both synthetic and real precipitation forecast data and compared to an approach where a model of the probability of precipitation is combined with a model of precipitation amounts using the laws of probability.

 

How to cite: Bremnes, J. B.: Censored Bernstein quantile networks for probabilistic precipitation forecasting, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13849, https://doi.org/10.5194/egusphere-egu23-13849, 2023.

EGU23-14425 | ECS | Posters on site | NP5.1

Lead time continuous statistical post-processing of ensemble weather forecasts 

Jakob Wessel, Chris Ferro, and Frank Kwasniok

Numerical weather prediction (NWP) models usually output their forecasts at a multiplicity of different lead times. For example, the Met Office ensemble prediction system for the UK (MOGREPS-UK) predicts atmospheric variables on a 2.2km grid for up 126h on hourly and sub-hourly timesteps. Even though for applications, information is often required on this range of lead times, many post-processing methods in the literature are either applied at fixed lead time or by fitting individual models for each lead time. This is also the case in systems used in practice such as the Met Office IMPROVER system. However, this is 1) computationally expensive because it requires the training of multiple models if users are interested in information at multiple lead times and 2) prohibitive because it restricts the training data used for training post-processing models and the usability of fitted models.

In this work we investigate lead time dependence of ensemble post-processing methods by looking at ensemble forecasts in an idealized Lorenz96 system as well as temperature forecast data from the Met Office MOGREPS-UK system. First, we investigate the lead time dependence of estimated model parameters in non-homogenous Gaussian regression (NGR -- a standard ensemble post-processing technique) and find substantial smoothness. Secondly, we look at the usability of models fitted for one lead time and employed at another to then thirdly fit models that are “lead time continuous”, meaning they work for multiple lead times simultaneously by including lead time as a covariate using spline regression. We show that these models can achieve similar performance to the classical “lead time separated” models, whilst saving substantial computation time. Fourthly and finally we make first steps towards the development of a cheap computational model including seasonality and working continuously over the lead time, needing to be fit only once.

How to cite: Wessel, J., Ferro, C., and Kwasniok, F.: Lead time continuous statistical post-processing of ensemble weather forecasts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14425, https://doi.org/10.5194/egusphere-egu23-14425, 2023.

EGU23-14560 | ECS | Posters on site | NP5.1

Quantile regression forests for post-processing ECWMF ensemble precipitation forecasts: hyperparameter optimization and comparison to EMOS 

Eva van der Kooij, Antonello Squintu, Kirien Whan, and Maurice Schmeits

Ensemble forecasts are important due to their ability to characterize forecast uncertainty, which is fundamental when forecasting extreme weather. Ensemble forecasts are however often biased and underdispersed and thus need to be post-processed.

A common approach for this is the use of ensemble model output statistics (EMOS), where a parametric distribution is fitted with a limited number of predictors. With recent advances in computer science and increased amounts of data available, machine learning techniques, like random forests, are becoming more popular for high dimensional regression problems. In this research, we explore the use of the quantile regression forest (QRF), a random forest adapted for conditional quantile estimation, applied to medium range gridded probabilistic precipitation forecasts. QRFs are non-parametric and allow for a larger number of predictors, which means they can possibly consider more dependencies that might otherwise not be captured with a simple EMOS.

A QRF takes several hyperparameters that influence the way the decision trees in the forest are constructed. We explore the minimum number of samples needed in a leaf to split it (minimum node size) and the number of predictors explored in each split (mtry). A hyperparameter space is constructed by setting ranges for both minimum node size and mtry, and the optimal hyperparameter set is determined by performing a cross validated grid search. Here, each model is assessed based on the continuous ranked probability skill score (CRPSS). For comparison, EMOS is applied with a zero-adjusted gamma (ZAGA) distribution, using a limited number of predictors that are physically correlated to precipitation. Both methods are verified on a separate testing data set and evaluated using several scores, including CRPSS and Brier skills score (BSS).

We consider 4 years (November 2018 – October 2022) of archived operational ECMWF-IFS ensemble forecasts for the Netherlands. The data is split into November 2018 – October 2021 for training and cross-validation, and October 2021 – October 2022 for testing, separating data for season, initialization time and lead-time. Forecasts are post-processed up to +10 days. Ensemble statistics on 60+ forecast variables are used as predictors. Spatially and temporally aggregated, gauge-adjusted radar observations are used as predictand. The raw ensemble is considered as the benchmark.

The results of this research will determine what method will be used to post-process the ensemble precipitation forecasts in the context of the early warning center (EWC) of the Royal Netherlands Meteorological Institute. The most suitable method could differ between shorter and longer lead times.

How to cite: van der Kooij, E., Squintu, A., Whan, K., and Schmeits, M.: Quantile regression forests for post-processing ECWMF ensemble precipitation forecasts: hyperparameter optimization and comparison to EMOS, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14560, https://doi.org/10.5194/egusphere-egu23-14560, 2023.

EGU23-14712 | ECS | Orals | NP5.1

NWP model updates and post-processing: a strategy for an EMOS model on ECMWF wind gusts forecasts 

Antonello A. Squintu, Eva van der Kooij, Kirien Whan, and Maurice Schmeits

In the framework of KNMI’s Early Warning Center (EWC), ECMWF ensemble (ENS) predictions are used to issue medium-range forecasts of severe weather. Timely forecasts of wind gusts extremes are important to prevent potential damage. However, ensemble forecasts are affected by biases and under- or over-dispersion. These errors lead to a reduction in the skill of the forecasts, especially for long lead-times and for extreme cases, such as windstorms and deep convective episodes. Hence, statistical post-processing is a fundamental step in the establishment of a skillful weather alert system for extreme wind gust events.     

However, weather models like ECMWF-IFS are subject to frequent updates, which include changes in the calculation of certain diagnostic variables and by consequence in statistical features of their ensemble distribution. This is the case for ECMWF wind gusts forecasts, whose bias has been reduced with the last update in October 2021. Therefore, the use of pre-update wind gusts forecasts in the training of the post-processing model must be considered with care.

In the context of the development of an Ensemble Model Output Statistics (EMOS) model, this limitation has been tackled by reconstructing wind-gusts forecasts with a preliminary EMOS model. This step has been performed by including in the regression those variables that are used by ECMWF for the calculation of wind gusts, which were less affected by the update.

The reconstructed wind gusts forecasts have been added to a set of summary statistics of the ensemble distribution of variables physically related to wind gusts. A process of forward selection has been applied to identify the most relevant contributions to the general EMOS model, highlighting reconstructed wind gusts as the most important predictor for all lead-times.

The post-processed forecasts obtained with this experimental EMOS model have been verified and compared to those calculated with a conventional EMOS model (performed ignoring the above caveats) and with the results of a non-parametric Quantile Regression Forest. These models have been trained on the same period (2018-2021) and tested on the period that has followed the update (2021-2022), including only grid-points and stations that cover the territory of the Netherlands and distinguishing between summer and winter half-years. The method showing the best performance will be employed operationally for the post-processing of ECMWF-ENS wind gust forecasts over the Netherlands and will be used in the EWC weather alert system.

How to cite: Squintu, A. A., van der Kooij, E., Whan, K., and Schmeits, M.: NWP model updates and post-processing: a strategy for an EMOS model on ECMWF wind gusts forecasts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14712, https://doi.org/10.5194/egusphere-egu23-14712, 2023.

EGU23-15152 | ECS | Posters on site | NP5.1

Towards sub-kilometer resolution probabilistic analysis of surface wind in complex terrain 

Francesco Zanetta, Daniele Nerini, Matteo Buzzi, and Mark A. Liniger

Correctly representing surface wind is critical for applications such as renewable energy, snow modelling or warning systems. However, numerical weather prediction models with their limited resolution cannot fully represent the strong variability due to complex topography. Downscaling techniques – functionally equivalent to postprocessing when the ground truth is given by observational data - can achieve remarkable results in reducing systematic biases of raw models and can be calibrated to yield accurate probabilistic information at any point in space. 

These techniques can be further improved at analysis time by including real-time measurements, allowing to produce a probabilistic sub-grid resolution analysis of surface wind. Such a product would enable other interesting applications, such as detailed climatologies or nowcasting, and could serve as a ground truth for training deep learning-based postprocessing models with generative approaches, allowing to model spatially and temporally consistent ensembles.  

The first important challenge is to integrate measurements in a statistically optimized and efficient way. Here, we share our ongoing work and preliminary results in a comparative analysis of different approaches, from naïve interpolations to geostatistical techniques or novel approaches based on neural networks. The analysis is based on a multi-year archive of hourly wind observations and NWP analyses from the operational COSMO-1E model over Switzerland. 

How to cite: Zanetta, F., Nerini, D., Buzzi, M., and Liniger, M. A.: Towards sub-kilometer resolution probabilistic analysis of surface wind in complex terrain, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15152, https://doi.org/10.5194/egusphere-egu23-15152, 2023.

EGU23-17348 | Orals | NP5.1

Postprocessing of ensemble precipitation forecasts over India using weather types 

Martin Widmann, Noemi Gonczol, Michael Angus, and Robert Neal

Accurate predictions of heavy precipitation in India are vital for impact-orientated forecasting, and an essential requirement for mitigating the impact of damaging flood events. Operational forecasts from non-convection-permitting models can have large biases in the intensities of heavy precipitation, and while convection-permitting models can perform better, their operational use over large areas is not yet feasible. Statistical postprocessing can reduce these biases for relatively little computational cost, but few studies have focused on postprocessing forecasts of monsoonal rainfall.

We present a postprocessing method for operational precipitation forecasts based on local precipitation distributions for 30 Indian weather types. It is applied to ensemble forecasts for daily precipitation with 12km spatial resolution and lead times of up to 10 days from the Indian National Centre for Medium Range Weather Forecasting (NCMRWF) Ensemble Prediction System (NEPS). The method yields local probabilistic forecasts that are the weighted mean of the observed local precipitation distributions for each weather type, with weights given by the relative frequency of the weather types in the forecast ensemble.

The general forecast skill is determined through the Continuous Ranked Probability Skill Score (CRPSS) and the skill for predicting the exceedance of the local 90th percentile is quantified through the Brier Skill Score (BSS). The CRPSS shows moderate improvement over most of India for forecasts with one day lead time, and substantial improvements almost everywhere for longer lead times. The BSS for one day forecasts indicates a spatially complex pattern of higher and lower performance, while for longer lead times the forecasts for heavy precipitation are improved almost everywhere. The improvements with respect to both measures are particularly high over mountainous or wet regions. We will also present reliability diagrams for the raw and postprocessed forecasts of threshold exceedances.

 

 

How to cite: Widmann, M., Gonczol, N., Angus, M., and Neal, R.: Postprocessing of ensemble precipitation forecasts over India using weather types, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17348, https://doi.org/10.5194/egusphere-egu23-17348, 2023.

EGU23-3730 | PICO | AS1.6

Simulating atmospheric dust and its radiative impact with a global variable-resolution model 

Chun Zhao, Jiawang Feng, Qiuyan Du, Mingyue Xu, Jun Gu, and Zhiyuan Hu

In this study, a global variable-resolution modeling framework of atmospheric dust and its radiative feedback is introduced and evaluated. In this model, atmospheric dust is simulated simultaneously with the meteorological fields, and dust-radiation interaction is included. Five configurations of global mesh with the refinement at different resolutions and over different regions of interest are used to explore the impacts of regional refinement on modeling dust lifecycle at regional and global scales. The model produces reasonably the overall magnitudes and spatial variabilities of global dust metrics such as surface mass concentration, total deposition, AOD, and radiative forcing compared to observations and previous modeling results. Two global variable-resolution simulations with mesh refinement over major deserts of North Africa (V16km-NA) and East Asia (V16km-EA) simulates less dust emissions and smaller dry deposition rate inside the refined regions due to the weakend near-surface wind speed caused by better resolved topographic complexity at higher resolution. Dust mass loading over North Africa is close to each other between V16km-NA and U120km, while over East Asia, V16km-EA simulates higher dust mass loading. Over the non-refined areas with the same resolution, the difference between global variable-resolution and uniform-resolution experiments also exist, which is partly related to their difference in dynamic time-step and the coefficient for horizontal diffusion. Refinement at convection-permitting resolution around the Tibet Plateau (TP) leads to significantly different dust and precipitation around the TP against coarse resolution, which implies that dust-precipitation interaction over this area deserves further investigation with this  global variable-resolution modeling framework in future. 

How to cite: Zhao, C., Feng, J., Du, Q., Xu, M., Gu, J., and Hu, Z.: Simulating atmospheric dust and its radiative impact with a global variable-resolution model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3730, https://doi.org/10.5194/egusphere-egu23-3730, 2023.

EGU23-3983 | PICO | AS1.6

Indirect and direct aerosol feedback in the global and regional scale NOAA UFS Weather Model 

Haiqin Li, Georg Grell, Ravan Ahmadov, Johana Romero-Alvarez, Li Zhang, Eric James, Barry Baker, Joseph Olson, Shan Sun, Jordan Schnell, and Ning Wang

Aerosols play a significant role in the radiation and atmospheric precipitation physics of microphysics and convection, and have a significant impact on air quality, visibility, public health, aviation, and climate. A physics suite, which includes the aerosol-aware double momentum Thompson-Eidhammer microphysics scheme (TH-E MP), the scale-aware and aerosol-aware Grell-Freitas (GF) convection scheme, and the MYNN-EDMF boundary layer and shallow cloud scheme, was developed at NOAA Global System Laboratory (GSL). The GSL physics suite is applied in the FV3GFS global model and the Rapid Refresh Forecast System (RRFS) regional model. We also developed the RRFS – Smoke and Dust model (RRFS-SD) at NOAA GSL with the Common Community Physics Package (CCPP), which is designed to facilitate a host-model agnostic implementation of physics parameterizations. Because of the interactive and strongly coupled nature of chemistry and physics, it is natural to allow for the smoke, dust and other chemical modules to be called directly from the physics suite. Here we embedded the plume rise modules for wildfire, sea-salt, dust, and anthropogenic emission modules into the regional model of RRFS and global UFS model using CCPP as subroutines of physics. The prognostic emissions of sea-salt, and organic carbon are combined to represent the “water friendly” aerosol emission, while the prognostic emission of dust is used to represent “ice friendly” aerosol emission for TH-E MP. With this implementation, we examined the aerosol indirect feedback when using the TH-E scheme in the global FV3GFS forecast with C768 (~13km) horizontal resolution and 127 vertical levels. There are significant cloud-radiation responses to the aerosol differences, and the severely positive precipitation bias over Europe and North America is significantly alleviated when applying this aerosol emission method for indirect feedback. We also examined the smoke direct feedback to the radiation in the RRFS-SD with 3km horizontal resolution and 64 vertical layers for September, 2020 during which the western US experienced extreme wildfires. The aerosol direct feedback run significantly improves the forecast of aerosol optical depth, surface 2m air temperature, 10m wind speed, and radiation fluxes.

How to cite: Li, H., Grell, G., Ahmadov, R., Romero-Alvarez, J., Zhang, L., James, E., Baker, B., Olson, J., Sun, S., Schnell, J., and Wang, N.: Indirect and direct aerosol feedback in the global and regional scale NOAA UFS Weather Model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3983, https://doi.org/10.5194/egusphere-egu23-3983, 2023.

The Chinese Meteorology Administration chemistry model CUACE is online integrated into the mesoscale operational weather prediction (NWP) model (GRAPES_Meso5.1) and aerosol-cloud-radiation interaction is achieved to establish the first version (V1) of chemistry-weather (CW) interacted model GRAPES-Meso5.1/CUACE CW V1. The most polluted winter 2016-2017 is selected to study the meteorology impacts on haze/fog prediction, the impact of aerosol-radiation, aerosol-cloud and CW interaction (ARI, ACI, CWI) on haze/fog prediction and NWP. Single way model without CWI displays reasonable PM 2.5 and visibility prediction in general. However, modeled PM2.5 peaks are underestimated and visibility valleys are overestimated during haze/fog pollution, the underestimation of relative humidity (RH) contributes major to this misestimation; CWI model cut the negative bias of PM 2.5 peaks and the positive bias of visibility valleys. The improvement of 5km and 3km low visibility by CWI during severe haze/fog period is more obvious than that of 10 km, which just compensates for the largest deficiency in low visibility prediction related with severe haze/fog by single way model; The NWP including sea level pressures, relative humidity(RH), temperature, wind speed are also improved by CWI from surface to upper troposphere; ARI contributes larger to the predicted PM2.5 ,visibility and NWP improvement than that of ACI, their relative contributions varies with model vertical height and the overlapping condition of cloud and aerosols. Due to the joint contribution of RH and PM2.5, CWI’s improving on visibility is larger than PM2.5. This study illustrates the importance of including CWI in air quality prediction model.

How to cite: Wang, H.: Chemistry-Weather Interacted Model System GRAPES_Meso5.1/CUACE CW V1.0: Development, Evaluation and Application in Better Haze/fog Prediction in China, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4025, https://doi.org/10.5194/egusphere-egu23-4025, 2023.

The representation of aerosol–cloud interaction (ACI) and its impacts in the current climate or weather model remains a challenge, especially for severely polluted regions with high aerosol concentration, which is even more important and worthy of study. Here, ACI is first implemented in the atmospheric chemistry model GRAPES_Meso5.1/CUACE by allowing for real-time aerosol activation in the Thompson cloud microphysics scheme. Two experiments are conducted focusing on a haze pollution case with coexisting high aerosol and stratus cloud over the Jing–Jin–Ji region in China to investigate the impact of ACI on the mesoscale numerical weather prediction (NWP). Study results show that ACI increases cloud droplet number concentration, water mixing ratio, liquid water path (CLWP), and optical thickness (COT), as a result improving the underestimated CLWP and COT (reducing the mean bias by 21% and 37%, respectively) over a certain subarea by the model without ACI. A cooling in temperature in the daytime below 950 hPa occurs due to ACI, which can reduce the mean bias of 2 m temperature in the daytime by up to 14% (∼ 0.6 ℃) in the subarea with the greatest change in CLWP and COT. The 24 h cumulative precipitation in this subarea corresponding to moderate-rainfall events increases, which can reduce the mean bias by 18%, depending on the enhanced melting of the snow by more cloud droplets. In other areas or periods with a slight change in CLWP and COT, the impact of ACI on NWP is not signifificant, suggesting the inhomogeneity of ACI. This study demonstrates the critical role of ACI in the current NWP model over the severely polluted region and the complexity of the ACI effect.

How to cite: Zhang, W., Wang, H., and Zhang, X.: Aerosol–cloud interaction in the atmospheric chemistry model GRAPES_Meso5.1/CUACE and its impacts on mesoscale numerical weather prediction under haze pollution conditions in Jing–Jin–Ji in China, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4146, https://doi.org/10.5194/egusphere-egu23-4146, 2023.

EGU23-11392 | PICO | AS1.6

Simulating direct and semi-direct effect of aerosols on subseasonal prediction: climatology versus interactive aerosols in the UFS model 

Shan Sun, Gregory Frost, Georg Grell, Li Zhang, Barry Baker, Jessica Meixner, and Anning Cheng

We investigate the aerosol direct and semi-direct effect on subseasonal prediction using NOAA’s fully coupled Unified Forecast System (UFS) model, which includes the atmospheric model FV3 with the Global Forecast System (GFS) physics package V17, MOM6 ocean model, WW3 wave model and CICE6 sea ice model. A systematic twin experiment is carried out: (i) UFS with prescribed aerosol climatology and (ii) UFS coupled to interactive aerosols from the GOCART aerosol module. Both experiments are deterministic 32-day hindcasts with monthly initialization over multiple years.

The modeled aerosol optical depth (AOD) in both experiments is in good agreement with the MODIS satellite observations. The AOD from the experiments with interactive aerosols captured the interannual variability seen in the observations. The estimated radiative forcing from the aerosol radiation interaction in these two sets of experiments is similar in the multi-year average. However, the advantage in the experiments with interactive aerosols can be seen clearly when simulating radiative forcing in the extreme dust storm and biomass burning events. Changes in cloud and precipitation are small between these two sets of experiments.

How to cite: Sun, S., Frost, G., Grell, G., Zhang, L., Baker, B., Meixner, J., and Cheng, A.: Simulating direct and semi-direct effect of aerosols on subseasonal prediction: climatology versus interactive aerosols in the UFS model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11392, https://doi.org/10.5194/egusphere-egu23-11392, 2023.

EGU23-13739 | PICO | AS1.6 | Highlight

Project FOCI - Non-CO2 Forcers and Their Climate, Weather, Air Quality and Health Impacts 

Tomas Halenka, Ranjeet Sokhi, and Alexander Baklanov

While overall global warming with the causes and global processes connected to well-mixed CO2, and its impacts on global to continental scales are well understood with a high level of confidence, there are knowledge gaps concerning the impact of many other non-CO2radiative forcers leading to low confidence in the conclusions. This relates mainly to specific anthropogenic and natural precursor emissions of short-lived GHGs and aerosols and their precursors. These gaps and uncertainties also exist in their subsequent effects on atmospheric chemistry and climate, through direct emissions dependent on changes in e.g., agriculture production and technologies based on scenarios for future development as well as feedback of global warming on emissions, e.g., permafrost thaw. In addition to the atmospheric radiative forcing (gaseous or aerosols), albedo changes connected to land use and land cover can play a role, depending on the adaptation or mitigation measures included in different scenarios.

The main goal of the EC Horizon Europe project FOCI (from the call HORIZON-CL5-2021-D1-01-0 Improved understanding of greenhouse gas fluxes and radiative forcers, including carbon dioxide removal technologies), is to assess the impact of key radiative forcers, where and how they arise, the processes of their impact on the climate system, to find and test an efficient implementation of these processes into global Earth System Models and into Regional Climate Models, eventually coupled with CTMs, and finally to use the tools developed to investigate mitigation and/or adaptation policies incorporated in selected scenarios of future development targeted at Europe and other regions of the world. We will develop new regionally tuned scenarios based on improved emissions to assess the effects of non-CO2 forcers. Mutual interactions of the results and climate services producers and other end-users will provide feedback for the specific scenarios preparation and potential application to support the decision-making, including climate policy.

How to cite: Halenka, T., Sokhi, R., and Baklanov, A.: Project FOCI - Non-CO2 Forcers and Their Climate, Weather, Air Quality and Health Impacts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13739, https://doi.org/10.5194/egusphere-egu23-13739, 2023.

EGU23-15355 | PICO | AS1.6

Changes to the IFS atmospheric composition model in support to the CAMS update for CY49R1. 

Samuel Remy, Vincent Huijnen, Chabrillat Simon, Swen Metzger, Jason Williams, Daniele Minganti, Christine Bingen, Mihai Alexe, and Johannes Flemming

The Integrated Forecasting System (IFS) of ECMWF is core of the Copernicus Atmosphere Monitoring Service (CAMS) to provide global analyses and forecasts of atmospheric composition, including reactive gases, as well as aerosol and greenhouse gases. The CAMS global model consists of the aerosol model of the IFS, IFS-AER, which is a sectional-bulk scheme, while the chemistry scheme is based on a CB05-based carbon-bond mechanism, with the option to couple this to BASCOE-based stratospheric chemistry. The composition model is updated regularly, aligned with updates of ECMWF’s operational meteorological model. Here we report on updates planned for the operational version after next, referred to as CY49R1. This concerns revisions on a large range of topics, as developed over the recent years, and therefore impacting many aspects of chemistry and aerosol composition in troposphere and stratosphere. Main aspects concern:

  • A review of the representation of polar stratospheric clouds and of their impact on stratospheric ozone,
  • An extension of IFS-AER to represent stratospheric sulfate aerosols, coupled with CB05 and BASCOE precursor gases,
  • An upgrade of gas-particle partitioning through the implementation of EQSAM4Clim in the IFS,
  • Computation of aerosol, cloud and rain pH, and use of the update pH values in aqueous chemistry,
  • A combined representation of aerosols and chemistry deposition processes (wet and dry),
  • Update of aerosol optics, including a simple representation of dust asphericity and hygroscopic growth,
  • Update of PM diagnostic output

In this contribution we provide an overview of expected changes with emphasis on changes in composition modeling aspects. We will present their expected impact on key atmospheric composition aspects, including air quality performance across major pollution regions across the world, aerosol optical depth, dust, and stratospheric composition products.

How to cite: Remy, S., Huijnen, V., Simon, C., Metzger, S., Williams, J., Minganti, D., Bingen, C., Alexe, M., and Flemming, J.: Changes to the IFS atmospheric composition model in support to the CAMS update for CY49R1., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15355, https://doi.org/10.5194/egusphere-egu23-15355, 2023.

EGU23-15547 | ECS | PICO | AS1.6 | Highlight

Introduction to the AQ-WATCH multi-model air quality forecast system 

Cathy Wing Yi Li, Mikhail Sofiev, Renske Timmermans, Richard Kranenburg, Gabriele Pfister, Rajesh Kumar, Adrien Deroubaix, Nicolas Huneeus, Mariel Opazo, Tomas Caballero, Dan Mo, Xuelei Zhang, Lukas Hubert Leufen, Felix Kleinert, Martin Schultz, Claire Granier, Sara Basart, Olivier Salvi, Bastien Caillard, and Guy Brasseur

AQ-WATCH (Air Quality: Worldwide Analysis and Forecasting of Atmospheric Composition for Health) is an international consortium, which co-develops and co-produces tailored products and services derived from space and in situ observational data for improving air quality forecasts and attribution. For this purpose, AQ-WATCH develops a supply chain leading to innovative downstream products and services for providing air quality information tailored to the identified needs of international users. This presentation will focus on one of the AQ-WATCH products, the AQ-WATCH air quality forecast system. Air quality forecast models provided by the AQ-WATCH consortium are set up for the focus regions in Asia and the Americas, based on the templates of Copernicus European and MarcoPolo-Panda Asian ensembles, but with much higher resolution and reliance on regional emission and observational information. The models are established over the focus regions using the meteorological and emission data taken from Copernicus repositories and other national archives and refined with local information wherever available. Each forecast model is then evaluated using local observational datasets and with the needs of the stakeholders. Machine learning workflows are being incorporated into the forecast system to improve both results from individual models and the model ensembles based on bias correction from observation data. Lessons learnt from model comparison in the focus regions will be presented. At last, the potential application of the system prototype, as well as the other AQ-WATCH products, namely the global and regional air quality atlas, the air quality attribution & mitigation, the dust and fire forecasts, and the fracking analysis tool, to other regions of the world will be discussed.

How to cite: Li, C. W. Y., Sofiev, M., Timmermans, R., Kranenburg, R., Pfister, G., Kumar, R., Deroubaix, A., Huneeus, N., Opazo, M., Caballero, T., Mo, D., Zhang, X., Leufen, L. H., Kleinert, F., Schultz, M., Granier, C., Basart, S., Salvi, O., Caillard, B., and Brasseur, G.: Introduction to the AQ-WATCH multi-model air quality forecast system, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15547, https://doi.org/10.5194/egusphere-egu23-15547, 2023.

EGU23-15869 | PICO | AS1.6

Extension and evaluation of the Integrated Forecast System (IFS) cycle 49R1 to stratospheric aerosols and chemistry for the global Copernicus Atmospheric Monitoring Service (CAMS) 

Christine Bingen, Simon Chabrillat, Quentin Errera, Vincent Huijnen, Swen Metzger, Daniele Minganti, Samuel Rémy, Jason Williams, and Johannes Flemming

The ECMWF’s Integrated Forecast System (IFS) is the global atmospheric model used by the Copernicus Atmospheric Monitoring Service (CAMS) to provide analyses and forecasts on atmospheric composition. Currently, the CAMS global model includes the aerosol model of the IFS, the aerosol module IFS-AER making use of a sectional-bulk scheme, and the chemistry scheme based on a CB05-based carbon-bond mechanism, with the option to couple this to stratospheric chemistry module BASCOE. The combined BASCOE will be used operationally in the CAMS global system starting from the upgrade to cycle 48R1 planned in June 2023. This abstract focuses on further developments related to stratospheric chemistry and aerosols that are to be implemented in the future operational cycle 49R1, as well as on a first evaluation of IFS’ performances in representing stratospheric aerosols and chemistry against different datasets.

Initially focussing on the troposphere, IFS-AER has been extended to include and represent stratospheric sulfate aerosol processes, keeping the existing tracers. The extended IFS-AER(strato) has been coupled to IFS(BASCOE) through the gaseous sulphuric acid tracer, to the IFS radiation scheme, and to the 4Dvar assimilation scheme. The evaluation of aerosol aspects makes use of aerosol datasets (aerosol extinction, AOD, …) from the Global Ozone Monitoring by Occultation of Stars (GOMOS, onboard Envisat), and the Global Space-based Stratospheric Aerosol Climatology (GloSSAC), based on different cases studies including quiescent and (highly) volcanic periods. It has also been tested against reference simulations from WACCM-CARMA. These intercomparisons show a reasonable agreement against retrieval datasets such as GloSSAC and reference simulations from WACCM-CARMA. In quiescent conditions, the new system showed a decreasing trend with respect to the reference datasets.

BASCOE includes a simple PSC parameterization, which has been updated and tuned in cycle 49R1. In order to assess the impact of this upgrade, we evaluate the composition of the polar lower stratosphere during the winter-spring seasons ("ozone hole" events) of 2008, 2009 and 2020 above the Antarctic and 2009, 2011, 2012 and 2020 above the Arctic, with a focus on 5 key species observed by Aura-MLS. This evaluation demonstrates the capacity of IFS(BASCOE) to forecast the chemical composition of the polar lower stratosphere above both the Arctic and the Antarctic for several years with very different evolution of the polar vortex. While further improvements are desirable and will require an overhaul of the PSC parameterization, the current performance allows us to study the interannual variability of ozone hole episodes.

How to cite: Bingen, C., Chabrillat, S., Errera, Q., Huijnen, V., Metzger, S., Minganti, D., Rémy, S., Williams, J., and Flemming, J.: Extension and evaluation of the Integrated Forecast System (IFS) cycle 49R1 to stratospheric aerosols and chemistry for the global Copernicus Atmospheric Monitoring Service (CAMS), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15869, https://doi.org/10.5194/egusphere-egu23-15869, 2023.

EGU23-16081 | ECS | PICO | AS1.6

Impact of the use of biofuels on the formation of ultrafine particles in southeastern Brazil 

Alejandro Herman Delgado Peralta and Maria de Fatima Andrade

Southeastern Brazil is the most developed and populous region with 89.5 million of inhabitants, according to the Instituto Brasileiro de Geografia e Estatística (IBGE) for 2021. The main metropolitan and industrialized areas are concentrated in its four states (São Paulo, Minas Gerais, Rio de Janeiro and Espírito Santo). One of them comprises the Metropolitan Area of São Paulo (MASP) with 7.3 million vehicles that releases air pollutant -gas and ultrafine particles- to the atmosphere due to the use of different fuel types; light-duty vehicles consume ethanol, gasohol (85% gasoline and 25% hydrous ethanol) or natural gas, and heavy vehicles (i.e., buses and trucks) run on diesel. So, frequently high concentrations of air pollutants (ozone and fine particles) in urban areas are above the recommended limits suggested by the World Health Organization (WHO) with high health risk mainly for children and elderly. The biggest concern is the high health risk of exposing the population to ultrafine particles, also called nanoparticles. Consequently, it is important to understand the formation of ultrafine particles, whether they are emitted directly or formed in the atmosphere. 

We study the formation processes of ultrafine particles in the scenario of fuel change in the road transport sector, including a greater use of biofuels. The air quality modeling system will analyze the impact of different scenarios in urban areas in southeastern Brazil. We begin with the air quality simulation for the current conditions as the base case scenario using the WRF-Chem model. As the main data input, we use emission data with two temporal profile distributions (monthly and hourly time average). First, we use available monthly anthropogenic emission's data processed by the European Copernicus Atmosphere Service (CAMS). Secondly, we added hourly road transport emission calculated with the LAPAT model, which use emission factors derived from measurements in experimental campaigns in tunnels where light and heavy vehicles circulate within the MASP. This simulation test with the WRF-Chem model considers the MOZART-MOSAIC mechanism and additional emissions from other sources such as biomass burning and chemical initial and boundary conditions from the CAM-Chem model. Experimental data and measurements of meteorological and air quality parameters will support the work to evaluate the performance of the model’s results.

How to cite: Delgado Peralta, A. H. and Andrade, M. D. F.: Impact of the use of biofuels on the formation of ultrafine particles in southeastern Brazil, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16081, https://doi.org/10.5194/egusphere-egu23-16081, 2023.

EGU23-16085 | PICO | AS1.6

Impact of pH computation from EQSAM4Clim on inorganic aerosols in the CAMS system 

Swen Metzger, Samuel Rémy, Vincent Huijnen, Jason Williams, Simon Chabrillat, Christine Bingen, and Johannes Flemming

The Integrated Forecasting System (IFS) of ECMWF is used within the Copernicus Atmosphere Monitoring Service (CAMS) to provide global analyses and forecasts of atmospheric composition, including aerosols as well as reactive trace gases and greenhouse gases. Inorganic gas/aerosol equilibrium involving the major sulphate and nitrate anions, i.e., H2SO4/HSO4-/SO42- and HNO3/NO3-, largely determines the aerosol acidity, while the gas/liquid/solid phase partitioning of semi-volatile cations, NH3/NH4+, and the liquid/solid partitioning of non-volatile mineral cations, particularly Ca2+, Mg2+, and K+, overall control the gas-liquid-solid aerosol equilibrium partitioning of reactive nitrogen compounds. For the NO3- and NH4+ equilibrium, our recent developments have focused on EQSAM4Clim, which has been recently integrated into the IFS as a computationally efficient means of describing aerosol pH in a global modeling system.

EQSAM4Clim is used in the IFS to estimate gas-liquid-solid partitioning and the aerosol associated liquid water content, which is subsequently used to estimate the associated aerosol, cloud and rain acidity. The aerosol, cloud and rain pH is computed by considering the liquid water (H2O) content in the respective liquid water phase using either the aerosol associated water computed by EQSAM4clim, and if present, the cloud and/or rain water of the IFS. The pH is coupled to the aqueous phase chemistry in IFS(CB05) and in the wet deposition of SO2 and NH3, which in-turn affects the aerosol composition through changes in the SO2/SO42-, NH3/NH4+and HNO3/NO3- partitioning, the aerosol associated liquid water content and solution pH.

Here we present first results of the of the impact of improved aerosol acidity in the solution (aerosol/cloud/rain water) on PM2.5 forecasts simulated in the IFS which are subject to gas-particle partitioning. In particular, the NH4+, NO3- and SO42- concentrations have been compared against observational datasets at the surface, showing promising improvements as a direct result of the new pH computations. When coupling the EQSAMClim pH into the aqueous phase chemistry routine, the surface concentrations of SO42- and the SO2 + SO42- wet deposition fluxes are improved over most of Europe, but degraded over parts of US. The relative impact of the improved pH appears generally small as compared to other related changes such as updates in aqueous chemistry rates. In the pH coupling, the aqueous chemistry component dominates the impact on the wet deposition of SO2/NH3. All of these results are highly dependent on the emissions input (SO2/NOx/NH3). 

How to cite: Metzger, S., Rémy, S., Huijnen, V., Williams, J., Chabrillat, S., Bingen, C., and Flemming, J.: Impact of pH computation from EQSAM4Clim on inorganic aerosols in the CAMS system, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16085, https://doi.org/10.5194/egusphere-egu23-16085, 2023.

EGU23-17426 | PICO | AS1.6

Extending and Improving JEDI-based Global Aerosol Data Assimilation System for UFS-Aerosols 

Bo Huang, Mariusz Pagowski, Cory Martin, Andrew Tangborn, Maryam Abdi-Oskouei, Jérôme E. Barré, Shobha Kondragunta, Georg Grell, and Gregory Frost

A global aerosol data assimilation (DA) system based on the ensemble-variational (EnVar) application in the Joint Efforts for Data assimilation Integration (JEDI) was recently developed for the Global Ensemble Forecast System - Aerosols (GEFS-Aerosols) in operations at NOAA/NWS/NCEP. The aerosol optical depth (AOD) retrievals at 550 nm are assimilated to improve the GEFS-Aerosols initial conditions and its subsequent forecasts. To account for aerosol emission uncertainty in the ensemble forecasts and thus enhance AOD assimilation, a stochastically-perturbed emission (SPE) approach was implemented in the Common Community Physics Package (CCPP)-based GEFS-Aerosols. The performance of this JEDI-based EnVar aerosol DA system has been evaluated using the CCPP-based GEFS-Aerosols in the near-real time (NRT) experiments at NOAA/OAR/GSL and the global aerosol reanalysis products that  assimilate 550 nm AOD retrievals from the the Visible Infrared Imaging Radiometer Suite (VIIRS) instruments and the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments, respectively. The NRT experiment results are displayed on the GSL website (https://ruc.noaa.gov/projects/nrt/Aerosol-DA/). Both the NRT experiment results and global aerosol reanalyses demonstrate that compared to the six-hour forecasts without AOD assimilation, the analyses and subsequent six-hour forecasts resulting from AOD assimilation show significantly improved agreement with AOD retrievals from VIIRS, MODIS and the Aerosol Robotic NETwork (AERONET), and AOD analyses/reanalyses from NASA and ECMWF. Although AOD retrievals, due to their column-integral nature, provide limited information regarding aerosol compositions and vertical profiles, AOD assimilation in our experiments generally contributes to improved aerosol analyses and forecasts verified against those from NASA and ECMWF.  

One of the ongoing Unified Forecast System (UFS)-Research to Operations (R2O) efforts aims to integrate and improve aerosol prediction within UFS (hereafter referred to as UFS-Aerosols). UFS-Aerosols will eventually replace the standalone GEFS-Aerosols for operations at NOAA/NWS/NCEP. Compared to GEFS-Aerosols, UFS-Aerosols is coupled with NASA's second-generation Goddard Chemistry Aerosol Radiation and Transport (GOCART) model including additional nitrate aerosol species, adopts improved biomass burning and dust emissions, and allows for aerosol-radiation interactions. Motivated by the promising results of assimilating AOD for GEFS-Aerosols and to advance aerosol assimilation and prediction in UFS, we are extending and improving this JEDI-based EnVar aerosol DA system for UFS-Aerosols. It requires further development of AOD forward operator, its tangent linear and adjoint models in JEDI’s Unified Forward Operator (UFO) to accommodate additional nitrate aerosol species in UFS-Aerosols. Enhancements to this DA system for UFS-Aerosols include implementing SPE within UFS-Aerosols to improve background ensemble and implementing assimilation of log-transformed AOD within JEDI to better satisfy the Gaussian assumptions in the DA update. To evaluate these new developments for UFS-Aerosols, cycled DA experiments will be performed to assimilate 550 nm AOD retrievals from VIIRS instruments on board NOAA’s satellites, and verified against various aerosol observations and reanalyses. Results will be presented.

How to cite: Huang, B., Pagowski, M., Martin, C., Tangborn, A., Abdi-Oskouei, M., E. Barré, J., Kondragunta, S., Grell, G., and Frost, G.: Extending and Improving JEDI-based Global Aerosol Data Assimilation System for UFS-Aerosols, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17426, https://doi.org/10.5194/egusphere-egu23-17426, 2023.

Including prognostic atmospheric composition (AC) simulations in numerical weather predication or climate modelling application to exploit AC – weather feedbacks is often prohibited by the high computational cost of adding complex AC simulation to the weather or climate model.  There are in principle two approaches to solve this problem: (i) drastically reduce the complexity of the aerosol and chemistry simulations in the weather model, or (ii)  safe cost by reducing the spatial resolution of the model components simulating the AC processes and implement a coupling mechanism.  

At ECMWF a dual configuration forecast (dcfc) approach for the of the Integrated Forecasting System (IFS) has been developed based on the infrastructure for Object-Oriented Prediction System (OOPS). It enables the coupled simulation of a high-resolution application and a low-resolution application of the IFS and a coupling mechanism. The low-resolution model instance simulates the aerosol and chemistry-processes as activated for the operational AC forecasts by the Copernicus Atmosphere Monitoring Service (CAMS)  

We show first scientific results of this dual configuration forecast (dcfc) for a sever dust storm event in Europe in March 2022. We will discuss to what extent and at what computational cost the dcfc application can forecast the meteorological impact of the dust on radiation and 2m temperatures. We will compare the dcfc result to the more expensive integrated IFS-CAMS configuration as well as to NWP forecast using the aerosol climatology as currently applied in the ECMWF operational weather forecasts.  

How to cite: Flemming, J. and Hamrud, M.: A multiple gird approach for atmospheric composition - aware NWP forecasts with the ECMWF forecast system, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17501, https://doi.org/10.5194/egusphere-egu23-17501, 2023.

EGU23-17561 | ECS | PICO | AS1.6 | Highlight

High-resolution dynamical downscaling of present and future air quality over the South Asia-Cordex domain with a focus on the megacity Delhi, India 

Ummugulsum Alyuz, Ranjeet Sokhi, Kester Momoh, Vikas Singh, Chandra Venkataraman, Arushi Sharma, Ganesh Gupta, Kushal Tibrewal, Ravindra Khaiwal, Suman Mor, and Gufran Beig and the PROMOTE Team

Through a NERC/MOES funded project, PROMOTE, analysis based on WRF and CMAQ models has been conducted to understand the impact of road transport emissions on air quality over Delhi. NCEP/FNL 1 data was used to drive WRF with four nested domains over India with resolutions of 45km, 15 km, 5 km, and 1.6 km for 2018. EDGAR v5.0 emission inventory (for 2015) 2 and Cam-Chem initial and boundary condition data 3 were used to drive the CMAQ model. In the baseline runs, all domains were considered without any change in emissions, while in Scenario 1, road transport sector was removed in the third domain (5km) covering Delhi region. Model performance for NOx, NO2, PM10, PM2.5 and O3 was evaluated with available observations, recognising that air quality and meteorological datasets were limited for the period analysed. In the later part of the study, OSCAR model 4 was used to predict the high-resolution air quality over Delhi and estimate the contributions from road transport emissions. Relative contributions to Delhi's air quality from local and regional long range transport sources are discussed. 

As part of a NERC funded COP26 project on Climate Adaptation for India, an overarching goal of this study is to quantify how air quality changes in South Asia in a changing climate under SSP245 (middle-of-the-road scenario) 5. A dynamical downscaling process was implemented and bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) data 6 was used to drive Weather Research and Forecasting (WRF) model simulations. Simulations have been conducted for the South Asia-Cordex domain for 2015 (representative of 2011-2020 years) and 2050 (representative of 2046-2055 years) with a 27 km grid resolution. The Community Multiscale Air Quality (CMAQ) model was driven with an average of ten years meteorology with future land use land cover, initial and boundary conditions, and future emissions 7 for India. To assess the impact of averaged meteorology on the CMAQ performance, the CMAQ model was run with both ten years' averaged meteorology around 2015 (2011-2020) and only 2015 meteorology.

Although averaging ten years around the desired year suppresses the diurnal variations, it provides an indication of monthly changes in climate and air quality variables. Under the selected SSP245 scenario, the CMAQ model predicted monthly means of PM2.5 anomalies (2050-2015) range over India between 8 to 41 μg/m3. Significant change is PM2.5, PM10, NOx, and O3 anomalies, especially in the urban regions of India, such as Delhi, before and after the Monsoon months (June to October) have been observed.

Financial Support: We acknowledge funding from NERC/MOES (Reference: NE/P016391/1) for the PROMOTE project and NERC funding (Reference: 2021COPA&R48Sokhi) for the COP26 Improving adaptation strategies for climate extremes and air pollution affecting India project.

References

1 NCEP/NOAA/U.S. 2015,  https://doi.org/10.5065/D65Q4T4Z.

2 Crippa M. et al. (2019): http://data.europa.eu/89h/377801af-b094-4943-8fdc-f79a7c0c2d19

3 Buchholz, R. R. et al, (2019). https://doi.org/10.5065/NMP7-EP60

Singh V, et al. (2020) Environmental Pollution, 257, 113623

5 van Vuuren, D.P. et al. (2011). Climatic Change 109, 5. https://doi.org/10.1007/s10584-011-0148-z

6 Xu, Z. et al.  (2021). Sci Data 8, 293. https://doi.org/10.1038/s41597-021-01079-3

7 SMoG-India v1 2015 and 2050 emissions dataset, NERC project.

How to cite: Alyuz, U., Sokhi, R., Momoh, K., Singh, V., Venkataraman, C., Sharma, A., Gupta, G., Tibrewal, K., Khaiwal, R., Mor, S., and Beig, G. and the PROMOTE Team: High-resolution dynamical downscaling of present and future air quality over the South Asia-Cordex domain with a focus on the megacity Delhi, India, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17561, https://doi.org/10.5194/egusphere-egu23-17561, 2023.

EGU23-1439 | ECS | Posters on site | AS1.7

Using MPAS model to forecast the Convectively Induced Turbulence 

Haoming Chen, Xiaoming Shi, Chiristy Yan-yu Leung, Ping Cheung, and St Chan

Convectively induced turbulence (CIT) is a serious aviation hazard and it is challenging to forecast the CIT in the region near convection. Previous studies used reginal model with high resolution or global model with low resolution and selected empirical indices to diagnose the turbulence. In this study, we used The Model for Prediction Across Scales (MPAS) to simulate some cases of CIT reported near Hong Kong. MPAS allows us to use convection-permitting resolution in the interested area while including the global-large scale circulation with coarser resolutions in other regions. The eddy dissipation rate (EDR) is computed to diagnose the potential occurrence of CIT. We compared three methods for calculating EDR from the resolved flow in the MPAS, the first one based on second order structure function, the second one based on Scale-Similarity in Large Eddy Simulation (LES) and the third is Near Cloud Turbulence (NCT) diagnostics by using Convective Gravity Wave Drag. Comparing with the NOAA Graphical Turbulence Guidance (GTG) product and flight data suggests that computing EDR with Scale-Similarity is more effective and accurate than second order structure function and NCT diagnostics. Resolution is also an important factor in forecast, we tested the method in mesh with different resolutions but similar distributions, the results from low resolution simulations can generate a useful turbulence pattern forecast, but the intensity is weak, highlighting the value of high resolution simulations that can resolve convection. We evaluated the sensitivity to several model physics and numeric options in simulations. Those variations can change the EDR prediction by influencing the intensity and the life cycle of the convection. No particular scheme produces systematically more intense turbulence than others, suggesting varying model physics captures some stochasticity of convection. Compared with flight records of EDR along the flight routes, MPAS could produce in three out of five cases showing maximum EDR is close to the observed intensity of turbulence (EDR>0.4). However, in the other two cases, the results are not satisfactory mainly because of significant location biases of the predicted convection. We also add initial condition perturbation-based large ensemble in one case and find it possible to improve the prediction of the failed cases by influencing the position of the convection. Further work should be conducted to prioritize the ensemble members since only a few members can capture the turbulence and doing the average will erase them easily.

How to cite: Chen, H., Shi, X., Leung, C. Y., Cheung, P., and Chan, S.: Using MPAS model to forecast the Convectively Induced Turbulence, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1439, https://doi.org/10.5194/egusphere-egu23-1439, 2023.

EGU23-2556 | ECS | Orals | AS1.7

SST-driven changes in cloud radiative heating in RCEMIP models and observations 

Blaž Gasparini, Aiko Voigt, Giulio Mandorli, and Claudia Stubenrauch

The interactions of ice particles with radiative fluxes in tropical high clouds substantially alter the heating structure within the atmosphere, also known as cloud radiative heating (CRH). CRH influences the upper-tropospheric temperature structure and thus modulates the strength and position of tropical and extratropical circulations. Moreover, it influences the life cycle of tropical high clouds through longwave destabilization of the cloud layer and lifting of clouds by absorption of both shortwave and longwave radiation by ice crystals. A possible change of CRH, for example, due to global warming, can substantially alter the tropical climate.Despite a large body of work that has explored interactions between clouds and radiation, responses of CRH to global warming remain largely unknown. We therefore use idealized SAM cloud-resolving model simulations, the RCEMIP multimodel dataset, and a 15-year-long satellite-derived CRH dataset to explore changes in CRH under different sea surface temperatures.

To a first approximation, the upper tropospheric CRH shifts nearly isothermally to a higher altitude level following a surface warming. In addition, upper-tropospheric CRH in 27 of the 32 analyzed models increase by 0.5 to 10%/K, with a mean value of about 3%/K. Interestingly, the CRH increases despite decreases in upper tropospheric ice water content and cloud fraction. The increase in CRH can be to a large extent explained by an increase in atmospheric transmissivity due to a 2-3 km vertical shift of high clouds, in an environment with decreased air density. Similarly, all models simulate an increase in the upper tropospheric clear-sky radiative cooling in warmer conditions.

Additionally, the CRH response to surface warming can be largely predicted by assuming a nearly isothermal vertical shift of upper tropospheric CRH profiles (as per the fixed anvil temperature hypothesis) following a warmer moist adiabat and by considering the increase in CRH magnitude due to changes in atmospheric density. Therefore, if we know the CRH of a reference climate state, we can, to a good approximation, estimate its response to surface warming.

The modeled CRH vertical shift and increase are confirmed by a 15-year-long satellite-derived tropical CRH dataset. The years with the highest SSTs lead to the most positive CRH that is shifted to higher levels, similarly to what is simulated by RCEMIP models.

How to cite: Gasparini, B., Voigt, A., Mandorli, G., and Stubenrauch, C.: SST-driven changes in cloud radiative heating in RCEMIP models and observations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2556, https://doi.org/10.5194/egusphere-egu23-2556, 2023.

The vertical structure of large-scale tropical circulations is determined by their complex coupling with both deep and shallow convection. This is reflected in our theoretical frameworks for understanding the tropical precipitation distribution, which consist of “deep” theories that focus on overturning circulations that extend throughout the depth of the troposphere and “shallow” theories that focus on low-level convergence driven by boundary-layer pressure gradients. While both types of theories suggest links between low-level thermodynamic fields and the precipitation distribution, shallow theories highlight the importance of the distribution of surface temperature, while deep theories additionally highlight the importance of the low-level humidity. 

Here we use idealised cloud-permitting simulations to elucidate the physical factors that control the vertical structure of tropical circulations. We first demonstrate how the influence of convective entrainment on the lapse rate can act to change the vertical structure of deep tropical circulations, with implications for the behaviour of precipitation in the current and future climate. We further investigate the interaction between deep and shallow tropical circulations  by simulating an idealised overturning circulation over varying surface conditions. By independently varying the sea-surface temperature and moisture availability, the low-level temperature and moisture distributions are manipulated such that the predictions of “deep" and “shallow" theories of the circulation may be distinguished. The results provide insight into the relative roles of oceanic SST gradients and land-ocean contrasts in determining the climatological precipitation distribution in the tropics.

How to cite: Singh, M.: Shallow and Deep Circulations in the Tropical Atmosphere, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3078, https://doi.org/10.5194/egusphere-egu23-3078, 2023.

Radiative-convective equilibrium is the simplest possible way to phrase many questions about a deep-convecting atmosphere and is accessible by a wide range of model types. The radiative-convective equilibrium project (RCEMIP) provides a common configuration, but reveals a large spread in the simulated climate across models, including profiles of temperature and relative humidity. Here we use simple models and theory to understand the intermodel spread in CAPE, relative humidity, and their responses to warming.

Across the RCEMIP ensemble, temperature profiles are systematically cooler than a moist adiabat, consistent with theory that they are set by dilute ascent. As horizontal grid spacing is reduced in models with explicit convection from 1 km to 200 m, CAPE and relative humidity increase. Across all models, CAPE increases with warming at a rate (14-19%/K) greater than that expected from the Clausius-Clapeyron relation. We find that there is higher CAPE (greater instability) in models that are on average moister in the mid-troposphere, which is consistent with the simple plume model of Romps (2016) in which both instability and relative humidity depend on entrainment and precipitation efficiency. The sign of the relationship suggests that differences in entrainment drive the intermodel spread. This relationship is true across both models with explicit and parameterized convection.

To more explicitly evaluate the drivers of the intermodel spread, we use the Romps (2016) model to diagnose theory-implied values of entrainment and precipitation efficiency given the simulated values of CAPE and relative humidity. We then decompose the the variability across models in CAPE and relative humidity (and their responses to warming) into contributions from entrainment, precipitation efficiency, and the depth of the convecting layer. Targeted microphysics parameter perturbation experiments with an individual cloud-resolving model in which precipitation efficiency is varied and explicitly diagnosed provide proof of concept for this decomposition technique. 

How to cite: Wing, A. and Singh, M.: Control of Tropical Stability and Relative Humidity in Radiative-Convective Equilibrium Simulations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3532, https://doi.org/10.5194/egusphere-egu23-3532, 2023.

The initiation of deep convection in a diurnal cycle is still one of the most important uncertainties in a climate numerical model. This is partially due to our poor understanding of the physical mechanisms leading to the transition from shallow to deep convection. In this work, we discuss the role of shallow cumulus clouds in the initiation of deep convection. By using a simple entraining plume model, we show that the interaction between an active and a passive shallow cumulus helps the former to reach higher altitudes and, in the right conditions, may initiate deep convection. It is also shown that the organization of passive and active clouds due to the formation of cold pools may act as a positive feedback. Furthermore, based on the proposed mechanism, a stochastic triggering function is derived, which can be implemented in climate models. As an important feature, the stochastic function is scale-aware, which makes it suitable for simulations at the gray-zone.

How to cite: Vraciu, C.-V.: The role of passive shallow cumuli in the transition from shallow to deep convection, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3561, https://doi.org/10.5194/egusphere-egu23-3561, 2023.

EGU23-4079 | ECS | Orals | AS1.7

Identifying the Deep-inflow Mixing Features in Orographically Locked Diurnal Convection 

Yu-Hung Chang, Wei-Ting Chen, Chien-Ming Wu, Yi-Hung Kuo, and J. David Neelin

This study focuses on the deep-inflow mixing features of the orographically locked diurnal convection, involving interactions between local circulation and the thermodynamic environment of the convection. Under the weak synoptic weather regime, orographically locked diurnal convection is a typical summertime phenomenon in Taiwan, a tropical island in the Asian monsoon region. Numerical simulations are carried out using the vector vorticity equation model with high-resolution Taiwan topography (TaiwanVVM), which can appropriately simulate the characteristics of diurnal convection and the evolution of boundary layer and local circulation. The semi-realistic approach, simplified by observed soundings as the uniform initial condition over the entire domain, emphasizes the decisive environmental factors that modulate the development of convection, representing the variability of the background environment by the ensembles. The analyses by the deep-inflow mixing framework, including the locally-derived convective structures and the upstream moist static energy (MSE) transport, improve the understanding of the interactive physical processes in the boundary layer development and local circulation evolution of orographically locked diurnal convection over complex topography. The convective structures of the deep-inflow mixing, increasing vertical velocity and convective mass flux with height through a deep lower-tropospheric inflow layer, are found in strong convective updraft columns within heavily-precipitating systems over precipitation hotspots. While the topography constrains the location of the convection, enhanced convective development is associated with higher upstream MSE transport through this deep-inflow layer via local circulation, augmenting the rain rate by 35% in precipitation hotspots. The results highlight the importance of non-local dynamical entrainment of the deep-inflow, transporting MSE via local circulation to supply the growth of orographically locked diurnal convection. Thus, the deep-inflow mixing framework can serve as the theoretical basis for describing the orographic locking feature of diurnal convection over complex topography. Guided by the simulations, the Storm Tracker mini-radiosondes are released upstream of the precipitation hotspot, targeting observations within the most common deep-inflow path. Initial field measurements support the presence of high MSE transport within the deep-inflow layer when organized convection occurs at the precipitation hotspot.

How to cite: Chang, Y.-H., Chen, W.-T., Wu, C.-M., Kuo, Y.-H., and Neelin, J. D.: Identifying the Deep-inflow Mixing Features in Orographically Locked Diurnal Convection, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4079, https://doi.org/10.5194/egusphere-egu23-4079, 2023.

EGU23-4150 | Orals | AS1.7

New GSRM global warming simulations and active sensors reveal robust changes of tropical convergence zones in cloud ice space 

Maximilien Bolot, Lucas Harris, Kai-Yuan Cheng, Peter Blossey, Christopher Bretherton, Spencer Clark, Alex Kaltenbaugh, Timothy Merlis, Linjiong Zhou, and Stephan Fueglistaler

Change of the intertropical convergence zone (ITCZ) with global warming has important consequences for the regulation of the tropical climate and for future precipitation projections. Most of the volume of the ITCZ is filled with ice associated with convective anvils, which opens the perspective of using the response of ice clouds to study changes of the tropical convergence zones with global warming. Past studies have shown a decrease of tropical high-cloud fraction with surface warming, whereby the response of anvil clouds is used to interpret the response of ice clouds as a whole. However, tropical clouds organize over a very wide range of scales, meaning that the response of ice clouds is more complex. In particular, precipitating deep convection may represent a small volume of total cloudiness, but it concentrates most of the ascending motion in the tropics and is therefore of crucial importance for the dynamics. Here we show how the high resolution in next generation convection-resolving climate models and in observations can be leveraged to directly measure the response of precipitating deep convection with surface warming in the ice signal. For this purpose, we use the first year-long simulations of global warming ever performed with a Global Storm Resolving Model (GSRM) at 3 km resolution. These simulations use the eXperimental System for High-resolution prediction on Earth-to-Local Domains (X-SHiELD), developed at the Geophysical Fluid Dynamics Laboratory (GFDL). By tracking the response of tropical clouds to surface warming from the response of ice water path (IWP), the vertical integral of ice mixing ratio, we show that the response of precipitating deep convection can be identified at high resolution and that this response, marked by an increase in frequency of very deep convective cores and a decrease in frequency of more moderate convection, is robust in model and active sensor observations. We discuss this result and show how it promotes a simple view of the changes of tropical convergence zones in ice-based coordinates.

How to cite: Bolot, M., Harris, L., Cheng, K.-Y., Blossey, P., Bretherton, C., Clark, S., Kaltenbaugh, A., Merlis, T., Zhou, L., and Fueglistaler, S.: New GSRM global warming simulations and active sensors reveal robust changes of tropical convergence zones in cloud ice space, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4150, https://doi.org/10.5194/egusphere-egu23-4150, 2023.

EGU23-4711 | Posters virtual | AS1.7

Sensitivity of projected storm track and jet latitude changes to the parameterization of convection: implications for mechanisms of the future poleward shift 

Ian White, Chaim Garfinkel, Benny Keller, Orli Lachmy, Ed Gerber, and Martin Jucker

While a poleward shift of the jet stream and storm track in response to increased greenhouse gases appears to be robust, the magnitude of this change
is uncertain and differs across models, and the mechanisms for this change are poorly constrained. An intermediate complexity GCM is used to explore
the factors governing the magnitude of the poleward shift and the mechanisms involved. The degree to which parameterized subgrid-scale convection is inhibited has a leading-order effect on the poleward shift, with a simulation with more convection (and less large-scale precipitation) simulating a significantly weaker shift, and eventually no shift at all if convection is strongly preferred over large-scale precipitation. Many of the mechanisms that have been proposed to lead to the poleward shift are present in all simulations (even those with no poleward shift), and hence we can conclude that these mechanisms are not of leading-order significance for the poleward shift in any of the simulations. In contrast, the thermodynamic budget is able to diagnose the reason the jet and storm track shift differs among the simulations, and helps identify midlatitude latent heat release as the crucial differentiator. These results have implications for intermodel spread in the jet, hydrological cycle, and storm track response to increased greenhouse gases in intermodel comparison projects.

How to cite: White, I., Garfinkel, C., Keller, B., Lachmy, O., Gerber, E., and Jucker, M.: Sensitivity of projected storm track and jet latitude changes to the parameterization of convection: implications for mechanisms of the future poleward shift, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4711, https://doi.org/10.5194/egusphere-egu23-4711, 2023.

EGU23-4968 | ECS | Posters on site | AS1.7

Evaluating Memory Properties in Convection Schemes Using Idealised Tests 

Yi Ling Hwong, Maxime Colin, Philipp Aglas, Caroline Muller, and Steven Sherwood

Two structural assumptions are frequently employed in convective parameterisation: the diagnostic and quasi-equilibrium assumptions. The former assumes an instantaneous relationship between the large-scale environment (“macrostate”) and subgrid-scale convective activity, while the latter postulates that convective processes are almost in equilibrium with slowly evolving large-scale forcing at all times. Both assumptions do not take into account the role of convective memory (“microstate” memory), which is defined as the dependence of convection on its own history. Here, we present the memory behaviour of three convection schemes by comparing their responses in two idealised RCE experiments in single-column models (SCMs) to those of a cloud-resolving model (CRM). Three main findings from these tests will be discussed. First, when the large-scale environment is held constant (“FixMacro”), precipitation remains invariant in time with the Zhang-McFarlane scheme, confirming that the scheme does not parameterise convective memory and is fully diagnostic. The org scheme (Mapes & Neale, 2011) displays similar behaviour to the CRM in that precipitation increases in the first moments after FixMacro starts, with larger entrainment rates associated with slower growth. However, its logarithmic growth shape differs from that of the CRM, which displays exponential growth, and can be explained using the scheme’s governing equations. Second, when the prognostic convective memory variable is set to zero at one time step (essentially wiping out microstate memory), the org scheme displays remarkably similar behaviour to the CRM, with precipitation dropping to zero and then recovering to its RCE value over a recovery time scale tmem. In comparison, precipitation in the LMDZ cold pool scheme (Grandpeix & Lafore, 2010) responds in the opposite direction: it grows and then falls back to its RCE value. Finally, the mean and temporal variance of the org variable were found to correlate strongly with memory strength (tmem), indicating that org has captured important aspects of convective memory. Overall, our results indicate that the org and LMDZ cold pool schemes partially, but do not fully capture CRM memory behaviour and are limited by their structural assumptions. They also demonstrate the usefulness of our simple idealised experiments to probe the memory behaviour of convection schemes. 

How to cite: Hwong, Y. L., Colin, M., Aglas, P., Muller, C., and Sherwood, S.: Evaluating Memory Properties in Convection Schemes Using Idealised Tests, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4968, https://doi.org/10.5194/egusphere-egu23-4968, 2023.

EGU23-5898 | ECS | Posters on site | AS1.7

On the organization of passive shallow cumulus clouds 

Andrei Marin and Cristian-Valer Vraciu

The shallow cumulus clouds are ubiquitous in the atmosphere, populating a large part of the subtropical oceans. They may play a strong climate feedback due to their cooling effect on the Earth atmosphere. As a result, a large number of studies investigated the organization of cumulus clouds and their interaction with the climate. However, the organization of passive shallow clouds and their impact on the atmospheric convection and climate change received very limited attention. In this work, we perform a series of large eddy simulations in order to investigate how the organization and the total cloud cover depends on the relative humidity of the environment. We show that although the active cumulus clouds only show a weak correlation with the relative humidity, the passive clouds are very sensitive to it. We show thus that the cloud cover of the shallow cumuli is very sensitive to the relative humidity which could be very important in the context of the climate change. Furthermore, we formulate a conceptual picture to explain the organization of passive shallow cumulus clouds.

How to cite: Marin, A. and Vraciu, C.-V.: On the organization of passive shallow cumulus clouds, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5898, https://doi.org/10.5194/egusphere-egu23-5898, 2023.

EGU23-6933 | ECS | Orals | AS1.7

Investigating Convective Self-Aggregation in the Transition from Land to Sea 

Irene L. Kruse and Jan O. Haerter

Within the atmospheric modelling community, a large focus in recent years has been on the concept of Convective Self-Aggregation (CSA): In an environment of radiative convective equilibrium, with homogeneous initial conditions and a constant-temperature tropical sea surface, convection can spontaneously aggregate into domain-wide patterns of persistent dry areas and constrained rainy areas over a temporal timescale of weeks to months. CSA, albeit still a modeling paradigm, could reveal the mechanisms behind some of the convective organization observed in the tropics.

This process of forming domain-wide structure can be accelerated to the order of days by imposing oscillating surface temperatures with a large enough amplitude [1]. The ‘diurnally aggregated’ cloud field is similar to CSA as it also constrains the surface rain field to certain parts of the domain. Further, pattern formation was found to initiate first as persistent dry patches in the uppermost layers of the simulated atmosphere. The dry patches subsequently penetrate through to the subcloud layer [2].

In this work we investigate how diurnal surface temperature amplitudes, typical of tropical land, affect the formation of persistent dry patches and the spatio-temporal extent of the emergent mesoscale convective systems. We run a set of cloud resolving simulations initialized with typical profiles of temperature and humidity. We impose a large-amplitude diurnally oscillating surface temperature, which we then set to constant at different times, to see the effect on the diurnally aggregated cloud field. We present the results of this study, which show a strong dependence on the degree of aggregation over ‘land’, in determining the aggregation over ‘sea’, and a form of hysteresis arises.

 

1. Haerter, Jan O., Bettina Meyer, and Silas Boye Nissen. ‘Diurnal Self-Aggregation’. Npj Climate and Atmospheric Science 3, no. 1 (30 July 2020): 1–11. https://doi.org/10.1038/s41612-020-00132-z.
2. Jensen, Gorm G., Romain Fiévet, and Jan O. Haerter. ‘The Diurnal Path to Persistent Convective Self-Aggregation’. Journal of Advances in Modeling Earth Systems 14, no. 5 (2022): e2021MS002923. https://doi.org/10.1029/2021MS002923.

 

How to cite: Kruse, I. L. and Haerter, J. O.: Investigating Convective Self-Aggregation in the Transition from Land to Sea, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6933, https://doi.org/10.5194/egusphere-egu23-6933, 2023.

The difficulty to accurately represent atmospheric convection in numerical weather forecasts contributes to persistent biases in weather and climate simulations – particularly tropical precipitation. Convection-permitting global forecasts are an improvement on global models with parametrized convection schemes, however it is not yet clear whether they improve forecast skill to match or improve upon the current approach of nesting a convection-permitting high-resolution regional model inside a global model with parameterized convection. This is far less computationally expensive than running a global convection-permitting model.

To test this, the Met Office is coordinating a UK K-scale project nesting high resolution (2.2 km) limited area models (LAMs) within global models that have between 5 and 10 km grid resolution. We compare these nested regional models with two different global simulations, run with parameterised and explicit convection science configurations. The 2.2 km resolution LAMs encompass a variety of domains focussing on both tropical land and ocean regions.

Our current work seeks to investigate if and where we see differences in model evolution between the high-resolution nested LAM approach and the explicit convection global driving model.  We focus on an active MJO event in January 2018 where enhanced convection propagated across the Indian Ocean and impacted the Maritime continent. For high-impact events such as this, do we see a marked change in the model forecast when explicitly simulating convection globally rather than in a regional limited area model (as currently used in operational forecasts)? Further, are differences between the global convection permitting and LAM forecasts more pronounced over ocean-dominated regions where the amplitude of the diurnal cycle of convection is smaller?

This talk will summarise our findings in the context of the wider K-scale project, evaluating how our recent work contributes to the development of more accurate weather forecasts.

How to cite: Macholl, J., Jones, R., and Lewis, H.: Globally modelling explicit convection: how does it compare with the nested limited area model approach at high horizontal resolutions?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7082, https://doi.org/10.5194/egusphere-egu23-7082, 2023.

EGU23-7224 | Posters on site | AS1.7

Parametrization of dust storms in the Sahel by cold pools 

Mamadou Lamine Thiam, Frédéric Hourdin, Jean-Yves Grandpeix, Catherine Rio, and Amadou Thierno Gaye

The cold pools, created below cumulonimbus from the evaporation of precipitation, generate the strong winds responsible for the large dust storms called “haboobs” which appear in the Sahel in summer. Most global climate models do not take into account these types of dust emissions due to lack of parameterization of cold pools and associated gusts (Marsham et al. 2011 ; Pantillon et al. 2015).

The introduction of a parameterization of cold pools in the LMDZ climate model has improved the representation of convection, and in particular of the diurnal cycle of continental precipitation in the tropics (Rio et al. 2009). The aim of this work is to develop a parameterization of gusts related to cold pools in order to take into account ‘‘hoobobs’’ in LMDZ model. To do this, we use Large Eddy Simulations (LES) performed on an oceanic domain and in Radiative-Convective Equilibrium (RCE) mode. We use a LES of an oceanic RCE case, easier to analyze because the temperatures are uniform on the surface and therefore the cold pools easier to detect. Before developing a gust parameterization, we evaluate the cold pools parameterization in LMDZ on this RCE case, which has never been done so far. If the comparison confirms the relevance of the scheme and its qualitative match to the LES behavior, is also led to substantial improvements and adjustments to this scheme. Next, we analyze the wind distributions in the LES in order to construct a parametrization based on a probability distibution function of the subgrid scale distribution of the wind which will allow us to take into account the effect of gusts on dust storms. The parametrization relates the moments of the distribution to large-scale wind speed, the spreading speed of the cold pools and the surface fraction covered by the latter. In the following, we will test the parametrization on the LMDZ model by focusing on dust storms in the Sahel during the rainy season.

How to cite: Thiam, M. L., Hourdin, F., Grandpeix, J.-Y., Rio, C., and Gaye, A. T.: Parametrization of dust storms in the Sahel by cold pools, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7224, https://doi.org/10.5194/egusphere-egu23-7224, 2023.

EGU23-9002 | ECS | Posters on site | AS1.7

A Lagrangian View to the Evolution of Convective Updrafts 

Thomas Hutton, John Thuburn, and Robert Beare

The representation of cumulus convection is a known source of uncertainty within current weather and climate models. Where model resolution is too coarse to accurately resolve convection, parameterisations are required to estimate the impact of small-scale convective processes. High resolution large eddy simulations (LES) can be used to diagnose many aspects of convective processes, such as heat and momentum budgets and rates of entrainment. However, LES is computationally expensive, making it impossible to use within operational models. This study aims to bridge the gap between current coarser models and LES by developing a stochastic Lagrangian model to represent an ensemble of air parcels. Vertical velocity, liquid water potential temperature, and total specific humidity are predicted following the ensemble of parcels. The random motions associated with turbulence are represented by a stochastic term within the w-tendency equation. The mean fields which the parcels interact with are defined by an ensemble average of nearby parcels. Several fixers have been developed to ensure that conservation properties are respected. At the current stage of development, the model can represent dry convective boundary layer and shallow convection cases. A theoretical study of the stochastic differential equations is useful to verify the self-consistency of the model and also as a tool for calibrating various parameters within the model. A key question for this project is how well the stochastic parcel model can replicate the statistics of LES results. This will act as a measure of the model’s success, allowing for a deeper understanding on accurately modelling convective processes. Due to the Lagrangian nature of the model, analysis can be conducted upon how the parcels’ characteristics change over time as the parcels experience smaller-scale convective processes such as entrainment. Ultimately, results from this model may yield better understandings of small-scale convective processes. This can create potential for improvements to parameterisations in operational models, reducing model uncertainty generated by convective processes.

How to cite: Hutton, T., Thuburn, J., and Beare, R.: A Lagrangian View to the Evolution of Convective Updrafts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9002, https://doi.org/10.5194/egusphere-egu23-9002, 2023.

The intrinsic failure of eddy-diffusion parameterizations in representing upward transport of heat in the convective boundary layer, recognized since the 70s, has lead to various propositions of parameterizations like counter-gradient terms and third order closures to account for the asymmetry of the vertical transport. An approach that is now well recognized consists in combining a mass flux parameterization of the organized structures of the convective boundary layer with a local TKE closure for small scale turbulence. The idea traces back to a proposition by Chatfield and Brost (1987) and is since often referred to as the Eddy Diffusion Mass Flux (EDMF) approach. The “thermal plume model” developed for LMDZ was the first EDMF scheme published and tested in a climate model (Hourdin et al., 2002). It was first introduced in the LMDZ5B atmospheric component of the IPSL model for CMIP5. However, this first version suffered from youth problems. It is only for CMIP6A, about 20 years after the development of the parameterization, that a first satisfactory version of the model was delivered. Through years, and more often with this last version, the key role of the representation of shallow convection on many component of the system has been realized: 1) the ventilation of air by the subsiding air around thermal plumes dries the surface, reinforcing the near surface evaporation. Representing this convection correctly both over trade winds and subsiding regions in the tropics, together with the associated cumulus and stratocumulus clouds, is one of the key for the reduction of the East Tropical Ocean warm bias; 2) the preconditioning of the deep convection by a phase of shallow convection is a key for a correct representation of the phasing of the diurnal cycle of convective rainfall over continents; 3) the strong diurnal cycle of the convective boundary layer in desert areas is essential to well represent the maximum of near surface wind in the morning, responsible for a maximum of dust emission, when the momentum of the nocturnal low level jet is brought suddenly back toward the surface when reached by the developing dry convection. 4) the thermal plume model being active about on half of the globe all the time, it controls the transport of all trace elements, with some non linear effects when the emissions themselves show a diurnal cycle. In this presentation, we review these lessons learned with LMDZ, identify the issues which should require further developments, and expose how new machine assisted techniques allow to reconcile improvement of parameterizations at process scale and climate model improvement.

Chatfield, R. B., & Brost, R. A. (1987). A two-stream model of the vertical transport of trace species in the convective boundary layer. Journal of Geophysical Research, 92, 13,263–13,276

Hourdin, F., Couvreux, F., & Menut, L. (2002). Parameterisation of the dry convective boundary layer based on a mass flux representation of thermals. Journal of the Atmospheric Sciences, 59, 1105–1123

How to cite: Hourdin, F. and Rio, C.: On the importance of dry and cloudy boundary layer convection and of its parameterization in climate models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9438, https://doi.org/10.5194/egusphere-egu23-9438, 2023.

EGU23-9855 | ECS | Posters on site | AS1.7

Tracking Convective Storms and their Environments with the tobac Tracking Package 

Sean Freeman, Rick Schulte, Gabrielle Leung, and Sue van den Heever

Understanding how convective storms respond to changes in their environment on a local scale is critical to begin to elucidate how Earth’s changing climate will affect storms globally. There is now a vast amount of storm-scale observational data, including from geostationary and low-earth orbiting satellites and ground-based observing systems. However, employing these datasets to build comprehensive databases of convective storms and the local environments that form them requires new analysis methodologies. Here, in preparation for the NASA INCUS satellite mission, we have used the tobac tracking package to identify, track and analyze storms and their environments with these big datasets. Using tobac to track storms with geostationary satellite and ground-based radar data, we have built a comprehensive, months-long database of convective storms over their entire lifetime. For each individual convective storm, the database contains their formation environments (including convective available potential energy, wind shear, etc.), evolution over time, and, where applicable, additional data, such as those from low earth orbiting satellites. In this presentation, we will employ this vast database of clouds and storms to quantify the relationship, on a storm scale, between thermodynamic and dynamic environments and storm properties, including lifetime, growth rate, and ice and liquid water paths. 

How to cite: Freeman, S., Schulte, R., Leung, G., and van den Heever, S.: Tracking Convective Storms and their Environments with the tobac Tracking Package, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9855, https://doi.org/10.5194/egusphere-egu23-9855, 2023.

EGU23-11285 | Orals | AS1.7

Tropical Convection through the Lens of the INCUS Mission 

Susan van den Heever, Ziad Haddad, Brenda Dolan, Sean Freeman, Leah Grant, Pavlos Kollias, Gabrielle Leung, Johnny Luo, Peter Marinescu, Derek Posselt, Kristen Rasmussen, Prasanth Sai, Richard Schulte, Graeme Stephens, Rachel Storer, and Hanii Takahashi

The convective mass flux within tropical convection influences the large-scale circulation, drives cloud radiative forcing, has integral links to the production of fresh water, and impacts extreme weather. CMF forms the focus of the recently selected Investigation of Convective Updrafts (INCUS) mission to be launched in 2026. This NASA mission is comprised of 3 spacecraft, all of which will carry a Ka-band cloud radar. One spacecraft will also carry a passive microwave radiometer. The 3 smallsats are to be separated by time intervals of 30, 90 and 120 seconds, thus allowing for the rapid and systematic sampling of the same storm with all three spacecraft. These time intervals (delta-ts) also facilitate the investigation of the magnitude and evolution of CMF, which will be examined as a function of storm type, storm lifecycle and environmental properties. INCUS will therefore provide the first global systematic investigation into CMF and its evolution within deep tropical convection.

A wide range of research tasks have been conducted in preparation for the INCUS mission and the development of the INCUS algorithms including: (1) running and analyzing extensive suites of large-domain, high-resolution model simulations; (2) examining ground-based Doppler radar observations obtained using adaptive scanning techniques during several recent field campaigns; and (3) evaluating anvil characteristics using passive microwave radiometer and geoIR data. This talk will focus on three specific highlights arising from these modeling and observational analyses. First, we will examine the temporal scales of updraft variability. Second, we will analyze the relationship between ice water path cores and convective updrafts. Finally, we will demonstrate proof of the INCUS delta-t concept linking changes in reflectivity to CMF through the use of ground-based radar analyses.

How to cite: van den Heever, S., Haddad, Z., Dolan, B., Freeman, S., Grant, L., Kollias, P., Leung, G., Luo, J., Marinescu, P., Posselt, D., Rasmussen, K., Sai, P., Schulte, R., Stephens, G., Storer, R., and Takahashi, H.: Tropical Convection through the Lens of the INCUS Mission, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11285, https://doi.org/10.5194/egusphere-egu23-11285, 2023.

EGU23-12581 | ECS | Posters on site | AS1.7

No evidence of spatial feedbacks causing convective clustering in the Tropical Western Pacific 

Alejandro Casallas, Adrian Tompkins, and Michie De Vera

Idealized high-resolution models show spontaneous aggregation of tropical convection on the beta-mesoscale driven by radiative feedbacks, and the resulting drying implies a potentially important impact on climate sensitivity missing in classic convective parameterization schemes. Here, we combine multiple state-of-the-art observations and reanalysis of the tropical atmosphere and ocean in a 1000 x 700 km region in the tropical Western Pacific warm pool region, along with numerical models and machine learning techniques to demonstrate that in boreal summer, while radiative and surface fluxes act to cluster convection, the convection remains in a random configuration as evidenced by very limited spatial variability in total column humidity. Instead, in the winter/spring period, when the warm pool is displaced southwards, the region lies on the warm pool boundary with stronger north-south surface temperature gradients. Convection usually remains strongly organized in these periods but is interspersed with occasional random episodes. This entails a sudden flipping into the random state associated with the southerly flow anomalies that advect convection and humidity over the cooler sea surface temperature (SST) regions. Observations and models suggest that this advection of humidity is the principal driver of organization and disorganization of convection and that diabatic feedbacks instead always act to try and cluster convection. Results also indicate that when convection is organized, the atmosphere is significantly drier than when convection is random and that the Longwave (LW) clear-sky top of atmosphere flux is significantly larger in the organized state, principally due to the moisture differences between both configurations. The LW all-sky flux difference between both states is less significant compared to the LW clear-sky because it is largely driven by the cloud cover, which, although smaller for the organized state, does not differ significantly. These differences between organized and random convective states, and the role of the diabatic processes in providing forcing for aggregation, mostly reproduce the findings of idealized models. However, this study indicates that in the real tropical atmosphere diabatic forcing is inadequate to lead to aggregation on its own over homogeneous SSTs, and instead, spatial SST gradients and large-scale dynamics are key to driving aggregation and determining its breakup over the warm pool region.

