A TC-removed technique was applied to global analyses to study the impact of TCs on the summertime subtropical ISO propagating over the western North Pacific (WNP). The TC-removed ISO pattern showed a westward shift from the area between Taiwan and Japan to the northern South China Sea. The monsoon trough thus weakened after TCs were removed from the circulation fields. Furthermore, the interaction between the ISO and submonthly wave patterns also showed weaker signals after TC removal. However, the activity over the South China Sea remained considerable strong because fewer TCs passed through this area. Therefore, the ISO and submonthly wave patterns retained considerable intensity over the South China Sea. The higher frequency of TC occurrences in the westerly phase results in a more pronounced energy reduction following TC removal compared to the easterly phase. Moreover, synoptic-wave PKE exceeds its submonthly counterpart, and the baroclinic conversion exhibits a north-south orientation, both due to the upstream recurving TCs that redirect their paths toward Japan. These findings reinforce our knowledge of climate variability, thus advancing climate modeling accuracy.This research underscores TCs' substantial impact on atmospheric circulations, highlighting their role in coordinating the submonthly wave patterns, synoptic waves, and ISOs in the WNP. This enhanced knowledge facilitates a more accurate explanation of climate variability. Nevertheless, comprehensive analyses and assessments across the global domain are essential to fully include the broader implications and variability of TC interactions with atmospheric perturbations worldwide.

How to cite: Ko, K.-C.: TCs’ contribution on summertime subtropical ISOs and submonthly wave patterns over the western North Pacific, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-1, https://doi.org/10.5194/ecss2025-1, 2025.

Additive Logistic Regression Models (AR-CHaMo) to predict the occurrence of tornadoes of intensity > (E)F1 were developed using lightning observations from the Arrival Time Difference Network (ATDnet), tornado reports from the European Severe Weather Database (ESWD), the Storm Prediction Centre (SPC) and the Australian Bureau of Meteorology (BOM) and environmental predictors from the ERA5 reanalysis. The models output the probability of a tornado as a function of environmental predictors from ERA5 and can be used both for forecasting and climate analysis. By applying the models to ERA5 for the period 1992-2023, we were able to map the modelled climatological occurrence of tornadoes > (E)F1 on a global scale. According to AR-CHaMo, tornadoes are most common across the Plains and the Southeast of the US, but also across Uruguay, Paraguay, and southern Brazil. Local hotspots are also modelled across southeastern South Africa, southeastern Australia, as well as southeastern and northeastern China. Conditions favouring tornadoes are climatologically less frequent in Europe, but local hotspots are present across coastal regions of the Mediterranean. Although a ground-based verification is impossible due to the lack of a globally consistent tornado reports database, the modelled spatial distribution from AR-CHaMo is in agreement with local climatologies from regions where reports are collected, such as the US and South America. Using 31 years of time series, we were able to detect long-term trends in modelled tornado frequency. In North America, AR-CHaMo indicates that tornadoes have increased in frequency across the US Southeast (most strongly) and the Upper Midwest, while they have locally decreased in the Great Plains. Large relative increases are also present in southeastern Canada. Trends are negative across South America, southern China, and Australia, while the occurrence has increased across southeastern Asia and locally in southern Europe. As part of the presentation, we will also report on the forecasting applications of the AR-CHaMo models, while focusing on a few recent tornado outbreaks across Europe and the US.

How to cite: Battaglioli, F., Groenemeijer, P., Taszarek, M., and Púčik, T.: A Statistical Model to Forecast Tornadoes and Reconstruct Their Climatology and Trends Globally, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-16, https://doi.org/10.5194/ecss2025-16, 2025.

Due to anthropogenic climate change, warmer and almost snowless winters are increasingly observed in mid-latitudes, including Poland. As a result, air masses can transport more moisture, making them more unstable, potentially leading to more convective phenomena, including thunderstorms. Although thunderstorms occurring in the cold half of the year, especially in winter, are extremely rare and not as dangerous as summer thunderstorms, they can be classified as extreme weather phenomena. At the same time, the increase in their frequency is another signal of climate change. 

This study presents changes in the occurrence of thunderstorms in the cold half of the year and in winter in Poland from 1951 to 2020. The research was based on data from 46 synoptic stations of the Institute of Meteorology and Water Management – National Research Institute (IMGW-PIB), and the basic indicator was a day with a thunderstorm. 

Studies have shown a clear spatial differentiation of thunderstorms occurring in the cold half of the year, which in some regions of the country accounted for even more than 8% of all cases in the year. The strongest influence on the occurrence of these phenomena in the cold season is air circulation and local conditions (especially the impact of the Baltic Sea in the north and varied topography in the south). In Poland in the period 1951–2020, there were on average 13.1 days with a thunderstorm from October to March (days where at least one station recorded a thunderstorm), including 3.4 days during meteorological winter. The number of such days at individual stations ranged from 0.5 to 1.8 and 0.01 to 0.59, respectively. In the period under study in Poland, the number of thunderstorm days in the cool season slowly increased, and the increase amounted to 0.35 days per decade. Most of the thunderstorms considered were associated with atmospheric fronts. The strongest occurred during the passage of dynamic cold fronts, which are characterised by low potential energy and high wind shear values.

How to cite: Wyrwas, J. and Bielec-Bąkowska, Z.: Long-term variability of winter thunderstorms in Poland (1951–2020), 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-28, https://doi.org/10.5194/ecss2025-28, 2025.

Over the past decade, hail has been responsible for most financial losses associated with severe convective storms, with costs steadily increasing. As the population grows and increasingly invests in vulnerable infrastructure, the risk of economic damage from large hail also rises. Accurate hazard assessment is therefore essential for effective mitigation.

While recent machine learning (ML) approaches have enabled the development of hail climatologies for hazard assessment, many existing datasets remain limited by regional biases and coarse spatial or temporal resolution.

This study aims to produce a novel, high-resolution large hail (> 2.5 cm in diameter) hazard climatology for the Contiguous United States (CONUS) using the gradient-boosted decision tree algorithm XGBoost. Our model will integrate multiple remotely sensed hail proxy observations, including hourly satellite-derived brightness temperature, radar-reflectivity, and lightning counts, along with key hail-related environmental parameters derived from the ERA5 reanalysis. The high resolution of the remotely sensed data will enable us to train the ML model at an unprecedented grid spacing of 4 km × 4 km, enhancing the spatial detail of large hail climatologies derived in previous datasets.

