Tornadoes are weather hazards that can kill people and severely damage infrastructure, whose small size and chaotic dynamics presently limit our capability of a deterministic reproduction of their frequency. Several studies show the role played by meteorological factors such as updraft strength and wind shear. In this study, we apply an empirical approach based on meteorological variables available from the ERA5 reanalysis dataset for the analysis of tornado occurrence over USA and Europe and compare its results to the observed tornado occurrences recorded by the European Severe Weather Database (ESWD) in Europe (https://www.essl.org/cms/) and the Storm Prediction Center (SPC) in the United States (https://www.spc.noaa.gov/wcm/#dat).  The analysis is based on   WS700 (lower troposphere wind shear) and WMAX (maximum updraft parcel vertical velocity associated with Convective Available Potential Energy., or CAPE). These variables are used to estimate the frequency of log10(p) exceedances over crucial thresholds (-3.5 and -4.5) and compare them to observed tornado counts using the methods of Ingrosso et al. (https://doi.org/10.5194/nhess-23-2443-2023). We complement this analysis with an estimate based on the simultaneous occurrence of large values of WMAX and WS700 (HTR, high-tornado-risk WMAX-WS700 conditions). In the United States, HTR WMAX-WS700 occurrences is a powerful indicator of tornado activity, particularly during spring (r = 0.98), with solid yearly correlations (r = 0.91) and significant skill even in winter. Probability thresholds (log₁₀(P) > -4.5, -3.5) reveal strong correlation in spring and annually (r ≈ 0.7-0.8), but weaker or even negative relationships in summer and autumn. Across all seasons, the occurrence-based metric HTR WMAX-WS700 regularly beats the use of probability thresholds in terms of correlation with observed tornadoes frequency, especially in the autumn, when probability-based indicators fail. In Europe, the HTR WMAX-WS700 approach performs less satisfactorily than in the USA (r = 0.50, p = 0.028 at the annual time scale), and probability thresholds perform poorly. Overall, our approach performs best when employing the HTR WMAX-WS700 approach during peak tornado seasons, particularly in the United States, whereas probability thresholds alone are insufficient for meaningful prediction outside of peak periods. These findings emphasize the importance of seasonally adaptive and occurrence-based approaches to tornado risk assessment.

This study was supported by funding from ICSC – Centro Nazionale di Ricerca in High Performance Computing, Big Data and Quantum Computing, as part of the European Union’s NextGenerationEU initiative. Project code: CN_00000033 CUP: C83C22000560007.

How to cite: Muhammadi, A. and Lionello, P.: Describing long term seasonal and interannual variability of tornado frequency across the USA and Europe, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-40, https://doi.org/10.5194/ecss2025-40, 2025.

Abstract: In July 2023, the western Balkans were struck by a serias of supercells and squall lines, that resulted in several fatalities, numerous injuries, and extensive property damage. In each of these cases, a trough at the 500 mb level facilitated the of a colder air mass from northern Europe, which collided with a warmer air mass from the south. This interaction, combined with surface heating and high Convective Available Potential Energy (CAPE) and a low Lifted Index (LI), led to development of cumulonimbus (Cb) clouds, which caused significant damage. These atmospheric instabilities produced hailstones exceeding 5 cm in diameter, wind gusts between 15-25 m/s (locally even stronger), heavy localized rainfall, and intense lightning activity. For most days with severe to extreme weather phenomena, numerical weather models provided accurate forecasts. However, on July 18, the Weather Research and Forecasting (WRF) with ARW core version 4.3.3 underestimated the event. The model, configured with Thompson microphysics and a horizontal resolution of 8 x 8 km (initialized with GFS data at 12 UTC on July 17, 2023), predicted the 500 mb trough and associated jet stream to be located farther west and north than the actual location. In reality, the suqall line affected most parts of northern Croatia, Bosnia nad Herzegovina, southewestern Serbia and Montenegro moving quickly from the Alps. As a result, real-time radar and satellite monitoring proved to be crucial for tracking the system. RGB composites, along with WV and IR satellite channels, were particulary effective in monitoringthe squall line on that day. Most of the supercells and instabilities observed during July 2023 followed a similar trajectory, originating over the Alps and progressing toward the Balkans and the Pannonian Plain.

