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On August 18, 2022, Europe experienced the most severe storm of the year. In the early morning, a derecho formed, causing significant damage along a path of over 1000 km as it travelled at an exceptional speed of up to 40 m/s, with wind gusts reaching a maximum of 62.2 m/s. The storm had a widespread impact, affecting Spain, France, Italy, Slovenia, Austria, and the Czech Republic. The severe weather caused fatalities in several countries, with the highest death tolls reported on Corsica and in the Alps. The focus of this analysis is to understand the factors that led to the derecho's exceptional intensity. We examine the storm's chronological development, and the intensification phases it underwent. We also investigate how external and internal forcing contributed to the rapid upscale growth of the storm. From the perspective of external factors, we show the importance of a mid-level front and warm air advection at the lower levels and their relation to the distribution of CIN in the vicinity of the event. We show that the development and movement of convective cells were influenced by the mid-level front. The system was also strongly influenced by the internal forcing as it formed in an environment of high CAPE values and strong low-level vertical wind shear, and intense storm-relative inflow. The combination of internal and external forcing factors eventually resulted in the extreme forward speed of the derecho. Due to the interaction with complex topography, the derecho underwent several weakening and strengthening phases, which we associate with the changes to the internal and external forcing. Finally, we compare the environment of the derecho to typical environments of severe convective wind gusts in Europe and compare the event to similar Mediterranean derecho cases from the past.

The representation of convection in ECMWF’s forecasting system has been improved in recent years by advances in computing, substantial upgrades of both horizontal and vertical resolutions, and by major changes in the moist processes in the model. These developments have also opened up the opportunity for improvements of existing convective products and the development of new ones, such as lightning density diagnostics. As part of this ongoing initiative ECMWF is partnering with the European Severe Storms Laboratory (ESSL) on a number of projects. The computation of Convective Available Potential Energy (CAPE) and Convective Inhibition (CIN) parameters from the model has been revised and more versions of CAPE and CIN have been implemented and are made available to the forecasting community. CAPE and composite CAPE-shear parameters have been included in ECMWF’s Extreme Forecast Index (EFI) to help forecasting outbreaks of severe convection in the medium range. Alongside objective statistical verification, the convective EFI has been evaluated at ESSL’s Testbed recently. ECMWF has implemented ensemble vertical profiles to facilitate forecasting convection among other applications. ECMWF is working with ESSL on providing more parameters and products for forecasting deep, moist convection and its attendant severe weather. These include Storm Relative Helicity (SRH) and post-processed probabilities of various convective hazards such as large hail and severe wind gusts. Following its open data policy, ECMWF has also provided more probabilistic and deterministic graphical convective products on its website. This presentation will provide a brief overview of all these recent developments.

An Additive Logistic Regression model for large hail (ARhail) was developed using convective parameters from the ERA5 reanalysis, hail reports from the European Severe Weather Database (ESWD) and lightning observations from the Met Office Arrival Time Difference network (ATDnet). This model was shown to accurately reproduce the climatological distribution and the seasonal cycle of observed hail events in Europe. To explore the value of this approach to medium-range forecasting, a similar four-dimensional model was developed using predictor parameters retrieved from the ECMWF reforecasts: Mixed Layer CAPE, Deep Layer Shear, Mixed Layer Mixing Ratio and the Wet Bulb Zero Height. This model was applied to ECMWF reforecasts to compute probabilistic large hail forecasts for all available 11 ensemble members, from 2008 to 2019 and for lead times up to 228 hours. First, we compared the hail ensemble forecasts for different lead times with observed hail occurrence from the ESWD focusing on a recent hail outbreak. Secondly, we systematically evaluated the model’s predictive skill depending on the forecast lead time using the Area under the ROC Curve (AUC) as a validation score. This analysis showed that ARhail has a very high predictive skill (AUC > 0.95) for forecasts up to 60 hours lead time. Although the performance scores progressively decrease with increasing lead time, ARhail retains a high predictive skill even for extended forecasts (AUC = 0.86 at 180 hours lead time) showing that it can provide useful guidance in hail forecasting well in advance. Finally, the performance of the four-dimensional model was compared with that of composite parameters such as the Significant Hail Parameter (SHP) and the product of CAPE and Deep Layer Shear (CAPESHEAR). Results show that ARhail outperforms CAPESHEAR (at all lead times) and SHP (especially at short lead times). This suggest that the developed Additive Logistic Regression model can improve hail forecasting compared to currently used composite indices in Europe.