We will assess model performance using held out test data and compare regional calibration across different climate regimes in the CONUS. Our research will also explore which predictors are most influential for large hail estimation and how effectively the model captures spatial heterogeneities in hail occurrence.

The resulting dataset will represent a refined tool for hail risk assessment in the CONUS. Moreover, with globally available satellite and reanalysis data, this framework also holds the potential for expanded application in other regions around the world.

How to cite: Koch, R., Prein, A., Lohmann, U., and Aellen, N.: A Machine Learning Based High-Resolution Large Hail Climatology for the Contiguous United States , 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-44, https://doi.org/10.5194/ecss2025-44, 2025.

In this study, we investigate the representation of atmospheric conditions favourable for severe convective storms using two different reanalyses: the regional, convection-permitting ALADIN model with a horizontal resolution of 2.3 km, and the global ERA5 dataset produced by the ECMWF, featuring a resolution of 0.25°. We focus on two essential environmental parameters: Most Unstable Convective Available Potential Energy (MUCAPE) and deep-layer (0–6 km) wind shear, which are widely used in both operational forecasting and climatological analyses of convective environments.

The comparison is performed for the region of Central Europe, with a dual focus. First, a point-based evaluation is conducted using vertical profiles from the upper-air sounding station Prague-Libuš, covering the period 1992–2019. This long-term observational reference enables a detailed assessment of the performance and consistency of both reanalyses in capturing convective parameters. Second, we examine the spatial distribution and seasonal characteristics of MUCAPE and wind shear fields over a broader Central European domain, based on daily data from the period 1991–2020.

By analysing both local and regional characteristics, we aim to better understand the strengths and limitations of each reanalysis in capturing convective potential and storm-related wind profiles. These findings are relevant for applications in climatology, model validation, and long-term assessments of severe weather risk in the region.

How to cite: Zacharov, P. and Kvak, R.: Comparison of convective precursors from ALADIN and ERA5 Reanalyses over Central Europe, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-61, https://doi.org/10.5194/ecss2025-61, 2025.

While mesoscale processes are generally associated with the development of severe convective events, it is the synoptic situation that creates the environment for convective events. Thus the knowledge of the synoptic and mesoscale conditions are crucial for forecasting such events, while statistical analyses are helpful for raising a general awareness of the possibility of severe convective events. Beyer et al. 2025 recently performed a statistical analysis of the occurrence of tornadoes in Germany. This study is now expanded with the goal of analysing the occurrence and characteristics of tornadoes under different synoptic conditions.

The study is based on data from the European Severe Weather Database (ESWD), with 1812 confirmed tornado reports within Germany from 1940 to 2024, together with an automatic classification of synoptic patterns. The automatic method, GWL-REA, is broadly based on a pattern correlation method using ERA5 reanalyses, with various optimizations and AI-based enhancements. Four meteorological variables are used for the inputs: mean-sea-level pressure, geopotential height at 500 hPa, 500–1000 hPa relative thickness and the total column precipitable water. Classifications are available from 1940 up to the present. The most widely used set of circulation patterns are the 29 Hess–Brezowsky Grosswetterlagen (GWL) for Central Europe. These are intuitively defined and named patterns which are in common use amongst synoptic meteorologists. They have been used e.g. in a study of thunderstorms under different synoptic patterns by Wapler and James (2015). The classification has since been slightly updated: The pattern BM (Zonal Ridge across Central Europe) has been split into an anticyclonic (BMa) and a cyclonic (BMz) representation. This yields 30 synoptic patterns.

The analysis reveals conditions favourable for tornadic storm development and highlights regions affected under different flow regimes. Additionally, the analysis shows that different synoptic conditions are typically associated with specific tornado characteristics, such as the direction of movement or tornado severity. These relationships can be explained meaningfully via a description of the synoptic-meteorological characteristics of each weather pattern.

The Grosswetterlagen Wz (Cyclonic Westerly) and SWz (Cyclonic South-Westerly) have been identified as patterns inducing the most tornadoes over Germany. Wapler and James (2015), found that the Grosswetterlagen most frequently associated with thunderstorms are Sz (Cyclonic Southerly), SEa (Anticyclonic South-Easterly), SWz (Cyclonic South-Westerly), TrW (Trough over Western Europe) and TB (Low over the British Isles).

How to cite: Wapler, K., Beyer, M., and James, P.: Tornado occurrence and characteristics in Central Europe under different synoptic conditions , 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-72, https://doi.org/10.5194/ecss2025-72, 2025.

Hail is a leading cause of property and crop damage in Australia, with individual events capable of inflicting over $1b worth of insured losses. Hail damage is increased if hailstones are larger, if there are coincident strong winds, and if hail swaths cover larger areas. Australia’s most populated region is also its most hail prone, meaning the country has high exposure to hail hazard. While hailstorms are expected to be affected by climate change, the details of changes are non-stationary and subject to high uncertainty. Here, we use downscaled simulations over major Australian cities to examine projected changes in hail frequency, damage potential, and swath properties under a climate change scenario with ~2.4 degrees C warming. The areas we consider cover more than 65% of Australia’s population. We used extreme value analysis to analyse changes in maximum hailstone size and hail-proximal wind speeds. We used object-based analysis to summarise swath properties and compare them between epochs. The simulations project increases in hail frequency in Sydney/Canberra and Brisbane regions, increases in maximum hail size around Melbourne, Sydney/Canberra, Kalgoorlie, and Perth, and decreases in hail-proximal wind speeds around Perth, Melbourne, Sydney/Canberra. This study provides the most comprehensive projections for changes in hail damage potential under climate change in Australia to date.

How to cite: Raupach, T. and Aldridge, J.: Projected changes in hail damage potential and swath properties over Australian cities under global warming, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-93, https://doi.org/10.5194/ecss2025-93, 2025.

A new tornado map for the United Kingdom and Ireland has been created for the years 1054-2025. This builds on an initial map which was first produced and published by the Tornado and Storm Research Organisation (TORRO) in 2015. Therefore, after a decade of receiving much new and also revised information, especially from detailed site investigations and updated historical data, this map presents a valuable contribution to better understanding tornado climatology. The United Kingdom is the only country in the world with a record of tornadoes (and waterspouts) for some 971 years. Presenting these tornadic events spatially with reference to intensity and seasonality allows the reader to infer much useful information. This presentation will examine the events, trends and hotspots. It will examine regionality, bias, and historical reporting along with presenting a striking visual of tornado climatology for the United Kingdom and Ireland.