How to cite: Casallas, A., Tompkins, A., and De Vera, M.: No evidence of spatial feedbacks causing convective clustering in the Tropical Western Pacific, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12581, https://doi.org/10.5194/egusphere-egu23-12581, 2023.

EGU23-13504 | Posters virtual | AS1.7

Response of Mature Storms to Soil Moisture State in Global Hotspot Regions 

Emma Barton, Cornelia Klein, Christopher Taylor, John Marsham, and Douglas Parker

Mesoscale Convective Systems (MCSs) represent some of the most intense and destructive thunderstorms in the world. Understanding the physical processes that drive these storms and influence their characteristics is vital for hazard prediction and mitigation. 

A significant amount of research in the “natural laboratory” of West Africa has shown that soil moisture heterogeneity on different spatial scales can influence the location of convective initiation (10s of km) and the intensification of remotely triggered storms (100s of km).

Previous studies have demonstrated that the control of soil moisture state on convective initiation identified in West Africa is also important elsewhere in the world whereas very little is known about the influence of surface conditions on travelling storms in other regions.

In the current work we combine satellite observations and reanalysis data to characterise the impact of pre-storm soil moisture conditions on the atmospheric environment and characteristics of mature storms in seven MCS hotspot regions, West Africa, South Africa, South America, Great Plains, India, China and Australia. 

We observe a clear latitudinal dependence of the coupling signal with distinct differences between regions where convection is predominately driven by monsoonal or frontal dynamics. However our results suggest that in all regions, large-scale (100s of km) soil moisture gradients are having an impact on convection within mature MCSs through moderation of the climatological temperature gradient in the lower atmosphere, which influences factors that favour convection such as shear and convergence.

How to cite: Barton, E., Klein, C., Taylor, C., Marsham, J., and Parker, D.: Response of Mature Storms to Soil Moisture State in Global Hotspot Regions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13504, https://doi.org/10.5194/egusphere-egu23-13504, 2023.

EGU23-13744 | Posters on site | AS1.7

The Diurnal Cycle of the Cloud Radiative Effect of Deep Convective Clouds over Africa from a Lagrangian Perspective 

William Jones, Martin Stengel, and Philip Stier

Tropical deep connective clouds (DCCs) have large top of atmosphere (ToA) cloud radiative effects (CREs) in both the shortwave (SW) and longwave (LW), which both have average magnitudes of greater than 100 Wm-2. Due to the opposite sign of the two components, the overall ToA CRE is generally assumed to average to approximately 0 Wm-2. Although there are a number of mechanisms that contribute to this balance, the fact that the daytime only SW CRE balances with the LW CRE indicates that the diurnal lifecycle of DCCs is a key component of this balance. Understanding how the diurnal cycle of DCCs influences their CRE is vital for understanding how any changes in their diurnal cycle of these clouds may influence the climate.

 

A year-long dataset of retrieved cloud properties and derived broadband radiative fluxes has been produced by the ESA Cloud CCI project using temporally highly resolved satellite observations. Using a novel method, we are able to detect and track both isolated DCCs and large, mesoscale convective systems (MCSs) over their entire lifecycle. We explicitly retrieve the cloud properties and CREs of DCCs over Africa, and how these properties change over the lifecycle of approximately 100,000 observed clouds. We find that the mean anvil SW CRE greatly varies depending on the initiation time of day and the lifetime of the DCC, whereas the LW CRE is consistent throughout the diurnal cycle and varies primarily with cloud top temperature.

 

As a result of our study we can confirm that the mean observed ToA CRE of all DCCs (integrated over area and lifetime) is indeed approximately 0 Wm-2, but very few DCCs individually have mean CREs near this value. Instead, we find that DCCs occurring during the daytime have a large cooling effect, and those at nighttime have a warming effect, resulting in a bimodal distribution. While MCSs make the largest contribution to the overall effect due to their large areas and lifetimes, because they tend to exist during both nighttime and daytime the overall magnitude of their ToA CREs tend to be smaller than those of isolated DCCs. As a result, factors which influence the diurnal cycle of deep convection – such as changes in CAPE generation or convective inhibition – may have a more important influence on the properties of isolated DCCs rather than larger MCSs.

How to cite: Jones, W., Stengel, M., and Stier, P.: The Diurnal Cycle of the Cloud Radiative Effect of Deep Convective Clouds over Africa from a Lagrangian Perspective, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13744, https://doi.org/10.5194/egusphere-egu23-13744, 2023.

EGU23-13748 | ECS | Posters on site | AS1.7

Sub-mesoscale temperature variability in observed and simulated convective cold pools 

Bastian Kirsch, Leah D. Grant, Nicholas M. Falk, Christine A. Neumaier, Jennie Bukowski, Felix Ament, and Susan C. van den Heever

The spatial and temporal variability of air temperature represents the imprint of various meteorological processes, ranging from microscale turbulence to synoptic-scale weather systems. Convective cold pools, formed by evaporatively cooled downdrafts of precipitating clouds, are known to be an important source of mesoscale variability over mid-latitude land. Cold pools both directly perturb the near-surface temperature field and influence variability by controlling larger-scale convective organization. However, their impact on the sub-mesoscale (100 m to 10 km) temperature variability is unclear due to insufficient observational data. Consequently, the validation of sub-mesoscale variability in numerical weather prediction (NWP) and Large-Eddy Simulation (LES) models is also impeded.

In this study, we apply the variogram framework to determine sub-mesoscale temperature variability in observations as well as in idealized and realistic simulations of cold pool events. The basis of the analyses are actual and virtual observations of a dense network of 99 surface measurement stations as part of the Field Experiment on Submesoscale Spatio-Temporal Variability in Lindenberg (FESSTVaL) conducted in eastern Germany during summer 2021. The observed variogram averaged over the lifetime of a cold pool shows enhanced temperature variance at scales between about 1 km and 15 km compared to well-mixed boundary layer conditions, although the magnitude of the perturbation strongly varies for single time steps. Except for the intensification phase, the cold pool generally reduces the temperature variability at sub-km scales compared to pre-cold pool conditions. This suggests smoothing of sub-km temperature gradients by enhanced mixing near the surface as well as damped turbulent surface fluxes.

Idealized cold pool simulations at LES grid spacings capture the overall variogram shape and evolution well but show the largest uncertainty for sub-km scales as compared to the observed variograms. The results are sensitive to the sampled lifetime stage of the cold pool, its environmental conditions, and the model representation of dissipation time scales and turbulent surface fluxes. These findings can help to identify the spatial and temporal scales of variability that are relevant to correctly simulate convective processes in the atmosphere and their interaction with the land surface.

How to cite: Kirsch, B., Grant, L. D., Falk, N. M., Neumaier, C. A., Bukowski, J., Ament, F., and van den Heever, S. C.: Sub-mesoscale temperature variability in observed and simulated convective cold pools, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13748, https://doi.org/10.5194/egusphere-egu23-13748, 2023.

EGU23-13971 | ECS | Posters on site | AS1.7

The Relationship Between Isolated Deep Convection Initiation and Topography in the North China Area 

Guilin Lu, Yangze Ren, Shizuo Fu, and Huiwen Xue

The characteristics of isolated deep convection initiation (DCI) and its relation to topography in the North China area are studies statistically and numerically. The infrared brightness temperature data from satellite Himawari-8 are utilized to identify DCI events in three summers. A total of 2534 DCI events are obtained and their locations show clustering over mountains and hills, suggesting the significance of local topography. Topography is described with elevation and relief amplitude. DCI events and grid boxes are counted. DCI events per grid box increases with elevation and relief amplitude. Among different types of topography, DCI is favored in mountains and hilly areas. Moreover, the morning cloud cover condition also shows notable impact on the relation of DCI and topography. For the regime characterized with less morning clouds (regime one), DCI strongly depends on elevation and relief amplitude, while for the regime with more morning clouds (regime two), topography shows a moderate impact on DCI. The time of DCI events are also recorded, and regime one shows a stronger diurnal variation and a peak occurring 2 hours earlier than that of regime two. The synoptic patterns show the difference of large-scale environment between the two regimes, which can explain their differences in DCI to some extent. To clarify the mechanism of topographic effect in DCI process, quasi-idealized numerical simulation in North China is conducted with WRF. The averaged 6-hourly ERA-Interim reanalysis data, which can maintain the major patterns of large-scale circulations, are inputted into the model as initial and boundary conditions. The elevation and relief amplitude of the study domain is varied in the model. The preliminary result shows that the speed of upscale convection growth changes with elevation and relief amplitude, which indicates that mechanisms involving topography-induced variation of solar heating may exist and need further numerical study. We suggest that special attention should be paid to elevation and relief amplitude (or topography type), as well as morning cloud cover condition when forecasting DCI in the North China area and mountainous areas around the world.

How to cite: Lu, G., Ren, Y., Fu, S., and Xue, H.: The Relationship Between Isolated Deep Convection Initiation and Topography in the North China Area, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13971, https://doi.org/10.5194/egusphere-egu23-13971, 2023.

EGU23-14317 | ECS | Orals | AS1.7

Using statistical emulation to quantify microphysical uncertainties for the Andreas hailstorm in 2013 

Lena Frey, Corinna Hoose, Michael Kunz, Annette Miltenberger, and Patrick Kuntze

We investigate microphysical uncertainties in hailstorms using statistical emulation in a single model framework with the objective to disentangle the relative contributions from aerosols, microphysical parameters and environmental conditions to the uncertainty in cloud-, precipitation- and hail-related parameters.

Our selected case study is the Andreas hailstorm on 28 July 2013 in the Neckar Valley and over the Swabian Jura in Southwest Germany. We perform model simulations on cloud-resolving scale with the numerical weather prediction model ICON coupled with the aerosol module ART (ICON-ART). We use a two-moment cloud microphysics scheme with a representation of ice nucleation by dust aerosols.
We generated a perturbed parameter ensemble (PPE) to sample uncertainties in cloud-, precipitation- and hail related parameters. Six parameters from the categories aerosols, microphysics and environmental conditions were jointly perturbed, namely the cloud condensation nuclei (CCN) and ice nuclei (IN) concentrations, the riming efficiency of graupel and hail, the convective available potential energy (CAPE) and vertical wind shear. The defined parameter ranges are based on forecast analysis and literature. We used the maximin Latin hypercube algorithm to distribute the parameters well-spaced in the six-dimensional parameter uncertainty space. For these six parameters, an ensemble of 90 members was generated and in addition a smaller independent ensemble of 45 members serves for validation.

We used the Gaussian process emulation and developed emulators for hail- and precipitation related output variables. To quantify contributions to the uncertainty in the output variables from the perturbed parameters individually as well as interactions between them, a variance-based sensitivity analysis was performed. We will present first results, which reveal the importance of the CCN concentration for controlling the number concentration of hail particles as well as the CCN concentration and environmental conditions for controlling the amount of hail and precipitation in the model. The geographical distribution of hail and precipitation shows a large variety among the ensemble members, with storm tracks shifted further to the north or south compared to the reference simulation. The path of the storm track is thereby mainly controlled by CAPE and the vertical wind shear, however, aerosol parameters seem to be important for the development of multiple storm tracks. 

How to cite: Frey, L., Hoose, C., Kunz, M., Miltenberger, A., and Kuntze, P.: Using statistical emulation to quantify microphysical uncertainties for the Andreas hailstorm in 2013, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14317, https://doi.org/10.5194/egusphere-egu23-14317, 2023.

EGU23-14672 | ECS | Posters on site | AS1.7

Modulation of Maritime Continent convection by the MJO: differences between parametrized and explicit convection 

Dan Shipley, Emma Howard, and Steven Woolnough

Convection over the Maritime Continent has large impacts for local extreme weather, as well as for global weather and climate. However, this convection and its impacts are poorly represented in current weather and climate models. This is largely due to complex multi-scale interactions between convection and the ocean, intricate island coastlines and topography, equatorial waves, and larger-scale dynamics such as the Madden-Julian oscillation (MJO). In order to better understand the modulation of convection by the MJO, and its representation in current models, we developed a new modelling suite that couples the Met Office Unified Model to a thermodynamic mixed-layer ocean model with additional corrections to account for ocean dynamics. This allows two-way interactions between the atmosphere and ocean on convection-relevant timescales without the expense of a full dynamical ocean model. We present results from simulations of 10 DJF seasons over the Maritime Continent at grid spacings of 12km (with a mass flux convection scheme) and 2km (without).  

We investigated the modulation of large-scale convective heating and moistening by MJO phase in both models. We show that: 

  • The 2km suite has more variability by MJO phase, and this variability is more realistic than that in the 12km suite when compared to observational data; 
  • There is more variability in the type of convection (defined by the shape of heating/moistening profiles) between MJO phases in the 2km suite; 
  • The dominant variation is between different types of convection in the two suites. 

We also present preliminary results on the modulation by the MJO of basic properties of the cloud field like feature size, and feature isotropy.  

How to cite: Shipley, D., Howard, E., and Woolnough, S.: Modulation of Maritime Continent convection by the MJO: differences between parametrized and explicit convection, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14672, https://doi.org/10.5194/egusphere-egu23-14672, 2023.

EGU23-15870 | ECS | Orals | AS1.7

Extreme Precipitation in Tropical Squall Lines 

Sophie Abramian, Caroline Muller, and Camille Risi

Squall lines are the consequence of the interaction of low-level shear with cold pools associated with convective downdrafts. Beyond a critical shear amplitude, squall lines tend to orient themselves at an angle with respect to the low-level shear. While the mechanisms behind squall line orientation seem to be increasingly well understood, uncertainties remain on the implications of this orientation. Roca & Fiolleau 2020 show that long lived mesoscale convective systems, including squall lines, are disproportionately involved in rainfall extremes in the tropics. One may then question whether the orientation of squall lines has an impact on rainfall extremes, and if so, why.

Using a cloud-resolving model, we perform idealized simulations of tropical squall lines by imposing a vertical wind shear in radiative-convective equilibrium. Our results show that precipitation extremes in squall lines are 40% more intense in the critical case and remain 30% superior in the supercritical regime. With a theoretical scaling of precipitation extremes (Muller & Takayabu 2019), we show that the condensation rates control the amplification of precipitation extremes in tropical squall lines, mainly due to its dynamic component. The critical case is not only optimal for squall line orientation, but also for the cloud base velocity intensity of new convective cells.

How to cite: Abramian, S., Muller, C., and Risi, C.: Extreme Precipitation in Tropical Squall Lines, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15870, https://doi.org/10.5194/egusphere-egu23-15870, 2023.

EGU23-1071 | Orals | AS1.8

Radiation, Clouds, and Self-Aggregation in RCEMIP Simulations 

Chris Holloway, Kieran Pope, Thorwald Stein, and Todd Jones

The responses of tropical anvil cloud and low-level cloud to a warming climate are among the largest sources of uncertainty in our estimates of climate sensitivity. However, most research on cloud feedbacks relies on either global climate models with parameterized convection, which do not explicitly represent small-scale convective processes, or small-domain models, which cannot directly simulate large-scale circulations. We investigate how self-aggregation, the spontaneous clumping of convection in idealized numerical models, depends on cloud-radiative interactions with different cloud types, sea surface temperatures (SSTs), and stages of aggregation in simulations that form part of RCEMIP (the Radiative-Convective Equilibrium Model Intercomparison Project). Analysis shows that the presence of anvil cloud, which tends to enhance aggregation when collocated with anomalously moist environments, is reduced in nearly all models when SSTs are increased, leading to a corresponding reduction in the aggregating influence of cloud-longwave interactions. We also find that cloud-longwave radiation interactions are stronger in the majority of General Circulation Models (GCMs), typically resulting in faster aggregation compared to Cloud-system Resolving Models (CRMs). GCMs that have stronger cloud-longwave interactions tend to aggregate faster, whereas the influence of circulations is the main factor affecting the aggregation rate in CRMs.

How to cite: Holloway, C., Pope, K., Stein, T., and Jones, T.: Radiation, Clouds, and Self-Aggregation in RCEMIP Simulations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1071, https://doi.org/10.5194/egusphere-egu23-1071, 2023.

EGU23-2791 | ECS | Orals | AS1.8

Turbulence properties inside and outside trade-wind cumulus clouds 

Jakub Nowak, Marta Wacławczyk, and Szymon Malinowski

Shallow trade-wind cumulus clouds originate from thermals which rise from the turbulent subcloud layer and penetrate high enough to reach their lifting condensation level. Those thermals transport heat and moisture into the cloud layer. Analogously, the subject of such a transport can be the small-scale turbulence.

Turbulence measurements near the cloud base and in the subcloud layer were performed in the course of the EUREC4A field campaign by the ATR research aircraft in a large number of repeatable flight segments (Brilouet et al., 2021). In this study, we exploit this extensive dataset to derive properties of turbulence corresponding to short 'local' domains, of the size of the order of 100 m, e.g. turbulence kinetic energy dissipation rate, anisotropy and inertial range scaling. Taking advantage of the substantial amount of data provided by the EUREC4A measurements, we compare the statistics of those parameters between the areas inside cumulus clouds, outside them at the same altitude and at three levels inside the subcloud layer.

Such a comparison indicates that the character of small-scale turbulence inside cumulus clouds can be considered comparable to the one observed in the subcloud layer but significantly differs from that observed at the same level outside the clouds. As the cloud fraction at cloud base is typically rather a small number (about 4% during EUREC4A), it is in consequence inherently difficult for large scale models to accurately parameterize the intensity of turbulence and mixing in the trade-wind regime.

How to cite: Nowak, J., Wacławczyk, M., and Malinowski, S.: Turbulence properties inside and outside trade-wind cumulus clouds, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2791, https://doi.org/10.5194/egusphere-egu23-2791, 2023.

EGU23-4127 | ECS | Posters virtual | AS1.8

Cloud Feedback on Earth's Long-Term Climate Simulated by a Near-Global Cloud-Permitting Model 

Mingyu Yan, Jun Yang, Yixiao Zhang, and Han Huang

The Sun becomes brighter with time, but Earth's climate is roughly temperate for life during its long-term history; for early Earth, this is known as the faint young Sun problem (FYSP). Besides the carbonate-silicate feedback, recent researches suggest that a long-term cloud feedback may partially solve the FYSP. However, the general circulation models they used cannot resolve convection and clouds explicitly. This study re-investigates the clouds using a near-global cloud-permitting model without cumulus convection parameterization. Our results confirm that a stabilizing shortwave cloud feedback does exist, and its magnitude is ≈6 W m−2 or 14% of the energy required to offset a 20% fainter Sun than today, or ≈10 W m−2 or 16% for a 30% fainter Sun. When insolation increases and meanwhile CO2 concentration decreases, low-level clouds increase, acting to stabilize the climate by raising planetary albedo, and vice versa.

How to cite: Yan, M., Yang, J., Zhang, Y., and Huang, H.: Cloud Feedback on Earth's Long-Term Climate Simulated by a Near-Global Cloud-Permitting Model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4127, https://doi.org/10.5194/egusphere-egu23-4127, 2023.

EGU23-4307 | ECS | Orals | AS1.8

The Sugar-To-Flower Shallow Cumulus Transition Under the Influences of Diel Cycle and Free-Tropospheric Mineral Dust 

Pornampai Narenpitak, Jan Kazil, Takanobu Yamaguchi, Patricia Quinn, and Graham Feingold

A shallow cumulus cloud transition from a sugar to flower type of organization occurred under a layer of mineral dust on 2nd February 2020, during the multinational Atlantic Tradewind Ocean-Atmosphere Mesoscale Interaction Campaign (ATOMIC) and the Elucidating the Role of Clouds-Circulation Coupling in Climate (EUREC4A) campaigns. Lagrangian large eddy simulations following an airmass trajectory along the tradewinds are used to explore radiative impacts of the diel cycle and mineral dust on the sugar-to-flower (S2F) cloud transition. The large-scale meteorological forcing is derived from the ECMWF Reanalysis 5th Generation (ERA5) and based on aerosol measurements from the U.S. Ronald H. Brown Research Vessel and the French ATR-42 Research Aircraft during the field campaigns. A 12-hr delay in the diel cycle accelerates the S2F transition at night, leading to more cloud liquid water and precipitation. The aggregated clouds generate more and stronger cold pools, which alter the original mechanism responsible for the organization. Although there is still mesoscale moisture convergence in the cloud layer, the near-surface divergence associated with cold pools transports the subcloud moisture to the drier surrounding regions. New convection forms along the cold-pool edges, generating new flower clouds. The modulation of the surface radiative budget by free-tropospheric mineral dust poses a less dramatic effect on the S2F transition. Mineral dust releases longwave radiation, reducing the cloud amount at night, and absorbs shortwave radiation during the day, cooling the boundary-layer temperature and increasing the overall cloud amount. Cloud-top radiative heating because of more clouds strengthens the mesoscale organization, enlarging the aggregate areas, and increasing the cloud amount further.

How to cite: Narenpitak, P., Kazil, J., Yamaguchi, T., Quinn, P., and Feingold, G.: The Sugar-To-Flower Shallow Cumulus Transition Under the Influences of Diel Cycle and Free-Tropospheric Mineral Dust, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4307, https://doi.org/10.5194/egusphere-egu23-4307, 2023.

EGU23-4689 | Posters virtual | AS1.8

What explains the population of daytime, optically-thin clouds below one km in the marine trade wind region? 

Paquita Zuidema, Isabel McCoy, Michael Perez, and Sunil Baidar

The cloud fraction of shallow non-precipitating cumulus residing at the lifting condensation level (LCL) increases in the afternoon, most evident in airborne lidar observations from EUREC4A. Observations from the HALO platform and from the R/V Ronald H. Brown are used to articulate the responsible process. Three hypotheses are investigated: 1) afternoon increases of the ocean sea surface temperature help support buoyancy fluxes that lift air parcels to saturation, as seen in tropical regions under low wind speeds; 2) shortwave absorption of the sub-cloud layer helps deepen the sub-cloud layer, so that its mixed-layer height can reach the LCL; 3) clouds form where the cloud layer is already moist. We invite the reader to take a moment here to choose which hypothesis you think is correct.

Analysis to date suggests #3 is the correct explanation. If so, then the next question is to identify why the daytime cloud layer is more or less moist in some places and times. Ideas for this can either be moisture redistribution from shallow circulations occurring at scales of approximately 200 km, or, moisture transport occurring at larger scales. These will be explored prior to the meeting, as well as ramifications for the diurnal cycle.

How to cite: Zuidema, P., McCoy, I., Perez, M., and Baidar, S.: What explains the population of daytime, optically-thin clouds below one km in the marine trade wind region?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4689, https://doi.org/10.5194/egusphere-egu23-4689, 2023.

The subtropical marine stratocumulus-to-cumulus cloud transition and associated cloud size distributions are studied using Large-Eddy Simulations based on EUREC4A data. The simulations with the DALES code follow a Lagrangian trajectory from initially overcast stratocumulus to the tropical shallow cumulus region at the HALO flight site near Barbados, covering four days and three complete diurnal cycles. Mean state and bulk properties for different domain sizes are evaluated against aircraft data. In addition, time-continuous high-frequency data from Geostationary Operational Environmental Satellite (GOES) are used to investigate the evolution of cloud size distributions, focusing on the diurnal evolution of mesoscale cloud features. TOA brightness temperature data from GOES is used at a spatial resolution of 2x2 km2 to characterize cloud populations and cloud morphology. These are compared to TOA brightness temperatures calculated from DALES output using the RRTOV simulator, as applied to subdomain-averages of similar dimensions. We find that the simulation with the largest domain size (100x100 km2) best reproduces the observed boundary layer and cloudy states at the HALO target site. The same applies to the amplitude and evolution of cloud cover as detected by GOES. The upstream nocturnal flower cloud organization is also reproduced, albeit with a slight time delay. 

How to cite: Ghazayel, S. and Neggers, R.: Evaluation of the diurnal evolution of flower cloud organization in multi-day Lagrangian large-eddy simulations based on EUREC4A against GOES satellite data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4907, https://doi.org/10.5194/egusphere-egu23-4907, 2023.

Mesoscale vertical velocity is a key element to understand links between clouds, radiation and circulation. However, in situ measurements of this variable remain sparse and costly.

Here, we present a method to estimate clear-sky free tropospheric mesoscale vertical motion from rapid-scan geostationary satellite radiance measurements in the water vapour absorption band. Subsidence is indeed associated with drying and a decrease of emission level height (and conversely for ascendance). Under basic physical assumptions, the associated temporal changes in brightness temperature can be quantitatively related to vertical velocity.

The retrieval method is evaluated against in situ observations from EUREC4A and OTREC field campaigns that sampled respectively the winter trades and the intertropical convergence zone. Although suffering from significant error bars (+/-4hPa/hr), retrievals are able to reproduce the general temporal evolution and spatial patterns of mid-tropospheric mesoscale vertical motion.

The retrieval method is further evaluated using kilometer-scale simulations associated with a radiative transfer code. Basic climatological features are captured such as the distribution of mesoscale vertical velocity or its influence on cloud cover.

Despite notable drawbacks, the method is able to provide time-continuous estimations of vertical velocity in clear sky regions of the whole tropical belt at the scale of the pixel of the satellite imager. First results suggest that mesoscale (20-200km) vertical velocity structures are ubiquitous in the tropical free troposphere.

These observations could prove valuable for studying dynamical links between deep convection and its environment, especially in association with the new generation of satellites, that will provide measurements of in-cloud convective mass flux and clear-sky time-continuous water vapour and temperature profiles.

How to cite: Poujol, B. and Bony, S.: A method to estimate clear sky mesoscale vertical motion from geostationary satellite imagery, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5009, https://doi.org/10.5194/egusphere-egu23-5009, 2023.

EGU23-5585 | Orals | AS1.8

Impact of elevated Saharan Air layer on shallow marine convection 

Silke Gross, Manuel Gutleben, and Martin Wirth

Mineral dust is one of the major contributors to the global aerosol load with the Sahara being its largest source. Dust particles can be transported over many days and thousands of kilometers. The main transport route spans from Africa over the Atlantic Ocean towards the Caribbean. Most of the time dust-transport takes place in the so-called Saharan Air Layer (SAL).  During its transport the SAL affects the Earth’s atmosphere by scattering and absorption of solar and terrestrial radiation, and by changing cloud evolution and cloud properties. The main season for the transatlantic dust transport is during the boreal summer months. However, dust can be transported towards the Caribbean also during wintertime, although this happens with less frequency.

Airborne lidar measurements with the combined water vapor differential absorption and high spectral resolution lidar system WALES provide simultaneous measurements of the water vapor mixing ratio and of aerosol properties. We use the measurements during the NARVAL-II experiment in August 2016 and during the EUREC4A experiment in January/February 2020 to characterize the long-range transported SAL in summer- and in wintertime, and to investigate its radiative effect and its impact on the subjacent shallow marine trade wind convection. We found, that a small amount of water vapor embedded in the SAL has a strong impact on the radiative heating effect of this layer and consequently also on the atmosphere’s stability. During summertime, when the SAL is well separated from the marine boundary layer, the radiative effect of the SAL dominates. The evolution of shallow marine clouds below the SAL is suppressed. In wintertime, the SAL is transported at lower altitudes and the dust layer is frequently mixed into the marine boundary layer. During this time of the year the effect of the SAL on the evolution and lifetime of marine trade wind convection is much more complex, as the dust particles within the SAL might additionally act as cloud or ice nuclei.

In our presentation we will give an overview of the performed measurements and the radiative transfer calculations. We will present the radiative effects of the separated summertime SAL, and show first results of the impact of the wintertime SAL on the atmosphere’s stability and cloud properties.

How to cite: Gross, S., Gutleben, M., and Wirth, M.: Impact of elevated Saharan Air layer on shallow marine convection, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5585, https://doi.org/10.5194/egusphere-egu23-5585, 2023.

EGU23-5796 | Posters on site | AS1.8

Tracking Clouds: Comparing Geostationary Satellite Observations and Model Data 

Felix Müller, Torsten Seelig, and Matthias Tesche

Tracking clouds has multiple applications. It is used for short-term weather forecasting as well as long-term weather and climate analyses. Our long-term goal is to investigate cloud life cycles under different conditions, such as marine or continental areas, over deserts, or in areas with increased anthropogenic aerosols. This is a key element in understanding cloud radiation effects and the human influence on the cloud life cycle.

To identify clouds and their trajectories, we are using Particle Image Velocimetry [1] which is well-known for measuring velocities in fluid dynamics. These velocity fields are used to predict the positions of clouds in the next timestep. The predicted positions are then compared to the observed positions to match clouds across timesteps. The algorithm can work on any geostationary satellite data set or equivalent model data [2].

Currently we are comparing satellite data from the EUREC4A campaign [3] (observed by the Advanced Baseline Image onboard the GOES-16 satellite) and model output from ICON-LEM [4]. Both datasets are located east of Barbados in the Caribbean Sea. This is done to benchmark the model settings and to identify which of the three model resolution best captures the satellite data. The cloud tracking allows us to look at the lifetimes of the clouds and the development of cloud physical properties over the lifetime of a cloud. This leads to a more refined investigation into the cloud behavior.

The presented results are twofold. Firstly, we will show a direct comparison of individual cloud trajectories between observed and model data to establish a deeper understanding of the methodology and datasets. Secondly, we will look at the distributions of clouds sizes and lifetimes to compare different resolutions of model data to the observed satellite data.

 

References:

[1] Raffel et al. (2007) "Particle Image Velocimetry - A Practical Guide", Springer Verlag, doi: 10.1007/978-3-540-72308-0

[2] Seelig et al. (2021) "Life cycle of shallow marine cumulus clouds from geostationary satellite observations", in JGR: Atmospheres, doi: 10.1029/2021JD035577

[3] EUREC4A campaign: www.eurec4a.eu

[4] Dipankar et al. (2015) “Large eddy simulation using the general circulation model ICON”, in Journal of Advances in Modeling Earth Systems 7(3): 963-986, doi: 10.1002/2015MS000431

How to cite: Müller, F., Seelig, T., and Tesche, M.: Tracking Clouds: Comparing Geostationary Satellite Observations and Model Data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5796, https://doi.org/10.5194/egusphere-egu23-5796, 2023.

EGU23-7513 | Posters virtual | AS1.8

Sub-cloud layer winds in the vicinity of trade-wind cumulus 

Louise Nuijens and Mariska Koning

Sailors have long used cumulus clouds to guide their ships into areas of favourable winds. On the upwind side of cumulus clouds, the clouds’ thermal circulation would add momentum to the prevailing flow, while on the downwind side, the opposing branch of the circulation would reduce the flow. In this study, we take a simple approach to evaluating this sailors’ theorem and visualise the winds in the sub-cloud layer in the vicinity of shallow cumulus clouds. This is done by collocating cloud radar and wind lidar profiling measurements during EUREC4A on board the RV Meteor and at the BCO for a six-month period. Is there evidence for a thermal circulation in the wind surrounding clouds, or for plume-like structures that support a mass-flux approach? We will discuss our findings for clouds of increasing depth, for which clustered convection and cold pool gustiness become increasingly important.

How to cite: Nuijens, L. and Koning, M.: Sub-cloud layer winds in the vicinity of trade-wind cumulus, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7513, https://doi.org/10.5194/egusphere-egu23-7513, 2023.

EGU23-8842 | ECS | Posters on site | AS1.8

Evaluation of mass flux closures using EUREC4A observations 

Raphaela Vogel and Juan Pedro Mellado

Determining the shallow-convective mass flux at cloud base is the principle closure needed in convective parameterizations. Closure methods are usually developed and tested based on large-eddy simulations of a limited number of idealized cases. Here we evaluate how well common closures reproduce the magnitude and variability of the cloud-base mass flux observed during the recent EUREC4A field campaign upstream Barbados. The true observed mass flux is estimated as a residual of the sub-cloud layer mass budget from the circular dropsonde arrays at the 200km scale. To assess the closures, we diagnose all parameters of the chosen closures from the same dropsonde data or from coincident turbulence and cloud measurements of a second aircraft. Preliminary results suggest that (i) both variability in the area fraction and vertical velocity scales should be accounted for to reproduce the observed mass flux variability, (ii) methods using the turbulence kinetic energy to approximate the vertical velocity scale outperform methods based on the subcloud convective velocity scale, and (iii) the closure formulations should be general enough to remain useful when applied to other data and regimes.

How to cite: Vogel, R. and Mellado, J. P.: Evaluation of mass flux closures using EUREC4A observations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8842, https://doi.org/10.5194/egusphere-egu23-8842, 2023.

EGU23-8935 | ECS | Orals | AS1.8

How do environmental mesoscale heterogeneities influence the trade-wind cloud organization? 

Thibaut Dauhut, Fleur Couvreux, and Dominique Bouniol

Cumuli clouds in the trade winds are a great source of uncertainty for the future climate as their net radiative effect is hardly represented in global models. The spatial organization of these clouds, that drives their radiative effect, has been categorized into 4 major patterns: Sugar, Flower, Gravel and Fish (Bony et al. 2020). The processes governing their spatial organization and the relationships with the environmental properties remain however unclear. This study investigates the sensitivity of the Flower organization to the environmental mesoscale heterogeneities in water vapor and winds. A case of Flower organization, producing 100-km wide cloud clusters, is selected from the EUREC4A-ATOMIC campaign that took place east of Barbados in January-February 2020. A Large-Eddy Simulations using the Meso-NH model and a 100-m horizontal grid-spacing has been extensively validated by satellite and aircraft high-resolution observations (Dauhut et al., 2022) and serves as a reference. By removing alternatively the humidity or the wind heterogeneities, we show that mesoscale humidity anomalies play a critical role in driving cloud organisation into Flower. Further investigations indicate that humidity heterogeneities in the cloud layer influence the development of a shallow mesoscale circulation and have a larger impact than the heterogeneities in the sub-cloud layer. Different chains of processes are proposed to explain such a sensitivity.

How to cite: Dauhut, T., Couvreux, F., and Bouniol, D.: How do environmental mesoscale heterogeneities influence the trade-wind cloud organization?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8935, https://doi.org/10.5194/egusphere-egu23-8935, 2023.

EGU23-10014 | ECS | Orals | AS1.8

How shallow circulations couple to moisture in the trades - A perspective from satellites 

Geet George, Dominique Bouniol, and Fleur Couvreux

Measurements over the north-Atlantic trade wind regions from the recent EUREC4A field campaign (ElUcidating the RolE of Cloud–Circulation Coupling in ClimAte) have revealed a large variability in mesoscale (ca. 200 km) vertical velocity. This variability is primarily attributable to shallow mesoscale overturning circulations (SMOCs) , which have also been shown to influence mesoscale moisture variability. From EUREC4A observations, it is found that the mesoscale horizontal divergence (D) averaged over the mixed layer covaries strongly with surface D. We exploit this finding by using satellite observations of surface divergence to understand SMOCs further. We mainly use WindSAT measurements for surface divergence due to its larger swath compared to scatterometers and its superior performance under precipitating conditions. In WindSAT observations, surface divergence shows a negative correlation with integrated water vapour (IWV), but also shows the large variance when IWV is large, indicating that there might be two regimes in the divergence-moisture relationship. To further investigate the divergence-moisture relationship, we perform object-identification in the IWV field and characterize surface divergence therein. A synergy with geostationary cloudiness fields from GOES-16 helps us further interpret these characteristics in the context of the spatial organization of clouds. As satellite observations go beyond the space-time coverage of field campaigns, we are able to document (a) statistics of the spatial scales of SMOCs as well as (b) some consistent relationships between SMOCs and atmospheric moisture.

How to cite: George, G., Bouniol, D., and Couvreux, F.: How shallow circulations couple to moisture in the trades - A perspective from satellites, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10014, https://doi.org/10.5194/egusphere-egu23-10014, 2023.

EGU23-10638 | Orals | AS1.8

Moisture export by shallow convective mixing during EUREC4A 

Adriana Bailey, David Noone, and Dean Henze

In 2020, the EUREC4A (ElUcidating the RolE of Clouds-Circulation Coupling in ClimAte) field mission set out to investigate the role of shallow convective mixing in regulating trade cumulus and their influence on global climate. Recent results from this mission refute the idea that shallow convective mixing reduces cloudiness, as previous studies had argued. Instead, they suggest that shallow convective mixing is positively correlated with cloudiness when both are modulated by mesoscale circulations. Here, we provide independent evidence that further substantiates these findings. Using the unprecedented collection of water isotopic data sampled during EUREC4A, we derive estimates of total moisture exported from the sub-cloud layer by shallow convective mixing. We also derive vertical profiles of exported sub-cloud layer moisture, which allow us to investigate how shallow convective mixing alters the vertical structure of thermodynamic quantities and clouds. We show a strong association between the amount of moisture exported, the top-heaviness of the exported-moisture profile, the trade wind inversion height, and the average cloud top altitude. All increase when large cloud decks are present, indicating a role for mesoscale convective organization. We extend the analysis with remotely sensed isotope ratios in order to investigate the associations between mixing, moisture export, and cloudiness on larger scales (in both time and space) and to examine the conditions that favor convective organization at the mesoscale.

How to cite: Bailey, A., Noone, D., and Henze, D.: Moisture export by shallow convective mixing during EUREC4A, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10638, https://doi.org/10.5194/egusphere-egu23-10638, 2023.

EGU23-10781 | Posters virtual | AS1.8

Evaluation of Trade Wind Mesoscale Morphology Evolution and Transitions 

Isabel L. McCoy, Paquita Zuidema, Sunil Baidar, Raphaela Vogel, Ryan Eastman, Hauke Schulz, and Alan Brewer

Mesoscale cloud morphology patterns in the trade-winds can be grouped by their distinct appearance, size, and radiative properties into four categories: Sugar, Gravel, Flowers, and the synoptically driven Fish. Two occurrence pathways for the larger boundary-layer cloud organization structures were observed during the wintertime 2020 EUREC4A-ATOMIC joint campaign: i) regional Gravel persistence and ii) transitions to Gravel and Flowers from smaller Sugar clouds. Understanding the contributions to larger cloud structure occurrence under pathways of persistence vs. transitions from smaller clouds has utility in predicting their occurrence under climate change. Two EUREC4A-ATOMIC case studies are developed for these respective pathways during multi-day periods when observational platforms were longitudinally distributed across the ocean in parallel with Barbados. A Lagrangian analysis framework is developed by using for/backward 30-hr boundary layer trajectories initialized every 3-hr from the RV Ronald H. Brown (i.e., the mid-evolution reference platform) to connect upwind (e.g., the Northwest Tropical Atlantic Station buoy) and downwind (e.g., the Barbados Cloud Observatory) platforms. This synergistic, multi-platform campaign dataset is supplemented with satellite observations and reanalysis. Motion-stabilized Doppler-lidar observations at the RV Ronald H. Brown and the Barbados Cloud Observatory allow us to examine characteristics of cloud and plume dynamics in addition to the impact of environmental conditions expected to influence cloud organization and development (e.g., surface wind speeds, energy and moisture fluxes, stability, entrainment, large- and meso-scale subsidence, and aerosols). Eulerian differences between key platforms over the campaign period are evaluated and campaign findings are further extended using multi-year Lagrangian analysis.

How to cite: McCoy, I. L., Zuidema, P., Baidar, S., Vogel, R., Eastman, R., Schulz, H., and Brewer, A.: Evaluation of Trade Wind Mesoscale Morphology Evolution and Transitions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10781, https://doi.org/10.5194/egusphere-egu23-10781, 2023.

EGU23-10856 | ECS | Orals | AS1.8

Evaluating hm-scale simulations of trade wind clouds using EUREC4A data 

Hauke Schulz, Stevens Bjorn, and Robert Wood

Recent observations revealed that meso-scale patterns of shallow convection in the downwind trades can be connected to specific atmospheric environments whose characteristics are not solely from within the trades but have traces from tropical or mid-latitudinal origin depending on the pattern. As a consequence of this co-variability of patterns and air-mass characteristics, a different feedback to a changing climate is anticipated and will be modulated by the observed, pattern-dependent net cloud radiative effects. By conducting large-eddy simulations we evaluate how well current climate models reproduce this co-variability in cloudiness and its environment and whether the meso-scale patterns are represented due to the observed mechanisms. To capture the full range of patterns and its processes these simulations are done on large-scale domains with grid-spacings of 625m, 312m and 156m and focus on the EUREC4A field campaign time period. By repeating the simulation with an increased aerosol load, we reveal pattern-dependent sensitivities. With frequently raining patterns showing the largest response, the importance of different processes depending on the meso-scale organization is emphasized.

How to cite: Schulz, H., Bjorn, S., and Wood, R.: Evaluating hm-scale simulations of trade wind clouds using EUREC4A data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10856, https://doi.org/10.5194/egusphere-egu23-10856, 2023.

Cloud cover products from multiple satellite projects are long enough to provide a robust evaluation of climate models. Using global atmosphere models forced by observed sea-surface temperature and employing satellite simulator software, three generations of the Community Atmosphere Model are evaluated. This inter-generational comparison shows how the cloud radiative effect has improved through time but cloud cover has shown only modest improvements over the past decade. Diagnostics are introduced that allow a decomposition of spatial biases to separately evaluate systematic errors in the mean from the spatial variability. Errors in cloud properties are evaluated using a dynamical regimes analysis to connect the climatological errors to the large-scale circulation. Two closely related, current-generation models, CESM2 and E3SM, are compared to show how slightly different model development and tuning decisions can impact the the cloud climatology. Leveraging multiple long-term satellite data sets suggest that despite improvements through time, there remain significant systematic errors in cloud cover. It is suggested that simultaneously constraining cloud radiative effect and cloud cover, and therefore reducing the longstanding "too few, too bright" bias, is feasible and could improve climate projections. 

How to cite: Medeiros, B.: Satellite-based evaluation of cloud cover through three generations of global atmosphere models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10934, https://doi.org/10.5194/egusphere-egu23-10934, 2023.

EGU23-11082 | Orals | AS1.8

The impact of dry intrusions on midlatitude cold-air outbreak cloud transitions 

George Tselioudis, Florian Tornow, Andrew Ackerman, and Ann Fridlind

Cold-air outbreaks (CAOs) form marine boundary layer (MBL) clouds that undergo rapid overcast-to-broken cloud regime transitions, initiated by substantial rain. CAOs are usually accompanied by dry intrusions (DIs) that subside as free-tropospheric (FT) air into the postfrontal sector of mid-latitude storms. For an exemplary cold-air outbreak in the NW Atlantic that showed faster transitions (corresponding to reduced extents of overcast clouds) closer to the low-pressure system, we posit that varying transitions are caused by an uneven meteorological pattern imposed by the prevailing DI. We compile satellite observations, reanalysis fields, and Lagrangian large-eddy simulations (LES) translating along MERRA2-based trajectories to show that postfrontal trajectories closer to the low-pressure system are uniquely favorable to rain formation (and, thus, cloud transitions) as they show (1) weaker FT subsidence rates, (2) greater FT humidity, (3) greater MBL windspeeds, and (4) a colder MBL as well as reduced lower-tropospheric stability. We present an updated conceptual view of postfrontal cloud formation that may guide future investigations.

How to cite: Tselioudis, G., Tornow, F., Ackerman, A., and Fridlind, A.: The impact of dry intrusions on midlatitude cold-air outbreak cloud transitions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11082, https://doi.org/10.5194/egusphere-egu23-11082, 2023.

EGU23-11662 | ECS | Orals | AS1.8

High spatial resolution retrieval of cloud droplet size distribution from polarimetric specMACS observations and application to simulated data 

Veronika Pörtge, Tobias Kölling, Anna Weber, Lea Volkmer, Claudia Emde, Tobias Zinner, Linda Forster, and Bernhard Mayer

We present novel remote sensing observations of cloud droplet size distributions retrieved from polarimetric observations of the wide-field airborne imaging system specMACS. The measurements were collected during the EUREC4A field campaign which took place in January and February 2020 in the trade wind region east of Barbados. We focus on observations of the cloudbow which is an optical phenomenon that results from single scattering of sunlight by liquid droplets close to the cloud top. The cloudbow signal strongly depends on the cloud droplet size distribution. By fitting model simulations (stored in a look-up table) to the cloudbow observations, both the effective radius and the effective variance (i.e., the width) of the droplet size distribution are retrieved. Traditional retrieval techniques based on total reflectance measurements are able to determine the effective radius but do not provide information on the effective variance. However, to fully understand cloud growth processes and the interaction between clouds and solar radiation, both parameters must be known. Furthermore, the cloudbow is only weakly affected by 3-D radiative transfer effects which is beneficial since these are usually a problem for traditional methods.

High-resolution maps of the cloud droplet size distribution with a spatial resolution of 100 m by 100 m are presented. The maps reveal patterns within the cloud droplet size distribution at cloud top that could originate from mechanisms like entrainment or mixing processes. We further show first results of an application of the retrieval to simulated specMACS observations. The images were generated using the 3-D radiative transfer model MYSTIC and are based on realistic LES cloud field simulations. We will investigate limitations and uncertainties of the retrieval using the simulated dataset.

How to cite: Pörtge, V., Kölling, T., Weber, A., Volkmer, L., Emde, C., Zinner, T., Forster, L., and Mayer, B.: High spatial resolution retrieval of cloud droplet size distribution from polarimetric specMACS observations and application to simulated data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11662, https://doi.org/10.5194/egusphere-egu23-11662, 2023.

EGU23-12257 | Orals | AS1.8

Complementary approaches in self-supervision to exploit EUREC4A measurements and satellite observations for cloud systems over North Atlantic trades 

Dwaipayan Chatterjee, Sabrina schnitt, Paula Bigalke, Claudia Acquistapace, and Susanne Crewell

The cloud systems of the North Atlantic trades (NAT) have been a topic of curiosity due to significant uncertainty in their physical characteristics, physical process understanding across various spatial and temporal scales, and their impact on the regional climate system. Initial research has provided the causal link for cloud systems having distinct organizational aspects (formerly described as Sugar, Gravel, Fish, and Flower) with the net radiative flux over the region. Questions have been raised about how the changing climate will influence the frequency of occurrence of these cloud regimes and how the net radiative impact will change the regional climate system.

 

However, cloud systems represent a continuous spectrum where not-so-visually distinct systems also occur. Existing clustering mechanisms sort organizations into separate classes. Yet, in reality, the organization often does not align with those pre-defined classes but transitions amongst them or simply occurs in a continuous spectrum. Using two complementary neural networks in self-supervision (without human interference), we investigate the representation learning of cloud systems both in a continuous space describing a cloud system spectrum and in a discreet space aiming to identify distinct cloud systems. 50,000 GOES-ABI cloud optical depth NAT images from 2017 – 2021 covering the EUREC4A study area are randomly cropped to 256 x 256 pixels and sorted/labeled by the machine.

 

We study the climatological representation of EUREC4A’s cloud patterns in the continuous embedding space. We follow the Maria S. Merian ship track inside the feature space matching the ship-based atmospheric remote sensing and ERA5 profiles with the K-nearest satellite images. This analysis examines the consistency of the environmental conditions for cloud systems identified as close to each other in the continuous feature space. We investigate the relationship between the net cloud radiative effect and the radiative flux characteristics in the continuous space, finding a strong functional relationship with the cloud system’s pattern and distributions.

 

In the discrete space, we aim to identify the optimal number of classes that could represent the continuous space. We also aim to understand if these discrete classes correspond to the categories identified in the physical and visual space. Moreover, to better understand the decision of the neural network for a particular cloud pattern, we visualize the network’s focus in the activation space. We find that different self-attention heads of the neural network learn to focus on different semantics of the cloud system distribution.

 

Finally, we found that different regularizations applied during the training of the network directly impact the representation learning of the cloud system, and we show how to use such regularizations to improve the understanding of cloud systems.

How to cite: Chatterjee, D., schnitt, S., Bigalke, P., Acquistapace, C., and Crewell, S.: Complementary approaches in self-supervision to exploit EUREC4A measurements and satellite observations for cloud systems over North Atlantic trades, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12257, https://doi.org/10.5194/egusphere-egu23-12257, 2023.

EGU23-12306 | Posters on site | AS1.8

First applications of the Virga-Sniffer – a new tool to identify precipitation evaporation using ground-based remote-sensing observations 

Heike Kalesse-Los, Anton Kötsche, Andreas Foth, Johannes Röttenbacher, Teresa Vogl, and Jonas Witthuhn

The dominant cloud type in the subtropical Atlantic is the trade wind cumulus with a cloud base located near the lifting condensation level (LCL) below 1 km. Other common clouds in this region with their base above 1 km are stratiform cloud layers or cloud edges near the trade wind inversion at 2-3 km. Precipitation in all these clouds mainly forms at temperatures above freezing point by collision and coalescence. Therefore, precipitation generally occurs as light rain/drizzle from stratiform cloud layers or as showers from well-developed trade wind cumuli. Precipitation underneath a cloud base is often visible as fall streaks. If the precipitation evaporates before reaching the ground, these fall streaks are called virga.

Combined continuous long-term ground-based remote-sensing observations with vertically pointing cloud radar and ceilometer are well-suited to identify these precipitation evaporation fall streaks. Here we show the first application of a new open-source tool, the Virga-Sniffer which was developed within the frame of RV Meteor observations during the ElUcidating the RolE of Cloud–Circulation Coupling in ClimAte (EUREC4A) field experiment in Jan–Feb 2020 in the Tropical Western Atlantic. In the simplest approach, it detects virga from time-height fields of cloud radar reflectivity and time series of ceilometer cloud base height. The Virga Sniffer was applied to RV Meteor observations during EUREC4A and statistical results as well as an evaporation case study are presented. Spectral W-band radar data from a fall streak, identified as virga by the Virga-Sniffer, was used to calculate evaporative cooling rates. Sensitivity studies were performed to investigate the influence of vertical wind and relative humidity uncertainties.  Possible future applications of the Virga-Sniffer within the frame of EUREC4A include detailed studies of precipitation evaporation with a focus on cold pools or cloud organization, or distinguishing moist processes based on water vapor isotopic observations.

How to cite: Kalesse-Los, H., Kötsche, A., Foth, A., Röttenbacher, J., Vogl, T., and Witthuhn, J.: First applications of the Virga-Sniffer – a new tool to identify precipitation evaporation using ground-based remote-sensing observations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12306, https://doi.org/10.5194/egusphere-egu23-12306, 2023.

The representation of shallow tradewind cumulus clouds in climate models accounts for the majority of inter-model spread in climate projections, highlighting an urgent need to understand these clouds better. In particular, their spatial organisation appears to cause a strong impact of their radiative properties and dynamical evolution. The precise mechanisms driving different forms of convective organisation which arise both in nature and in simulations are, however, currently unknown.

We show how the continuum of convective organisation states can be analysed as an emergent  property of the embedding space representation learnt by a neural network through unsupervised learning.  Specifically we will use a technique to extract an estimate of the manifold in a high-dimensional space on which possible states of convective organisation lie.  Through composition of reanalysis and observations onto this manifold we are able to extract the characteristics of the atmosphere which coincide with different forms of convective organisation, and further we are able to map transitions between different states of organisation and study how these develop.

We will show results from analysing: a) what the radiative properties of different forms of organisation are, b) what atmospheric characteristics coincide with different forms of organisation and c) what transitions occur when following air-masses along Lagrangian trajectories.  Specifically, we find: a) net radiation changes significantly between different forms of organisation, b) agreement with previous studies on the importance of boundary layer wind-speed and to some degree atmospheric stability, and c) we are able to succinctly capture what transitions occur between regimes.

How to cite: Denby, L.: Charting the realms of Convective Cloud Organisation using Unsupervised Learning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12508, https://doi.org/10.5194/egusphere-egu23-12508, 2023.

In January and February 2020, the joint EUREC4A/ATOMIC field campaign took place in the Tropical Atlantic near Barbados, with the goal to advance our understanding of the interplay between clouds, convection and circulation including their role in climate change. Within the scope of this campaign, several unique satellite-based datasets have been collected, including very high-spatial resolution multispectral images with 10x10m² pixel size acquired by polar-orbiting Copernicus Sentinel-2 satellites. In this presentation, the first analysis of these high-resolution observations focused on tropical trade cumuli is given. This cloud type is characterized by small-scale spatiotemporal variability that is unresolved at the spatial resolution of current meteorological satellite imagers.

Using the high-resolution Sentinel-2 observations, we will show the clouds can be considered as individual objects with associated properties, such as shape and size parameters, but also their mean radiative properties. A novel technique will be presented for deriving cloud height from Sentinel-2 observations, which exploits the geometric relationship between cloud objects and their shadows. Furthermore, the cloud fraction and cloud size distribution are calculated for various trade cumulus scenes. The uncertainties arising from choices in our cloud detection scheme will be discussed.

We show that a substantial fraction of clouds has equivalent diameters below the pixel size of commonly used meteorological satellite instruments. Consequently, and consistent with previous studies, the cloud size distribution and domain-average cloud fraction from coarse-resolution satellite imagers are shown to be biased and highly sensitive to pixel resolution. In addition, a large fraction of pixels identified as cloudy contains significant clear-sky contributions, and it is no longer possible to characterize clouds as objects. We will discuss how this affects the accuracy of cloud property determination and biases estimates of cloud radiative forcing.

How to cite: Ritter, O., Bley, S., and Deneke, H.: Object-based characterization of Tropical Trade Cumuli During the EUREC4A/ATOMIC Field Campaign using Sentinel-2 observations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13751, https://doi.org/10.5194/egusphere-egu23-13751, 2023.

Cloud resolving models run to equilibrium in idealized simulations of radiative-convective equilibrium often show the deep convection spontaneously transitioning from random organization to a state where convection in aggregated into clusters.  This results in a drier mean state and aggregation could be important for climate sensitivity, and is missing in classical parameterization schemes.  However, the onset and nature of the equilibrium, and the sensitivity to lower boundary conditions, differs dramatically between models that use different representations of moist physics and diffusion parameterizations, and varying dynamical cores.  In order to shed light on this, we develop a highly idealized, spatially explicit, stochastic reactive-diffusive model for the column relative humidity in the tropics.

The model is run to equilibrium and it is found that, depending on the model parameter settings and experimental framework, it can produce equilibrium states where the convection remains random, or states where the convection is highly aggregated. Many results of the full-physics models are reproduced, such as their sensitivity to model resolution and domain size, with aggregation more likely using coarse grid sizes and larger domains. The simple model thus allows to explain these sensitivities of the full physics models, with convective nearest-neighbor distances constrained to decrease with smaller domains or higher resolution, which reduces the spatial heterogeneity of column humidity and makes aggregation less likely.  Expanding on these arguments, we use dimensional analysis to combine the model parameters that describe how sensitive convection is to humidity, the subsidence drying rate, and the spreading of humidity by advection and diffusion processes, along with the domain size and resolution.  Using large ensembles of over 1000 simulations, we demonstrate that aggregation occurs at a precise critical value of the resulting dimensionless parameter, which will refer to as the aggregation number.   We suggest that the aggregation number could prove useful to diagnose the differences between full physics models of the atmosphere. 

How to cite: Tompkins, A. and Biagioli, G.: A dimensionless parameter to predict spontaneous convective aggregation onset in a idealized stochastic-diffusive model of radiative-convective equilibrium, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14609, https://doi.org/10.5194/egusphere-egu23-14609, 2023.

EGU23-14787 | ECS | Orals | AS1.8

Reponse of precipitation to dynamics in global-storm resolving models 

Lucile Ricard, Athanasios Nenes, Claudia Stephan, and Fabrizio Falasca

Most climate models show a precipitation increase with warming that is smaller than the increase in moisture, which requires a weakening of the convective mass flux and a slowing of the overturning circulation. In this study we use global-storm resolving models (DYAMOND models) to identify the systematic relationships between the precipitation, the vertical velocity and the overturning circulation in the tropics. The cloud-resolving simulations that are 40-day long in winter allow us to study the dynamical response of precipitation over a wide range of spatial scales. A data reduction and inference method, δ-MAPS, provides an efficient way to reduce the complexity and dimensionality of high-resolution simulations. We use the domains identified in 2d fields of atmosphere mass content of water vapor – interpreted as regions of homogeneous precipitable water – as preferential domains to derive the isentropic distribution of vertical mass transport and the isentropic streamfunction. The isentropic analysis consists in sorting the air parcels in terms of equivalent potential temperature, which offers a simple representation of the convective overturning. A multiscale decomposition allows us to quantify the contribution of the mesoscale circulation in comparison to the large-scale overturning circulation. Finally, the results are compared between the different DYAMOND models to evaluate the intermodel spread. By doing so, we evaluate to what extent the spread in precipitation in model ensemble may arise from the differences in representation of the overturning circulation at different scales.

How to cite: Ricard, L., Nenes, A., Stephan, C., and Falasca, F.: Reponse of precipitation to dynamics in global-storm resolving models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14787, https://doi.org/10.5194/egusphere-egu23-14787, 2023.

EGU23-14814 | Orals | AS1.8

The WInd VElocity Radar Nephoscope (WIVERN): a candidate mission for the ESA Earth Explorer 11 

Alessandro Battaglia, Anthony Illingworth, Frederic Tridon, Ali Rizik, Paolo Martire, and Filippo Emilio Scarsi

The WIVERN (WInd VElocity Radar Nephoscope) concept, now in Phase 0 of the ESA Earth Explorer program, promises to complement Doppler wind lidar by globally observing, for the first time, the vertical profiles of winds in cloudy areas. The mission will also strengthen the cloud and precipitation observation capability of the Global Observing System by providing unprecedented revisit time of cloud and precipitation vertical profiles. The mission hinges upon a single instrument, i.e., a dual-polarization Doppler W-band scanning cloud radar with a 3 m circular aperture non-deployable main reflector. The WIVERN antenna conically scans a large swath (of about 800 km) around nadir at an off-nadir angle of about 38o at 12 rpm (revolutions per minute). This viewing geometry allows daily revisits poleward of 50°, 50-km horizontal resolution, and approximately 1-km vertical resolution. A key element is the use of closely spaced pulse pairs one of which is H polarised the other V polarised, so that the target does not have time to reshuffle, and, providing there is no significant cross-talk between the two returns, the high velocities associated with wind storms can be retrieved. 

In this paper we will discuss the scientific objectives of the mission and will outline some of the technical challenges of the measuring technique. In particular we will discuss how to correct for wind biases introduced by the satellite motion and wind shear across the beam, how to account for cross-talk between the H and V returns due to depolarisation by meteorological targets, how to calibrate the instrument and how to identify mis-pointing of the antenna that could affect Doppler accuracy. We will also present examples of Level 1 products via an end to end simulations applied to high resolution cloud resolving models and expected performances of the instrument in terms of cloud/precipitation and wind coverage.

How to cite: Battaglia, A., Illingworth, A., Tridon, F., Rizik, A., Martire, P., and Scarsi, F. E.: The WInd VElocity Radar Nephoscope (WIVERN): a candidate mission for the ESA Earth Explorer 11, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14814, https://doi.org/10.5194/egusphere-egu23-14814, 2023.

EGU23-17058 | ECS | Posters on site | AS1.8

Measuring meso-scale gradients in the Arctic during HALO-(AC)³ 

Fiona Paulus, Roel Neggers, Gunilla Svensson, and Michail Karalis

Boundary layer cloud transitions at high latitudes play a key role in Arctic climate change, and are partially controlled by large-scale dynamics such as subsidence. While measuring large- and mesoscale divergence has proven notoriously difficult, the recent NARVAL and EUREC4A airborne campaigns in the subtropics have finally achieved this goal using multiple dropsondes releases in circular patterns. If this method also works at high latitudes is still an open research question, given the considerable differences in atmospheric dynamics. Answering this question was one of the main objectives of the recent HALO-(AC)^3 field campaign near Svalbard in Spring 2022. Circular dropsonde patterns were realized during various research flights by two airplanes, independently sampling Cold Air Outbreaks (CAO) in the Fram Strait with multiple dropsondes. This study presents a first overview of the results. We find that the method indeed yields reliable estimates of mesoscale gradients in the Arctic, yeilding robust vertical profiles of both subsidence and vorticity. Sensitivity to aspects of the method is investigated, including dependence on sampling area and the divergence calculation. Ongoing work to drive targeted Lagrangian high resolution simulations of the observed CAOs exclusively with HALO-(AC)³ data will be briefly discussed.

How to cite: Paulus, F., Neggers, R., Svensson, G., and Karalis, M.: Measuring meso-scale gradients in the Arctic during HALO-(AC)³, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17058, https://doi.org/10.5194/egusphere-egu23-17058, 2023.

EGU23-17350 | ECS | Orals | AS1.8

On the properties of greenCu: continental, organized shallow clouds 

Tom Dror, Ilan Koren, Orit Altaratz, Michael D. Chekroun, and Vered Silverman

Prevalent over the world’s oceans and continents, shallow clouds still comprise a main aspect of the uncertainty related to cloud feedback and climate sensitivity. Compared to shallow clouds over the ocean, confined to specific marine environments, shallow cumulus (Cu) over land occur in diverse locations throughout the globe.

Motivated by an intriguing observation regarding the universality of continental shallow Cu fields regardless of their geographical location, we explore their similarities. We combine satellite observations, along with machine learning classification and numerical modelling to show that these cloud fields share many important properties, such as the patterns they form and their tendency to form over and near forests and vegetated lands, thus termed greenCu.

Moreover, we show that in spite of their occurrence in different climatic regions, from the tropics to mid- and high-latitudes, greenCu fields are associated with similar large-scale meteorological conditions.

How to cite: Dror, T., Koren, I., Altaratz, O., Chekroun, M. D., and Silverman, V.: On the properties of greenCu: continental, organized shallow clouds, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17350, https://doi.org/10.5194/egusphere-egu23-17350, 2023.

Spring precipitation over the southeastern Tibetan Plateau (SETP) produces more than 34% of annual precipitation, which is comparable to summer precipitation. This pre-monsoon rainfall phenomenon, influenced synthetically by atmospheric circulations and topography, makes the SETP an exception to its surroundings. Here, fine-scale characteristics and typical synoptic backgrounds of this unique phenomenon have been investigated. The spring precipitation over the SETP is characterized by high frequency at hourly scale, with a single diurnal peak at night. Event-based analysis further demonstrates that the spring precipitation is dominated by long-lasting nocturnal rainfall events. From early to late spring, the dominant synoptic factor evolves from terrain-perpendicular low-level winds to atmospheric moisture, influencing the spatial heterogeneity and fine characteristics of the spring precipitation. The westerly-dominated type, featured by lower geopotential height over the TP and enhanced westerlies along the Himalayas, produces limited-area precipitation at those stations located at topography perpendicular to low-level winds. In contrast, the moisture-dominated type is featured by an anomalous cyclone over the Bay of Bengal and induces widespread precipitation around the SETP, which is the leading contributor to the spring precipitation there. Due to the moist environment and weak instability, the spring precipitation influenced by the moisture-dominated type is characterized by long-lasting nocturnal events, with a large portion of weak precipitation. Findings revealed in this study complete the picture of spring precipitation influenced by different dominant synoptic factors over the SETP, which deepen the current understanding of the joint influence of circulation and topography on the hydrological cycle of complex terrains.

How to cite: zhao, Y., li, J., ren, L., li, N., and li, P.: Fine-scale characteristics and dominant synoptic factors of spring precipitation over complex terrain of the southeastern Tibetan Plateau, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1347, https://doi.org/10.5194/egusphere-egu23-1347, 2023.

The seasonal migration of the Intertropical Discontinuity (ITD) is critical for monitoring seasonal moist convective processes and associated rainfall over West Africa. This study constitutes a new analysis of the seasonality of moist convection over West Africa, relative to the ITD, based on NASA's Atmospheric Infrared Sounder (AIRS) measurements from 2003-2018. Results show that AIRS resolves the seasonal march of the ITD, including its inherent diurnal-scale variations. AIRS captures the north - south daytime skin temperature dipole around the ITD, with greater relative temperatures to the north, especially during March - August. In the vicinity of the nighttime ITD, AIRS profiles indicate increased instability that is characteristic of nocturnal thunderstorm propagation. On thunderstorm days, the mean latitude of the AIRS-derived ITD is displaced 3o , 0.2o, and 2o north of its DJF, MAM, and SON climatological positions, respectively, and 1.2o south in JJA. The findings of this study are critical to building local tropical weather forecasting capacity and capabilities in West Africa.

How to cite: Osei, M.: Observation of the moist convective environment of West Africa by the Atmospheric InfraRed Sounder, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1683, https://doi.org/10.5194/egusphere-egu23-1683, 2023.

EGU23-3406 | ECS | Posters on site | AS1.9

Enhanced climatology of large hail in the UK: Radar-derived diurnal cycle and storm mode 

Henry Wells, John Hillier, Freya Garry, Nick Dunstone, Huili Chen, Abdullah Kahraman, William Keat, and Matthew Clark

Large hail, with a diameter of at least 20 mm, is a hazard associated with severe convective storms (SCS) that can cause significant damage. Understanding of atmospheric environments conducive to large hail is underpinned by catalogues of past events. Because of the small footprint of hail events, these often rely on crowdsourced reports. In the UK, the relative rarity of large hail and low public awareness of SCS hazards makes obtaining a complete set of reports difficult, and in many cases the precise time of the hail is not recorded. In this study, the two major databases of UK large hail reports are merged for the first time. Composite radar reflectivity data are used to verify and enhance 260 reports since 2006. Time of the hail and the basic storm mode (isolated, clustered or linear) are visually estimated from animations. Compared to the UK’s most severe historic hailstorms (1800–2004), our quality controlled climatology of all sizes of large hail shows a diurnal cycle with a slightly broader peak. Around 55% of large hail events are associated with isolated cells, while 34% have supercellular characteristics, a much lower proportion than found in the USA. The full event set (1979–2022), comprising over 850 reports, is used to update the seasonal, spatial and size distributions of large hail in the UK. We intend that this hail event set forms part of a multi-hazard analysis of UK SCS, also including tornadoes and extreme rainfall, and its relationship to background atmospheric conditions. The effect of climate change on UK SCS will be investigated through past and future trends in these background conditions.

How to cite: Wells, H., Hillier, J., Garry, F., Dunstone, N., Chen, H., Kahraman, A., Keat, W., and Clark, M.: Enhanced climatology of large hail in the UK: Radar-derived diurnal cycle and storm mode, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3406, https://doi.org/10.5194/egusphere-egu23-3406, 2023.

EGU23-4332 | Orals | AS1.9

A Merger-Formation Bow Echo Caused by Low-Level Mesovortex in South China 

Qiqing Liu, Xin Xu, Kun Zhao, and Ang Zhou

Based on operational radar observations and high-resolution analyses from the Variational Doppler Radar Analysis System (VDRAS), a bow echo producing high-winds and heavy rainfall that occurred over South China in the pre-rainy season is studied. Results show that this bow echo developed from a quasi-linear convective system (QLCS) and acquired a well-defined bow shape after merging with a pre-line convective cell (CC). Interestingly, the rear-inflow jet (RIJ), which has been well recognized to play a key role in the formation of a bow echo, was absent in this merger-formation bow echo (MFBE). This is ascribed to the weak cold pool and line-end vortices generated within the QLCS as it developed in the monsoon environment of high humidity and weak low-level vertical wind shear.

A new pathway of bow echo formation was proposed instead, which highlighted the importance of the low-level mesovortex (MV) on the leading edge of the QLCS. The MV originated from a weak vertical vorticity band ahead of the QLCS. Vertical vorticity budget analyses revealed that the enhanced stretching effect during the QLCS-CC merger was the main cause of the growth of the MV. The well-developed MV thereby provided a RIJ-like flow wrapping cyclonically from north of the QLCS, forcing the QLCS to distorted into a bow echo. This MV contributed foremost to the near surface gales as well.

Combined with the well-resolved dynamical processes aforementioned, observations from an S band polarimetric radar are employed, aiming to uncover the microphysical and dynamical structures and their interaction processes accounting for the heavy rainfall. The precipitation was shown to be featured of high concentration of large hydrometeors, with maxima basically limited within the intensified MV. The deep QLCS developing far above the freezing level favored for significant ice-phase processes, further enhancing rain rate through melted graupel and hail. High spatiotemporal correlation between the precipitation extremes and the MV suggests the non-negligible role the MV played to determine the microphysics process of this precipitation, which required more detailed researches next.

How to cite: Liu, Q., Xu, X., Zhao, K., and Zhou, A.: A Merger-Formation Bow Echo Caused by Low-Level Mesovortex in South China, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4332, https://doi.org/10.5194/egusphere-egu23-4332, 2023.

EGU23-5208 | ECS | Posters on site | AS1.9 | Highlight

Dynamical Impacts of Warm-Starting Operational Weather Models over Africa 

Fran Morris, James Warner, Caroline Bain, Juliane Schwendike, Doug Parker, and Jon Petch

Weather models which allow explicit convection can add value to weather forecasting by improving the intensity and timing of precipitating systems and their dynamics, which is particularly valuable in the tropics where moist diurnal convection dominates. In West Africa, convection can become organised to form mesoscale convective systems which are crucial for supplying water but may have devastating impacts, and while convection-permitting models improve forecasts, issues remain in the implementation of operational convection-permitting models. A major problem is initialising weather models in the tropics, where measurements are sparse and weather systems are dominated by nonlinear diabatic processes, which makes data assimilation challenging. Currently, the UK Met Office runs a regional operational convection-permitting model in Africa, the Tropical Africa Model, which is initialised using lower-resolution global models. However, the global models have extremely limited convective-scale structures and as a result, there is a spin-up time of around 12-18 hours before the model begins to accurately reflect precipitation.

To counteract this problem, a “warm-starting” method has been trialled. The warm-starting technique blends large-scale features from the global model and fine-scale fields below a certain length scale from previous runs of the high-resolution model to use as an initial state in a new model run. It combines the more realistic convective structures of the regional model and the more accurate synoptic conditions in the global model. Not only is the approach cheaper and quicker than traditional data assimilation, both in terms of development and computational cost, but it also shows demonstrable improvements in the representation of precipitation for the first 12 hours of the model and beyond relative to simulations where the model has simply been initialised with the global model (a “cold-start”). The cold-start simulations appear to consistently predict rainfall that is too intense even beyond the first 12 hours.

We investigate why warm-starting models produces more realistic rainfall distributions by examining the dynamical structures: producing statistics of rainfall objects as forecasts evolve and examining their connection to the dynamics. We examine the energetics of convection in the convection-permitting models, aiming to provide a justification for the scale length at which we include structure from previous model runs using this technique.

How to cite: Morris, F., Warner, J., Bain, C., Schwendike, J., Parker, D., and Petch, J.: Dynamical Impacts of Warm-Starting Operational Weather Models over Africa, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5208, https://doi.org/10.5194/egusphere-egu23-5208, 2023.

EGU23-5258 | ECS | Orals | AS1.9

Comparison of Mesoscale Convective Systems in a Seasonal Convection-Permitting Simulation With Observations Over the Indian Monsoon Zone 

Manisha Tupsoundare, Sachin Deshpande, Zhe Feng, Medha Deshpande, Subrata Kumar Das, and Harshad Hanmante

The largest type of deep convection, mesoscale convective systems (MCSs), regulate changes in the hydrological cycle and large-scale tropical circulation. During the Indian summer monsoon (June-September), synoptic-scale systems move across the monsoon zone, causing MCSs to form frequently. MCSs cause widespread and heavy rain throughout the monsoon zone. Past MCS studies in India used either observations or simulation in a short period or with case studies approach. Studies on structure and evolution of MCSs highlighting the organization of convection over the monsoon zone are lacking.

In this study, a 4-month, convection-permitting simulation is conducted over the Indian monsoon zone using the Weather Research Forecast (WRF) model with 4-km grid spacing and two microphysics parameterizations and is compared with observations to evaluate composite MCS characteristics and microphysics sensitivities. We first apply a cloud-tracking algorithm to two high-resolution observation data sets, NASA global merged infrared brightness temperature (IR Tb) and GPM IMERG surface precipitation to identify and track individual MCS events during monsoon. Ground-based S-band radar observations are used to examine the 3-D structures of storms embedded within the tracked MCSs and analyze evolution of convective, stratiform and anvil components of the MCSs. A similar cloud-tracking algorithm is then applied to WRF simulated data (radar reflectivity, IR Tb and precipitation) to identify and track MCS in model simulation. As a result, the observed and simulated MCSs are consistently identified and tracked, making it possible to compare WRF MCS population statistics with observed MCSs.

Results show that the properties of MCS including composite evolution, and frequency distribution are reasonably captured by the two simulations with some noticeable differences. In general, the Thompson simulation produces better agreement with observations for convective area and precipitation amount, MCS propagation speed but exhibits underestimation of stratiform area. The composite evolution of simulated MCS cloud and precipitation structures showed a gradual increase from convective initiation to around the first half of the MCSs lifetime, which was consistent with observations. The MCS eccentricity reaches to minimum value at maximum horizontal extent, indicating a quasi-circular shape of MCS. We observed that PDF of MCS precipitation intensity largely agrees well with observations. The highest altitude reached by intense convective cores (30-dBZ echo-tops) is 8 km, but the model significantly underestimates it. The detailed comparison of multiple aspects of MCSs (e.g., initiation, size, intensity, lifetime, propagation) and embedded storms (e.g., convective-stratiform areas) and associated precipitation between the simulation and observations for one monsoon season will be discussed.

How to cite: Tupsoundare, M., Deshpande, S., Feng, Z., Deshpande, M., Das, S. K., and Hanmante, H.: Comparison of Mesoscale Convective Systems in a Seasonal Convection-Permitting Simulation With Observations Over the Indian Monsoon Zone, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5258, https://doi.org/10.5194/egusphere-egu23-5258, 2023.

EGU23-5342 | ECS | Orals | AS1.9

Sensitivity of simulated mesoscale convective systems over East Asia to the treatment of convection in a high-resolution GCM 

Puxi Li, Mark Muetzelfeldt, Reinhard Schiemann, Haoming Chen, Jian Li, Kalli Furtado, and Moran Zhuang

Mesoscale convective systems (MCSs) downstream of the Tibetan Plateau (TP) exhibit unique precipitation features. These MCSs can have damaging impacts and there is a critical need for improving the representation of MCSs in numerical models. However, most global climate models are typically run at resolutions that are too coarse to reasonably resolve MCSs, and it is still unclear how well higher-resolution global models can reproduce the precipitation characteristics of MCSs. In this study, the sensitivity of MCSs simulated by a global high resolution (~10km), atmosphere-only climate model to different treatments of convection (with and without parametrized convection, and a hybrid representation of convection) have been investigated. The results show that explicit convection (i.e., non-parameterized) can better reproduce the observed pattern of MCS precipitation over the East Asian Summer Monsoon (EASM) region. In general, explicit convection better simulates the diurnal variability of MCSs over the eastern China, and is able to represent the distinctive diurnal variations of MCS precipitation over complex terrain particularly well, such as the eastern TP and the complex terrain of central-northern China. It is shown that explicit convection is better at simulating the timing of initiation and subsequent propagating features of the MCS, resulting in better diurnal variations and further a better spatial pattern of summer mean MCS precipitation. All three experiments simulate MCS rainfall areas which are notably smaller than those in observations, but with much stronger rainfall intensities, implying that these biases in simulated MCS morphological characteristics are not sensitive to the different treatment of convection.

How to cite: Li, P., Muetzelfeldt, M., Schiemann, R., Chen, H., Li, J., Furtado, K., and Zhuang, M.: Sensitivity of simulated mesoscale convective systems over East Asia to the treatment of convection in a high-resolution GCM, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5342, https://doi.org/10.5194/egusphere-egu23-5342, 2023.

EGU23-6107 | ECS | Posters on site | AS1.9 | Highlight

Deforestation and changes in rainfall across the Amazon – reducing uncertainty using a continental scale convection permitting domain 

Richard Bassett, Luis Garcia-Carreras, Douglas Lowe, Lincoln Alves, Gilberto Fisch, Kate Halladay, Ron Kahana, and José Veiga

The Amazon rainforest holds more than 40% of all remaining tropical rainforest and is a key component of the climate system. The scale of deforestation in the Amazon significantly impacts both local and global climates. Under a business-as-usual scenario as much as 40% of the Brazilian Amazon rainforest will be lost by 2050. Despite the magnitude of these changes and its importance, the overall effects of deforestation on rainfall remain uncertain. Land-use change influences rainfall through a variety of mechanisms acting at local to continental scales. As such, previous research indicates conflicting responses to rainfall depending on the scales studied. In reality, rainfall processes interact across these scales, but until recently have been impossible to capture within a single model due to computational expense. Consequently we are unable to rely on these simulations as future estimations of rainfall for such a sensitive and anthropogenically impacted region as the Amazon.

 

In this study, we overcome these limitations by running convection permitting simulations (horizontal resolution 4.5km) over a large domain (6000km covering the majority of South America) using a Tropical configuration of the UK Met Office Unified Model. The high-resolution and continental-scale of these simulations present an opportunity to reduce the uncertainty in Amazonian rainfall estimates within a single model and ensures rainfall processes and interactions across scales are captured. To investigate the impacts of deforestation we will include a series of land-use sensitivity runs making use of a range of socioeconomic scenarios to 2050. Here we present initial results from our simulations, indicating how localised storms, mesoscale convective systems and large-scale circulations respond to land-use change.

How to cite: Bassett, R., Garcia-Carreras, L., Lowe, D., Alves, L., Fisch, G., Halladay, K., Kahana, R., and Veiga, J.: Deforestation and changes in rainfall across the Amazon – reducing uncertainty using a continental scale convection permitting domain, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6107, https://doi.org/10.5194/egusphere-egu23-6107, 2023.