How to cite: Mrkonjic, D.: The Severe to Extreme storms over Bosnia and Herzegovina in July 2023, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-82, https://doi.org/10.5194/ecss2025-82, 2025.

Cloud dynamical and microphysical characteristics are among the critical aspects that still produce the largest uncertainty in weather and climate models. Beyond the inherent technical limitations of these models, a major factor contributing to this uncertainty is the lack of sufficient in situ observations of cloud characteristics. Here, we use high-altitude aircraft observations from the ACRIDICON-CHUVA campaign near tropical deep convective clouds to examine the cloud characteristics and understand the dynamical and microphysical aspects. We analyse several critical parameters, including in-cloud vertical velocity, cloud water content, and particle size distribution to quantitatively explain the cloud properties. This is done through identifying updrafts and downdrafts using vertical velocity observations. In this study, a draft is defined as a region with a continuous non-zero positive or negative vertical velocity value maintained for 500 meters. Our analyses show that the updrafts and downdrafts have very similar cloud water content, along with a comparable mean cloud particle distribution, which could indicate mixing between drafts. Furthermore, we observe supersaturated regions with respect to ice in the high-altitude downdrafts, which suggests that latent cooling from sublimation might not be the driving factor of these downdrafts. Detailed discussions on these results will be presented during the conference.

How to cite: Kizhuveettil, S., Vilà-Guerau de Arellano, J., Krämer, M., Afchine, A., A. T. Machado, L., Zöger, M., and Frey, W.: High-altitude cloud characteristics in tropical deep convective clouds from Aircraft observations, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-106, https://doi.org/10.5194/ecss2025-106, 2025.

Deep moist convective updraughts are associated with various severe weather hazards, including hail formation, heavy precipitation, strong surface winds and turbulence. Yet, the actually realised hazards critically depend not only on the updraught strength, but also on the specific evolution related to the associated organised convective storm. A low-dimensional model of the governing updraught dynamics would potentially benefit parametrisations and short-term forecasting. However, despite ongoing efforts no satisfying low-dimensional model has been proposed so far. In this talk, we present a novel approach to deep-convective updraught modelling, motivated by the cauliflower-like visual appearance of cumulus clouds in the atmosphere. This appearance readily suggests that cumulus convection is the consequence of the collective dynamics of a large number of similar bubble-like elementary entities. Our model considers a central parcel that evolves according to classical parcel theory but is dynamically coupled to an ensemble of surrounding parcels. All parcels are modelled as (nonlinear, non-harmonic) oscillators. In the limit of very many interacting parcels, we adopt an approach from statistical physics to reduce the multi-body problem to a low-dimensional representation of the central-parcel evolution in terms of a generalised Langevin equation. This model essentially describes deep-convection updraughts as a Brownian motion in a potential well representing buoyancy. In particular, coupling of the central parcel to the environment causes a damping and (stochastic) forcing. We show that the model qualitatively agrees with well-reported features of atmospheric deep convection. For the quantitative assessment of our model, we compare with updraught measurements reported in the literature and those estimated from cumulus cloud-top cooling rates in geostationary satellite imagery. In particular, we give an account on the difficulties involved in directly comparing analytical models with these observations. Overall, we show that our updraught model correctly reproduces the governing features observed in atmospheric deep convection by correcting classical parcel theory. These results are encouraging and may stimulate new modelling attempts in the future.

How to cite: Bölle, T. and Mecikalski, J.: A novel analytical deep-convection updraught model and how it compares against observations, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-130, https://doi.org/10.5194/ecss2025-130, 2025.