TORRO was established in 1974 (www.torro.org.uk) as a privately-supported research body serving the national and international public interest. TORRO would like to thank the hundreds of members and site investigators who have contributed to the quality of the database over the last 50 years. Key contributors to this ongoing effort have been Terence Meaden, Mike Rowe and Paul Brown, Peter Kirk (data analysis) and John Tyrrell (Ireland events). Special contribution has been made by Tim Prosser for the map creation, where full credit should be given.

How to cite: Doe, R. and the Tornado and Storm Research Organisation (TORRO): A New Tornado Map for the United Kingdom and Ireland 1054-2025, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-113, https://doi.org/10.5194/ecss2025-113, 2025.

Recent advancements in satellite data re-calibration and homogenization have enabled the development of long-term climatologies of deep convective clouds (DCCs), particularly using geostationary data from two generations of Meteosat satellites. This study presents a comprehensive analysis of DCC occurrence over Europe based on over four decades of satellite observations. For the period 1983–2006, we utilize the Fundamental Climate Data Record (FCDR) from the Meteosat Visible and Infrared Imager (MVIRI) onboard the Meteosat First Generation (MFG), while for 2004–2024, data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG) are used.

The analysis addresses key challenges in combining the two datasets, including: (1) limited spectral information (only water vapor ~6.2 µm and infrared window ~11.0 µm channels were available for both instruments), requiring careful method selection for DCC detection; (2) differences in spectral response functions, mitigated through spectral band adjustment using IASI observations; and (3) lack of consistent cloud top height (CTH) products, which we overcome by developing a unified CTH estimation method applicable to both MVIRI and SEVIRI. Optimal DCC detection thresholds were calibrated through cross-comparison with CloudSat-CALIPSO observations. Our results provide a consistent climatology of DCC frequencies over Europe, offering valuable insights into long-term convective variability and trends.

This research was funded by the National Science Centre of Poland. Grant no. UMO-2020/39/B/ST10/00850. We also acknowledge Polish high-performance computing infrastructure PLGrid (HPC Center: ACK Cyfronet AGH) for providing computer facilities and support within computational grant no. PLG/2025/018115.

How to cite: Kotarba, A.: Deep Convective Cloud (DCC) occurrence over Europe from 1983 to 2024, based on geostationary satellite data, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-118, https://doi.org/10.5194/ecss2025-118, 2025.

Destructive tornadoes and damaging hail are a rare but present hazard in the United Kingdom (UK), as illustrated by the November 2023 Jersey storm. However, improving our ability to understand and forecast these events requires moving beyond case studies and towards a climatological view of both severe and non-severe convection. Not only do severe convective environments vary between regions, but differences in the non-severe ‘baseline’ further modulate the most useful parameters for forecasting.

We present the first climatological investigation of severe hail environments in the UK, and the largest to date of tornado environments, using thundeR convective parameters derived from ERA5 reanalysis. We show that lightning flash data, often used to identify non-severe (null) cases, are poorly suited to the UK, on top of only being available for the past ~20 years. Instead we develop a novel method using ERA5 convective precipitation, inclusive of unelectrified but potentially tornado-producing storms common during the cool season. The resulting long study period (1950–2022) enables a larger sample size (~400 severe hail days and ~950 tornado days) than has previously been achieved in regions with temperate, strongly maritime climates and low severe hail incidence such as the UK.

UK severe hail and tornado environments are unlike typical European or American ones. Most notably, instability (i.e. CAPE) is much lower in the UK. Nonetheless, CAPE effectively identifies severe hail environments, because it is also much lower in non-severe environments. Conversely, shear parameters generally show reduced separation between non-severe and severe distributions. Exceptions to this, such as the link between very large hail and 1–6 km shear, may identify physical constraints on severe hazard occurrence. Many UK severe environments, particularly outside of summer, are of the ‘high-shear, low-CAPE’ type. However, this kind of environment also typifies cool-season, non-severe convection, increasing the forecasting challenge.

These results suggest that most forecasting rules of thumb and composite parameters cannot simply be re-applied to the UK. Instead, we seek ‘analogue’ regions with which comparison and forecasting experience are likely to be most useful. Candidates include other parts of Europe’s maritime periphery, from Portugal to the Netherlands and potentially to Fennoscandia and, further afield, the US Pacific Coast and South Australia.

How to cite: Wells, H. M., Hillier, J., Garry, F. K., Dunstone, N., Clark, M. R., Kahraman, A., and Taszarek, M.: Comparing the environments of large hail, tornadoes and non-severe convection in the United Kingdom, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-132, https://doi.org/10.5194/ecss2025-132, 2025.

Long-term trends in convective environments suggest a decline in environmental vertical wind shear, however instability (i.e. CAPE) is projected to increase. This may be particularly important in the Southeastern U.S. cool season, where instability is characteristically limited but vertical shear is generally very large and can still be favorable for convection given an overall decline. An increase in cool-season instability could result in more frequent hazardous convective weather (HCW) as well as a change in storm mode, resulting in a different distribution of hazards that can impact a new subset of the population that would not currently expect HCW. We exploit 10-year present and future global time-slice MPAS simulations from Michaelis et. al (2019) as a baseline for studying the change in frequency, mode, and intensity of HCW in the Southeastern U.S. The MPAS model uses a global-scale, 60 km grid which is reduced to a high resolution 15 km grid over the Northern Hemisphere to incorporate the effects of large-scale processes. We identify convective windows using the MPAS convective precipitation, CAPE, and 0-6 km vertical shear parameters at 6-hour output intervals. First, we address whether the location, frequency, and character of these windows is changing over time in the non-convection-allowing MPAS simulations. Subsequently, we use a downscaling approach to study whether the mode and severity of resolved convection will change within the convective environments extracted from MPAS. 

How to cite: Toomey, R. and Parker, M.: Long-Term Trends in Convective Weather and Environments in the Southeastern United States, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-135, https://doi.org/10.5194/ecss2025-135, 2025.