EGU23-6994 | Posters on site | AS1.9

Grid spacing effects on convection initiation and aerosol-cloud interactions: A case study of a supercell storm from the Swabian MOSES 2021 field campaign 

Christian Barthlott, Beata Czajka, Martin Kohler, Corinna Hoose, Michael Kunz, Harald Saathoff, and Hengheng Zhang

The predictability of deep moist convection is subject to large uncertainties, mainly due to inaccurate initial and boundary data, incomplete description of physical processes, or uncertainties in microphysical parameterizations. In this study, we present hindcasts of a supercell storm that occurred during the Swabian MOSES field campaign in southwestern Germany in summer 2021. The supercell storm of 23 June 2021 passed directly over the main observation site equipped with various instruments, allowing a detailed comparison of simulations and observations. The preconvective radiosonde observations revealed suitable conditions for supercell development, i.e., low convective inhibition, moderate convective available potential energy, sufficient deep-layer shear, and a Bulk Richardson number of 22. Numerical simulations were performed with the ICOsahedral Non-hydrostatic (ICON) model using two horizontal grid spacings (i.e., 2 km/1 km) with a single-moment and a double-moment microphysics scheme. The double-moment scheme allows us to study aerosol effects on clouds and precipitation with cloud condensation nuclei (CCN) concentrations ranging from low to very high. Numerical results show that all 2-km model realizations do not simulate convective precipitation at the correct location and time. For the 1-km grid spacing, changes in aerosol concentration resulted in large changes in convective precipitation, causing the supercell to disappear completely in some simulations. Only the 1-km model run, which assumes a clean environment, is able to realistically capture the supercell storm. During the Swabian MOSES field campaign, aerosol particle concentrations and size distributions were continuously measured with an optical particle counter from June to August 2021. The day of the supercell storm was characterized by the lowest potential CCN values of the month, suggesting that the low aerosol concentration in the successful model run is a reasonable assumption for this case study. Possible reasons for the discrepant model results, i.e., effects of grid spacing on convection initiation and detailed analyses of microphysical process rates, are discussed. These results demonstrate the benefits of using an aerosol-aware double-moment microphysics scheme at high model resolution for convection initiation and cloud evolution, and that the use of different CCN concentrations can determine whether a supercell is successfully simulated or not.

How to cite: Barthlott, C., Czajka, B., Kohler, M., Hoose, C., Kunz, M., Saathoff, H., and Zhang, H.: Grid spacing effects on convection initiation and aerosol-cloud interactions: A case study of a supercell storm from the Swabian MOSES 2021 field campaign, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6994, https://doi.org/10.5194/egusphere-egu23-6994, 2023.

EGU23-9500 | Posters on site | AS1.9

Investigating links among heatwaves, precipitation, and land use types using the Convection-Permitting Model in the Southwest UK for the 2022 boreal summer 

Kwok Pan Chun, Yasemin Ezber, Emir Toker, Michelle Simões Reboita, Rosmeri Porfirio da Rocha, Bayu Christoforus Risanto, Omer Yetemen, Thanti Octavianti, Nevil Quinn, Omer Lutfi Sens, and Christopher Castro

To improve sub-seasonal forecasts, different global initiatives generate continental convection-permitting simulations for resolution less than 10 kilometres for multiple decades. These simulations, however, are based on land use maps with only single urban type. In this study, we explore how the density and height information of the urban canopy based on Local Climate Zones (LCZs) affect the dynamics among temperatures, precipitation and land use types for the 2022 summer heatwave in the Southwest UK. Four numerical experiments at a 3 km grid are run by switching off the parameterization of deep-convection in the Weather Research and Forecasting (WRF) models. These experiments are based on (i) the no urban scenario, (ii) the default MODIS land use scheme, (iii) the building environment parameterization (BEP), and (iv) the building energy model (BEM).

Results show that the cold advection over the UK led to downward motion according to a Q-vector analysis. The regional downward motion caused the formation of a heat dome. It is against the hypothesis that the 2022 summer heatwave was due to the hot circulation from Spain and equatorial Africa. Even though four land use schemes have similar simulated cold advection across the UK, our findings show that land use types affected water recycling due to local convection differently. These differences were related to the strength of rainstorms at the dissipating heatwave stage. Our results suggest that urban areas were more likely to have more persistent heatwaves since the intensity of rainstorms was affected by the lower local water recycling. This advanced understanding of the UK heatwave mechanism based on regional advection conditions and local convection processes will guide us on how to improve our sub-seasonal forecast in the urban area.

How to cite: Chun, K. P., Ezber, Y., Toker, E., Simões Reboita, M., Porfirio da Rocha, R., Risanto, B. C., Yetemen, O., Octavianti, T., Quinn, N., Sens, O. L., and Castro, C.: Investigating links among heatwaves, precipitation, and land use types using the Convection-Permitting Model in the Southwest UK for the 2022 boreal summer, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9500, https://doi.org/10.5194/egusphere-egu23-9500, 2023.

EGU23-10212 | ECS | Orals | AS1.9 | Highlight

Severe hail in France: reconstruction of Storm Ela’s and late June 2022 hailstorms 

Davide Panosetti, Christopher Allen, Obaidullah Yaqubi, and Orane Thollon

Hail is by far the greatest contributor to insured losses from severe convective storms on an annual basis. Individual severe convective storm outbreaks can cause hail losses well above EUR 1 bn. In May and June 2022 a series of such events impacted France, Germany and Belgium. Of these, those occurring on 19-22 June 2022 were particularly damaging as they hit the large metropolitan region of Ile-de-France. There were many reports of large hailstones, causing significant damage to property and motor vehicle. Total insured hail loss estimates in France alone exceeded EUR 2.4 bn, of which EUR 1.34 bn of property loss and EUR 1.08 bn of motor vehicle loss. These were the largest hail events in France in terms of losses since Storm Ela’s, which on 9-10 June 2014 resulted in insured hail losses in excess of 900 mn in 2021 EUR.

Common denominator to these two impactful events were persistent meteorological situations conducive to large-scale severe convective storms for several consecutive days. These compounded with local conditions favorable for the development of severe hail. Maximum hailstone sizes of 12 cm in diameter were observed in the administrative regions of Centre-Val-De-Loire (Ela) and Occitanie (June 2022). In this study we present a reconstruction of these events based on eye-witness reports cross-referenced with weather radar data. We analyze the synoptic configurations and pre-convective environments that characterized them, with particular focus on those properties and features that are peculiar to severe hail-forming thunderstorms. These event reconstructions are part of our effort to construct a Realistic Disaster Scenario (RDS) model for France and Belgium to stress test both individual client portfolios and the market as a whole.

How to cite: Panosetti, D., Allen, C., Yaqubi, O., and Thollon, O.: Severe hail in France: reconstruction of Storm Ela’s and late June 2022 hailstorms, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10212, https://doi.org/10.5194/egusphere-egu23-10212, 2023.

The topography plays an essential role in initiation and development on precipitating clouds, therefore has a profound effect on the ultimate spatial distributions of precipitation. This study investigates the fine-scale characteristics of synoptic-induced precipitation over Southwest China, a region characterized by a sequence of steep mountains aligned roughly north-south. Based on the convection-permitting simulation for a realistic case, the results show that the model successfully reproduces the observed precipitation, which is induced by a low-level shear line over Southwest China. The spatial distribution of precipitation over three small-scale mountains (named as M1, M2 and M3 from east to west) exhibits distinct inhomogeneity. The precipitation is notably enhanced on the leeward slope of M1, the high-altitude area of M2, as well as the windward slope of M3, which is driven by the steep topography relief, through exerting dominant influences on the local atmospheric circulations. Further results of the high-resolution experiment shows that the thermal instabilities and topographic lifting over the high-altitude ridges are beneficial to the enhanced precipitation. In addition, the small-scale vortex generated on the leeward slope of M1, as well as the convergence zones established over M2 and the windward slope of M3, dynamically contribute to the intensification of precipitation over these three small-scale mountains. In sensitivity simulation with the terrain height of M2 reduced to the comparable height as the other two mountains, the enhanced precipitation decreases significantly over M2. The dynamic blocking effect of M2 on airflow is weakened, leading to the maximum precipitation over M3 moving to its mountaintop.

How to cite: Zhang, M., Li, J., and Li, N.: Spatial inhomogeneity of synoptic-induced precipitation in a region of steep topographic relief, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10335, https://doi.org/10.5194/egusphere-egu23-10335, 2023.

It has been known that potential vorticity (PV) diagnostics can be employed to (a) evaluate large-scale dynamics of hurricane movement, and (b) assess the storm’s influence on its own track. Moreover, PV variations and temperature adjustments at the tropospheric interior and the associated general circulation theory are closely related to the surface PV. Diagnosis of the surface PV is, however, complicated due to data availability/coarse-resolution configurations across the wide terrain in topographic regions. In this work we develop a high-resolution configuration for the Gulf of Mexico (GoM) region for employing in the Weather Research and Forecasting (WRF) model to study Hurricanes Harvey and Ida. The new configuration includes horizontal resolutions of 5 km and 1.67 km in the main and nest domains, respectively; 55 vertical heights (potential pressure levels) are also considered. Forecasts of Hurricane Harvey for 132-hours (5days + 12 hrs), and Hurricane Ida for 78-hours (3days + 6 hrs) are performed, and outputs are stored at every 15 minutes. It is shown that surface PV changes its sign when the Hurricane Harvey/Ida arrives over the land while PV at high altitudes are conserved. We show that the surface PV change is due to the change of vertical temperature gradient at the surface (i.e. change of surface layer stability). These dynamical evolutions are coincident with an increase in precipitation rate and accumulated precipitation of hurricane aftermath. We discuss how these meteorological processes can possibly influence hurricane movements.

How to cite: Khani, S. and Dawson, C. N.: Potential vorticity and surface layer stability in hurricane movement: case studies of Hurricanes Harvey and Ida, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11156, https://doi.org/10.5194/egusphere-egu23-11156, 2023.

EGU23-11509 | ECS | Posters on site | AS1.9

A study on the diurnal variation of the snowfall structure in the western coastal region of the Korean Peninsula. 

Soojin Yoo, Eun-Chul Chang, and GyuWon Lee

 On the western coastal region of the Korean Peninsula in the winter, heavy snowfall occurs due to air mass modification which is called the western coast snowfall. The western coast snowfall occurs through a mechanism similar to the lake effect snowfall that is formed over the Great Lakes in the North America. In the winter season, cold and dry northwesterly wind blowing from the south-eastern flank of the Siberian High is formed over the Yellow Sea. The cold and dry air mass from the continent gets heat and moisture from the ocean when it passes over the relatively warm sea surface, , which invigorate snow clouds. The snow clouds generated over the ocean flow into the western coastal region by the westerly winds, hence predicting when the snow clouds flow into the land is important for snowfall forecast. Although the western coast snowfall can persist for several days when the synoptic environment is maintained, diurnal fluctuations in snowfall inflow appears during the snowfall cases. In this study, the diurnal variation of snowfall inflow on the western coastal region was investigated by analyzing of the dynamic/thermodynamic factors affecting the diurnal variation. The western coast snowfall shows snowfall inflow into the land in the evening, then inflow decreases after sunrise, with the snowfall becoming concentrated over the ocean, and the snowfall inflow increases after sunset. The diurnal variation of the snowfall inflow structure appears with the diurnal variation of the dynamic/thermodynamic structure according to the solar radiation diurnal cycle. During the evening, as the temperature of the lower troposphere over the land decreases due to radiative cooling, the lower troposphere thermal stability increases. After sunrise, the planetary boundary layer (PBL) height grows due to radiative heating, and the wind in the lower troposphere weakens, limiting the snowfall inflow to 9 LST, where both factors affect simultaneously. In addition, as the lower troposphere temperature over the land decreases, the land-sea horizontal temperature contrast increases, and the density wall of the colder land blocks the inflow of the snowfall. On the other hand, during the daytime, the lower troposphere temperature of the land rises due to radiative heating and the thermal stability decreases. As the horizontal temperature contrast decreases and the PBL height decreases after sunset, the lower troposphere wind becomes stronger, which allows the snowfall penetrates into the land. According to the time lag in heating/cooling by radiation of the lower troposphere, it is analyzed that the time point of snowfall inflow interruption (increasing) appears after sunrise (sunset).

 

Acknowledgement

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government(MSIT) (No. 2021R1A4A1032646).

How to cite: Yoo, S., Chang, E.-C., and Lee, G.: A study on the diurnal variation of the snowfall structure in the western coastal region of the Korean Peninsula., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11509, https://doi.org/10.5194/egusphere-egu23-11509, 2023.

EGU23-14475 | ECS | Posters on site | AS1.9

Changes in land surface effects on organised convection in a convection-permitting climate projection 

Cornelia Klein, Emma Barton, and Christopher Taylor

Convection-permitting (CP) climate simulations represent a major advance in capturing land surface effects on convection. From observational analyses in West Africa, we know that land surface conditions are a major driver of storm initiation as well as intensification during later stages of the storm life cycle. Dry soils of 10 km to several 100s of km scale can cause anomalous warming of the planetary boundary layer and affect horizontal circulations, regional moisture convergence as well as instability. However, to date it remains unclear whether, in a warming climate, larger and more intense storms may change the scale and frequency of surface patterns, feeding back on these identified processes. Here, we evaluate the ability of a pioneering convection-permitting (4.4km) pan-African climate simulation to capture the observed land effects on the pre-convective environment in West Africa and subsequent storm characteristics. This is compared to a CP climate projection representing a decade under a very high emission scenario around 2100 in order to reveal potential changes in process interactions and consequences for organised convection in the future. 

How to cite: Klein, C., Barton, E., and Taylor, C.: Changes in land surface effects on organised convection in a convection-permitting climate projection, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14475, https://doi.org/10.5194/egusphere-egu23-14475, 2023.

EGU23-14661 | ECS | Posters on site | AS1.9

Analysis of the impact of selected sources of uncertainty on precipitation simultaions of summer convection over Central Europe 

Beata Czajka, Christian Barthlott, Martin Kohler, Andreas Wieser, and Corinna Hoose

In this study we investigate the impact of several selected sources of uncertainty on convective precipitation prediction. For this purpose, we conduct numerical simulations with the ICOsahedral Non-hydrostatic (ICON) model for two consecutive days in June, 2021, on which deep moist convection triggered by different synoptic forcing occurred over southwestern Germany. We use single- and double-moment microphysics schemes and vary the initial soil moisture, grid spacing, and cloud condensation nuclei (CCN) concentration. We compare the results with measurements conducted on the same two days during the Swabian MOSES (Modular Observation Solutions for Earth Systems) field campaign. We find that the applied dry bias (initial soil moisture in the model reduced by 25%) much better represents the actual soil moisture conditions and leads to an improved quantitative precipitation forecast when compared to radar-derived precipitation amounts. Furthermore, the model resolution impacts the precipitation amount, intensity, and the timing of convection initiation: while 1-km runs show the least root mean square error for 24-hour precipitation sums, the onset of convective precipitation in 2-km resolution runs matches better the observations. However, the overall impact of this factor is not always systematic. The comparison of several radiosounding-derived convective indices (e.g. lifted index, convective available potential energy, convective inhibition) with model data yield many non-systematic results. For instance, CCN concentrations do not seem to have any significant impact on any of the calculated indices. At the same time, runs with coarser resolution (2-km) often better depict the temporal development of CAPE but overestimate its amount.

How to cite: Czajka, B., Barthlott, C., Kohler, M., Wieser, A., and Hoose, C.: Analysis of the impact of selected sources of uncertainty on precipitation simultaions of summer convection over Central Europe, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14661, https://doi.org/10.5194/egusphere-egu23-14661, 2023.

EGU23-15734 | ECS | Posters on site | AS1.9

Do Mesoscale Convective Systems precipitation follows the Clausius-Clapeyron relationship? 

Nicolas Da Silva and Jan Haerter

Floods related to heavy precipitation are common over Europe during both the warm and the cold seasons. In a way to better understand these heavy precipitation systems and their potential evolution in a warming climate, several studies investigated the dependency of precipitation extremes to temperature over Europe (e.g. Lenderink et al., 2008; Berg et al., 2013). It was found that the scaling of precipitation extremes can exceed the scaling expected from the Clausius-Clapeyron (CC) relationship, relating temperature to the water holding capacity of the atmosphere. While several potential explanations were proposed, a recent study (Lochbihler et al., 2017) noted the important role of large systems in determining this “super-CC” scaling over the Netherlands.

Building on this study, we further investigate the role of Mesoscale Convective Systems (MCS) in determining the temperature precipitation relationship over Europe. The detection and tracking of MCSs is based on the recent Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG; Huffman et al., 2019) satellite precipitation climatology. We use the EUropean Cooperation for LIghtning Detection (EUCLID) lightning dataset to distinguish between stratiform (or shallow convective) and deep convective rain patches without introducing bias in precipitation intensity. We select the temperature upstream of the MCS tracks, as a proxy of the moisture source involved in the formation of MCS precipitation.

MCS can display strong dynamical features such as the rear inflow jet or cold pools, of which the effects on precipitation as well as their changes with temperature are still unclear. It suggests that MCS precipitation may deviate significantly from the CC scaling. Additionally, the processes involved in MCS precipitation may differ depending on the stage of the MCS life cycle. We thus characterize the temperature dependency of MCS precipitation and their 2-D structure at different stages of their life cycle. This work contributes to better understanding the drivers of MCS precipitation and how these may evolve in a warming climate.

References

Berg, P., Moseley, C., & Haerter, J. O. (2013). Strong increase in convective precipitation in response to higher temperatures. Nature Geoscience, 6(3), 181-185.

Huffman GJ, Stocker EF, Bolvin DT, Nelkin EJ, Tan J. 2019. GPM IMERG final precipitation L3 half hourly 0.1 degree x 0.1 degree V06, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center. doi: 10.5067/GPM/IMERG/3B-HH/06

Lenderink, G., & Van Meijgaard, E. (2008). Increase in hourly precipitation extremes beyond expectations from temperature changes. Nature Geoscience, 1(8), 511-514.

Lochbihler, K., Lenderink, G., & Siebesma, A. P. (2017). The spatial extent of rainfall events and its relation to precipitation scaling. Geophysical Research Letters, 44(16), 8629-8636.



How to cite: Da Silva, N. and Haerter, J.: Do Mesoscale Convective Systems precipitation follows the Clausius-Clapeyron relationship?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15734, https://doi.org/10.5194/egusphere-egu23-15734, 2023.

EGU23-16303 | ECS | Orals | AS1.9 | Highlight

Environmental Precursors to Mesoscale Convective Systems 

Mark Muetzelfeldt, Robert Plant, and Hannah Christensen

Mesoscale convective systems (MCSs) are important components of the Earth’s weather and climate systems. They produce a large fraction of tropical rainfall and their top-heavy heating profiles can feedback onto atmospheric dynamics. Understanding the large-scale environmental precursor conditions that cause their formation is normally done as case studies or on a regional basis. Here, we take a global view on this problem, linking tracked MCSs to the environmental conditions that lead to their growth and maintenance. We consider common variables associated with deep convection, such as CAPE, total column water vapour and moisture convergence. We take care to distinguish between conditions associated with deep convection, and conditions associated with MCSs specifically. Furthermore, we pose the question in a way that is useful for the development of an MCS parametrization scheme, by asking what environmental conditions lead to MCS occurrence, instead of locating an MCS and then finding the associated conditions.

How to cite: Muetzelfeldt, M., Plant, R., and Christensen, H.: Environmental Precursors to Mesoscale Convective Systems, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16303, https://doi.org/10.5194/egusphere-egu23-16303, 2023.

EGU23-22 | Orals | AS1.10

Observational and Modeling Studies of High Ice Water Content Clouds: Implications for Process–Oriented Understanding 

Greg McFarquhar, Yongjie Huang, Yachao Hu, Peter Brechner, Alexei Korolev, Hugh Morrison, Jason Milbrandt, Mengistu Wolde, Cuong Nguyen, and Alain Protat

High ice water content (HIWC) regions with small ice crystals, where ice water contents (IWCs) are greater than 1.5 g m-3 and median mass diameters (MMDs) less than about 300 micrometers, occur above tropical mesoscale convective systems (MCSs) and can have detrimental impacts on aircraft engines. Data collected by the French Falcon aircraft and the National Research Council of Canada Convair-580 during the 2014 and 2015 High Altitude Ice Crystals and High Ice Water Content (HAIC/HIWC) projects are revisited here along with coordinated modeling studies to investigate processes that can produce such HIWCs. In particular, data collected from 2014 in the vicinity of Darwin Australia and from 2015 in the vicinity of Cayenne French Guyana are used to determine how bulk microphysical properties (e.g., number concentration, IWC, median volume diameter) and characteristics of ice crystal size distributions (i.e., multimodal nature, parameters fit to gamma distributions for each mode) vary with environmental conditions such as temperature, vertical velocity, MCS age, distance from MCS core, and surface characteristics. It is determined that temperature and vertical velocity are the biggest controls of small ice crystals, but younger cells, stronger convective strengths and closer proximity to convective cores also increase the relative importance of small crystals.

Numerical simulations conducted using the Weather Research and Forecasting model with four different bulk microphysics schemes generally reproduce the observed temperature, dew-point, and wind structure. However, comparison of regime-specific observations against properties simulated over Cayenne using a variety of existing parameterization schemes show that although the coverage and evolution of convection is well predicted, simulations overestimate the intensity and spatial extent of observed airborne X-band radar reflectivity and do not well depict the peak of observed size distributions with maximum dimensions between 0.1 and 1 mm. To explore formation mechanisms for large numbers of small ice crystals, a series of simulations varying the representation of secondary ice production (SIP) processes were conducted. Simulations including one of three SIP mechanisms separately (i.e., the Hallett–Mossop mechanism, fragmentation during ice–ice collisions, and shattering of freezing droplets) did not replicate the observed ratio of number concentration divided by IWC. However, the simulation including all three SIP processes produced HIWC regions consistent with observations in terms of number concentration and radar reflectivity, which was not replicated using the original P3 two-ice category configuration that only included the Hallett-Mossop mechanism. In summary, observations and simulations show primary ice production plays a key role in generating HIWC regions at temperatures < -40 Celsius, shattering of freezing droplets dominates ice particle production in HIWC regions between -15 and 0 Celsius during the early stage of convection, and fragmentation during ice–ice collisions dominates between -15 and 0 Celsius during the later stage of convection and between -40 and -20 Celsius over the whole convection period. This study thus shows the dominant role of SIP processes in the formation of numerous small crystals in HIWC regions. Implications for future measurement and modeling needs are discussed.

How to cite: McFarquhar, G., Huang, Y., Hu, Y., Brechner, P., Korolev, A., Morrison, H., Milbrandt, J., Wolde, M., Nguyen, C., and Protat, A.: Observational and Modeling Studies of High Ice Water Content Clouds: Implications for Process–Oriented Understanding, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-22, https://doi.org/10.5194/egusphere-egu23-22, 2023.

EGU23-829 | ECS | Posters on site | AS1.10

Improving the Balloon-borne Ice Cloud Particle Imager (B-ICI) 

János Stenszky and Thomas Kuhn

Atmospheric constituents, such as aerosols and clouds, greatly affect the
radiative properties of the atmosphere. Clouds play a substantial role in this
radiative balance. To better understand the contribution of cirrus clouds im-
proved modelling and in-situ observations are needed.
For further improving current climate-modelling parameters, accurate pa-
rameterization of these clouds are required. From in-situ measurements, the
size distribution of cirrus ice particles, their concentration and shape param-
eters can be determined. This can be achieved with the iBalloon-borne Ice
Cloud particle Imager (B-ICI). Campaigns done with the B-ICI and resulting
parameetrizations have contributed to more accurate characterization of cirrus
clouds.
The B-ICI is collecting and imaging ice particles with a pixel resolution
of 1,65 µm/pixel. With detailed image analysis at this accuracy particles >
20µm can be distinguished, dimensions and concentration can be derived, and
particles can be sorted according to their shape. An improved version of B-ICI
is currently being developed. This new version of the instrument is primarily
improving image quality to enable easier and more automated image processing.
Secondarily, changes in the design will reduce the weight of the instrument
and simplify the method for sampling of ice particles. A more light-weight
instrument will allow adding other sensors. In particular, an optical particle
counter to measure aerosol and small ice particles will be added to the B-ICI.
This addition of an optical particle counter will result in more accurate size
distributions in addition of providing complementary aerosol measurements. In
this paper, we will highlight these changes and improvements in the B-ICI set-
up.

How to cite: Stenszky, J. and Kuhn, T.: Improving the Balloon-borne Ice Cloud Particle Imager (B-ICI), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-829, https://doi.org/10.5194/egusphere-egu23-829, 2023.

EGU23-2309 | ECS | Posters on site | AS1.10

An idealized model to assess the impact of gravity waves on ice crystal populations in the Tropical Tropopause Layer 

Milena Corcos, Albert Hertzog, Riwal Plougonven, and Aurélien Podglajen

The role of gravity waves on microphysics of tropical cirrus clouds and air parcel dehydration was studied using the combination of Lagrangian observations of temperature fluctuations and a 1.5 dimension model. High frequency measurements during isopycnal balloon flights were used to resolve the gravity wave signals with periods ranging from 15min to a few days. The detailed microphysical simulations with homogeneous freezing, sedimentation and a crude horizontal mixing represent the slow ascent of air parcels in the Tropical Tropopause Layer. A reference simulation describes the slow ascent of air parcels in the tropical tropopause layer, with nucleation occurring only below the cold point tropopause with a small ice crystals density. The inclusion of the gravity waves modifies drastically the low ice concentration vertical profile and weak dehydration found during the ascent alone: numerous events of nucleation occur below and above the cold point tropopause, efficiently restoring the relative humidity over ice to equilibrium with respect to the background temperature, as well as increase the cloud fraction in the vicinity of the cold-point tropopause. The increased ice crystal number and size distribution agree better with observations.

How to cite: Corcos, M., Hertzog, A., Plougonven, R., and Podglajen, A.: An idealized model to assess the impact of gravity waves on ice crystal populations in the Tropical Tropopause Layer, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2309, https://doi.org/10.5194/egusphere-egu23-2309, 2023.

The HIAPER Cloud Radar (HCR) is a 94 GHz W-band radar deployed in an underwing pod on the NCAR HIAPER aircraft. We use dual polarized Doppler observations collected in three major field campaigns:

  • The Cloud Systems Evolution in the Trades (CSET) study focused on the characterization of the cloud fields in the stratocumulus and the fair-weather cumulus regimes within the subtropical easterlies over the northern Pacific.
  • Motivated by challenges in their modeling, Southern Ocean clouds were observed south of Tasmania during the Southern Ocean Clouds, Radiation, Aerosol Transport Experimental Study (SOCRATES).
  • Deep convective clouds in a tropical environment were the focus in the Organization of Tropical East Pacific Convection (OTREC) field campaign.

In this study we classify clouds sampled by HCR in these very different environments into twelve categories, based on the clouds’ convective and stratiform characteristics. We calculate dimensional and convective properties of the clouds in the different categories and contrast and compare derived statistics. We analyze updraft regions observed in all cloud categories, their dimensions and velocities. Characteristics of precipitation shafts from the precipitating clouds, such as precipitation fraction or strength are also provided.

How to cite: Romatschke, U.: Cloud properties from airborne radar observations collected in field campaigns, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2868, https://doi.org/10.5194/egusphere-egu23-2868, 2023.

EGU23-2964 | Orals | AS1.10

Implementing a process-based contrail parametrization in the Unified Model 

Timmy Francis, Alex Rap, Kwinten Van Weverberg, James Manners, Kalli Furtado, Weiyu Zhang, Piers Forster, and Cyril Morcrette

     The global aviation fleet modifies cloudiness through contrail formation and their subsequent competition with natural cirrus for ambient water vapor, along with enhanced ice-nuclei concentrations from aircraft soot emissions. Contrails form in the upper troposphere at temperatures below 233 K and pressures below 300 hPa, when plume gases from jet engines, having appreciable water vapor content, saturate with respect to liquid water (Schmidt-Appleman Criterion, SAC). Realistic assessments of the aviation-induced modifications to global cloud cover demand improved representation of contrails and their interaction with background cloudiness in climate models. We have implemented a process-based parametrization of contrail cirrus, that applies to both young (≤ 5 h) and aged contrails, in the UK Met Office Unified Model, version 12.0. Contrail cirrus is introduced as a new prognostic cloud class, forming in the parametrized, fractional ice supersaturated area which then undergoes advection, depositional growth, sublimation and sedimentation. The proxy for the fractional supersaturated area is calculated using the same total water PDF as used for natural cirrus but with a different critical relative humidity, rcc - a value at which part of the model grid box is at least ice-saturated. The persistence of contrails being allowed in the ice supersaturated areas, the simulated coverage is not confined to flight corridors, but is advected to air traffic free zones as well. The simulated annual mean global coverage due to young contrails is 0.13%, with the main traffic areas of Europe and North America having the maximum coverage. Similar to natural cirrus, the contrail ice particles reflect the solar short-wave (SW) radiation and trap outgoing long-wave (LW) radiation, thereby modifying the radiative balance of the Earth’s atmosphere. Contrail cirrus is radiatively active in the model with forcing studies enabled via a ‘double radiation call’ approach, wherein parallel runs of the radiation scheme ‘with’ (prognostic) and ‘without’ (diagnostic) the contrail radiative effects isolates the contrail-induced perturbations. Contrails are seen to induce a short-wave cooling and long-wave warming and the net (SW+LW) direct top-of-atmosphere radiative forcing by young contrails amounts globally to 0.5 mWm-2, with the peak forcing seen along the main air traffic areas of North America, Europe and East Asia. The implementation of this process-based parametrization in the UM enables the simulation of the life cycle of persistent contrails, and can provide valuable insights to the aviation-induced modifications to the global cloud cover.

How to cite: Francis, T., Rap, A., Van Weverberg, K., Manners, J., Furtado, K., Zhang, W., Forster, P., and Morcrette, C.: Implementing a process-based contrail parametrization in the Unified Model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2964, https://doi.org/10.5194/egusphere-egu23-2964, 2023.

EGU23-4195 | ECS | Posters on site | AS1.10

Modeling Secondary Ice Processes on a midlatitude squall line 

Jie Gao and Huiwen Xue

Secondary ice processes (SIPs) can produce ice crystals with a number concentration much higher than that of ice nucleating particles (INPs) in mixed-phase clouds, and therefore influence cloud glaciation and precipitation. But the role of SIPs in midlatitude continental mesoscale convective systems (MCSs) such as squall lines is still unknown. This study investigates the relative importance of rime splintering, freezing drop shattering, and collision breakup in the mature stage of a squall line case in North China on 18 August 2020 using the WRF model. The simulations show that collision breakup has the most pronounced effect on ice production, and rime splintering plays a secondary role. It is because ice multiplication from SIPs can feedback to collision breakup and rime splintering in different ways. Collision breakup has a positive feedback because the numerous snow and graupel from SIPs in turn promote a higher collision breakup rate, while rime splintering is limited by itself and also limited by collision breakup because the weaker riming due to the two SIPs leads to a lower rime splintering rate. Freezing drop shattering has a negligible effect on ice production because there are few large droplets in the mature stage. Collision breakup can also redistribute surface precipitation in the squall line, which decreases in the convective region and increases in the stratiform region. The influence of aerosols as CCN and INPs on SIPs is further studied. Preliminary simulation results show that the effects of aerosol concentration on the rate of SIPs and anvil ice concentration are nonlinear. The mechanism remains to be analyzed.

How to cite: Gao, J. and Xue, H.: Modeling Secondary Ice Processes on a midlatitude squall line, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4195, https://doi.org/10.5194/egusphere-egu23-4195, 2023.

EGU23-5000 | ECS | Orals | AS1.10

Airborne observations of riming in arctic mixed-phase clouds during HALO-(AC)3 

Nina Maherndl, Maximilian Maahn, Manuel Moser, Johannes Lucke, Mario Mech, and Nils Risse

Ice crystal formation and growth processes in mixed-phase clouds (MPCs) are not sufficiently understood leading to uncertainties of atmospheric models in representing MPCs. One of these processes is riming, which occurs when liquid water droplets freeze onto ice crystals. Riming plays a key role in precipitation formation in MPCs by efficiently converting liquid cloud water into ice. However, riming is challenging to observe directly and there are only few studies quantifying riming in Arctic MPCs.

In this study, we derive the normalized rime mass 𝑀 to quantify riming. We use airborne data collected during the (AC)3  field campaign HALO-(AC)3  performed in 2022. For this campaign, two aircraft were flying in formation collecting closely spatially collocated and almost simultaneous in situ and remote sensing observations. We aim to quantify 𝑀 by two methods. First, we present an Optimal Estimation algorithm to retrieve 𝑀 from measured radar reflectivities. We find 𝑀 by matching measured with simulated radar reflectivities 𝑍𝑒obtained from in situ particle number concentration observations. As forward operators, we use the Passive and Active Microwave radiative TRAnsfer tool (PAMTRA) and empirical relationships of 𝑀 and particle properties. The latter are derived via aggregation and riming model calculations. Second, we derive 𝑀 from in situ measured particle shape. We calculate the complexity 𝜒 of in situ measured particles, which relates particle perimeter to area. We then derive 𝑀 from empirical relationships that were again obtained from synthetic particles. We compare the obtained 𝑀 derived by both methods and evaluate the occurrence of riming in terms of meteorological conditions and macrophysical cloud properties to understand external drivers and variability of riming. This will lead to a better understanding of riming and thereby helps to improve modelling of this important arctic MPC process.

How to cite: Maherndl, N., Maahn, M., Moser, M., Lucke, J., Mech, M., and Risse, N.: Airborne observations of riming in arctic mixed-phase clouds during HALO-(AC)3, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5000, https://doi.org/10.5194/egusphere-egu23-5000, 2023.

EGU23-5002 | ECS | Orals | AS1.10

Identification of cirrus formation regimes using cluster analysis of back trajectories and satellite data 

Kai Jeggle, David Neubauer, and Ulrike Lohmann

In recent years our understanding of cirrus cloud processes has been significantly advanced. However, a large uncertainty regarding the influence of cirrus formation mechanisms on the microphysical properties, and hence radiative properties of cirrus clouds still remains. This leads to uncertainty in global climate models and climate change projections. In this work we aim to identify different cirrus formation regimes and analyze their influence on cirrus microphysical properties. We combine DARDAR-Nice satellite observations with Lagrangian back trajectories of meteorological and aerosol reanalysis data on the Northern Hemisphere. Our goal is to classify observed cirrus clouds by means of their trajectories and investigate the trajectories' influence on observed cirrus microphysical properties. With our data-driven nested clustering approach we identify different meteorological regimes that lead to cirrus formation. We are also able to isolate the effect of dust ice nucleating particle (INP) exposure along the trajectory from meteorological variability.

We identify four different meteorological clusters that lead to characteristic cirrus cloud microphysical properties and can be associated with liquid origin and in-situ formed cirrus clouds. Furthermore, we find that dust concentrations in cirrus cloud back trajectories are significantly higher compared to cloud free trajectories with comparable meteorological conditions. This indicates the importance of dust acting as INP during heterogeneous nucleation. The magnitude of the dust concentration, however, has only a negligible effect on cirrus microphysical properties.

How to cite: Jeggle, K., Neubauer, D., and Lohmann, U.: Identification of cirrus formation regimes using cluster analysis of back trajectories and satellite data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5002, https://doi.org/10.5194/egusphere-egu23-5002, 2023.

EGU23-5327 | Orals | AS1.10

Ice multiplication in simulated deep convective clouds with the ICON model 

Cunbo Han, Corinna Hoose, and Viktoria Dürlich

Ice multiplication processes have been recognized to play an important role in the forming of cloud ice crystals, and multiple mechanisms have been proposed to describe ice multiplication. Ice multiplication processes have been investigated for a variety of cloud types, but mostly for stratiform clouds or shallow cumulus, which do not reach temperatures of homogeneous freezing. In this study, sensitivity experiments are performed to study the role of ice multiplication in the developing stages of deep convective clouds. A double-moment cloud physics scheme was adopted. Except as the default Hallett-Mossop rime splintering process, two additional ice multiplication processes, which are droplet shattering during the freezing of supercooled drops and the collisional breakup of ice particles, are implemented. Moreover, two different parameterization schemes for the collisional breakup of ice particles. Simulation results reveal that the ice multiplication processes have a significant impact on the cloud microphysical properties and thermodynamic phase distribution within the cloud. At the cloud top, the fingerprint of ice multiplication is weaker. Collisional breakup is found to dominate ice multiplication, and the collisional breakup process rate is larger than rime splintering and droplet shattering process rates by 4 and 3 orders of magnitude, respectively. The ice enhancement factor (the ratio of ice mass or number in simulations with and without ice multiplication) has a strong vertical variation, with the maximum around -10°C and -25°C. Besides, the cascade effect on ice cloud number concentration was also investigated.

How to cite: Han, C., Hoose, C., and Dürlich, V.: Ice multiplication in simulated deep convective clouds with the ICON model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5327, https://doi.org/10.5194/egusphere-egu23-5327, 2023.

EGU23-6077 | ECS | Posters on site | AS1.10

Representation of Arctic mixed-phase clouds in ECMWF forecasts during ACLOUD 

Hanno Müller, Johannes Röttenbacher, Michael Schäfer, André Ehrlich, and Manfred Wendisch

The representation of Arctic clouds in numerical weather prediction models is challenging, especially for mixed-phase clouds with both a liquid and ice phase present. We compare measurements conducted during the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign, which took place in May/June 2017 northwest of Svalbard, Norway, with the operational ‘Atmospheric Model high resolution’ configuration (HRES) of the Integrated Forecasting System (IFS), operated by the European Centre for Medium-Range Weather Forecasts (ECMWF). Instead of using cloud retrieval products from airborne remote sensing, the comparison is performed in the observational space of spectral solar irradiances reflected by the clouds. To allow such an analysis along the flight track at flight level, the operational ecRad radiation scheme of the IFS is used in offline mode. Besides the HRES model output, vertical profiles of concentrations of trace and greenhouse gases provided by the ECMWF Atmospheric Composition Reanalysis 4 serve as the input for ecRad. The ability of the IFS to realistically represent the airborne radiation measurements collected during ACLOUD is evaluated for flight sections above sea ice and open ocean. Inconsistencies between the upward irradiance observed during ACLOUD and the simulations by ecRad are found and may originate from uncertainties introduced by the cloud fraction, the cloud phase, the sea ice albedo, and the ice optics parameterization. Our analysis aims to separate the influence of the different macro- and microphysical parameters on the upward irradiance. To disentangle the impact of these parameters, the spectral irradiance is analyzed where e.g. the impact of liquid and ice phase can be separated. Different case studies give insight into a sub-grid cloud cover variability that is not seen by the IFS above open ocean and an overestimation of the measurements by ecRad above sea ice that can be explained by the lack of cloud brightness. EcRad is additionally run with improved ice optics parameterizations. The choice of the applied ice optics becomes more important with an increasing ice water path of the clouds and is investigated in detail within the near-infrared bands of ecRad.

How to cite: Müller, H., Röttenbacher, J., Schäfer, M., Ehrlich, A., and Wendisch, M.: Representation of Arctic mixed-phase clouds in ECMWF forecasts during ACLOUD, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6077, https://doi.org/10.5194/egusphere-egu23-6077, 2023.

EGU23-6114 | ECS | Posters on site | AS1.10

Climatological analysis of warm conveyor belt contributions to UTLS moisture content 

Ziyan Guo, Cornelis Schwenk, Maxi Boettcher, Nils Brast, Philip Reutter, and Annette Miltenberger

The Upper Troposphere-Lower Stratosphere (UTLS) is a transition region for coupled dynamical, chemical and microphysical processes. These coupled processes play an essential role in climate change. Water vapor, ozone and aerosols in the UTLS region have important impacts on the Earth’s radiation budget. Systematic biases in UTLS moisture are known to exist in global climate models. Understanding the sources of UTLS moisture and quantifying the transport processes that control water vapor and clouds in the UTLS can provide important insights into the model uncertainties and improve model simulations. In the extratropics ascending airstreams in extratropical cyclones, particularly the warm conveyor belt (WCB), and deep convection are thought to be the most important sources of UTLS moisture. Here, we utilize ERA5 reanalysis data and IAGOS aircraft measurements to quantify the contribution of WCBs to UTLS moisture for the decade 2010 to 2019. WCB outflow regions are defined using Lagrangian trajectories. The moisture anomaly in the WCB outflow compared to average UTLS moisture content is quantified as well as its evolution over the 2 days after WCB ascent. ERA5 suggests significant positive moisture anomalies in the WCB outflow that persists over several days. Finally, ERA5 UTLS moisture content is compared to IAGOS humidity measurements with a particular focus on WCB outflow regions. In summary, we present a comprehensive climatological picture of the role of WCB moisture transport for the UTLS composition.

How to cite: Guo, Z., Schwenk, C., Boettcher, M., Brast, N., Reutter, P., and Miltenberger, A.: Climatological analysis of warm conveyor belt contributions to UTLS moisture content, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6114, https://doi.org/10.5194/egusphere-egu23-6114, 2023.

Recent experiments and modelling studies suggest that secondary ice production (SIP) may close the gap between observed Arctic ice nucleating particle (INP) concentrations and ice crystal number concentrations (Ni). Here we explore model sensitivities with respect to the complexity of different INP parameterisations in numerical simulations under the premiss that Ni is governed by SIP. Idealised, cloud-resolving simulations are performed for the marine cold air outbreak cloud deck sampled during M-PACE (cloud-top temperature of -17°C) with the ICOsahedral Nonhydrostatic (ICON) model.

Droplet shattering (DS) of rain drops according to Phillips et al. (2018), and collisional breakup (CB) (Phillips et al. 2017) were implemented and tested in addition to the existing Hallet-Mossop (HM) rime splintering implemented in ICON’s state-of-the-art two-moment bulk microphysics scheme. Furthermore, a fully prognostic temperature-dependent budget representation of INP (Solomon et al. 2015) was implemented and contrasted to a less sophisticated time-relaxation formulation of atmospheric INP concentrations.

Overall, 16 different model experiments (24h runs) were performed and analysed. Despite the considerable amount of uncertainty remaining with regard to ice production mechanisms and their process representation in numerical models we conclude from these experiments that: (i) Ni-enhancement through SIP can close the gap between measured and simulated Ni concentrations during M-PACE in ICON consistent with previous studies (e.g. Sotiropoulou et al. 2020; Zhao et al. 2021), (ii) only simulations where DS dominates the SIP signal (potentially amplified by CB) capture the vertical Ni in-cloud profile correctly, (iii) INP recycling remains necessary for MPC maintenance during M-PACE even if Ni is dominated by SIP, and (iv) experiments using a computationally more efficient relaxation-based prognostic parameterisation of primary nucleation are statistically invariant from simulations considering a prognostic INP budget.

How to cite: Possner, A., Pfannkuch, K., and Ramadoss, V.: Interplay between Primary and Secondary Ice Production (SIP) in Arctic Mixed-Phase Clouds (MPCs) as simulated for the M-PACE campaign in ICON, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6658, https://doi.org/10.5194/egusphere-egu23-6658, 2023.

Warm conveyor belts (WCB) are regions of large-scale coherent airflow within extratropical cyclones that rapidly ascend from the boundary layer to the upper troposphere. During their ascent, WCBs transport water vapour and cloud condensate to the upper troposphere, and thereby significantly contribute to the moisture content of the extra-tropical upper troposphere-lower stratosphere (UTLS) as well as upper tropospheric cloudiness. UTLS moisture content and cloudiness are important for the radiative budget of the Earth and future changes thereof, but are often poorly represented in numerical models and reanalysis products. A detailed quantitative understanding of the processes governing water transport in WCBs provides vital clues to the origin of these biases and for evaluating predicted future changes in WCB moisture transport. Furthermore, recent studies have found that deep and embedded convection play an important role in WCBs. This points to the necessity of high-resolution simulations, that are well validated with observational data to provide a “benchmark” for coarser-resolution global (climate) models. Here we investigate the physical processes governing WCB moisture transport in simulations of a case-study from the WISE campaign with a particular focus on (i) the impact of grid spacing (including the use of convection parameterisations) on WCB moisture transport, (ii) the microphysical processes controlling moisture loss from the WCB, and (iii) the cloud microphysical properties of the cirrus clouds in the WCB outflow.

To this end we conducted two ICON simulations of an extratropical cyclone using (i) a global (~13km resolution), convection-parameterizing and (ii) a doubly nested (~13km, ~6km and ~3km resolution) convection permitting set up. In both set-ups online trajectories are calculated that capture convective ascent and allow for a Lagrangian analysis of WCB moisture transport and WCB cloud structure.

The Lagrangian metrics show large differences in ascent timescales and the efficiency with which water is transported from the boundary-layer to the UTLS. It is shown that this impacts the UTLS moisture content in the WCB outflow region. Local changes in UTLS moisture content induced by different representations of convection are shown to project onto larger-scale structures in the moisture and cloud fields over the 1-2 days after WCB ascent.

How to cite: Schwenk, C. and Miltenberger, A.: Physical processes controlling warm conveyor belt moisture transport to the UTLS and dependence on model resolution, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6987, https://doi.org/10.5194/egusphere-egu23-6987, 2023.

EGU23-7012 | ECS | Posters on site | AS1.10

Quantification of the Radiative Effect of Arctic Cirrus by Airborne Radiation Measurements - A Case Study 

Johannes Röttenbacher, Hanno Müller, André Ehrlich, and Manfred Wendisch

Observations of cloud related processes in the Arctic are needed to evaluate the representation of clouds in weather and climate models and to improve our understanding of processes of Arctic amplification and Arcitc-midlatitude linkages. One remaining uncertainty of the Arctic climate system are cirrus clouds and their influence on the radiative budget. Arctic cirrus is known to warm the climate system on annual average, especially when present over the sea ice covered central Arctic. 
The HALO-(AC)³ airborne campaign in spring 2022 investigated changes within air masses on their way in and out of the central Arctic with the High Altitude LOng Range research aircraft (HALO), which was equipped with a suite of remote sensing instrumentation. Two flights were used to explicitly investigate the cloud radiative effect of single layer isolated cirrus between 81 and 90 degrees North.
Flight legs above and below the cirrus with measurements of spectral solar irradiance from the Spectral Modular Airborne Radiation measuremenT system (SMART) make a direct estimation of the cloud radiative effect possible. The cirrus was sufficiently thick to reduce the transmission of solar radiation by around 25%. However, significant inhomogeneities in the cirrus were observed.
We present a case study of the radiative effect of Arctic cirrus and compare airborne irradiance measurements to simulations from an offline run of the ecRad radiation scheme which is operationally used in the ECMWF's Integrated Forecasting System.

How to cite: Röttenbacher, J., Müller, H., Ehrlich, A., and Wendisch, M.: Quantification of the Radiative Effect of Arctic Cirrus by Airborne Radiation Measurements - A Case Study, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7012, https://doi.org/10.5194/egusphere-egu23-7012, 2023.

EGU23-7035 | Orals | AS1.10

Characterization of Tropical Tropopause Layer clouds combining balloon-borne and space-borne observations 

Thomas Lesigne, Francois Ravetta, Aurélien Podglajen, Dung Tran, Jérôme Bureau, Vincent Mariage, Jacques Pelon, and Alain Hauchecorne

Tropical Tropopause Layer clouds have a significant impact on the Earth's radiative budget and regulate the amount of water vapor entering the stratosphere. They are a key component of the climate system but their observation is still challenging. The Strateole-2 project aims at a  better understanding of dynamical, transport, and processes in the Tropical Tropopause Layer (TTL) using long-duration super-pressure balloons flying for several months in the lower stratosphere along the equator belt. From October 2021 to late January 2022, three microlidars flew onboard stratospheric balloons, slowly drifting just a few kilometers above the clouds. These observations have unprecedented sensitivity to thin cirrus and provide a fine scale description of cloudy structures both in time and space. Statistical comparisons with spaceborne lidar CALIOP are discussed, highlighting the unique ability of the microlidar to detect optically thin clouds. The modulation of outgoing longwave radiation by tropical clouds is also investigated using the balloon-borne observations. 

How to cite: Lesigne, T., Ravetta, F., Podglajen, A., Tran, D., Bureau, J., Mariage, V., Pelon, J., and Hauchecorne, A.: Characterization of Tropical Tropopause Layer clouds combining balloon-borne and space-borne observations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7035, https://doi.org/10.5194/egusphere-egu23-7035, 2023.

EGU23-7474 | Posters on site | AS1.10

Measurements of microphyscs in cold air Outbreks 

Tom Choularton and Gary Lloyd and the M-phase ACAO

Measurements were made in 2 sets of cold air outbreaks using the UK FAAM BAE 146  research aircraft. The first set were performed in March 2022 over the Eastern Atlantic the second set were perform in October to early November 2022 in the Western Atlantic over the Labrador Sea based in Goose Bay, Eastern Canada. In each set of experiments the focus was to study the evolution of the cloud microphysics as influenced by Cloud condensation nuclei, ice nuclei and secondary ice processes  in the stratocumulus clouds being advected southwards over progressively warmer sea until cloud break-up occurred into convective clouds. The aims were to improve the treatment of these cloud types in Global climate models and weather forecast models. These projects formed part of m-Phase funded by NERC as part of its Cloud Sense programme and ACAO a Met office program to study these clouds.A range of aerosol and cloud microphysical equipment was used in the 2 projects which will be discussed in the presentation.Analysis of the data set including a new novel Holographic instrument is still underway at the time of writing; however, some preliminary results indicate that:

  • Generally the ice crystal number concentration exceeded the ice nucleus concentrations measured at the same temperature
  • Some regions consisted entirely of super cooled water
  • A range of secondary ice particle production mechanisms were observed including ice splinter production during riming and droplet shattering on freezing after capture by ice crystals
  • Generally if the convective region was reached by the aircraft then secondary ice production was greater than in the stratocumulus region
  • Precipitation was mostly in the ice phase

How to cite: Choularton, T. and Lloyd, G. and the M-phase ACAO: Measurements of microphyscs in cold air Outbreks, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7474, https://doi.org/10.5194/egusphere-egu23-7474, 2023.

EGU23-8660 | Orals | AS1.10

A Global Merged Diurnal Ice/Snow Cloud Product from Spaceborne Passive Microwave Observations and Its Applications to Model Evaluation 

Jie Gong, Chenxi Wang, Dong Wu, Yiding Wang, Leah Ding, and Donifan Barahona

Ice cloud and floating snow play critical roles in Earth’s energy budget and hydrological cycle. Their diurnal variation is tightly coupled with convection development life cycle, hence it also greatly impacts the diurnal cycle of surface precipitation and top of the atmosphere radiation. Due to the high degree of freedom of ice crystal microphysical properties, remote sensing of ice/snow cloud is challenging for passive spaceborne sensors.

In this work, we present a global diurnal ice/snow cloud product by merging three spaceborne passive microwave sensor observations together (GPM-GMI, NPP-ATMS, and MT-SAPHIR). This dataset includes ice water path (cloud ice + falling snow), cloud top height (CTH) and cloud bottom height (CBH) at pixel level between 2015 – 2016, and monthly gridded values at 2deg X 2deg X 2 hours grid scale. The convolutional neural network (CNN) approach is adopted for the algorithm development by learning from collocated CloudSat observations, and the Monte Carlo dropout method is used for uncertainty estimation. A customized loss-function is developed to retrieve cloud mask and mass together.

We evaluated the retrieval at collocated pixels as well as against other independent field campaign and ground-based measurements. Diurnal and semi-diurnal distributions of the IWP will be presented. We will also demonstrate how we use this product to evaluate model performance on capturing the general distribution and diurnal variation of the frozen hydrometeors in the atmosphere.

How to cite: Gong, J., Wang, C., Wu, D., Wang, Y., Ding, L., and Barahona, D.: A Global Merged Diurnal Ice/Snow Cloud Product from Spaceborne Passive Microwave Observations and Its Applications to Model Evaluation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8660, https://doi.org/10.5194/egusphere-egu23-8660, 2023.

EGU23-9818 | ECS | Orals | AS1.10

A novel approach to investigate Cirrus cloud formation 

Tim Lüttmer and Peter Spichtinger

Warm conveyor belts (WCB) lead to formation of horizontally wide spread Cirrus clouds in the upper troposphere. However, the contribution of different ice formation processes and the resulting micro- and macrophysical properties of the Cirrus ,e.g., their radiative effects are still poorly understood. We want to especially address the research question of in-situ vs. liquid origin ice formation.

Common microphysics bulk schemes only consider a single ice class which includes sources from multiple formation mechanisms. We developed and implemented a two-moment microphysics scheme in the atmosphere model ICON that distinguishes between different ice modes of origin including homogeneous nucleation, deposition freezing, immersion freezing, homogeneous freezing of water droplets and secondary ice production from rime splintering, frozen droplet shattering and collisional break-up, respectively. Each ice mode is described by its own size distribution, prognostic moments and unique formation mechanism while still interacting with all other ice modes and microphysical classes like cloud droplets, rain and rimed cloud particles.

Using this novel microphysics scheme we can determine the contribution of the various ice formation mechanisms to the total ice content. For the first time this allows us to directly investigate the competition of in-situ and liquid origin Cirrus as well as homogeneous and heterogeneous ice nucleation with regards to environmental conditions and choice of microphysical parameterisations.

We performed an ensemble of simulations for selected WCB cases to cover a range of microphysical properties and compared the results of our liquid origin vs in-situ analysis with other Cirrus categorization algorithms.

How to cite: Lüttmer, T. and Spichtinger, P.: A novel approach to investigate Cirrus cloud formation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9818, https://doi.org/10.5194/egusphere-egu23-9818, 2023.

EGU23-10696 | Posters on site | AS1.10

How important are secondary ice processes – preliminary results from FOR-ICE 

Luisa Ickes, Montserrat Costa Surós, Patrick Eriksson, Hannah Frostenberg, Paraskevi Georgakaki, Maria Gonçalves Ageitos, Hanna Hallborn, Anna Lewinschal, Eleanor May, Athanasios Nenes, David Neubauer, Carlos Pérez García-Pando, Ulrike Proske, and Georgia Sotiropoulou

Global climate models poorly represent mixed-phase clouds, which leads to uncertainties in cloud radiative forcing and precipitation. In the FORCeS ice experiment (FOR-ICE) we compare three global climate models (ECHAM-HAM, NorESM, EC-Earth) and show which processes are crucial for a realistic representation of cloud ice and supercooled water in each global climate model framework using the factorial method as a statistical approach. A specific focus of the experiments is on secondary ice production (SIP) - which apart from one mechanism (rime splintering) is typically not represented in models, even if observations of ice crystal concentrations of ice crystal number in warm mixed-phase clouds often exceed available ice nuclei by orders of magnitude. We evaluate the importance of three SIP mechanisms combined (rime splintering, ice-ice collisions, and droplet shattering) compared to all other processes that can modulate ice mass and number in mixed-phase clouds: ice nucleation, sedimentation, and transport of ice crystals, and the Wegener-Bergeron-Findeisen process. To describe SIP we adopt two approaches: an explicit microphysical representation of the processes, and a parameterization based on a random forest regression of high-resolution two-year simulations in the Arctic using the polar Weather Research and Forecast model (polar-WRF). Satellite observations are used to evaluate if including descriptions of SIP leads to a more realistic representation of mixed phase clouds.

How to cite: Ickes, L., Costa Surós, M., Eriksson, P., Frostenberg, H., Georgakaki, P., Gonçalves Ageitos, M., Hallborn, H., Lewinschal, A., May, E., Nenes, A., Neubauer, D., Pérez García-Pando, C., Proske, U., and Sotiropoulou, G.: How important are secondary ice processes – preliminary results from FOR-ICE, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10696, https://doi.org/10.5194/egusphere-egu23-10696, 2023.

EGU23-11199 | Orals | AS1.10

Secondary ice production - No evidence of a productive rime-splintering mechanisms during dry and wet growth 

Susan Hartmann, Johanna Seidel, Alice Keinert, Alexei Kiselev, Thomas Leisner, and Frank Stratmann

Mixed-phase clouds are essential elements in Earth’s weather and climate system. Atmospheric observation of mixed-phase clouds occasionally demonstrated a strong discrepancy between the ice particle and ice nucleating particle number concentration of several orders of magnitude at modest supercooling [1, 4, 6]. Various secondary ice production (SIP) mechanisms have been hypothesized which can increase the ice particle number concentration by multiplication of primary ice particles [2, 3].

In this study, we focus on SIP as a result of droplet-ice collisions, commonly known as rime-splintering or Hallett-Mossop (HM) process. During riming supercooled droplets collide with an ice particle and freeze upon impact and lead to the formation of secondary ice particles. Our main objectives are to quantify the number of secondary ice particles and to learn more about the underlying physics. Therefore, we conducted laboratory experiments at IDEFIX (Ice Droplets splintEring on FreezIng eXperiment) in which small droplets collide with a fixed ice particle of 1 mm in diameter. IDEFIX is designed to simulate atmospheric relevant conditions regarding temperature, humidity, impact velocities and collision rates. The riming process was observed with high-speed video microscopy and infrared thermography to visualize the growing rimer structures and the surface temperature of the riming ice particle, respectively. Further, the secondary ice particles were counted via inertial impaction on a supercooled sugar solution in the ice counting device (cut off diameter of 2 µm) developed at IMK-AAF, KIT.

The following parameters were investigated: the air temperature was varied between -4°C and -10°C, the ice-droplet impact velocities were set either to 1 ms-1 or 3 ms-1, and the lognormal droplet size distribution was adjusted to have the mode diameter between 18 µm and 30 µm with the standard deviation between 1.6 µm and 8.4 µm. Under these conditions, the collisions rates between droplets and rimer were between 102 and 10mm-1s-1 , as determined from the video records and with a rimer heat balance model [5] using measured surface temperature as input data. Thus, the simulated riming process is typical for convective clouds; both dry and wet growth could be realized in IDEFIX. We found no efficient and reproducible secondary ice production during riming within the range of the investigated parameters. The amount of secondary ice particles produced in all our experiments was well below the values expected from the HM mechanism [3, 7], where several hundreds of secondary ice particles per mg rime were found at optimal conditions. Six potential SIP cases (out of 31) could be identified where ice was detected in the ice counting device. Four of them could be attributed to rime spicules break-off due to sublimation.

[1] Crosier, J., et al. 2011, DOI: 10.5194/acp-11-257-2011.

[2] Field, P.R., et al. 2016, DOI: 10.1175/amsmonographs-d-16-0014.1.

[3] Korolev, A. and T. Leisner 2020, DOI: 10.5194/acp-20-11767-2020.

[4] Luke, E.P., et al. 2021, DOI: 10.1073/pnas.2021387118.

[5] Pruppacher, H.R. and J.D. Klett, Microphysics of Clouds and Precipitation. 2010, Springer Dordrecht.

[6] Taylor, J.W., et al. 2016, DOI: 10.5194/acp-16-799-2016.

How to cite: Hartmann, S., Seidel, J., Keinert, A., Kiselev, A., Leisner, T., and Stratmann, F.: Secondary ice production - No evidence of a productive rime-splintering mechanisms during dry and wet growth, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11199, https://doi.org/10.5194/egusphere-egu23-11199, 2023.

EGU23-11386 | Orals | AS1.10

Large-eddy simulation of a two-layer boundary-layer cloud system from the Arctic Ocean 2018 expedition 

Annica M. L. Ekman, Ines Bulatovic, Julien Savre, Michael Tjernström, and Caroline Leck

The most common type of cloud in the Arctic latitudes is mixed-phase stratocumulus. These clouds play a critical role in the Arctic energy budget. Previous observations in the central (north of 80° N) Arctic have shown a high occurrence of prolonged periods of a shallow, single-layer mixed-phase stratocumulus at the top of the boundary layer (altitudes ~300-400m). However, recent observations from the summer of 2018 showed a prevalence of a two-layer boundary-layer cloud system. Here we use large-eddy simulation to examine the maintenance of one of the cloud systems observed in 2018 as well as the sensitivity of the cloud layers to different micro- and macro-scale parameters. We find that the model generally reproduces the observed thermodynamic structure well, with two near-neutrally stratified layers in the boundary layer caused by a low cloud (located within the first few hundred meters) capped by a lower temperature inversion, and an upper cloud layer (based around one kilometer or slightly higher) capped by the main temperature inversion of the boundary layer. The investigated cloud structure is persistent unless there are low aerosol number concentrations (<5 cm-3), which cause the upper cloud layer to dissipate, or high large-scale wind speeds (>8.5 m s-1), which erode the lower inversion and the related cloud layer. These types of changes in cloud structure led to a substantial reduction of the net longwave radiation at the surface due to a lower emissivity or higher altitude of the remaining cloud layer. The findings highlight the importance of better understanding and representing aerosol sources and sinks over the central Arctic Ocean. Furthermore, they underline the significance of meteorological parameters, such as the large-scale wind speed, for maintaining the two-layer boundary-layer cloud structure encountered in the lower atmosphere of the central Arctic.

How to cite: Ekman, A. M. L., Bulatovic, I., Savre, J., Tjernström, M., and Leck, C.: Large-eddy simulation of a two-layer boundary-layer cloud system from the Arctic Ocean 2018 expedition, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11386, https://doi.org/10.5194/egusphere-egu23-11386, 2023.

EGU23-13062 | Orals | AS1.10

A probabilistic approach to determine the thermodynamic cloud phase using passive satellites 

Johanna Mayer, Luca Bugliaro, Florian Ewald, and Christiane Voigt

The cloud thermodynamic phase (ice / mixed-phase / liquid) is a crucial parameter to understand the earth radiation budget, hydrological cycle and atmospheric thermodynamic processes. The phase partitioning of clouds and their parameterization in global climate models have therefore become of particular interest.

To improve our understanding of the frequency of occurrence and temporal evolution of cloud phase, geostationary passive sensors can be very useful due to their wide field of regard and high temporal resolution. However, the retrieval of cloud phase using passive instruments is challenging since the spectral signature of the phase is weak compared to other parameters of the clouds and atmosphere. Especially the distinction between ice and mixed-phase clouds is difficult and previous efforts to retrieve cloud phase often only distinguished between ice and liquid phase.

We present a new method to detect clouds and retrieve their phase using the passive instrument SEVIRI aboard the geostationary satellite Meteosat Second Generation. The method uses probabilities derived from active observations (the Lidar-Radar product DARDAR) of cloud top phase. Combining these probabilities for different SEVIRI channels gives probabilities for the presence of a cloud and for its cloud top phase. Our probabilistic approach includes a measure of uncertainty and allows us to distinguish between ice, mixed-phase, supercooled liquid, and warm liquid clouds. The method is tested against active satellite measurements and shows good agreement. Finally, we discuss its advantages and limitations. In the future, we plan to use our method to study the microphysical (such as optical thickness and effective radii) and macrophysical (such as temporal evolution and extent) properties of ice and mixed-phase clouds.

How to cite: Mayer, J., Bugliaro, L., Ewald, F., and Voigt, C.: A probabilistic approach to determine the thermodynamic cloud phase using passive satellites, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13062, https://doi.org/10.5194/egusphere-egu23-13062, 2023.

EGU23-14023 | ECS | Posters on site | AS1.10

Unraveling secondary ice production in winter orographic clouds through a synergy of in-situ observations, remote sensing and modeling 

Paraskevi Georgakaki, Anne-Claire Billault-Roux, Eliot Perrin, Romanos Foskinis, Georgia Sotiropoulou, Franziska Vogel, Maria Gini, Konstantinos Eleftheriadis, Ottmar Moehler, Satoshi Takahama, Alexis Berne, and Athanasios Nenes

The representation of orographic clouds in numerical weather prediction models remains a great challenge, as a consequence of our incomplete understanding of the microphysical processes acting on them and the complex interactions between the large-scale and orographic flow dynamics. Mixed-phase conditions are frequently occurring in orographic clouds, highlighting the importance of correctly simulating the microphysical evolution of ice- and liquid-phase hydrometeors. In this study we employ the mesoscale Weather Research and Forecasting (WRF) model to investigate the drivers of intense snowfall events observed during the Cloud-AerosoL InteractionS in the Helmos background TropOsphere (CALISHTO) campaign, that took place from Fall 2021 to Spring 2022 at Mount Helmos in Peloponnese, Greece. Vertical profiles of reflectivity, Doppler velocity, as well as full Doppler spectra measured by a vertically pointing W-band (94 GHz) Doppler cloud radar, in synergy with Doppler and aerosol depolarization lidar data, help gain insight into the snowfall microphysics involved and set the basis for evaluating the performance of the WRF model. A radar simulator coupled with WRF enables the direct comparison between the mesoscale simulations and remote sensing products, and allows us to find the optimal model set-up that minimizes deviations from the observations. Comparing the modeled ice crystal number concentrations (ICNCs) with the Ice Nucleating Particles (INPs) measured in-situ at the Helmos High Altitude Monitoring Station (2314 m, 42°N 05' 30'', 34°E 14' 25'') by the Portable Ice Nucleation Experiment (PINE) instrument, we seek to quantify the ice enhancement factors due to secondary ice production (SIP) or seeding ice particles and their potential role in enhancing orographic precipitation. The synergy between high-resolution modeling and radar observations gives us the opportunity to infer SIP signatures from remote sensing observations, which is an important outcome given the abundance of the latter.

How to cite: Georgakaki, P., Billault-Roux, A.-C., Perrin, E., Foskinis, R., Sotiropoulou, G., Vogel, F., Gini, M., Eleftheriadis, K., Moehler, O., Takahama, S., Berne, A., and Nenes, A.: Unraveling secondary ice production in winter orographic clouds through a synergy of in-situ observations, remote sensing and modeling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14023, https://doi.org/10.5194/egusphere-egu23-14023, 2023.

EGU23-14247 | ECS | Posters on site | AS1.10

Studying secondary ice production mechanisms: from a remote sensing and hydrometeors dynamics perspective 

Florian Le Roy De Bonneville, Yasmin Aboel Fetouh, Jan Cermak, Corinna Hoose, Emma Järvinen, Thomas Leisner, and Markus Uhlmann

Ice crystal number concentrations were often found to be orders of magnitude higher than the number concentration of ice nucleating particles; a finding that indicated the presence of secondary ice production (SIP).  Although 6 mechanisms of SIP have been both discovered and theorized, it is still not fully understood and the recent studies have been inconclusive in identifying the dominant process in real conditions.  This lack of constraint of ice multiplication adds to the uncertainty of cloud simulations in climate models. Studying SIP is challenging due to the various interfering factors involved.
In this study, we attempt to further our knowledge in understanding the SIP mechanisms using two different but complementary approaches. The first consists of using remote sensing tools such as Himawari-8 and MODIS retrievals in addition to the SOCRATES in-situ data to identify the presence of SIP and categorize the possible mechanism involved.
The second approach utilizes numerical simulations to further understand these mechanisms that are potentially responsible for SIP, but through the study of the dynamics of the different particles (ice crystals, supercooled droplets, graupel...) involved in these processes. In this approach we focus on the characteristics of the particles, such as their diameter and concentration, as well as the presence of turbulence, that are crucial in describing their movement and the feasibility of the mechanisms under study. 

How to cite: Le Roy De Bonneville, F., Aboel Fetouh, Y., Cermak, J., Hoose, C., Järvinen, E., Leisner, T., and Uhlmann, M.: Studying secondary ice production mechanisms: from a remote sensing and hydrometeors dynamics perspective, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14247, https://doi.org/10.5194/egusphere-egu23-14247, 2023.

EGU23-14329 | ECS | Posters on site | AS1.10

Investigating ice cloud formation mechanisms from satellite observations and Lagrangian transport and microphysics models 

Athulya Saiprakash, Patrick Konjari, George Horner, Christian Rolf, Martina Krämer, and Odran Sourdeval

Ice clouds are challenging because of the high complexity and diversity of their composition  (microphysics) as well as formation and growth processes. As a result, there has been little constraint from observations until recently, resulting in significant limitations in our understanding and representation of ice clouds. A major problem with satellite measurements is the lack of information on the environmental context, which is necessary to identify and understand the formation mechanism and evolution of clouds; these renditions indeed only represent a snapshot of the state of a cloud and its microphysical properties at a given time. This work tackles this issue by providing additional metrics on ice cloud history and origin along with operational satellite products.

Here, we present a novel framework that combines geostationary satellite observations with Lagrangian transport and ice microphysics models, in order to obtain information on the history and origin of air parcels that contributed to their formation. The trajectory of air parcels encountered along the DARDAR-Nice track has been traced using the air mass transport models CLAMS (Chemical LAgrangian Model of the Stratosphere). CLaMS - Ice model is jointly used to simulate cirrus clouds along trajectories derived by CLaMS. This approach provides information on the cloud regime as well as the ice formation (in-situ vs liquid origin) pathway. For tropical cirrus of convective origin, a Time Since Convection dataset from geostationary observations can also be incorporated into this approach. Preliminary results of this approach obtained on case studies representative of multiple cloud types will be shown here.

How to cite: Saiprakash, A., Konjari, P., Horner, G., Rolf, C., Krämer, M., and Sourdeval, O.: Investigating ice cloud formation mechanisms from satellite observations and Lagrangian transport and microphysics models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14329, https://doi.org/10.5194/egusphere-egu23-14329, 2023.

EGU23-15307 | Orals | AS1.10

Do detrained cirrus clouds have memory of the deep convection they came from? 

George Horner and Edward Gryspeerdt

The large cirrus outflows that arise from deep convection play a vital role in modulating the energy balance of the Earth’s atmosphere. One important question is how much do the initial conditions of the deep convection influence the subsequent evolution of the detrained cirrus, and if these initial conditions are important, over what timescales do they matter? Characterising how these cirrus outflows evolve over their entire lifetime, and how they might change in response to anthropogenic emissions is important in order to understand their role in the climate system and to constrain past and future climate change.

Building on the ‘Time Since Convection’ product used in Horner & Gryspeerdt (2023), this work investigates how the initial conditions of the deep convection influence the subsequent evolution of the detrained cirrus- in particular, how does the timing, location, and meteorological environment of the deep convection alter the detrained cirrus, and for how long are these initial conditions important for the cirrus properties- is there a ‘memory’ of the initial conditions of the deep convection imprinted on the properties of the cirrus hours or days after the initial deep convection has dissipated? To answer this question, data from the DARDAR, ISCCP, and CERES products are used to build a composite picture of the radiative and microphysical properties of the clouds, which is investigated under varying initial conditions.

The initial state of the convection is found to have a considerable impact on cirrus development under a variety of conditions. The diurnal cycle, particularly the timing of the convection, is a strong control on the cloud radiative effect, particularly in regions of strong convective activity. The initial aerosol perturbation is also shown to play a role in cirrus development, both in the large scale properties of the cirrus and the microphysical properties.

This demonstrates a potential time dependent impact of aerosol and convection on cloud properties and provides a template for future studies of cloud development incorporating diverse sets of measurements.

How to cite: Horner, G. and Gryspeerdt, E.: Do detrained cirrus clouds have memory of the deep convection they came from?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15307, https://doi.org/10.5194/egusphere-egu23-15307, 2023.

EGU23-15602 | ECS | Orals | AS1.10

Differences in microphysical properties of cirrus at high and mid latitudes from airborne measurements 

Elena De La Torre Castro, Tina Jurkat-Witschas, Armin Afchine, Valerian Hahn, Simon Kirschler, Martina Krämer, Johannes Lucke, Nicole Spelten, Heini Wernli, Martin Zöger, and Christiane Voigt

Cirrus in mid latitudes (<= 60° N) are often affected by aviation and pollution while cirrus in high latitudes (> 60° N) develop in a more pristine atmosphere. In this study, we compare the microphysical properties of cirrus measured in mid latitudes and cirrus measured in high latitudes. The analyzed properties are: the ice crystal number concentration (N), effective diameter (ED) and ice water content (IWC) of cirrus from in situ measurements during the CIRRUS-HL campaign in June and July 2021. We use a combination of cloud probes covering ice crystals sizes between 2 and 6400 µm. The differences in cirrus properties are investigated with dependence on altitude and latitude and we show that there exist differences between mid-latitude and high-latitude cirrus. An increase in ED and a reduction in N is observed in high-latitude cirrus compared to mid-latitude cirrus.

In order to investigate the cirrus properties in relation to the region of formation, we also combine our measurements with 10-day backward trajectories to identify the location of cirrus formation and the cirrus type: in situ or liquid origin cirrus. According to the latitude of cloud formation and latitude of the measurement, we classify the cirrus in three groups: cirrus formed and measured at mid latitudes (M-M), cirrus formed at mid latitudes and measured at high latitudes (M-H) and cirrus formed and measured at high latitudes (H-H). This analysis shows that part of the cirrus measured at high latitudes are actually formed at mid latitudes and therefore influenced by mid-latitude air masses. We discuss the differences of the cirrus properties under this new classification. Our study helps to advance the understanding of upper-tropospheric cirrus properties at mid and high latitudes in summer and the influence of anthropogenic perturbations.

How to cite: De La Torre Castro, E., Jurkat-Witschas, T., Afchine, A., Hahn, V., Kirschler, S., Krämer, M., Lucke, J., Spelten, N., Wernli, H., Zöger, M., and Voigt, C.: Differences in microphysical properties of cirrus at high and mid latitudes from airborne measurements, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15602, https://doi.org/10.5194/egusphere-egu23-15602, 2023.

EGU23-15765 | Posters on site | AS1.10

Sensitivity of Satellite Lidar-Radar Cirrus Retrievals to PSD Assumptions: DARDAR-Nice v2 and Simulator 

Odran Sourdeval, Irene Bartolome Garcia, Guillaume Penide, and Martina Krämer

Ice clouds constitute a challenge to satellite remote-sensing due to the variability of their microphysical properties. A central parameter to understand and represent ice clouds in modelling as well as in remote-sensing is the ice particle size distribution (PSD), whose shape largely varies depending on the environmental conditions in which the ice cloud has formed and evolved. This shape is typically assumed in satellite retrieval algorithm, for instance as a mono-modal gamma-modified distribution. Our representation of PSDs has greatly improved over the last decades, largely due to novel parameterisation methods as well as the increasing availability and accuracy of in-situ measurements that can serve as a solid basis to calibrate retrieval algorithms.

This study investigates the impact of the PSD shape assumptions on cirrus retrievals obtained from lidar-radar satellite observations (DARDAR-Nice), with a strong focus on the ice crystal number concentration. Recent in-situ measurements from the JULIA dataset were recently processed to propose new parameterisations of the PSD that offer a better representation of small ice concentrations. The added-value of considering the observed bi-modality when representing PSDs for remote sensing applications was also discussed. We here assess the consequences of including such new parameterisations in DARDAR-Nice. Comparisons between v1 and v2 (offering updated PSD assumptions) of this satellite product are also discussed.

Finally, preliminary results from a DARDAR-Nice simulator will be shown. This simulator allows to perform synthetic lidar-radar observations and retrievals on high-resolution cloud model outputs. Comparisons between the model “truth” and synthetic retrievals will be investigated and discussed in the context of underlying PSD assumptions.

How to cite: Sourdeval, O., Bartolome Garcia, I., Penide, G., and Krämer, M.: Sensitivity of Satellite Lidar-Radar Cirrus Retrievals to PSD Assumptions: DARDAR-Nice v2 and Simulator, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15765, https://doi.org/10.5194/egusphere-egu23-15765, 2023.

EGU23-15890 | ECS | Posters on site | AS1.10

Organization of SIP mechanisms among basic cloud types 

Akash Deshmukh, Vaughan Phillips, Deepak Waman, Sachin Patade, Aaron Bansemer, and Ashok Gupta

 Clouds are a fundamental aspect of the Earth’s atmosphere. One of the major challenges in cloud-resolving models (CRM) is the formation and generation of new cloud ice particles from pre-existed ice and liquid. Based on the basic broad cloud types, it is helpful to distinguish between their fundamental microphysical properties. The four basic cloud types are defined as: (1) warm-based convective and stratiform clouds; and (2) cold-based convective and stratiform clouds. Recent studies of ice initiation in clouds have shown that most ice particles in the mixed-phase region of clouds are from secondary ice production (SIP) mechanisms but have generally concentrated on only one specific cloud system.

In this study, Aerosol-Cloud model (AC) is used. AC includes the four mechanisms of secondary ice production as follows: ice-ice collisional breakup, raindrop freezing fragmentation, Hallett-Mossop (HM) process and sublimational breakup. The intent is to generalize the contribution of each SIP mechanism among basic cloud types. The numerical simulations are performed using our AC for each cloud type and validated against in-situ cloud observations. The observational data is collected during four different cloud observational campaigns, each representing a contrasting cloud type than others.

Here, we study the contributions from each process of SIP (HM process, ice-ice collisional breakup, raindrop-freezing fragmentation and sublimational breakup) by performing control simulations of each basic cloud type. For the warm cloud convective clouds, the HM process prevails near freezing level and contributes significantly from 0 to -15oC. In cold-based convective clouds, the ice-ice collisional breakup is the most dominating SIP mechanism in each cloud type. In warm-based stratiform clouds, the HM process dominates the contribution of ice in the -5 to -15oC temperature range for updrafts up to 8 m/s. In the slightly warm-based convective clouds, the breakup due to ice-ice collision is the most dominating mechanism for the convective updrafts between -5oC and cloud top temperatures. 

How to cite: Deshmukh, A., Phillips, V., Waman, D., Patade, S., Bansemer, A., and Gupta, A.: Organization of SIP mechanisms among basic cloud types, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15890, https://doi.org/10.5194/egusphere-egu23-15890, 2023.

A new CALIPSO satellite retrieval for cirrus clouds has been developed over the last 1.5 years that retrieves ice particle number concentration, effective diameter, and ice water content.  It compares favorably with in situ measurements from many field campaigns around the world.  This talk would briefly describe the new method targeting single-layer cirrus clouds and focus on new findings resulting from this retrieval, relating them to climate model predictions.  These results indicate that there are two types or categories of cirrus clouds.  Type 1 cirrus appear to form through heterogeneous ice nucleation (het), have visible optical depths < 0.3, and are most abundant; they are what most people visualize as a “cirrus cloud”.  Type 2 cirrus may form through a combination of het and homogeneous ice nucleation, have visible optical depths > 0.3 (with visible extinction coefficients typically 4 times greater than type 1 cirrus), and are often associated with warm fronts, orographic gravity waves, and other lifting processes.  However, type 2 cirrus clouds constitute 76% to 88% (depending on latitude) of the estimated net cloud radiative effect of all cirrus clouds.  Based on comparisons between retrieved and predicted ice particle number concentrations and effective diameters, these type 2 cirrus clouds are poorly represented in climate models, possibly partly due to the predicted dependence of ice nucleation on layer-average pre-existing ice (not realistic near cloud top where ice nucleation occurs).  Predicted ice nuclei concentrations may also need revising. 

How to cite: Mitchell, D. and Garnier, A.: Characterizing two types of cirrus clouds that differ in nucleation mechanism and radiative effect, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16885, https://doi.org/10.5194/egusphere-egu23-16885, 2023.