Low-dimensional representations of the governing thunderstorm dynamics are essential for parametrisations and short-term predictions of severe weather. These are important prerequisites for safe and efficient operations of various sociotechnical systems (e.g. aviation, coupled energy systems). The prototype of the convection-scale thunderstorm evolution and elementary building block of organised thunderstorm systems is the cell lifecycle. In this presentation, we propose an analytical, low-dimensional model of the thunderstorm lifecycle. The very concept of a lifecycle implicitly assumes that thunderstorms are definite and recurrent coherent structures. This suggests a modelling approach in terms of macroscopic variables that characterise thunderstorms integrally. Inspired by Doswell et al.’s ingredients-based method and past experience with expert systems, we adopt a rule-based approach. This way, we formalise the general features of the lifecycle in a set of reaction rules, which are equivalent to a system of coupled, nonlinear differential equations. By design, this model is qualitatively consistent with the known features of the thunderstorm lifecycle. In order to verify that our model quantitatively captures the essential features of actual thunderstorm manifestations in the atmosphere, we compare our model against remote-sensing observations. In particular, we use satellite imagery from the SEVIRI instrument onboard the Meteosat Second Generation satellite and radar data from the WX composite over Germany, operated by the German Meteorological Service (DWD). Our model is intended to capture the most fundamental, repeatable features of the thunderstorm lifecycle. We therefore present an elementary post processing of the remote-sensing data to single out the relevant observational signatures associated with single-cell thunderstorm occurrence. Eventually, we demonstrate that our model correctly captures this temporal signature of post-processed remote-sensing observations quantitatively. Ultimately, our thunderstorm-lifecycle model may improve parametrisations as well as traditional nowcasting or physics-informed machine-learning approaches.

How to cite: Bölle, T., Metzl, C., and Vahid Yousefnia, K.: A low-dimensional model of the thunderstorm lifecycle and its verification in remote-sensing observations, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-131, https://doi.org/10.5194/ecss2025-131, 2025.

Quasi-linear convective system (QLCS) tornadoes are particularly difficult for forecasters to predict, resulting in short or even negative warning lead times. This is due in part to the relatively shallow nature of parent mesovortices and thus an increased reliance on low-level radar data, which are often absent in the U.S and worldwide. However, it is hypothesized that relatively deep, discrete updrafts may indicate portions of a linear system where tornadogenesis is most probable. Notably, these updrafts are easily identifiable in upper-tropospheric radar data, which are still available far from the nearest radar site, whereas low-level data can only be gathered relatively close to a radar. Using a dataset of QLCS tornadoes covering three years, it is shown that around 62% of tornadoes are preceded by discrete radar reflectivity cores several kilometers aloft, identified using gridded Multi-Radar Multi-Sensor (MRMS) data and indicating the presence of a deep updraft. Analysis of the near-storm environment at the time of tornadogenesis in each case reveals that 0-6 km and 3-6 km shear are especially good predictors of which tornadoes will be co-located with reflectivity cores, with greater shear resulting in more tornadoes having discrete updrafts in the mid-levels. We hypothesize that strong mid-level shear results in a negative pressure perturbation aloft that is supportive of deep QLCS updraft growth and that these updrafts indicate where low-level lifting is most capable of tilting and stretching vorticity to tornadic strength. The implications of null cases on the operational capability of reflectivity cores will also be discussed.

How to cite: Wolff, E., Trapp, R., and Nesbitt, S.: Identification of discrete updrafts within quasi-linear convective systems using gridded radar data and potential implications for tornadogenesis prediction, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-183, https://doi.org/10.5194/ecss2025-183, 2025.

Urban land use may cause an intensification of convective rainfalls over or downstream of cities. Little is known about the effect of urban land use on other damaging convective phenomena, such as convective windstorms. This is a relevant topic since cities are far more vulnerable and exposed than rural areas to weather-related risks. The question is well-posed because severe local storms are influenced by the thermodynamic and kinematic properties of the atmospheric boundary-layer that respond directly to the presence of a city.

To explore the origin of the interaction between an urban land use and a convective windstorm, high-resolution numerical simulations are set-up using the Weather Research and Forecasting model on a relevant case study that occurred on July 25, 2023, in Milan, Northwestern Italy. An urban and a no-urban, i.e., with urban land use replaced by croplands, physics ensemble at 1 km of grid-spacing are generated, employing the Building Effect Parametrization (BEP) and the Building Energy Model (BEM), different microphysics and atmospheric boundary-layer schemes, and land use datasets.

Simulations highlight an alteration due to the urban land use with a northward shift of the storm already in the upwind region. Over the city, wind gusts are reduced by about 13% due to the buildings drag, and updrafts are intensified. After passing over the city, the storm is broken, with a delay of about 5 km compared to a no-urban scenario. The above observations are accompanied by a decrease of surface equivalent potential temperature and a decrease of storm relative helicity over the city in the pre-storm environment. In conclusion, even an intense convective windstorm is significantly impacted by the urban land use: its trajectory, morphology, and intensity are modified by the city. These modifications seem to be mostly related to the effect of the buildings on the gust front rather than on the thermodynamic alteration induced by the urban land use in the pre-storm environment.