Quasi-Linear Convective System (QLCS) is a type of convective mode characterized by a linear organization of convective cells known for generating severe weather at midlatitudes, including Europe. In this work, we created a radar-based climatology of QLCS in Europe using 8 years (2014–2021) of Operational Programme for the Exchange of Weather Radar Information (OPERA) radar data, lightning detection network (ATDnet) data, and severe weather reports (ESWD). First, 15-minute OPERA radar scans were examined, identifying 1475 QLCS cases. The manual evaluation of each QLCS allowed us to recognize their  features such as morphological and precipitation archetypes, areal extent, width, length, duration, speed, and forward motion. In the next step, severe weather reports, lightning data, and morphological properties were used to classify QLCSs according to their intensity into 1151 marginal (78.0%), 272 moderate (18.5%), and 52 derecho (3.5%) events. We found that QLCSs are the most common during summer in Central Europe, while in the southern part of Europe, their frequent occurrence is extended to late autumn. Our study reveals that the bow echo morphological archetype was present in around 29% of QLCS cases, and a mesoscale convective vortex developed in almost 9%. Among precipitation modes, around 50% of QLCS were organized into trailing and embedded stratiform types.  Using severe weather reports we found  that the most common QLCS-related threat was lightning (taking up on average 94.4% of the area impacted by QLCS), followed by severe wind gusts (7.9%), excessive precipitation (6.1%), large hail (2.9%), and tornadoes (0.5%). Moreover, derechos had the most extensive coverage of severe wind gusts (49.8%), whereas back-building QLCSs were mainly associated with excessive precipitation events (13.5%). QLCSs caused 104 fatalities and 886 injuries. Ten of the most impactful events were responsible for nearly half of QLCS-related fatalities and injuries.

How to cite: Surowiecki, A., Pilguj, N., Taszarek, M., Piasecki, K., Púčik, T., and Brooks, H.: Quasi-Linear Convective Systems and Derechos across Europe: Climatology, Accompanying Hazards, and Societal Impacts, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-160, https://doi.org/10.5194/ecss2025-160, 2025.

Post-tropical cyclones are a subset of tropical cyclones that have undergone extratropical transition, a process by which they lose tropical characteristics and take on those of extratropical cyclones. These cyclones can then impact areas outside typical tropical cyclone extent with high winds and copious amounts of precipitation. Due to their relative rarity (in the North Atlantic approximately 50% of the ~14 tropical systems that form annually undergo extratropical transition) the data on these storms is relatively scarce.

Our aim is to build a model capable of generating a global dataset of transitioning storms so their risks can be calculated despite the paucity of data. This model will be built as an extension of STORM (Synthetic Tropical cyclOne generRation Model) which has had success in generating synthetic tropical cyclone tracks and pressure profiles. We will model the jet stream, the transition of the storm, different extratropical transition pathways, storm position and windspeed, and finally storm lysis. This involves several challenges, as statistical models cannot capture all the complex interactions that take place during extratropical transition. The parameters of interest will be identified through literature and model refinement. Data will be drawn from model simulations and data produced in literature. Initial work has shown that the model can generate cyclone tracks and reproduce basic interactions with the jet stream.

How to cite: Ribberink, M., Bloemendaal, N., Coumou, D., Robson, A., and Hemmati, M.: STORM-EX: Towards bridging the transition gap in statistical synthetic storm modelling, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-162, https://doi.org/10.5194/ecss2025-162, 2025.

The complex orography of the Alpine area exerts a significant influence on the convective process. However, many aspects, particularly those related to the initiation and evolution of convection, are still poorly understood, especially in the context of climate change, where the projections seem to be directed at sustaining a future amplification of storms at the local scale.  

This PhD research project aims to analyse the thunderstorms in the Alps, with a particular focus on the Trentino-South Tyrol region, looking at changes registered in the last few decades. One of the main tasks is to develop a robust climatology of convective triggering using data from the C-band meteorological radar located on Mount Macaion, supplemented with data from ground meteorological stations and satellite observations. To reinforce the analysis the MASHA technique developed by Laviola et al. (2025, in submission) will also be used. MASHA is a hybrid advanced satellite technique capable of detecting the hail-bearing convection developing in the Mediterranean basin every 5 min at very high spatial resolution (3-5 km). 

This research is part of the broader TIM (Thunderstorm Intensification from Mountains to Plains) project promoted by ESSL, intending to improve the understanding of convective phenomena in mountain environments and their implications for impact prediction and mitigation.

How to cite: Di Felice Fabrizi, C., Zardi, D., and Laviola, S.: Preliminary investigations on convective storm initiation and evolution in the Alpine region, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-164, https://doi.org/10.5194/ecss2025-164, 2025.

Tropical Cyclone Impact Sensitivity to Different Aerosol Conditions with CLIMADA Risk Platform

Tropical cyclones are one of the most severe natural hazards and pose major risks to coastal regions through extreme winds, heavy precipitation, flooding, and storm surges. During the period 1980 - 2011 these hazards contributed to 47% of all U.S. billion-dollar natural hazard losses (Smith and Katz, 2013), which are expected to increase with climate change and increasing coastal exposure (IPCC, 2021). To mitigate tropical cyclone risk, it is crucial to understand their evolution under future climate conditions. It is expected that reductions in anthropogenic emissions will lead to a decline in aerosol concentrations (Riahi et al., 2017). We already know that aerosols influence the formation and evolution of tropical cyclones by affecting cloud microphysics and precipitation patterns (Khain et al., 2010). Depending on the location of aerosol intrusion the convective invigoration can either weaken or strengthen the storm winds and further modulate the precipitation intensities (Hoarau et al., 2018; Lin et al., 2023). However, these effects remain largely unaccounted for in many operational forecasting and risk assessment models.
This thesis aims to understand how aerosol concentrations may alter tropical cyclone wind and precipitation patterns with a focus on the 2020 hurricane season in North America. Looking at different aerosol concentrations, we combine numerically simulated tropical cyclone tracks from ICON with the open-source probabilistic risk assessment platform CLIMADA (Aznar-Siguan and Bresch, 2019). This platform integrates hazard, exposure and vulnerability so we can link the impacts of different aerosol concentrations on the seasonal tropical cyclone activity to resulting economic damages and population exposure. With this, we evaluate how the inclusion of aerosol effects in tropical cyclone risk models could improve the risk assessment. This can support decision-makers in implementing more effective adaptation strategies in affected coastal regions.