EGU23-643 | ECS | Orals | AS1.11

Cloud cover estimation using different methods exploiting solar radiation measurements at various sites in Antarctica 

Claudia Frangipani, Raul Cordero, Adriana M. Gulisano, Angelo Lupi, Hector A. Ochoa, Penny Rowe, and Vito Vitale

Observations at the surface in Antarctica have always been challenging, but cloud observations are particularly scarce due to different factors, among which the polar night and lack of instruments and observers. One way to obtain information on cloud cover, and fill the gap, is through broadband radiation measurements thanks to methods based on the effect that clouds have on solar and terrestrial radiation. In this work three different algorithms have been studied and implemented: i) Long et al.[1] method, which exploits global and diffuse shortwave radiation components; ii) Kasten and Czeplak[2], based on global shortwave component alone; iii) APCADA[3] algorithm, which requires longwave downward radiation measurements and meteorological variables data, and is specially chosen as it yields results also at (polar) night. Different methods were selected to adapt to the data available at each site and to cross-check the results. The algorithms are tested on common-time data sets from three different stations: Marambio (64°14’50’’S - 56°37’39’’W), where upward and downward components for shortwave and longwave radiation are measured along with diffuse shortwave radiation; Professor Julio Escudero (62°12’57’’S - 58°57’35’’W) where downward shortwave and longwave radiation data are available; and Concordia (75°05’59’’S - 123°19’57’’E) where data on all components of both solar and terrestrial radiation are collected. Before any computation, data quality control is executed following tests[4] recommended by the Baseline Surface Radiation Network[5], showing good quality for all three data sets. Sky conditions depend on the location of the stations: Marambio and Escudero are coastal sites located on islands on opposite sides of the Antarctic Peninsula where cloudy skies are expected to occur, while Concordia is situated on the East Antarctic Plateau where the sky should be clearer. Such expectations are confirmed by the preliminary results obtained from the tested algorithms, indicating that clouds occur very often with almost scarce clear sky periods at the coastal stations. 

 

Bibliography
[1] Long C. N., Ackerman T. P., Gaustad K. L., and Cole J. N. S. (2006): “Estimation of fractional sky cover from broadband shortwave radiometer measurements”, J. Geophys. Res. 111, doi: 10.1029/2005JD006475
[2] Dürr B. and Philipona R. (2004): “Automatic cloud amount detection by surface longwave downward radiation measurements”, J. Geophys. Res. 109, doi: 10.1029/2003JD004182
[3] Kasten F., Czeplak G. (1980): “Solar and terrestrial radiation dependent on the amount and type of cloud”, Solar Energy 24, doi: 10.1016/0038-092X(80)90391-6
[4] Long and Shi (2008): “An automated quality assessment and control algorithm for surface radiation measurements”, Open Atm. Science J. 2, doi: 10.2174/1874282300802010023
[5] https://bsrn.awi.de/

How to cite: Frangipani, C., Cordero, R., Gulisano, A. M., Lupi, A., Ochoa, H. A., Rowe, P., and Vitale, V.: Cloud cover estimation using different methods exploiting solar radiation measurements at various sites in Antarctica, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-643, https://doi.org/10.5194/egusphere-egu23-643, 2023.

EGU23-667 | ECS | Orals | AS1.11 | Highlight

Cloud and precipitation profiles from observations  and Polar-WRF simulations over Vernadsky station (western Antarctic Peninsula) during austral winter 2022 

Anastasiia Chyhareva, Svitlana Krakovska, Irina Gorodetskaya, and Lyudmyla Palamarchuk

Intense moist intrusions originating from the lower latitudes of the Pacific Ocean have been found to have a significant impact on the Antarctic Peninsula (AP), including enhancement of surface melt events, increased runoff, reduction in sea-ice cover and ice shelves destabilization. Clouds play an important role in the surface energy budget during these events and in precipitation formation. Precipitation phase and amounts determine local and regional surface mass and energy budget. Our  research focuses on cloud and precipitation microphysical and dynamic characteristics over the AP region, using  ground based remote sensing at the Ukrainian Antarctic Station Akademic Vernadsky Moreover, an enhanced radiosonde program was launched during the austral winter at the Vernadsky station as part of the Year of Polar Prediction in the Southern Hemisphere (YOPP-SH) international initiative (May-August 2022). Here we present detailed analysis of one of the Targeted Observing Periods (TOPs) during an intense moisture and heat intrusion affecting the AP.

Although there is a lot of research on the atmospheric processes over the AP region, the local dynamic and microphysical characteristics of clouds and precipitation are still poorly understood and misrepresented in the models due to the lack of direct measurements, particularly in winter.

Further we performed  Polar-WRF model simulations, forced by ERA5 reanalysis and configured with Morrison double moment cloud microphysical scheme. The simulations were run at 1-km spatial resolution with 10-minute temporal output centered over the Vernadsky region. Simulation results were verified with precipitation properties derived from Micro Rain Radar-Pro measurements and radiosonde profiles. We found that there is  more snow in PolarWRF outputs in comparison to MRR-Pro measurements. Thus it does not represent mixed phased precipitation properly. At the same time Polar WRF shows warm temperature bias compared to radiosounding. 

Measurements and model output are used to analyze cloud ice and water particle distribution, thickness and precipitation particle spectra over the Vernadsky station and the AP mountains during the extreme precipitation events in the Antarctic Winter. In overall there were five TOPs over the AP region. However, not all of them were associated with extreme precipitation on Vernadsky station.

Our preliminary results show the importance of the transition between dry and wet snowfall during intense moisture transport events at the AP (particularly remarkable during winter at the location of Vernadsky station). Polar-WRF shows differences in simulating the timing and intensity of such transitions probably related to the biases in temperature profiles influencing the melting layer height.

How to cite: Chyhareva, A., Krakovska, S., Gorodetskaya, I., and Palamarchuk, L.: Cloud and precipitation profiles from observations  and Polar-WRF simulations over Vernadsky station (western Antarctic Peninsula) during austral winter 2022, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-667, https://doi.org/10.5194/egusphere-egu23-667, 2023.

EGU23-901 | ECS | Orals | AS1.11 | Highlight

Warm Temperature Anomalies Associated with Snowfall in Antarctica 

Aymeric Servettaz, Cécile Agosta, Christoph Kittel, and Anaïs Orsi

Antarctica, the coldest and driest continent, is home to the largest ice sheet. A common feature of polar regions is the warming associated with snowfall, as moist oceanic air and cloud cover contribute to increase the surface temperature. Consequently, the ice accumulated onto the ice sheet is deposited under unusually warm conditions. Here we use the polar-oriented atmospheric model MAR to study the statistical difference between average and snowfall-weighted temperatures. Most of Antarctica experiences a warming scaling with snowfall, although with strongest warming at sites with usually low accumulation. Heavier snowfalls in winter contribute to cool the snowfall-weighted temperature, but this effect is overwritten by the warming associated with atmospheric perturbations responsible for snowfall, which particularly contrast with the extremely cold conditions in winter. Disturbance in apparent annual temperature cycle and interannual variability may have major implications for water isotopes, which are deposited with snowfall and commonly used for paleo-temperature reconstructions.

How to cite: Servettaz, A., Agosta, C., Kittel, C., and Orsi, A.: Warm Temperature Anomalies Associated with Snowfall in Antarctica, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-901, https://doi.org/10.5194/egusphere-egu23-901, 2023.

On the East Antarctic Plateau, in winter, rapid warming events originated by the advection of warm, moist air from lower latitudes, cause the disruption of the stable thermal structure of the atmosphere, and can be linked to the warming of the Plateau region itself. Continuous monitoring of these events can shed light on temperature trends in East Antarctica, trends which are still not clearly defined in terms of origin and amount.

Since the main mechanism acting in the warming events is the strong increase in cloud cover linked to the higher water content of the advected air, for a systematic monitoring of warming phenomena a simultaneous detection of water vapor vertical profile and cloud properties is needed. These two tasks can be both performed through the analysis of spectrally resolved atmospheric downwelling emitted radiances.

The REFIR (Radiation Explorer in the Far Infrared) Fourier transform spectroradiometer was installed at Concordia station, in the Dome C region of the Antarctic Plateau, in December 2011, and it has been performing continuous measurement since then. REFIR measures the downwelling atmospheric radiance in the 100-1500 cm-1 (6.7-100 µm) spectral interval, with a resolution of 0.4 cm-1, and with a repetition rate of about 10 minutes. The measured spectral interval extends from the far infrared, which includes the water vapor rotational band, to the atmospheric window region (8-14 µm), which provides information about the radiative effects of clouds.

A dedicated inversion code was developed to retrieve vertical profiles of water vapor and temperature from the measured emission spectra. The retrieved profiles allow for the monitoring of the evolution of the vertical structure of the troposphere on a 10 minutes timescale, whereas the spectral radiance itself provides, in a more direct way, information on the cloud cover. Therefore, the dataset produced by the REFIR instrument allow us to detect and obtain statistics about warming events in the Dome C region.

How to cite: Bianchini, G., Belotti, C., Di Natale, G., and Palchetti, L.: Exploiting a decadal time-series of spectrally resolved downwelling infrared radiances at Dome C, Antarctica to assess the occurrence of advective warming events, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1528, https://doi.org/10.5194/egusphere-egu23-1528, 2023.

EGU23-5075 | Orals | AS1.11

Measuring snowfall properties with the open-source Video In Situ Snowfall Sensor 

Maximilian Maahn, Nina Maherndl, and Isabelle Steinke

We do not know the exact pathways through which ice, liquid, cloud dynamics, and aerosols are interacting in clouds while forming snowfall but the involved processes can be identified by their fingerprints on snow particles. The general shape of individual crystals (dendritic, columns, plates) depends on the temperature and moisture conditions during growth from water vapor deposition. Aggregation can be identified when multiple individual particles are combined into a snowflake. Riming describes the freezing of cloud droplets onto the snow particle and can eventually form graupel. In order to exploit these unique fingerprints of cloud microphysical processes, optical in situ observations are required.

The Video In Situ Snowfall Sensor (VISSS) was specifically developed for a campaign in the high Arctic (MOSAiC) to determine particle shape and particle size distributions. Different to other sensors, the VISSS minimizes uncertainties by using two-dimensional high-resolution images, a large measurement volume, and a design limiting the impact of wind. Tracking of particles over multiple frames allows determining fall speed and particle tumbling. The instrument design and software will be released as open-source. Here, we present the design of the instrument, show how particles are detected and tracked and introduce first results from campaigns in the high Arctic (MOSAiC), in the Colorado Rocky Mountains (SAIL), and in and Hyytiälä (Finland).  

How to cite: Maahn, M., Maherndl, N., and Steinke, I.: Measuring snowfall properties with the open-source Video In Situ Snowfall Sensor, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5075, https://doi.org/10.5194/egusphere-egu23-5075, 2023.

EGU23-5650 | ECS | Orals | AS1.11

Mixed-phase Multilayer Clouds in the Arctic: A Simulation Study using ICON 

Gabriella Wallentin, Corinna Hoose, Peggy Achtert, and Matthias Tesche

Multilayer clouds (MLCs), defined as individual, vertically overlapping clouds, are frequently occurring worldwide but have been far less studied than single layered clouds. Earlier studies have suggested a clear abundance of MLCs in the Arctic compared with the rest of the world and with data from the MOSAiC campaign in 2019-2020 we have classified multilayered clouds at a 52% frequency of occurrence. The microphysical interaction between these cloud layers is expected to be complicated, such as the seeder- feeder mechanism, and we thus employ a model to further investigate these clouds. 

Cases from the MOCCHA campaign in 2018 as well as the MOSAiC campaign in 2019-2020 have been selected for MLC occurrences. These cloud systems vary from vertically distinct layers with no potential of seeding (subsaturated layer of >3km) to a doubly layered system within the boundary layer with frequent seeding events. The structure of the former can be simulated at a coarse grid spacing, provided appropriate initial conditions and aerosol concentration, whilst the latter is highly dependent on initial and boundary conditions, resolution, and parameterisation for the boundary layer. 

Together with an analysis of the measurements on board of the ships, the ICON (ICOsahedral Non-hydrostatic) model was deployed. The simulations are run with refined nests down to 75 meters horizontal grid spacing in ICON-LEM. Initial and boundary data are supplied by both ICON Global and IFS. As the Arctic aerosol contribution is yet to be parameterised, we are further making use of the prognostic aerosol module ART (Aerosol and Reactive Trace gases) developed by KIT, set up specifically for cloud condensation nuclei activation for sea salt and sulfate. 

Various sensitivity experiments have been performed on these case studies including (i) sensitivity to microphysical parameters, such as CCN and INP parameterisation and concentration, (ii) sensitivity to horizontal and vertical resolution as well as (iii) initial and boundary condition impacts on resolving the cloud layers. Furthermore, the aerosol concentration has been scaled, in the existing parameterisations in ICON, to represent the measurements on site as well as prognostically run using ICON-ART. 

Preliminary results on the modelled multilayer cloud system highlight a high dependency on the initial and boundary data quality as well as domain resolution while the microphysics have a smaller impact on the formation and detailed structure of the multilayer cloud system.

How to cite: Wallentin, G., Hoose, C., Achtert, P., and Tesche, M.: Mixed-phase Multilayer Clouds in the Arctic: A Simulation Study using ICON, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5650, https://doi.org/10.5194/egusphere-egu23-5650, 2023.

EGU23-5802 | ECS | Orals | AS1.11

Transforming cloudy air masses and surface impacts: a case study confronting MOSAiC observations, reanalyses and coupled model simulations 

Sandro Dahlke, Amélie Solbès, Matthew D. Shupe, Christopher J. Cox, Marion Maturilli, Annette Rinke, Wolfgang Dorn, and Markus D. Rex

Variability in the components of the Arctic surface energy budget and the atmospheric boundary layer (ABL) structure are to a large extent controlled by synoptic-scale changes and associated air mass properties. The transition of air masses between the radiatively clear and cloudy states, along with their characteristic surface impacts in radiation and ABL structure, can occur in either direction and on short time scales. In both states as well as during the transition, insufficient model representation of radiative processes and cloud microphysical properties cause biases in numerical weather prediction- and climate models. We employ observations from radiosondes, MET tower, and the ShupeTurner cloud microphysics product, which itself synthesizes a wealth of instruments, for the classification of an event of transition between low-level mixed phase cloud and clear conditions. The observed air mass properties and transition process are compared to ERA5 reanalysis data and output from a simulation of the coupled regional climate model HIRHAM-NAOSIM which applied non-spectral nudging to ERA5 in order to reproduce the observed synoptic-scale changes. The approach highlights the potential of event-based analysis of transformations of cloudy Arctic air masses by confronting models with observations.

 

How to cite: Dahlke, S., Solbès, A., Shupe, M. D., Cox, C. J., Maturilli, M., Rinke, A., Dorn, W., and Rex, M. D.: Transforming cloudy air masses and surface impacts: a case study confronting MOSAiC observations, reanalyses and coupled model simulations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5802, https://doi.org/10.5194/egusphere-egu23-5802, 2023.

EGU23-5876 | ECS | Orals | AS1.11

Airborne measurements of the cloud impact on the surface radiative energy budget in the Fram Strait 

Sebastian Becker, André Ehrlich, Michael Schäfer, and Manfred Wendisch

Clouds play an important role in the climate system of the Arctic. The interaction of clouds with atmospheric radiation has a significant influence on the radiative energy budget (REB) of the Arctic surface, which is quantified by the surface cloud radiative effect (CRE). Due to the counteraction of the cooling effect of clouds in the solar and their warming effect in the thermal-infrared spectral range, the total CRE depends on a complex interplay of the illumination, surface, thermodynamic, and cloud conditions.

To characterize the CRE for a variety of environmental conditions, broadband radiation measurements were performed during three seasonally distinct airborne campaigns. The flights were conducted over sea ice and open ocean surfaces in the eastern Fram Strait. The analysis focusses on the differences of the CRE with respect to the different campaigns and surface types. It was found that clouds cool the open ocean surface during all campaigns. In contrast, clouds mostly have a warming effect on sea ice–covered surfaces, which neutralizes during mid-summer. Given the seasonal cycle of the sea ice distribution, these results imply a cooling effect of clouds on the surface during the sea ice minimum in late summer and a warming effect during the sea ice maximum in spring in the Fram Strait region. The variability of, e. g., cloud and synoptic conditions causes deviations of the CRE from these statistics. In particular, the study presents the evolution of the CRE during selected cases of warm air intrusions and marine cold air outbreaks.

How to cite: Becker, S., Ehrlich, A., Schäfer, M., and Wendisch, M.: Airborne measurements of the cloud impact on the surface radiative energy budget in the Fram Strait, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5876, https://doi.org/10.5194/egusphere-egu23-5876, 2023.

EGU23-6007 | ECS | Orals | AS1.11

Impact of Atmospheric Rivers on Poleward Moisture Transport and Arctic Climate on Interannual Timescales 

Marlen Kolbe, Jeroen Sonnemans, Richard Bintanja, Eveline van der Linden, Karin van der Wiel, Kirien Whan, and Imme Benedict

The projected increase in poleward moisture transport (PMT) towards warmer climate has mainly been linked to the larger moisture holding capacity of warmer air masses. However, the future of interannual fluctuations of PMT and associated driving mechanisms are fairly uncertain. This study demonstrates the extent to which atmospheric rivers (ARs) explain the interannual variability of PMT, as well as related variables such as temperature, precipitation and sea ice. Such linkages help to clarify if extreme precipitation or melt events over Arctic regions are dominantly caused by the occurrence of ARs. A main focus is set on the impact of ARs on Arctic sea ice on interannual timescales, which so far has been poorly studied, and varies from colder to warmer climates.

To robustly study these interannual linkages of ARs and Arctic Climate, we examine Arctic ARs in long climate runs of one present and two future climates (+2°C and +3°C), simulated by the global climate model EC-Earth 2.3. To enhance the significance of the results, three different moisture thresholds were used to detect ARs. Further, the use of additional thresholds relative to the 2°C and 3° warmer climates allowed a distinction between thermodynamic and dynamic processes that lead to changes of ARs from colder to warmer climates. It is found that most PMT variability is driven by ARs, and that the share of ARs which explain moisture transport increases towards warmer climates. We also discuss the role of the position and strength of the jet stream in driving AR variability and highlight the importance of ARs in generating interannual fluctuations of Arctic climate variables such as temperature and precipitation.

How to cite: Kolbe, M., Sonnemans, J., Bintanja, R., van der Linden, E., van der Wiel, K., Whan, K., and Benedict, I.: Impact of Atmospheric Rivers on Poleward Moisture Transport and Arctic Climate on Interannual Timescales, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6007, https://doi.org/10.5194/egusphere-egu23-6007, 2023.

EGU23-7246 | Orals | AS1.11 | Highlight

HALO-(AC)3: Airborne Observations of Arctic Clouds in Airmass Transformations 

André Ehrlich, Manfred Wendisch, Marcus Klingebiel, Mario Mech, Susanne Crewell, Andreas Herber, and Christof Lüpkes and the HALO-(AC)3 team

Clear indications of the phenomenon of Arctic Amplification include the above-average increase of the near-surface air temperature and the related dramatic retreat of sea ice observed in the last decades. The mechanisms behind these features are widely discussed. Especially the role of clouds and of air mass transports into and out of the Arctic associated with related transformation processes are still poorly understood. Therefore, the HALO-(AC)3 campaign was performed to provide observations of meridional air mass transports and corresponding transformations in a quasi-Lagrangian approach. Three research aircraft equipped with state-of-the-art instrumentation performed measurements over the Arctic ocean and sea ice in March/April 2022. The German High Altitude and Long Range Research Aircraft (HALO), equipped with a comprehensive suite of active and passive remote sensing instruments and dropsondes, was operated from Kiruna, Sweden. The flight pattern covered long distances at high altitudes up to the North Pole probing air masses multiple times on their way into and out of the Arctic. The Polar 5 (remote sensing) and Polar 6 (in-situ) aircraft from the Alfred Wegener Institute operated in the lower troposphere out of Longyearbyen in the lower troposphere over Fram Strait West of Svalbard. Several coordinated flights between the three aircraft were conducted with Polar 6 sampling in-situ aerosol, cloud, and precipitation particles within the boundary layer, Polar 5 observing clouds and precipitation from above roughly at 3 km altitude, and HALO providing the large scale view on the scene following air masses.
The observations cover a major warm air intrusion event with atmospheric river embedded bringing warm and moist air far into the Arctic. Multiple cold air outbreaks were characterized in their initial stage close to the sea ice edge with Polar 5 and 6 and in a quasi-Lagrangian perspective with HALO, which allowed to quantify the air mass transformation by changes of thermodynamic profiles, large scale subsidence, and cloud properties over a period of 24 hours. Single events of high latitude Arctic cirrus and the formation of a polar low are included in the data set. The presentation reports on first results of the campaign by illustrating the capabilities of the multi-aircraft operation.

How to cite: Ehrlich, A., Wendisch, M., Klingebiel, M., Mech, M., Crewell, S., Herber, A., and Lüpkes, C. and the HALO-(AC)3 team: HALO-(AC)3: Airborne Observations of Arctic Clouds in Airmass Transformations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7246, https://doi.org/10.5194/egusphere-egu23-7246, 2023.

EGU23-7692 | ECS | Orals | AS1.11

The effect of cloud top cooling on the evolution of the Arctic boundary layer observed by balloon-borne measurements 

Michael Lonardi, Christian Pilz, Elisa F. Akansu, André Ehrlich, Matthew D. Shupe, Holger Siebert, Birgit Wehner, and Manfred Wendisch

The presence of clouds significantly affects Arctic boundary layer dynamics. However, the accessibility of clouds over the Arctic sea ice for in-situ observations is challenging. Measurements from tethered balloon platforms are one option to provide high-resolution data needed for model evaluation.

The tethered balloon system BELUGA (Balloon-bornE moduLar Utility for profilinG the lower Atmosphere) was deployed to profile the boundary layer at the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC), and in Ny-Alesund. A set of scientific payloads for the observation of broadband radiation, turbulence, aerosol particles, and cloud microphysics properties were operated to study the interactions in the cloudy and cloud-free boundary layer.

Measurements obtained under various cloud conditions, including single-layer and multi-layer clouds, are analyzed. Heating rates profiles are calculated to validate radiative transfer simulations and to study the temporal development of the cloud layers. 

The in-situ observations display the importance of radiation-induced cloud top cooling in maintaining stratocumulus clouds over the Arctic sea ice. Case studies also indicate how the subsequent turbulent mixing can lead to the entrainment of aerosol particles into the cloud layer.

How to cite: Lonardi, M., Pilz, C., Akansu, E. F., Ehrlich, A., Shupe, M. D., Siebert, H., Wehner, B., and Wendisch, M.: The effect of cloud top cooling on the evolution of the Arctic boundary layer observed by balloon-borne measurements, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7692, https://doi.org/10.5194/egusphere-egu23-7692, 2023.

EGU23-8107 | ECS | Orals | AS1.11 | Highlight

The extraordinary March 2022 East Antarctica heatwave 

Jonathan Wille and the East Antarctica heatwave project

Between March 15-19th 2022, East Antarctica experienced an unprecedented heatwave with widespread 30-45° C temperature anomalies across the ice sheet. This record-shattering event saw numerous monthly temperature records being broken including a new all-time temperature record of -9.4 °C on March 18th at Concordia station despite March typically being a transition month to the Antarctic coreless winter. The driver for these temperature extremes was an unprecedently intense atmospheric river (AR) advecting heat and moisture deep into the Antarctic interior. The scope of the temperature records spurred a large, diverse collaborative effort to study the heatwave’s meteorological drivers, impacts, and historical climate context using an array of observations, models, and analysis techniques. 

 From these efforts, we present the following

  • Temperature observations and records
  • Meteorological drivers including tropically forced Rossby wave activity along with AR and warm conveyor belt dynamics
  • Radiative forcing impacts on surface temperatures and inversions
  • Surface mass balance impacts
  • Discussion of the AR impacts on isotope and cosmic ray measurements from Concordia station
  • AR influence on the Conger Ice Shelf disintegration
  • Event return time analysis
  • Implications on past climate reconstructions
  • Future event likelihood from IPSL-CM6 simulations

How to cite: Wille, J. and the East Antarctica heatwave project: The extraordinary March 2022 East Antarctica heatwave, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8107, https://doi.org/10.5194/egusphere-egu23-8107, 2023.

EGU23-8500 | ECS | Orals | AS1.11

The effects of warm air intrusions in the high arctic on cirrus clouds 

Georgios Dekoutsidis, Silke Groß, and Martin Wirth

In the last decades scientist have noticed that the average global temperature of the Earth has been increasing. Moreover, the arctic is warming significantly faster than the global average, a phenomenon labeled Arctic Amplification. Two atmospheric components contributing to the warming of the atmosphere in the arctic are water vapor and cirrus clouds. Both have an effect on the radiation budget of the atmosphere and more specifically the longwave radiation. A Warm Air Intrusion (WAI) event is defined as the meridional transport of warm, water-vapor-rich airmasses into the arctic. During such events large amounts of water vapor can be transported into the arctic, which also leads to high supersaturations aiding the formation and longevity of cirrus clouds. There is a strong hypothesis that WAI events in the high arctic are becoming more frequent, so it is important to study the effects these events have on the macrophysical and optical properties of cirrus clouds in the arctic.

The HALO-(AC)3 flight campaign was conducted in March/April 2022 with the central goal of studying WAI events in the arctic regions of the Northern Hemisphere. For this campaign the German research aircraft HALO was equipped with remote sensing instrumentation, including the airborne LIDAR system WALES which we use in this study. WALES is a combined water vapor differential absorption and high spectral resolution lidar. It provides water vapor measurements in a 2D field along the flight track. We combine these measurements with ECMWF temperature data and calculate the Relative Humidity with respect to ice (RHi) inside and in the vicinity of cirrus clouds. For each flight we studied the synoptic situation and created two groups: One containing flights were cirrus that formed in arctic airmasses were measured and another were cirrus were measured during WAI events, henceforth arctic cirrus and WAI cirrus respectively. Our main goal is to compare the humidity characteristics inside and in the vicinity of arctic cirrus clouds and WAI cirrus clouds.

For the arctic cirrus we find that 49 % of the in-cloud data points are supersaturated with RHi mostly below the lower threshold for heterogeneous nucleation (low HET). The cloud-free air around these clouds has a supersaturation percentage of 8.5 %. The WAI cirrus are measured in a wider temperature range and also have a significantly higher supersaturation percentage inside as well as in the cloud-free air, 61.7 % and 9.3 % respectively. The majority is again in the low HET regime. Additionally, WAI cirrus are on average geometrically thicker than arctic cirrus. Finally, regarding the vertical distribution of RHi within these clouds we find that WAI cirrus have their highest supersaturations near the cloud top and become gradually subsaturated towards cloud-bottom. On the other hand, arctic cirrus have their highest supersaturations near cloud-middle, with lower supersaturations at cloud-top and subsaturated cloud-bottom.

How to cite: Dekoutsidis, G., Groß, S., and Wirth, M.: The effects of warm air intrusions in the high arctic on cirrus clouds, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8500, https://doi.org/10.5194/egusphere-egu23-8500, 2023.

EGU23-9110 | Posters on site | AS1.11

Multi-year precipitation characteristics based on in-situ and remote sensing observations at the Arctic research site Ny-Ålesund, Svalbard 

Kerstin Ebell, Christian Buhren, Rosa Gierens, Melanie Lauer, Giovanni Chellini, Sandro Dahlke, and Pavel Krobot

Precipitation is a key variable in the hydrological cycle. However, observations of precipitation are quite challenging and even more so in remote locations such as the Arctic. The Arctic is experiencing a rapidly changing climate with a strong increase in near-surface air temperature, known as Arctic Amplification. In particular, the Svalbard archipelago is located in the warmest region of the Arctic and reveals the highest temperature increase (Dahlke and Maturilli, 2017). Such changes also affect the hydrological cycle. For example, climate models reveal a strong increase in precipitation in the Arctic (McCrystall et al., 2021) with rain becoming the most dominant precipitation type (Bitanja and Andry, 2017). Continuous detailed observations, which can also be set in context to satellite products and reanalyses data, are necessary to better understand precipitation and precipitation related processes in the Arctic.

In this study, we make use of the complementary precipitation observations performed as part of the Transregional Collaborative Research Centre on Arctic Amplification TR172 (http://www.ac3-tr.de; Wendisch et al., 2017) at the Arctic research station AWIPEV at Ny-Ålesund, Svalbard, to analyze precipitation characteristics in detail. The observations include an OTT Pluvio2 weighing gauge, an OTT Parsivel2 distrometer and a METEK MRR-2 micro rain radar (MRR). While the Pluvio and the Parsivel provide information on surface precipitation amount and type, the MRR provides information on the vertical structure of precipitation up to a height of 1 km. Measurements are available since spring/summer 2017 allowing for an analysis of more than 4 years of data.

First results show that the yearly precipitation amount based on Pluvio ranges from 306 mm to 552 mm (values are uncorrected for undercatch). Using the one-minute resolved data of Parsivel, precipitation frequency is highly variable within the different months ranging from 0.4 % to 18.8 % with solid precipitation being the most dominant type typically from September to March and liquid precipitation in the months May to August. In addition to monthly and yearly statistics, we will also characterize and analyze in detail the individual precipitation events. One question to be addressed is how much of the precipitation is related to atmospheric rivers (ARs). ARs are long, narrow, and transient corridors of strong horizontal water vapor transport which account for 80-90 % of the poleward moisture transport. Although their occurrence in the Arctic is limited, they are a significant source of rain and snow in the Arctic. Understanding linkages between precipitation and weather events and using observational data to evaluate models and reanalysis in the current climate will aid developing more accurate future predictions.

How to cite: Ebell, K., Buhren, C., Gierens, R., Lauer, M., Chellini, G., Dahlke, S., and Krobot, P.: Multi-year precipitation characteristics based on in-situ and remote sensing observations at the Arctic research site Ny-Ålesund, Svalbard, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9110, https://doi.org/10.5194/egusphere-egu23-9110, 2023.

EGU23-9323 | Posters on site | AS1.11

Observations of ice optical and microphysical properties in Arctic low-level mixed-phase clouds during ACLOUD 

Emma Järvinen, Franziska Nehlert, Guanglang Xu, Fritz Waitz, Guillaume Mioche, Regis Dupuy, Olivier Jourdan, and Martin Schnaiter

Observations of late spring and summer time stratiform clouds over pack ice, marginal sea ice zone and open water during the ACLOUD campaign have shown that relatively high ice particle number concentrations up to 35 L-1 are observed in cases where cloud top temperatures are between -3.8 and -8.7°C. This elevation in ice crystal number can likely be linked with secondary ice production. Simultaneous measurements of ice optical properties showed that a relative low asymmetry parameter between 0.69 and 0.76 can be associated with the mixed-phase cloud ice crystals. The condensed water path is dominated by the liquid phase at the cloud top in most of the studied cases except in one case study of a system with embedded convection where ice extinction exceeded the liquid extinction. Radiative transfer simulations have shown that the ice phase in low-level mixed-phase clouds, otherwise dominated by liquid phase, can also be radiatively important in cases where ice phase contributes to the cloud top extinction. This highlights the importance of an accurate vertical information of ice extinction within Arctic low-level clouds. The results of this study provide an important basis for testing and improving cloud microphysical parameterizations in models in order to accurately predict Arctic warming.

How to cite: Järvinen, E., Nehlert, F., Xu, G., Waitz, F., Mioche, G., Dupuy, R., Jourdan, O., and Schnaiter, M.: Observations of ice optical and microphysical properties in Arctic low-level mixed-phase clouds during ACLOUD, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9323, https://doi.org/10.5194/egusphere-egu23-9323, 2023.

EGU23-9784 | ECS | Posters on site | AS1.11

Airborne Closure of Moisture Budget inside Arctic Atmospheric Rivers 

Henning Dorff, Heike Konow, Vera Schemann, Davide Ori, Mario Mech, and Felix Ament

Among arctic moist air intrusions, atmospheric rivers (ARs) provide substantial moisture transport over long distances poleward. Along their corridors, warm and moist air masses undergo various transformation processes and can cause regional sea ice decline, especially when they induce precipitation as rain. Quantifying the components of the atmospheric moisture budget in arctic ARs is key to elucidate their precipitation efficiency. We close the AR moisture budget by measurements of the High Altitude LOng range research aircraft (HALO) during the recent HALO-(AC)³ campaign (Spring, 2022) in the vicinity of the Fram Start and Arctic ocean.

Our analysis is based on a strong AR event that HALO observed on two consecutive days during the occurrence of a sequence of moist air intrusions mid of March 2022. Dropsondes detect the vertical atmospheric profile and therefrom quantify the integrated water vapour transport (IVT) along AR cross sections. Applying regression methods then allows calculating the divergence of IVT. Since the limited number of dropsondes may deteriorate such calculations, we estimate the arising uncertainties using the ICOsahedral Nonhydrostatic model (ICON) in a storm-resolving configuration. Retrieved moisture profiles from the microwave radiometer (HAMP) further complement the sporadic sonde-based moisture profiles. We use the nadir cloud and precipitation radar mounted aboard HALO to derive precipitation rates along the flight curtains.

As the comparison with ICON suggests, the set of dropsondes to derive the IVT divergence within a reasonable range. The advection of moisture is roughly twice as strong as mass convergence. Both components act on different heights, with convergence dominating in the boundary layer (0-1 km) near the low-level jet, whereas moisture advection is more elevated (1-4 km). The strongest moisture convergence arises in the warm prefrontal AR sector while precipitation dominates slightly westwards in the AR centre. The investigated AR event caused rain over sea-ice with a melting layer up to 1.5 km. While there was less IVT on the second observation day, mean precipitation increased from the first day. Model simulations show that evaporation makes only a small contribution to the budget.  Within the ICON simulations, the comparison of precipitation purely based on the along-track radar curtain against that over the entire AR corridor indicates that the along-track curtain captures the mean precipitation intensity of the AR corridor, but misrepresents its spatial variability. However, the HALO devices outperform the ICON simulations in terms of the vertical variability of moisture conversion processes.

How to cite: Dorff, H., Konow, H., Schemann, V., Ori, D., Mech, M., and Ament, F.: Airborne Closure of Moisture Budget inside Arctic Atmospheric Rivers, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9784, https://doi.org/10.5194/egusphere-egu23-9784, 2023.

EGU23-10197 | Orals | AS1.11

Atmospheric moisture intrusion into the Arctic: sources, impact, and trends 

Hailong Wang, Rudong Zhang, Yufei Zou, Weiming Ma, Philip Rasch, and Travis O'Brien

Atmospheric water vapor plays an enormously important role in the water cycle and energy budget of the Arctic. Water vapor in the Arctic also participates in many important feedback mechanisms influencing the climate response to forcing agents and the Arctic amplification. In this study, we conduct analysis of atmospheric moisture transport into the Arctic based on reanalysis products and CMIP6 model simulations. We are particularly interested in the episodic atmospheric-river-like features (AR or moisture intrusion) that play an important role in delivering water to the Arctic. Based on the method of using column-integrated meridional vapor transport for characterizing AR events, we find that the mean AR frequency peaks in the Atlantic sector in all seasons except that it’s more zonally widespread in summer. An increasing trend in the Arctic AR frequency in the recent decades identified from ERA5 can be captured by few CMIP6 models. The historical Arctic AR frequency, sea ice concentration and Arctic warming are highly correlated. Atmospheric circulation patterns that drive the interannual and decadal Arctic AR variation contribute substantially to the historical Arctic warming. We also use the Community Earth System Model (CESM), equipped with a water tagging capability, to quantify contributions of surface evaporation within the Arctic versus from lower-latitude regions as a source of water to the Arctic and characterize moisture transport pathways that control the Arctic water vapor distribution.

How to cite: Wang, H., Zhang, R., Zou, Y., Ma, W., Rasch, P., and O'Brien, T.: Atmospheric moisture intrusion into the Arctic: sources, impact, and trends, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10197, https://doi.org/10.5194/egusphere-egu23-10197, 2023.

EGU23-10530 | ECS | Orals | AS1.11 | Highlight

Central tropical Pacific convection drives extreme high temperatures and surface melt on the Larsen C Ice Shelf, Antarctic Peninsula 

Kyle Clem, Deniz Bozkurt, Daemon Kennett, John King, and John Turner

Northern sections of the Larsen Ice Shelf, eastern Antarctic Peninsula (AP) have experienced dramatic break-up and collapse since the early 1990s due to strong summertime surface melt, linked to strengthened circumpolar westerly winds. Here we show that extreme summertime surface melt and record-high temperature events over the eastern AP and Larsen C Ice Shelf are triggered by deep convection in the central tropical Pacific (CPAC), which produces an elongated cyclonic anomaly across the South Pacific coupled with a strong high pressure anomaly over Drake Passage. Together these atmospheric circulation anomalies transport very warm and moist air to the southwest AP, often in the form of “atmospheric rivers”, producing strong foehn warming and surface melt on the eastern AP and Larsen C Ice Shelf. Therefore, variability in CPAC convection, in addition to the circumpolar westerlies, is a key driver of AP surface mass balance and the occurrence of extreme high temperatures.

How to cite: Clem, K., Bozkurt, D., Kennett, D., King, J., and Turner, J.: Central tropical Pacific convection drives extreme high temperatures and surface melt on the Larsen C Ice Shelf, Antarctic Peninsula, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10530, https://doi.org/10.5194/egusphere-egu23-10530, 2023.

EGU23-11436 | Orals | AS1.11 | Highlight

Moisture transport into the Arctic in a past and future climate 

Sabine Eckhardt, Tove Svendby, Birthe Steensen, Gunnar Myhre, Ada Germundsen, and Dirk Olivie

The Arctic is warming at a faster rate than the rest of the globe. There are both remote and local mechanism identified driving this process. While albedo changes and atmospheric stability happens within in the Arctic, transfer transport processes, both in the ocean and atmosphere, heat and moisture into the Arctic. These processes can be analysed in a Eulerien way, by observing the fluxes through a curtain defining the Arctic or/and by Lagrangian analysis which follows this transport processes all the way from uptake in the mid/high latitudes until the inflow into the Arctic. 

We use a Lagrangian Particle Transport model FLEXPART running with ECMWF reanalysis data as well as with data from the norwegian earth system model NorESM, which represents the future climate scenarios until 2100. In this way we investigate the inflow of moisture and energy for the last 50 years, but can also project it in the future by considering the climate model output.

We find that the the transport through the 65N Latitude, defining the Arctic area is highly inhomogenious in space, but has also a distinct seasonal variability. The end of the storm tracks, especially the Northern Atlantic stormtrack show the most important region of inflow. While moisture origins over ocean areas in winter, continental areas in summer act as a source. The patterns in the reanalysis data from ECMWF and in the climate simulations are very similar. Those patterns are stable over time, but intensify in a warming climate.

How to cite: Eckhardt, S., Svendby, T., Steensen, B., Myhre, G., Germundsen, A., and Olivie, D.: Moisture transport into the Arctic in a past and future climate, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11436, https://doi.org/10.5194/egusphere-egu23-11436, 2023.

EGU23-11620 | Posters on site | AS1.11

Analyzing the development of cold air outbreaks and warm air intrusions based on remote sensing and dropsonde data from (AC)3 campaigns 

Marcus Klingebiel, Lukas Monrad-Krohn, Benjamin Kirbus, Mario Mech, André Ehrlich, and Manfred Wendisch

Within the framework of (AC)3, four airborne campaigns were conducted in the vicinity of Svalbard to investigate the Arctic airmass transformations during warm air intrusions (WAI) and marine cold air outbreaks (CAO). In this study, we will take a deeper look into the development process of CAOs starting from the marginal sea-ice zone towards the open ocean, using data from active and passive remote sensing instruments. In addition, we will present data from more than 450 dropsondes launched during the HALO-(AC)3 campaign and analyze the development of the vertical profiles along WAIs and CAOs. This is done by using a Lagrangian analysis of the campaign, which delivers same-day and next-day trajectory matches of the HALO flights.

How to cite: Klingebiel, M., Monrad-Krohn, L., Kirbus, B., Mech, M., Ehrlich, A., and Wendisch, M.: Analyzing the development of cold air outbreaks and warm air intrusions based on remote sensing and dropsonde data from (AC)3 campaigns, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11620, https://doi.org/10.5194/egusphere-egu23-11620, 2023.

EGU23-11951 | ECS | Posters on site | AS1.11

Influence of atmospheric rivers, cyclones and fronts on precipitation in the Arctic – a climatological perspective 

Melanie Lauer, Annette Rinke, Irina Gorodetskaya, Michael Sprenger, Mario Mech, and Susanne Crewell

The enhanced warming in the Arctic compared to the global mean – a phenomenon called Arctic Amplification - has different effects, including impacts on the hydrological cycle and thus the precipitation. In the Arctic, there are two major sources of moisture leading to increased precipitation formation: The enhanced local evaporation due to the missing insulation due to reduced sea-ice cover and the increased poleward moisture transport which is often associated with atmospheric rivers (ARs).

Previous studies have shown that ARs are a significant source for rain and snow in the Arctic. ARs are dynamically linked to the extratropical cyclones and fronts. Thus, AR-related precipitation can be not only concentrated within the AR itself, but also occur within the cyclone and frontal boundaries. Therefore, we developed a new method to distinguish precipitation within the AR shape and the precipitation related to cyclones and fronts based on ERA5 reanalysis. Thereby, we estimate how much precipitation occurs within AR, cyclone and frontal boundaries, separately and overlapping together. We applied this method for different case studies during two campaigns performed at and around Svalbard within the Collaborative Research Center “Arctic Amplification: Climate Relevant Atmospheric Surface Processes, and Feedback Mechanisms (AC)3”. Differences in the contributions of ARs, cyclones and fronts to the total precipitation could be identified comparing the both campaigns. During the early summer campaign (ACLOUD), precipitation (both rain and snow) was more confined within the AR shapes, especially in the area in which the AR is connected to fronts. In contrast, during the early spring campaign (AFLUX), precipitation (predominantly snow) was more restricted to the cyclone regions without connection to ARs and fronts. Generally, a higher precipitation intensity was found within ARs, especially when they are connected with cyclones and fronts.

In a climatological perspective, we apply this method to the ERA5 reanalysis data (1979 - 2020) to quantify the occurrence and influence of ARs and related cyclones and fronts. For this extended analysis, we consider the whole Arctic. This allows us to analyse the change of precipitation (in terms of type and frequency) related to the different weather systems during the last four decades. Furthermore, we can assess seasonal differences. In summary, we can investigate in which regions ARs, cyclones and fronts have a greater impact and if and how it also depends on different surface types (sea ice, open ocean, and land).

This work is supported by the DFG funded Transregioproject TR 172 “Arctic Amplification (AC)3“.

How to cite: Lauer, M., Rinke, A., Gorodetskaya, I., Sprenger, M., Mech, M., and Crewell, S.: Influence of atmospheric rivers, cyclones and fronts on precipitation in the Arctic – a climatological perspective, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11951, https://doi.org/10.5194/egusphere-egu23-11951, 2023.

EGU23-13074 | ECS | Orals | AS1.11

Linking aerosol size distribution and hygroscopicity to cloud droplet formation at an Arctic mountain site 

Ghislain Motos, Gabriel Freitas, Paraskevi Georgakaki, Jörg Wieder, Wenche Aas, Chris Lunder, Radovan Krejci, Julie T. Pasquier, Jan Henneberger, Robert O. David, Claudia Mohr, Paul Zieger, and Athanasios Nenes

The regulation of energy transfer by clouds and fog is a key process affecting the climate of the Arctic, a region that exhibits frequent cloud cover and suffers an extreme vulnerability to climate change. Measurements were performed over a whole year at the Zeppelin station, Ny-Ålesund, Svalbard, Norway from October 2019 to October 2020 in the framework of the NASCENT campaign (Ny-Ålesund AeroSol Cloud ExperimeNT). Aiming at a better understanding of the susceptibility of cloud droplet formation, we analyzed particle number size distributions obtained from differential mobility particle sizers and chemical composition derived from filter samples and an aerosol chemical speciation monitor. Combined with updraft velocity information from a wind lidar and an ultrasonic anemometer, the data were used as input parameters for a state-of-the-art cloud droplet formation parameterization to investigate the particle sizes that can activate to cloud droplets, the levels of supersaturation as well as potential cloud droplet formation and its susceptibility to aerosol. We showed that low aerosol levels in fall and early winter led to clouds that are formed under an aerosol-limited regime, while higher particle concentrations centered around the Arctic Haze together with a drop in cloud supersaturation could be linked to periods of updraft velocity-limited cloud formation regime. In the latter case, we observed that the maximum number of cloud droplets forming - also called the limiting droplet number - and the updraft velocity follow a relationship that is universal, as proved by similar studies previously performed in different environments and cloud types. Finally, we successfully performed a droplet closure, proving, for the first time, the ability of our cloud droplet parameterization to predict cloud droplet number not only in liquid clouds but also in mixed-phase clouds with a very high degree of glaciation. This closure suggests that rime splintering may not be significant enough to affect droplet concentrations, which is consistent with previous observations and model simulations.

How to cite: Motos, G., Freitas, G., Georgakaki, P., Wieder, J., Aas, W., Lunder, C., Krejci, R., T. Pasquier, J., Henneberger, J., O. David, R., Mohr, C., Zieger, P., and Nenes, A.: Linking aerosol size distribution and hygroscopicity to cloud droplet formation at an Arctic mountain site, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13074, https://doi.org/10.5194/egusphere-egu23-13074, 2023.

EGU23-13124 | ECS | Posters on site | AS1.11

Assessing Arctic low-level clouds and precipitation from above - a radar perspective 

Imke Schirmacher, Susanne Crewell, Katia Lamer, Mario Mech, and Manfred Wendisch

According to satellite-based estimations, a lot of clouds over the Arctic Ocean occur below
2 km. Most information on Arctic low-level clouds come from CloudSat radar measurements.
However, CloudSat lacks a complete representation of low-level clouds because the blind
zone masks the lowest kilometer and the coarse spatial sampling conceals cloud patterns.
Thus, higher resolved observations of cloud characteristics are needed to determine how
the cloud fraction varies close to the ground and how it depends on surface characteristics
and meteorological situation.

Our study investigates the low-level hydrometeor fraction of Arctic clouds over the ocean
using airborne remote sensing measurements by the Microwave Radar/radiometer for Arctic
Clouds (MiRAC) flown on the Polar 5 aircraft. Four campaigns have been conducted in the
vicinity of Svalbard during different seasons: ACLOUD, AFLUX, MOSAiC-ACA, and HALO-
AC3. We convolute the MiRAC radar reflectivity measurements to adapt the fine MiRAC and
coarse CloudSat resolution. The convoluted measurements are compared with the original
airborne observations over all campaigns to investigate the effects of CloudSat’s spatial res-
olution, clutter mask, and sensitivity on the low-level hydrometeor fraction. Measurements
reveal high hydrometeor fractions of up to 60% in the lowest 1.5 km, which CloudSat would
miss due to the blind zone. CloudSat would especially underestimate half of the total pre-
cipitation. During cold air outbreaks, when rolling cloud structures evolve, CloudSat over-
estimates the hydrometeor fraction most. Moreover, CloudSat does not resolve the separate
layers of multilayer clouds but rather merges them because of its coarse vertical resolution.

How to cite: Schirmacher, I., Crewell, S., Lamer, K., Mech, M., and Wendisch, M.: Assessing Arctic low-level clouds and precipitation from above - a radar perspective, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13124, https://doi.org/10.5194/egusphere-egu23-13124, 2023.

EGU23-13191 | ECS | Orals | AS1.11

The evolution of clouds in Arctic marine cold air outbreaks 

Rebecca Murray-Watson and Edward Gryspeerdt

Marine cold air outbreaks (MCAOs) are important parts of the high-latitude climate system and are characterised by strong surface fluxes generated by the air-sea temperature gradient. These fluxes promote cloud formation, which can be identified in satellite imagery by the distinct transformation of stratiform cloud 'streets' into a broken field of cumuliform clouds downwind of the outbreak. This evolution of cloud morphology changes the radiative properties of the cloud and therefore is of importance to the surface energy budget.  

While the drivers of stratocumulus-to-cumulus transitions have been extensively studied for subtropical clouds, such as aerosols or the sea surface temperature gradient, the factors influencing transitions at higher latitudes are relatively poorly understood. This work uses reanalysis data to create a set of composite trajectories of cold air outbreaks moving off the Arctic ice edge and co-locates these trajectories with data from multiple satellites to generate a unique view of cloud development within cold air outbreaks. 

Clouds embedded in MCAOs have distinctive properties relative to clouds following other, more stable trajectories in the region. The initial instability and aerosol environments have distinct impacts on cloud development within outbreaks. The strength of the outbreak has a lasting effect on the magnitude of cloud properties along the trajectory. However, it does not strongly affect the timing of the transition to cumuliform clouds. In contrast, the initial aerosol concentration changes the timing of cloud break-up rather than the size of the cloud response.

How to cite: Murray-Watson, R. and Gryspeerdt, E.: The evolution of clouds in Arctic marine cold air outbreaks, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13191, https://doi.org/10.5194/egusphere-egu23-13191, 2023.

EGU23-13388 | Posters on site | AS1.11

Occurrence of multilayer clouds and ice-crystal seeding during the Arctic Ocean 2018 and MOSAiC research campaign 

Peggy Achtert, Matthias Tesche, Gabriella Wallentin, and Corinna Hoose

Previous research on arctic clouds has focused on single-layer clouds. However, the occurrence of multi-layer clouds in the Arctic is of importance, since in such systems upper clouds can influence the phase of lower clouds. This is the case when ice crystals fall from above into supercooled liquid water clouds and trigger the formation of mixed-phase clouds.

The aim of our project is to investigate the occurrence of multi-layer clouds and seeding using the combination of radiosonde and cloud radar observations. The focus is on the MOSAiC campaign. In order to classify and interpret the results, previous measurements will be used as well.

During the Arctic Ocean 2018 campaign multi-layer clouds were observed 56% of the time and 48 % showed a likelihood of seeding. Previous satellite studies on multi-layer-clouds showed an occurrence of 11 %. During the MOSAiC campaign multi-layer clouds occurred around 50 % of the time and showed a latitude dependency, with more multi-layer clouds north of 84°N.

How to cite: Achtert, P., Tesche, M., Wallentin, G., and Hoose, C.: Occurrence of multilayer clouds and ice-crystal seeding during the Arctic Ocean 2018 and MOSAiC research campaign, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13388, https://doi.org/10.5194/egusphere-egu23-13388, 2023.

EGU23-14418 | ECS | Orals | AS1.11

Simulating the effects of Ice-nucleating particles in Antarctica in COSMO-CLM² 

Florian Sauerland, Niels Souverijns, Anna Possner, Heike Wex, Preben Van Overmeiren, Alexander Mangold, Kwinten Van Weverberg, and Nicole van Lipzig

The remoteness of the Antarctic continent has important implications for the microphysical properties of clouds: In particular, the rare abundance of ice-nucleating particles (INP) limits the primary nucleation of ice crystals. Yet, persistent mixed-phase clouds with ice crystal number concentrations of 0.1-1l-1 are still observed in the Arctic and Antarctic. However, the ability of regional climate models to reproduce these mixed-phase clouds remains limited, much like the knowledge about their climatological effects. Thus, we added a module to the regional climate model COSMO-CLM² aimed at improving the parametrisation of the aerosol-cycle, which allows us to prescribe different concentrations of INPs. We examined the model response to different concentrations by running it in an area around the Belgian Princess Elisabeth Station in Dronning Maud Land for one month and with four different concentration settings: The first, corresponding to the low end of INP concentrations we observed at the station, the second, corresponding to the high end of INP concentrations we observed at the station, and the third and fourth, to the low and high end of continental observations. The performance was evaluated by comparing the simulation results with radar and ceilometer observations taken at the station. Finally, we analysed the differences between the four simulations to determine the overall sensitivity of the model to variability in INP concentrations, which allows us to draw conclusions about the importance of accurately simulating processes related to ice nucleation, and about the climatological implications that a change in aerosol concentrations would have.

How to cite: Sauerland, F., Souverijns, N., Possner, A., Wex, H., Van Overmeiren, P., Mangold, A., Van Weverberg, K., and van Lipzig, N.: Simulating the effects of Ice-nucleating particles in Antarctica in COSMO-CLM², EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14418, https://doi.org/10.5194/egusphere-egu23-14418, 2023.

EGU23-15022 | ECS | Posters on site | AS1.11

Impact of Atmospheric Rivers on the Arctic Surface Energy Budget 

Sofie Tiedeck, Benjamin Kirbus, Melanie Lauer, Susanne Crewell, Irina Gorodetskaya, and Annette Rinke

Atmospheric Rivers (ARs) are long, narrow atmospheric structures which carry anomalously warm and moist air from lower latitudes into higher latitudes. Therefore, ARs are discussed to contribute to Arctic Amplification due to water vapor feedback and cloud-radiation processes. The detailed impact on the surface energy budget (SEB), however, is not fully understood.

We analyze the impact of ARs on the SEB of an early winter and spring case study, using ERA5 reanalysis data and model output from limited area simulations of ICON (ICON-LAM). Both cases show less energy loss of the surface compared to climatology, especially due to more downward longwave radiation and less upward sensible heat. The effect depends on the surface type, open ocean or sea ice. Next, we provide a climatological perspective on the impact of Atmospheric Rivers on the SEB based on ERA5.

How to cite: Tiedeck, S., Kirbus, B., Lauer, M., Crewell, S., Gorodetskaya, I., and Rinke, A.: Impact of Atmospheric Rivers on the Arctic Surface Energy Budget, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15022, https://doi.org/10.5194/egusphere-egu23-15022, 2023.

EGU23-16007 | ECS | Orals | AS1.11

One year of Aerosol and Cloud measurements in Rothera on the Antarctic Peninsula 

Floortje van den Heuvel, Tom Lachlan-Cope, Jonathan Witherstone, Joanna Dyson, Freya Squires, Daniel Smith, and Michael Flynn

Our limited understanding of clouds is a major source of uncertainty in climate sensitivity and climate model projections. The Southern Ocean is the largest region on Earth where climate models present large biases in short and long wave radiation fluxes which in turn affect the representation of sea surface temperatures, sea ice and ultimately large scale circulation in the Southern Hemisphere. Evidence suggests that the poor representation of mixed phase clouds at the micro- and macro scales is responsible for the model biases in this region. The Southern Ocean Clouds (SOC) project is a multi-scale, multi-platform approach with the aim of improving understanding of aerosol and cloud microphysics in this region, and their representation in numerical models.

In February 2022 we installed a suite of instruments at the Rothera research station on the Antarctic peninsula to measure the physical and chemical properties of aerosol, the number concentrations of Cloud Condensation Nuclei and Ice Nucleating Particles, and cloud height and thickness all year round. Here we will report the first observations and statistics of one full year of aerosol and cloud measurements from the Rothera research station.

How to cite: van den Heuvel, F., Lachlan-Cope, T., Witherstone, J., Dyson, J., Squires, F., Smith, D., and Flynn, M.: One year of Aerosol and Cloud measurements in Rothera on the Antarctic Peninsula, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16007, https://doi.org/10.5194/egusphere-egu23-16007, 2023.

EGU23-2324 | Orals | AS1.12

Observing the dynamics of deep convection using a tandem of spaceborne microwave radiometers 

Helene Brogniez, Remy Roca, Jean-Pierre Chaboureau, Franck Auguste, Ilhem Gharbi, Thomas Lefebvre, Thomas Fiolleau, and Dominique Bouniol

Deep convection plays a fundamental role in the climate system by transporting from the lower layers of the atmosphere to the free troposphere, air, water and momentum. Although its study has been the subject of intense and rich scientific activities for decades, our ignorance of the vertical distribution of convective movements in the heart of convective cells is today an important scientific and operational obstacle. Only space-borne observations can meet the needs in documentation necessary to progress on the science of the water and energy cycle and simultaneously improve numerical forecasting systems. Pending the emergence (hypothetical) of microwave missions in geostationary orbit with high repeatability (~ 1 minute), an approach based on satellite constellations in convoys could provide a first response.

The “Convective Core Observations through MicrOwave Derivatives in the trOpics”, or C2OMODO for short, proposes to rely on 2 passive microwave radiometers with a multispectral sampling of the 183 and 325 GHz lines in a mini-train of 2 satellites. The time-spacing of 60 to 180sec between the 2 swaths encompasses information on the updraft motions of hydrometeors, and is thus used to characterize the intensity and the size of individual updrafts in deep convective systems.

We will present this original observational strategy, associated to the NASA / AOS general framework, as well as its expected added-value for the characterization of deep convection.

How to cite: Brogniez, H., Roca, R., Chaboureau, J.-P., Auguste, F., Gharbi, I., Lefebvre, T., Fiolleau, T., and Bouniol, D.: Observing the dynamics of deep convection using a tandem of spaceborne microwave radiometers, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2324, https://doi.org/10.5194/egusphere-egu23-2324, 2023.

EGU23-3105 | Posters on site | AS1.12

Insight of deep convection and sea surface wind gusts link through collocated GEO and LEO data 

Yu Li, Tran Vu La, Ramona-Maria Pelich, Marco Chini, Patrick Matgen, and Christophe Messager

Convective system (CS) is an extreme weather event occurring regularly over the subtropical and tropical regions such as the Gulf of Guinea, the Gulf of Mexico, Lake Victoria, Southeast Asia, India, and Australia. Certain CS types, i.e., mesoscale CS, supercell convective storms, squall lines, are disastrous for human life, infrastructures, and economic activities since they can produce strong surface winds, heavy rainfall, and significant lightning. Over the last decades, the CS observing, monitoring, and forecasting have been much improved thanks to a dense network of GEOstationary (GEO) satellites, including Meteosat, GEOS, Himawari, and Gaofen, covering Europe, Africa, America, and the Asia Pacific, respectively. However, the observation and prediction of the extreme weather events associated with deep convection are still a big challenge since they often occur suddenly, develop quickly, and become intense in a short time (several hours). Such unpredicted features are a significant issue for the numerical weather prediction models. While the prediction of intense rainfall associated with deep convection is still ongoing, the estimation of surface convective wind gusts has some important advancements. La et al. [1-2] indicated Sentinel-1 C-band Synthetic Aperture Radar (SAR) data with a high spatial resolution and wide swath bring significant advantages for observing and estimating ocean surface convective wind gusts. Indeed, through the images acquired by the Sentinel-1 Low Earth Orbit (LEO) satellite, one can observe convective wind patterns at both mesoscales and sub-mesoscales, as well as wind hot spots (15-25 m/s) at a small scale. The studies [1-2] also showed the relationship between surface wind patterns and deep convective clouds observed on Meteosat GEO images. In particular, the collocation of Sentinel-1, Aeolus Lidar, and Meteosat devices [3] enabled a multi-dimensional view of deep convection and its vertical and horizontal dynamics.

Following the previous studies, we illustrate in this paper more interesting cases of multi-dimensional CS observations by the collocated GEO and LEO sensors. They include sea surface convective wind patterns observed by Sentinel-1 LEO, intense downdrafts detected by Aeolus Lidar LEO, and deep convective clouds observed by Meteosat GEO. These cases expected to strengthen the relationship between deep convection and strong surface winds over the sea. In particular, we present the assessment of surface convective wind gust estimates through comparisons to in situ wind measurements by the moored buoys and weather stations. This work is a significant step to strengthen the conclusion that the high-intensity radar backscattering observed on Sentinel-1 C-band SAR images is associated with surface convective wind gusts rather than induced by precipitation.

[1] T. V. La and C. Messager, "Convective System Observations by LEO and GEO Satellites in Combination," IEEE JSTARS, vol. 14, pp. 11814-11823, 2021, doi: 10.1109/JSTARS.2021.3127401.

[2] T. V. La and C. Messager, "Different Observations of Sea Surface Wind Pattern Under Deep Convection by Sentinel-1 SARs, Scatterometers, and Radiometers in Collocation," IEEE JSTARS, vol. 15, pp. 3686-3696, 2022, doi: 10.1109/JSTARS.2022.3172375.

[3] La, T. V., & Messager, C. (2021). Convective system dynamics viewed in 3D over the oceans. Geophysical Research Letters, 48(5), e2021GL092397.

How to cite: Li, Y., La, T. V., Pelich, R.-M., Chini, M., Matgen, P., and Messager, C.: Insight of deep convection and sea surface wind gusts link through collocated GEO and LEO data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3105, https://doi.org/10.5194/egusphere-egu23-3105, 2023.

EGU23-4910 | Posters on site | AS1.12

Evaluating the L-MEB forward radiative transfer model for the assimilation of SMOS observations 

Mozhdeh Jamei and Ebrahim Asadi Oskouei

Satellite observations play an important role in providing the initial conditions for the Numerical Weather Prediction (NWP) models. Satellite data are assimilated into the first estimate provided by NWP models using a radiative transfer model. The impact of satellite observations significantly depends on the accuracy of the simulation performed by the radiative transfer (RT) models. In recent years, there have been significant advances in RT modeling for microwave and infrared observations, which are not sensitive to the surface. However, in the case of sensitive surface observations such as Soil Moisture and Ocean Salinity (SMOS) satellite observations, the assimilation has been limited by inaccuracy in the forward calculations. This study investigates the accuracy of the L-band Microwave Emission of the Biosphere (L-MEB) RT model for SMOS frequencies using high-quality in-situ observations as input. The L-MEB model is the forward RT model used in the SMOS L2 algorithm, specifically developed to simulate brightness temperature (TB) over the land surfaces at different incidence angles (between 0° and 60°). The L-MEB model simulated the SMOS TB data with the horizontal (H) and vertical (V) polarization at the lowest SMOS incidence angles at the meteorological stations over Iran.The land cover at these stations is either bare soil or low vegetation. The comparison between simulated TB and the SMOS TB products showed a suitable RMSE and a relatively low bias for horizontally and vertically polarized channels. The relatively low bias can justify the assimilation of SMOS observations into the data assimilation systems. However, cross-comparison of the RT models used at the NWP centers and the RT models such as L-MEB, which were mainly developed to work with the SMOS data, is required to ensure that the operational RT models used at the NWP centers meet the same accuracy.

 

How to cite: Jamei, M. and Asadi Oskouei, E.: Evaluating the L-MEB forward radiative transfer model for the assimilation of SMOS observations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4910, https://doi.org/10.5194/egusphere-egu23-4910, 2023.

It has long been known that microphysics parameterizations are among leading sources of model uncertainty in storm and convective scale weather prediction.  The uncertainty results from combination of imperfect knowledge of the microphysics processes, inability to explicitly resolve them at computationally feasible spatial and phase-space resolutions, as well as from inherent limited predictability of micro to turbulent scale processes.   Representing these in the context of improving probabilistic prediction skill using ensembles has been the subject of many studies, but remains an outstanding problem.  The problem is especially acute in storm and convective scale ensemble prediction, where there may be strong coupling of errors between ensemble data assimilation and forecasting. 

Over the last decade, the inclusion of stochastic representation of model uncertainty associated with physical parameterizations has emerged as a viable approach for representing the intrinsic uncertainties of the microphysical parameterizations.  This study examines sensitivity of storm scale ensemble simulations to representation of microphysics parameterization uncertainties using a cloud resolving model.  We compare several stochastic parameter (SP) perturbation methods, including various parameter distributions and parameter covariance models, applied to physical parameters in a bulk microphysics parameterization.  The study follows a prior study, in which a 1D column version of the 3D cloud resolving model was used to test non-stochastic and several SP perturbation methods for which the parameter perturbation statistical distributions were based on Markov Chain Monte Carlo (MCMC) inversions with synthetic observations. That study indicated that SP schemes produce significantly more ensemble variance of microphysics states than non-stochastic, and that inclusion of parameter covariances, and specifically those that vary with the state of the system, improve their performance.

The current study investigates impacts of SP scheme configurations on microphysics with dynamical feedbacks in 3D ensemble simulations.  The statistical parameter distributions used for the SP scheme are obtained as in the 1D study using MCMC inversions with synthetic observations. The results are evaluated in terms of changes to the ensemble mean and variance of microphysical and dynamical states and the simulated column integral microphysics-sensitive satellite-based observable quantities. We discuss the results and note the implications for convective scale ensemble data assimilation and forecasting. 

How to cite: Vukicevic, T., Posselt, D., and Jurlina, S.: Evaluation of stochastic parameter representation of microphysics parameterization uncertainty for convective scale ensemble data assimilation and prediction, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5714, https://doi.org/10.5194/egusphere-egu23-5714, 2023.

Data assimilation techniques can improve the simulation of regional precipitation and temperature over complex regions. Nowadays, regional climate simulations using convection-permitting scales are becoming available, but the number of those simulations including an additional data assimilation scheme is rather small because of their high computational costs. Hence, it is important to evaluate the effect of data assimilation schemes for such convection-permitting simulations, and to determine if data assimilation produces any improvement in the simulation of temperature or precipitation fields.

To investigate this, we employ the Weather Research and Forecasting model (WRF; version 3.8.1) to dynamically downscale the state-of-the-art ERA5 reanalysis over Western Europe. A 3 km spatial resolution grid is employed, together with 51 vertical levels. The temporal resolution of the WRF outputs is one hour. Two model configurations are tested in two experiments spanning the period 2010-2020 after a one-year spin-up. In the first experiment (NoDA), after the initialization of the model, the boundary conditions drive the model. The second experiment (DA) is configured the same way as NoDA, but the additional 3DVAR data assimilation step (WRFDA) is run every six hours (00, 06, 12 and 18 UTC – analysis times). Observations obtained from the PREPBUFR dataset (NCEP ADP Global Upper Air and Surface Weather Observations) are employed, and only those included inside a 120 min window around analysis times were assimilated. For DA, monthly varying background error covariance matrices were created. In both cases, the model uses the Noah-MP land surface model, and high-resolution daily-varying SST fields from the NOAA OI SST v2 data set instead of the SST field from ERA5.

The results of this study show that both experiments produce similar monthly precipitation patterns to those from observational data sets such as IMERG and CHIRPS, or the reanalysis ERA5. However, in general, and particularly during summer months, DA produces larger amounts of precipitation than NoDA. These amounts are in line with those from CHIRPS. In terms of temperature, DA show colder temperatures than NoDA in most of the months, which again are similar to those from observational data sets such as CRU or EOBS. The monthly temperature patterns of both experiments are similar to those from both observational data sets. These results highlight the fact that NoDA already is able to generate reliable precipitation and temperature fields compared to diverse gridded observational data sets, but the 3DVAR data assimilation can additionally improve the performance of the regional model when convection-permitting scales are employed.

How to cite: González-Rojí, S. J. and Raible, C. C.: The effect of 3DVAR data assimilation and convection-permitting scales on the simulation of precipitation and temperature over Western Europe, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6378, https://doi.org/10.5194/egusphere-egu23-6378, 2023.

EGU23-7868 | Posters on site | AS1.12

Learning model parameters from observations by combining data assimilation and machine learning 

Tijana Janjic, Yvonne Ruckstuhl, and Stefanie Legler

Parametrization of microphysics as well as parametrization of processes in the surface and boundary layers typically contain several tunable parameters. The parameters are not observed and are only crudely known. Traditionally, the numerical values of these model parameters are chosen by manual model tuning, leading to model errors in convection permitting numerical weather prediction models. More objectively, parameters can be estimated from observations by the augmented state approach during the data assimilation or by combing data assimilation with machine learning (ML).

If the parameters are updated objectively according to observations, they are flexible to adjust to recent conditions, their uncertainty is considered, and therefore the uncertainty of the model output is more accurate. To illustrate benefits of online augmented state approach, Ruckstuhl and Janjic (2020) show in an operational convection-permitting configuration that the prediction of clouds and precipitation is improved if the two-dimensional roughness length parameter is estimated. This could lead to improved forecasts of up to 6 h of clouds and precipitation. However, when parameters are estimated by the augmented state approach, stochastic model for the parameters needs to be pre-specified to keep the spread in parameters. Alternatively, Legler and Janjic (2022) investigate a possibility of using data assimilation for the state estimation while using ML for parameter estimation in order to overcome this problem. We train two types of artificial neural networks as a function of the observations or analysis of the atmospheric state.  The test case uses perfect model experiments with the one-dimensional modified shallow-water model, which was designed to mimic important properties of convection. Through perfect model experiments we show that Bayesian neural networks (BNNs) and ensemble of point estimate neural networks (NNs) are able to estimate model parameters and their relevant statistics. The estimation of parameters combined with data assimilation for the state decreases the initial state errors even when assimilating sparse and noisy observations.

How to cite: Janjic, T., Ruckstuhl, Y., and Legler, S.: Learning model parameters from observations by combining data assimilation and machine learning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7868, https://doi.org/10.5194/egusphere-egu23-7868, 2023.

Deep convective cloud systems are one of the leading contributors to weather related disasters, provide much of the fresh water used by society, and contribute significantly to the interactions among weather and climate. Convection is known to be influenced strongly by the characteristics of its environment, including the vertical structure of temperature, moisture, and wind. It has also been shown in many numerical modeling studies to be sensitive to the assumptions made in the representation of cloud processes.

 

This presentation will explore the relative influence of environmental (extrinsic) factors and cloud microphysical parameter (intrinsic) uncertainty in the evolution of tropical deep convection. The effect of both types of factor on the energy and water cycle, as well as on convective dynamics and heating, are shown. Ensemble Monte Carlo experiments quantify convective storm sensitivity, while ensemble data assimilation experiments provide traceability from convective outcomes to control factors. The results have implications for modeling, data assimilation, and the design of future observing systems.

How to cite: Posselt, D.: The relative sensitivity of convective simulations to perturbations in initial conditions and microphysics parameters, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8429, https://doi.org/10.5194/egusphere-egu23-8429, 2023.

EGU23-9488 | Orals | AS1.12 | Highlight

Predictive hazards from convective systems with deep learning 

Jussi Leinonen, Ulrich Hamann, Ioannis Sideris, and Urs Germann

Convection is a complex spatiotemporal process, which has made it a particularly attractive application for deep learning, which excels at both spatial and temporal reasoning. We have developed deep learning models for predicting the occurrence of hazards caused by convective storms, so that this information may be used by forecasters, emergency services and infrastructure managers to respond to the threats caused by these hazards.

Our network is based on a recurrent-convolutional architecture that can process input data at multiple resolutions. It issues probabilistic predictions of hazard occurrence, currently up to 1 hour to the future. As inputs, we use data from weather radars, geostationary satellites, ground-based lightning detections, numerical weather predictions and digital elevation models. We have studied the importance of each data source to the quality of the predictions, finding that radar-based inputs contribute most to the prediction quality; however, some hazards can be well predicted also without radar, indicating that it is plausible to create warning systems for these hazards in areas where radar networks are not available.

In this presentation, we will describe the model architecture and case studies, as well as our experiences so far in bringing the model to real-time use by forecasters and automated warning systems at MeteoSwiss. We will also discuss future directions of this research.

How to cite: Leinonen, J., Hamann, U., Sideris, I., and Germann, U.: Predictive hazards from convective systems with deep learning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9488, https://doi.org/10.5194/egusphere-egu23-9488, 2023.

Clouds are the first area-wide observable signal of convection. Although heavily used in nowcasting applications, the use of cloud-affected satellite observations in data assimilation is very limited.

This work aims to estimate the potential impact of assimilating cloud-affected satellite observations of visible (0.6 µm) and near thermal infrared wavelength (6.2 µm and 7.3 µm) relative to the impact of assimilating radar reflectivity observations. The observation types are evaluated in observing system simulation experiments (OSSE) featuring two cases: isolated and scattered supercells. In the first case, a supercell is triggered by a warm bubble (temperature perturbation) with uncertain location and strength but equal evolution in time. In the second case, random perturbations give rise to numerous supercells scattered throughout the domain, which are in different stages of their lifetime. Observations are simulated using the radiative transfer model RTTOV/MFASIS and assimilated by the Ensemble Adjustment Kalman Filter in the Data Assimilation Research Testbed (DART). The Weather Research and Forecasting (WRF) model at 2-km grid resolution was used for forecasts. 

Results show that the forecast impact is notably different in the two cases. For example, the Fractions Skill Score of precipitation and cloudiness indicates that satellite observations can be as beneficial as three-dimensional radar reflectivity observations in the first case, in which the prior contains no error in the stage of storm development but only in horizontal position and strength. Hence, the vertical structure information contained in three-dimensional radar reflectivity does not seem to add value compared to satellite observations, resulting in a similar impact of both observation types. In the second case, however, three-dimensional radar observations constrain the vertical structure and improve upon forecasts that only use satellite observations.

How to cite: Kugler, L. and Weissmann, M.: Assimilating cloud-affected visible & infrared satellite observations in idealized simulations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9876, https://doi.org/10.5194/egusphere-egu23-9876, 2023.

EGU23-10418 | ECS | Orals | AS1.12

Assessing the added value of Aeolus winds in the ECCC forecast system 

Chih-Chun (Gina) Chou, Paul J. Kushner, and Stéphane Laroche

The European Space Agency (ESA)’s Aeolus mission, launched in August 2018, provides the first global horizontal line-of-sigh (HLOS) wind profile measurements. Many Numerical Weather Prediction (NWP) centres, including ECMWF, DWD, Météo-France, Met-Office and ECCC, have shown that assimilating Aeolus winds improves overall forecast skill, especially in the tropics and data-sparse regions. To better characterize the locations and drivers of improved skill from Aeolus, we use a series of Observing System Experiments (OSEs) with the ECCC Global Deterministic Prediction System (GDPS) covering the period July to September 2019 and December 2019 to March 2020. Three experiments are used: CNTRL, CNTRL+Aeolus, and CNTRL-winds. All the observations assimilated in the GDPS are included in the CNTRL experiment. The Aeolus winds are added in the CNTRL+Aeolus experiment and the operational wind observations are withheld in the CNTRL-wind experiment. The impact of the operational winds and Aeolus are quantified by comparing the forecast error of the CNTRL-winds and CNTRL experiments with the CNTRL and CNTRL+Aeolus experiments. 

As expected, the operational winds improve the tropospheric forecast over the tropics the most, with a normalized forecast error of 8% for the wind field. By adding the Aeolus winds, which account for less than 1% of the observations, the tropospheric forecast further improves by 0.7-0.9% over the tropics and the Arctic, and by 0.5-0.6% over the data-sparse Southern Hemisphere extra-tropics. The added value of Aeolus winds is further highlighted when its impact on forecasts as a function of length scale is investigated, using a spherical harmonic decomposition. The impact is measured as the difference of the 250-hPa kinetic energy forecast error spectra between experiments. The impact of operational winds and Aeolus is dominated by the transient component whose impact is nearly four times greater than the impact on the mean component. The operational winds largely improve the forecast of global scale to intermediate scale in the short-range forecasts. The impact then decreases as forecast range increases. On the other hand, the impact of Aeolus is mostly seen in the intermediate to large scale range with a peak around spherical harmonics of degree 9 (scales about 4000 km), and is the smallest on day 1 and increases until days 4 to 5. This analysis suggests that Aeolus winds provide estimates of the wind state that are valuable and complementary to that provided from current operational winds.

How to cite: Chou, C.-C. (., Kushner, P. J., and Laroche, S.: Assessing the added value of Aeolus winds in the ECCC forecast system, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10418, https://doi.org/10.5194/egusphere-egu23-10418, 2023.

The NASA TROPICS Earth Venture (EVI-3) CubeSat constellation mission will provide nearly all-weather observations of 3-D temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high-value science investigations of tropical cyclones. TROPICS will provide rapid-refresh microwave measurements (median refresh rate of approximately 60 minutes for the baseline mission) over the tropics that can be used to observe the thermodynamics of the troposphere and precipitation structure for storm systems at the mesoscale and synoptic scale over the entire storm lifecycle. The TROPICS constellation mission comprises four 3U CubeSats (5.4 kg each) in two low-Earth orbital planes. Each CubeSat comprises a Blue Canyon Technologies bus and a high-performance radiometer payload to provide temperature profiles using seven channels near the 118.75 GHz oxygen absorption line, water vapor profiles using three channels near the 183 GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel at 205 GHz that is more sensitive to precipitation-sized ice particles. TROPICS spatial resolution, measurement sensitivity, and calibration accuracy and stability are all comparable with current state-of-the-art observing platforms. Two launches for the TROPICS constellation mission are planned for the Summer of 2023. Data will be downlinked to the ground via the KSAT-Lite ground network. NASA's Earth System Science Pathfinder (ESSP) Program Office approved the separate TROPICS Pathfinder mission, which launched on June 30, 2021, in advance of the TROPICS constellation mission as a technology demonstration and risk reduction effort. The TROPICS Pathfinder mission continues to yield excellent data over 18+ months of operation and has provided an opportunity to checkout and optimize all mission elements prior to the primary constellation mission. This presentation will describe the on-orbit results for the successful TROPICS Pathfinder precursor mission and will describe the recent development progress for the TROPICS constellation mission and discuss recent activities to improve the data latency and generation of near-real-time products for forecasting applications.

How to cite: Blackwell, W.: 18+ Months of Tropical Cyclone and Convective Storm Observations with the NASA TROPICS Pathfinder Satellite, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10494, https://doi.org/10.5194/egusphere-egu23-10494, 2023.

EGU23-10561 | ECS | Orals | AS1.12

High-frequency microwave satellite radiances data assimilation using NICAM-LETKF in the OSSE framework 

Rakesh Teja Konduru, Jianyu Liang, and Takemasa Miyoshi

This study investigates the impact of high frequency, such as 3-hourly and 1-hourly satellite microwave radiances, in global atmospheric data assimilation. To understand the impact of such a high-frequency satellite radiances data assimilation, we designed an observing system simulation experiment (OSSE) using the global NICAM-LETKF system at 56 km horizontal resolution. A free run was conducted with the NICAM model and treated as the reference (Nature) for the OSSE experiments. With the NICAM-LETKF system, we conducted five experiments, without data assimilation (NoDA), with only conventional data assimilation but not satellite radiances (NoSat), 6-hourly (6H), 3-hourly (3H), and 1-hourly (1H) satellite clear-sky radiances assimilation. The results showed that satellite microwave radiances assimilation improved the forecast of air temperature and wind over the global ocean compared to NoSat experiments. With the increase in the assimilation frequency of the satellite radiances, the air temperature and winds showed improvement in their representation over the ocean but degraded over land. Over the ocean, microwave radiances assimilation improved the typhoon eyewall wind intensities and its structure for 1H satellite radiances assimilation compared to 6H. These improvements in the wind intensities are prominent during the landfall stage of the typhoon. Forecasting landfall storms' strong winds are essential for disaster prevention and mitigation.

How to cite: Konduru, R. T., Liang, J., and Miyoshi, T.: High-frequency microwave satellite radiances data assimilation using NICAM-LETKF in the OSSE framework, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10561, https://doi.org/10.5194/egusphere-egu23-10561, 2023.