How to cite: De Martin, F., Zonato, A., and Di Sabatino, S.: Effects of the urban land use on a severe convective windstorm, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-197, https://doi.org/10.5194/ecss2025-197, 2025.

The Ivanovo tornado outbreak on 9 June 1984 is one of the most destructive in the history of instrumental observations in the USSR and Russia. According to different data, at least eight convective storms led to the formation of eight to thirteen tornadoes that day, although this number may be underestimated. This study presents an analysis of the Ivanovo tornado outbreak using simulations with the non-hydrostatic mesoscale model WRF-ARW with several nested grids, the innermost of which have a resolution of 1 and 3 km, in convection-permitting mode. The ability of the model to simulate convective events was evaluated in comparison with satellite and ground-based observations.

It was found that the 3 km resolution model reliably reproduced the observed convective storms of the outbreak, including the supercells. The closer the cells were located to the centre of the cyclone’s occlusion, the more accurately the model reproduced their characteristics. By analyzing updraft helicity, it was confirmed the presence of at least four mesocyclones, which resulted in formation of tornadoes identified earlier from satellite data on windthrow and by eyewitness observations. The higher-resolution mode (1 km) enabled some of the characteristics of the analysed storms to be specified. In particular, supercell merging and a kind of ‘the Fujiwhara effect’ were identified. Characteristic signatures were detected in areas where particularly large tornadoes occurred. The process of rear flank downdraft occlusion and tornado genesis in the Ivanovo supercell was analysed. It has been suggested that an anticyclonic tornado occurred alongside the main F4 tornado that passed through Ivanovo.

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

How to cite: Gostev, K., Vazaeva, N., Shikhov, A., Stepanenko, V., and Chernokulsky, A.: Analysis of the 1984 Ivanovo tornado outbreak using the WRF-ARW model, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-239, https://doi.org/10.5194/ecss2025-239, 2025.

Raindrop size distributions (DSDs) are crucial for understanding the microphysical mechanisms of rainfall. This study investigates DSD characteristics for convective and stratiform rainfall in Great Britain (GB) using data from eleven Thies laser precipitation monitors (LPMs), one OTT Parsivel², and one Joss–Waldvogel disdrometer (RD-69) collected between 2017 and 2019. Approximately 1.1 million high-resolution one-minute raindrop samples were fitted to the normalized gamma distribution model, parameterized by the concentration parameter (N_w), the mass-weighted mean diameter (D_m), and the shape parameter (μ). The core focus of this presentation is to elucidate how these DSD characteristics vary both temporally and spatially within GB. Temporally, we investigate distinct seasonal shifts in D_m, N_w, and μ for both rain types, exploring linkages to seasonal changes in atmospheric thermodynamics and dynamics. Spatially, we examine the influence of geographical factors and topography on the DSD parameters, assessing how local environment modulates raindrop spectra. Furthermore, the presentation will detail the characteristic relationships between these key DSD parameters (N_w, D_m) and the rainfall rate (R), highlighting differences between convective and stratiform regimes and how these relationships themselves may exhibit spatial and seasonal dependencies across the different regions of Great Britain. This analysis provides vital insights into regional precipitation microphysics.

How to cite: Jiang, S. and Rico-Ramirez, M.: How do the raindrop size distributions of convective and stratiform precipitation change in Great Britain?, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-251, https://doi.org/10.5194/ecss2025-251, 2025.

In Japan, approximately 10% of convective systems that produce tornadoes are supercell-type storms. Most of them are mini-supercells that form within the outer rainbands of tropical cyclones. However, the case that occurred on September 30, 2018, represents a highly unusual event. Firstly, the convective systems yielding tornadoes located outside the outer rainbands, far from the eye of the Typhoon, ‘Trami’. Furethermore, their arrangement was nearly parallel to the typhoon's radial direction, distinguishing them from typical outer rainband configurations

    The present study aims to clarify the structure and generation mechanism of the parent convective system. We used the data obtained from JMA Muroto operational radar and our own X-band radar network, and the initial values of mesoscale model provided by JMA.