REFERENCES

Aznar-Siguan, G., Bresch, D.N., 2019.  https://doi.org/10.5194/gmd-12-3085-2019

Hoarau, T., Barthe, C., Tulet, P., Claeys, M., Pinty, J.-P., Bousquet, O., Delanoë, J., Vié, B., 2018. https://doi.org/10.1029/2017JD028125

IPCC, 2021. https://doi.org/10.1017/9781009157896

Khain, A., Lynn, B., Dudhia, J., 2010. https://doi.org/10.1175/2009JAS3210.1

Lin, Y., Wang, Y., Hsieh, J.-S., Jiang, J.H., Su, Q., Zhao, L., Lavallee, M., Zhang, R., 2023. https://doi.org/10.5194/acp-23-13835-2023

Riahi, K., van Vuuren, D.P., Kriegler, E., Edmonds, J., O’Neill, B.C., Fujimori, S., Bauer, N., Calvin, K., Dellnik, R., Fricko, O., Lutz, W., Popp, A., Cuaresma, J.C., KC, S., Leimbach, M., Jiang, L., Kram, T., Rao, S., Emmerling, J., Ebi, K., Tavoni, M., 2017. https://doi.org/10.1016/j.gloenvcha.2016.05.009

Smith, A.B., Katz, R.W., 2013. https://doi.org/10.1007/s11069-013-0566-5

How to cite: Dreifuss, M., Caratsch, A., and Lohmann, U.: Tropical Cyclone Impact Sensitivity to Different Aerosol Conditions with CLIMADA Risk Platform, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-174, https://doi.org/10.5194/ecss2025-174, 2025.

In recent decades, insured losses from hailstorms have shown a marked upward trend across Europe. Notable events such as Qiara and Maya in France (2022), and Unai in northern Italy (2023), underscore the growing potential of severe convective storms to cause catastrophic damage. These events highlight the increasing relevance of hail as a key peril for the insurance and reinsurance sectors, necessitating a modernised and data-driven approach to risk assessment.

To address this evolving risk landscape, Swiss Re has developed a new severe convective storm model that incorporates a pan-European probabilistic event set. This model aims to realistically capture the insurance-relevant characteristics of hail events at a continental scale, including their frequency, severity, spatial extent, and clustering behaviour. Key parameters such as the geometry of hail streaks, the distribution of hailstone sizes within these streaks, and the spatial correlation of impacts are explicitly modelled to reflect the complexity of real-world events.

One of the primary challenges in constructing such a model lies in the scarcity and heterogeneity of observational hail data across Europe. To overcome this, we employed statistical learning techniques to infer the daily probability of hail occurrence from convective environments using reanalysis datasets. This approach enabled the creation of a robust, multi-decadal hail climatology, which serves as the foundation for geographically differentiated risk estimates and realistic event footprints.

Building on this climatology and supplemented by literature-based insights into hail intensity distributions, we generated a stochastic event set simulating tens of thousands of years of hail activity. This synthetic catalogue supports underwriting applications by enabling consistent risk evaluation at both local and portfolio scales. The model’s outputs have been validated against existing climatologies to ensure their suitability for operational use in insurance pricing and risk management.

This contribution presents the methodology, validation, and implications of Swiss Re’s new hail model, offering insights into how advanced statistical and climatological techniques can enhance the industry's understanding and quantification of hail risk in Europe.

How to cite: Zeder, J., Spreitzer, E., de Jong, R., and Viktor, E.: From Observation to Simulation: Building a Continental-Scale Hail Model for Re/Insurance Applications, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-184, https://doi.org/10.5194/ecss2025-184, 2025.

Tornadoes frequently occur in Japan. Their information is published in the tornado database by Japan Meteorological Agency. The database provides on the JEF scale, damaged area, synoptic environment, and more. Unfortunately, there is no information about the convective systems causing tornadoes. We expect that the tornado warnings could be significantly improved if we understand the variety of convective systems and their environmental indices. The present study aims to examine tornado climatology in Japan with respect to parent convective systems causing tornadoes. We picked the tornado events that occur in the observation range of JMA radars and XRAIN (Ministry of Land, Infrastructure, Transport and Tourism radar network) radars for 2013 to 2024, and then classify the convective systems based on the shape of >40 dBZ echo region in reflectivity, the size of vortices in Doppler velocity distributions, and moving velocity of the systems.

We analyzed 178 tornado events for 11 years. At this time, we classified six types of convective systems: Isolated cumulonimbus, Supercells, Cloud clusters, Quasi-linear convective system, Local front, and Inner rainband of typhoon. Cloud clusters were the most common system, followed by Isolated cumulonimbus. Furthermore, these two systems accounted for the majority of all systems. Therefore, we focused on these systems, looking for trends of occurrence with respect to location, time, season and so on.

As a result, Cloud clusters tend to occur on south coast of Japan facing the Pacific Ocean, Tohoku district faced on the Sea of Japan and inland areas, throughout year and in the morning and early afternoon. Isolated cumulonimbi tend to occur on the sea and coastal area in the late afternoon from summer to autumn. Most of tornado vortices tend to move east or landfall from the sea. The velocity difference of vortices tends to decrease, and their diameter tends to shrink after landfall. The lower limit of the maximum wind velocity of tornadoes causing damages is found to be 22 m/s at about 1 km AGL.

We found that there are various types in cloud cluster. For example, some supercells in the Outer rainbands of typhoon are just classified as Supercell. The other systems without mesocyclone in the Outer rainbands may be classified as Cloud cluster. Then, we will classify such systems in detail with respect to various observation scales, temporal change of shape and so on. In this presentation, we will report the results of the detailed investigation.

How to cite: Shibayama, T. and Sassa, K.: Tornado Climatology focused on the shape of parent convective system in Japan, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-190, https://doi.org/10.5194/ecss2025-190, 2025.

Ecuador’s equatorial location and diverse topography, spanning coastal plains, Andean highlands, and Amazonian rainforests, result in complex rainfall regimes strongly modulated by the El Niño–Southern Oscillation (ENSO). This study investigates the evolution of rainfall climatology and the predictability of extreme precipitation events over two distinct periods (1981–1999 and 2000–2018), focusing on the multidecadal modulation of ENSO’s impacts. Using homogenized daily precipitation data from over 1,000 stations provided by the Instituto Nacional de Meteorología e Hidrología (INAMHI) and satellite-derived datasets (MSWEP, IMERG, CHIRPS), we analyze seasonal rainfall patterns and extreme events through climatic indices such as Consecutive Dry Days (CDD), Consecutive Wet Days (CWD), R95p, R99p, Rx1day, and Rx5days.