EGU23-10858 | Orals | AS1.12

Parametrizing the evolution of convective updraft vertical velocities 

Ziad Haddad, Sai Prasanth, Sue van den Heever, Peter Marinescu, Sean Freeman, and Derek Posselt

Moisture convergence, latent heat, upper-level divergence all contribute to the genesis and growth of convective updrafts. In order to characterize the morphology of this evolution, and identify its constituent modes, we analyzed a large data set of synthetic updrafts simulated using a convection-resolving differential-equation solver run at high spatial and temporal resolutions (respectively 100 meters and 10 seconds). The analysis started by fitting each simulated updraft with a 6-parameter analytic representation, so that the joint statistics of the 6 parameters and of their evolution in time can be quantified. The first result is that an effective 6-parameter representation does exist and approximates the vertical profiles with a residual relative error whose r.m.s. value is smaller than 10% for 59% of all cases, and smaller than 20% for 89% of all cases. The r.m.s value of the absolute error is smaller than 0.4 m/s for 97% of all cases. Having established the suitability of this approximation, the variability of the 6 parameters for the 2-minute average Wa of a profile W was quantified, as was the variability of the evolution of W – Wa over a two-minute interval. The analysis reveals that 4 scalars suffice to capture the bulk of the variability of the evolution of convective updrafts. The modes (spanning the range of values of these 4 scalars) turn out to be related to the maximum amplitudes of w and to the heights at which they are achieved. This description paves the way toward the characterization of the environmental determinants of updraft evolution and, in turn, the determination of the effects of updraft characteristics on upper-level air density, divergence and the resulting anvil clouds.

How to cite: Haddad, Z., Prasanth, S., van den Heever, S., Marinescu, P., Freeman, S., and Posselt, D.: Parametrizing the evolution of convective updraft vertical velocities, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10858, https://doi.org/10.5194/egusphere-egu23-10858, 2023.

EGU23-11119 | Posters on site | AS1.12

The development of a detailed mineralogical database from satellite remote sensing products, towards an improved representation of dust transport in NWP simulations. 

Nikolaos S. Bartsotas, Olga Sykioti, Christos Spyrou, Kostas C. Douvis, Vassilis Amiridis, Christos Zerefos, and Stavros Solomos

A broad spectrum of environmental processes such as radiation, cloud formation, ocean fertilization and human health are affected from the presence of mineral dust. The transport of dust particles is dictated by the prevailing meteorological conditions as well as the composition and physiochemical properties of the particles themselves. Which, in turn, are bound to the soil mineralogy at the source region.

Numerical weather prediction models can estimate the transport of dust particles, yet a more refined mineralogical categorization can significantly improve the dust transport estimations and  increase preparedness for implications on weather, biogeochemistry and health. This novel mineralogical representation is derived from multi-spectral satellite remote sensing sensors (Sentinel 2A) over a limited area around Lake Chad in Sahara desert by taking into account dust particle characteristics such as size, composition and optical properties. The mineralogy map will be implemented in WRF/CHEM model to improve the accuracy of atmospheric simulations. The final product will be juxtaposed against current state-of-the-art mineralogical products such as the NASA’s Earth Surface Mineral Dust Source Investigation (EMIT) mission. Dust transport simulations will be compared against field measurements from Antikythera PANGEA station in the Mediterranean and ASKOS campaign in the Atlantic Ocean.

How to cite: Bartsotas, N. S., Sykioti, O., Spyrou, C., Douvis, K. C., Amiridis, V., Zerefos, C., and Solomos, S.: The development of a detailed mineralogical database from satellite remote sensing products, towards an improved representation of dust transport in NWP simulations., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11119, https://doi.org/10.5194/egusphere-egu23-11119, 2023.

EGU23-12321 | ECS | Orals | AS1.12

Predictability of moist convection through ensemble-based convective-scale data assimilation 

Masashi Minamide and Derek Posselt

The development of atmospheric deep moist convection has been a challenging topic for numerical weather prediction, due to its chaotic nature of the development with multi-scale physical interactions. We recently found that greater than 20-km scale (as commonly known as meso-α (2000-200 km) and meso-β (200-20 km) scales) initial features helped to constrain the general location of convective activity with a few hours of lead time, but meso-γ (20-2 km) or even smaller scale features with less than 30-minute lead time were identified to be essential for capturing the spatiotemporal features of individual convection. To examine the potentials of ensemble-based data assimilation in capturing the individual convective development, as well as the subsequent development of severe weather events, we have conducted large ensemble convection-permitting data assimilation experiments with all-sky infrared satellite radiances from the latest-generation geostationary satellites. We found that the greater number of ensembles more effectively suppressed the spurious correlation for convective-scale data assimilation. However, the exact signals of convective development were not clearly captured in covariances even with thousands of ensemble members. These results suggest the potential limitation of the traditional “Eulerian” (i.e. physical grid-based) ensemble approach in convective-scale data assimilation.

How to cite: Minamide, M. and Posselt, D.: Predictability of moist convection through ensemble-based convective-scale data assimilation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12321, https://doi.org/10.5194/egusphere-egu23-12321, 2023.

EGU23-13441 | Posters on site | AS1.12

Impact study of Aeolus/ALADIN bias correction in the KIM data assimilation system 

Hyemin Shin, Jeon-Ho Kang, and In-Hyuk Kwon

The Aeolus Atmospheric Laser Doppler Instrument (ALADIN) sensor onboard Aeolus provides the Horizontal Line Of Sight (HLOS) wind. The satellite-based HLOS wind profile data is significant because it complements the southern hemisphere, tropical and polar regions where existing wind observations are insufficient. The KMA also assimilates the HLOS wind for the operational data assimilation (DA) system since 2021, showing slightly positive impacts on average in the analysis field. However, it was confirmed that the impacts were relatively lower than those of the leading centers and limited due to systematic or random errors in the observation. 
In this study, we tested if we could enhance the positive impacts by applying the bias correction (BC) method to the HLOS wind observation. To this end, the Total Least Squares (TLS) were tested to conduct on the KIM Package for Observation Processing (KPOP) system, which is a system to provide well-qualified observations to the DA system. It shows better statistics in the mean and standard deviation of the first guess departures (O-B) by applying the TLS BC method with -0.19 m/s and 3.30 m/s from -0.44 m/s and 6.22 m/s, relatively. Detailed impacts on the analysis and forecast fields from the cycling experiments will be presented.

How to cite: Shin, H., Kang, J.-H., and Kwon, I.-H.: Impact study of Aeolus/ALADIN bias correction in the KIM data assimilation system, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13441, https://doi.org/10.5194/egusphere-egu23-13441, 2023.

Convection-permitting data assimilation requires observations with high spatial density and high temporal frequency to provide information on appropriate scales for high resolution forecasting. Those observation types (e.g., geostationary satellite data) were found to exhibit strong spatial error correlations. Explicitly introducing correlated error statistics in the assimilation may increase the computational complexity and parallel communication costs of the matrix-vector multiplications with the observation precision matrices (the inverse observation error covariance matrices). Therefore, without suitable approaches we cannot take full advantage of the new observation uncertainty estimates. In this work, we present a new numerical approximation method, called the local SVD-FMM, which is developed based on a particular type of the fast multipole method (FMM) using a singular value decomposition (SVD), and a domain localization approach. The basic idea of the local SVD-FMM is to divide the observation domain into boxes of (approximately) equal size and then separates the calculations of the matrix-vector products according to the domain partition. These calculations can be done in parallel with very low communication overheads. Moreover, the local SVD-FMM is easy to implement and applicable to a wide variety of the precision matrices. We applied the local SVD-FMM in a simple variational data assimilation system and found that the computational cost of the variational minimisation was dramatically reduced while preserving the accuracy of the analysis. This new method has the potential to be used as an efficient technique for practical data assimilation applications where a large volume of observations with mutual error correlations needs to be assimilated in a short period of time.

How to cite: Hu, G. and Dance, S. L.: A Novel Numerical Approximation Method for Computations with Spatially Correlated Observation Error Statistics in Data Assimilation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14476, https://doi.org/10.5194/egusphere-egu23-14476, 2023.

EGU23-17558 | ECS | Posters on site | AS1.12

Toward the Application of Nonlinear Ensemble Data Assimilation Methods to Convective-Scale Parameter Estimation 

Hristo Georgiev Chipilski and Derek Posselt

Recent work has demonstrated that convective-scale model parameters, such as those related to cloud microphysical schemes, are nonlinearly related to dynamic/thermodynamic variables in forecasts and observations. This leads to errors when data assimilation (DA) schemes based on linear-Gaussian assumptions are used to estimate the uncertain model parameters. Nonlinear modifications to the standard ensemble Kalman filter (EnKF) have been shown to perform better for systems governed by convective dynamics, and recent algorithms leveraging advances in AI/ML appear to be especially promising.

 

In this talk, we will present results from previous experiments that demonstrate how and why linear EnKF methods fall short for the challenging task of nonlinear parameter estimation. We will discuss the potential improvements that may result from a new class of ensemble DA algorithms leveraging the powerful framework of latent Gaussian models. In particular, two generalizations of the classical EnKF will be described – one which exploits the special mathematical properties of invertible neural networks (ECTF) and another one based on ideas from measure transport in the context of two-step ensemble filtering (TGA-EnKF). The advantages of these new methods will be illustrated through idealized DA experiments, which will then motivate further discussion on their applicability to convective-scale DA problems.

How to cite: Chipilski, H. G. and Posselt, D.: Toward the Application of Nonlinear Ensemble Data Assimilation Methods to Convective-Scale Parameter Estimation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17558, https://doi.org/10.5194/egusphere-egu23-17558, 2023.

EGU23-10 | ECS | Posters on site | AS1.13

Tropical cyclone Vayu under climate change scenario RCP 8.5 

Pubali Mukherjee and Balaji Ramakrishnan

 

The Northern Indian Ocean has witnessed the genesis of several devastating cyclones over the years due to the typical warm climate. The effect of climate change on these cyclones is an essential topic of research owing to the socio-economic impacts of these cyclones on the coastlines. Climate change is expected to influence the various synoptic parameters of these storms, like translational speed, intensification, frequency, etc. Most of the studies about the impact of climate change on cyclones have been done related to the Atlantic and Pacific Oceans; very few have explored the storms of the Indian Ocean in this context. Considering this context, the present study attempts to understand the track, intensity, and synoptic parameters of Tropical cyclone Vayu-June 2019 under the climate change scenario of RCP 8.5 with the Community Earth Systems Model, CESM data simulated with GPU-based WRF-ARW model. The model is simulated at a 9km single domain with a selected set of physical settings based on the previous studies on the cyclones of the Northern Indian Ocean. The track and intensity of the simulated storm are compared with the present-day hurricane Vayu from the IMD best track estimates.

Interestingly under RCP 8.5, unlike the present-day cyclone Vayu, under RCP 8.5, Vayu would have made landfall along the west coast of India with a sustained wind speed of ~ 15 m/s w. At the same time, he presents a scenario in Vayu weakened over the ocean due to several interactions with the mid-latitude westerlies. The results indicate a considerable change in the future thermodynamics under which Vayu sustained the intensity till landfall. Under RCP 8.5 simulations, the initial posting error is high; other than that, the coming cyclone Vayu seemed to follow a similar track as the present-day storm except for the landfall.

Regarding wind speed intensity, Vayu under RCP 8.5 shows equal wind intensity as that of the present day, with similar underestimation at the mature stage of the storm. The initial results of this study indicate that changes in large-scale thermodynamics in future warming scenarios can influence the modulations in track and intensity of a very severe cyclonic storm like Vayu. Such results highlight the importance of closely monitoring Arabian Sea cyclones to understand the impending disaster mitigations under probable warming scenarios.

 

 

How to cite: Mukherjee, P. and Ramakrishnan, B.: Tropical cyclone Vayu under climate change scenario RCP 8.5, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10, https://doi.org/10.5194/egusphere-egu23-10, 2023.

EGU23-44 | ECS | Posters on site | AS1.13

Influence of MJO on cyclone activity in the north Indian Ocean and Western North Pacific 

Rahul Raghudhas, Jayanarayanan Kuttippurath, Arun Chakraborty, and Akhila Rajeev

We investigate the changes in cyclogenesis and tropical cyclone (TC) activity by the warped life cycle of MJO triggered by the two-fold expansion of the warm pool that occurred during the period of the past 40 years (1979-2019). To study the impact of MJO on TC genesis and activity, we have used the genesis potential index (GPI), accumulated cyclonic energy (ACE) and frequency of cyclones in the active, moderately active and non-active periods of MJO in the North Indian Ocean (NIO) and Western North Pacific (WNP). We find an inverse characteristic of anomalies of relative humidity, vertical wind shear, absolute vorticity, potential intensity, GPI and sea surface temperature over the tropical region between active and non-active years of MJO (1979-2019). High TC activity is experienced during the moderately active years of MJO over the Bay of Bengal (BoB) and WNP. The impact of MJO on TC activity over WNP from October to December (OND) is not particularly dominant during the active years. The genesis of TCs over the Arabian Sea (AS) have also increased during the active years of MJO; indicating that the impact of MJO is increasing over AS. In addition, stalling of eastward propagation of MJO is noticed over the Maritime Continent (MC) during the active and moderately active MJO years. After phase 5, a strong decline in the trend of the phase duration over WNP is noticed, which can be attributed to the reduced TC genesis and activity over WNP during the MJO active years. Reduced MJO activity during OND over WNP, along with lower absolute vorticity and vertical velocity, resulted in lower TC activity and genesis. Our analysis reveals the basin dependency of TC activity and genesis over AS, BoB and WNP due to the stalled propagation of MJO over MC by the extended Indo-Pacific warm pool driven by anthropogenic activities.

How to cite: Raghudhas, R., Kuttippurath, J., Chakraborty, A., and Rajeev, A.: Influence of MJO on cyclone activity in the north Indian Ocean and Western North Pacific, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-44, https://doi.org/10.5194/egusphere-egu23-44, 2023.

EGU23-75 | ECS | Orals | AS1.13

Kelvin Waves and Tropical Cyclogenesis: Connections to Convection and Moisture 

Quinton Lawton and Sharanya Majumdar

In recent years, research has illuminated a distinct relationship between Convectively Coupled Kelvin Waves (CCKWs) and tropical cyclone (TC) formation. In basins that support TCs, there is a pronounced increase in the number of TC genesis events 1-3 days following the passage of a CCKW’s convectively-active phase. It has been hypothesized that this lagged relationship could be the result of the modification of environmental and kinematic factors by the CCKW. However, little work has been done to try to connect these environmental changes to the processes involved in TC genesis. Observational and modeling studies alike have indicated that the development of TCs may be intimately tied to convective-radiative feedbacks and pre-moistening of the atmosphere. How might CCKWs be impacting these processes?

To investigate this, we leverage a 39-year database of African Easterly Waves (AEWs) and associated TC genesis events in the Atlantic Ocean basin from 1981 to 2019. Environmental composites of ERA5 reanalysis and satellite data show an increase in column specific humidity and convective coverage beginning two days prior to TC genesis. This supports previous hypotheses of AEW trough preconditioning. A moist static energy (MSE) variance budget surrounding AEWs is also calculated. This analysis indicates that the dominant source of MSE variance during TC genesis – a proxy for convective aggregation – are longwave-radiative feedbacks, further solidifying the role of convection-related feedbacks in TC development.

Environmental fields around developing AEWs are then composited relative to passing CCKWs. Convectively-active CCKWs temporarily promote an increase in convection, specific humidity, and relative vorticity around AEWs. AEW-CCKW passages are shown to be quite common, with 76% of all developing AEWs passing at least one CCKW in their lifetime. We also compare AEW-CCKW passages that result in TC genesis versus those that do not. The primary discriminator between these two outcomes appears to be convective coverage and diabatic heating at the time of CCKW passage. There is also a pronounced increase in the longwave-radiative feedback term following the CCKW passage for cases that result in TC genesis.

While it is hard to separate the simultaneous effects of a multi-day TC genesis process from that of passing CCKWs, this analysis provides at least circumstantial evidence that CCKW-related modifications to convection and humidity could play an indirect role in preconditioning the AEW and a direct role in strengthening radiative-convective feedbacks. These results also motivate investigation of AEW-CCKW interactions in numerical simulations, which may be more suited to investigate cross-scale interactions and better determine causality.

How to cite: Lawton, Q. and Majumdar, S.: Kelvin Waves and Tropical Cyclogenesis: Connections to Convection and Moisture, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-75, https://doi.org/10.5194/egusphere-egu23-75, 2023.

EGU23-127 | ECS | Posters on site | AS1.13

Dynamic circulations and Windward Flow over Reunion Island 

samira El Gdachi, Pierre Tulet, and Anne Réchou

Numerical Weather Prediction models still have difficulties to predict local-scale phenomena, such as thermal breezes circulation.  They are local driven wind systems that form over coastal zones (sea/land breeze) or mountainous terrain (slope/valley breeze), produced by the buoyancy effects associated with the diurnal cycle of heating and cooling of the lower atmospheric layers (Zardi et Whiteman, 2013). These circulations can drive abrupt changes that generate localized wind gusts, extreme precipitation, air pollution episodes in the lower layers, or sea state perturbations. 

The characteristics of the volcanic and tropical island of Reunion Island  (Indian Ocean, 21°07’S, 55°32’E) offer an exceptional natural field of investigation for these process studies. The meteorological circulations on Reunion Island have been extensively studied by Lesouëf et al. (2010), Durand et al. (2014), Tulet et al. (2017), Foucart et al. (2018), and Réchou et al. (2019). These works show that the island is affected by a regime of southeast trade winds, which is intense in winter (June-August) and moderate to weak in summer (December to February). This weather regime is the cause of intense winds on the southwest and northeast edges of the island and a branch of northwesterly leeward circulation forcing in the northwest of the island (Maïdo area). In this region, thermal circulations are added to this regional circulation. This return loop occurs almost daily in this part of the island in the boundary layer. The oceanic air masses are advected on the slopes of the Maïdo area by the sea and valley breezes. This convection on the mountain slopes causes an almost daily formation of clouds, which are generally weakly developed vertically and generally with low water content. 

An intensive measurement campaign BIOMAÏDO (Bio-physicochemistry of tropical clouds at Maïdo) took place from 11 March to April 7, 2019, at Réunion Island, in order to study the chemical and biological composition of the air mass, the formation processes of secondary organic matter in heterogeneous environments, the dynamics and the evolution of the boundary layer, and the macro and micro-physical properties of clouds.  

In this study, we detail and analyze the dynamics circulations using the observations of the campaign and compare them to a high-resolution (100m horizontal resolution) numerical simulation with the Meso-NH model. Such a model turned during the selected days in which a dynamical connection between the sites was found (Rocco et al., 2022).

The preliminary results have shown that a vertical resolution smaller than a few meters (~1m)  is needed to capture the katabatic flows and the structure of the valley boundary layer, these circulations have an abrupt variation (~1 hour) and the anabatic flow takes nearly 1 h to arrive to the top of the mountain. 

The temporal and spatial structure of this breezes regimes is analyzed with the use of the wet bulb potential temperature (Davies-Jones., 2007), and the turbulence kinetic energy budgets determined by the numerical model;  this study aims to quantify which processes have the most important role during the diurnal breeze evolution. 

How to cite: El Gdachi, S., Tulet, P., and Réchou, A.: Dynamic circulations and Windward Flow over Reunion Island, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-127, https://doi.org/10.5194/egusphere-egu23-127, 2023.

In this study we have conducted a survey of Mixed Rossby-Gravity (MRG) wave events in the upper troposphere and quantified their association with the intrusions of extratropical disturbances for the period 1979-2019. MRG events are identified by projecting the equatorial meridional winds at 200 hPa onto the meridional structure of theoretical MRG waves2390 MRG events are identified and majority (61%) of them occurred during May-October months, and 65% of the total MRG events occurred over the central-east Pacific and Atlantic Ocean domains. Not only the frequency of occurrence but also the amplitude, wavenumber and trapping scale of the MRG events are found to exhibit a clear seasonality. MRG events associated with intrusions of extratropical disturbances are identified as when the potential vorticity on the 350K isentropic surface at 15° latitude exceeded 1 PVU in the vicinity of the MRG events. We find that 37% of the MRG events are intrusion MRG events and a large majority (88%) of such events occurred over the central-east Pacific and Atlantic Ocean domains. It is also noteworthy that nearly 70% of such intrusions occurred in the winter Hemisphere where the westerly wind ducts are well developed. Over the central-east Pacific during Northern Hemispheric (NH) winter, it is observed that the amplitude of intrusion MRG events are larger and have a larger meridional extent compared to non-intrusion MRG events. They also exhibit a similar spatial scale as the extratropical disturbances implying that resonant interactions may be a primary mechanism for the genesis of MRG events. During NH summer, on the other hand, MRG events are primarily triggered by convective processes and the extratropical disturbances may be instrumental in amplifying their amplitude. 

How to cite: Keshri, S. and Ettammal, S.: A survey of Mixed Rossby-Gravity waves and quantification of their association with extratropical disturbances., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-845, https://doi.org/10.5194/egusphere-egu23-845, 2023.

EGU23-873 | ECS | Orals | AS1.13

Role of land in the unusual track of cyclones Gulab and Shaheen 

Ashish Navale and Karthikeyan Lanka

Cyclones lead to heavy precipitation in a very short period causing severe damage to life and socio-economy along its track. Globally, it is projected that there will be an increase in extreme weather events, which will lead to flooding in places like the Indian subcontinent because of irregular monsoon patterns and cyclonic storms. Extremely rare climatic events occasionally display unexpected phenomena, and cyclone Gulab and Shaheen's formation was one such extraordinary occurrence. Cyclone Gulab developed over the Bay of Bengal on 25th September 2021. The cyclone moved westward and made landfall on the east coast of India in the state of Andhra Pradesh on 26th September. Cyclone Shaheen formed in the North East Arabian sea from the remnants of cyclone Gulab. Although these cyclones were not particularly powerful compared to others in this region, it followed a very unusual track. As the cyclone entered the land, it started losing energy but continued to move across the Indian peninsula as a low-pressure system before emerging into the North Eastern Arabian Sea. Favorable atmospheric and oceanic factors for cyclogenesis in this region caused the system to reintensify on 1st October 2021. The system continued to move westward steadily for two days and intensified into a severe cyclonic storm, Shaheen. On 3rd October, cyclone Shaheen made landfall on the Northeastern coast of Oman and made history as the first severe cyclone to strike the Northern coast of Oman for one and a half-century.

After the landfall of cyclone Gulab, the low-pressure system sustained over land and eventually developed into cyclone Shaheen, suggesting that land was a significant source of moisture. Thus, in this study, we quantified the moisture contributed by land in the form of evapotranspiration to the cyclones Gulab and Shaheen. We used an Eulerian water tracking technique incorporated in the state-of-the-art Weather Research and Forecasting (WRF) model to track moisture. The model allows us to specify a source region of moisture originating as evapotranspiration, which can be tracked throughout the atmosphere. This moisture is tracked till it results in precipitation or advects out of the domain. The precipitation associated with this tracked moisture is termed recycled precipitation. ERA5, a fifth-generation ECMWF atmospheric reanalysis data, is used to set up the model's initial and boundary conditions. The microphysical, cumulus, and planetary boundary layer schemes used are WSM6, Kain-Fritsch, and YSU, respectively. Eulerian water tracking being one of the most accurate tracking techniques, will enable us to get accurate contributions of different regions and land use to the cyclonic system. In this study, we mainly focus on the contributions of moisture from the forested areas and understanding the role of antecedent soil moisture in sustaining the low-pressure system across the Indian landmass. Our results showed that Northeast India and Myanmar's dense vegetated regions contributed copious amounts of moisture to the cyclonic systems in the Bay of Bengal.

How to cite: Navale, A. and Lanka, K.: Role of land in the unusual track of cyclones Gulab and Shaheen, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-873, https://doi.org/10.5194/egusphere-egu23-873, 2023.

EGU23-923 | ECS | Orals | AS1.13

Uncovering the Intrinsic Intensity-Size Relationship of Tropical Cyclones 

Jie Sun, Ming Cai, Guosheng Liu, Ruikai Yan, and Da-Lin Zhang

The central theme of this study is to explore if and how the intensity of a tropical cyclone (TC) is related to its size. This subject has puzzled atmospheric scientists since the work of Depperman (1947) but the existence of this relationship still remains elusive. The improved understanding of the intensity-size relationship of TCs will help coastal communities to prepare for the maximum potential damage as both the intensity and size have important impacts on wind damages, storm surges, and flooding. This study considers 33 years (1988–2020) of TC records of maximum surface winds and radii of maximum and gale-force winds over the North Atlantic Basin derived from the Extended Best Track Dataset. Analysis of these TC records reveals a robust positive correlation between loss of earth and relative angular momentum. This finding together with the inspiration from the seminal work of Emanuel and his collaborators leads us to combine absolute angular momentum and its frictional loss as a radially invariant quantity, referred to as “effective absolute angular momentum” (eAAM), for radial profiles of TC surface winds. It is demonstrated that the eAAM model can reproduce the observed complex intensity-size relationship of TCs, which can be further reduced to a quasi-linear one after factoring out the angular momentum loss and the radius of maximum surface winds. The findings of this study would not only advance our understanding of the complex TC intensity-size relation, but also allow for operational assessments of TC severity and potential damage just using its outer wind information.

How to cite: Sun, J., Cai, M., Liu, G., Yan, R., and Zhang, D.-L.: Uncovering the Intrinsic Intensity-Size Relationship of Tropical Cyclones, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-923, https://doi.org/10.5194/egusphere-egu23-923, 2023.

This study examines the role of tropical dynamics in the formation of global tropical cyclone (TC) clusters. Using theoretical analyses and idealized simulations, it is found that global TC clusters can be produced by the internal dynamics of the tropical atmosphere, even in the absence of all landmass surface and zonal sea surface temperature (SST) anomalies. Theoretical analyses of a two-dimensional InterTropical Convergence Zone (ITCZ) model reveal indeed some large-scale stationary waves whose zonal and meridional structures could support the formation of TC clusters at the global scale. Additional idealized simulations using the Weather Research and Forecasting (WRF) model confirm these results for a range of experiments. Specifically, the examination of two common tropical wave types including the equatorial Rossby (ER) wave and the equatorial Kelvin (EK) wave shows that ER waves could develop a stationary structure for a range of zonal wavenumbers $m\in[5-11]$, while EK waves do not. This modeling result is consistent with the ITCZ analytical model and suggests that large-scale ER waves could support stationary "hot spots" for global TC formation without any zonal SST anomalies. The findings in this study offer different insights into the importance of tropical waves in producing global TC clusters beyond the traditional explanation based on zonal SST variability.   

How to cite: Kieu, C. and Vu, T.-A.: On the Roles of Tropical Waves in the Formation of Global Tropical Cyclone Clusters, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1258, https://doi.org/10.5194/egusphere-egu23-1258, 2023.

Rapid intensification/weakening (RI/RW) refers to a significant increase/decrease in tropical cyclone (TC) intensity over a short period of time. A TC can also undergo multiple RI/RW events during its lifetime, and these events pose a significant challenge for forecasting TC activity. In fact, RW is one major source of large intensity forecasting errors as well as RI. These processes can be associated to particular large-scale conditions, both in terms of atmospheric drivers - such as vertical wind shear or dry air intrusion - and oceanic drivers - such as sea surface temperature (SST) gradient.

In this work we aim to verify the ability of the new CMCC-CM3 model (a preliminary version of the General Circulation Model that will take part to the 7th Coupled Model Intercomparison Project - CMIP7 effort) in representing Tropical Cyclone activity with a particular focus on RI and RW. The simulations used in this work have been provided within the EU project BlueAdapt at a 25km horizontal resolution in atmosphere and ocean components, ensuring the representation of realistic TCs both in terms of spatial variability and intensity. Less agreement is found in representing RI/RW timing and duration, but better results are obtained, compared to the previous version of the model CMCC-CM2. The role of the ocean in determining RI and RW is also investigated.

How to cite: Scoccimarro, E. and Peano, D.: Rapid Intensification and Rapid Weakening of Tropical Cyclones, as represented by the CMCC-CM3 Climate Model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1541, https://doi.org/10.5194/egusphere-egu23-1541, 2023.

EGU23-1692 | Orals | AS1.13 | Highlight

The slowdown tends to be greater for stronger tropical cyclones 

Yuan Sun, Wei Zhong, Hongrang He, and Yao Yao

Understanding the impact of climate change on tropical cyclones (TCs) has become a hot topic. The slowdown of TC translation speed contributes greatly to the locally accumulated TC damage. While the recent observational evidence shows that TC translation speed has decreased globally by 10% since the mid-twentieth century, the robustness of the trend is questioned by other studies as effects of changes in observational capability can strongly affect the global trend. Moreover, none of the published studies considered dependence of TC slowdown on TC intensity. This is the caveat of these analyses as the effect of TC slowdown is closely related to TC intensity. Here, we investigate the relationship between TC translation speed trend and TC intensity, and reveal possible reasons for the trend. We show that the global slowing trend without weak TC moments (≤ 17 m s-1) is about double of that with weak TC moments in a recent study. This is because the slowing trend is dominated by strong TCs’ trend. Stronger (weaker) TCs tend to be controlled more by upper-level (lower-level) steering flow, and the calculated trend of upper-level steering flow is much larger than that of lower-level steering flow. This may be an important reason for the large difference between the slowing trend without weak TC moments and that with weak TC moments. Furthermore, the changes of TC tracks (including inter-basin trend and latitudinal shift), which are partly attributed to data inhomogeneity, make a much larger contribution to the slowing trend, compared with the weakening of tropical circulation, which is related to anthropogenic warming.

How to cite: Sun, Y., Zhong, W., He, H., and Yao, Y.: The slowdown tends to be greater for stronger tropical cyclones, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1692, https://doi.org/10.5194/egusphere-egu23-1692, 2023.

EGU23-1799 | ECS | Orals | AS1.13

Role of subtropical Rossby waves in governing the track of cyclones in the Bay of Bengal 

Vineet Singh, Roxy Mathew Koll, and Medha Deshpande

The cyclones during November in the Bay of Bengal follow two distinct tracks. Analysis for the period 1982–2019 shows that some cyclones move
west-northwestward and make landfall at the Odisha, Andhra Pradesh or Tamil Nadu coast of India, or the Sri Lanka coast, while others move north-northeastwards and make landfall at the West Bengal, Bangladesh or Myanmar coast. Our analysis shows there is a significant difference in the steering winds governing these two different cyclone tracks. The north-northeastward moving cyclones are associated with an anomalous upper-level cyclonic circulation over India which is part of a subtropical Rossby wave train triggered by an anomalous upper-level convergence over the Mediterranean region. This wave train propagates along the subtropical westerly jet from the east Atlantic/Mediterranean region and reaches the Indian subcontinent in 4 days. It induces an anomalous cyclonic circulation over the Indian landmass and provides south-to-north and west-to-east steering over the Bay of Bengal, causing the cyclones to move in a north-northeastward direction. On the other hand, for west-northwestward moving cyclones, there is no Rossby wave intrusion over the Indian subcontinent, hence the cyclones move in a west-northwestward direction assisted by the beta effect and climatological winds which are from east to west over the south and central Bay of Bengal. This shows that the track of cyclones in the north Indian Ocean can be modulated by atmospheric changes in the extratropics and can act as a precursor for the prediction of the track of cyclones in this region.

How to cite: Singh, V., Mathew Koll, R., and Deshpande, M.: Role of subtropical Rossby waves in governing the track of cyclones in the Bay of Bengal, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1799, https://doi.org/10.5194/egusphere-egu23-1799, 2023.

EGU23-2007 | ECS | Orals | AS1.13

Mid-Level Dry Air Intrusions over the southern Maritime Continent 

Ashar Aslam, Juliane Schwendike, Simon Peatman, Cathryn Birch, Massimo Bollasina, and Paul Barrett

Patterns in extreme precipitation across the Maritime Continent in Southeast Asia are known to be modulated by many processes, from large-scale modes of variability such as the Madden-Julian Oscillation and planetary waves, to finer-scale processes such as the diurnal cycle. Transient mid-level dry air intrusions are an example of a process not extensively studied over the Maritime Continent, which has the potential to influence rainfall patterns.  

Through Lagrangian trajectory and event composite analyses, we use a humidity metric which identifies mid-level dry air intrusions. These intrusions originate from upper-level disturbances along the subtropical jet. Mid-level cyclonic circulation anomalies northwest of Australia from December-February (DJF) intensify westerlies in the southern Maritime Continent, advecting dry air eastward. In contrast, mid-level anticyclonic circulation anomalies northwest of Australia from June-August (JJA) intensify southern Maritime Continent easterlies, advecting dry air westward. The resultant transport direction of associated air parcels is also dependent on the seasonal low-level monsoon circulation, and potentially convective entrainment.  

Dry air intrusions are found to be important in influencing low-level wind circulations and rainfall patterns in the southern Maritime Continent. Dry air suppresses rainfall over seas near to the southern Maritime Continent in both seasons. Further suppression matches intrusions trajectories, such as over southern Maritime Continent islands in DJF, and the Indian Ocean in JJA. In both seasons, there is enhanced rainfall to the east of the intrusion, where there is moist return flow to the extratropics.  

How to cite: Aslam, A., Schwendike, J., Peatman, S., Birch, C., Bollasina, M., and Barrett, P.: Mid-Level Dry Air Intrusions over the southern Maritime Continent, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2007, https://doi.org/10.5194/egusphere-egu23-2007, 2023.

Convectively coupled equatorial Rossby waves (CCERWs) are an intrinsic part of the spectrum of tropical weather systems, and can bring extreme precipitation to tropical locations. They are usually interpreted as modified versions of the theoretical dry equatorial Rossby wave solutions of the shallow water equations. However, the structure and dynamics of CCERWs are rather different to their theoretical cousins. Here, a vorticity budget is presented for both theoretical equatorial Rossby waves and for CCERWs (based on reanalysis data). The different strengths of the vorticity budget terms between the theoretical waves and CCERWs gives insights into CCERW propagation and growth mechanisms, and provides a focus and testbed for future model and forecast improvements.

How to cite: Matthews, A.: Vorticity budget of convectively coupled equatorial Rossby waves: propagation and growth mechanisms, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2020, https://doi.org/10.5194/egusphere-egu23-2020, 2023.

EGU23-2857 | Orals | AS1.13

Organization of Tropical East Pacific Convection Field Project 

Zeljka Stone, David Raymond, and Stipo Sentic

The OTREC (Organization of Tropical East Pacific Convection) field project took place from August 5 to October 3, 2019. The operational center was in Liberia, Costa Rica. During OTREC, we performed 127 research flight hours in the area of the Eastern Pacific and southwest Caribbean. We deployed 648 dropsondes in a grid to evaluate mesoscale thermodynamic and vorticity budges. We also used the Hiaper Cloud Radar to determine the characteristics of cloud populations. Both of these tools were deployed from the NSF/NCAR Gulfstream V aircraft.

The Eastern Pacific has a strong cross-equatorial gradient in sea surface temperature. The southwest Caribbean exhibits uniform ocean temperatures. The two regions together provide a broad range of atmospheric conditions and a great deal of diversity in convective behavior.

The main goal of the project was to study convection in diverse environments to improve global weather and climate models. In this talk I will present an overview of OTREC, the highlights of the field project and the results that OTREC has yielded that include the thermodynamics of the environment and the vertical mass flux profiles. In particular, column relative humidity, low to mid-tropospheric moist convective instability, and convective inhibition are shown to be useful predictors for moisture convergence, and hence rainfall.

How to cite: Stone, Z., Raymond, D., and Sentic, S.: Organization of Tropical East Pacific Convection Field Project, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2857, https://doi.org/10.5194/egusphere-egu23-2857, 2023.

EGU23-3335 | ECS | Orals | AS1.13

Tropical Cyclones in High-Resolution Global Climate Simulations with the IPSL Model 

Stella Bourdin, Sébastien Fromang, Arnaud Caubel, Josefine Ghattas, Yann Meurdesoif, and Thomas Dubos

The availability of a new icosahedral dynamical core (DYNAMICO) for the IPSL model was the opportunity to participate in the HighResMIP protocol. We present the results of four historical 1950-2015 atmosphere-only (forced SST) simulations at horizontal resolutions equal to 200, 100, 50, and 25 km. We compare them with two simulations that use the same configuration but were performed with the previous longitude-latitude dynamical core at 250 and 75km horizontal resolutions.

We use these simulations to perform the first assessment of Tropical Cyclones (TC) in the IPSL model. This evaluation is done across four resolutions, gathering methodologies from recent literature (Roberts et al., 2020 a&b; Moon et al., 2020; Chavas et al., 2017; Camargo et al., 2020; Bourdin et al., 2022).
We first show that the results obtained with DYNAMICO compare favorably with the previous dynamical core of the IPSL model.
Then, we analyze how increasing horizontal resolution from 200km to 50km improves the TC climatology. Our results align with the current expectation that frequency and geographical distribution get closer to the observation but that the intensity is still significantly under-resolved.
In the highest-resolution simulation TC activity in the North Atlantic basin is well represented in terms of geographical distribution and inter-annual variability. However, regional biases remain, especially in the Western North Pacific, where there is a significant deficit in TC number and a shift of activity towards the east of the basin. These regional biases are robust with resolution but are not associated with any obvious climatological bias in the simulations.
Finally, we study composites, TC size, and life cycles to document the physics of the model's TCs. They show that the model simulates realistic TC structures with primary and secondary circulations, an eyewall, and a warm core. TC size diminishes with resolution and less so with intensity.

We conclude that the IPSL model is able to simulate a realistic climatology of Tropical Cyclones at 25 km horizontal resolution, with maximum intensities limited by the current maximum resolution.

How to cite: Bourdin, S., Fromang, S., Caubel, A., Ghattas, J., Meurdesoif, Y., and Dubos, T.: Tropical Cyclones in High-Resolution Global Climate Simulations with the IPSL Model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3335, https://doi.org/10.5194/egusphere-egu23-3335, 2023.

Tropical cyclone activity usually negatively affects people’s lives in coastal countries, especially in East-Asia including China. In order to reduce the effect, various approaches are utilized to study tropical cyclones. The Murray and Simmonds Cyclone Tracking algorithm, which has been mainly used in tracking extratropical cyclones, is, for the first time, applied to detect and track tropical cyclones in the West-Pacific based on mean sea level pressure data. Since this algorithm only requires one variable field as input, if it would achieve similar performance as other more complex tracking algorithms, this could be a good algorithm to use for construction of large physically consistent tropical cyclone event sets.

In the presentation, a preliminary evaluation on the performance of the Murray and Simmonds Cyclone Tracking algorithm on tracking tropical cyclones in West-Pacific, using ERA5 and IBTrACS, will be presented. The sensitivity of the performance of the algorithm on different parameter settings will also be discussed. Furthermore, the added value of combining the Murray and Simmonds Cyclone Tracking algorithm and an impact-based storm tracking algorithm, WiTRACK, from the disaster risk reduction and mitigation perspective will also be demonstrated.

How to cite: Zhang, X., Leckebusch, G. C., and Ng, K. S.: Objective Tracking of Tropical Cyclones and their Impact on Relevant Wind Fields in the West-Pacific for Construction of Physically Consistent Event Sets, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3390, https://doi.org/10.5194/egusphere-egu23-3390, 2023.

EGU23-3628 | Orals | AS1.13 | Highlight

Forced trends in the tropical Pacific and global tropical cyclones: An investigation using a statistical-dynamical downscaling model 

Chia-Ying Lee, Suzana Camargo, Adam Sobel, Richard Seager, Boniface Fosu, and Kevin Reed

The response of tropical cyclone activity to anthropogenic radiative forcing remains uncertain, with even the direction of the change uncertain in some respects (e.g., TC frequency), both globally and regionally. One important source of uncertainties is the Pacific zonal SST gradient. At the interannual time scale, this SST gradient, through the El Niño Southern Oscillation, is known to strongly influence global TC activity. Global climate models in CMIP5/6 generations project this SST gradient to weaken and lead to a more El Niño-like mean state in the future. Observations over the past several decades, however, show a strengthening of the SST gradient and thus a more La Niña-like mean state. While the observed strengthening of the SST gradient may be due to natural variability or merely an observational issue, some recent studies have marshalled evidence, backed up with modeling, to argue that the projected weakening is erroneous and a consequence of a common climatological cold tongue bias that has persisted in a few generations of global climate models. If the above argument is correct, at the transient forced response of Pacific SST over the upcoming decades will be towards a La Niña-like mean state, in contrast to the climate models. This means that the projected trends in TC activity from current state-of-the-art global climate models may be incorrect in some basins. In this presentation, we will report an initial investigation of the above problem using synthetic TCs from the Columbia tropical cyclone HAZard model (CHAZ) downscaled from CMIP6 models. Although all show El Niño-like forced responses, we will group the CMIP6 models/members based on the magnitudes of their climatological cold tongue biases, their historical trends of the zonal and meridional SST gradients, and the correlation between their trends and the observed one. For each stratified group, we will then evaluate SST gradient projections and how these projections affect the large-scale atmospheric and oceanic environment conditions that are important to TC activity and thus influence the forced trends in the CHAZ-CMIP6 downscaled TCs.  This work will inform on how much a potential model bias towards the wrong sign of the tropical Pacific zonal SST gradient change matters for projections of global TCs.

How to cite: Lee, C.-Y., Camargo, S., Sobel, A., Seager, R., Fosu, B., and Reed, K.: Forced trends in the tropical Pacific and global tropical cyclones: An investigation using a statistical-dynamical downscaling model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3628, https://doi.org/10.5194/egusphere-egu23-3628, 2023.

EGU23-3655 | ECS | Orals | AS1.13

A new born theory for the genesis and dynamics of Madden–Julian oscillation-like structure 

Masoud Rostami, Bowen Zhao, and Stefan Petri

By means of a new multilayer pseudo-spectral moist-convective thermal rotating shallow-water (mcTRSW) model in a full sphere, we present a possible equatorial adjustment beyond Gill’s mechanism for the genesis and dynamics of the Madden–Julian oscillation (MJO). According to this theory, an eastward-propagating MJO-like structure can be generated in a self-sustained and self-propelled manner due to nonlinear relaxation (adjustment) of a large-scale positive buoyancy anomaly, depressed anomaly, or a combination of these, as soon as this anomaly reaches a critical threshold in the presence of moist convection at the Equator. This MJO-like episode possesses a convectively coupled “hybrid structure” that consists of a “quasi-equatorial modon” with an enhanced vortex pair and a convectively coupled baroclinic Kelvin wave (BKW), with greater phase speed than that of dipolar structure on an intraseasonal time-scale. Interaction of the BKW, after circumnavigating the entire Equator, with a new large-scale buoyancy anomaly may contribute to excitation of a recurrent generation of the next cycle of MJO-like structure. Overall, the generated “hybrid structure” captures a few of the crudest features of the MJO, includingits quadrupolar structure, convective activity, condensation patterns, vorticity field, phase speed, and westerly and easterly inflows in the lower and upper troposphere. Although moisture-fed convection is a necessary condition for the “hybrid structure” to be excited and maintained in the proposed theory in this study, it is fundamentally different from moisture-mode theories, because the barotropic equatorial modon and BKW also exist in “dry” environments, while there are no similar “dry” dynamical basic structures in moisture-mode theories. The proposed theory can therefore be a possible mechanism to explain the genesis and backbone structure of the MJO and to converge some theories that previously seemed divergent (DOI:10.1002/qj.4388). 

How to cite: Rostami, M., Zhao, B., and Petri, S.: A new born theory for the genesis and dynamics of Madden–Julian oscillation-like structure, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3655, https://doi.org/10.5194/egusphere-egu23-3655, 2023.

Tropical Cyclone Debbie (2017) made landfall near Airlie Beach on 28 March 2017 causing 14 fatalities and an estimated US$2.67B economic loss and was ranked as the most dangerous cyclone to hit Australia since TC Tracy in 1974. In addition to the extreme flooding as TC Debbie moved onshore and down the east coast of Australia, it intensified rapidly just offshore from Category 2 to Category 4 in approximately 18 hours and finally made landfall as a Category 4 TC, causing widespread and disastrous damage.

 

A high-resolution WRF simulation (1-km horizontal, and 10-min temporal resolution) is used to analyze the inner-core structure and evolution during the offshore rapid intensification period in the current conditions and potential future change. In current condition, Debbie’s a rapid intensification (RI) stage is characterized by three rounds of eyewall breakdown into mesovortices and re-development events. Each round of breakdown and re-establishment brings high potential vorticity and equivalent potential temperature air back into the eyewall, re-invigorating eyewall convection activity and driving intensification. The potential future changes in the inner-core structure and eyewall evolution will also be discussed using WRF with the Coupled Model Intercomparison Project Phase 6 (CMIP6) perturbed conditions to better assess the possible TC intensity change under different climate change scenarios.

How to cite: Deng, D. and Ritchie, E.: High-resolution simulation of Tropical Cyclone Debbie (2017):The current and future changes in the inner-core structure and evolution during offshore intensification., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3704, https://doi.org/10.5194/egusphere-egu23-3704, 2023.

EGU23-3718 | Orals | AS1.13

Relationship between the Tropical Cyclone Forecast Skill and the Western North Pacific Summer Monsoon in the ECMWF Monthly Ensemble 

Hsiao-Chung Tsai, Tzu-Ting Lo, Meng-Shih Chen, Yun-Jing Chen, Jui-Ling Kuo, and Han-Yu Hsu

In this study, week-1 to week-4 forecasts of tropical cyclones (TCs) in the western North Pacific are evaluated. The CWB TC Tracking System 2.0 (Lo et al. 2021) is used to objectively detect TCs in the 46-day ECMWF ensemble (ENS) forecasts in the 2021 season and also the reforecasts during 2001-2020. Preliminary evaluations of the probabilistic TC activity forecasts in the 20-year reforecasts show promising forecast skills. The reliability diagrams indicate slight over-forecasting bias in the weeks 1-4 forecasts, and the AUCs (Area Under Curves) are ranging from 0.91 (week-1) to 0.80 (week-4). The relationship between the TC activity forecast skill and the western North Pacific summer monsoon (WNPSM) is also investigated. The WNP monsoon index (WNPMI) proposed by Wang et al. (2001) is computed to provide a measure for the summer monsoon, and the TC forecast skills are evaluated under different levels of the WNPMI. To identify the potential false alarms, a spatial-temporal track clustering technique (Tsai et al. 2019) is implemented to objectively group similar vortex tracks in the 51-member forecasts. The corresponding ensemble mean track for each cluster is then used for performing the event-based verifications after the end of season. More details about the TC forecast verifications in weeks 1-4 using the ECMWF monthly ensemble will be presented in the meeting.

How to cite: Tsai, H.-C., Lo, T.-T., Chen, M.-S., Chen, Y.-J., Kuo, J.-L., and Hsu, H.-Y.: Relationship between the Tropical Cyclone Forecast Skill and the Western North Pacific Summer Monsoon in the ECMWF Monthly Ensemble, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3718, https://doi.org/10.5194/egusphere-egu23-3718, 2023.

EGU23-3995 | ECS | Orals | AS1.13

Impact of the MJO on the extreme precipitations in the Mexican Valley 

Liset V. Proveyer and Alejandro Jaramillo

This research aims to determine how the Madden-Julian oscillation (MJO) influences extreme summer precipitation events in the Metropolitan Area of the Mexican Valley (MAMV). Using the Real-time Multivariate MJO Index (RMM), we found a higher frequency of days with extreme events during phases 1 and 2 of the MJO (wet phases), with the lowest occurrence during phases 6, 7, and 8 (dry phases). These frequencies are associated with positive (negative) humidity anomalies in the whole atmospheric column of the study region during the wet (dry) phases. The interaction of a humid flow from the Caribbean Sea with the mountain systems of the region plays a fundamental role in the occurrence of deep convection. Also, the formation of mesoscale convective systems in the central region of the Mexican territory contributes to the moisture content in the Mexican Valley. We used the Dynamic Recycling Model to quantify the relative contributions of different source regions to the atmospheric humidity in MAMV. We found that the greatest contributions to the humidity anomalies are from the Caribbean Sea and Central Mexico during the wet phases of the MJO. During the remaining phases, we observe a weakening of the humid flow from the east as the Caribbean low-level jet intensifies. Additionally, during phases 7 and 8, the mountainous systems that limit the MAMV constitute natural barriers to the flow of humidity that tends to be predominantly from the eastern Pacific. The MAMV is highly vulnerable to extreme precipitation events and their effects, such as pluvial floods and landslides. Therefore, studying the phenomena that modulate these extreme events is essential to improve their predictability and perform better risk management.

How to cite: Proveyer, L. V. and Jaramillo, A.: Impact of the MJO on the extreme precipitations in the Mexican Valley, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3995, https://doi.org/10.5194/egusphere-egu23-3995, 2023.

EGU23-4002 | Posters on site | AS1.13

Effect of the Coastal Large-Scale Environment on the Tropical Diurnal Cycle 

Eric Maloney, Michael Natoli, Emily Riley Dellaripa, Hien Bui, Charlotte DeMott, and Ewan Short

Environmental conditions supporting offshore propagation of diurnal precipitation near tropical coastlines are examined. In particular, the effect of the near-coastal background wind, moisture, and surface wind speed and fluxes on offshore precipitation propagation is assessed for the Philippines, northern Australia, and Panama Bight region near Colombia. Reanalysis fields, satellite precipitation, surface wind speed (from the CYGNSS satellite), and flux observations, and the Cloud Model 1 (CM1) are used in this work. In general, a moist offshore environment and enhanced wind-driven surface fluxes support offshore propagation of strong diurnal convective disturbances. Near the west coast of Luzon, a weak offshore wind in the lower free troposphere also supports offshore propagation, as often occurs in the transition phases of the boreal summer intraseasonal oscillation from suppressed to enhanced daily mean convection. Vertically-integrated moist static energy budget analysis is used to support these results. Sensitivity tests with the CM1 verify the importance of weak offshore flow and a moist offshore environment for supporting offshore propagation of diurnal precipitation.

How to cite: Maloney, E., Natoli, M., Riley Dellaripa, E., Bui, H., DeMott, C., and Short, E.: Effect of the Coastal Large-Scale Environment on the Tropical Diurnal Cycle, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4002, https://doi.org/10.5194/egusphere-egu23-4002, 2023.

EGU23-4126 | ECS | Posters on site | AS1.13

A Dynamical Framework to Understand and Predict the Indian Summer Monsoon Low Pressure Systems 

K. S. S. Sai Srujan, Sukumaran Sandeep, and Hariprasad Kodamana

About 60% of the rainfall during the Indian Summer Monsoon (ISM) is manifested by the synoptic-scale storms form over North Bay of Bengal (BoB) and the adjacent land area known as “Low-Pressure Systems” (LPS). Unlike tropical cyclones, the storms during this season (LPSs) are embedded in the background monsoon flow, which makes them difficult to predict, considering the chaotic nature of the monsoon. Nearly one-third of these synoptic-scale storms are formed due to the amplification of disturbance which is propagating from the Western North Pacific (WNP) (categorized as “downstream LPS”). We observed an association of tropical cyclones (TCs) originating over WNP with the genesis mechanisms of downstream LPS over the BoB. The TCs over the WNP are classified into different clusters based on different features like length, genesis location, landfall, etc., using the gaussian mixture models. We found that four major clusters of WNP TCs are responsible for triggering 83% of the downstream LPS genesis. We established a causality using the transfer entropy analysis between the fluctuations in mean sea-level pressure over BoB and the Rossby wave activity over the WNP prior to the initiation of an LPS.

Our results suggest a plausible prediction of downstream LPS at least a week ahead. The current generation of climate models has low skill in simulating the LPS; understanding the dynamics behind the genesis of LPS is the way to improve the LPS-related precipitation in climate models. The recent advancement in using AI/ML in predicting various weather and climate phenomena, including our recent study in predicting the synoptic-scale sea-level pressure using the ConvLSTM model explains the importance of dynamics-based data-driven ML models to predict complex weather patterns. Understanding the dynamics of such physical phenomena will help in identifying the appropriate predictors for the data-driven ML models.

How to cite: Srujan, K. S. S. S., Sandeep, S., and Kodamana, H.: A Dynamical Framework to Understand and Predict the Indian Summer Monsoon Low Pressure Systems, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4126, https://doi.org/10.5194/egusphere-egu23-4126, 2023.

EGU23-4491 | ECS | Orals | AS1.13

Influence of the MJO on extreme precipitation events over the Eastern Pacific Ocean 

Luis Lazcano and Christian Domínguez

The Madden-Julian Oscillation (MJO) is the main mode of intraseasonal variability over the tropics. We aim to explore the MJO modulation on extreme precipitation events by analyzing atmospheric variables from ERA5 and oceanic variables from the NOAA and HYCOM reanalysis over the Eastern Pacific Ocean from May to November during the 1982-2018 period. The Real-time Multivariate MJO Index (RMM) is used to define the MJO phases. Only strong MJO phases are considered for this study. During MJO phases 3-7, the Eastern Pacific Ocean warm pool goes through a large expansion, but rainfall decreases near the Mexican Pacific coast. On the other hand, MJO phases 8, 1, and 2 induce an increase in precipitation over the continental part of the Middle Americas, making extreme precipitation events more frequent, but these phases decrease the warm pool extension near the Pacific coast. Additionally, the MJO compounds are classified according to El Niño Southern Oscillation (ENSO) years. MJO phases under Neutral and El Niño years have similar patterns in the atmospheric variables. However, these patterns drastically change in MJO phases under La Niña years, as the warm pool expansion decreases and the decrease/increase in rainfall is more intense compared to Neutral and El Niño years. We also noticed that the warm pool expansion and extreme precipitation events do not occur simultaneously. There is a lag of 7 days, as previous studies found but for the Indian Ocean. We conclude that these results are important to understand the air-ocean coupling for MJO and its application for sub-seasonal forecasts.

How to cite: Lazcano, L. and Domínguez, C.: Influence of the MJO on extreme precipitation events over the Eastern Pacific Ocean, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4491, https://doi.org/10.5194/egusphere-egu23-4491, 2023.

EGU23-4550 | ECS | Orals | AS1.13

On the critical layer interaction of the stratospheric Kelvin waves 

Ahmed Shaaban and Paul Roundy

Stratospheric Kelvin waves are known to be absorbed by the background flow via mechanical and thermal damping and, to less extent, by the critical layer interaction. Critical layer interaction occurs when the Kelvin waves' phase speed approaches the background flow's speed. This study aims to depict the structure of the Kelvin waves while approaching the critical layer, where the phase speed of the wave matches the speed of the background flow. In the time domain, the wavelet filtering technique filters Kelvin waves at a specific location and phase speeds using ERA-I zonal wind. Linear regression yields the pattern of specific phase speed's Kelvin wave. Yet, the critical layer interaction of the Kelvin waves with the environmental flow could be studied by choosing a background environment in which its flow speed matches the wave's phase speed, which could be implemented using the varying-coefficient regression technique. We found that the in-phase relationship between the zonal wind and height, associated with the structure of the Kelvin waves, relaxes with the decreasing of the Doppler-shifted speed; then, at a further reduction of the Doppler-shifted speed, the Gill pattern appears. Furthermore, Kelvin waves were found to be absent under an environment of westerly shear.

How to cite: Shaaban, A. and Roundy, P.: On the critical layer interaction of the stratospheric Kelvin waves, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4550, https://doi.org/10.5194/egusphere-egu23-4550, 2023.

EGU23-4664 | ECS | Posters on site | AS1.13

Record-breaking rainfall accumulations in eastern China produced by Typhoon In-fa (2021) 

Xin Huang, Johnny C. L. Chan, Ruifen Zhan, Zifeng Yu, and Rijin Wan

Persistent heavy rainfall produced by western North Pacific (WNP) tropical cyclones (TCs) can lead to widespread flooding and landslides in Asian countries. On July 2021, unprecedent rainfall amount occurred when Typhoon In-fa passed through the highly populated eastern China. While the associated synoptic features have been analyzed, the extreme characteristics and return periods of rainfall induced by In-fa remain unexplored. Analyses of rainfall data from a WNP TC database of the China Meteorological Administration (CMA) show that Typhoon In-fa not only produces record-breaking rainfall accumulations at individual surface stations, but generates unprecedent rainfall amounts for the whole area of eastern China. Quantitatively, 2, 4, 11, 24 and 55 stations are exposed to once in 200-, 100-, 50-, 20- and 10-year extreme TC rainfall accumulations, respectively, and total rainfall at 75 stations reaches a record high since 1980. Overall, the return period is up to ~481 years for the total rainfall amount accumulated in eastern China during the 1980-2019 baseline. The extremely long rainfall duration is identified as key to the torrential rains in the Yangtze River Delta before In-fa changes its direction of movement from northwestward to northeastward, while the extreme rain rate plays a dominant role in the northern areas afterwards. Probabilities of occurrence of such an unprecedented TC rainfall event have increased in most (~75%) of the eastern China during the period of 2000-2019 compared with those during 1980-1999. Our study highlights the likely increase in risk of extreme TC-induced rainfall accumulations which should be considered in disaster risk mitigation.

How to cite: Huang, X., Chan, J. C. L., Zhan, R., Yu, Z., and Wan, R.: Record-breaking rainfall accumulations in eastern China produced by Typhoon In-fa (2021), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4664, https://doi.org/10.5194/egusphere-egu23-4664, 2023.

EGU23-4688 | Orals | AS1.13

Contribution of tropical cyclone seeds in the poleward shift of the tropical cyclone formation 

Jung-Eun Chu, Axel Timmermann, Pavan Harika Raavi, Sun-Seon Lee, Johnny C. L. Chan, and Hung Ming Cheung

Tropical cyclones (TCs), the generic name for typhoons, are among the most destructive natural hazards. It is important to understand how climate change affects TC frequency, to minimize human and economic losses. Some studies have suggested that the number of TCs will decrease, and their formation will shift poleward. However, there is a major lack of fundamental understanding of the origin and development of the TCs from the initial precursory vortex, called a TC seed. The changes in the number of TC seeds and their survival rate (i.e., the proportion that successfully develops into TCs) will eventually control the future TC frequency. However, key challenges are mainly due to a lack of consensus in TC seed definition and a lack of computing resources for TC modeling.

This study aims to meet the above challenges, through the following three tasks: (1) to identify the representation of TC seeds based on three different definitions from early-stage to matured stage; (2) to investigate the future changes in TC seeds and survival rate and their contribution to the poleward shift in TC genesis location; and (3) to unravel the physical mechanisms responsible for the change in response to climate change. We use a high-resolution fully-coupled Community Earth System Model (CESM) with an atmospheric resolution of 0.25° and an ocean resolution of 0.1° with present-day, doubling, and quadrupling CO2 concentrations. Our results show TC seeds defined by early-stage definition show more equatorward distribution with a strong connection to vertical velocity than those defined by matured stage. Interestingly, all three definitions exhibit a statistically significant reduction in the frequency of TC seeds while that in survival rate is not significant. Details of the methods and mechanisms will be further discussed during the presentation. The outcomes of this project will strengthen fundamental scientific knowledge of the TC seeds and their future change mechanisms, as well as provide a scientific basis for future risk assessment and precautionary strategies.

How to cite: Chu, J.-E., Timmermann, A., Raavi, P. H., Lee, S.-S., Chan, J. C. L., and Cheung, H. M.: Contribution of tropical cyclone seeds in the poleward shift of the tropical cyclone formation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4688, https://doi.org/10.5194/egusphere-egu23-4688, 2023.

EGU23-4734 | Posters on site | AS1.13

Investigation of TC track uncertainty using multiple ensembles for the official TC forecast 

Jinyeon Kim, Dongjin Kim, Daejoon Kim, Joohyung Son, and Dong-Ju Ham

The official tropical cyclone information in Korea includes a deterministic forecast position of TC center and its uncertainty with the 70% probability circle, which is statistically determined by previous 3 year’s operational track errors. Therefore, the current probability circle does not represent situational uncertainty. In this study, it is investigated for using an ensemble prediction system (EPS) to represent the TC position uncertainty with three different methods: circle (CIR), ellipse with an along-track and a cross-track axes (EAC), ellipse with eigenvector axes (EEV). Five single EPSs, ECMWF, NCEP, UKMO-UM, JMA and KMA-UM, and two multiple ensembles, a simple one (SME) and a calibrated one (CME) which coincides the ensemble means, were evaluated. The methods and the ensembles were verified for 5 days with the hit rate which is defined as the percentage of the observed TC central positions within circles or ellipses.
In order to verify the new probability areas as well as the operation, the hit rate which is defined as the percentage of the observed TC central positions within 70% probability circle or ellipses were used. The operational radii have over 70% hit rate, around 0.8 for all forecast times. It means that the official forecast skill is getting better year by year and the current circle is overestimated. EPS based circle or ellipse showed better performance apart from the EAC. In more detail, the CME for both circle and ellipse method outperformed the operational method until 48 forecast hours. Since the five single EPSs were under-spread at this time, the multiple ensembles could overcome this shortage. After 72 forecast hours, SME and CME are too overspread, so that a single EPS is more likely to be consistent with the 70% probability area.
Although it is definitely sure that the EPS based one is better, there are still limitations to use them. It is difficult to say which method is the best because performance of methods is different according to the forecast time and to get other organizations’ EPS data in real time. Nevertheless, utilizing ensemble for TC track is valuable information since EPS can provide the best method for estimating uncertainty. 

How to cite: Kim, J., Kim, D., Kim, D., Son, J., and Ham, D.-J.: Investigation of TC track uncertainty using multiple ensembles for the official TC forecast, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4734, https://doi.org/10.5194/egusphere-egu23-4734, 2023.

EGU23-4792 | Posters on site | AS1.13

Characteristics of rapidly intensifying tropical cyclones in the South China Sea, 1980-2016 

Lei Yang, Xi luo, Fenghua Zhou, Dongxiao Wang, and Weiqiang Wang

The differences in the characteristics of the rapid intensification (RI) during the TCs that form in the SCS (referred as local TCs) and that
enter the SCS from the western North Pacific (WNP; referred as entering TCs) have not been well studied, which could contribute the inaccuracy
of current TC intensity forecast in the SCS. In this study, we used TC observations, reanalysis data and model experiments to analyze the RI
occurrences during local TCs and entering TCs in 1980e2016. We found that the significant interannual and interdecadal variations in RI
occurrences during local eastward-moving TCs were related to the strong intraseasonal oscillation (ISO) over the SCS and the WNP under La
Nina conditions. RI during local westward-moving TCs showed insignificant variations as a result of the complex interactions among the
monsoon trough, ISO and the large-scale circulation. RI during entering TCs showed strong interdecadal variations, with increased RI after
1997, even though the total number of entering TCs has decreased since 1997, which is a result of a higher number of entering TCs in the
northwestern quadrant of the WNP, a stronger ISO and weak vertical windshear over the SCS and east of the Philippines under negative phase of
Pacific Decadal Oscillation. The different variations and related mechanisms of RI indicates that distinct forecasting factors should be considered
for intensity prediction during local eastward- and westward-moving TCs and entering TCs.

How to cite: Yang, L., luo, X., Zhou, F., Wang, D., and Wang, W.: Characteristics of rapidly intensifying tropical cyclones in the South China Sea, 1980-2016, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4792, https://doi.org/10.5194/egusphere-egu23-4792, 2023.

EGU23-5056 | ECS | Orals | AS1.13

Relationships of the Diurnal Pulse to Structure and Intensity of Tropical Cyclones 

Xinyan Zhang and Weixin Xu

The radially-outward propagating, cloud-top cooling, diurnal pulse (DP) is a prominent feature in tropical cyclones (TCs) that has important implications for changes in TC structure and intensity. By using an objective diurnal-pulse identification algorithm, this study characterizes DPs both globally and regionally over various ocean basins and examines their relationships to TC structure and intensity. Active DPs (ACTDPs) occur on 52% of TC days globally. They are the most frequent over the Northwest Pacific (NWP, 60.4%). The median duration and propagation distance of ACTDPs are 12–15 h and 500–600 km, respectively. Some ACTDPs (20–25%) last longer than 18 h and propagate as far as 700–800 km. Although the mean propagation speed of ACTDPs is 11–13 m s-1, persistent ACTDPs (lasting >15 h) mostly propagate at speeds similar to internal inertial gravity waves (5–10 m s-1). Most ACTDPs initiate in the inner core overnight, in phase with inner-core deep convection. Nearly half of the ACTDPs are coupled with the outward propagation of precipitation within TCs. The TC inner-core deep convection is significantly enhanced on ACTDP days. Specifically, the 20 dBZ echo top in the upshear quadrant of TCs rises the most evidently with the occurrence of the ACTDP, leading to a more symmetric structure of the inner-core convection. The occurrence ACTDPs may promote the rapid intensification (RI) of TCs. The frequency and duration of ACTDPs are strongly correlated with the TC intensification rate. RI TCs have a markedly higher frequency of the very long-duration ACTDPs (≥15h) and longer mean pulse duration than steady-state and gradually intensifying TCs. Overall, the DP is a potentially useful signal for the RI of TCs.

How to cite: Zhang, X. and Xu, W.: Relationships of the Diurnal Pulse to Structure and Intensity of Tropical Cyclones, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5056, https://doi.org/10.5194/egusphere-egu23-5056, 2023.

Mixed Rossby-Gravity (MRG) Waves are westward propagating synoptic scale equatorial disturbances which play a crucial role in the formation of tropical cyclones and tropical depressions, and they constitute a significant part of various modes of tropical variability such as the Madden-Julian Oscillation (MJO) and Quasi-Biennial Oscillation (QBO). In this study, we have investigated the trends and Inter Annual Variability (IAV) in the occurrence of upper tropospheric MRG events using ERA-I reanalysis data for the period 1979-2018. The MRG events are identified by projecting the upper tropospheric meridional winds onto the theoretical spatial structure of MRG waves. A steady increasing trend is observed in the occurrence of MRG events which is contributed by the MRG events associated with the intrusion of extratropical disturbances. The possible factors that govern the observed trends and IAV in the occurrences of MRG events are El Nino Southern Oscillation (ENSO), MJO and extratropical forcing. The MRG events over the central and Eastern Pacific contribute maximum to the IAV. ENSO explains about 25% of the IAV. It exhibits a positive correlation with non-intrusion MRG events and a negative correlation with intrusion MRG events. These observations have been investigated by exploring the strength and the extent of the westerly duct at 200 hPa and the Outgoing Longwave Radiation (OLR) during El Nino and La Nina years over the central-Eastern Pacific ocean. The convectively active state of the MJO over the Western Pacific explains 20% of the IAV over the central-Eastern Pacific. Besides ENSO, MJO exhibits a diametrically opposite correlation with intrusion and non-intrusion MRG events. The antisymmetric heating with respect to the equator, associated with the MJO, enhances non-intrusion MRG events. The subtropical easterlies forbid the intrusion of extratropical disturbances, thereby lowering the occurrences of intrusion MRG events. The increasing trend in the intrusion of extratropical disturbances explains the observed trend in the upper tropospheric MRG events. Such an increasing trend is not observed in the strength or extent of the upper tropospheric westerly duct over the central-Eastern Pacific.

How to cite: Na, M., Keshri, S., and Ettammal, S.: Major Factors Governing the Trends and Interannual Variability in the Occurrences of Mixed Rossby-Gravity Wave Events, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5340, https://doi.org/10.5194/egusphere-egu23-5340, 2023.

This study investigated rapid intensification (RI, +30 kt in 24 h) and rapid weakening (RW, -20 kt in 24 h) for Typhoon Trami (2018) using the Weather Research and Forecasting V4.2 with the three-dimensional Price-Weller- Pinkel ocean model. As with the previous Typhoon Lan (2017) case study, the three-dimensional relative humidity field reproduced from Tropical Cyclones-Pacific Asian Research Campaign for the Improvement of Intensity Estimations/Forecasts dropsonde data and Himawari-8 satellite imagery was assimilated during every tropical cyclone dynamical initialization process. Specifically, dropsonde data obtained from two aircraft campaigns for Lan and Trami is used. Numerical results showed that compared to without this special data assimilation, Trami’s RI and RW simulations were better improved with this special data assimilation with respect to track and intensity forecasts. Around the RI period, vertical wind shear noticeably decreased and convective bursts (vertical velocity ≥ 3 m s-1 with 30 dBZ at 2 km height) significantly increased during the RI period. With these favorable ambient and storm inner-core environments, Trami quickly formed an eye structure. After RI and slow intensification periods, Trami eventually reached the Category 5 Saffir-Simpson hurricane scale. This maximum intensity was almost maintained until it had turned northwards. After that, as its translation speed significantly decreased, RW occurred with substantial upwelling. This upwelling caused a stable boundary layer and made significant asymmetry of surface heat fluxes and convective clouds. During this significant sea surface cooling period, deep convective cells were significantly suppressed in the eyewall area. As a result, Trami underwent RW during this period. To sum up, Trami’s RI may be associated with the reduction of negative dynamic forcing around the RI period, whereas Trami’s RW may be related to negative thermodynamic forcing by ocean cooling with a very slow translation speed during the RW period. More numerical results and detailed analyses of Trami’s RI and RW will be shown in the 2023 EGU General Assembly.

 

Keywords: dropsonde data assimilation, tropical cyclone dynamical initialization, rapid intensification, rapid weakening, WRF atmosphere and ocean coupled model

 

Acknowledgment

This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMI2022-00410.

 

How to cite: Lee, J., Chang, E.-C., Ito, K., and Wu, C.-C.: Effects of the Assimilation of Relative Humidity Reproduced From T-PARCII and Himawari-8 Satellite Imagery Using Dynamical Initialization and Ocean Coupled Model: A Case Study of Typhoon Trami (2018), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5434, https://doi.org/10.5194/egusphere-egu23-5434, 2023.

EGU23-5825 | ECS | Orals | AS1.13

GPM-DPR observed microphysical characteristics of the Arabian Sea tropical cyclone 

Amit Kumar, Atul Kumar Srivastava, and Manoj Kumar Srivastava

The precipitation characteristics of tropical cyclones (TCs) formed between 2014-2021 over the Arabian Sea during the onset phase of monsoon and after the monsoon (post-monsoon) seasons have been investigated through the space-borne dual-frequency precipitation radar of the Global Precipitation Measurement (GPM-DPR) satellite level 2, V07 observation. In a cloud that is producing precipitation, the two-dimensional frequency distribution of the liquid water content (LWC; g/m2) and non-liquid water content (IWC; g/m2) exhibits a clear seasonal and cloud-type dependence. For the precipitating cloud of stratiform origin of TCs in the monsoon and post-monsoon seasons, a significant part of rain droplets is present in the LWC limit of 0-800 g/m2 and the IWC limit of 0-350 g/m2. In contrast to the stratiform precipitation associated with the TCs, the LWC quantity is additionally more, and IWC is less for the convective origin precipitating cloud. In the monsoon and post-monsoon season, the mean values of the mass-weighted mean diameter, Dm (mm), are 1.29 (1.47) mm and 1.27 (1.31) mm, respectively, for the stratiform (convective) cyclonic cloud. It is noticed that when the value of Dm increases, the normalised intercept parameters (Nw) decrease, regardless of the season and cloud type related to the TCs. While stratiform precipitation contains a considerably high concentration of smaller-sized rain droplets during both seasons, the number concentration of bigger rain droplets is significantly high during convective precipitation. From the contoured frequency with altitude diagram (CFAD) plots for Dm and Ze for the cyclonic cloud in both seasons, we observe a large concentration of ice and supercooled liquid particles available above the melting layer and a significant concentration of rain droplets in liquid state present below the melting layer. We derived the contribution of the different microphysical processes (break-up, size-sorting, collision-coalescence, and evaporation processes) in the rain droplets formation below the melting layer. It is found that the process of collision-coalescence is predominating microphysical process for convective precipitation. The break-up process is a primary microphysical process in the precipitating cloud of stratiform origin.

 

How to cite: Kumar, A., Srivastava, A. K., and Srivastava, M. K.: GPM-DPR observed microphysical characteristics of the Arabian Sea tropical cyclone, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5825, https://doi.org/10.5194/egusphere-egu23-5825, 2023.

EGU23-6086 | Orals | AS1.13

Influence of Potential Vorticity Structure on North Atlantic Tropical Cyclone Activity 

Ulrike Lohmann, Bernhard Enz, David Neubauer, and Michael Sprenger

Tropical cyclones are among the most devastating natural phenomena that can cause severe damage when hitting land. Some of this damage could be prevented with more reliable short-term and seasonal forecasts. In the wake of the poorly forecast 2013 North Atlantic hurricane season, Rossby wave breaking has been linked to tropical cyclone activity measured by the accumulated cyclone energy. Here, ERA5 reanalysis data and HURDAT2 tropical cyclone data are used to show that the latitude of the 2 potential vorticity unit (PVU) contour on the 360 K isentropic surface in the western North Atlantic is linked to changes in vertical wind shear and relative humidity during the month of September.

A more equatorward position of the 2 PVU contour is linked to an increase in vertical wind shear and a reduction in relative humidity, as manifested in an increased ventilation index, in the tropical western North Atlantic during September. The more equatorward position of the 2 PVU contour is further linked to a reduction in the number of named storms, hurricane days, hurricane lifetime, and number of tropical cyclones making landfall due to changes in genesis location. In summary, the 2 PVU contour latitude in the western North Atlantic can therefore potentially be used as a predictor in seasonal and sub-seasonal forecasting.

How to cite: Lohmann, U., Enz, B., Neubauer, D., and Sprenger, M.: Influence of Potential Vorticity Structure on North Atlantic Tropical Cyclone Activity, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6086, https://doi.org/10.5194/egusphere-egu23-6086, 2023.

EGU23-6157 | ECS | Posters on site | AS1.13

Intensification mechanisms of tropical cyclones 

Andrea Polesello, Caroline J. Muller, Claudia Pasquero, and Agostino N. Meroni

Wind Induced Surface Heat Exchange (WISHE) mechanism is considered very important for tropical cyclone intensification in a large part of the scientific literature([1], [2], [3] ): heat flux from the ocean increase with increasing wind speed, building up a positive feedback on the intensification.
Simple WISHE-based models of tropical intensification predict that tropical cyclones intensify up to a steady state at the Potential Intensity (PI), obtained from the balance of heat supply rate from the ocean and dissipation rate in the boundary layer and dependent on boundary conditions only ([1]). The main problem of such models is the fact that they typically drastically simplify the convective motion within the cyclone, assuming a troposphere neutral to moist convection. ([4]).
In our work we tested these predictions in idealized numerical experiments performed using the non-hydrostatic, high-resolution model System for Atmospheric Modelling (SAM). The results showed a significantly different intensity evolution, with the cyclone undergoing a oscillation in surface wind speed with peak intensity significantly lower than the PI.
This intensity evolution was related to that of the environmental conditions along the whole air column: convective heating exports latent and sensible heat in the middle-upper troposphere, increasing environmental air buoyancy and so reducing CAPE. Radiative heating from the clouds further stabilizes the upper troposphere, weakening convection and thus cyclone intensity. After the intensity decay phase the upper level air surrounding the cyclone cools down through radiation emission: entrainment of cold air by the cyclone itself rebuilts CAPE and triggers a new intensification. Despite this work showed some limits in the predictivity of WISHE theory, WISHE feedback itself was proved to be fundamental for tropical cyclone intensification with a sensitivity numerical experiment.

 

[1]  K. Emanuel et al., “Tropical cyclones,” Annual review of earth and planetary sciences, vol. 31,
no. 1, pp. 75–104, 2003

[2]  K. A. Emanuel, “An Air-Sea Interaction Theory for Tropical Cyclones. Part I: Steady-State
Maintenance.,” Journal of Atmospheric Sciences, vol. 43, pp. 585–605, Mar. 1986.

[3]  C. J. Muller and D. M. Romps, “Acceleration of tropical cyclogenesis by self-aggregation
feedbacks,” Proceedings of the National Academy of Sciences, vol. 115, no. 12, pp. 2930–
2935, 2018.

[4]  K. A. Emanuel, “The behavior of a simple hurricane model using a convective scheme based
on subcloud-layer entropy equilibrium,” Journal of Atmospheric Sciences, vol. 52, no. 22,
pp. 3960 – 3968, 1995.

How to cite: Polesello, A., Muller, C. J., Pasquero, C., and Meroni, A. N.: Intensification mechanisms of tropical cyclones, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6157, https://doi.org/10.5194/egusphere-egu23-6157, 2023.

EGU23-6549 | ECS | Orals | AS1.13

Extreme precipitation in South Sulawesi triggered by equatorial waves and its representation in MetUM forecasts 

Natasha Senior, Adrian Matthews, Ben Webber, Beata Latos, and Dariusz Baranowski

The Indonesian island of Sulawesi lies at the heart of the Maritime Continent, a region prone to extreme rainfall. On seasonal timescales, rainfall frequency and intensity increases during the monsoon season (Nov-March). On subseasonal scales, rainfall is modulated by the Madden-Julian Oscillation (MJO) which increases moisture and moisture convergence in its active phase. Higher frequency modes include convectively coupled equatorial waves which influence rainfall variability on daily timescales. On 22nd January 2019, these large-scale meteorological drivers coincided resulting in the South Sulawesi region experiencing its largest flood on record. Specifically, the extreme rainfall event was linked to a convectively coupled Kelvin wave (CCKW) and a convectively coupled equatorial Rossby wave (CCERW) embedded within an active MJO envelope, as well as a cross equatorial cold surge (Latos et al, 2021). Interactions between these modes resulted in increased moisture transport and convergence that lead to the development of a mesoscale convective system (MCS) over Java and the Java Sea on 21st January 2019. This MCS traversed towards Sulawesi bringing extreme rainfall to the region in the evening and overnight on the 22nd reaching its peak mid-afternoon. Cases like this present a unique challenge for forecasters, to not only to accurately represent the individual equatorial modes but their interactions. In the present work we study the MCS in reanalysis and satellite data and discuss how the various equatorial modes contributed to its development. Then we examine its representation in different convection permitting Met Office Unified Model (MetUM) configurations. We find that the MetUM performed well in capturing the trajectories of the equatorial modes, however the representation of the MCS itself varies between ensemble members and model configurations. We further examine how well the RAL1T+ configuration represents the equatorial modes through comparing filtered fields of daily model data at fixed lead times to those in observations.

How to cite: Senior, N., Matthews, A., Webber, B., Latos, B., and Baranowski, D.: Extreme precipitation in South Sulawesi triggered by equatorial waves and its representation in MetUM forecasts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6549, https://doi.org/10.5194/egusphere-egu23-6549, 2023.

As tropical cyclones (TCs) undergo extratropical transition (ET), they develop distinct frontal boundaries across the resulting extratropical cyclone. In the North Atlantic Ocean (NATL), this can often happen near the Gulf Stream (GS). Previous work has demonstrated that the GS can influence the development of fronts in midlatitude winter cyclones. The mechanisms of air-sea interactions associated with WBCs occur at multiple spatiotemporal scales, with the extent and exact nature of those interactions debated within the literature. Could the influence of the GS on frontal development in midlatitude winter storms also apply to storms undergoing ET? Here, we present both an observational-based statistical analysis, as well as results from case-study simulations, of a possible pathway for the GS to influence TCs undergoing ET via local small-scale SST gradient changes.