    The radar data showed that the mesocyclones of about 2 km in diameter, persisted for 35 minutes and a tornado vortex was located to the southeast of the mesocyclone. We also observed a vault structure within the mesocyclone. These features confirm that the parent storm was a mini-supercell. The mesocyclone appeared at the southwestern end of a linear rainband, which measured approximately 20 km in length and 4 km in width. Each rainband was organized from merged small cumulonimbi, indicating that the parent storm was an aggregate of small convective cells with a mini-supercell positioned at its southwestern extremity. Their rainbands propagated northwestward, almost perpendicular to their orientations. Such fact shows the presence of a cold pool from the preceding rainband in the forward flank of the parent rainband, and it was found that the mesocyclone was unable to receive moist warm air necessary as energy for the parent storm.

    In this presentation, we will introduce these anomalous features of this unique storm and will pose a question regarding the precise definition of a supercell.

How to cite: Sassa, K.:  A strange supercell embedded in a linear convective system, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-301, https://doi.org/10.5194/ecss2025-301, 2025.

Recent summers in Europe were accompanied by significant convective storm outbreaks with widespread large hail, flash floods, and severe wind phenomena. Particularly severe outbreaks have occurred upstream of concurrent heatwaves. On a continental scale, this leads to considerable compound hazards from heatwaves and thunderstorm hazards. 

Utilizing reanalysis data, we investigate the connection between high temperatures and synoptic conditions leading to severe convective environments (SCE), which are conducive to severe convection. Our analysis reveals that SCE across Central and Western Europe are preceded by high temperatures and a slow-moving upper-level wave pattern. More strikingly, they reveal a strongly increased heatwave frequency downstream of SCE. 75% of SCE are associated with a heatwave, usually ~500km downstream. The remaining minority take place in much cooler, predominantly low-pressure situations, with less persistent SCE. Inversely, 80% heatwaves are also associated with upstream SCE. These heatwaves are significantly hotter by >1°C than those not associated with convection. 

This strong co-occurrence of severe convective outbreaks and heatwaves implies a dynamical link. The upper-level wave pattern may drive both the SCE through the advection of unstable airmasses and high wind shear in the prefrontal zone, as well as the heatwave by warm air advection, radiative heating, and a strong ridge. Further feedback between heatwaves and SCE is possible via diabatic heating processes and soil moisture feedback. This study highlights a previously underexplored continental-scale compound event relationship between severe convective environments and downstream heatwaves in Europe, suggesting a common synoptic driver and potential two-way interactions.

How to cite: Feldmann, M., Domeisen, D. I. V., and Martius, O.: Severe convective outbreaks and heatwaves – a continental-scale compound event, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-36, https://doi.org/10.5194/ecss2025-36, 2025.

The Asian summer monsoon (ASM) anticyclone is the largest circulatory system in the northern hemisphere. Deep convective systems develop in the ASM, providing fast pathways to (re)distribute aerosols, trace gases, and water vapour throughout the troposphere, eventually even overshooting into the stratosphere. Here, we will present unique in situ observations from within deep convective clouds, obtained during the StratoClim campaign (over Nepal) during the ASM in 2017, that employed the high altitude aircraft Geophysica (max. ceiling 21km). The Geophysica was carrying a set of in situ cloud microphysical instrumentation (scattering and optical array probes, and a back scatter sonde), as well as a miniature lidar for observing clouds in the vicinity of the aircraft. Additionally, instrumentation for trace gas observations were onboard.

We will present the general vertical microphysical structure of the probed clouds, by means of ice water content, mean particle sizes and numbers, and size distributions. Furthermore, trace gas measurements are used to identify up- and downdrafts in the clouds, to enable comparison of cloud microphysical properties in updrafts and downdrafts. The high altitude measurements were able to provide observations from within convective overshoots reaching into the stratosphere (above roughly 17.7km). Very large cloud particles of up to 900µm in diameter were observed in those overshoots. We will compare these rare data with similar observations from other tropical regions.

How to cite: Frey, W., van den Hurk, B., Bevers, C., Syaifuddin, R., Cairo, F., Mitev, V., Matthey, R., Khaykin, S., Viciani, S., Ravegnani, F., Ulanovski, A., and Krämer, M.: Inside the Asian Summer Monsoon: in situ observations from within deep convective clouds, 12th European Conference on Severe Storms, Utrecht, The Netherlands, 17–21 Nov 2025, ECSS2025-121, https://doi.org/10.5194/ecss2025-121, 2025.