Significant shifts in precipitation patterns were observed, with a marked increase in dry spells (CDD) in the coastal region and a reduction in wet days (CWD) and extreme precipitation events (R95p, R99p) in the Andes during 2000–2018 compared to 1981–1999. The teleconnection with ENSO also evolved: while Niño 1+2 dominated rainfall variability in the earlier period, Niño 3.4 and Niño 4 anomalies became more influential post-2000, particularly during the dry season (JAS) and transitional periods (OND). These changes indicate reduced predictability of extreme rainfall events using traditional ENSO indices, highlighting increased hydroclimatic risks, including droughts in the Amazonía and flooding in coastal areas. By integrating in-situ and satellite data, this study enhances the understanding of storm climatologies and provides critical insights for refining seasonal forecasting and climate adaptation strategies. These findings underscore the urgent need to reassess climate risk in Ecuador under a changing climate, offering valuable guidance for mitigating the impacts of extreme weather on agriculture, infrastructure, and ecosystems.

How to cite: Paliz Acosta, C., Rodriguez de Fonseca, B., and Losada Doval, T.: Modulation of Rainfall Patterns and Extreme Events in Ecuador under Multidecadal ENSO Influence, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-191, https://doi.org/10.5194/ecss2025-191, 2025.

Over the last decades, the NOAA Storm Prediction Center has developed a unique technique of predicting severe convective storm hazards by issuing so-called convective outlooks. Over time, those products have gained recognition and proved to be an effective tool in informing the general public about possible hazards associated with severe convective storms. Following the SPC idea, similar solutions have also been used in other regions of the world (e.g., ESTOFEX, PREVOTS). SPC outlooks translate the probability of occurrence of large hail, severe wind and tornadoes over the period of 24h into specific risk level categories, which since 2014 involve: (level 0) thunderstorm, (level 1) marginal, (level 2) slight, (level 3) enhanced, (level 4) moderate, and (level 5) high. In this work, we employ ERA5 reanalysis data between 1960 and 2024 (3h steps at 0.25 deg grid), and ASTORP models (Automated Severe Thunderstorm Outlooks from the thundeR Package) to construct a preliminary global climatology and trends of convective hazard probabilities corresponding to specific SPC risk categories. By doing this, we want to address two main aspects. Globally, the United States has the most comprehensive severe storm dataset, which may suggest that environments favoring extreme storms are the most frequent in this country. First, we test this hypothesis by comparing the modeled frequency of SPC risk categories between different parts of the world to determine how globally unique severe storm environments are in the United States. Second, we explore how the frequency of modeled SPC risk categories and specific severe storm hazards changed over time on the global scale, also in the context of a warming climate and with a special focus on densely populated areas. Our preliminary results indicate that while a frequency of situations resulting in non-severe or marginally severe thunderstorms has decreased over time, we observed an increase in the environments associated with particularly large probabilities for the occurrence of severe and significant severe convective hazards.

How to cite: Taszarek, M., Pilguj, N., Matczak, P., and Surowiecki, A.: Global climatology and trends in modeled Storm Prediction Center (SPC) risk categories , 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-219, https://doi.org/10.5194/ecss2025-219, 2025.

Derechos are large windstorms that cause significant damage to forests, vegetation, and infrastructure not only due to their scale but also their intensity. Although only a few such events typically occur each year in Central Europe, forecasting these windstorms remains a major challenge for meteorologists.

In our study, we examined the convective environment associated with derechos from 1999 to 2024 using the ERA5 reanalysis and the high-resolution Central-European ALADIN reanalysis during the full life cycle of each event. The path of each derecho was refined both spatially and temporally by combining data from the European Severe Weather Database (ESWD) with weather radar observations and other sources (mainly case studies). We also analyzed vertical profiles across modelled conditions one to two hours prior to each derecho occurrence, ensuring they were not contaminated by ongoing convection.

Each derecho path was divided into segments based on storm evolution: regions of intensification, mature phase, and weakening. For each segment, we assessed environmental precursors of convection such as CAPE, vertical wind shear, or helicity, along with composite parameters, moisture characteristics, and characteristics of lapse rate. Apart from that, we also studied the convective environment across whole Central Europe in relation to derechos, using both the ERA5 and the ALADIN reanalysis datasets.

Our findings revealed notable differences in key precursor parameters (such as CAPE, CIN, and wind shear) between the intensifying and dissipating phases of derechos. Interestingly, even with low CAPE and vertical wind shear values ​​during the dissipating phases, some derechos were still capable of producing damaging winds, especially where surface moisture and temperature gradients remained favourable. In some cases, this fact prolonged the area of the derecho's impact by up to 200 kilometers. We also analyzed vertical profiles of air temperature, humidity, and wind before the derecho arrived, using median and mean Skew-T diagrams and hodographs derived from the ERA5 reanalysis. Profiles showed that relative humidity in the lower and mid-troposphere in Central Europe is, on average, quite homogeneous unlike in the derecho environments in the USA, where the relative humidity at low levels is higher and at mid-levels is lower than in Central Europe. We found out that hodographs were slightly curved from 0 to 3 km in height which suggests the connection between derechos, bow echoes and supercells.

How to cite: Staněk, M., Rýva, D., and Müller, M.: Conditions during the formation of warm-season derechos in Central Europe during last 25 years, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-232, https://doi.org/10.5194/ecss2025-232, 2025.

Derechos and derecho-like storms are severe, long-lived convective wind events that regularly cause fatalities and widespread damage, including large-scale forest loss. This study presents the first dataset on derecho-like storms that have occurred in the Russian forest zone in the 21st century, and considers their main climatic characteristics and formation environments.