Composites of NATL TCs indicate that the magnitude of the GS sea surface temperature (SST) gradient in the time prior to the TC passing is significantly weaker for TCs that begin the ET process but ultimately do not complete it, compared with TCs that do complete ET. Using a simple index of the GS SST gradient strength, both the sensible heat flux gradient and, to a lesser degree, lower-tropospheric diabatic frontogenesis are shown to scale with the local SST gradient used in this index. Our results suggest that there is some support for a mechanism in which the GS SST gradient influences the sensible heat flux gradient and subsequent surface diabatic frontogenesis in the region, impacting the favorability of the environment for a passing TC to complete ET.

To investigate this possible mechanism more closely and establish causality, we use the Weather Research and Forecasting (WRF) model to test case study simulations of Hurricane Teddy as it undergoes ET near the GS. We analyze this by modifying the magnitude and strength of the local grid point-scale SST gradient strength associated with the GS in the North Atlantic in the days prior to Teddy passing over the GS. These different simulations are then compared to determine impacts in terms of the track, intensity, frontal development, strength of both the adiabatic and diabatic frontogenesis, during Teddy’s ET. These results provide insight into the dynamical mechanisms by which surface forcing could exert an influence on ET.

How to cite: Jones, E., Wing, A., and Parfitt, R.: Investigating A Potential Pathway for Gulf Stream Influence on the Extratropical Transition of North Atlantic Tropical Cyclones, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6628, https://doi.org/10.5194/egusphere-egu23-6628, 2023.

EGU23-6722 | Orals | AS1.13 | Highlight

Impact of Deforestation in the Maritime Continent on the Madden–Julian Oscillation 

Chuing-Wen June Chang, Min-Hui Lo, Wan-Ling Tseng, Yu-Cian Tsai, and Jia-Yuh Yu

Deforestation is a major issue affecting both regional and global hydroclimates. This study investigated the effect of deforestation in the Maritime Continent (MC) on tropical intraseasonal climate variability. Using a global climate model with Madden–Julian Oscillation (MJO) simulations, we examined the effect of deforestation over the MC region by replacing the forest canopy with grassland. The results revealed that under constant orographic and land–sea contrast forcing, the modification of the canopy over the MC altered the characteristics of the MJO. We noted the amplification of the MJO and increases in wet–dry fluctuation and the zonal extent. We analyzed more than 100 MJO cases by performing K-means clustering and determined that the continuous propagation of the MJO over the MC increased in 35% and 61% of the total 110 cases in the control and deforestation experiments, respectively. This phenomenon was associated with more substantial vanguard precipitation, increased soil moisture, and a suppressed diurnal cycle in land convection. Furthermore, when the MJO convection was over the Indian Ocean (IO), we observed the enhancement of low-level moisture over the MC region in the deforestation experiment. Grassland surface forcing provides a thermodynamic source for triggering instability in the atmosphere, resulting in low-level moisture convergence. The MJO exhibited a stronger energy recharge–discharge cycle in the deforestation experiment than in the control experiment, and this difference between the experiments enlarged from the IO to MC.

 

How to cite: Chang, C.-W. J., Lo, M.-H., Tseng, W.-L., Tsai, Y.-C., and Yu, J.-Y.: Impact of Deforestation in the Maritime Continent on the Madden–Julian Oscillation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6722, https://doi.org/10.5194/egusphere-egu23-6722, 2023.

The variation of the thermodynamic cycle and energy of tropical cyclones (TCs) under vertical wind shear (VWS) is analyzed, and its associated TC thermal and dynamical structure evolutions are explored. The thermodynamic cycles extracted using the Mean Airflow as Lagrangian Dynamics Approximation (MAFALDA) method show that the maximum energy obtained by the TC decreases with the reduction of storm intensity in VWS. The thermodynamic cycles of sheared TC experience a two-stage evolution. During the early stage, the ascending branch of the MAFALDA cycle shifts toward lower entropy, which is attributed to the reduction of the entropy in the eyewall and the increase of the upward motion and entropy outside the eyewall. In the latter stage, the entropy increases, and the downward motion weakens in the ambient and upper troposphere, allowing the descending legs shifts toward high values of entropy. A backward Lagrangian diagnostic of air parcels associated with variations in thermodynamic cycles is employed to analyze the relative importance of distinct pathways. In addition to the low-, mid-, and upper-level ventilation pathways, the enhanced inner and outer rainbands, outward advection of high entropy air in mid- and upper-troposphere eyewall, the outflow layer with reduced height, and the inflow below the outflow layer are also important for the reduction of the energy gained by TC.

How to cite: Liu, Z.-Q. and Tan, Z.-M.: How Vertical Wind Shear Impacts Tropical Cyclone by Different Thermodynamic Pathways: Energetics and Lagrangian Analysis, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6747, https://doi.org/10.5194/egusphere-egu23-6747, 2023.

EGU23-6758 | ECS | Posters on site | AS1.13

The Decadal Variation of Eastward-Moving Tropical Cyclones in the South China Sea During 1980–2020 

Xi luo, Lei Yang, Sheng Chen, Dong Liang, Johnny C. L. Chan, and Dongxiao Wang

The track of tropical cyclones (TCs) formed in the South China Sea (SCS) can be divided into eastward and westward directions. Significant decadal variation during 1980–2020 only exists in the number of eastward-moving TCs, especially during July–September, with 47% TCs moving eastward during 1994–2004 (Period II), 22% during 1980–1993 (Period I) and only 15% during 2005–2020 (Period III). This decadal change is related to the zonal shift of Western Pacific Subtropical High (WPSH). An eastward-retreated WPSH during 1994–2004 leads to upward motion and westerly flow anomaly over the northern SCS, and therefore favors TC genesis and eastward motion. The eastward-retreated WPSH is associated with a warm sea surface temperature anomaly over the tropical western-central Pacific which induces a cyclonic flow and weakens the WPSH. With the weaker modulation of WPSH, stronger intraseasonal oscillation (ISO) in the SCS during Period II favors eastward-moving TCs due to the westerly flow associated with the ISO.

How to cite: luo, X., Yang, L., Chen, S., Liang, D., Chan, J. C. L., and Wang, D.: The Decadal Variation of Eastward-Moving Tropical Cyclones in the South China Sea During 1980–2020, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6758, https://doi.org/10.5194/egusphere-egu23-6758, 2023.

EGU23-7841 | ECS | Posters on site | AS1.13

The diurnal cycle of precipitation over the Maritime Continent: characterisation in observations and models 

Jack Mustafa, Adrian Matthews, Rob Hall, Karen Heywood, and Marina Azaneu

The meteorological diurnal cycle over the Maritime Continent is a major component of observed variability and features see-sawing of intense precipitation from over land through the afternoon and evening to over surrounding seas and oceans through the night into the morning. This high-frequency land-locked mode of variability interacts with lower-frequency propagating modes of tropical variability, such as the Madden-Julian Oscillation, therefore accurate forecasting of downstream impacts of these intraseasonal modes of variability depends on accurate understanding and model representation of the diurnal cycle.

In this presentation we compare the observed diurnal cycle of precipitation with the diurnal cycle generated by regional hindcast runs of the UK Met Office Unified Model with parameterised and with explicitly-resolved convection. A novel characterisation framework is used to quantify the cycle at each location in order to optimise the intuitive simplicity and the completeness of the characterisation.

How to cite: Mustafa, J., Matthews, A., Hall, R., Heywood, K., and Azaneu, M.: The diurnal cycle of precipitation over the Maritime Continent: characterisation in observations and models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7841, https://doi.org/10.5194/egusphere-egu23-7841, 2023.

EGU23-7870 | Orals | AS1.13 | Highlight

Ocean-Atmosphere Observations from Uncrewed Saildrones and Gliders during the 2022 Atlantic Hurricane Season 

Gregory Foltz and the 2022 NOAA Saildrone Hurricane Observations Team

During the 2022 Atlantic hurricane season, uncrewed systems were used in an innovative and coordinated effort to measure the upper ocean and air-sea interface inside and outside of tropical cyclones. The main objectives were to advance understanding of air-sea interactions in and around tropical cyclones and aid forecaster situational awareness, with the ultimate goal of improving tropical cyclone intensity forecasts. The uncrewed systems included seven saildrones and five underwater gliders that operated in the western Atlantic Ocean, Caribbean Sea, and Gulf of Mexico. Nearly collocated and simultaneous measurements were acquired by an underwater glider and saildrone through the eye of Hurricane Fiona south of Puerto Rico in September. Another saildrone was directed through Fiona after it had intensified to a Category 4 Hurricane in the North Atlantic, measuring sustained winds of 35 m/s and significant wave height of 15 m. Two other saildrones obtained measurements in Fiona when it was a tropical storm east of the Caribbean and as a Category 1 hurricane north of Puerto Rico. Later in September, after Hurricane Ian made landfall in southwestern Florida and then re-intensified to a hurricane east of Florida, a saildrone was directed through its center, measuring winds of 29 m/s and an air-sea temperature difference of 8 deg. C near the Gulf Stream. This presentation gives an overview of the 2022 effort and the data acquired, discusses challenges and lessons learned, and looks toward the future of uncrewed systems observations in tropical cyclones.

How to cite: Foltz, G. and the 2022 NOAA Saildrone Hurricane Observations Team: Ocean-Atmosphere Observations from Uncrewed Saildrones and Gliders during the 2022 Atlantic Hurricane Season, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7870, https://doi.org/10.5194/egusphere-egu23-7870, 2023.

EGU23-8613 | ECS | Orals | AS1.13

Veer and shear in the tropical cyclone lower boundary-layer 

Sara Müller, Xiaoli Guo Larsén, and David Verelst

Tropical cyclones are associated with extreme wind speeds, enhanced turbulence, vertical wind shear, and veer. All these elements increase loads acting on structures such as wind turbines, bridges, and high-rise buildings. While most studies focus on maximal wind speeds in tropical cyclones, we analyze wind shear and veer in the lowest 300 m of the atmosphere, which is relevant for wind energy applications. We use the Weather Research and Forecasting model to model and analyze the distribution and spatial structure of wind shear and veer in Typhoon Megi (2016) at different radii. We found maximal mean shear and veer in the eyewall region. Shear and veer are on average smaller in the rainbands, but their respective distribution is positively skewed due to spatially organized outliers. These outliers are associated with convective cells and downdrafts, that propagate over structures with speeds of around 30 ms⁻¹. Consequently, structures experience rapid changes in shear and veer. We further analyze vertical cross-sections through convective cells and their propagation velocity. The study highlights differences in characteristics of the low-level wind field between the eyewall region and rainbands, which suggest distinct forces acting on structures.

How to cite: Müller, S., Guo Larsén, X., and Verelst, D.: Veer and shear in the tropical cyclone lower boundary-layer, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8613, https://doi.org/10.5194/egusphere-egu23-8613, 2023.

EGU23-8675 | ECS | Posters on site | AS1.13

The influence of weather patterns and the Madden-Julian Oscillation on extreme precipitation over Sri Lanka 

Akshay Deoras, Andrew G. Turner, and Kieran M. R. Hunt

Sri Lanka is affected by extreme precipitation events every year that cause floods, landslides, and tremendous economic losses. Unlike for other countries in South Asia such as India, there has been a limited investigation of weather patterns associated with extreme precipitation events in Sri Lanka. In this study, we use the ERA5 reanalysis dataset to understand the association between extreme precipitation events and 30 weather patterns, which were originally derived to represent the variability of the Indian climate during January–December 1979–2016. Furthermore, we analyse the modulation of extreme precipitation events by the Madden-Julian Oscillation (MJO). We also use the daily rainfall data from 51 meteorological stations in Sri Lanka to take some account of the observational uncertainty.

We find that weather patterns that are most common during the northeast monsoon (December–February) and second intermonsoon (October–November) seasons produce the highest number of extreme precipitation events. Moreover, extreme precipitation events occurring during these two seasons are more persistent than those during the southwest monsoon (May–September) and first intermonsoon (March–April) seasons. The frequency of extreme precipitation events is enhanced (suppressed) in MJO phases 1–4 (5–8) for most weather patterns. The results of this study could benefit meteorologists, hydrologists, and researchers in developing forecasting products based on the identification of these weather patterns and MJO phases in numerical weather prediction and the subseasonal-to-seasonal prediction models, envisaging improved disaster preparedness in Sri Lanka.

How to cite: Deoras, A., Turner, A. G., and Hunt, K. M. R.: The influence of weather patterns and the Madden-Julian Oscillation on extreme precipitation over Sri Lanka, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8675, https://doi.org/10.5194/egusphere-egu23-8675, 2023.

EGU23-8710 | ECS | Orals | AS1.13

Has there been a recent shallowing of tropical cyclones? 

Tsz-Kin Lai and Ralf Toumi

Many aspects of tropical cyclone (TC) properties at the surface have been changing but any systematic vertical changes are unknown. Here we document a recent trend of high thick clouds of TCs. The global inner-core high thick cloud fraction measured by satellite has decreased from 2002 to 2021 by about 10% per decade. The TC inner-core surface rain rate is also found to have decreased during the same period by a similar percentage. This suppression of high thick clouds and rain has been largest during the intensification phase of the strongest TCs. Hence, these two independent and consistent observations suggest that the TC inner-core convection has weakened and that TCs have become shallower recently at least. For this period the lifetime maximum intensity of major TCs has not changed and this suggests an increased efficiency of the spin-up of TCs.

How to cite: Lai, T.-K. and Toumi, R.: Has there been a recent shallowing of tropical cyclones?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8710, https://doi.org/10.5194/egusphere-egu23-8710, 2023.

EGU23-8949 | ECS | Orals | AS1.13

Impact of tropical waves on rainfall modulation and heavy rainfall event occurrence over western equatorial Africa 

Marlon Maranan, Idene-Flore Mantho T., Andreas H. Fink, Derbetini A. Vondou, Peter Knippertz, and Roderick van der Linden

Tropical waves, particularly convectively coupled equatorial waves (CCEWs), are known to modulate rainfall in tropical Africa on intraseasonal down to convective time scales, the latter of which includes the dynamics of heavy rainfall events. Data scarcity in large parts of Africa, especially in equatorial Africa, has long prevented a clearer picture on the regional variability of extreme rainfall. Thus, making use of globally gridded satellite data and a unique in-situ rainfall dataset for Cameroon, this study aims for a systematic comparison of the role of tropical waves on the occurrence and variability of intense rainfall over western equatorial Africa.

For the study period 2001-2019 in a selected domain over Cameroon, heavy daily rainfall (i.e. the 20% strongest and spatially most extensive) events are identified using both the satellite-based rainfall estimates of the Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) and largely unique station data from the Karlsruhe African Surface Station-Database (KASS-D). The outgoing longwave radiation (OLR) dataset of the National Oceanic and Atmospheric Administration (NOAA) are then used (a) to support evidence of the occurrence of the intense rainfall events, and (b) to apply a wavenumber-frequency filtering in order to evaluate the co-occurrence of tropical waves around these events. These include the fast modes such as Kelvin waves and tropical disturbances (TD), in the study region commonly represented by African Easterly Waves (AEWs), as well as slow modes represented by equatorial Rossby waves and the Madden-Julian Oscillation (MJO). Finally, to account for regional differences in seasonal rainfall characteristics, the analysis is performed for a southern and northern sub-domain during the bi-modal (March–May/September–November) and unimodal (May–October) rainy seasons, respectively.

Results show that: 1) the passage of Kelvin waves and TDs have the strongest impact on daily rainfall rates in the two sub-regions, whereas the effect of the MJO is the weakest ; 2) the modulation by Kelvin waves is strongest in southern Cameroon whereas that of TDs is strongest in the north; 3) there is a shift between the wet wave phases in OLR and rainfall (IMERG, KASSD); 4) up to 78% of the cases with heavy rain coincide with the passage of a tropical wave; 5) Kelvin and TD are again the most likely to be associated with a heavy rainfall event, featuring an up to five times higher local wave intensity as compared to the other waves.

To further test potential dependencies of results on the applied wave identification method, tropical waves have also been identified with a 2D spatial projection method based on parabolic cylinder functions (PCFs) using horizontal wind fields from ERA5. Here, first results suggest that the projection method overall yields less intense and slower Kelvin waves. Furthermore, the occurrence of a Kelvin wave appears to be related to heavy rainfall to a lesser degree compared to the wavenumber-frequency approach. This potentially stresses the importance of a careful choice of the suitable wave identification method for a given application, the details of which are currently evaluated.

How to cite: Maranan, M., Mantho T., I.-F., Fink, A. H., Vondou, D. A., Knippertz, P., and van der Linden, R.: Impact of tropical waves on rainfall modulation and heavy rainfall event occurrence over western equatorial Africa, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8949, https://doi.org/10.5194/egusphere-egu23-8949, 2023.

The very active month of September 2020 included the formation of 10 named storms, the most on record for the month of September, and 5 concurrent tropical cyclones (TCs) in the North Atlantic basin on September 14th. The Model for Prediction Across Scales (MPAS) is used to explore potential opportunity to predict TC activity out to 4 weeks. First, the MPAS model climatology for September TC activity is established. Next, the predictability of an active September is explored using MPAS simulations with initial atmospheric and oceanic conditions from the global forecast system (GFS) and compared with MPAS climatology. MPAS simulations for 2020 are initialized over the last two weeks of August and run freely through September. The total number of TCs, TC days, accumulated cyclone energy (ACE), and the track density are each evaluated relative to observations. In addition, the simulations resulting in the most and least active month are analyzed in further detail to understand why those model simulations predicted an active or inactive September. Lastly, differences with and without a regionally refined 3 km mesh are explored.

How to cite: Nystrom, R. and Judt, F.: Predictions of North Atlantic tropical cyclone activity out to 4 weeks with global MPAS simulations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10481, https://doi.org/10.5194/egusphere-egu23-10481, 2023.

EGU23-10920 | Posters on site | AS1.13

Characteristics of Mesoscale Convective Systems in the Philippines 

Ma. Cathrene Lagare, Takeshi Yamazaki, and Junshi Ito

Mesoscale convective systems (MCSs) are organized clusters of convection that often bring in heavy to extreme rainfall, which can cause devastating effects such as flooding, landslides, and significant crop and infrastructural damages. Studies on severe weather in the Philippines, a part of the Maritime Continent where frequent and intense convective activities occur, focus predominantly on synoptic-scale systems (e.g., tropical cyclones). The characteristics of MCSs in the Philippines remain understudied. 

Motivated by this research gap, a long-term MCS climatology over the Philippines was constructed using the global MCS tracking database of Feng et al. (2021), and its large-scale environments are investigated to understand the formation of MCSs. Preliminary results show that large-scale flows largely affect MCS formation. MCSs occur more frequently during the peak of the Asian summer monsoon (JJA), producing large rainfall amounts over the west of the Philippines. Meanwhile, the Asian winter monsoon during DJF has a different effect on MCS formation in the Philippines as it does not directly correspond to high occurrences of MCSs. However, the convective systems during DJF still produce high rainfall amounts over the east of the Philippines. Based on these results, additional analyses for the MCSs during the boreal winter are conducted. 

 

Reference:

Feng, Z., Leung, L. R., Liu, N., Wang, J., Houze Jr, R. A., Li, J., ... & Guo, J. (2021). A global high-resolution mesoscale convective system database using satellite-derived cloud tops, surface precipitation, and tracking. Journal of Geophysical Research: Atmospheres, 126(8), e2020JD034202.

How to cite: Lagare, Ma. C., Yamazaki, T., and Ito, J.: Characteristics of Mesoscale Convective Systems in the Philippines, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10920, https://doi.org/10.5194/egusphere-egu23-10920, 2023.

In a recent model evaluation of the African Easterly Wave (AEW) that became Helene (pre-Helene; 2006) over the Atlantic, the wave was categorized as a mixed-off-equatorial moisture mode during tropical cyclogenesis as it evolved under weak temperature gradient balance. It was found that the simulated pre-Helene waves were more intense and overall slower than in ERA5, especially the wave that evolved in a more moisture-rich environment. The growth and propagation of the wave were related to the position of the convection with respect to the center of the wave vortex. The influence of environmental moisture on wave propagation before and during genesis remains an open question. Motivated by the recent findings, in this study, moisture sensitivity experiments are performed with a convection-permitting model to further evaluate the moisture dependency of the pre-Helene wave and later tropical cyclogenesis. The Model for Prediction Across Scales (MPAS) regional configuration is used to allow altering initial and lateral boundary conditions of relative humidity (RH) through the entire atmospheric column using ERA5 pressure-level data. Preliminary results reveal that over land the strength of the wave-trough meridional flow is related to mid-to-upper-level diabatic heating tendencies from clouds located in the northerly phase of the wave and to the lack of shallow convection within the vortex. In MOIST (RH x 1.2 experiment), the wave moves slower, yet organized convection propagates out of phase with the wave speed, ultimately weakening the wave and subsequent tropical cyclogenesis. In CONTROL, where the wave propagates faster, the phasing between wave and convection supports a stronger wave prior to genesis and ultimately genesis when compared to MOIST. A moister atmosphere (MOIST) favors a larger fraction of shallow convection (bottom heavy and weaker updrafts) at the center and ahead of the vortex, detraining the mid-troposphere and weakening the mid-tropospheric vorticity. This leads to a wave that weakens prior to genesis compared to CONTROL as well as a more abrupt decrease in speed prior to genesis. The lack of cloud microphysics heating tendencies in DRY (RH x 0.5 experiment) resulted in a weaker mid-to-upper-level circulation but stronger surface-to-low-level winds. The lack of moisture is detrimental to the simulated pre-Helene; however, a moister environment does not necessarily result in a more intense wave or tropical cyclogenesis event. A wave that propagates more slowly (‘moist wave’ versus ‘dry wave’), does not necessarily favor growth. For further growth, convection that is in phase with the vortex should be deep moist convection.

How to cite: Núñez Ocasio, K. and Davis, C.: Wave Propagation and Growth Dependency to Environmental Moisture: A Case of an Atlantic Tropical Cyclogenesis, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10985, https://doi.org/10.5194/egusphere-egu23-10985, 2023.

This study investigated long-term changes of tropical cyclones (TCs) activity and rainfall produced by TCs, hereafter TC-rainfall, over Vietnam in the period of 1979-2021. Furthermore, it is investigated how rainfall changes are influenced by the North Pacific (NP) pattern.

First, it was found that TC activity has not changed significantly in its frequency, and its related rainfall including TC and tropical depression (TDs) produced rainfall, hereafter TCTD-rainfall over entire Vietnam. On the other hand, significant increasing trend of TC activity (XX per 10 year), TC-rainfall (65 mm per 10 year), TCTD-rainfall (75 mm per 10 year), and total rainfall (440 mm per 10 year) is found in North Vietnam in the period of 1979-2021. However, TC, TD activity, TC-rainfall and TCTD-rainfall did not show any significant trends in Central and South Vietnam. Second, decadal and inter-decadal variation of rainfall in North Vietnam are significantly correlated with the North Pacific (NP) pattern during autumn season (October-December). Negative (positive) phases of the NP is characterized by a low (high) sea level pressure (SLP) located over the northern North Pacific Ocean and anomalously warm (cold) sea surface temperature (SST) over central and eastern tropical Pacific, resulting in to less (more) TCs activity and rainfall events over the South China Sea and Vietnam. In summary, it is found that rainfall produced by TCTD exhibits significantly increasing trend in North Vietnam, as well as total rainfall and the NP pattern plays an active role in altering rainfall anomalies in North Vietnam in the decadal and inter-decadal timescales.

How to cite: Thi Ngoc Huyen, H. and Yoon, J.-H.: Tropical Cyclone produced rainfall trends in Vietnam and their relationship with the North Pacific (NP) pattern during 1979 – 2021, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11096, https://doi.org/10.5194/egusphere-egu23-11096, 2023.

EGU23-12007 | Posters on site | AS1.13

Statical prediction system of the typhoon intensity using Numerical Weather Prediction model for correction 

Jeong-Ho Bae, Jung-Rim Lee, Seong-Hee Won, and Dong-Ju Ham

The accuracy of tropical cyclone (TC) forecasts from NWP models have been improved especially for the track. Relatively, TC intensity forecasts still include huge uncertainties though the dynamics, physics processes, and resolutions of NWP systems become higher in both horizontal and vertical. For this reason, many operational centers and academia for TC forecasts implemented statistical prediction systems and Artificial Intelligence (AI) algorithms based on long-term dynamic model forecasts for better predictions of typhoon intensity.
The National Hurricane Center (NHC) developed the Statistical Hurricane Intensity Prediction Scheme (SHIPS) which is a statistical model based on NWP forecasts (parameters from atmosphere and ocean). Also, infrared imagery from geostationary satellite is used as predictors for the regression. SHIPS is implemented for the North Atlantic and East Pacific regions. Otherwise, the Joint Typhoon Warning Center (JTWC) implemented this model for the Northwest Pacific region. Also, Korea Meteorological Administration (KMA) and Japan Meteorological Administration (JMA) developed the statistical based typhoon prediction systems (called STIPS and TIFS, respectively). However, the accuracy of these systems is not stable because it is not easy to define the tendency of NWP forecasts for TC intensity. 
The National Typhoon Center of KMA developed a new statistical model (Statistical Prediction Intensity of Korea mEteorological administrator, SPIKE) for typhoon intensity prediction based on ECMWF forecast. While the ECMWF Integrated Forecast System (IFS) has an excellent performance in forecasting track of typhoons, the intensity tends to be underestimated compared to typhoons analysis information. 
SPIKE is basically developed as a multi-linear regression model, and its predictors are extracted from the IFS forecast. The average prediction error of typhoon intensity of SPIKE in 2022 decreased by about 30% compared to the ECMWF forecasts. However, there was still a limitation, especially for cases of rapid intensification (RI). More studies to reflect real-time intensity, cloud development, center location, and prediction errors of the model are conducted. Then, the second multi-linear regression model to account for these parameters is developed. Finally, an additional improvement of about 30% was achieved. Also, the performance for RI cases developing more than 35 knots within 24 hours was greatly improved. 

How to cite: Bae, J.-H., Lee, J.-R., Won, S.-H., and Ham, D.-J.: Statical prediction system of the typhoon intensity using Numerical Weather Prediction model for correction, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12007, https://doi.org/10.5194/egusphere-egu23-12007, 2023.

EGU23-12516 | ECS | Posters on site | AS1.13

The inner life of the Atlantic ITCZ 

Julia Windmiller and Bjorn Stevens

The intertropical convergence zone (ITCZ) is a central component of the global circulation system, but remarkably little is known about the dynamical and thermodynamical structure of the convergence zone itself. This is true even for the structure of the low-level convergence that gives the ITCZ its name. Following on from the major international field campaigns in the 1960s and 70s, we performed extensive atmospheric profiling of the Atlantic ITCZ during a ship-based measurement campaign aboard the research vessel SONNE in summer 2021. Combining the data we collected during our north-south crossing of the ITCZ with reanalysis data shows that there are generally two low-level convergence lines that roughly mark the southern and northern edges of the region of intense precipitation. Based on the location of these two edges, we construct a composite view of the structure of the Atlantic ITCZ. The ITCZ, far from being simply a region of enhanced deep convection, has a rich inner life, i.e., a rich dynamical and thermodynamic structure that changes throughout the course of the year and has a northern edge that differs systematically from the southern edge. 

How to cite: Windmiller, J. and Stevens, B.: The inner life of the Atlantic ITCZ, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12516, https://doi.org/10.5194/egusphere-egu23-12516, 2023.

EGU23-13886 | ECS | Posters on site | AS1.13

Influence of Indian Summer Monsoon on the Post-Monsoon Cyclones 

Feba Francis, Vikas Kushwaha, and Ashok Karumuri

The North Indian Ocean (NIO) has two Tropical cyclone (TC) seasons, i.e., pre-monsoon and post-monsoon. We find that the Indian summer monsoon (ISM) has an influence on the frequency of cyclones in the post-monsoon in the NIO. Flood years show a higher frequency of TCs, and drought years show a lesser frequency of TCs than normal years. By the examination of Grey-Sikka parameters for cyclogenesis, we show that during the drought years, the mid-tropospheric humidity, low-level vorticity, and Tropical Cyclone Heat Potential are lower than in normal years and the vertical shear is higher over most of the NIO. These factors lead to the reduced cyclonic frequency in the Bay of Bengal during drought years and more frequent cyclones in flood years, though the relation is more ambiguous in the Arabian Sea. This study builds an unexplored relation between ISM and TCs in the NIO and would help in improving TC seasonal prediction.

How to cite: Francis, F., Kushwaha, V., and Karumuri, A.: Influence of Indian Summer Monsoon on the Post-Monsoon Cyclones, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13886, https://doi.org/10.5194/egusphere-egu23-13886, 2023.

EGU23-14195 | ECS | Posters on site | AS1.13

Machine learning-based bias correction for tropical cyclone track simulation of the WRF model over the western North Pacific 

Kyoungmin Kim, Donghyuck Yoon, Dong-Hyun Cha, and Jungho Im

The tropical cyclone (TC) tracks are usually simulated with the numerical models, which have an intrinsic error, although the performance of numerical models is continuously improving. Recently, machine learning has been suggested as a good tool to correct the intrinsic error of the model outputs. This study used an artificial neural network (ANN) to correct the error of TC tracks hindcasted by the Weather Research and Forecasting (WRF) model over the western North Pacific (WNP). TCs whose intensity was higher than tropical depression (i.e., tropical storm, severe tropical storm, and typhoon) from June to November were hindcasted, and TC positions at 72 h were set as the target of bias correction. WRF model output, best track data, and wind field of reanalysis were used as input variables of ANN. The structure of ANN was optimized for TCs during 2006-2015, and the optimized ANN was verified for TCs from 2016-2018. In the verification of ANN, TCs were classified using k-mean clustering to analyze the results of bias correction because the performance of the numerical model for the TC track varied depending on the region of WNP. The ANN corrected the error of WRF by 8.81% for four clusters where ANN was most effective. Moreover, the post-processing was applied to other clusters with less effect of ANN. Consequently, ANN with post-processing improved the accuracy of WRF by 4.34%.

How to cite: Kim, K., Yoon, D., Cha, D.-H., and Im, J.: Machine learning-based bias correction for tropical cyclone track simulation of the WRF model over the western North Pacific, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14195, https://doi.org/10.5194/egusphere-egu23-14195, 2023.

EGU23-14848 | ECS | Posters on site | AS1.13

Multivariate forecasting of tropical cyclones using combined neural networks. 

Yegor Hudozhnik and Andreas Windisch

Tropical Cyclones (TCs) are extremely dangerous and destructive events which pose a danger to human lives every year. Conventional TC forecasting methods are computationally intensive and require a relatively large amount of energy and time.

In the light of climate change due to the process of global warming, the behavior of TCs may change, and therefore require the use of modern, more flexible learning methods for estimation and forecasting.

In recent years, the study of the application of Deep Learning (DL) in this area proved to be highly effective. These methods are designed to facilitate the prediction process, as well as automatically detect possible trends that may occur over time.

In this work, an application of neural networks such as LSTMs and GRUs is investigated to forecast tracks and classify the evolution of TC systems using satellite image data series as an input, where historical track data and the satellite image data are used to train the network. Particular attention is paid to adaptivity of DL approaches to recent trends and edge cases.

How to cite: Hudozhnik, Y. and Windisch, A.: Multivariate forecasting of tropical cyclones using combined neural networks., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14848, https://doi.org/10.5194/egusphere-egu23-14848, 2023.

EGU23-15063 | Orals | AS1.13

Physical mechanisms of offshore propagation of convection in the Maritime Continent 

Simon Peatman, Cathryn Birch, Juliane Schwendike, John Marsham, Chris Dearden, Stuart Webster, Emma Howard, Steven Woolnough, Ryan Neely, and Adrian Matthews

The Maritime Continent, located within the Indo-Pacific warm pool, experiences some of the most intense convective rainfall on Earth, with a pronounced diurnal cycle. The spatio-temporal variability of convection, its organisation and its offshore propagation away from the islands overnight all depend on many factors including the topography of island coastlines and mountains, and large-scale weather phenomena such as the Madden-Julian Oscillation, El Niño–Southern Oscillation and equatorial waves. However, numerical weather prediction and climate models typically suffer from considerable biases in simulating the diurnal convection and its propagation, hence there is a need to improve our understanding of the underlying physical mechanisms of these phenomena.

While the nocturnal offshore propagation of convection is often thought to be forced by gravity waves triggered by land-based diurnal convection, alternative hypothesized mechanisms exist in the literature, related to the propagation of the offshore land breeze and cold pools. Using convection-permitting simulations of selected case studies of convection propagating offshore from Sumatra, we find a squall line propagating overnight due to low-level convergence caused by the land breeze and environmental winds. This is reinforced by cold pools, which we diagnose using model tracers. However, gravity waves also play a role, triggering localized (non-organized) convection which does not itself propagate, but can appear as propagation along wave trajectories when compositing the diurnal cycle over many days.

The investigation is extended to other coastlines in the Maritime Continent, using convection-permitting simulations for 900 days during boreal winters, to demonstrate broader evidence for these physical mechanisms; to understand why the offshore propagation occurs on some days but not others; and to show how the strength, timing and causes of offshore propagation vary for different Maritime Continent islands, due to variations in the large-scale winds, orography and the topography of coastlines.

How to cite: Peatman, S., Birch, C., Schwendike, J., Marsham, J., Dearden, C., Webster, S., Howard, E., Woolnough, S., Neely, R., and Matthews, A.: Physical mechanisms of offshore propagation of convection in the Maritime Continent, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15063, https://doi.org/10.5194/egusphere-egu23-15063, 2023.

The organization and propagation of inner rainbands of landfalling Typhoon Cempaka (2021) during rapid intensification (RI) are investigated from two ground-based Doppler radars. Dual-Doppler analysis based on ground-based radars provide long-lasting high temporal and spatial three dimensional wind fields to examine the possible mechanisms for the organization of inner rainbands. In the early period when the convections were preferentially located inside the RMW, deformation plays an important role in the formation of inner rainbands. Convective cells were advected by the cyclonically rotating tropical cyclone swirling flow while being deformed into spiral shapes. In the later period when the convections were preferentially located outside the RMW, positive part of wavenumber-2 reflectivity associated with the rainband is collocated with the positive component of wavenumber-2 vorticity. The wavenumber-2 reflectivity moved at an azimuthal phase speed of 64.5% of the local tangential wind and very close to the theoretically predicted speed. It is evident that vortex Rossby wave is associated with the organization of rainband in the later stage.

How to cite: Fan, X.: Differences in the Formation and Evolution of the Inner Rainbands during the Rapid Intensification of Typhoon Cempaka (2021), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15194, https://doi.org/10.5194/egusphere-egu23-15194, 2023.

EGU23-15259 | ECS | Orals | AS1.13

Impacts of the MJO and Equatorial Waves on Tracked Mesoscale Convective Systems Over Southeast Asia 

Julia Crook, Fran Morris, Rory Fitzpatrick, Simon Peatman, Juliane Schwendike, Thorwald Stein, Cathryn Birch, and Sam Hardy

Southeast Asia is a region dominated by intense convection and characterised by the high-impact weather associated with synoptic scale tropical depressions, typhoons, or tropical cyclones (TCs). However, more localised convection such as mesoscale convective systems (MCSs) can also produce intense precipitation which can be a major risk for loss of lives and property for the communities in the region. Due to these high-impact weather features, its complex orography, and the significant impact of large-scale weather features on its meteorological variability, predicting weather in Southeast Asia is of great importance and scientific interest, but is a challenge. We aim to characterise the distribution of MCSs in the region and capture how the systems are modulated by the Madden-Julian Oscillation (MJO) and equatorial waves. 

MCSs in Southeast Asia between 2015 and 2020 were tracked using Himawari satellite data, their associated rainfall estimated using IMERG, and classified by lifetime and propagation speed. TC-related rainfall was also deduced using data from IBTrACS to identify certain cloud clusters as associated with TCs. Between 10S and 10N, MCSs account for 45-70% of the precipitation between November and April, and over most of the region, the fractional MCS contribution to rainfall is higher than average on extreme wet days (>55%). Long-lived  (>12 hours) MCSs contribute disproportionately, providing 84% of the rainfall despite comprising only 34% of all MCSs.

The MJO modulates MCS rainfall in a similar way to total rainfall, contributing >50% of the total rainfall anomaly, with the number of MCSs being greater in convectively active phases. However, in the West part of the region there are more fast-moving MCSs in the active MJO phases and more slow-moving MCSs in the inactive phases, resulting in fast-moving MCSs having a greater impact on the MJO-associated variation in MCS rainfall. This variation in MCS rainfall is larger in the West part of the region than the East. Meanwhile, variation in the area-mean rainfall rate within the storms, and sizes of storms were less well correlated with MCS rainfall in different phases; when areas were large, area-mean rainfall rate was generally low, and vice versa, providing compensating effects.

In the low-level convergence phase of an equatorial Kelvin wave, MCS rainfall and non-organized rainfall both increase, accounting for 20-50% of local rainfall anomalies, a pattern which is again enhanced in the West of the region. By contrast, Westward-propagating Mixed Rossby-Gravity waves, and Rossby-1 waves, do not strongly modulate MCS rainfall, and instead their rainfall anomalies are dominated by TC-related rainfall.

These relationships between MCSs and the MJO and Kelvin waves provide useful insight into forecasting MCSs in Southeast Asia by utilising knowledge of the synoptic weather regimes that are or will be affecting the region.

How to cite: Crook, J., Morris, F., Fitzpatrick, R., Peatman, S., Schwendike, J., Stein, T., Birch, C., and Hardy, S.: Impacts of the MJO and Equatorial Waves on Tracked Mesoscale Convective Systems Over Southeast Asia, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15259, https://doi.org/10.5194/egusphere-egu23-15259, 2023.

EGU23-15866 | ECS | Orals | AS1.13

Investigation of the microphysical processes during the rapid intensity changes of tropical cyclones over the Bay of Bengal: A modelling approach 

Yerni Srinivas Nekkali, Krishna Kishore Osuri, Ananda Kumar Das, and Dev Niyogi

Tropical cyclones (TCs) are one of the natural destructive weather phenomena. The accurate prediction of TC intensity is dependent on the understanding of the physical processes behind that. This study exposes the importance of microphysical (MP) processes in the rapid intensity changes of cyclones. For this, tropical cyclone simulations were made from the WRF model with a double nested (9 km-Static and 3 km-moving nests) configuration. This study shows that the heating generated by the MP processes in the TC’s inner-core region is highly (moderately) correlated with precipitated (non-precipitated) hydrometeors. During the rapid intensification (RI) period, heat-released microphysical processes such as condensation, freezing due to the accretion of liquid hydrometeors with ice particles, and deposition, etc., are dominant as compared to cooling-induced processes. In addition, the saturated envelope in the TC Phailin (2013) is responsible for more convection, heating, and hence consecutive RI episodes. While dry air intrusion hampers the prolonged RI episodes in TC Fani (2019). However, rapid weakening (RW) in TC Lehar (2013) is promoted by asymmetric, limited convection, and hence, lesser heating. During this RW period, the warm rain (ice) microphysical processes mainly produce heating (cooling).

How to cite: Nekkali, Y. S., Osuri, K. K., Das, A. K., and Niyogi, D.: Investigation of the microphysical processes during the rapid intensity changes of tropical cyclones over the Bay of Bengal: A modelling approach, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15866, https://doi.org/10.5194/egusphere-egu23-15866, 2023.

EGU23-15922 | Orals | AS1.13

The Potential of the W-band polarization diversity Doppler radar envisaged for the WIVERN mission for sampling tropical cyclones 

Frederic Tridon, Alessandro Battaglia, and Anthony Illingworth

The WIVERN (WInd VElocity Radar Nephoscope) mission, currently under the Phase-0 of the ESA Earth Explorer program, promises to complement AEOLUS Doppler wind lidar by globally observing, for the first time, vertical profiles of winds in cloudy areas. The objective of this work is to assess the potential of WIVERN for sampling tropical cyclones from the long-term CloudSat dataset. Realistic WIVERN synthetic observations are produced thanks to the recently developed end to end simulator of the WIVERN dual-polarization Doppler conically scanning 94 GHz radar based on CloudSat reflectivity observations and ECMWF co-located winds. The resulting multi-year dataset provides statistics on how well the WIVERN mission can sample the cloud systems associated to tropical cyclones and monitor their genesis and lifecycle. The analysis of the results provides statistics for addressing the following questions for tropical systems: What is the frequency of reliable wind estimates as a function of height? What is the effect of ghost echoes produced by cross-polarization? What is the impact of noise error and how often will the 94 GHz radar signal be fully attenuated by rain?

How to cite: Tridon, F., Battaglia, A., and Illingworth, A.: The Potential of the W-band polarization diversity Doppler radar envisaged for the WIVERN mission for sampling tropical cyclones, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15922, https://doi.org/10.5194/egusphere-egu23-15922, 2023.

Characterizing inflow structure is important to better represent tropical cyclone impacts in numerical models. While much research has considered the impact of storm translation on the distribution of inflow angle, comparatively less research has examined its distribution relative to the environmental wind shear. This study analyzes data from 3,655 dropsondes in 44 storms to investigate the radial and shear-relative distribution of surface inflow angle. Emphasis is placed on its relationship with intensity change. The results show that the radial variation in the inflow angle is small and not significantly dependent on the shear magnitude or intensity change rate. In contrast, the azimuthal distribution of the inflow angle shows a significant asymmetry, with the amplitude of the asymmetry increasing with shear magnitude. The maximum inflow angle is located in the downshear side. The degree of asymmetry is larger in the outer core than in the eyewall. Intensifying storms have a smaller degree of asymmetry than steady-state storms under moderate shear.

How to cite: Ming, J.: The Shear-Relative Variation of Inflow Angle and Its Relationship to Tropical Cyclone Intensification, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16246, https://doi.org/10.5194/egusphere-egu23-16246, 2023.

EGU23-16512 | ECS | Posters on site | AS1.13

Spatial and temporal variability of floods in Indonesia based on governmental data, Twitter messages and paper reports 

Beata Latos, Dariusz Baranowski, Maria Flatau, Jens de Bruijn, Katarzyna Barabasz, Michał Łabuz, Donaldi Permana, and Jaka Paski

Indonesia, with its tropical and monsoonal climate, is exposed to heavy precipitation and enormous rainfall accumulation which results in weather-driven hazards, including extreme rainfall events and floods. There are several conventional sources of data to estimate potential of anomalously high precipitation in Indonesia, including rain gauge data, satellite data and meteorological reanalysis. Even though they allow assessment of precipitation variability, their usefulness is limited by biases and data gaps. Furthermore, assessment of a variability in precipitation patterns is not the same as identification of their adverse societal effects, such as floods.  

Due to the proliferation of social media, these conventional data sets can be supplemented with crowd-sourced information that can potentially provide longer-term, accurate records and cover a larger area. In this study, we demonstrated that Twitter is a useful source for flood detection and created a flood database. Twitter-based flood database is derived for subregions of major islands within Indonesia: Java, Sumatra, Borneo and Sulawesi, and validated against data from governmental reports and local paper articles. Results show that Twitter-based retrieval performs well in comparison with other sources, but only in regions characterized by sufficiently large pool of active users. 

Flood events and extreme rainfall events (defined using in-situ and satellite data) were compared in terms of their spatial and temporal distribution, as well as their meteorological drivers. In general, on each of the island, there is a seasonal cycle: a wet season during boreal winter, when the Southeast Asian monsoon provides an environment supportive of rain events, and a dry season during boreal summer. On intraseasonal scale, Madden-Julian Oscillation (MJO) creates the conditions favorable for weather extremes. MJO activity causes an increase in the local rainfall rate, with a significant increase in a chance of observing extreme precipitation during favorable MJO phase.  

How to cite: Latos, B., Baranowski, D., Flatau, M., de Bruijn, J., Barabasz, K., Łabuz, M., Permana, D., and Paski, J.: Spatial and temporal variability of floods in Indonesia based on governmental data, Twitter messages and paper reports, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16512, https://doi.org/10.5194/egusphere-egu23-16512, 2023.

EGU23-16737 | Orals | AS1.13

Three Dimensional Wind and Rain Aircraft-Based Observations within the Hurricane Inner Core 

Zorana Jelenak, Joe Sapp, Paul Chang, Clayton Bjorland, James Carslwell, and Stephen Guimond

The three dimensional observations of wind and rain within the inner core of major hurricanes in the Atlantic basin were collected utilizing the Imaging Wind and Rain Profiler (IWRAP) on board a National Oceanographic Atmospheric Administration (NOAA) P-3 aircraft during the 2020-2022 hurricane seasons. With 30 m vertical and 150 m horizontal resolution, these measurements represent the highest resolution hurricane boundary layer (HBL) observations collected to date with a remote sensing instrument. State of the art IWRAP radar control and data acquisition system collects both in-phase (I) and quadrature (Q) signals for the entire observational profile. This allows for the full spectrum to be derived by utilizing a series of Fast Fourier Transforms (FFTs) on every single range gate resulting in the availability of the observations within lowest 500 m of the HBL. Previously, these observations were only possible from drop sondes. High resolution reflectivity profiles are processed into both three dimensional wind and rain products utilizing Ku- and C-band microwave observations. Over the course of three hurricane seasons, observations of 9 major hurricanes were collected and processed.

            With its unprecidented resolution these measurements are providing insights into turbulant processes within HBL of the major hurricanes and can possibly lead into new HBL parametarization of the hurricane models. Validation of measurements were carried out with flight level aircraft measurements, Step Frequency Microwave Radiometer surface wind measurements and Tail Doppler Radar 3d Wind and Reflectivity data.

            The measurement technique, collected data, validation results and data availability will be discussed and presented.

How to cite: Jelenak, Z., Sapp, J., Chang, P., Bjorland, C., Carslwell, J., and Guimond, S.: Three Dimensional Wind and Rain Aircraft-Based Observations within the Hurricane Inner Core, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16737, https://doi.org/10.5194/egusphere-egu23-16737, 2023.

EGU23-16746 | Posters on site | AS1.13

A study on precipitation characteristics of Kal Baishakhi: a premonsoon thunderstorm event 

Srinivasa Ramanujam Kannan

Kal Baishaki, a heavy thunderstorm event, recurs yearly during the premonsoon period (March-May) over the Indo-Gangetic plain and northeastern part of India. The event is highlighted by vigorous thunderstorm activity often associated with lightning and heavy to very heavy precipitation. Though the event has significant health and economic impact, the precipitation characteristics are not clearly understood. This is mainly due to a lack of continuous observation across a vast area covering West Bengal, Jharkhand, Orissa, Bihar, Assam, and other northeastern states of India. Precipitation measuring instruments onboard the Tropical Rainfall Measuring Mission satellite, followed by the Global Precipitation Measurement Mission, have provided an unprecedented data set that provides rainfall estimates at a high spatial, but sparsely temporal scale. The accuracy of data products has been refined over the years by comparing them with measurements from ground stations worldwide. The present work aims to consider rainfall data measured between 2001 and 2020 using remotely sensed instruments to analyse the precipitation characteristics of the significant rain event using a time series analysis approach.

How to cite: Kannan, S. R.: A study on precipitation characteristics of Kal Baishakhi: a premonsoon thunderstorm event, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16746, https://doi.org/10.5194/egusphere-egu23-16746, 2023.

EGU23-716 | ECS | Posters on site | AS1.14

Analysis of the Genesis Potential Index in Subtropical Cyclones off the Coast of Brazil 

João Gabriel Martins Ribeiro, Gabriel Teodoro da Paz, Michelle Simões Reboita, Luiz Felippe Gozzo, Glauber Willian de Souza Ferreira, and Rosmeri Porfírio da Rocha

The coastal region of southern and southeastern Brazil, which is part of the South Atlantic Ocean basin, is a genesis region for subtropical cyclones and, therefore, is susceptible to weather changes caused by these systems. The first named subtropical cyclone in the South Atlantic basin was Anita in 2010. Since then, some studies on subtropical cyclones have been carried out, but there are still several questions to be investigated. Thus, this study aims to: (a) describe the main physical mechanisms of genesis of the subtropical cyclones that were named in the South Atlantic Ocean between 2010 and 2021 and (b) identify the value of the Genesis Potential Index (GPI) between the pre-cyclogenesis and the phase in which these systems acquire subtropical characteristics. The rationale for analyzing the CPI is that we want to identify a possible pattern that helps in operational weather forecasting. The main database used in the study is the ERA5 reanalysis. Of the 14 cyclones studied, only two systems did not have cyclogenesis with subtropical characteristics, but acquired it 24 hours after cyclogenesis. The results indicate that 5 cyclones have a genesis associated with mid-level troughs in the atmosphere, and 9 with blocking patterns (cutoff low type). As most of the cyclones studied occur in an environment with blocking structure, this indicates that the condition of weak vertical wind shear is an important factor for subtropical cyclones. As the GPI does not show a standard value in the 14 cyclones studied, between pre-cyclogenesis and the moment when these systems become subtropical, as it varies from 0.35 in the Deni genesis to 22.71 in the Anita genesis, perhaps it is not possible to use it with a threshold in operational practices. The authors thank Programa de P&D regulado pela ANEEL e empresa Engie Brasil Energia e a Companhia Energética Estreito for the financial support.

How to cite: Ribeiro, J. G. M., da Paz, G. T., Reboita, M. S., Gozzo, L. F., Ferreira, G. W. D. S., and da Rocha, R. P.: Analysis of the Genesis Potential Index in Subtropical Cyclones off the Coast of Brazil, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-716, https://doi.org/10.5194/egusphere-egu23-716, 2023.

Previous studies showed that the midlatitude atmospheric circulation generally shifts poleward in response to climate change induced by increased greenhouse gas concentration, including the midlatitude storm track and the eddy-driven jet. The magnitude of this shift varies widely between different climate models and depends on the season, hemisphere and longitude. In this study we aim to reexamine the connection between the shifts of the sensible eddy heat flux and the eddy-driven jet in response to climate change and the role of diabatic heating and latent eddy heat flux in this relation. Our approach is to use the constraints of the zonally averaged heat and momentum budgets in order to connect the eddy-driven jet latitude to the heat budget terms. First, we examine the relation between the eddy-driven jet latitude and the eddy heat flux latitude in the inter-model spread of CMIP6 models. We find that the latitudinal separation between the eddy heat flux and eddy-driven jet depends on the amount of diabatic heating in the midlatitude midtroposphere, which varies widely between different models. This relation is explained based on the heat and momentum budgets.

Next, we use an idealized general circulation model with interactive water vapor and full radiation. We customized the model with different levels of saturation vapor pressure by increasing CO2 concentration and by increasing the humidity factor in the Clausius-Clapeyron relation. We found that in both the cases the atmospheric circulation responds in a similar way and the heat budget terms shift upward and poleward, signifying an upward and poleward shift of the storm track. We found that when the diabatic heating rises upward and strengthens enough over the midlatitude mid-troposphere in response to climate change, the adiabatic cooling by the Ferrel cell rising branch balances the diabatic heating and an equatorward shift of the eddy driven jet and the Ferrel cell is observed. These results provide further insight to the relation between the responses of the midlatitude circulation and the poleward energy flux terms to climate change.

How to cite: Ghosh, S., Lachmy, O., and Kaspi, Y.: The latitudinal shift of the midlatitude atmospheric circulation in response to climate change and the role of midlatitude diabatic heating, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1801, https://doi.org/10.5194/egusphere-egu23-1801, 2023.

EGU23-1812 | ECS | Orals | AS1.14

Extreme rainfall events in Morocco: spatio-temporal characteristics and climate drivers 

Abdelaziz Chaqdid, Alexandre Tuel, Abdelouahed EL Fatimy, and Nabil EL Moçayd

Extreme precipitation drives a series of natural disasters such as floods, flash floods, landslides, or crop losses. These disasters directly impact people's lives, their homes, and their food security. Located at the edge of the subtropics, on the northern edge of the Sahara desert, Morocco is particularly vulnerable to extreme precipitation. Indeed, between 1951 and 2015, Morocco experienced more than 35 major floods, which resulted in significant material and human losses. Understanding the spatio-temporal characteristics of extreme precipitation is key to better predicting and mitigating the risks associated with extreme precipitation events (EPEs). Yet, the spatio-temporal distribution and physical drivers of extreme precipitation in Morocco remain poorly understood. To address this gap, we apply temporal and spatial clustering methods to precipitation data from the ERA5 database as well as from observational databases to identify the main drivers of EPEs in Morocco. We find that Morocco exhibits five spatially coherent regions in terms of EPE timing, corresponding to mixed influences of large-scale extratropical and tropical weather systems. Indeed, EPEs in northern regions are caused by weather patterns similar to the negative phase of the North Atlantic Oscillation (NAO), associated with strong upper air flow enhanced by Greenland blocking and Rossby wave breaking (RWB). By contrast, extreme precipitation in southern regions is associated with tropical-extratropical interactions. There, EPEs are linked to an intense water vapor transport from the tropics and a relatively weak upper air flow.

How to cite: Chaqdid, A., Tuel, A., EL Fatimy, A., and EL Moçayd, N.: Extreme rainfall events in Morocco: spatio-temporal characteristics and climate drivers, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1812, https://doi.org/10.5194/egusphere-egu23-1812, 2023.

EGU23-1890 | Orals | AS1.14

The thermodynamic differences between winter cyclones from midlatitudes and high latitudes 

Dandan Tao, Camille Li, Richard Davy, Shengping He, Clio Michel, and Andrea Rosendahl

Cyclones carry heat and moisture that impact local conditions along their path. Cyclones with different origins can, however, have different life cycles and cause different impacts. To quantify differences in the thermodynamic evolution of cyclones originating from different latitudes during wintertime, we separate the cyclones according to their origin (cyclogenesis location):  midlatitude (ML) cyclones originating in the North Atlantic and high-latitude (HL) cyclones originating in the Nordic Seas and Barents Seas. It is found that HL cyclones generally carry lower thermodynamic energy as they originate in a cold environment. In contrast, ML cyclones have much higher thermodynamic energy throughout their lifecycle, even though they lose a large amount of heat as they travel long distances from their origin towards the Arctic. For a given region in the high latitudes (e.g., the Barents Sea), the mean vertical profiles of temperature and moisture from the HL group are colder and drier compared to the ones from the ML group, but the maximum values in the HL group can reach those of the ML group. Further analysis for the top 10% warmest profiles in the HL group suggests that these HL cyclones form in a preconditioned warm and moist environment. The precondioning is set up by the large-scale circulation with influences from the upstream North Atlantic. Under special conditions, the formation of high latitude cyclones in a preconditioned warm and moist environment can lead to extreme warming events in the deep Arctic like the one during New Year’s 2015/16.

How to cite: Tao, D., Li, C., Davy, R., He, S., Michel, C., and Rosendahl, A.: The thermodynamic differences between winter cyclones from midlatitudes and high latitudes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1890, https://doi.org/10.5194/egusphere-egu23-1890, 2023.

EGU23-2195 | ECS | Orals | AS1.14

Origin of low-tropospheric potential vorticity in Mediterranean cyclones 

Alexander Scherrmann, Emmanouil Flaounas, and Heini Wernli

Mediterranean cyclones are extratropical cyclones, typically of smaller size and weaker intensity than other cyclones that develop over the main open ocean storm tracks. Nevertheless, Mediterranean cyclones can attain high intensities, even comparable to the ones of tropical cyclones, and thus cause large socio-economic impacts in the densely populated coasts of the region. After cyclogenesis takes place, a large variety of processes are involved in the cyclone’s development, contributing with positive and negative potential vorticity (PV) changes to the lower-tropospheric PV anomalies in the cyclone center. Although the diabatic processes that produce these PV anomalies in Mediterranean cyclones are known, it is still an open question whether they occur locally within the cyclone itself or remotely in the environment (e.g., near high orography) with a subsequent transport of high-PV air into the cyclone center. This study introduces a Lagrangian method to determine the origin of the lower-tropospheric PV anomaly, which is applied climatologically to ERA5 reanalysis and to 12 monthly simulations, performed with the IFS model. We define and quantify so-called "cyclonic" and "environmental" PV and find that the main part of the lower-tropospheric PV anomaly (60%) is produced within the cyclone, shortly prior (-12 h) to the cyclones’ mature stage. Nevertheless, in 19.5% of the cyclones the environmental PV production near the mountains surrounding the Mediterranean basin plays a significant role in forming the low-tropospheric PV anomaly, and therefore in determining the intensity of these cyclones. The analysis of PV tendencies from the IFS simulations reveals that the major PV production inside the cyclone is typically due to convection and microphysics, whereas convection and turbulent momentum tendencies evoke most of the positive PV changes in the environment.

How to cite: Scherrmann, A., Flaounas, E., and Wernli, H.: Origin of low-tropospheric potential vorticity in Mediterranean cyclones, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2195, https://doi.org/10.5194/egusphere-egu23-2195, 2023.

EGU23-4675 | ECS | Posters on site | AS1.14

Storms and associated damages in Norway 

Ashbin Jaison, Asgeir Sorteberg, Clio Michel, and Øyvind Breivik

Extreme winds account for more than half of Norway’s insurance claims related to natural hazards [1]. Quantifying windstorm-damage relations is crucial to prepare for and mitigate the effects of future wind events. However, there has never been an attempt to quantify windstorm-damage relations at the municipality level in Norway. The work in hand employs four different damage functions at the municipality level of Norway. Along with the newly proposed modified Prahl damage function [2], an ensemble means of the damage estimates are tested for 356 municipalities in Norway. We evaluate the damage functions in terms of forecast accuracy. The spatial distribution of losses suggests severe damages along the west coast of Norway. Further inland in Norway, there are seldom any losses due to Norway’s unique topography and demography. The losses above the 99.7th percentile in each municipality constitute 85% of total national loss, and we focus on this extreme loss class. A significant agreement between the observed and estimated losses at the municipality and national levels indicates that the damage functions are suited for forecasting storm-induced damages. The damage functions are also able to successfully reconstruct the spatial spread and pattern of losses caused by very extreme windstorms.

References

1] Finance Norway, Natural Disaster Statistics (NASK), (2019)
[2] B.F. Prahl et al., Applying stochastic small-scale damage functions to German winter storms, Geophysical Research Letters 39, (2012)

 
 

How to cite: Jaison, A., Sorteberg, A., Michel, C., and Breivik, Ø.: Storms and associated damages in Norway, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4675, https://doi.org/10.5194/egusphere-egu23-4675, 2023.

EGU23-5690 | ECS | Posters on site | AS1.14 | Highlight

Investigating the predictability of Mediteranean cyclones and their severity 

Benjamin Doiteau, Florian Pantillon, Matthieu Plu, Laurent Descamps, and Thomas Rieutord

Cyclones are essential elements of the climate and of the water cycle in the Mediterranean. The most intense of them lead to natural disasters because of their violent winds and extreme rainfall, which can cause significant damage to the territories bordering the Mediterranean (coast and mountain ranges). Reliable forecasts of cyclones are therefore essential to better anticipate and prevent their societal impact. However, their predictability is often limited by their particularities: smaller cyclones with a shorter life cycle than in the North Atlantic, complex topography, interactions with the relatively warm sea and air masses laden with dust from the Sahara.

We investigate the predictability of Mediterranean cyclones in a systematic framework using an ensemble prediction system. A reference dataset was first obtained by tracking cyclones in the ERA5 reanalysis (1979-2021), using an algorithm developped for the North Atlantic and adapted for the Mediterranean region. We then investigated the predictability using ARPEGE ensemble reforecasts in a homogeneous configuration over 22 years (2000-2021).

We restricted the study on 500 cases, which were selected using a storm severity index based on wind gusts and adapted for the Mediterranean region. The cases were then divided in several categories following their dynamical context, their intensity and their geographical origin. The predictability of the reforecasts was finally quantified on each of those categories, using probabilistic scores on cyclone trajectories (along and cross track error) and on intensities (mean sea level pressure and storm severity index).

While past studies have been limited by the fact that regular updates of operational forecasting systems do not allow the predictability of cases to be compared with each other, the homogeneous configuration of the ARPEGE ensemble reforecasts makes it possible to systematically identify the limitation to the predictability of Mediterranean cyclones.

How to cite: Doiteau, B., Pantillon, F., Plu, M., Descamps, L., and Rieutord, T.: Investigating the predictability of Mediteranean cyclones and their severity, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5690, https://doi.org/10.5194/egusphere-egu23-5690, 2023.

A large number of intense cyclones occur every year in the Mediterranean basin, a relatively small and densely populated region, but also a worldwide climate-change hotspot. Given their importance for the variability of the regional climate and its extremes, Mediterranean cyclones have lately attracted much of attention, especially due to the broad range of severe socio-economic and environmental impacts that they produce.

This talk aims at summarizing the concentrated knowledge of the last decade on the dynamics, climatology and relevant impacts of Mediterranean cyclones. We will especially focus on the processes that take place in different spatiotemporal scales triggering cyclogenesis and turning Mediterranean cyclones into catastrophic storms. We will also discuss the role of the unique regional geographical features therein, along with the influence of the latitudinal location of the Mediterranean basin. Finally, we will discuss the different subtypes of Mediterranean cyclones that develop in the region, devoting special attention to medicanes, i.e. cyclones with tropical characteristics and subjects of numerous recent studies. Througout the talk, research perspectives that advance the field of Mediterranean cyclones as a whole will be highlighted, along with current trends in community efforts within the framework of MedCyclones COST Action that address relevant topics to the complex dynamics of Mediterranean cyclones and consequent severe socio-economic impacts.

How to cite: Flaounas, E.: Mediterranean cyclone dynamics and climatology: current knowledge and research perspectives, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6278, https://doi.org/10.5194/egusphere-egu23-6278, 2023.

EGU23-6570 | Posters on site | AS1.14

Cloud-radiative heating shapes idealized extratropical cyclones by changing atmospheric stability 

Aiko Voigt, Behrooz Keshtgar, and Klara Butz

"All models are wrong. Some are wrong in a useful manner.” (adapted by the authors from George Box) In this presentation, we utilize an error in the surface flux formulation of the ICON-NWP numerical weather prediction model to elucidate how cloud-radiative heating affects the intensity of idealized extratropical cyclones.

We present idealized baroclinic life cycle simulations with two versions of the global atmosphere model ICON-NWP. Both versions simulate the same cyclone when run without radiative heating, but disagree when cloud-radiative heating is allowed to affect atmospheric temperature and the cyclone evolution. In version 2.1, taking into account cloud-radiative heating leads to a weaker cyclone, while in version 2.6 a stronger cyclone results. The simulations use a new modeling technique for which only cloud-radiative heating interacts with the cyclone and clear-sky radiative heating is omitted. The technique circumvents changes in the mean state due to clear-sky radiative heating that has complicated the interpretation of previous work.

A defining difference between the two model versions is the amount of simulated low-level clouds. Compared to version 2.6, version 2.1 simulates twice as many low-level clouds and a twice as strong cooling of the planetary boundary layer by cloud-radiative heating. While the increase in low-level clouds is tied to an error in the surface flux formulation in version 2.1 that was corrected in version 2.6, the error provides an opportunity to probe the impact of cloud-radiative heating in the boundary layer (below 2 km) versus the free-troposphere (above 2 km). Sensitivity studies show that negative cloud-radiative heating in the boundary layer from the tops of low-level clouds weakens the cyclone by making the atmosphere more stable. At the same time, they show that negative cloud-radiative heating near the tropopause from the tops of high-level clouds strengthens the cyclone by decreasing atmospheric stability. The changes in stability are particularly evident in regions of upward motion.

Overall, our results indicate that the vertical distribution of clouds and their radiative heating are an important factor for the dynamics of extratropical cyclones and that model differences in the simulation of low-level clouds can translate to model differences in cyclone intensity.

How to cite: Voigt, A., Keshtgar, B., and Butz, K.: Cloud-radiative heating shapes idealized extratropical cyclones by changing atmospheric stability, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6570, https://doi.org/10.5194/egusphere-egu23-6570, 2023.

EGU23-6629 | ECS | Posters on site | AS1.14

Effects of climate variability and change on cyclones in the Mediterranean 

Onno Doensen, Martina Messmer, Woon Mi Kim, and Christoph Raible

The Mediterranean is characterized by a high extratropical cyclone activity. These cyclones are an important source for water availability in the region, but at the same time they have the potential to cause extreme weather in the form of precipitation and wind extremes. The Mediterranean is heavily affected by the ongoing anthropogenic climate change, which is expected to have a profound effect on cyclones in this area. In this study, we investigate the effects of internal climate variability and anthropogenic climate change on the characteristics of Mediterranean cyclones. The analysis is based on two simulations from the Community Earth System Model 1.2 (CESM): a seamless simulation spanning 3500 years from 1500 BCE to 2012 CE and a simulation of future RCP8.5 scenario from 2013 to 2300 CE. The simulations have a 1.9°x2.5° horizontal resolution, and cyclones are identified using an established detection and tracking algorithm. Comparison with the ERA5 reanalysis for the period 1981–2010 shows that CESM is able to realistically represent cyclone frequency on a global scale, though it slightly underestimates cyclone activity in the Mediterranean. Our results indicate that cyclone activity in the Mediterranean varies on interdecadal to centennial time scales before 1850 CE. These variations are linked to positive and negative climate anomalies and fluctuations in strength of several modes of circulation, such as the North Atlantic Oscillation. The variations caused by internal variability are, however, of smaller magnitude than the effects of future climate change on the Mediterranean cyclones. In the RCP8.5 scenario, Mediterranean cyclones will become less frequent based on our simulation, and cyclone related precipitation will decrease in addition to that, which is contrary to what is being observed in other important storm track regions, such as the North Atlantic. We hypothesize that the changes in cyclone characteristics are more pronounced in the Western Mediterranean than in the Eastern Mediterranean. Overall, the study suggests that cyclone activity in the Mediterranean is projected to leave the bandwidth of variability of the last 3500 years near the end of the century.

How to cite: Doensen, O., Messmer, M., Kim, W. M., and Raible, C.: Effects of climate variability and change on cyclones in the Mediterranean, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6629, https://doi.org/10.5194/egusphere-egu23-6629, 2023.

Extratropical cyclone airstreams, such as warm conveyor belts (WCBs), are linked to strong precipitation along with latent heat release at low levels and, thus, changes in the low-level PV distribution. Previous studies have shown significant changes in PV anomalies in a future climate under the RCP8.5 scenario, which are also associated with changes in strong near-surface winds. However, the source of these PV anomalies is still unclear, especially at upper levels. Based on the 1% strongest winter-cyclones in the North Atlantic (NA) region over the two periods 1990-2000 and 2091-2100, we adopt a Lagrangian perspective to investigate such changes in CESM Large Ensemble simulations.
Backward trajectories are computed to explicitly identify the contributions of diabatic processes to future changes in cyclone-associated PV anomalies. Moreover, the role of specific airstreams in PV generation/destruction is examined with Lagrangian composites.
The results show a sinificant change in the mean trajectory properties 24 hours before the maximum cyclone intensity at low and upper levels. This period of 24 hours is taken to construct Lagrangian composites at 700 hPa and 250 hPa, which provide insights into changes in WCB and dry intrusion (DI) airstreams. We further analyze these airstrem changes by constructing cross sections downstream (WCB regime) and at the equatorward side (DI regime) of the cyclone center.
In general, increased diabatic heating along backward trajectories amplifies positive PV anomalies near the cyclone center at both lower and upper levels in a warmer future climate. More specifically, a poleward and upward shift of the WCBs with a larger PV production at middle levels are is found. DIs near the cyclone center are projected to be responsible for stronger PV production at low levels to the south of the cyclone center. At upper levels, the decreased PV anomaly to the south of the cyclone center results from a combined effect of a decreased climatological PV in the NA region and a shift in the origin of the air masses. The increasing importance of diabatic processes in a wamer climate suggests that a better representation of these processes in climate models is necessary to reduce uncertainties.

How to cite: Dolores-Tesillos, E. and Pfahl, S.: Future changes in North Atlantic winter cyclones in CESM-LE simulations from a Lagrangian-composite perspective, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6851, https://doi.org/10.5194/egusphere-egu23-6851, 2023.

EGU23-7236 | ECS | Posters on site | AS1.14

Objective assessment of storm surge risk in the German Bight – historical events and future climate change 

Laura Schaffer, Nico Becker, Ludwig Schenk, Claudia Hinrichs, Gabriel Ditzinger, Nils H. Schade, Daniel J. Befort, and Tim Kruschke

Storm surges in the German Bight can have great destructive potential. This includes devastating floods, structural damage to infrastructure, and even loss of life. The most important driver of storm surge events in the German Bight is strong winds from north-westerly directions, often related to intense extra-tropical cyclones travelling from the North Atlantic into the North Sea region.

Making use of an objective, impact-oriented identification and tracking scheme, we analyse storm events related to storm surges in the German Bight. This particular version of the tracking algorithm includes the so-called Storm Surge Severity Index (SSSI) and is used as a complementary tool in operational forecasting by the German Federal Maritime and Hydrographic Agency (BSH). The SSSI takes wind speed and direction into account and intends to quantify storm surge risk in the German Bight. However, to date, the SSSI has never been systematically evaluated for past storm surge events. To fill this gap and to prove that the SSSI can be used as a proxy for storm surge risk, we analyse the relationship between SSSI values of past storm events and the associated water levels recorded in the German Bight using ERA5 atmospheric reanalysis data. Moreover, we analyse potentially storm surge-relevant storms in a multi-model ensemble of global climate model simulations to assess potential future changes in storm surge risk in the German Bight.

How to cite: Schaffer, L., Becker, N., Schenk, L., Hinrichs, C., Ditzinger, G., Schade, N. H., Befort, D. J., and Kruschke, T.: Objective assessment of storm surge risk in the German Bight – historical events and future climate change, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7236, https://doi.org/10.5194/egusphere-egu23-7236, 2023.

EGU23-8826 | ECS | Orals | AS1.14

Global climatology of cyclone clustering in present and future climates 

Chris Weijenborg, Thomas Spengler, and Matthew Priestley

Cyclone clustering, the swift succession of multiple extratropical cyclones in a geographically confined region during a short period of time, constitutes a large fraction of European weather extremes. The idea that several cyclones follow a similar track dates back to the centennial concept of cyclone families of Bjerknes and Solberg. To investigate the dynamical causes of cyclone clustering, it is necessary to diagnose the occurrence of cyclone clustering and to determine their characteristics. So far, most diagnostics focused either on local impact or on a statistical analysis of storm recurrence. While the first cannot be applied globally, the latter is difficult to relate to individual events. We therefore use a novel method to globally detect cyclone clustering that is closer to the original concept of Bjerknes and Solberg, where extratropical cyclones follow similar tracks within a given time period.

Using this novel cyclone clustering diagnostic based on spatio-temporal distance between cyclone tracks, we analyse cyclone clustering globally in Era-Interim for the period 1979 until 2016 as well as for 10 CMIP6 models. We separate the cyclone clusters into two types: one representing the ‘classical’ bjerknes-type clusters, and one representing more stationary clusters. We find that cyclone clustering mainly occurs along the climatological storm tracks, with the bjerknes-type more common at the western side of the storm tracks, while the stationary-type of cyclone clusters occurs more downstream. In general, clustered cyclones are stronger than non-clustered cyclones. While CMIP6 models feature a slight bias towards an equatorward shift of the storm tracks, cyclone clustering in a future climate occurs more poleward. Furthermore, the average number of storms per cluster decreases in a future climate, though the mean intensity of the cyclones that are clustered increases slightly.

How to cite: Weijenborg, C., Spengler, T., and Priestley, M.: Global climatology of cyclone clustering in present and future climates, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8826, https://doi.org/10.5194/egusphere-egu23-8826, 2023.

EGU23-9393 | ECS | Orals | AS1.14

Growing Pacific Linkage with Western North Atlantic Explosive Cyclones 

Jacob Stuivenvolt-Allen, Simon S.-Y. Wang, Yoshimitsu Chikamoto, Jonathan Meyer, and Zachary Johnson

Explosive cyclones (ECs), defined as developing extratropical cyclones that experience pressure drops of at least 24 hPa in 24 hours, are impactful weather events which occur along highly populated coastal regions in the eastern United States. These storms occur due to a combination of atmospheric and surface processes, such as jet stream intensification and latent heat release. Even though previous literature has elucidated the role of these processes in EC formation, the sources of interannual variability that impact seasonal EC frequency are not well known. To analyze the sources of interannual variability, we track cases of ECs and dissect them into two spatial groups: those that formed near the east coast of North America (coastal) and those in the North Central Atlantic (high latitude). The frequency of high-latitude ECs is strongly correlated with the North Atlantic Oscillation, a well-known feature, whereas coastal EC frequency exhibits a growing relationship with an atmospheric wave-train emanating from the North Pacific in the last 30 years. This wave-train pattern of alternating high-and-low pressure resulted in heightened upper-level divergence and baroclinic instability along the east coast of North America. Using a coupled model experiment, we show that the tropical Pacific Ocean and North Pacific oceans are the main driver of this atmospheric wave train and the subsequent enhancement seasonal baroclinic instability in the North Atlantic.

How to cite: Stuivenvolt-Allen, J., Wang, S. S.-Y., Chikamoto, Y., Meyer, J., and Johnson, Z.: Growing Pacific Linkage with Western North Atlantic Explosive Cyclones, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9393, https://doi.org/10.5194/egusphere-egu23-9393, 2023.

EGU23-9411 | ECS | Posters on site | AS1.14

Explosive Cyclones in the Mediterranean Sea exploiting ERA5 dataset: detection, classification, statistical and synoptic analysis of their occurrance 

Cosimo Enrico Carniel, Rossella Ferretti, Antonio Ricchi, Gabriele Curci, Mario Marcello Miglietta, Marco Reale, Piero Serafini, Evan David Wellmeyer, and Dino Zardi

In the semi-enclosed basin of the Mediterranean Sea, a wide variety of cyclone mechanisms are known to develop, including baroclinic waves coming from the Atlantic, Mediterranean cyclones originating from the cut-off of baroclinic waves, Warm Seclusions, Tropical-Like Cyclones (TLC), Rapid-Cyclogeneses (RC) and Intense Mediterranean Cyclones (IMC). Depending on the cyclone's type, the characteristic frequency of appearance can vary, ranging from tens per month to around 1-1.5 per year, as in the TLC case. RCs are among the rarest and probably most intense and destructive cyclone events that can develop in nature; they usually originate at high latitudes, during wintertime, and mainly over the sea, preferring areas with high Sea Surface Temperature (SST) gradients. It is generally accepted that these events are described by quick drop of pressure, close to 1hPa/hr for 24 hours, within the eye of the cyclone. Several recent studies investigated the formation of RC’s over Mediterranean Basin (MB). RCs formation is an extremely complicated process, and in the MB  it is mostly driven by dry air intrusions from the stratosphere and by the trigger of Atmospheric Rivers.

Using ERA5 dataset, we firstly conducted a physical and dynamical analysis of the most intense cyclone events occurred in the Mediterranean basin in the period 1979-2020, identifying factors which triggered, generated and contributed to the intensification of such events. According to Sanders’ and Gyakum’s definition of Bergeron, a parameter which describes RCs’ deepening rate and varies from 28mb/(24h) at the pole to 12 mb/(24h) at latitude 25°N, we were able to classify them in the three aforementioned categories. With the help of EOF analysis, we outlined synoptic configuration more likely to drive the phenomena, highlighting the role of SCAND index and NAO-. Moreover, we have investigated the deepening with a new promising approach involving the use of 6 hours timespans, in order to single out the cyclones with higher gradients of pressure and faster evolution in semi enclosed basins. Further analysis is being undertaken to determine the cyclones’ phase and their main morphological characteristics, as well as their correlation with atmospheric rivers and SST anomalies exhibited by the Central Mediterranean Basin.

How to cite: Carniel, C. E., Ferretti, R., Ricchi, A., Curci, G., Miglietta, M. M., Reale, M., Serafini, P., Wellmeyer, E. D., and Zardi, D.: Explosive Cyclones in the Mediterranean Sea exploiting ERA5 dataset: detection, classification, statistical and synoptic analysis of their occurrance, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9411, https://doi.org/10.5194/egusphere-egu23-9411, 2023.

EGU23-10041 | ECS | Posters on site | AS1.14

Tropical and extratropical circulation biases and the Southern Hemisphere Hadley cell width 

Pia Freisen, Julie Arblaster, Christian Jakob, and José Rodriguez

The widening of the Southern Hemisphere tropical meridional circulation has been attributed to various forcings from increased greenhouse gases, ozone depletion and natural variability. While climate models can reproduce some characteristics of this observed change, there is some uncertainty in the operating mechanisms and driving regions setting the edge of the tropical circulation. Here we examine the impacts of systematic model biases of the atmosphere-only Unified Model onto the simulation of the Southern Hemisphere tropical extent. We utilise nudging experiments with prescribed sea-surface temperatures, where potential temperature and horizontal winds are relaxed back to reanalysis for a 20-year period. Specifically, experiments with regionally-defined bias correction aide to determine the influence of remote model biases on the tropical width. The experiments are applied to different tropical width metrics previously identified to measure the boundary between the tropical to extratropical circulation. We uncover a more consistent improvement of the location of the Hadley cell edge by correcting Southern Hemisphere extratropical circulation biases, than tropical ones. The analysis is further expanded to the range of atmosphere-only model simulations of the Coupled Model Intercomparison Project Phase 6 (CMIP6). We explore the relationships between tropical and extratropical biases and the models’ representation of the Hadley cell.

How to cite: Freisen, P., Arblaster, J., Jakob, C., and Rodriguez, J.: Tropical and extratropical circulation biases and the Southern Hemisphere Hadley cell width, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10041, https://doi.org/10.5194/egusphere-egu23-10041, 2023.

EGU23-10466 | Posters on site | AS1.14

Extratropical storm track activity change in future climate change scenarios 

Ui-Yong Byun, Eun-Chul Chang, Joowan Kim, Donghyun Cha, Joong-Bae Ahn, and Seung-Ki Min

In the mid-latitudes, synoptic-scale phenomena like high and low-pressure systems generate the variability of the regional-scale weather system. To identify the weather variability of extra-tropical region storm track activity has been analyzed based on observations since the mid-nineteenth century. After early-stage research that directly counted the movement of cyclones, the time filtering method based on grid analysis has been used for an isolated disturbance with periods of 2~7 days. This bandpass filtering method has the advantage of being able to examine the distribution and the variability of the storm track spatially in vertical and horizontal space.

In this study, we confirm the storm track activity in the East Asia region using the dynamical down-scale results from CORDEX (COordinated Regional climate Downscaling EXperiment) East Asia projects. We verify the reproducibility and confirm the temporal change in the storm track activity from various RCM data. In addition to the historical period, we examine the difference in storm track intensity over future climate change scenarios. Through this, we also discuss the role of added value from RCM.

 

This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMI2022-01210.

How to cite: Byun, U.-Y., Chang, E.-C., Kim, J., Cha, D., Ahn, J.-B., and Min, S.-K.: Extratropical storm track activity change in future climate change scenarios, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10466, https://doi.org/10.5194/egusphere-egu23-10466, 2023.

EGU23-10857 | ECS | Posters on site | AS1.14

An assessment of extreme precipitation within cyclone composites using ERA5 

Cameron McErlich, Adrian McDonald, and James Renwick

Extra-tropical cyclones are key components of the atmospheric general circulation due to their ability to transport large quantities of heat, moisture, and momentum. Cyclones are an important contributor to extreme weather as their passage is associated with strong winds, and large precipitation accumulations. Here we connect a cyclone compositing scheme with regionally derived distributions of precipitation to present a framework for classifying spatially dependent extremes relative to the cyclone centre. Using this framework, cyclone composites for both average (50th percentile) and extreme (90th and 98th percentile) precipitation are derived from ERA5 reanalysis output. Composites are then partitioned into different stages of the cyclone lifecycle to assess the spatial and temporal evolution of precipitation extremes. We find that most extreme precipitation occurs within the comma-cloud structure close to the cyclone centre, with the extreme precipitation occurrence and intensity occurring in that region. Extreme precipitation is also identified to be largest during the period of deepening before the maximum cyclone intensity is reached. These regions of the cyclone correspond to places where large fractions of precipitation are above the extreme threshold. Strong spatial correlation are also seen between the average and extreme precipitation during the deepening phase for the precipitation mean, occurrence and fraction. This correlation weakens as the cyclone evolves and as the threshold used to determine extreme precipitation increases.

How to cite: McErlich, C., McDonald, A., and Renwick, J.: An assessment of extreme precipitation within cyclone composites using ERA5, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10857, https://doi.org/10.5194/egusphere-egu23-10857, 2023.

EGU23-12391 | ECS | Posters on site | AS1.14

High-resolution loss modeling for European Windstorms 

Dhirendra Kumar, Len Shaffrey, Richard Dixon, Hannah Bloomfield, Paul Bates, and John Hillier

European windstorms are a frequent and damaging natural hazard that can cause loss of human life and damage to property and infrastructure. As there is a high degree of uncertainty in climate projections, it is crucial to understand the physical risks and economic losses at regional and local scales associated with European Windstorms. In this study, we develop a simple model to estimate historical windstorm losses over the European region. The model uses winds from the ERA5 reanalysis and different exposure datasets based on countrywide total insured property values, gross domestic product, and historical population density.

We find that the estimated losses associated with major historical storms in North-western Europe and estimated average EU-wide losses are comparable to the reported estimates and those from propriety vendor models. However, estimated losses from windstorms in France and Germany are lower than reported. Differences in the estimated losses are attributed to the contrasts in the regional-level exposure within and between different exposure datasets. We also tested the sensitivity of regional-level vulnerabilities and find that accounting for regional-level vulnerability differences slightly improves the biases in countrywide losses. Further, we also find that the major contribution to the estimated losses comes from the United Kingdom, France, and Germany for most of the storm seasons, and thus it is important to correctly represent the exposure and vulnerabilities over these countries. The ability of the model to estimate reported losses is also limited by the representation of the winds in ERA5, which has limited skill in representing the hazard footprint, especially for specific storms such as the Great October Storm of 1987.

Keywords: Losses, Windstorms, Climate Change, Natural Hazards

How to cite: Kumar, D., Shaffrey, L., Dixon, R., Bloomfield, H., Bates, P., and Hillier, J.: High-resolution loss modeling for European Windstorms, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12391, https://doi.org/10.5194/egusphere-egu23-12391, 2023.

EGU23-12526 | ECS | Posters virtual | AS1.14

Volcanically induced increase in extra-tropical cyclone frequency 

Laurits Andreasen, Joona Corner, Peter Abbott, Victoria Sinclair, Felix Riede, and Claudia Timmreck

Volcanic eruptions are well known to influence Earth's temperature, however, how eruptions influence the atmosphere's circulation pattern, especially on the scale of everyday weather is poorly understood. Changing Earth's temperature can affect temperature gradients which in turn could affect baroclinicity and hence high- and mid-latitude weather. Yet, to what extent volcanic eruptions do in fact exert  such an influence is not clear.

To answer this, we followed two independent lines of investigation: First, we query the Greenland ice-core proxy record for Indications of increased extra-tropical cyclone frequency that correlates with evidence for volcanism. This is done by comparing the storm proxy sea salt (a substance transported to the ice sheet by wind)  with the volcanological proxy sulfur. Secondly, we simulate eruptions with the MPI-ESM1.2 Earth System Model and use the TRACK algorithm to explore how extra-tropical cyclone frequency is affected in the model  experiments. Both approaches suggest that volcanic eruptions impact high- and mid-latitude weather by increasing the number of extra-tropical cyclones especially at higher latitudes. A detailed interrogation of the simulated eruption scenarios suggests that this increase in cyclone frequency is associated with features such as an increase in isentropic slopes and sea-ice extent most commonly found under  colder climate regimes and is the reverse of what one finds in more equable climates such as that projected for the future.

How to cite: Andreasen, L., Corner, J., Abbott, P., Sinclair, V., Riede, F., and Timmreck, C.: Volcanically induced increase in extra-tropical cyclone frequency, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12526, https://doi.org/10.5194/egusphere-egu23-12526, 2023.

EGU23-13180 | ECS | Posters on site | AS1.14

Drivers of large footprints of extreme winds and rainfall and their projected future changes 

Colin Manning, Elizabeth Kendon, Hayley J. Fowler, Jennifer L. Catto, Steven C. Chan, and Philip Sansom

Extratropical cyclones produce extreme surface wind speeds and heavy rainfall which can individually and jointly influence impacts and potentially produce large aggregate impacts. Within this study, we assess the UKCP 12-member ensemble of local convection-permitting 2.2 km climate projections. We quantify the likelihood of cyclones producing large footprints of both extreme winds and rainfall over the UK in a control (1981-2000) and future (2061-2080, RCP8.5) climate simulation. Following this, we characterise the convective and frontal drivers of wet and windy conditions within cyclones, and identify the characteristics of cyclones, their tracks and interactions with the jet stream that contribute to the occurrence of large, combined footprints in the control and future simulations. The future simulations project an increased probability of extratropical cyclones producing extremely wet and windy conditions in the same storm, as well as an increase in the land area covered by such conditions. In both the control and future simulations, combined wet and windy extremes largely occur close to cold and warm fronts, likely due to the warm conveyor belt which produces heavy rainfall (due its ascent over the frontal boundaries) and high winds (when occurring within a region of tight pressure gradients). Cyclone composites reveal that the largest changes in joint extremes are closely located within the sector of cyclones where we expect to see the warm conveyor belt, suggesting their change arises partly through the response of this shared driver rather than being a simple consequence of increased rainfall due to thermodynamics. In further analysis, we identify favourable conditions and cyclone characteristics that lead to cyclones producing large rainfall and wind footprints over the UK.

How to cite: Manning, C., Kendon, E., Fowler, H. J., Catto, J. L., Chan, S. C., and Sansom, P.: Drivers of large footprints of extreme winds and rainfall and their projected future changes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13180, https://doi.org/10.5194/egusphere-egu23-13180, 2023.

EGU23-13914 | Posters on site | AS1.14

Decadal variability of extreme winds and potential storm losses in Europe using large RCM ensembles 

Jisesh Sethunadh, Joaquim G. Pinto, Patrick Ludwig, Hendrik Feldmann, and Florian Ehmele

Windstorms (major winter storms) are one of the most important natural hazards in Europe. Despite the large observed socioeconomic losses, the impact of windstorms and its decadal variability is not yet fully understood. This study aims to assess the loss potentials associated with European windstorms and the variability in the wind speed climatology across Europe. We use the 12,500-years LAERTES-EU (LArge Ensemble of Regional climaTe modEl Simulations for EUrope) RCM ensemble to study the spatio-temporal distribution and variability of windstorms over Europe. LAERTES-EU is validated against reanalysis data (ERA5) and available ground-based station observations. The associated windstorm losses are estimated by computing statistics of extreme wind speeds and related indices. Different loss indices are validated using historical loss data from the insurance sector. The results reveal that the loss index (LI) is a good proxy for the estimation of potential losses associated with windstorms across Europe in winter. The derived statistics of extreme windstorms such as return periods (RP) show hardly any change in the severity and frequency of windstorms during the covered period 1900-2028, but a strong decadal variability is apparent.

How to cite: Sethunadh, J., Pinto, J. G., Ludwig, P., Feldmann, H., and Ehmele, F.: Decadal variability of extreme winds and potential storm losses in Europe using large RCM ensembles, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13914, https://doi.org/10.5194/egusphere-egu23-13914, 2023.

EGU23-13929 | ECS | Posters on site | AS1.14

European windstorm risk at the regional scale under recent and future climate conditions 

Inovasita Alifdini, Julia Moemken, and Joaquim G. Pinto

European windstorms are among the natural hazards with the highest economic losses. We investigate the impact of European windstorms under recent and future climate conditions at high spatial resolution. With this aim, we use hourly surface wind data at 30 km resolution from ERA5 reanalysis for 1959-2021, and 3-hourly surface wind data at 12.5 km resolution from 60 different global-to-regional climate model (GCM-RCM) chains from EURO-CORDEX (EUR-11). The windstorm activity is compared in 30-year periods from the historical events (1976-2005) to the future events (under RCP8.5 scenario) at global warming levels (GWL) of +2°C and +3°C.  We apply different indices (meteorological index and loss index) to quantify the severity of windstorms and to estimate the corresponding impacts. For the historical period, storm Wiebke in 1990 (storm names as used by the German Weather Service DWD) caused the highest loss for Central Europe, followed by storm Lothar in 1999. The United Kingdom and Germany are countries in Central Europe that have the highest loss index (more vulnerable to the European windstorms). The results from the EURO-CORDEX ensemble show only small changes in windstorm activity between the historical period and the different GWLs, but display decadal variability.

How to cite: Alifdini, I., Moemken, J., and Pinto, J. G.: European windstorm risk at the regional scale under recent and future climate conditions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13929, https://doi.org/10.5194/egusphere-egu23-13929, 2023.

EGU23-14410 | ECS | Posters on site | AS1.14

Estimating worst-case European windstroms, and worst-case seasons, using seasonal forecasts. 

Jacob Maddison, Jennifer Catto, Stefan Siegert, and Sandra Hansen

Windstorms pose continual risk to Europe. Among their associated hazards, strong near-surface winds can be particularly damaging, threatening infrastructure, life and billions of pounds in insured losses. Insurers (and reinsurers) therefore need to prepare for the potential cost of extreme windstorms. Storm severity indices (SSIs) have been developed to quantify the potential losses associated with windstorm winds. Here, the most extreme windstorms that could potentially occur in the current climate are estimated using seasonal forecast data together with a cyclone-tracking algorithm, and their potential losses quantified using an SSI. As maximum wind gusts, the typical input variable for SSIs, are not available in the seasonal forecast dataset, a method is developed to calculate SSIs using wind speed data and a bias correction used to convert to SSI values representative of those obtained when calculated using wind gusts. Nearly 700 extended winter seasons of forecast data are analysed, representing a much larger sample of potential windstorms compared to that available from reanalysis or observational products. The storm track is reasonably well represented in the seasonal forecast data: spatial features are similar to those in a reanalysis, but there exists a slight poleward bias and underestimation of number of storms per season (maximal underestimation of around 10%). Additionally, distributions of SSI values for several countries in Europe are similar in the forecast data and reanalysis. Together, these suggest that the seasonal forecast data is suitable for analysing windstorm statistics and informing on potential extreme storms. We give estimates of worst-case storms, and worst-case seasons, that are identified in the forecast data and compare to those seen in a reanalysis, highlighting the potential insurance loss implications.

How to cite: Maddison, J., Catto, J., Siegert, S., and Hansen, S.: Estimating worst-case European windstroms, and worst-case seasons, using seasonal forecasts., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14410, https://doi.org/10.5194/egusphere-egu23-14410, 2023.

EGU23-14446 | ECS | Orals | AS1.14

A framework for understanding the correlation between aggregated losses of compound events 

Toby Jones, David Stephenson, and Matthew Priestley

The risk from individual natural hazards (such as extratropical cyclones) can be large, but the aggregate loss over yearly timescales is significantly greater. For example, wind damage from the three major European windstorms in February 2022 caused more than €3.5 billion of insured losses.

This study proposes a random sum modelling framework for understanding the correlation between aggregate risks that occur from compound events. By considering the frequency and intensities of compound events as random variables, the framework provides an expression for correlation between two random sums (which each represent different types of loss from compound events).

The framework shows that this correlation will generally increase monotonically towards one as the dispersion (clustering) of the number of events increases. Under certain conditions, the correlation will always monotonically increase with dispersion.

The framework has been illustrated by applying it to annual sums from 1980-2020 using wind speed and precipitation as proxy measures for insured loss. This is calculated from ERA5 reanalysis data which includes 39587 storm events and covers the European region and Atlantic Ocean (from 30°N 100°W to 75°N 40°E).

The framework performs well, capturing the general behaviour of the correlation, with large positive correlation over the N. Atlantic Ocean and weaker correlations over European land regions.

How to cite: Jones, T., Stephenson, D., and Priestley, M.: A framework for understanding the correlation between aggregated losses of compound events, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14446, https://doi.org/10.5194/egusphere-egu23-14446, 2023.

EGU23-14695 | Posters on site | AS1.14

Assessing the boundaries of seasonal forecast skill for European winter storms from different hindcast suites 

Gregor C. Leckebusch, Lisa Degenhardt, Elleanor Berrie, Kelvin S. Ng, and Elisa Spreitzer

European winter storms are a significant threat to communities, public infrastructure, and private and commercial properties. On seasonal timescales, potential predictability was evidenced in recent state-of-the-art seasonal hindcast suites e.g., the UK Met Office’s GloSea5. Related positive and potentially usable forecast skill for frequency and intensity measures were based on pre-season model initialisation around the beginning of November for the following core winter (DJF) season’s assessment.

This study expands on these findings by analysing extended lead times of seasonal forecast into autumn and late summer before the winter season. Here, in a systematic way, a multi-model ensemble of hindcasts is analysed to evaluate current models’ capability to forecast the seasonal activity for initialisations from September to November. First results indicate potential predictability precursors already from the September initialisations for storm frequencies. These results vary from model to model though. The presentation will discuss differences between models as well as lead times for both, storm frequency and intensity.

How to cite: Leckebusch, G. C., Degenhardt, L., Berrie, E., Ng, K. S., and Spreitzer, E.: Assessing the boundaries of seasonal forecast skill for European winter storms from different hindcast suites, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14695, https://doi.org/10.5194/egusphere-egu23-14695, 2023.

EGU23-408 | ECS | Posters on site | CL2.2

El Niño Southern Oscillation influence over the Orinoco low-level jet variability 

Alejandro Builes, Johanna Yepes, and Hernán D. Salas

We studied the most active season of the Orinoco Low-Level jet (OLLJ), December-January-February (DJF), during the El Niño-Southern Oscillation canonical phases, El Niño and La Niña. In particular, we studied the occurrence days of the jet in each month, wind speed, moisture transport and precipitation over northern south America. In terms of the occurrence of the OLLJ, during El Niño in January, the jet exhibits its highest reduction with changes up to 24% in the eastern Colombian plains. On the contrary, during La Niña, the jet exhibits an increase between 6–16% in the frequency of occurrence mainly located in the eastern Colombian plains and the border between Colombia, Ecuador and Peru. Although the diurnal cycle of the OLLJ windspeed remains unaltered during the ENSO phases the maximum decrease (increase) up to -2m/s (up to 1 m/s) during El Niño (La Niña). Regarding moisture transport there is a gradual reduction during the season in both ENSO phases reaching up to 18 gm-1 kgm-1 during El Niño, and the precipitation also shows a reduction of around 5 mm/day. In conclusion, during DJF at the ENSO canonical phases the OLLJ shows changes in its occurrence along the jet corridor, and the region experiences changes in both moisture transport and precipitation.

How to cite: Builes, A., Yepes, J., and Salas, H. D.: El Niño Southern Oscillation influence over the Orinoco low-level jet variability, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-408, https://doi.org/10.5194/egusphere-egu23-408, 2023.

EGU23-410 | Orals | CL2.2

Phase-Locking between precipitation and El Niño-Southern Oscillation over northern South America 

Hernán D. Salas, Germán Poveda, Óscar J. Mesa, Alejandro Builes-Jaramillo, Niklas Boers, and Jürgen Kurths

We study phase-locking between the El Niño - Southern Oscillation (ENSO) and precipitation at inter-annual time scales over northern South America. To this end, we characterize the seasonality of the regional patterns of sea surface temperature, surface pressure levels, and precipitation anomalies associated with the states of the canonical ENSO. We find that the positive (negative) precipitation anomalies experienced in northern South America differ from those previously reported in the literature in some continental regions. In particular, the Orinoco Low-level Jet corridor separates two regions with negative (positive) rainfall anomalies during El Niño (La Niña), which are located in the Guianas (northeastern Amazon) and the Caribbean. Moreover, we show that the ENSO signal is phase-locked with the inter-annual rainfall variability in most of the study regions although some areas exhibit phase-locking without a significant change in the anomalies of precipitation. This suggests that ENSO could induce changes only in terms of phases and not so in terms of magnitude. This work provides new insights into the non-linear interactions between ENSO and hydro-climatic processes over the tropical Americas.

How to cite: Salas, H. D., Poveda, G., Mesa, Ó. J., Builes-Jaramillo, A., Boers, N., and Kurths, J.: Phase-Locking between precipitation and El Niño-Southern Oscillation over northern South America, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-410, https://doi.org/10.5194/egusphere-egu23-410, 2023.

EGU23-1522 | ECS | Orals | CL2.2

Future climate response to observed extreme El Niño analogues 

Paloma Trascasa-Castro, Yohan Ruprich-Robert, and Amanda Maycock

Model simulations show a robust increase in ENSO-related precipitation variability in a warmer climate, but there remains uncertainty in whether the characteristics of ENSO events themselves may change in the future. Our study aims to disentangle these effects by addressing how the global impacts of observed large El Niño events would change in different background climate states covering the preindustrial, present and future periods.

Pacemaker simulations with the EC-Earth3-CC model were performed replaying the 3 strongest observed El Niño events from the historical record (1982/83, 1997/98, 2015/16). Model tropical Pacific sea surface temperature (SST) anomalies were restored towards observations, while imposing different background states, mimicking past, present and future climate conditions (following the SSP2-4.5). All variables outside the restoring region evolve freely in a coupled-atmosphere ocean transient simulation. For each start date, 30 ensemble members with different initial conditions were run for 2 years. Using this approach we ask ‘what impacts would arise if the observed El Niño occurred in the past or future’?

In response to the same imposed El Niño SST anomalies, precipitation anomalies are shifted towards the Eastern equatorial Pacific in the future compared to the present day, leading to changes in the extratropical response to El Niño. Some examples are an amplification of the surface temperature response over north-eastern North America, northern South America and Australia in boreal winter. We link the changes of El Niño related tropical Pacific precipitation to a decrease in the climatological zonal SST gradient in the equatorial Pacific, as we move from past to future climatologies, which potentially leads to a higher convection sensitivity to SST anomalies over the Central and Eastern equatorial Pacific in the future. Interestingly, the simulations indicate there has already been an intensification of El Niño impacts between present day and preindustrial, which is comparable to the differences found between future and present. This nonlinear behaviour highlights the need to understand potential changes to convection thresholds in the tropical Pacific to be able to explain El Niño teleconnections under climate change scenarios. Ongoing work is exploring the changes in atmospheric circulation that lead to the overall intensification of El Niño impacts that we show in our study.

How to cite: Trascasa-Castro, P., Ruprich-Robert, Y., and Maycock, A.: Future climate response to observed extreme El Niño analogues, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1522, https://doi.org/10.5194/egusphere-egu23-1522, 2023.

EGU23-1960 | Posters on site | CL2.2

Two regimes of inter-basin interactions between the Atlantic and Pacific Oceans on interannual timescales 

Jae-Heung Park, Sang-Wook Yeh, Jong-Seong Kug, Young-Mean Yang, Hyun-Su Jo, Hyo-Jeong Kim, and Soon-Il An

Understanding the inter-basin interactions between the Atlantic and Pacific Oceans is of great concern due to their substantial global climatic implications. By analyzing observational reanalysis datasets (1948-2020), we found that there are two regimes in Atlantic–Pacific inter-basin interactions: (i) the Pacific-driven regime, and (ii) the Atlantic-driven regime. In the Pacific-driven regime before the mid-1980s, the El Niño-Southern Oscillation (ENSO) in winter effectively drives the primary mode of sea surface temperature anomaly (SSTA) in the tropical Atlantic (i.e., NTA mode) in boreal spring. The NTA mode has a meridional contrast of SSTA along the Atlantic Intertropical convergence zone due to the ENSO effect, similar to the Atlantic Meridional Mode. Whereas, in the Atlantic-driven regime after the mid-1980s, the ENSO effect on the NTA becomes remarkably weaker, so that the NTA mode is featured with a SSTA monopole. Notably, the NTA mode without the meridional contrast of SSTA is capable of modulating an ENSO event. Our analyses of the latest climate models participating in the Coupled Model Intercomparison Project (CMIP) phases 6 support the hypothesis that the two regimes engendered by the Atlantic-Pacific inter-basin interactions are likely due to natural variability.

How to cite: Park, J.-H., Yeh, S.-W., Kug, J.-S., Yang, Y.-M., Jo, H.-S., Kim, H.-J., and An, S.-I.: Two regimes of inter-basin interactions between the Atlantic and Pacific Oceans on interannual timescales, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1960, https://doi.org/10.5194/egusphere-egu23-1960, 2023.

EGU23-2136 | ECS | Posters on site | CL2.2

A multi-modal representation of El-Niño Southern Oscillation Diversity 

Jakob Schlör, Antonietta Capotondi, and Bedartha Goswami

Sea surface temperature anomalies (SSTA) associated with the El-Niño Southern Oscillation (ENSO) show strong event-to-event variability, known as ENSO diversity. El Niño and La Niña events are typically divided into Eastern Pacific (EP) and Central Pacific (CP) types based on the zonal location of peak SSTA. The separation of these types is usually based on temperature differences between pairs of predefined indices, such as averages over boxes in the Eastern and Central Pacific or the two leading Principal Components of tropical SSTA. 
Using results from unsupervised learning of SSTA data, we argue that ENSO diversity is not well described by distinctly separate classes but rather forms a continuum with events grouping into "soft'' clusters. We apply a Gaussian mixture model (GMM) to a low-dimensional projection of tropical SSTA to describe the multi-modal distribution of ENSO events. We find that El-Niño events are best described by three overlapping clusters while La-Niña events only show two "soft'' clusters. The three El-Niño clusters are described by i) maximum SSTA in the CP, ii) maximum SSTA in the EP, and iii) strong basin-wide warming of SSTA which we refer to as the "super El-Niño'' cluster. The "soft'' clusters of La-Niña correspond to i) anomalous cool SST in the CP and ii) anomalously cool SST in the EP. We estimate the probability that a given ENSO event belongs to a chosen cluster and use these probabilities as weights for estimating averages of atmospheric variables corresponding to each cluster. These weighted composites show qualitatively similar patterns to the typically used averages over EP and CP events. However, the weighted composites show a higher signal-to-noise ratio in the mid-latitudes for the "super El-Niño'' events. 
We further apply our approach to CESM2 model data and discuss the potential of GMM clustering for evaluating how well ENSO diversity is captured in Global Circulation models.

How to cite: Schlör, J., Capotondi, A., and Goswami, B.: A multi-modal representation of El-Niño Southern Oscillation Diversity, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2136, https://doi.org/10.5194/egusphere-egu23-2136, 2023.

An information theory based framework is developed to assess the predictability of the ENSO complexity, which includes different types of the ENSO events with diverse characteristics in spatial patterns, peak intensities and temporal evolutions. The information theory advances a unique way to quantify the forecast uncertainty and allows to distinguish the predictability limit of each type of event. With the assistance of a recently developed multiscale stochastic conceptual model that succeeds in capturing both the large-scale dynamics and many crucial statistical properties of the observed ENSO complexity, it is shown that different ENSO events possess very distinct predictability limits. Beyond the ensemble mean value, the spread of the ensemble members also has remarkable contributions to the predictability. Specifically, while the result indicates that predicting the onset of the eastern Pacific (EP) El Ninos is challenging, it reveals a universal tendency to convert strong predictability to skillful forecast for predicting many central Pacific (CP) El Ninos about two years in advance. In addition, strong predictability is found for the La Nina events, corresponding to the effectiveness of the El Nino to La Nina transitions. In the climate change scenario with the strengthening of the background Walker circulation, the predictability of sea surface temperature in the CP region has a significant response with a notable increase in summer and fall. Finally, the Gaussian approximation exhibits to be accurate in computing the information gain, which facilitates the use of more sophisticated models to study the ENSO predictability.

How to cite: Fang, X. and Chen, N.: Quantifying the Predictability of ENSO Complexity Using a Statistically Accurate Multiscale Stochastic Model and Information Theory, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2209, https://doi.org/10.5194/egusphere-egu23-2209, 2023.

EGU23-2470 | ECS | Orals | CL2.2

The Dynamics of the El-Niño Southern Oscillation (ENSO) Diversity 

Priyamvada Priya, Dietmar Dommenget, and Shayne McGregor

This study investigates the observed El-Niño Southern Oscillation (ENSO) dynamics for the eastern Pacific (EP) and central Pacific (CP) events. Here we use the recharge oscillator (ReOsc) model concept to describe the ENSO phase space, based on the interaction of sea surface temperatures in the eastern equatorial Pacific (T) and thermocline depth (h), for the different types of ENSO events. We further look at some important statistical characteristics, such as power spectrum and cross-correlation, as essential parameters for understanding the dynamics of ENSO. The results show that the CP and EP events are very different in the ENSO phase space and less well described by the ReOsc model than a T index-based model. The EP events are closer to the idealised ReOsc model, with clear propagation through all phases of the ENSO cycle and strongly skewed towards the El-Niño and subsurface ocean heat discharge states. The CP events, in turn, do not have a clear propagation through all phases and are strongly skewed towards the La-Nina state. Also, the CP events have a slower cycle (67 months) than the EP events (50 months). Further, the CP events collapse after the La-Nina phase, whereas the EP events appear to collapse after the discharging phase. The characteristics out-of-phase cross-correlation between T and h is nearly absent for the CP events, suggesting that the interaction between T and h is not as important as for the EP or the canonical ENSO events. Furthermore, the coupling factor of T and h is smaller for the CP events than the EP events, implying that the CP events are not influenced much by T and h interactions. This study will provide new insight to understand these events by developing a dynamical approach to explain the observed ENSO dynamics for the EP and CP events in the ReOsc model framework.

How to cite: Priya, P., Dommenget, D., and McGregor, S.: The Dynamics of the El-Niño Southern Oscillation (ENSO) Diversity, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2470, https://doi.org/10.5194/egusphere-egu23-2470, 2023.

EGU23-2477 | Posters on site | CL2.2

ENSO phase space dynamics with an improved estimate of the thermocline depth 

Dietmar Dommenget and Priyamvada Priya

The recharge oscillator model of the El Niño Southern Oscillation (ENSO) describes the ENSO dynamics as an interaction and oscillation between the eastern tropical Pacific sea surface temperatures (T) and subsurface heat content (thermocline depth; h), describing a cycle of ENSO phases. h is often approximated on the basis of the depth of the 20oC isotherm (Z20). In this study we will address how the estimation of h affects the representation of ENSO dynamics. We will compare the ENSO phase space with h estimated based on Z20 and based on the maximum gradient in the temperature profile (Zmxg). The results illustrate that the ENSO phase space is much closer to the idealised recharge oscillator model if based on Zmxg than if based on Z20. Using linear and non-linear recharge oscillator models fitted to the observed data illustrates that the Z20 estimate leads to artificial phase dependent structures in the ENSO phase space, which result from an in-phase correlation between h and T. Based on the Zmxg estimate the ENSO phase space diagram show very clear non-linear aspects in growth rates and phase speeds. Based on this estimate we can describe the ENSO cycle dynamics as a non-linear cycle that grows during the recharge and El Nino state, and decays during the La Nina states. The most extreme ENSO states are during the El Nino and discharge states, while the La Nina and recharge states do not have extreme states. It further has faster phase speeds after the El Nino state and slower phase speeds during and after the La Nina states. The analysis suggests that the ENSO phase speed is significantly positive in all phases, suggesting that ENSO is indeed a cycle. However, the phase speeds are closest to zero during and after the La Nina state, indicating that the ENSO cycle is most likely to stall in these states.

How to cite: Dommenget, D. and Priya, P.: ENSO phase space dynamics with an improved estimate of the thermocline depth, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2477, https://doi.org/10.5194/egusphere-egu23-2477, 2023.

EGU23-3263 | ECS | Orals | CL2.2

Model Resolution Effects on ENSO and its Teleconnections 

Ned Williams, Adam Scaife, and James Screen

The El Niño-Southern Oscillation (ENSO) influences climate on a global scale and is a source of long-range predictability. Accurate modelling of the impact of ENSO requires accurate representation of teleconnections as well as of ENSO itself. We consider a set of CMIP6 models and assess the effect of increasing model resolution on ENSO and its boreal winter teleconnections. The spatial structure, strength and asymmetry of both ENSO and its teleconnection to the extratropical North Pacific are considered. We find evidence of an improved El Niño teleconnection in high resolution models, but this effect is weaker for La Niña. We aim to establish whether ocean or atmospheric resolution is the primary driver of resolution-based trends, and we evaluate the relevance of mean state biases on these trends. 

How to cite: Williams, N., Scaife, A., and Screen, J.: Model Resolution Effects on ENSO and its Teleconnections, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3263, https://doi.org/10.5194/egusphere-egu23-3263, 2023.

EGU23-3278 | ECS | Posters on site | CL2.2

Oceanic and Atmospheric Feedbacks Associated with the Spreading of Pacific Coastal Niño Events 

Daniel Rudloff and Joke Lübbecke

In early 2017 a very strong coastal warming occurred off the coast of Peru. This event, which caused heavy rainfalls and flooding over land, marked the strongest so called ‘Pacific Coastal Niño Event’ observed. Most intriguing about this event was the fact that the central Pacific was not showing any significant anomalies during that time. Since then several studies have investigated Pacific Coastal Niños but the exact mechanisms of how such events behave are still not clear. While most studies focus on their onset mechanisms, we here analyze their evolution and decay and in particular their connection to the central equatorial Pacific.

To address those questions, we are using the coupled climate model FOCI (Flexible Ocean Climate Infrastructure). Starting from a long control simulation with pre-industrial conditions we perform sets of 2-year long sensitivity experiments in which a coastal warming is generated by a local wind stress anomaly utilizing a partial coupling approach. Once the warming is initiated by reduced upwelling the wind forcing is switched off and the model can evolve freely, which enables us to investigate the evolution and decay of the warming. The approach allows to vary the forcing in strength, location and timing. By starting from different conditions in terms of equatorial heat content and applying the forcing during different months, the influences of both the background state of the equatorial Pacific during the Coastal Niño and the seasonality of the coastal warming are investigated. To understand which factors influence the spreading of the warm anomaly we analyze both local coastal feedbacks, which lead to an alongshore extension of the anomaly, and equatorial feedbacks that are crucial for a spreading along the equator.

How to cite: Rudloff, D. and Lübbecke, J.: Oceanic and Atmospheric Feedbacks Associated with the Spreading of Pacific Coastal Niño Events, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3278, https://doi.org/10.5194/egusphere-egu23-3278, 2023.

EGU23-3440 | ECS | Posters on site | CL2.2

New insight into multi-year La Niña dynamics from the perspective of a near-annual ocean process 

Fangyu Liu, Wenjun Zhang, Fei-Fei Jin, Feng Jiang, Julien Boucharel, and Suqiong Hu

The El Niño-Southern Oscillation (ENSO) exhibits highly asymmetric temporal evolutions between its warm and cold phases. While El Niño events usually terminate rapidly after their mature phase and show an already established transition into the cold phase by the following summer, many La Niña events tend to persist throughout the second year and even re-intensify in the ensuing winter. While many mechanisms were proposed, no consensus has been reached yet and the essential physical processes responsible for the multi-year behavior of La Niña remain to be illustrated. Observations show that a unique ocean physical process operates during multi-year La Niña events. It is characterized by rapid double reversals of zonal ocean current anomalies in the equatorial Pacific which exhibits a fairly regular near-annual periodicity. Analyses of mixed-layer heat budget reveal comparable contributions of the thermocline and zonal advective feedbacks to the SST anomaly growth for the first year of multi-year La Niña events; however, the zonal advective feedback plays a dominant role in the re-intensification of La Niña events. Furthermore, the unique ocean process is identified to be closely associated with the preconditioning heat content state in the central to eastern equatorial Pacific before the first year of La Niña, which sets the stage for the future re-intensification of La Niña. The above-mentioned oceanic process can be largely reproduced by state-of-the-art climate models despite systematic underestimation, providing a potential predictability source for the multi-year La Niña events.

How to cite: Liu, F., Zhang, W., Jin, F.-F., Jiang, F., Boucharel, J., and Hu, S.: New insight into multi-year La Niña dynamics from the perspective of a near-annual ocean process, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3440, https://doi.org/10.5194/egusphere-egu23-3440, 2023.

EGU23-3598 | Orals | CL2.2 | Highlight

Prediction Challenges from Errors in Tropical Pacific Sea Surface Temperature Trends 

Michelle L'Heureux, Michael Tippett, and Wanqiu Wang

Initialized, monthly mean predictions of the tropical Pacific Ocean are made against the backdrop of a warming climate, and it is unclear to what extent these predictions are impacted by trends.  Here, we analyze the forecast models that comprise the North American Multi-Model Ensemble (NMME) and uncover significant linear trend errors that have consequences for the tropical Pacific basin and ENSO variability.  All models show positive trend errors over the eastern equatorial Pacific over the 1982-2020 hindcast and real-time period.  These positive trend errors interact with the mean bias of each respective model, reducing, over time, the bias of models that are too cold and increasing the bias of models that are too warm.  These trend errors lead to a tropical Pacific that is too warm and too wet over the basin, and is significantly correlated with an increase in El Niño false alarms.  Finally, we explore the consequences of these tropical Pacific Ocean trend errors on predictions of global precipitation anomalies. 

How to cite: L'Heureux, M., Tippett, M., and Wang, W.: Prediction Challenges from Errors in Tropical Pacific Sea Surface Temperature Trends, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3598, https://doi.org/10.5194/egusphere-egu23-3598, 2023.

EGU23-3631 | Posters on site | CL2.2

Multiyear ENSO dynamics as revealed in observations, CMIP6 models, and linear theory 

Tomoki Iwakiri and Masahiro Watanabe

El Niño–Southern Oscillation (ENSO) events occasionally recur one after the other in the same polarity, called multiyear ENSO. However, the dynamical processes are not well understood. This study aims to elucidate the unified mechanisms of multiyear ENSO using observations, CMIP6 models, and the theoretical linear recharge oscillator (RO) model. We found that multiyear El Niño and La Niña events are roughly symmetric except in some cases. The composite multiyear ENSO reveals that anomalous ocean heat content (OHC) in the equatorial Pacific persists beyond the first peak, stimulating another event. This prolonged OHC anomaly is caused by meridional Ekman heat transport counteracting geostrophic transport induced recharge–discharge process that otherwise acts to change the OHC anomaly. A meridionally wide pattern of sea surface temperature observed during multiyear event is responsible for the Ekman heat transport. CMIP6 multi-model ensemble shows a significant correlation between the ENSO meridional width and the occurrence ratio of multiyear ENSO. A multiyear ENSO-like oscillation was simulated using the linear RO model that incorporates a seasonally varying Bjerknes growth rate and a weak recharge efficiency representing the effect of Ekman transport. When the recharge efficiency parameter was estimated using reanalysis data based on geostrophic transport alone, a multiyear ENSO rarely occurred, confirming the importance of Ekman transport in retarding the recharge–discharge process.

How to cite: Iwakiri, T. and Watanabe, M.: Multiyear ENSO dynamics as revealed in observations, CMIP6 models, and linear theory, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3631, https://doi.org/10.5194/egusphere-egu23-3631, 2023.

EGU23-3637 | ECS | Posters on site | CL2.2

Is a Preceding Strong El Niño Required to Generate Multi-year La Niña? 

Ji-Won Kim, Jin-Yi Yu, and Baijun Tian

By analyzing observational data covering the period from 1900 to 2021, we show that the known mechanism linking multi-year La Niña with a preceding strong El Niño has been overemphasized. A majority of multi-year La Niña (64%; 7 out of 11 events) do not require a preceding strong El Niño to generate their 2nd-year La Niña. We find that the negative phase of the Pacific Meridional Mode (PMM) during 1st-year La Niña’s decaying spring, rather than the preceding strong El Niño, offers the key mechanism to produce 2nd-year La Niña, resulting in a multi-year La Niña. It is further found that the westward extension of the 1st-year La Niña cold sea surface temperature anomalies, which interacts with the eastern edge of the western Pacific warm pool, is a key factor inducing the negative PMM. The negative PMM mechanism to generate multi-year La Niña is also applied to the 3rd-year La Niña of multi-year La Niña, giving rise to a triple-dip event. The possible reason(s) how and why a multi-year La Niña can become either a double-dip or a triple-dip event will be discussed.

How to cite: Kim, J.-W., Yu, J.-Y., and Tian, B.: Is a Preceding Strong El Niño Required to Generate Multi-year La Niña?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3637, https://doi.org/10.5194/egusphere-egu23-3637, 2023.

EGU23-4180 | Orals | CL2.2

Why is El Nino warm? 

Stephan Fueglistaler, Laure Resplandy, and Allison Hogikyan

El Nino years stand out in the global average temperature time series as record-warm years. The coupled atmosphere-ocean dynamics leading to warming in the climatologically cold equatorial Eastern Pacific are well understood, but cannot be the cause for the very strong signal in global average temperarture. The latter must be caused by an increase in subcloud Moist Static Energy (MSE) in the domain of highest subcloud MSE where atmospheric deep convection couples the surface, boundary layer and free troposphere. Transformation of the data from geographical space to sea-surface temperature (SST) percentiles eliminates the large spatial see-saws in all variables arising from the geographic reorganization of the general circulation, and brings to light the mechanism: While in the Eastern Pacific region oceanic heat uptake is reduced (corresponding to a heat flux out of the ocean), the deep convective domain sees a heat flux from the atmosphere into the ocean. We show that this heat flux into the ocean at the high end of SSTs - the opposite of the canonical perspective of a warming due to a heat flux from the ocean to the atmosphere - is mechanically forced: surface wind speeds are lower in regions of active deep convection than in ENSO neutral (and La Nina) years. The resulting reduced evaporation leads to the increase in subcloud MSE that causes the global temperature signal.

How to cite: Fueglistaler, S., Resplandy, L., and Hogikyan, A.: Why is El Nino warm?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4180, https://doi.org/10.5194/egusphere-egu23-4180, 2023.

The equatorial Atlantic zonal sea surface temperature (SST) gradient, which has significant climatic and biogeochemical effects, is closely associated with the equatorial Pacific zonal SST gradient through Walker circulation on seasonal and interannual time scales. However, discrepancies in current SST datasets mean that its long-term trend is not well understood. Here, using multiple datasets, we find a robust weakening long-term trend (i.e., greater warming in the east than west) in the equatorial Atlantic zonal SST gradient over the period 1900–2010 in all datasets. We also find that this weakening trend is closely linked to the tropical Pacific cold tongue mode (CTM), which corresponds to a strong increasing long-term trend of zonal SST gradient along the equatorial Pacific (i.e., warming in the west and cooling in the east). Specifically, the long-term cooling SST anomalies associated with the CTM modify the Walker circulation, and leads to weaker trade winds over the western equatorial Atlantic. These in turn deepen the thermocline in the eastern equatorial Atlantic, and cause the weakening long-term trend of SST gradient along the equatorial Atlantic. The long-term trend of the CTM is induced by ocean dynamical feedback in response to global warming, suggesting that global warming could affect the equatorial Atlantic zonal SST gradient via the CTM. Our results provide a novel explanation of the linkages between the long-term trend of equatorial Atlantic zonal SST gradient and the CTM under global warming, which carries important implications for the relationship between global warming and the equatorial Atlantic zonal SST gradient.

How to cite: Li, Y.: Long-term trend of equatorial Atlantic zonal SST gradient linked to the tropical Pacific cold tongue mode under global warming, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4360, https://doi.org/10.5194/egusphere-egu23-4360, 2023.

EGU23-4971 | ECS | Orals | CL2.2

Indo-Pacific teleconnection changes during the Holocene: model-proxy comparison 

Isma Abdelkader Di Carlo, Pascale Braconnot, Mary Elliot, and Olivier Marti

The teleconnections between the Indian and Pacific Oceans are very complex, involving multiple modes of variability and phenomena such as the El Niño-Southern Oscillation, Indian Ocean Dipole, Indian Ocean Basin mode, and the Asian monsoon. Their interactions are complex because changes in one of these phenomena affect the others. Insufficient agreement exists on the predicted evolution of mean states of both basins and the impacts of climate variability in this region in response to increasing CO2 emissions. To better constrain Indo-Pacific interactions, we have studied the Holocene period. We consider four transient simulations from three General Circulation Models (GCM) and a collection of paleo-archives from the Holocene in the Indo-Pacific region. Our study allows us to put into perspective the links between long-term changes in variability and in the mean state. The main driver is insolation and trace gases (CO2) that have increased the mean sea surface temperature of the tropical ocean over the last 6,000 years. Our first results show that modeled trends in the regional long-term variability are in agreement, but differences are observed when we analyze the data at shorter interannual timescales. We also explain why the simulations differ or agree with the paleoclimate reconstructions. One way is to look at the relative role of temperature and salinity in determining the changes in δ18O recorded by the various climate archives. 

How to cite: Abdelkader Di Carlo, I., Braconnot, P., Elliot, M., and Marti, O.: Indo-Pacific teleconnection changes during the Holocene: model-proxy comparison, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4971, https://doi.org/10.5194/egusphere-egu23-4971, 2023.

EGU23-5205 | ECS | Posters on site | CL2.2

Impact of tropical SSTs on the monthly signal over the North Atlantic-European region 

Sara Ivasić, Ivana Herceg Bulić, and Margareta Popović

Targeted numerical simulations were designed to test the potential impact of tropical sea surface temperatures (SSTs) on the geopotential heights at 200 hPa (GH200) signal over the North Atlantic-European region. Five experiments with SST anomalies prescribed in different areas, acting as lower boundary forcing, were created with an intermediately complex atmospheric general circulation model (ICTP AGCM). In the AGCM experiments, the SST forcing was prescribed globally, in the tropical zone of all oceans, only in the tropical Atlantic, tropical Indian Ocean and limited to the tropical Pacific. All of the simulations covered a 156-year-long period.

The monthly GH200 signal was calculated based on the difference between the ensemble mean of each experiment and the climatological mean for the considered period. In addition, to inspect the impact of the El Niño-Southern Oscillation (ENSO), the signal was calculated for ENSO and non-ENSO years, respectively. Here, the ENSO years were classified according to the value of the late-winter Niño3.4 index.

Additionally, each experiment’s monthly signal was averaged over the signal maximum over the North Atlantic-European region. The characteristics of the spatially averaged signal were compared to the signal averaged over a similar signal maximum observed over the Pacific North American region.

Results have shown that the GH200 signal is the strongest in the late-winter months in all experiments. The AGCM experiment with SST boundary forcing prescribed only in the tropical Atlantic consistently had the smallest signal amplitude. The strongest signal linked to ENSO events was found in the experiment with the SST forcing prescribed only in the tropical Pacific. The signal averaged over the NAE maximum generally yields smaller values than the PNA maximum average. Also, the differences between the (non) ENSO signal and the signal for all years are less pronounced in the case of the NAE maximum average.

How to cite: Ivasić, S., Herceg Bulić, I., and Popović, M.: Impact of tropical SSTs on the monthly signal over the North Atlantic-European region, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5205, https://doi.org/10.5194/egusphere-egu23-5205, 2023.

EGU23-5310 | ECS | Orals | CL2.2

Distinct and reproductible northem hemisphere winter teleconnection pattern during strong El Niño events : relative roles of Sea Surface Temperature forcing and atmospheric nonlinearities 

Margot Beniche, Jérôme Vialard, Matthieu Lengaigne, Aurore Voldoire, Srinivas Gangiredla, and Nicholas Hall

The strengthening and north-eastward shift of El Niño Northern hemisphere winter teleconnections relative to those of La Niña is a well-known asymmetry of ENSO (El Niño Southern Oscillation). It is generally attributed to atmospheric nonlinearities associated with the Sea Surface Temperature (SST) threshold for tropical deep convection. Here, we re-examine these teleconnection asymmetries in the context of ENSO SST pattern diversity. We find that the asymmetries are mainly attributable to strong El Niño events (eg. 1982-83, 1997-98, 2015-16), both in observations and in ensemble simulations with the atmospheric component of the CNRM-CM6 model. This strong El Niño teleconnection pattern also results in specific impacts, characterized by enhanced rainfall along the United States (US) west coast and warm anomalies over Canada and the Northern US. Our ensemble simulations further indicate that moderate “Eastern Pacific” El Niño events exhibit teleconnection patterns that are similar to those of “Central Pacific” El Niño, or to the opposite of La Niña events. We also find that the teleconnection spread between ensemble members or events is reduced for strong El Niño relative to moderate El Niño or La Niña events, with important implications for predictability. Sensitivity experiments in which the atmospheric model is forced by the opposite of observed SST anomalies are used to assess the mechanisms inducing the strong El Niño teleconnection pattern. In addition to the well-known influence of atmospheric nonlinearities, these experiments reveal an important contribution from the Eastward-shifted SST pattern during strong El Niño events.

 

How to cite: Beniche, M., Vialard, J., Lengaigne, M., Voldoire, A., Gangiredla, S., and Hall, N.: Distinct and reproductible northem hemisphere winter teleconnection pattern during strong El Niño events : relative roles of Sea Surface Temperature forcing and atmospheric nonlinearities, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5310, https://doi.org/10.5194/egusphere-egu23-5310, 2023.

The amplitude of El Niño/Southern Oscillation (ENSO) varied considerably over the last 140 years, for which we have relatively reliable Sea Surface Temperature (SST) observations over the tropical Pacific. The difference between periods of high and low ENSO amplitude results mainly from the number of strong Eastern Pacific (EP) El Niños, while the amplitude of Central Pacific (CP) El Niños is comparable in both periods. Further, the asymmetry of ENSO, i.e. that the SST anomalies during El Niño are on average stronger and located further to the east than during La Niña, covaries with ENSO amplitude in observations, indicating that the number of strong EP El Niño events dominates both ENSO amplitude and asymmetry variations.

We find similar relations in the 40 historical runs of the Large Ensemble with the CESM1-CAM5-BGC model that can simulate the ENSO asymmetry quite realistically.  Further, there is a strong relation between the ENSO amplitude and the tropical Pacific mean state, indicating that a warmer eastern equatorial Pacific favors more EP El Niños due to a lower convective threshold in that area. We also analyze the spatial asymmetry and amplitude asymmetry of the atmospheric and oceanic feedbacks and show that the spatial asymmetry is more pronounced in the atmospheric feedbacks, while the amplitude asymmetry is more pronounced in the oceanic feedbacks, and that both together form the observed asymmetry of ENSO.  A comparison with 360 years-long CESM1 experiments with a -4.0 K colder and +3.7 K warmer mean state indicates that the present-day ENSO may be in a transition zone between a CP El Niño dominated ENSO state and an EP El Niño dominated ENSO state and that ENSO may lock-in into the EP El Niño dominated state under global warming.

Finally, our analysis of ENSO-amplitude variability in preindustrial control simulations of the CMIP6 database supports a strong relation of ENSO amplitude and asymmetry with the number of strong EP El Niño events.

How to cite: Bayr, T., Lübbecke, J. F., and Latif, M.: The role of strong Eastern Pacific El Nino events in ENSO-amplitude variability in Observations and Climate Models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6109, https://doi.org/10.5194/egusphere-egu23-6109, 2023.

Using observational analysis and numerical experiments, we identify that the dipole mode of 
spring surface wind speed (SWS) over the Tibetan Plateau (TP) could act as a trigger for subsequent winter El 
Niño–Southern Oscillation events. During the positive phase of spring SWS dipole mode (south-positive and 
north-negative), a self-sustaining “negative sensible heating–baroclinic structure” prevails over the western TP, 
which is characterized by negative surface sensible heating anomalies, anomalous low-level anticyclones, and 
mid–high-level cyclones. The “negative sensible heating–baroclinic structure” stimulates the surface westerly 
wind anomalies over the tropical western Pacific in May through two pathways, favoring the occurrence of 
subsequent El Niño events. One is through weakening the zonal monsoon circulation over the tropical Indian 
Ocean and the Walker circulation over the tropical western Pacific. The other is modulating the air–sea 
interaction over the North Pacific through triggering Rossby waves. The negative SWS dipole mode tends to 
induce La Niña events.

How to cite: Yu, W.: Potential Impact of Spring Thermal Forcing Over the Tibetan Plateau on the Following Winter El Niño–Southern Oscillation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6401, https://doi.org/10.5194/egusphere-egu23-6401, 2023.

EGU23-7693 | Orals | CL2.2

Atmospheric nonlinearities strong contribution to the skewed ENSO amplitude and phase transition 

Jérôme Vialard, Srinivas Gangiredla, Matthieu Lengaigne, Aurore Voldoire, Takeshi Izumo, and Eric Huilyardi

ENSO features prominent asymmetries, in terms of amplitude, spatial pattern and phase-transition between warm and cold events. Here we examine the contribution of atmospheric nonlinearities to ENSO asymmetries through a set of forced experiments with the CNRM-CM6 AGCM and the NEMO OGCM. Control experiments can reproduce the major atmospheric and oceanic asymmetries of ENSO, with stronger signals east of the dateline for strong El Niño events, and west of it for strong La Niñas. Ensemble atmospheric experiments forced by observed ENSO SST anomalies and their opposites allow diagnosing asymmetries in air-sea heat and momentum fluxes directly attributable to atmospheric nonlinearities. They indicate that atmospheric nonlinearities are largely attributable to nonlinearities in the rainfall-SST relation and act to enhance El Niño atmospheric signals east of the dateline and those of La Niña west of it. An ocean simulation where the non-linear signature of air-sea fluxes is removed from the forcing reveals that asymmetries in the ENSO SST pattern are primarily due to atmospheric nonlinearities, and result in a doubling of eastern Pacific warming during the peak of strong El Niño events and a 33% reduction during that of strong La Niña events. Atmospheric nonlinearities also explain most of the observed prolonged eastern Pacific warming into boreal summer after the peak of strong El Niño events. Overall, these results imply that properly simulating the nonlinear relationship between SST and rainfall in CGCMs is essential to accurately simulate asymmetries in ENSO amplitude, spatial pattern and phase transition. Finally, we discuss the inherent limitations to our two-tier forced approach.

How to cite: Vialard, J., Gangiredla, S., Lengaigne, M., Voldoire, A., Izumo, T., and Huilyardi, E.: Atmospheric nonlinearities strong contribution to the skewed ENSO amplitude and phase transition, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7693, https://doi.org/10.5194/egusphere-egu23-7693, 2023.

EGU23-7791 | Posters on site | CL2.2

The multiverse future of ENSO diversity in large ensembles of climate models 

Bastien Dieppois, Nicola Maher, Antonietta Capotondi, and John O'Brien

El Niño Southern Oscillation (ENSO) shows large differences from one event to another in terms of its intensity, spatial pattern, and temporal evolution, which are typically referred to as “ENSO diversity”. While such differences in ENSO patterns are associated with different regional climate impacts throughout the world, influencing the skill of impact prediction systems, large uncertainties remain concerning its potential future evolution and trends. The location and intensity of ENSO events are indeed strongly influenced by internal/natural climate variations, limiting the detection of forced changes.

Here, we exploit the power of single model initial-condition large ensembles (SMILEs) from 13 fully coupled climate models from both CMIP5 and CMIP6 (totalling 580 realizations in historical and SSP-RCP scenarios) to first examine the ability of climate models to simulate realistic diversity of ENSO events compared to multiple observational datasets, and then use those models to characterize future trajectories in the location and intensity of El Niño and La Niña events. We define the location of ENSO events as the longitude of the absolute maximum (the intensity) of sea-surface temperature anomalies (SSTa) during boreal Winter (December-February) in the equatorial Pacific. Future projections of ENSO diversity are assessed in terms of joint probability distributions of ENSO events’ location and intensity.

While some models show a degree of diversity in the location and intensity of events that are comparable with observed statistics, other models tend to favour the occurrence of eastern or central Pacific events. Such contrasting performances during the historical period are found to be associated with different future trajectories of ENSO diversity: i) models favouring the occurrence of eastern Pacific events (e.g., ACCESS-ESM1-5, CanESM2, and 5) show a westward shift in event location over the 21st century; ii) models simulating ENSO events anomalously westward tend to show an eastward shift in event locations and an increased intensity in the 21st century (e.g., CESM1 and 2, CSIRO-MK3-6-0, GFDL-CM3, GFDL-ESM2M, MIROC-ES2L, MIROC6). Nevertheless, we note that models showing the closest match to observed statistics during the historical period also present a westward shift in ENSO locations and a slight increase in intensity in the 21st century (e.g., GFDL-SPEAR and IPSL-CM6-LR).

Although the physical cause of model discrepancies remains unclear, this study provides a broader perspective on expected ENSO changes over the 21st century in different models and highlights the spread of projections among models.

How to cite: Dieppois, B., Maher, N., Capotondi, A., and O'Brien, J.: The multiverse future of ENSO diversity in large ensembles of climate models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7791, https://doi.org/10.5194/egusphere-egu23-7791, 2023.

EGU23-8299 | ECS | Orals | CL2.2

Effect of Indian Ocean Dipole on ocean meridional heat transport depends on ENSO 

Kay McMonigal and Sarah Larson

Meridional heat transport within the Indian Ocean can drive climate and ecosystem impacts, by changing ocean temperature. Previous studies have linked variability in meridional heat transport to Indian Ocean Dipole (IOD) and El Niño-Southern Oscillation (ENSO). Recent studies have shown that some IOD events are caused by ENSO (termed “ENSO forced IOD”), while other events occur without ENSO (termed “internal IOD”). It is unclear whether these different kinds of IOD have different effects on the ocean. By comparing a climate model that includes ENSO to the same climate model but with ENSO dynamically removed, we show that internal IOD does not lead to variability in Indian Ocean meridional heat transport. However, ENSO forced IOD does lead to meridional heat transport variability. This is due to differing wind patterns associated with each kind of IOD event. These results suggest that the ecosystem and climate effects of IOD likely depend upon whether the IOD occurs with or without ENSO. 

How to cite: McMonigal, K. and Larson, S.: Effect of Indian Ocean Dipole on ocean meridional heat transport depends on ENSO, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8299, https://doi.org/10.5194/egusphere-egu23-8299, 2023.

EGU23-8733 | ECS | Orals | CL2.2

Stochastic perturbations of El Nino Southern Oscillations (ENSO) : a Wiener chaos approach 

Yusuf Aydogdu, Peter Baxendale, and N. Sri Namachchivaya

The phenomena of El Nino Southern Oscillations (ENSO) is modeled by coupled atmosphere-ocean mechanism together with sea surface temperature (SST) budget at the equatorial Pacific and has a significant impact on the global climate.  We consider a modeling framework that was originally developed by Majda and co-workers in (Chen et al. 2018; Thual et al. 2016), which is physically consistent and amenable to detailed analysis. The coupled model is mainly governed by the equatorial atmospheric and oceanic Kelvin and Rossby waves and it is shown that stochastic forcing gives rise to the model anomalies and unpredictable behavior. The purpose of our work is to investigate the influence of randomness on the model dynamics,  construct the appropriate model components with stochastic noise and calculate the statistical properties. We also provide analytical and numerical solutions of the model to prove the convergence of the numerical scheme developed in our work. 

We use Wiener-Chaos Expansion (WCE) to study stochastic ENSO models. The WCE method is based on reducing stochastic partial differential equations (SPDEs) into an infinite hierarchy of deterministic PDEs called propagators-Fourier modes (Lototsky and Rozovsky, 2006) and represents the stochastic solution as a spectral decomposition of deterministic components with respect to a set of random Hermite bases. We solve the WCE propagators, which are forced by a set of complete orthonormal bases,  by applying numerical integration and finite-difference methods. We compare WCE-based results with Monte Carlo simulations of SPDEs.

Our results depict that the mean and variance of the solutions obtained from the WCE method provide remarkably accurate results with a reasonable convergence rate and error range.  We first test the WCE-based method on the ocean  model with white noise and show that 10-Fourier modes are able to approach the theoretical variance values. We also show that the OU process with a specific noise strength and dissipation over a one-time period can be recovered with less than 50-Fourier modes for the ENSO model.  To illustrate the particular weight of variance, we also generate the ensembles of solutions by using different stochastic bases. We also derive the analytical formulation of propagators for the coupled model with nonlinear SST by using the properties of Wick polynomials that construct the foundation of numerical schemes. 

How to cite: Aydogdu, Y., Baxendale, P., and Namachchivaya, N. S.: Stochastic perturbations of El Nino Southern Oscillations (ENSO) : a Wiener chaos approach, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8733, https://doi.org/10.5194/egusphere-egu23-8733, 2023.

EGU23-8904 | Orals | CL2.2

Forecasting the El Niño type well before the spring predictability barrier 

Josef Ludescher, Armin Bunde, and Hans Joachim Schellnhuber

The El Niño Southern Oscillation (ENSO) is the most important driver of interannual global climate variability and can trigger extreme weather events and disasters in various parts of the globe. Depending on the region of maximal warming, El Niño events can be partitioned into 2 types, Eastern Pacific (EP) and Central Pacific (CP) events. The type of an El Niño has a major influence on its impact and can even lead to either dry or wet conditions in the same areas on the globe. Here we show that the zonal difference ΔTWP-CP between the sea surface temperature anomalies (SSTA) in the equatorial western Pacific and central Pacific is predictive of the type of an upcoming El Niño. When at the end of a calendar year, ΔTWP-CP is positive, an El Niño event developing in the following year will probably be an EP event, otherwise a CP event. Between 1950 and present, the index correctly indicates the type of 18 out of 21 El Niño events (p = 9.1⋅10-4).
For early actionable forecasts, the index has to be combined with a forecast for the actual onset of an El Niño event. The previously introduced climate network-based forecasting approach provides such forecasts for the onset of El Niño events also by the end of the calendar year before onset. Thus a combined approach can provide reliable forecasts for both the onset and the type of an event: at a lead time of about one year, 2/3 of the EP El Niño forecasts and all CP El Niño forecasts in the regarded period are correct. The combined model has considerably more predictive power than the current operational type forecasts with a mean lead time of about 1 month and should allow early mitigation measures.

How to cite: Ludescher, J., Bunde, A., and Schellnhuber, H. J.: Forecasting the El Niño type well before the spring predictability barrier, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8904, https://doi.org/10.5194/egusphere-egu23-8904, 2023.

Since the early 1990s the Pacific Walker circulation has strengthened, while SSTs in the eastern equatorial Pacific became colder, which is opposite to future model projections. Whether these trends, evident in many climate indices especially before the 2015 El Niño, reflect the coupled ocean-atmosphere response to global warming or the negative phase of the Pacific Decadal Oscillation (PDO) remains debated. Here we show that sea surface temperature (SST) trends during 1980-2020 are dominated by three signals: a spatially uniform warming trend, a negative PDO pattern, and a Northern Hemisphere/Indo-West Pacific warming pattern. The latter pattern, which closely resembles the transient ocean thermostat-like response to global warming emerging in a subset of CMIP6 models, shows cooling in the central-eastern equatorial Pacific but warming in the western Pacific and tropical Indian ocean. Together with the PDO, this pattern drives the Walker circulation strengthening. CMIP6 historical simulations appear to underestimate this pattern, contributing to the models’ inability to replicate the Walker cell strengthening. We further discuss how such changes in the Walker circulation can effect ENSO.

Reference:  Heede, U. and A.V. Fedorov, 2023: Colder eastern equatorial Pacific and stronger Walker circulation in the early 21st century: separating the forced response to global warming from natural variability. In press, GRL

How to cite: Fedorov, A. and Heede, U.: Colder eastern equatorial Pacific and stronger Walker circulation in the early 21st century: an Indo-Pacific ocean thermostat  versus natural variability, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10347, https://doi.org/10.5194/egusphere-egu23-10347, 2023.

EGU23-10801 | Orals | CL2.2 | Highlight

Causes and Consequences of the Prolonged 2020-2023 La Niña 

Michael J. McPhaden, Nahid Hasan, and Yoshimitsu Chikamoto

The tropical Pacific has witnessed three successive years of unusually cold sea surface temperatures, with peak anomalies in late 2020, 2021 and 2022.  These conditions represent the first "triple dip" La Niña of the 21st century with major climatic impacts felt around the world.  Three year La Niña events are rare but not unprecedented; similar events occurred in 1998-2001 and in 1973-76.  A leading hypothesis for multi-year La Niñas is that they occur on the rebound from preceding extreme El Niños which, through recharge oscillator dynamics, drain the equatorial band of upper ocean heat content leaving a large heat deficit that takes multiple years to recover. The current multi-year La Niña does not conform to this scenario--antecedent conditions in the tropical Pacific in 2019 were characterized by a borderline El Niño that did not lead to a large upper ocean heat content discharge. What caused the this La Niña is thus a topic of considerable interest.  In this presentation we hypothesize that tropical inter-basin interactions were instrumental in initiating and prolonging the event. In particular, we suggest that the event was triggered from the Indian Ocean by a record Indian Ocean Dipole in late 2019, then boosted in 2021 by unusually warm conditions in the tropical Atlantic involving the strongest Atlantic Niño since the 1970s. Whether climate change may have played a role in these developments will be discussed.

How to cite: McPhaden, M. J., Hasan, N., and Chikamoto, Y.: Causes and Consequences of the Prolonged 2020-2023 La Niña, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10801, https://doi.org/10.5194/egusphere-egu23-10801, 2023.

EGU23-11500 | Orals | CL2.2

Representation of tropical SST trends in ECMWF seasonal hindcasts and implications for recent ENSO forecasts 

Michael Mayer, Magdalena Alonso Balmaseda, and Steffen Tietsche

Operational seasonal forecasts are routinely issued with their bias removed, which is estimated from hindcasts covering a sufficiently long period. An increased number of false alarms for the occurrence of El Nino by various dynamical forecasting systems in recent years challenges the view that forecast biases are stationary. Here we assess the ability of ECMWF’s operational seasonal prediction system SEAS5 to represent observed trends in tropical SSTs since 1993, with a focus on the Pacific.

SEAS5 hindcasts overestimate SST warming in the equatorial Pacific when compared to observations. Although present for all start dates, the trend error is most pronounced for May starts. As a result, SEAS5 forecasts in recent years tended to predict too warm ENSO states despite bias correction. The hindcasts also fail to reproduce the observed meridional dipole in SST trends in the eastern Pacific, with warming in the northern and cooling in the southern subtropics. We assess several numerical experiments to investigate the role of the evolving ocean observing system, the ocean data assimilation system, and the atmospheric model. Results show that the increase in Argo observations amplifies the spurious trends in the hindcasts, which points to biases in the ocean initial conditions when observational constraints are lacking prior to Argo. Furthermore, observed-SST experiments show that the atmospheric model is unable to reproduce the magnitude of increasingly northward winds that are observed in the eastern equatorial Pacific, which are associated with the meridional structure of observed SST trends and have been speculated to reduce ENSO variability. This suggests that shortcomings of the atmospheric model physics further contribute to the system’s inability to predict the recent triple La Nina period. The results call for more sophisticated calibration methods of seasonal forecasts and ultimately improved models and initialization to provide more reliable ENSO forecasts under varying background conditions.

How to cite: Mayer, M., Alonso Balmaseda, M., and Tietsche, S.: Representation of tropical SST trends in ECMWF seasonal hindcasts and implications for recent ENSO forecasts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11500, https://doi.org/10.5194/egusphere-egu23-11500, 2023.

There are large interannual variations in the area integral of the Pacific-wide annual-mean net surface heat fluxes within 5o of the equator. They are shown to be very well correlated (r2 = 0.75) with the zonal-mean, annual-mean, zonal component of the surface wind stress on the equator, both in UK-HadGEM3 coupled climate simulations and in the ERA5 wind-stress and DEEPC net surface heat flux re-analyses. For the model data the corresponding correlations are small for monthly means (r2 = 0.25) but are large (r2 > 0.6) for time-mean periods between 6 months and 10 years (the latter being calculated from 700 year pre-industrial control simulations). The amplitude of these annual mean fluctuations in the DEEPC net surface heat fluxes is almost twice as large as that in the UK-HadGEM3 simulations. Comparison of the area-mean fields in the Nino3 and Nino4 regions from 4 member ensembles of N216O025 historical simulations with the ERA5 winds, DEEPC heat fluxes and EN4 ocean re-analyses shows that the model’s mean values and seasonal cycle of the zonal wind stress and net surface heat flux agree well with the re-analyses. In the Nino3 region however the model’s surface temperature is 1.5oC colder than the re-analyses and the depth of the 20oC isotherm (t20d) is between 10 and 15 m shallower than that in EN4.  Comparison of the amplitudes of El Nino and La Nina composite anomalies in the Nino3 and Nino4 regions shows that the surface temperature anomalies are well simulated but that the amplitudes of the wind stress anomalies in Nino4 and the t20d anomalies and surface heat flux anomalies in Nino3 are about half those in ERA5, EN4 and DEEPC respectively. These findings are somewhat similar to those from the (lower resolution)  Kiel Climate Model. The characteristic spatial patterns of the surface fields might be used to attribute the differences between the model and re-analysis net surface fluxes to particular component fluxes (e.g. the surface latent heat flux and the surface solar flux). It is also a plausible hypothesis that the under-estimation of these variations in the net surface heat fluxes is a significant contributor to the signal-to-noise paradox.       

 

How to cite: Bell, M.: HadGEM3  underestimates interannual variations in heat fluxes, zonal winds and thermocline displacements  in the tropical Pacific, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12824, https://doi.org/10.5194/egusphere-egu23-12824, 2023.

EGU23-13335 | ECS | Posters on site | CL2.2

Using Causal Discovery to Clarify Observed and Simulated Relationships Between ENSO and Other Ocean Basins 

Rebecca Herman and Jakob Runge

Observed sea-surface temperatures in various ocean basins are confounded by anthropogenic and natural radiative forcing and by teleconnections to modes of internal variability, especially the El Nino Southern Oscillation (ENSO). While confounding due to anthropogenic and natural forcing can be removed in coupled simulations, confounding due to ENSO is unavoidable. When not appropriately characterized and quantified, this confounding can obscure causal relationships between various ocean basins and atmospheric phenomena of huge humanitarian import, such as monsoon rainfall, with implications for attribution of past disasters and prediction of the future. These relationships have been difficult to characterize in part because observational data is limited and simulated data may not represent the observed climate system. This study uses causal discovery to examine the coupled relationships between ENSO and other ocean basins in simulations and observations. We begin by evaluating the (L)PCMCI(+) causal discovery algorithms under various conditions and assumptions on data generated by two continuous idealized models of ENSO: the classic Zebiak-Cane model and a simple stochastic dynamical model proposed by Thual, Majda, Chen, and Stechmann. We then apply the causal discovery algorithms to seasonally and spatially-averaged sea surface temperature (SST) indices for ENSO and other ocean basins in preindustrial control simulations from the Coupled Model Intercomparison Project Phase 6. We discuss the robustness of the results, and the differences between the causal relationships in different General Circulation Models. Finally, we apply the causal learning algorithm to observed SST, and discuss to what extent simulated relationships can be used to learn about the observed climate system. We additionally demonstrate the implications of this study for other scientific questions, specifically for understanding variability in Sahel Monsoon rainfall.

How to cite: Herman, R. and Runge, J.: Using Causal Discovery to Clarify Observed and Simulated Relationships Between ENSO and Other Ocean Basins, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13335, https://doi.org/10.5194/egusphere-egu23-13335, 2023.

EGU23-13812 | ECS | Orals | CL2.2

ENSO–IOD Inter-Basin Connection Is Controlled by the Atlantic Multidecadal Oscillation 

Jiaqing Xue, Jing-Jia Luo, Wenjun Zhang, and Toshio Yamagata

The interactions between El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) are known to have great implications for global climate variability and seasonal climate predictions. Observational analysis suggests that the ENSO–IOD inter-basin connection is time-varying and related to the Atlantic Multidecadal Oscillation (AMO) with weakened ENSO–IOD relationship corresponding to AMO warm phases. A suite of Atlantic pacemaker simulations successfully reproduces the decadal fluctuations in ENSO–IOD relationship and its link to the AMO. The warm sea surface temperature (SST) anomalies associated with the AMO drive a series of Indo-Pacific mean climate changes through tropical-wide teleconnections, including the La Niña-like mean SST cooling over the central Pacific and the deepening of mean thermocline depth in the eastern Indian Ocean. By modulating ocean–atmosphere feedback strength, those mean state changes decrease both ENSO amplitude and the Indian Ocean sensitivity to ENSO forcing, therefore decoupling the IOD from ENSO.

How to cite: Xue, J., Luo, J.-J., Zhang, W., and Yamagata, T.: ENSO–IOD Inter-Basin Connection Is Controlled by the Atlantic Multidecadal Oscillation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13812, https://doi.org/10.5194/egusphere-egu23-13812, 2023.

EGU23-15824 | ECS | Orals | CL2.2

Future Changes in the early winter ENSO teleconnections to the North Atlantic European region 

Muhammad Adnan Abid and Fred Kucharski

North Atlantic European (NAE) winter climate variability is strongly modulated through the stratospheric and tropospheric pathways, where El Niño-Southern Oscillation (ENSO) teleconnections play an important role. Recent studies showed intra-seasonal changes of the ENSO response in the NAE circulation anomalies from early to late winter.  One mechanism for this behavior is that the Indian Ocean (IO) dominate over the direct ENSO teleconnections in early winter favoring an in-phase North Atlantic Oscillation (NAO) response over NAE region. On the other hand, the direct ENSO response dominates in latter half of winter, where it projects onto the opposite phase of the NAO. In present study, we analyze the early to late winter ENSO-NAE teleconnections in future climate projections by adopting the sixth assessment report Coupled Model Intercomparison Project (CMIP6) model datasets. During early winter, we noted an increase in the ENSO-induced precipitation variability in the Pacific as well as over western and central Indian Ocean, while decrease is noted over the eastern IO. Moreover, a strengthening of the ENSO and Indian connections are noted in almost all models except few, where these connections are not well represented in the present climate. Interestingly, the changes in ENSO forced wave train are noted, which may lead to the negative NAO like circulation anomalies over the NAE region in future compared to the present climate. 

How to cite: Abid, M. A. and Kucharski, F.: Future Changes in the early winter ENSO teleconnections to the North Atlantic European region, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15824, https://doi.org/10.5194/egusphere-egu23-15824, 2023.

EGU23-16921 | Orals | CL2.2

The role of spatial shifting in El Niño/Southern Oscillation complexity 

Sulian Thual and Boris Dewitte

The El Niño-Southern Oscillation (ENSO) represents the most consequential fluctuation of the global climate system, with dramatic societal and environmental impacts. Here we show that the spatial shifting movements of the Walker circulation control the ENSO space-time complexity in a major way. First, we encapsulate the process in a conventional recharge-discharge oscillator for the ENSO by replacing the regionally fixed sea surface temperatures (SST) index against a warm pool edge index. By doing so, we can model essential ingredients of ENSO diversity and nonlinear behavior without increasing the complexity of the dynamical model. Second, we propose a data-driven method for estimating equatorial Pacific SST variability resulting from spatial shifting. It consists in time-averaging conditions respective to the evolving warm pool edge position, then generating back SST data with reduced dimensionality (one degree of freedom) from the movements of the resulting "shifted-mean" profile. It is shown that the shifted-mean SST generated in this fashion reasonably reconstructs observed interannual SSTs both in terms of amplitude and pattern diversity. We discuss implications of the present paradigm of spatial shifting for understanding ENSO complexity, including tropical basins interactions.

How to cite: Thual, S. and Dewitte, B.: The role of spatial shifting in El Niño/Southern Oscillation complexity, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16921, https://doi.org/10.5194/egusphere-egu23-16921, 2023.

EGU23-307 | ECS | Orals | AS1.17

Circulation aspects associated with heat wave events over Iraq 

Hasanain Al-Shamarti, Thomas Birner, and Philip Rupp

Heat waves lead to increased mortality due to heat exhaustion and heatstroke, wildfire, reduced agricultural yields, increased energy demand, economic predicaments and other societal issues. Heat wave events over the Middle-East have received far less attention compared to events elsewhere. Here, we provide a comprehensive characterization of heat wave events over Iraq, covering the period 1980-2019.
We use ERA5 reanalysis data for Northern summer (June-July-August) to identify heat waves in daily maximum 2-m temperature (Tmax) data and study them using composite analyses and clustering. We define a heat wave event if the Tmax anomaly exceeds the 90th percentile over three consecutive days, provided this threshold exceedance covers at least 50% of our target area.

The composite-mean evolution of daily Tmax anomalies demonstrates that our heat waves typically strengthen gradually over the week preceding the central day with a sharp decline in strength at positive lags, reaching an average maximum anomaly of ~3.7 K at the central day. We find the heat waves to extend from the Arabian peninsula northward across Iraq toward southwestern Russia. Clustering of all heat wave events reveals two dominant flow anomaly patterns that roughly distinguish early from late summer events.

The first cluster (early summer events) is associated with anomalous anticyclonic flow associated with a quasi-stationary upper-level high pressure system to the north-east of Iraq precisely over Caspian sea. This anomalous anticyclonic flow is embedded in a Rossby wave train that initially propagates along the north Atlantic wave-guide, then further equatorward along the North African-Asian jet just before the central day. Our composite-mean evolution for this first cluster further shows mid-tropospheric subsidence over the Zagros mountains, i.e., upstream of our heat wave target area. Downslope Foehn winds appear to enhance the heat wave over Iraq.

In contrast, the second cluster is primarily composed of late-summer events and shows strong anomalies in the Shamal winds - a pronounced low-level north-westerly jet along the western edge of the Zagros mountains. During these late summer heat wave events the Shamal jet is substantially weakened or even reversed, transporting warm air from the Persian gulf into the target region. 

 

How to cite: Al-Shamarti, H., Birner, T., and Rupp, P.: Circulation aspects associated with heat wave events over Iraq, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-307, https://doi.org/10.5194/egusphere-egu23-307, 2023.

EGU23-459 | ECS | Posters on site | AS1.17

Investigating the Hadley Cell and eddies with varying sea surface temperature gradients 

Abu Bakar Siddiqui Thakur, Jai Sukhatme, and Nili Harnik

We examine the tropical meridional overturning circulation in an aquaplanet GCM with fixed orbital parameters and uniform insolation angle. The atmosphere is forced by an imposed non-interactive sea surface temperature (SST) distribution which is varied between present-day Earth-like to a latitudinally uniform profile. A conventional Hadley Cell (HC) -like flow is observed in all experiments along with the poleward transport of energy and momentum. In simulations forced by a non-zero SST gradient, latent heat released from organized convection near the equator sets up a deep tropical cell. Rossby wave activity generated near the extratropical surface propagates upward and turns equatorward on reaching the tropopause. These waves break on the edge of the HC, fluxing heat and momentum poleward and reinforcing a thermally direct cell in the same sense as the HC. When the SST distribution becomes globally uniform, the traditional midlatitude Rossby waves are trapped near the surface as the mean flow inhibits their upward propagation. But, near the tropopause, baroclinicity generates waves that ride on a sharp upper tropospheric potential vorticity gradient. These waves propagate downwards towards the lower equatorial troposphere and transport angular momentum out of the tropics. Together with a dominant MJO-like mode, which facilitates near-equatorial convergence, this leads to a conventional tropical overturning circulation. As the SST gradient weakens, the HC moves from a regime intermediate to thermally and eddy-driven to one that's strongly influenced by eddies. Moreover, the thermal structure of the troposphere becomes uniform with weak gradients, and for flat SSTs, the tropopause in the midlatitudes is also set by convection. A Transformed Eulerian Mean perspective is consistent with this view and highlights the diabatic nature of the midlatitude circulation in the limit of flat sea surface temperatures.

How to cite: Thakur, A. B. S., Sukhatme, J., and Harnik, N.: Investigating the Hadley Cell and eddies with varying sea surface temperature gradients, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-459, https://doi.org/10.5194/egusphere-egu23-459, 2023.

Extratropical Rossby waves intrude over tropical region as well as the Indian region and exert significant influence on the weather features. Over Indian region, the pre-monsoon is a dry summer season. During this season, several studies have identified drivers of heatwaves based on different aspects such as the synoptic-scale systems, regional factors, and large-scale teleconnection patterns around the globe (Perkins 2015). Essentially these drivers identified for the Indian region do not describe the heatwave events as the intensification of some modes. Midlatitude heatwaves, on the other hand, are identified as the extreme phase of Rossby Wave mode amplification. However, over the Indian region studies do not explicitly point out the existence of temperature intraseasonal modes during April-May over the Indian region, and it is not clear if some of the drivers of heatwaves can also explain the April-May temperature variations during heatwaves as derivatives (or amplification) of some subseasonal modes. This study identifies the dominant pair of the intrinsic mode of temperature intraseasonal oscillations (ISO) related to subtropical and extratropical Rossby waves, which can also explain the heatwave spikes.

            The ISO modes are derived using the empirical orthogonal function analysis of the detrended surface temperature and further regression analysis demonstrates the dynamical origin of these spatial modes. It is found that both the modes are driven by the mid-latitudinal Rossby waves which propagate towards the Indian region following the ‘preferred teleconnection pathways’ (Ambrizzi and Hoskins 1997). The dominant mode is related to the subtropical westerly jet waveguide, and the second mode is induced by the extratropical to European eddy-driven jet which follows the Europe-Middle East-Indian Ocean pathway. From the different phases of the oscillation obtained from these modes, two phases are favorable for the extreme temperature events and these two phases account for more than 50% of the extreme event occurred over the Indian region.