By combining ground-based and satellite observations, particularly satellite-derived data on windthrow events, we identified 41 derecho-like storms, 31 of which occurred in European Russia. Based on their path length and storm intensity indicators, we classified five events as derechos, including two previously confirmed derecho events that occurred in the summer of 2010 and one derecho event that was first confirmed in Siberia. The frequency of derecho-like events in the Russian forest zone is three to four times lower than that of warm-season derechos in Central and Western Europe. The highest frequency (one case every four to five years) is found in the Middle Volga region. The highest number of events occurred in June and July in 2010 and 2020. Despite their low frequency, derecho-like storms cause substantial damage; for example, 91 fatalities and 539 injuries have been associated with the 41 storms considered. However, data on economic losses is incomplete. Derecho-like storms are responsible for the loss of forests in an area totalling 2,705 km², which constitutes 41.7% of the total windthrow area in Russia between 2001 and 2024, and 52.4% of that in the forest zone of European Russia.

According to satellite observations, the majority of these storms in the Russian forest zone are produced by quasi-linear convective systems or mesoscale convective complexes of meso-α scale. Progressive and hybrid events dominate the sample, which is typical of the warm season. According to the ERA5 reanalysis data, the convective environments of derecho-like events are similar to those associated with severe convective windstorms in the U.S. and Europe during the warm season. For example, most events form under conditions of high CAPE and high shear. However, the most severe storms, classified as derechos, do not correspond to the highest values of convective variables. 

The study was supported by the Russian Science Foundation (grant no 24-17-00357).

How to cite: Shikhov, A., Chernokulsky, A., Yarinich, Y., and Davletshin, S.: Derecho and derecho-like events in northern Eurasian forests, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-238, https://doi.org/10.5194/ecss2025-238, 2025.

Radar technology has been demonstrated to be a reliable remote sensing method for detecting hail occurrence. Nevertheless, the determination of the severity of detected hail cells remains challenging. The tracking algorithm TRACE3D was applied to a 3D radar composite (from 16 single-polarized C-band radars operated by the German Weather Service, DWD) in order to detect potential hail cells at a high level of spatial and temporal homogeneity over twenty years (2005 - 2024). To go a step beyond purely cell tracking, various attributes of each detected cell were utilized as proxys for hail severity: Area and size of high reflectivity values, echotop height, and integrated reflectivity in the hail growth area. Additionally, insurance and lightning data were used for a more detailed classification of entire hail streaks in the radar data.

This relatively long dataset of real-time measurements of potential hail-bearing cells and their attributes allows us not only to conduct an in-depth examination of climatologies with high resolution, but also to carry out severity-dependent trend analyses. Furthermore, the relationship between the frequency and intensity of the tracks and various environmental parameters well-known to be highly relevant for hail occurrence, including Convective Available Potential Energy (CAPE), Lifted Index (LI), and storm-relative helicity (SRH), was analyzed.

Regionally differentiated climatologies for Germany depending on hail severity as well as trend analyses depending on cell attributes are presented for the first time. Those analyses provide deep insight into systematic changes in hail formation, especially in the context of climate change.

How to cite: Augenstein, M., Sperka, C., Tonn, M., and Kunz, M.: A Comprehensive 20-Year Evaluation of radar-detected Hail Cell Severity in Germany, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-247, https://doi.org/10.5194/ecss2025-247, 2025.

On 17 August 2022, the western Mediterranean experienced an unusual thermodynamic environment with extremely high unstable atmospheric conditions, combined with strong wind shear. These conditions, with the help of a shortwave trough, led to the formation of a bow-shaped system of thunderstorms, which developed into a derecho, very rare in the region. This system produced a long path of severe winds, stretching from the Balearic Islands to southern Czech Republic on 18 August. The strongest wind gust reached 62.2 m s⁻¹ at Corsica, where numerous records were beaten. Unfortunately, 12 people lost their lives, and 106 were injured during this event.

A record-breaking marine heatwave (MHW) was present in the western Mediterranean simultaneously during the summer of 2022, peaking in July. The extremeness of the summer 2022 MHW is evidenced by the high SST anomalies in the first half of August 2022, ranking first among all years since 1940. An attribution exercise with numerical experiments and novel results (González-Alemán et al., 2023) indicated that this derecho event was substantially amplified by the extreme MHW and suggested that current anthropogenic climate change forcing contributed to triggering the severe storm by creating a thermodynamical environment more favorable for convective amplification.

However, no answers can be obtained regarding its dynamical contribution. Thus, to further investigate this event and the dynamical role of global warming in it, we explore the atmospheric circulation mechanisms that can lead to such a record-breaking event and other years with extreme convective activity over the western Mediterranean.

How to cite: González-Alemán, J. J., Oltmanns, M., Gonzalez, S., Vitard, F., Donat, M., Doblas-Reyes, F., Riboldi, J., Barriopedro, D., Calvo-Sancho, C., and Jiménez-Esteve, B.: From Greenland to the Mediterranean: Unveiling a new cascading atmospheric circulation mechanism promoting extreme convective activity?, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-274, https://doi.org/10.5194/ecss2025-274, 2025.

Over the past decade, the U.S. renewable energy sector has experienced significant growth, with solar energy playing a key role in the transition to low-carbon power generation. Utility-scale solar projects are increasingly being sited in the Southern Great Plains and Upper Midwest—regions frequently impacted by severe convective storms and large hail—introducing a heightened risk to solar farms. According to a recent study by kWh Analytics, while hail-related claims are less frequent than other sources of losses to solar farms, they accounted for nearly 50% of total claim severity for U.S. solar assets between 2018 and 2023. This highlights the disproportionate financial impact of hail on solar assets and underscores the challenges insurers face in understanding and insuring such risks.

To support the (re)insurance industry in understanding and quantifying hail risk to solar farms of different capacities, a detailed, analytical, component based engineering framework has been developed to assess hail risk. This study outlines the key components of this vulnerability framework, which relies primarily on disecting solar farms of various throughout capacities into sub-components and quantifying their vulnerability to hail at the component level. Component-level damage/vulnerability functions are based on understanding the component’s resistance towards hail impact and explicitly accounting for commonly observed damage mechanisms. These component relationships are then aggregated to farm-level damage functions using component cost distributions, derived from the National Renewable Energy Laboratory dataset. The framework accounts for variation in vulnerability across different farm configurations, including ground-mounted fixed-tilt, single-axis and dual-axis tracking systems, as well as rooftop: mounted and ballasted installations. It incorporates data from the Energy Information Administration’s Solar Energy Database to reflect common tilt angles and orientation, which significantly influence exposure to hail impact. One of the key features of the framework is its ability to quantify risk using hail impact kinetic energy as the intensity measure. Kinetic energy is a robust intensity metric since it can capture both the vertical and horizontal components of impact, as well as the full distribution of hailstone sizes within the hail swath—rather than relying solely on maximum diameter—to capture the full damage potential. This component-level methodology enables a more physically representative and granular understanding of hail risk for such type of assets. By integrating engineering, cost, and observational data, the framework provides (re)insurers, asset managers, and solar farms developers with an effective tool for assessing and managing hail-related exposures in the growing U.S. solar market.