            Global warming is however steering these two inherent modes of ISOs in surface temperature with the first mode having a significant decreasing trend and the second mode showing an increasing trend. The modal difference in trend is likely to be related to the weakening of the subtropical jetstream waveguide and the strengthening of the extratropical jetstream in a warming scenario (Archer and Caldeira 2008). The usefulness of this study is that the ISOs defined in this study could explain the maximum number of extreme temperature events occurring over the Indian region as a projection on two temperature modes. The modal trend could also account for the regional asymmetry of warming over the Indian region in the global warming scenario, and is related to the trend in jetstream waveguide those steers these modes towards the Indian region.

References

Ambrizzi T, Hoskins BJ (1997) Stationary rossby-wave propagation in a baroclinic atmosphere. Q J R Meteorol Soc 123:919–928. https://doi.org/https://doi.org/10.1002/qj.49712354007

Archer CL, Caldeira K (2008) Historical trends in the jet streams. Geophys Res Lett 35:. https://doi.org/https://doi.org/10.1029/2008GL033614

Perkins SE (2015) A review on the scientific understanding of heatwaves—Their measurement, driving mechanisms, and changes at the global scale. Atmos Res 164–165:242–267. https://doi.org/https://doi.org/10.1016/j.atmosres.2015.05.014

How to cite: Saradambal, L. and Chattopadhyay, R.: Propagation of Mid-Latitudinal Rossby waves along the Jetstream waveguides and their Role in Summer Temperature Intraseasonal Oscillations and Extremes over the Indian Region, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1199, https://doi.org/10.5194/egusphere-egu23-1199, 2023.

We examine regional and seasonal variations of extratropical storm tracks and their maintenance in terms of a column-mean local wave activity budget.  Seasonal climatology of wave activity in ERA5 reveals spatial and temporal variations of storm tracks in both hemispheres broadly consistent with previous studies based on other metrics. The seasonal-mean budget consists of horizontal convergence of wave activity fluxes, input from the surface (the upward Eliassen-Palm flux), a small storage, and the residual. When averaged hemispherically, surface injection of wave activity due to baroclinic instability and forced stationary waves is balanced by a negative residual (dissipation) due to mixing and radiative damping.

However, the budget terms show considerable zonal, meridional and seasonal variations, especially in the Northern Hemisphere. Wave activity migrates downstream from a source region to a sink, where the residual is negative and largely balanced by flux convergence. In addition to the surface sources in the regions of strong baroclinicity, the residual term, though negative on average, shows significant positive values where cloud water abounds, suggesting diabatic (and/or nonquasigeostrophic) sources of wave activity.

By reconstructing the budget driven by a fixed transport velocity and damping rate evaluated from the seasonal climatology but suppressing the positive residual values, we estimate the impact of diabatic sources on the mean wave activity. It is found that the diabatic sources contribute to 26% and 20%, respectively, of North Atlantic and North Pacific storm track activities in winter, 28% of wave activity over the Pacific Northwest in summer, and 34% of activity in the Indo-western Pacific sector of the austral storm track in summer.

How to cite: Nakamura, N.: How much does diabatic heating affect storm track activity?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2533, https://doi.org/10.5194/egusphere-egu23-2533, 2023.

Clustering extreme rainfall events are successive occurrences over multiple regions. As climate continues to warm up, cluster occurrence is becoming a prevailing feature of extreme weather events and leading to significant socioeconomic impacts. Understanding the associated atmospheric teleconnection patterns and their underlying mechanisms can help quantify their risk, i.e., the probability of occurrence and severity of cluster extremes in the future. In this study, we identified over 400 events of clustering extreme rainfall events over South Asia, East Asia, and North America in the past 42 years. Diagnostic analyses of these events reveal the diversity of teleconnection that paved the road to the events. Three Rossby wave patterns: (1) circum-Pacific Rossby wave, (2) cross-Pacific Rossby wave, and (3) Pacific anticyclone Rossby wave breaking, are the major synoptic-scale dynamics responsible for clustering rainfall events. Specifically, the circum-Pacific Rossby wave dominates in autumn and early winter, while the cross-Pacific Rossby wave pattern prevails during the Indian summer monsoon season. The occurrence frequency of the anticyclone Rossby wave breaking does not show significant seasonal differences.

The key driving mechanisms behind these wave patterns are: 1) The poleward propagation of the circum-Pacific wave can be excited by the heating anomaly originating in the tropics. 2) The mid-latitude cross-Pacific Rossby wave is a portion of the circum-global teleconnection pattern. This recurrent Rossby wave connects Asia and North America, influenced by the Indian summer monsoon. 3) Pacific anticyclone Rossby wave breaking is a quasi-stationary synoptic wave pattern causing persistent extreme weather. The frequency of this pattern increases significantly during La Niña years with a relatively weak subtropical jet. The single or synergistic effects of these three patterns cause the cluster occurrence of extreme rainfall. Findings from this work offer a better understanding of rainfall teleconnection and tropic/midlatitude interaction.

How to cite: Song, Y. and Lu, M.: Cluster occurrence of extreme rainfall events over Indo-Pacific and their associated diverse Rossby wave patterns, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2751, https://doi.org/10.5194/egusphere-egu23-2751, 2023.

EGU23-3115 | ECS | Posters on site | AS1.17

Jet streaks from a PV gradient perspective: A Lagrangian analysis of diabatic-adiabatic interaction in km-scale simulations 

Mona Bukenberger, Stefan Rüdisühli, and Sebastian Schemm

The jet stream is a circumpolar global band of high wind speeds in the upper troposphere. Meridional meanders of the jet lead to high-impact weather events and may synchronize them over thousands of kilometres. As a Rossby waveguide, the jet influences paths of synoptic-scale eddies, which in turn alter jet dynamics. Coherent regions of enhanced wind speed, so-called jet streaks, typify the jet locally and anomalously strong jet streaks often coincide with extreme precipitation and wind events.

Despite their relevance, process understanding remains limited regarding the formation of jet streaks in interaction with lower-level weather systems. The same is true for the influence of jet streaks on Rossby wave evolution. One way to further the understanding of jet streak dynamics is to study the interaction between adiabatic and diabatic processes during jet streak evolution. However, the relative importance of those processes is difficult to disentangle. 

This study utilises a Lagrangian-based PV gradient perspective by applying it to a jet streak relative coordinate system to obtain composites throughout the lifecycles of multiple jet streak events. The theoretical foundation of this approach is the link between the horizontal isentropic PV gradient and wind speed. Local maxima of the normalised isentropic PV gradient are collocated with centers of jet streaks. As PV is conserved under adiabatic and frictionless flow, the PV gradient perspective allows for an investigation of diabatic-adiabatic interaction.

We analyse a convection-resolving 1.1 km COSMO simulation in the eastern North Atlantic in autumn 2016, using PV gradient analysis and online air parcel trajectories to separate diabatic and adiabatic contributions to jet streak development. Cloud processes play an important role in the establishment and maintenance of a strong event, while the dynamics of a weaker jet streak is dominated by effects of adiabatic deformation.

After demonstrating the approach in two case studies, we present results from a composite analysis of multiple jet streak events to achieve a more systematic understanding of diabatic-adiabatic interaction during their evolution.

How to cite: Bukenberger, M., Rüdisühli, S., and Schemm, S.: Jet streaks from a PV gradient perspective: A Lagrangian analysis of diabatic-adiabatic interaction in km-scale simulations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3115, https://doi.org/10.5194/egusphere-egu23-3115, 2023.

EGU23-3912 | ECS | Posters on site | AS1.17

The Role of North American Convective Storms on Jet Stream Dynamics: A Negative Potential Vorticity Perspective 

Alexander Lojko, Andrew Winters, Christiane Jablonowski, and Ashley Payne

Synoptic-scale filaments of negative potential vorticity (PV) in the northern hemisphere tropopause can form adjacent to the jet stream in the presence of convection and moderate shear (i.e., severe thunderstorm environments). Case-studies have shown that synoptic-scale negative PV can influence in-situ jet stream dynamics. Negative PV arises due to strong vorticity in convective updrafts, driven by the horizontal gradient of diabatic heating (O < 10 km).  Its origin from scales not resolvable by contemporary global weather models can thus also impinge on jet stream forecast skill.

Nevertheless, little is still known about the characteristics of synoptic-scale negative PV. How frequently is it observed? And what are its ‘typical’ impacts on the jet stream?

Focusing on North America where severe thunderstorms are frequent, we design an algorithm that tracks the temporal evolution of closed contours of upper-level, negative PV air using ERA5 data. We composites instances in which it is in close-proximity to (‘interacts with’) the jet stream and assess its dynamical response. The role of negative PV on jet evolution and its downstream response over the Atlantic is facilitated through a combination of lagged composite analysis and K-means clustering.

Our composite results in combination with preliminary high-resolution model simulations highlight that elongated bands of negative PV frequently interact with the jet stream, intensify jet wind maxima and may serve as an amplification source for Rossby waves.

How to cite: Lojko, A., Winters, A., Jablonowski, C., and Payne, A.: The Role of North American Convective Storms on Jet Stream Dynamics: A Negative Potential Vorticity Perspective, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3912, https://doi.org/10.5194/egusphere-egu23-3912, 2023.

EGU23-3942 | ECS | Orals | AS1.17

Persistent anomalies of the North Atlantic jet stream and associated surface extremes over Europe 

Vera Melinda Galfi and Gabriele Messori

Persistent unusual configurations of the North Atlantic jet stream affect the weather and climate over Europe. We focus on winter and on intraseasonal and seasonal time scales, and study persistent jet anomalies through the lens of large deviation theory using CMIP6 simulations of the MPI-ESM-LR model and ERA5 reanalysis data. Our results show that persistent temperature and precipitation extremes over large European regions are anomalously frequent during the unusual, persistent jet configurations we identify. Furthermore, the relative increase in frequency of surface extremes is larger as we consider more intense surface extremes and/or more extreme jet anomalies. The highest extreme event frequencies at the surface are observed in case of precipitation over the Mediterranean and Western Europe during anomalously zonal and/or fast jet events, pointing to these jet anomalies matching rather homogeneous large-scale atmospheric configurations with a clear surface footprint. Additionally, our results emphasise the usefulness of large deviation rate functions to estimate the frequency of occurrence of persistent jet anomalies, and more generally of unusual, persistent atmospheric circulation patterns.

How to cite: Galfi, V. M. and Messori, G.: Persistent anomalies of the North Atlantic jet stream and associated surface extremes over Europe, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3942, https://doi.org/10.5194/egusphere-egu23-3942, 2023.

EGU23-5448 | ECS | Orals | AS1.17

A new atmospheric background state to diagnose local waveguidability 

Christopher Polster and Volkmar Wirth

Rossby waveguides constrain the propagation of Rossby waves by ducting eddy activity along paths of enhanced waveguidability in the atmosphere. Conceptually, waveguidability is the property of an eddy-free background state on which waves exist as perturbations. Because eddies are always present in the atmosphere, a procedure is required to separate the waves from the background. The choice of procedure is of practical importance when diagnosing waveguides. For example, a zonal-mean background state is easy to compute from data and often used, but does not allow for longitudinal variation of waveguidability. It has also been shown to exhibit waveguide artifacts in the presence of finite-amplitude eddies.

We introduce a new procedure to obtain an eddy-free background state for the analysis of waveguides in the atmosphere. It utilizes a redistribution (so-called zonalization) of Ertel potential vorticity on isentropes to remove eddies, including those of finite amplitude, while retaining local information. Because the procedure can be applied to instantaneous data without a need for temporal aggregation, it is suitable for causal analyses and can be applied to forecast data without lead time restrictions. Our construction is based on the "slowly evolving background state" by Nakamura and Solomon (2011) and Methven and Berrisford (2015), with additions and approximations to achieve a pragmatic compromise between theoretical grounding, usability and ease of computation.

The effectiveness of the procedure to meaningfully separate waves and the background state is illustrated with reanalysis data. Rossby waveguides are diagnosed from the background-state PV fields with a gradient-based metric. We show that our localized procedure leads to regional differences in the diagnosed waveguidability and discuss the existence of circumglobal waveguides.

How to cite: Polster, C. and Wirth, V.: A new atmospheric background state to diagnose local waveguidability, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5448, https://doi.org/10.5194/egusphere-egu23-5448, 2023.

EGU23-5969 | ECS | Posters on site | AS1.17

Winter North Atlantic jet variability under global warming: Past trends and future projections 

Alejandro Hermoso and Sebastian Schemm

Regional weather variability and the occurrence of extreme weather events are highly connected to the position of jet streams. Climate models generally project a poleward shift of the jets under the influence of anthropogenic warming. However, ERA5 reanalysis data show that the North Atlantic jet stream in winter has roughly remained in place. We investigate the mechanisms that lead to this behavior.  The analysis reveals that upper-level temperature trends produce a reduction in stability that leads to an increase in baroclinicity. Furthermore, momentum convergence is also intensified across the jet core, producing an acceleration of the jet and not a weakening as suggested by arguments based solely on the Artic amplification. 

 

Numerical simulations from an ensemble of fully coupled climate simulations run with the Community Earth System Model under the SSP3.7 scenario are also analyzed along with idealized warming experiments in an aquaplanet setup with a zonal asymmetry in sea surface temperature. The climate simulations exhibit a large spread during the historical period and only a few ensemble members reproduce the observed trends, suggesting that trends only based on ensemble means could lead to misleading projections. Additionally, the aquaplanet runs display high sensitivity to the location of the asymmetry. This provides a supplementary argument in support of inspecting all individual climate projections as small variations in the original jet position can lead to large disparities in the projected trends. 

How to cite: Hermoso, A. and Schemm, S.: Winter North Atlantic jet variability under global warming: Past trends and future projections, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5969, https://doi.org/10.5194/egusphere-egu23-5969, 2023.

EGU23-7466 | ECS | Orals | AS1.17

On the relationship between Atmospheric Blocking and Arctic Amplification 

Marco Cadau, Giorgia Fosser, Simona Bordoni, Gianmaria Sannino, and Marco Gaetani

Atmospheric blocking is known to be one of the most important drivers of large-scale atmospheric variability at mid-high latitudes. Blocking events consist of a disruption and/or deceleration of the mean westerly circumpolar flow, and are generally associated with large-scale high-pressure patterns, which may be connected with the occurrence of climate extremes, such as heat waves and cold spells. Atmospheric dynamics in the Arctic region may be very important in shaping the spatial and temporal patterns of blocking at mid-high latitudes, and consequently the occurrence of associated climate extremes. In particular, Arctic Amplification (AA), namely the recent amplified warming in the Arctic region compared to lower latitudes, has recently been argued to have an impact on blocking patterns and behaviour at mid-high latitudes.

The objective of this study is to investigate the most relevant mechanisms playing a role in the relationship between blocking and Arctic Amplification, by analysing the variability and frequency of the associated spatial patterns at various timescales using variables from the ERA5 reanalysis dataset for the time interval 1959-2022. Blocking events are detected based on geopotential height gradients between mid- and high-latitude regions, while Arctic Amplification is quantified as the difference of 1000hPa temperature between high and mid latitudes.

The climatological number of events per year and their average lifetime, along with the long-term trends and their relationship with the AA are analysed. Furthermore, possible mechanisms linking blocking variability and the AA are explored through the analysis of the jetstream dynamics and teleconnection patterns in the Northern Hemisphere.

How to cite: Cadau, M., Fosser, G., Bordoni, S., Sannino, G., and Gaetani, M.: On the relationship between Atmospheric Blocking and Arctic Amplification, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7466, https://doi.org/10.5194/egusphere-egu23-7466, 2023.

Since 1980, the U.S. experienced 338 different billion-dollar weather and climate disasters, with greater than 25% (n = 96) of these occurring in the cold season of December–March. These events can have lasting societal and economic impacts that make diagnosing their likelihood of occurrence in the next week, season, or decade an important problem in the context of our changing climate. This analysis will focus on a case study of the predictability and dynamics of the 2021 US cold air outbreak (CAO) and provide a multiscale overview of the event on subseasonal-to-seasonal (S2S) timescales. The analysis of the dynamics focuses on the role of the stratospheric recovery from the January 2021 sudden stratospheric warming and a stratospheric Rossby wave reflection event in the context of the development of high amplitude flow in early February 2021. The second part considers the ability of S2S forecast models to resolve the predecessor events to this CAO. The predictability of this CAO and the role of the stratosphere in the development of CAO are considered by analyzing both high-top and low-top S2S forecast model from the S2S prediction Project Database.

How to cite: Lang, A.: The dynamics and predictability of US winter extremes—a multiscale case study of the 2021 U.S. cold air outbreak, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7975, https://doi.org/10.5194/egusphere-egu23-7975, 2023.

EGU23-8062 | ECS | Orals | AS1.17

Potential Role of Inter-Basin Interactions in Eurasian Summer Blocking 

Lina Boljka, Nour-Eddine Omrani, Ho-Nam Cheung, Noel Keenlyside, Hisashi Nakamura, Clemens Spensberger, and Fumiaki Ogawa

Atmospheric blocking events are persistent tropospheric weather patterns that are associated with extreme events, such as heatwaves. In the summer, they primarily occur at high latitudes, e.g., over northern Eurasia. However, blocking frequency over these regions is underestimated in climate models, and often overestimated over the midlatitudes, while causes for such discrepancies remain elusive. To improve model representation of blocking frequency, it is important to understand different processes that affect it. Here, we explore blocking frequency in a reanalysis and experiments with an atmospheric general circulation model forced with different sea surface temperature (SSTs) profiles. The configurations range from an idealized no SST-front experiment and prescribing idealized SST-front in different regions to prescribing realistic climatological SSTs. Surprisingly, this reveals that more idealized (realistic) experiments lead to more (less) realistic blocking frequency. We find that weaker (less realistic) blocking frequency over northern Eurasia is primarily caused by the circulation changes related to SST gradients over the North Pacific. This suggests an important role of inter-basin interactions between the Atlantic and the Pacific. Additionally, tropical teleconnections can also play a role. This may suggest that models struggle with circulation response to SSTs in boreal summer, especially over the North Pacific. Thus, this work has implications for simulating (future) summer heat (and other) extremes over the high latitudes.

How to cite: Boljka, L., Omrani, N.-E., Cheung, H.-N., Keenlyside, N., Nakamura, H., Spensberger, C., and Ogawa, F.: Potential Role of Inter-Basin Interactions in Eurasian Summer Blocking, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8062, https://doi.org/10.5194/egusphere-egu23-8062, 2023.

The successful prediction of heatwave onsets on the medium-range forecast time scale (here, 5-12 days) mainly relies on the adequate forecasting of large-scale Rossby wave patterns and their dynamics. In the mid-latitude regions of Europe, lasting heatwaves are often associated with a substantial blocking of the large-scale atmospheric flow due to amplified and/or breaking Rossby waves. To characterize such anomalous flow configurations, which may come in different patterns, we adopt the concept of Euro-Atlantic weather regimes. Based on Empirical Orthogonal Function analysis and subsequent k-means clustering, this widely-used metric reduces the complexity of the atmospheric flow field by projecting it onto the seven main modes of synoptic-scale variability in this domain.  In this study, we therefore examine heatwave characteristics in different European regions in relation to Euro-Atlantic weather regimes. A focus is set on the question to which extent the medium-range predictability of heatwave onsets depends on the current or preceding weather regime as well as to flow anomalies further upstream or other potential precursors not directly related to Rossby wave dynamics such as abnormally dry soils. 

Heatwaves are objectively diagnosed as a 90th percentile exceedance in 2m maximum temperatures for a minimum of 3 days in both a local and regional context.  Using ERA-5 data for the period 1979-present, we find that British and Scandinavian heatwaves are mainly associated with classic blocking regimes (Scandinavian and European blocking), whereas the picture is more diverse for Central Europe where the „no regime“ case is also frequently observed. Remarkably, over the last 20 years, European heatwaves associated with a European blocking seem to be significantly related to pre-existing anomalously dry soils over large parts of Northern America which is, however, not the case for heatwaves related to any other weather regime. 

The medium-range predictability of heatwaves is investigated for the period 2001-2018, using hindcast ensembles of two state-of-the art weather forecast models ECMWF-IFS and GEFS-v12, by means of usual metrics such as 500hPa geopotential anomaly correlation coefficients (ACC) and 850hPa temperature mean absolute errors. Preliminary results with a focus on Central Europe suggest that heatwaves in this region seem to be slightly more predictable (roughly one more day until ACC drops below 0.8) when they occur in conjunction with a Scandinavian or European blocking compared to the case with no apparent regime. This may be explained by the overall more transient and phase-error prone nature of the „no regime“-type heatwaves. Interestingly, heatwaves with the worst predictability at 10 days lead time show an intensified jet stream over the Atlantic one week prior and a slight tendency toward wetter than normal soils over North America and Central Europe.

Finally, we also investigate to which extent medium-range forecasts of local maximum temperatures further depend on more local, diabatic processes (soil moisture, cloud cover forecast) and whether there are systematic differences between lead times and weather regimes.

How to cite: Lemburg, A. and Fink, A. H.: Investigating European heatwaves and their medium-range predictability in relation to weather regimes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8139, https://doi.org/10.5194/egusphere-egu23-8139, 2023.

EGU23-8210 | Orals | AS1.17

A linearized approach to study stability and waveguidability of barotropic Rossby waves 

Antonio Segalini, Jacopo Riboldi, Volkmar Wirth, and Gabriele Messori

The propagation and the characteristics of Rossby waves are influenced by the large-scale background flow where they occur: for instance, the role of upper-level jet streams in promoting Rossby wave propagation along preferred directions (so-called “waveguidability”) is a classic problem in climate dynamics. We propose a linear framework to study barotropic Rossby waves over a spherical domain for arbitrary orographic forcing and zonal background flow configurations, including cases with localised single and double jet streams. The approach allows to analytically obtain the steady-state linear flow response to orographic forcing without performing lengthy numerical integrations, together with the flow evolution as a combination of few modes composed by the various eigensolutions of the unforced problem (thus independent of the forcing). The connection between jet strength and waveguidability noticed by previous studies is confirmed. Background flow states featuring a strong jet stream are also prone to barotropic instability.

The eigenvalue analysis reveals the spatial structure of the associated Rossby modes and their growth rates, allowing to detect the presence of instabilities. We notice that, even in presence of a damping term, some background flow configurations allow wave instabilities to exist. According to the linear theory, the flow should diverge from the equilibrium state, since some waves are linearly unstable. Nonlinear simulations are performed to provide insights about the waves evolution in the unstable case. Such simulations reveal two interesting effects: 1) a damping effect operated by the nonlinear terms (i.e., the flow is unstable linearly but stable nonlinearly) for medium jet strengths; 2) a quasi-periodic behaviour around the unstable equilibrium state for the strongest jets, indicating the existence of a limit cycle. The linear analysis was still able to capture the unstable equilibrium state at the center of the limit cycle and to provide insights about the spatial structure of the dominant modes. These results indicate the usefulness of linearized approaches in the development of a reduced-order model to describe the barotropic instability mechanisms driving spherical Rossby waves.

How to cite: Segalini, A., Riboldi, J., Wirth, V., and Messori, G.: A linearized approach to study stability and waveguidability of barotropic Rossby waves, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8210, https://doi.org/10.5194/egusphere-egu23-8210, 2023.

EGU23-8331 | ECS | Orals | AS1.17

Extremes of meridional energy transports in Northern Hemisphere mid-latitudes across zonal wavenumbers and dominant weather regimes 

Valerio Lembo, Federico Fabiano, Vera Melinda Galfi, Rune Grand Graversen, Valerio Lucarini, and Gabriele Messori

Extremes in extratropical meridional energy transports in the atmosphere are associated with the dynamics of the atmosphere at multiple spatial scales, from planetary to synoptic. This is related to the nature of amplifying baroclinic waves, that are fundamentally intermittent and sporadic, significantly affecting the net seasonal transport across latitudes. Here, we use the ERA5 reanalysis data to perform a wavenumber decomposition of meridional energy transports in the Northern Hemisphere mid-latitudes during winter and summer. Extreme transport events are linked to atmospheric circulation anomalies and dominant weather regimes, identified by clustering 500 hPa geopotential height fields. Partitioning the extreme events across zonal wavenumber highlights the different role of scales in different seasons and regions. In general, planetary-scale waves determine the strength and meridional position of the synoptic-scale baroclinic activity with their phase and amplitude. 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. Focusing on recently occurred exceptionally strong summertime heat waves and wintertime cold spells, we notice that regime structures of these events are typical of extremely large poleward meridional energy transports.

How to cite: Lembo, V., Fabiano, F., Galfi, V. M., Graversen, R. G., Lucarini, V., and Messori, G.: Extremes of meridional energy transports in Northern Hemisphere mid-latitudes across zonal wavenumbers and dominant weather regimes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8331, https://doi.org/10.5194/egusphere-egu23-8331, 2023.

EGU23-8399 | ECS | Posters on site | AS1.17

Jet Regimes Induced by Stratification Changes in a Dry Dynamical Core Model 

Pablo Conrat Fuentes, Thomas Birner, and Hella Garny

The tropical circulation is typically not well represented in idealized models used to study jet dynamics. 
We implement a convective relaxation algorithm into a dry dynamical core model following Schneider and Walker (2006) to improve the representation of the driving mechanism behind the subtropical jet: the tropical meridional overturning.
We study the dependence of the general circulation on the vertical stratification set by a convective relaxation scheme.
Varying tropospheric lapse rates produces two jet regimes that are characterized by the distance between the subtropical jet and the eddy-driven jet.
The separated jet state features distances of more than 12° latitude between subtropical and eddy-driven jet and is dominant in simulations with higher tropospheric static stability.
Both jets approximately coincide in the joined jet regime, which is dominant in lower stability simulations.

In addition to a steady state analysis, transitions from one regime to the other are induced by changes in convective lapse rate.
Regime changes are also observed as events produced by natural variability in some of the model runs.
This time-dependent perspective shows that the structure of net Rossby wave dissipation in the upper troposphere, measured by the Eliassen-Palm flux divergence, is crucial in order to understand the regimes.
Jet merge and split events are mediated by upper tropospheric momentum flux variability.
They are preceded by heat flux variability and are tied to variations in the hemispheric eddy kinetic energy.
The results are also interpreted through the concept of criticality, relating meridional and vertical gradients in potential temperature.
The analysis highlights the importance of static stability and its changes to mid-latitude jet dynamics.

How to cite: Conrat Fuentes, P., Birner, T., and Garny, H.: Jet Regimes Induced by Stratification Changes in a Dry Dynamical Core Model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8399, https://doi.org/10.5194/egusphere-egu23-8399, 2023.

EGU23-8465 | ECS | Posters on site | AS1.17

Long-term variability of Rossby Wave Breaking events over the Indian subcontinent 

Biyo Thomas, Ravi Kumar Kunchala, Bhupendra Bahadur Singh, and Niranjan Kumar Kondapalli

The synoptic scale upper level Rossby wave breaking (RWB) has a great influence on the weather pattern on the underlying regions. The RWB events have been studied extensively in the mid-latitude regions as it is prone to such events which often lead to extreme weather conditions. However, studies are elusive especially over the Indian sub-continent except few cases. RWB climatology and variability on monthly, interannual as well as on decadal scales is still poorly understood over this region. To address these shortcomings, in this study, we have used the reanalysis data and implemented a contour searching algorithm to identify RWB events over the period 1979-2021. Using the implemented algorithm, we have detected 513 RWB events for the study period which we further use to examine RWB climatology and variability over the subcontinent (5-40oN, 55-105oE). Our results suggest a significant increase in the number of RWB events per year during the last  two decades, as well as an increase in the intensity over the northwest region of the Indian subcontinent. We note that the RWB frequently affects the northwest region in winter, which later shows a shift in peak number of occurrences of RWB towards central India at the end of winter. This shift is linked to seasonal changes in the background zonal wind in the upper-troposphere. Also, the monthly climatology of vertical intrusions of the PV streamers indicate that intrusions are stronger during winter than other months. In addition, the role of RWB on the dynamical changes of the atmosphere such as anomalies of wind circulation patterns and moisture content is analyzed using composite analysis. The variability of the RWB events and its linkages with global sea surface temperature particularly conditions in the Pacific Ocean have also been studied.

How to cite: Thomas, B., Kunchala, R. K., Singh, B. B., and Kondapalli, N. K.: Long-term variability of Rossby Wave Breaking events over the Indian subcontinent, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8465, https://doi.org/10.5194/egusphere-egu23-8465, 2023.

When different weather extremes occur at multiple locations at the same time, their aggregated impact can exceed the one of the individual events. Examples can be concomitant summer heatwaves over major breadbasket regions, leading to potential food shortages at the global scale, or the connection between cold spells over North America and windstorms over Europe. These compound events often attract a broad interest by the media and society, as anomalous weather conditions seem to occur “everywhere at the same time”. If it is possible to identify a physical linkage between them, those separate extremes can be considered as parts of a single, spatially compounding weather extreme. Pinpointing a common physical driver is not trivial, however, and it might well be that such extreme events just co-occur by coincidence.

This overview presentation will discuss how the linear and nonlinear dynamics of Rossby waves can help to understand spatially compounding extremes. Examples of linear dynamics involve the propagation of Rossby wave packets across broad portions of the middle latitudes, aided by the presence of upper-level waveguides. The link between extreme weather and atmospheric blocking, on the other hand, can be seen as involving a nonlinear sort of dynamics. Analytical, idealized and data-driven approaches to the study of Rossby waves can shed light on the drivers of spatially compounding extremes, and result in useful tools to study how the drivers of such extremes are being affected by anthropogenic global warming.

How to cite: Riboldi, J.: On the connection between Rossby waves and spatially compounding weather extremes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8587, https://doi.org/10.5194/egusphere-egu23-8587, 2023.

EGU23-8620 | ECS | Posters on site | AS1.17

Variability of beta-plane zonal jets 

Wenzhong Wang and Peter Haynes

The dynamics of the mid-latitude atmospheric jet is an important component of internal variability in real and modelled climate. The variability may also potentially affect the response to deterministic external forcing, with implications for seasonal prediction including the ‘signal-to-noise’ paradox. Recent research has used ad hoc probabilistic approaches to investigate the paradox but has given little dynamical insight into the behaviour observed in models. This motivates further dynamical study of the factors determining variability and response to forcing. We use a simple stochastically forced barotropic model containing the essential mechanisms for beta-plane jet variability to conduct a range of numerical experiments. We consider first the dependence of the behaviour on the damping time scale and on the amplitude and latitudinal width of stochastic forcing that is statistically homogeneous in longitude. We consider leading empirical orthogonal functions of the zonal mean wind velocity, use these as quantifiers of jet behaviour, and analyse the amplitude, latitudinal structure, and autocorrelation time scale of the simulated variability. We move on to examine cases where there is imposed longitudinal variation. An appropriate decorrelation time scale of the zonal jet stream could be displayed by the model, partly depending on the damping time scale. We conduct experiments with applied forcing to determine whether the basic prediction of the fluctuation-dissipation theorem, that response to forcing is proportional to the autocorrelation time scale for natural variability, holds in this system. This simple dynamical model has good implications for a physical understanding of jet persistence and the signal-to-noise paradox. 

How to cite: Wang, W. and Haynes, P.: Variability of beta-plane zonal jets, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8620, https://doi.org/10.5194/egusphere-egu23-8620, 2023.

EGU23-9353 | ECS | Posters on site | AS1.17

A Thermal Wind Perspective of Driving Changes in Jet Stream Patterns 

Mehmet Sedat Gözlet, Joakim Kjellsson, and Mojib Latif

It is evident that the jet streams are becoming more erratic and unstable in a changing climate. We investigate changes both in position and speed of the midlatitude jet streams at 300 hPa in  31 Atmospheric Model Intercomparison Project (AMIP) runs and the ERA5 reanalysis dataset investigating the ability of the thermal wind concept to explain changes in place and the regime of the jet streams, which are disturbed by Arctic amplification, is the core of this work. All data covers the period 1979-2014. 
 
It is revealed that the changes in jet stream magnitude and position in the multi-model mean (MMM) can largely be explained by the thermal wind. We also discovered that the AMIP models reproduce trends in jet position and strength seen in  ERA5. Yet it is a must to state that when inspecting individual models, we find that some models can reproduce ERA5 trends in NH. The large variance in modelled trends, however, leads to a poorly represented MMM.
 
In the end, the jet stream plays a significant role in shaping global weather patterns and is affected by changing climate as becoming more wobbly and unstable. The potential impact of Arctic warming on the jet stream and how it may lead to more extreme weather events in the mid-latitudes is taken under inspection from the window of thermal wind concept with this study. 

How to cite: Gözlet, M. S., Kjellsson, J., and Latif, M.: A Thermal Wind Perspective of Driving Changes in Jet Stream Patterns, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9353, https://doi.org/10.5194/egusphere-egu23-9353, 2023.

EGU23-9918 | ECS | Orals | AS1.17

Extreme weather in the Southern Hemisphere in early 2022: from Rossby waves to planetary-scale conditions 

Andries Jan De Vries, Jake William Casselman, Hilla Afargan-Gerstman, Shingirai Shepard Nangombe, Romain Pilon, Emmanuele Russo, Wolfgang Wicker, Priyanka Yadav, and Daniela I.V. Domeisen

In early 2022, several extreme weather events occurred in the Southern Hemisphere. Devastating floods killed more than 500 people in South Africa (11-12 April) and about 26 people in eastern Australia (24-28 February and 25-31 March), while an unprecedented heatwave broke temperature records in Antarctica (16-22 March). This study presents a multiscale perspective of the atmospheric processes associated with these extreme events from synoptic to planetary scales. Equatorward Rossby wave breaking facilitated the transport of moist air from tropical oceans to the subtropical regions affected by the extreme precipitation events, while poleward Rossby wave breaking forced an intrusion of warm and moist extratropical air masses into the Antarctic Peninsula. Southern hemispheric extratropical wave activity demonstrated relatively normal conditions during February and March, while wave energy reached extremely large values for wave number 5 during April. From a planetary-scale perspective, we investigate how tropical variability, including the El-Nino Southern Oscillation (ENSO; in a La Nina phase) and the Madden-Julian Oscillation (MJO), modulates large-scale atmospheric circulation patterns, extratropical wave activity, and Rossby wave breaking. Overall, this study clarifies the role of regional and remote atmospheric processes in the recent weather extremes in the Southern Hemisphere.

How to cite: De Vries, A. J., Casselman, J. W., Afargan-Gerstman, H., Nangombe, S. S., Pilon, R., Russo, E., Wicker, W., Yadav, P., and Domeisen, D. I. V.: Extreme weather in the Southern Hemisphere in early 2022: from Rossby waves to planetary-scale conditions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9918, https://doi.org/10.5194/egusphere-egu23-9918, 2023.

Wind-driven dust emission from dry, exposed land surfaces plays an important role in the climate system, and also contributes to severe weather and public health hazards around the world. In the past several years, the Northern Hemisphere midlatitude region was stuck by several extreme dust storms with severe socioeconomic and environment consequences within and beyond the dryland source areas. For instance, the 26-27 May 2018 salt storm from the dried-up Aral Sea was considered a first-of-its-kind ecological catastrophe over Central Asia. In March 2021, northern China was hit by the worst sand storm in a decade. Later in November, Uzbekistan recorded the worst dust storm through the country’s meteorological record. Currently, significant knowledge and methodological gaps exist in characterizing the multivariate compound dust events. This study is a first attempt to develop a multivariate approach and ground-based climatology to improve our knowledge of the historical variations, spatial distributions, and governing factors of extreme dust outbreaks over the drylands of Central and East Asia. Detailed case studies will also be conducted to elucidate the role of tropic Pacific and Arctic warming and Rossby wave activities in triggering recent extreme dust events.

How to cite: Xi, X.: A first look at the multivariate extreme dust outbreak over Northern Hemisphere midlatitudes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10425, https://doi.org/10.5194/egusphere-egu23-10425, 2023.

EGU23-12319 | ECS | Orals | AS1.17

Heatwaves of 2018: connecting large-scale to synoptic scale circulation 

Maria Pyrina and Daniela Domeisen

The intensity of heat extremes has been increasing in recent decades, with several recent notable heatwaves afflicting highly populated areas. Previous studies have related heatwaves to slow moving amplified Rossby waves, due to the formation of circumglobal teleconnections (i.e., European heatwaves of 2003 and 2010). Other studies have found that there is a statistical link between high amplitude upper-tropospheric transient Rossby wave packets (RWPs) and increased probability of lower-tropospheric temperature extremes. These non-circumglobal RWP amplitudes were found to be better linked to temperature extremes than Fourier amplitudes quantifying circumglobal waviness, including the European heatwaves of 2003 and 2010. In the summer of 2018, several record-breaking and persistent heatwaves occurred simultaneously around the globe and were linked to an amplified hemisphere-wide wavenumber 7 circulation pattern. Here, we investigate the relation of the synoptic RWPs and the circumglobal characteristics of atmospheric circulation characteristics with the heatwaves during 1998-2018, with a focus on the heatwaves that occurred during the summer of 2018.  Preliminary results show that the dominant circumglobal pattern for the 2018 summer heat extremes was dominated by a zonal wavenumber 6 circulation pattern and that its amplitude was connected to high amplitude RWPs that occur across the Northern Hemisphere.

How to cite: Pyrina, M. and Domeisen, D.: Heatwaves of 2018: connecting large-scale to synoptic scale circulation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12319, https://doi.org/10.5194/egusphere-egu23-12319, 2023.

EGU23-12703 | ECS | Orals | AS1.17

Intransitive Atmosphere Dynamics Leading to Persistent Hot–Dry or Cold–Wet European Summers 

Ruud Sperna Weiland, Karin van der Wiel, Frank Selten, and Dim Coumou

Persistent hot–dry or cold–wet summer weather can have significant impacts on agriculture, health, and the environment. For northwestern Europe, these weather regimes are typically linked to, respectively, blocked or zonal jet stream states. The fundamental dynamics underlying these circulation states are still poorly understood. Edward Lorenz postulated that summer circulation may be either fully or almost intransitive, implying that part of the phase space (capturing circulation variability) cannot be reached within one specific summer. If true, this would have major implications for the predictability of summer weather and our understanding of the drivers of interannual variability of summer weather. Here, we test the two Lorenz hypotheses (i.e., fully or almost intransitive) for European summer circulation, capitalizing on a newly available very large ensemble (2000 years) of present-day climate data in the fully coupled global climate model EC-Earth. Using self-organizing maps, we quantify the phase space of summer circulation and the trajectories through phase space in unprecedented detail. We show that, based on Markov assumptions, the summer circulation is strongly dependent on its initial state in early summer with the atmospheric memory ranging from 28 days up to ~45 days. The memory is particularly long if the initial state is either a blocked or a zonal flow state. Furthermore, we identify two groups of summers that are characterized by distinctly different trajectories through phase space, and that prefer either a blocked or zonal circulation state, respectively. These results suggest that intransitivity is indeed a fundamental property of the atmosphere and an important driver of interannual variability.

How to cite: Sperna Weiland, R., van der Wiel, K., Selten, F., and Coumou, D.: Intransitive Atmosphere Dynamics Leading to Persistent Hot–Dry or Cold–Wet European Summers, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12703, https://doi.org/10.5194/egusphere-egu23-12703, 2023.

EGU23-14014 | Orals | AS1.17

Potential impact of tropopause sharpness on jet latitude 

Thomas Birner and Lina Boljka

The wintertime extratropical general circulation may be viewed as being primarily governed by interactions between Rossby waves and the background flow. These Rossby waves propagate vertically and meridionally away from their sources and amplify within the core of the tropopause-level jet, which acts as a waveguide. The strength of this waveguide is in part controlled by tropopause sharpness, which itself is a function of the strength of tropopause inversion layer (TIL), a layer of enhanced static stability just above the tropopause. Here, we report a strong relation between interannual-to-multidecadal variations in the strength of the midlatitude TIL and jet latitude in a reanalysis and climate models. Similar relationships hold for the variability across climate models. Experiments with a mechanistic model show that a sharper tropopause promotes an intensified general circulation and an equatorward shifted jet.

Reference: https://doi.org/10.1038/s41612-022-00319-6

How to cite: Birner, T. and Boljka, L.: Potential impact of tropopause sharpness on jet latitude, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14014, https://doi.org/10.5194/egusphere-egu23-14014, 2023.

EGU23-14529 | Posters on site | AS1.17

Summer jet stream response to global af-/reforestation and deforestation 

Iris Manola, Dim Coumou, Fei Luo, Suqi Guo, Felix Havermann, Steven De Hertog, Quenting Lejeune, Inga Menke, Julia Pongratz, Carl Schleussner, Sonia Seneviratne, and Wim Thiery

 

Global-scale af-/reforestation (A/R) and deforestation substantially changes the Earth’s energy and water fluxes, thereby affecting the large-scale atmospheric circulation and thus have significant impacts on weather systems. During summer, A/R and deforestation induced changes in the soil moisture are shown to have an impact on the planetary wave response through the jet stream. Such changes might lead to high-amplitude, quasi-stationary circumglobal Rossby waves that have been associated with extreme summer heatwaves and persistent high-impact extremes. In this study we investigate how idealized global land use and land management changes can alter the boreal summer circulation with a focus on the response of the jet stream. For the analysis we conducted model experiments with three fully coupled Earth System Models (EC-EARTH, MPI-ESM and CESM). Each scenario run for 160 years from which we analyze the final 30 years.  A control run with constant current land use and land management is compared to a global A/R and a global deforestation (global cropland expansion) simulation. In order to assess clean land-atmosphere interactions, all simulations are kept with constant present-day atmospheric forcings (year 2014). We investigate the potential changes in the amplitude of the waves, the likelihood of quasi-stationary wave activity, and of summer blockings within the three different simulations, and the weather consequences that such changes lead to.

How to cite: Manola, I., Coumou, D., Luo, F., Guo, S., Havermann, F., De Hertog, S., Lejeune, Q., Menke, I., Pongratz, J., Schleussner, C., Seneviratne, S., and Thiery, W.: Summer jet stream response to global af-/reforestation and deforestation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14529, https://doi.org/10.5194/egusphere-egu23-14529, 2023.

EGU23-15986 | ECS | Posters on site | AS1.17

Projected changes on quasi-resonant amplification by CMIP5 and CMIP6 toward the persistence in extreme summer weather events 

Sullyandro Oliveira Guimarães, Michael E. Mann, Stefan Rahmstorf, Stefan Petri, Kai Kornhuber, Dim Coumou, Byron A. Steinman, Daniel Brouillette, and Shannon Christiansen

 
High-amplitude quasi-stationary atmospheric Rossby waves with zonal wave numbers 6 to 8 associated with the phenomenon of quasi-resonant amplification (QRA) have been linked to persistent summer extreme weather events in the Northern Hemisphere. We project future occurrence of QRA events based on an index derived from the zonally averaged surface temperature field, comparing results from CMIP5 and CMIP6 (Coupled Model Intercomparison Projects) climate projections. Under the scenarios analyzed, there is a general agreement among models, with most simulations projecting a substantial increase in QRA index. Larger increases are found among CMIP6-SSP585 (42 models, 46 realizations) models with 85% of models displaying a positive trend, as compared with as compared with 60% of CMIP5-RCP85 (35 models, 75 realizations), and a reduced spread among SSP585 models. The CMIP6-SSP370 (24 models, 28 realizations) simulations display qualitatively similar behavior to SSP585, indicating a substantial increase in QRA events under business-as-usual emissions scenarios. Our analysis suggests that anthropogenic warming will likely lead to an even more substantial increase in QRA events (and associated summer weather extremes) than our previous analysis of CMIP5 simulations.

How to cite: Oliveira Guimarães, S., E. Mann, M., Rahmstorf, S., Petri, S., Kornhuber, K., Coumou, D., A. Steinman, B., Brouillette, D., and Christiansen, S.: Projected changes on quasi-resonant amplification by CMIP5 and CMIP6 toward the persistence in extreme summer weather events, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15986, https://doi.org/10.5194/egusphere-egu23-15986, 2023.

EGU23-16490 | Posters on site | AS1.17

On the role of Rossby wave phase speed for persistent temperature extremes 

Wolfgang Wicker and Daniela Domeisen

Case studies of mid-latitude summer heatwaves commonly regard stationary synoptic-scale Rossby waves as the primary dynamical forcing. Whether this relationship between upper-tropospheric Rossby wave phase speed and persistent temperature extremes can be generalized is less clear. Here, we evaluate interannual and intra-seasonal variability of Rossby wave phase speed in reanalysis datasets employing circumglobal spectral analysis and investigate episodes with a low or a high zonal phase speed, respectively. Locally, we find evidence of Rossby wave phase preferences during episodes with a low phase speed, where preferred locations of ridges coincide with regions of increased heatwave frequency, but globally, there is no indication of an increased heatwave frequency. Unexpectedly, the finding of Rossby wave phase preferences and increased heatwave frequency also hold for episodes with a high phase speed, although in different areas of the summer hemisphere mid-latitudes. These findings, in particular about episodes with a zonal phase speed, will improve our mechanistic understanding of the dynamical drivers of heatwaves.

How to cite: Wicker, W. and Domeisen, D.: On the role of Rossby wave phase speed for persistent temperature extremes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16490, https://doi.org/10.5194/egusphere-egu23-16490, 2023.

EGU23-16756 | ECS | Orals | AS1.17

Role of Quasi-resonant Planetary Wave Dynamics in Winter Precipitation Extremes over India’s High Mountain Region 

Nischal Sharma, Raju Attada, and Kieran M.R. Hunt

Abstract

Extreme precipitation during winter over the western Himalayas (WH) is associated with western disturbances embedded in sub-tropical westerly jet streams, which are potentially linked to planetary wave dynamics. In this study, we explore a possible connection of quasi-resonant amplification (QRA) to precipitation extremes observed over WH using the global high-resolution reanalysis ERA5 during the period 1979-2019. Precipitation extremes have been identified using percentile approach (peak over threshold) where daily precipitation amount from the entire time series of precipitation exceeds the 95th percentile threshold at a particular grid point. Our analysis suggests that substantially magnified, quasi stationary mid-latitude planetary waves with zonal wavenumbers 6 to 8 accompany these extremes, highlighting the influence of QRA phenomenon. Furthermore, we also identified a fingerprint for QRA occurrence in terms of the zonally averaged surface temperature field. Lastly, we classified extreme precipitation intensities and various related key variables using k-means clustering and analyzed the wavenumbers associated with different categories. Our results underpin the significant role of the QRA mechanism in amplification of planetary waves, in turn, favoring western Himalayan precipitation extremes. Detailed results will be discussed.

Keywords: Quasi-resonant amplification, zonal wavenumber, precipitation extremes, western Himalayas

*E-mail of corresponding author: rajuattada@iisermohali.ac.in

How to cite: Sharma, N., Attada, R., and Hunt, K. M. R.: Role of Quasi-resonant Planetary Wave Dynamics in Winter Precipitation Extremes over India’s High Mountain Region, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16756, https://doi.org/10.5194/egusphere-egu23-16756, 2023.

Indian Ocean Dipole (IOD) is an air-sea coupled variability in the Tropical Indian Ocean (TIO), which strongly impacts climate variability over the Indian Ocean rim countries. Though many positive IODs co-occurred with El Niño Southern Oscillation (ENSO), IODs do evolve independently, suggesting the possible role of internal dynamics of the Indian Ocean. In this study, the subtropical IOD (SIOD) is reported as one of the triggers for non-ENSO IODs. The study highlights the existence of cyclic feedback between IOD and SIOD through tropical subtropical interaction, a possible mechanism for the biennial tendency of both IOD and SIOD modes. The positive SIOD induce warming in the southwest of the Subtropical South Indian Ocean (SSIO) during April-May months and creates a meridional cell with subsidence over the southwestern TIO region (10oS). The subsidence expands the existing anticyclonic circulation over SSIO towards the equator and develops easterlies along the equator, warming the western TIO region. A zonal-vertical cell with convection over the western TIO and subsidence over the eastern TIO originates during June-July, which subsequently generates positive IOD in the following months. The positive IOD triggers negative SIOD by developing a stationary Rossby wave train in the midlatitudes. The southeastern anticyclonic circulation develops during the IOD peak season as Gill’s response initiates warm SST anomalies in the northeastern subtropics. As a result of the warming, the evolution of upper-level divergence and high absolute vorticity gradient over the subtropics generate an equivalent barotropic Rossby wave number 3 pattern in the extratropics. The cyclonic circulation over the southwest SSIO related to this Rossby wave pattern creates cold SST anomalies there. The cooling in the southwest and the warming in the northeast SSIO persisted from the IOD peak season, which strengthened the cyclonic circulation over SSIO, reinforcing the existing negative and positive SST anomalies through a positive feedback mechanism and generating negative SIOD, which peaks in the following January-March months.

How to cite: Sebastian, A. and Gnanaseelan, C.: Coupled feedback between the tropics and subtropics of the Indian Ocean with emphasis on the coupled interaction between IOD and SIOD, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-373, https://doi.org/10.5194/egusphere-egu23-373, 2023.

Tropical cyclone (TC) activity varies substantially yearly, and tropical cyclone-related damage also changes. Longer-term prediction of tropical cyclones plays an important role in reducing the wear and human loss caused by TCs. In this study, we have used a Causal-network-based algorithm to find the main development regions and precursors responsible for TC genesis and intensification. However, all the extreme events are interconnected through various global links. Therefore, analysis of the teleconnection and correlation of Tropical Cyclones with El Nino Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and North Atlantic Oscillation (NAO) during the satellite era (1980-2020) over the North Indian Ocean (NIO) basins using this Causal Effect Network (CEN) based algorithms is checked. The most appropriate metric for cyclone energy is Accumulated Cyclone Energy (ACE); its correlation with the various factors are investigated. We examined the variation in TCs activity during all three phases (positive, negative, and neutral phases).

The results show an increasing trend in ACE over the NIO region during that specific period. The duration of most intense cyclones is increased, but their frequency decreases in this period. A shift in ACE starts after 1997 and still rises significantly. Analysis of Sea Surface Temperature (SST), Vertical Wind Shear (VWS) between 850 and 250 hPa, mid-tropospheric (800 hPa) Relative Humidity (RH), low level (850 hPa) Relative Vorticity (RV), and Tropical Cyclone Heat Potential (TCHP) is done, and it shows positive changes and variability of ACE. These results may help get better knowledge about the atmospheric or oceanic teleconnections between the events, and improved tropical cyclone prediction can help reduce the loss caused by the TCs.        

How to cite: kumar sagar, A.: identification of robust predictors of tropical cyclones using causal effect network over the north indian ocean, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-502, https://doi.org/10.5194/egusphere-egu23-502, 2023.

EGU23-595 | ECS | Posters on site | CL4.6

Intra-decadal variability of the Indian Ocean shallow meridional overturning circulation during boreal winter 

Rahul Pai, Anant Parekh, Jasti S Chowdary, and Gnanaseelan Chellappan

The variability of Indian Ocean shallow meridional overturning circulation (SMOC) is studied using the century-long ocean reanalysis simple ocean data assimilation (SODA) data. Though SMOC exhibits stronger southward transport during boreal summer, it displays stronger variability during boreal winter. The spectrum analysis of the winter SMOC index reveals the presence of the highest amplitude between 5 to 7 years at 95% confidence level, suggesting the dominance of intra-decadal SMOC variability. The robustness of intra-decadal SMOC variability is also confirmed in different ocean reanalysis data sets. Composite analysis of filtered upper Ocean Heat Content, sea level, thermocline depth, and Sea Surface Temperature anomalies for strong (weak) SMOC years show negative (positive) anomalies over north and East of Madagascar. Correlation analysis, of filtered SMOC index and sea level pressure (zonal winds) over the Indian Ocean, found a significant negative (positive) correlation coefficient north of 40 °S (around 10 °S) and a significantly positive (negative) correlation coefficient over the 45 °S to 70 °S (20 °S to 50 °S and north of 5 °S). This meridional pattern of the correlation coefficient for sea level pressure, manifesting the out-of-phase relationship between sub-tropics and high latitude mean sea level pressure, resembles Southern Annular Mode (SAM). We conclude that the intra-decadal variability of mean sea level pressure leads to zonal wind variation around 10 °S modulating SMOC, which in turn affects the upper ocean thermal properties in the east and north of Madagascar. This study for the first time brought out coherent intra-decadal evolution of SAM and SMOC during boreal winter.

How to cite: Pai, R., Parekh, A., Chowdary, J. S., and Chellappan, G.: Intra-decadal variability of the Indian Ocean shallow meridional overturning circulation during boreal winter, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-595, https://doi.org/10.5194/egusphere-egu23-595, 2023.

EGU23-864 | ECS | Posters on site | CL4.6

The Teleconnection of Indian Summer Monsoon Clouds with Global Predictors: An Unexplored Measure for Coupled Model development 

Ushnanshu Dutta, Anupam Hazra, Hemantkumar S Chaudhari, Subodh Kumar Saha, Samir Pokhrel, and Utkarsh Verma

The teleconnection studies regarding Indian summer monsoon (ISM) clouds are not focused on detail from both observational and modeling aspects. This is despite the fact that clouds play a seminal role in governing rainfall variability through the modulation of heating and induced circulation. Therefore, we find it essential to explore whether the inter-annual variability of ISM clouds is also remotely influenced by the slowly varying predictable component e.g. Sea Surface Temperature (SST). 

The findings reveal the linkage of observed TCF (and rainfall) over the ISM region with slowly varying forcing (e.g., global SST). The observed/reanalysis teleconnection pattern of TCF-SST is almost similar to that of rainfall-SST.In the long-term period, TCF and SST show a strong and positive correlation with Extra-Tropics (R ~ 0.41), NAO (R ~ 0.51), and AMO (R ~ 0.41) SST regions, in addition to canonical ENSO teleconnection (R ~ −0.39). This is better captured in CMIP6-MME than in CMIP5-MME. The representation of the global teleconnection pattern has been significantly improved in participating models from CMIP5 to CMIP6. The teleconnection with extra-tropics and north Atlantic mode of variability is markedly enhanced in CMIP6-MME compared to CMIP5-MME. The present study has also shown the lag correlations in the teleconnection analysis, i.e., the correlation of June–September (JJAS) mean of rainfall/TCF with October–December (OND) SST from observation/reanalysis, CMIP5-MME, and CMIP6-MME. The CMIP6-MME performs better than CMIP5-MME as compared to observation/reanalysis. 

Thus, the improved understanding of the teleconnection of cloud variables with ENSO and other predictors (ET, NAO, and AMO) will help researchers take up the challenges of improving the ISMR skill far ahead using the new generation coupled climate models. This may facilitate reliable seasonal ISM forecasting.

Keywords: Indian Summer Monsoon, Clouds, Teleconnection, CMIP5, CMIP6

How to cite: Dutta, U., Hazra, A., Chaudhari, H. S., Saha, S. K., Pokhrel, S., and Verma, U.: The Teleconnection of Indian Summer Monsoon Clouds with Global Predictors: An Unexplored Measure for Coupled Model development, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-864, https://doi.org/10.5194/egusphere-egu23-864, 2023.

EGU23-1944 | ECS | Orals | CL4.6

ENSO-driven abrupt phase shift in North Atlantic Oscillation in early January 

Xin Geng, Jiuwei Zhao, and Jong-Seong Kug

El Niño-Southern Oscillation (ENSO) teleconnections exhibit a strong dependency on seasonally and intraseasonally varying mean states, which leads to impactful short-term variations in regional climate. The North Atlantic Oscillation (NAO)-ENSO relation is a typical example, in that its phase relationship reverses systematically between the early and late winter. However, the details and underlying mechanisms of this relationship transition are not well understood yet.

Here based on observations and an ensemble of atmosphere-only climate model simulations, we first reveal that this NAO phase reversal occurs synchronously in early January, which indicates strong abruptness. We demonstrate that this abrupt NAO phase reversal is caused by the change in ENSO-induced Rossby wave-propagating direction from northeastward to southeastward over the northeastern North American region, which is largely governed by a climatological alteration of the local jet meridional shear. We also provide evidence that the North Atlantic intrinsic eddy–low-frequency flow feedback further facilitates and amplifies the NAO responses. This abrupt NAO phase reversal signal is strong enough during the ENSO winter to be useful for intraseasonal climate forecasting in the Euro-Atlantic region.

How to cite: Geng, X., Zhao, J., and Kug, J.-S.: ENSO-driven abrupt phase shift in North Atlantic Oscillation in early January, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1944, https://doi.org/10.5194/egusphere-egu23-1944, 2023.

Weather type classification is a well-established and thoroughly researched field of study in atmospheric sciences. One of its applications is the analysis of occurrence of and transitions between large scale synoptic types. This is typically done by calculating the moving average of, or estimating linear or polynomial fits to relative frequencies. The presented work points out the theoretical inconsistencies implied by such approaches and, instead, employs binomial and multinomial logistic regression for consistent estimation of long-term trends in occurrence and transition probabilities between synoptic types, while assuming first-order Markovian behaviour throughout. The methodological framework's functioning is demonstrated using two prominent examples of weather type classification schemes with regional focus on Germany and central Europe. Temporal refinement to seasonal and monthly level and aggregation into combined groups of classes allows for tracing of observed trends, providing a more comprehensive understanding of the systems investigated. The results, by and large, fit in well with expectations about circulatory changes suggested by research about global warming induced climate change and can be verified by existing research in some cases. Inspection of transition probability changes allows for differentiation between changes in occurrence probability caused by changes in the mean vs. changes in circulatory dynamics. Limitations and favourable implementational details of the approach are determined and the Wald Null test is recommended for assessing statistical significance.

How to cite: Schoeller, H.: Occurrence and Transition Probabilities for two Weather Classification Systems over Germany, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2004, https://doi.org/10.5194/egusphere-egu23-2004, 2023.

EGU23-2125 | Orals | CL4.6

Resolving weather fronts increases the large-scale circulation response to Gulf Stream SST anomalies 

Robert Jnglin Wills, Adam Herrington, Isla Simpson, and David Battisti

Canonical understanding based on general circulation models (GCMs) is that the large-scale circulation responds only weakly to extratropical sea-surface temperature (SST) anomalies, compared to the larger influence of tropical SST anomalies. However, the horizontal resolution of modern GCMs, which ranges from roughly 200 km to 25 km, is too coarse to fully resolve mesoscale atmospheric processes such as weather fronts. Here, we investigate the large-scale atmospheric circulation response to idealized Gulf Stream SST anomalies in a variable resolution version of the Community Atmospheric Model (CAM6), with regional grid refinement of 14 km over the North Atlantic, and compare it to versions with 28-km regional grid refinement and global 111-km resolution. The high-resolution simulations show a large positive response of the wintertime North Atlantic Oscillation (NAO) to positive SST anomalies in the Gulf Stream, a 1-standard-deviation NAO anomaly for 2°C SST anomalies. The lower-resolution simulations show a much weaker response, and in some cases, a different spatial structure of the response. The enhanced large-scale circulation response at high resolution results from an increase in resolved vertical motions, which enables SST forcing to have a larger influence on transient-eddy heat and momentum fluxes. In response to positive SST anomalies, these processes contribute to a stronger North Atlantic jet that varies less in latitude, as is characteristic of the positive phase of the NAO. Our results suggest that the atmospheric circulation response to extratropical SST anomalies is fundamentally different at higher resolution. Regional refinement in key regions offers a potential pathway towards improving simulation of the atmospheric response to extratropical SST anomalies and thereby improving multi-year regional climate predictions.

How to cite: Jnglin Wills, R., Herrington, A., Simpson, I., and Battisti, D.: Resolving weather fronts increases the large-scale circulation response to Gulf Stream SST anomalies, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2125, https://doi.org/10.5194/egusphere-egu23-2125, 2023.

EGU23-5034 | ECS | Orals | CL4.6

Impact of tropical eastern Pacific warming bias on Caribbean climate 

Marta Brotons Blanes, Rein Haarsma, and Nadie Bloemendaal

During the last decades, CMIP5 models simulate a warming trend in the tropical eastern Pacific that has not been present in observations (Seager et al., 2019). Associated with this, the Walker circulation has experienced a westward migration while CMIP5 models simulate an eastward migration. This mismatch is still present in CMIP6 models and might affect climate projections worldwide. In the Caribbean region, CMIP6 models project a strong drying at the end of the 21st century. El Niño-like changes in the Walker circulation are the dominant teleconnections driving the Caribbean drying. The models that project a strong Caribbean drying also simulate generally a strong equatorial eastern Pacific warming trend over the recent decades. Thus, the mismatch between observed and simulated warming trends over the equatorial eastern Pacific questions the reliability of the Caribbean precipitation projections. The warming bias might also have implications for tropical cyclones’ projections in the Atlantic and Pacific through the effect of vertical wind shear, which is related to shifts in the Walker circulation. In addition, the double Intertropical Convergence Zone (ITCZ) bias might be influenced by the mismatching trends. The strong influence of El Niño-Southern Oscillation (ENSO) dynamics on the world’s climate demands more in-depth studies addressing the drivers of the Walker circulation and the equatorial Pacific warming bias.

How to cite: Brotons Blanes, M., Haarsma, R., and Bloemendaal, N.: Impact of tropical eastern Pacific warming bias on Caribbean climate, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5034, https://doi.org/10.5194/egusphere-egu23-5034, 2023.

Climate change affects the hydrological cycle and induces extreme weather events, such as storms, floods and droughts. Adaptation to climate change needs to be based on assessments of future impacts. The new generation of Coupled Model Inter-comparison Project Phase 6 (CMIP6) is widely used in future flood prediction and drought risk assessment. However, many studies have found that CMIP6 global climate models for simulating land surface water and energy fluxes have significant biases, which poses a problem for using CMIP6 as input data for hydrological impact studies. Therefore, the output of CMIP6 cannot be directly used in hydrological models to project the impacts of future climate change. To overcome this problem, the correction of model output towards observations for its subsequent application in climate change impact studies has now become a standard procedure. And hydrological simulations generally use bias corrected output. But bias correction methods cannot really correct bias. The commonly used bias correction approaches only force the model outputs to match observations, and does not consider the mechanisms within the model and the interaction between variables. This study systematically evaluates water and energy fluxes of CMIP6 model over the Tibetan Plateau. Results show that the inter-model variability is substantial in temperature simulations. Snow that the largest component of the cryosphere responds significantly to changes in temperature. In the study, we study snow depth simulations corresponding to temperature simulations of different models over the Tibetan Plateau. Based on the water balance formula, analysis of how water balance fluxes respond to temperature changes in CMIP6, and determine the sources of error and ultimately lead to improved predictions.

How to cite: Liu, S., Liu, Z., and Duan, Q.: Evaluation of CMIP6 models for water and energy fluxes and analysis of source of errors over the Tibetan Plateau, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5066, https://doi.org/10.5194/egusphere-egu23-5066, 2023.

EGU23-5176 | ECS | Orals | CL4.6

Global warming induces more internally generated extremes of North Atlantic Oscillation and East Atlantic pattern 

Quan Liu, Johann Jungclaus, Daniela Matei, and Juergen Bader

Increased weather and climate extreme events are often attributed solely to either human-induced climate change or internal variability, under the assumption that external forcing does not influence the internal variability. However, with the development of single-model initial-condition large ensembles, recent research shows the impact of global warming on internal variability. This study investigates how global warming influences the North Atlantic Oscillation (NAO) and the East Atlantic (EA) pattern, which are the dominant large-scale circulation/teleconnection modes in the North Atlantic sector.

The study analyzes the geopotential height data of the Max Planck Institute Grand Ensemble (MPI-GE)  with 100 ensemble members. The internal variability is quantified as the deviation from the ensemble mean. The influence of global warming on the internal variability is checked with a 1pcCO2 experiment, where the  concertation is increased by 1% every year. This experiment provides a scenario for relatively strong global warming based on increasing greenhouse gas concentration alone. The extreme NAO and EA are defined as those years where the indexes are above (positive extremes) or below (negative extremes) 2 standard deviations.

The results show increases in extreme events, especially negative extremes, for both NAO and EA during wintertime, in a warmer climate. While NAO extremes increase consistently across the whole troposphere, EA extremes increase more at higher altitudes (500hpa-200hpa) than at lower altitudes. The warming effect of positive extreme NAO over northern Eurasia gets weaker, while the cooling effect of negative extreme NAO over northern Eurasia gets stronger. The effects of both, positive and negative extremes of EA, extend eastward till Eastern Asia. Overall, this study underlines the impact of global warming onto the internal variability of NAO and EA.

How to cite: Liu, Q., Jungclaus, J., Matei, D., and Bader, J.: Global warming induces more internally generated extremes of North Atlantic Oscillation and East Atlantic pattern, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5176, https://doi.org/10.5194/egusphere-egu23-5176, 2023.

EGU23-5279 | Orals | CL4.6

Reconciling conflicting evidence for the cause of the observed early 21st century Eurasian Cooling 

Stefan Sobolowski, Stephen Outten, and Camille Li

Arctic amplification of global warming is accompanied by a dramatic decline in sea ice. This, in turn, has been linked to cooling over the Eurasian subcontinent over recent decades, most dramatically during the period 1998-2012. Such a coherent and pronounced cooling is a counterintuitive impact under global warming. Some studies have proposed a causal teleconnection from Arctic sea ice retreat to Eurasian wintertime cooling; others argue that Eurasian cooling is mainly driven by internal variability. Overall, there is an impression of strong disagreement between those holding the “ice-driven” versus “internal variability” viewpoints. We offer an alternative framing that shows that the sea ice and internal variability views can be compatible. Key to this is viewing Eurasian cooling through the dual lens of dynamics (linked primarily to internal variability with a small contribution from sea ice; cools Eurasia) and thermodynamics (linked to sea ice retreat; warms Eurasia). This framing, combined with recognition that there is uncertainty in the hypothesized mechanisms themselves, allows both viewpoints (and others) to co-exist and contribute to our understanding of Eurasian cooling. A simple autoregressive model shows that strong Eurasian cooling is consistent with internal variability, with some periods being more susceptible to strong cooling than others. Rather than posit a “yes-or-no” causal relationship between sea ice and Eurasian cooling, a more constructive way forward is to consider whether the cooling trend was more likely given the observed sea ice loss, as well as other sources of low-frequency variability. Taken in this way both sea ice and internal variability are factors that affect the likelihood of strong regional cooling in the presence of ongoing global warming. Improving our understanding of the underlying mechanisms is critical for quantifying regional responses and impacts as well as producing reliable near-term climate predictions. 

How to cite: Sobolowski, S., Outten, S., and Li, C.: Reconciling conflicting evidence for the cause of the observed early 21st century Eurasian Cooling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5279, https://doi.org/10.5194/egusphere-egu23-5279, 2023.

EGU23-5775 | ECS | Orals | CL4.6 | Highlight

Impacts of a weakened AMOC on the European climate 

Katinka Bellomo, Virna Meccia, Roberta D'Agostino, Federico Fabiano, Sarah Larson, Jost von Hardenberg, and Susanna Corti

Previous studies have shown that the response of the Atlantic Meridional Overturning Circulation (AMOC) to increasing greenhouse gas forcing is a key driver of inter-model uncertainties. While all models project an AMOC decline, the inter-model spread in the decline rate drives very different climate change impacts, including temperature, precipitation, and large-scale atmospheric circulation patterns. Here we investigate the impacts of a weakened AMOC by performing idealized climate model experiments using EC-Earth3, a state-of-the-art GCM participating in CMIP6. We compare results from a control experiment run under preindustrial forcing, with an experiment in which we force a weakened AMOC by applying a virtual salinity flux in the North Atlantic/Arctic basin. Here we analyze previously unexplored aspects of the climate response to a weakened AMOC, focusing on impacts on wintertime daily timescales in the Euro-Atlantic region.

We find that a weakened AMOC forces an overall drier climate over most of Europe; however, some regions especially in northwestern Europe experience an increase in the number of very wet days. We investigate drivers of precipitation changes by performing a moisture budget and analyzing the association with changes in weather regimes at daily timescales. We find that an increase in the occurrence of the NAO+ days (going from a frequency of ~26% of occurrence to above 42%) together with an enhanced and more central jet, favors drier conditions over southern Europe and wetter conditions over northwestern Europe. Further, enhanced but drier storms cause dryness over Europe while thermodynamic processes per se, namely the Clausius-Clapeyron constraint on temperature, play a second role. Finally, we explore these relationships in additional experiments in which we keep the AMOC constant in a forced 4xCO2 experiment by applying a reversed virtual salinity flux, which allows us to separate the effects of 4xCO2 forcing from the weakened AMOC on climate change impacts. Our results have broader implications for understanding the role of the AMOC response on future climate change, allowing us to separate the impacts of the AMOC from those of the CO2 increase.

How to cite: Bellomo, K., Meccia, V., D'Agostino, R., Fabiano, F., Larson, S., von Hardenberg, J., and Corti, S.: Impacts of a weakened AMOC on the European climate, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5775, https://doi.org/10.5194/egusphere-egu23-5775, 2023.

The central role of tropical sea surface temperature (SST) variability in modulating Northern Hemisphere (NH) extratropical climate has long been known. However, the prevailing pathways of teleconnections in observations and the ability of climate models to replicate these observed linkages remain elusive. Here, we apply maximum covariance analysis between atmospheric circulation and tropical SST to reveal two co-existing tropical-extratropical teleconnections albeit with distinctive spatiotemporal characteristics. The first mode, resembling the Pacific-North American (PNA) pattern, favors a Tropical-Arctic in-phase (warm-Pacific-warm-Arctic) teleconnection in boreal spring and winter. The second mode, predominant in summer and autumn, is manifested as an elongated Rossby-wave train emanating from the tropical eastern Pacific that features an out-of-phase relationship (cold-Pacific-warm-Arctic) between tropical Pacific SST and temperature variability over the Arctic. This Pacific-Arctic teleconnection (PARC) mode partially explains the observed summertime warming around the Arctic. The reliability of climate models to replicate these leading teleconnections is of primary interest in this study to improve decadal prediction on regional climate. While climate models participating in CMIP6 appear to successfully simulate the PNA mode and its temporal characteristics, the majority of models’ skill in reproducing the PARC mode is obstructed by apparent biases in simulating low-frequency SST and rainfall variability over the tropical eastern Pacific and the summer climatological mean flow over the North Pacific. Considering the contribution of the PARC mode in shaping low frequency climate variations over the recent decades from the tropics to the Arctic, improving models’ capability to capture the PARC mode is essential to reduce uncertainties associated with decadal prediction and climate change projection over the NH.

How to cite: Feng, X.: Possible causes of model biases in simulating Tropical-Arctic teleconnections in CMIP6, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6017, https://doi.org/10.5194/egusphere-egu23-6017, 2023.

EGU23-6966 | ECS | Orals | CL4.6

Opposite Impacts of Interannual and Decadal Pacific Variability in the Extratropics 

Melissa Seabrook, Doug Smith, Nick Dunstone, Rosie Eade, Leon Hermanson, Adam Scaife, and Steven Hardiman

It is well established that the positive phase of El Niño Southern Oscillation (ENSO) tends to weaken the Northern Hemisphere stratospheric polar vortex (SPV), promoting a negative North Atlantic Oscillation (NAO). Pacific Decadal Variability (PDV) is characterised by a pattern of sea surface temperatures similar to ENSO, but its impacts are more uncertain: some studies suggest similar impacts of ENSO and PDV on the SPV and NAO, while others find the opposite. We use climate model experiments and reanalysis to find further evidence supporting opposite interannual and decadal impacts of Pacific variability on the extratropics. We propose that the decadal strengthening of the SPV in response to positive PDV is caused by a build-up of stratospheric water vapour leading to enhanced cooling at the poles, an increased meridional temperature gradient and a strengthened extratropical jet. Our results are important for understanding decadal variability, seasonal to decadal forecasts and climate projections.

How to cite: Seabrook, M., Smith, D., Dunstone, N., Eade, R., Hermanson, L., Scaife, A., and Hardiman, S.: Opposite Impacts of Interannual and Decadal Pacific Variability in the Extratropics, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6966, https://doi.org/10.5194/egusphere-egu23-6966, 2023.

EGU23-7011 | ECS | Orals | CL4.6

AMOC variations modulated by Tropical Indio-Atlantic SST Gradient 

Brady Ferster, Leonard Borchert, Juliette Mignot, and Alexey Fedorov

A potential future slowdown or acceleration of the Atlantic Meridional Overturning Circulation (AMOC) would have profound impacts on global and regional climate. Recent studies have shown that AMOC responds, among many other processes, to anthropogenic changes in tropical Indian ocean (TIO) temperature. However, internal unforced co-variations between these two basins are largely unexplored as of yet. Here, we use the ERSST v5, HadISST v1, and COBE v2 gridded observational products for the period 1870-2014, as well as dedicated simulations with coupled climate models, and show that internal changes in sea surface temperature gradients between the Indian and Atlantic Ocean (SSTgrad) can drive teleconnections that influence internal variations of North Atlantic climate and AMOC.

We separate the unforced observed component (i.e., internal signal) from the forced signal following the residuals method presented by Smith et al. (2019). In the absence of direct AMOC observation we estimate AMOC variability from an SST index (SSTAMOC; Caesar et al., 2018). We find a robust observed relationship between the unforced tropical SSTgrad and SSTAMOC when TIO leads by ~25 years. This time-lag is in line with a recently described mechanism of anomalous tropical Atlantic rainfall patterns that originate from TIO warming and cause anomalously saline tropical Atlantic surface water which slowly propagate northward into the subpolar North Atlantic, ultimately altering oceanic deep convection and AMOC (Hu and Fedorov, 2019; Ferster et al. 2021). Our study now suggests that it is the tropical SSTgrad that drives those AMOC changes, with a limited role for the western tropical Pacific. Pre-industrial control simulations with the IPSL-CM6A-LR model confirm this relationship, indicating a time lag of ~25 years between SSTgrad and SSTAMOC variations. These simulations also confirm that the SSTAMOC is representative of unforced AMOC variations when SSTAMOC leads by 5 years. This work therefore indicates that an unforced pathway between tropical ocean temperature and AMOC exists with a ~20 year lag, which opens the potential for using SSTgrad as precursor to predict future AMOC changes.

 

Caesar, L., Rahmstorf, S., Robinson, A., Feulner, G., & Saba, V. (2018). Observed fingerprint of a weakening Atlantic Ocean overturning circulation. Nature, 556(7700), 191-196.

Ferster, B. S., Fedorov, A. V., Mignot, J., & Guilyardi, E. (2021). Sensitivity of the Atlantic meridional overturning circulation and climate to tropical Indian Ocean warming. Climate Dynamics, 1-19.

Hu, S., & Fedorov, A. V. (2019). Indian Ocean warming can strengthen the Atlantic meridional overturning circulation. Nature climate change, 9(10), 747-751.

Smith, D. M., Eade, R., Scaife, A. A., Caron, L. P., Danabasoglu, G., DelSole, T. M., ... & Yang, X. (2019). Robust skill of decadal climate predictions. Npj Climate and Atmospheric Science, 2(1), 1-10.

How to cite: Ferster, B., Borchert, L., Mignot, J., and Fedorov, A.: AMOC variations modulated by Tropical Indio-Atlantic SST Gradient, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7011, https://doi.org/10.5194/egusphere-egu23-7011, 2023.

A detailed assessment of climate variability of the Baltic Sea area for the period 1958-2009 (Lehmann et al. 2011) revealed that recent changes in the warming trend since the mid-1980s, were associated with changes in the large-scale atmospheric circulation over the North Atlantic. The analysis of winter sea level pressure (SLP) data highlighted considerable changes in intensification and location of storm tracks, in parallel with the eastward shift of the North Atlantic Oscillation (NAO) centres of action. Additionally, a seasonal shift of strong wind events from autumn to winter and early spring existed for the Baltic area. Lehmann et al. (2002) showed that different atmospheric circulation regimes force different circulation patterns in the Baltic Sea. Furthermore, as atmospheric circulation, to a large extent, controls patterns of water circulation and biophysical aspects relevant for biological production, such as the vertical distribution of temperature and salinity, alterations in weather regimes may severely impact the trophic structure and functioning of marine food webs (Hinrichsen et al. 2007). To understand the processes linking changes in the marine environment and climate variability, it is essential to investigate all components of the climate system which of course include also the large-scale atmospheric circulation. Here we focus on the link between changes/shifts in the large scale atmospheric conditions and their impact on the regional scale variability over the Baltic Sea area for the period 1950-2021. This work is mostly an extension of previous studies which focused on the response of the Baltic Sea circulation to climate variability for the period 1958-2008 (Lehmann et al. 2011, Lehmann et al. 2014). Now extended time series ECMWF ERA 5 reanalysis for 7 decades are available, highlighting recent changes in atmospheric conditions over the Baltic Sea. The main focus of this work is to identify predominant large scale atmospheric circulation patterns (climate regimes) on a monthly/seasonal time scale influencing the regional atmospheric circulation over the Baltic Sea area. Furthermore, long-term changes on the annual to decadal time scale will also be investigated.

How to cite: Lehmann, A., Post, P., and Myrberg, K.: Changing impact of the large-scale atmospheric circulation on the regional climate variability of the Baltic Sea for the period 1950-2022, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8461, https://doi.org/10.5194/egusphere-egu23-8461, 2023.

EGU23-10582 | Orals | CL4.6 | Highlight

Impacts of oceanic warming patterns versus CO2 radiative forcing on the Hadley Circulation 

Yong Sun, Gilles Ramstein, Alexey V. Fedorov, Lin Ding, and Bo Liu

The Hadley circulation (hereafter HC) is one of the most prominent meridional overturning circulations in the climate system. In addition to maintaining energy balance and momentum exchange in tropics and extratropics, it can also shape the Intertropical Convergence Zone (ITCZ) and subtropical dry arid zones by regulating the hydrological cycle in tropical and extratropical regions. Weakening and expanding HC and narrowing of the ITCZ are projected with human greenhouse gas emissions. However, no consensus has been achieved regarding the relative importance of direct CO2 radiative effect and indirect effects via SST changes in shaping the future HC changes. This limits our deep understanding of the climate impacts imposed by changes in the HC. Here we analyze a broad range of CMIP5 experiments and show that future changes in SST patterns play the leading role in the determining the future changes in HC and ITCZ. In addition, a series of individual basin perturbation experiments were conducted at 1.5°C, 2°C, and 3°C temperature thresholds to identify key basins that determine HC strength, edges, and ITCZ locations. Our work highlights the overwhelming role of future tropical Indian Ocean warming on the HC and ITCZ changes.

How to cite: Sun, Y., Ramstein, G., Fedorov, A. V., Ding, L., and Liu, B.: Impacts of oceanic warming patterns versus CO2 radiative forcing on the Hadley Circulation, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10582, https://doi.org/10.5194/egusphere-egu23-10582, 2023.