How to cite: Mistry, H., Johnson, T., Bobby, S., and Ramanathan, K.: Hailstorms and Solar Farms: A Holistic Framework to Assess the Risk Potential to Emerging Renewable Assets, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-280, https://doi.org/10.5194/ecss2025-280, 2025.

Extreme precipitation events in central Europe during the summer months are typically associated with intense convection. In this study, we perform Lagrangian analysis of convective cells under different large-scale circulation regimes. Precipitation is commonly analysed from an Eulerian perspective, in which rainfall is considered at a fixed location. Lagrangian analysis of precipitation represents an alternative approach: precipitation objects are identified in a precipitation field and are tracked through space and time, allowing object properties over the lifecycle of a convective cell to be computed. This approach offers additional insights into the mechanisms by which convective cells develop, behave across their lifecycle, and how these may respond to warming.

Here we analyse convection-permitting simulations with the COSMO-CLM at 3-km resolution over central Europe. Precipitation objects are tracked through space and time, collecting cell characteristics for each object, e.g. cell area, intensity, distance travelled, etc. Convective cells are identified using an objective algorithm. These are are then categorized based on their accompanying synoptic-scale circulation patterns using a physically based objective classification method. Cell properties – as well as how these respond to warming – are then compared between the different categories, offering insight into the impact of the large scale circulation on the response of convective precipitation – both mean and extreme – and the associated cell characteristics to warming.

How to cite: Meredith, E., Ulbrich, U., and Rust, H.: Warming response of convective rainfall under different synoptic forcings, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-282, https://doi.org/10.5194/ecss2025-282, 2025.

How to cite: Rauhala, J., Virman, M., and Jylhä, K.: Environments of major convective wind events in Finland , 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-296, https://doi.org/10.5194/ecss2025-296, 2025.

Supercell storms annually cause substantial property damage, injuries, and fatalities across Europe. These storms, characterized by deep, rotating updrafts, generate violent phenomena like flash floods, large hail, and strong convective winds. They are also responsible for Europe's most intense tornadoes (IF2+), including those in Poland. Despite these significant threats, there's been no prior climatological research on supercells in Poland.
This study aimed to analyse the spatial and temporal characteristics of supercell thunderstorms in Poland over a 15-year period (2008-2022). To achieve this, a database of supercell thunderstorms has been developed. This involved manually analysing 10-minute interval radar data and severe weather reports from the European Severe Weather Database (ESWD). We also incorporated lightning data from the PERUN network to differentiate supercell environments from non-supercell storms. Identification criteria included typical radar signatures (e.g., bounded weak echo regions, velocity couplets, hook echoes) and/or long, continuous paths of high radar reflectivity with deviant motion. We categorized identified supercells into three groups based on detection confidence, ranging from plausible to those producing significant severe weather.
Our analysis identified a total of 1748 confirmed and possible supercell cases, more than 100 as average per year. Nearly half of them (862 cases, 49.4%) were fully confirmed, with 616 (35.2%) highly probable and 270 (15.4%) possible, because of not enough sufficient data for full confirmation.
This manual evaluation of 15 years of data allowed for a climatological analysis of supercell track widths and lengths, storm duration, spatiotemporal frequency, associated hazards, and propagation characteristics (e.g., right- or left-moving). The supercell season in Poland mirrors the general storm season, with most occurrences from May to August. The earliest detection was in early March, the latest in late October. Most cases were observed in southern Poland - an area with complex topography that may influence wind shear. Furthermore, we utilized ERA5 reanalysis to study the atmospheric environments accompanying these supercells, calculating pre-convective profiles and hodographs for each. A significant contribution of this work is the calculation of environmental parameters (like storm relative helicity or streamvise vorticity) using radar-derived observed storm motion vectors, rather than relying on estimations.

How to cite: Piasecki, K., Taszarek, M., Pilguj, N., and Surowiecki, A.: The climatology of supercell thunderstorms across Poland based on multisource data., 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-311, https://doi.org/10.5194/ecss2025-311, 2025.

The global distribution of severe convection has become a topic of increasing interest in recent decades with the arrival of the 4^th and 5^th generation reanalysis products at horizontal and temporal resolutions that have a good capacity to represent convective environments. Intercomparison and evaluation of reanalysis relative to observed profiles globally reveals inconsistencies in how these best-guess analyses represent convective environments. This suggests to capture global severe convective environments a multi-reanalysis ‘ensemble’ is necessary, as no single product can be considered to be equally performative across different regions. Traditionally, modelers have focused on regionally invariant relationships, or calibrated approaches to balance performance across different domains, however, this presents a significant challenge when the well observed regions are typically confined to mid-to-high latitudes. Like the single reanalysis approach, single models or parameter combinations have proven of limited utility in depicting the wide range of environments that can produce these hazards across different regions.

This poster will illustrate the evidence for variable reanalysis performance, a multi-reanalysis climatology of convective environments, and introduce a hierarchical random forest modeling to represent the regional and seasonal variations in potential environments. This novel approach will be compared to existing models that use linear or fixed threshold approaches to approximate environment frequency, and highlight regions where the hierarchical approach shows considerable differences. Finally, spatial maps and distributional spaces will be used to illustrate how these environments relate to traditional phase spaces, and regions of common convective environment characteristics.

How to cite: Allen, J., Cuervo Lopez, C., and Taszarek, M.: Global Perspectives on Convective Storm Frequency from Multi-Reanalysis Climatology, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-314, https://doi.org/10.5194/ecss2025-314, 2025.

How to cite: Jentsch, H. and Schröer, K.: Identifying Hotspots of Convective Events in the European Alps by Analyzing Synoptic Circulation Types and Report Data of the last 33 Years, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-171, https://doi.org/10.5194/ecss2025-171, 2025.