Here we report on the development of the International Fujita (IF) scale, developed by ESSL and partners, which provides a globally applicable framework for rating tornado and convective wind damage. Around the world, tornado damage is rated using the Enhanced Fujita (EF-)scale, the original Fujita scale, the T-scale, or national adaptations of the Enhanced Fujita scale. ESSL started the development of the IF-scale when noted that the original Fujita scale damage description provided insufficient guidance for rating tornadoes in Europe, mostly because of varying sturdiness of damaged buildings, an issue that Fujita himself addressed in his later work. The development of the IF-scale was catalysed by the introduction of the EF-scale in the USA in 2007, which drastically reduced wind speed estimates for higher wind speeds while simultaneously raising it for the F0/F1 boundary compared to the original F-scale: a change apparently motivated by a need to correct for biases in tornado rating practices. Instead of referring to building types typical for a specific region, the IF-scale instead defines categories of Damage Indicators that are more universal and can be adapted to other regions, using a damage indicator ‘building’ with an attribute ‘sturdiness’. Any building can be a damage indicator after being assigned a level of sturdiness. The IF-scale also retains the original Fujita-scale wind speed estimates, at least until measured data are available that give better estimates. The wind speed that the scale relates to is instantaneous rather than the average wind speed at 10 m above ground, as evidence is accumulating (through high-quality videos and mobile doppler radar measurements) that the wind speeds responsible for tornado damage often have a much shorter duration than the typical averaging periods for wind gust measurements. The IF-scale heavily borrows from experience in regions that have adapted the EF-scale locally, such as the Japanese and Canadian adaptations, and adds additional damage indicators such as for trees, road and rail vehicles, and many other objects. Recently, ESSL evaluated a preliminary version of the IF-scale by applying it to a violent tornado case in Czechia on 24 June 2021. This application revealed weaknesses that have since been addressed. We will present the latest version of the IF-scale that has become the standard scale used in ESSL’s record of severe weather in Europe, the European Severe Weather Database.

Until now, studies on lightning fatalities have been available from a few individual countries but not for Europe as a whole. We here report on lightning strike fatalities in the period from 2001 to 2020 that happened across Europe, all of Turkey, the Caucasus countries (Armenia, Azerbaijan, and Georgia), based on reports from the European Severe Storms Database (ESWD). The ESWD records are based on publicly available data derived from local authorities, police and fire departments, newspapers, and news agencies, which are collected by ESSL and its partners. In total, 1280 individual fatalities were recorded in the ESWD during this period. We report on the spatial distribution of fatalities, and the distribution of fatalities per age group and sex, whether the victims were at work or undertaking leisurely activities, and in which kind of landscape they were hit. Furthermore, we considered the circumstances that led to lightning fatalities that occur indoors. We found that an average of 64 people are killed by lightning strikes every year, and that the majority (78%) are male. The countries with the highest rate of lightning fatalities per capita are Bulgaria (8.6 per million per year), Moldova (7.7), and Romania (5.8). The lowest rates are found in Belgium (0.1), Malta (0.1), and Portugal (0.1). The proportion of fatalities in work activities increases from Western to Southeastern Europe. When working, people are most typically killed when working on the fields while during leisure, people are most typically killed when hiking. Of the rare indoor fatalities (1.6%), a majority (11 of 15 known cases, 72%) were killed by fire and smoke that broke out after the lightning struck. Referring to the age of fatalities, people at the age of 10-19 have the biggest share of all age decennium with a peak at the age of 15 (33 fatalities). Divided by sex, male fatalities also show the biggest share in the age decade of 10-19, while female fatalities peak in the age decade of 50-59.

Additive Logistic Regression Models for different convective hazards were developed across Europe and a portion of North America using lightning observations, severe weather reports and convective parameters from the ERA5 reanalysis. To model convective hazards, convective initiation was taken explicitly into account by computing, for instance, Phail (probability of hail) as the product of P­storm (probability of convective initiation) and Phailstorm (conditional probability of hail given a storm). We will report on the development of models that are skilful across Europe and North America, and on the regionally dependent skill of convective parameters used as model predictors. To reconstruct the probability of lightning, large hail, and very large hail from 1950 to 2021, the models were applied to the ERA5 reanalysis, at one hourly intervals across both regions. The modelled hazard climatologies are in strong agreement with observed patterns and can accurately resolve local-scale features thanks to the (0.25 x 0.25° degree) spatial resolution of the ERA5 reanalysis. We analysed long-term trends over the 71 year period and detected important differences between the regions. Across North America, 1950–2021 hail trends were found to be weak and mostly non-significant, but a period of enhanced lightning activity (+30% to 1950–2021 average) was detected between 1980 and 1990 across the Central Plains. In Europe, trends are mostly positive and significant, with the highest trend modelled across Northern Italy. Here, the convective activity has seen an abrupt increase with very large hail 3 times as likely in recent years (2012–2021) than in the 1950s. Apart from a sharp increase in frequency, the year-to-year variability has also increased with yearly differences in occurrence exceeding 100% for large and 200% for very large hail compared to the long-term average. In addition to (very) large hail, preliminary results on the development of models for severe wind gusts and tornadoes models along with the corresponding long-term trends will be presented.

To prepare users for the Meteosat Third Generation of satellites, the first of which was launched in December 2022, ESSL conducts testbeds and expert workshops in cooperation with EUMETSAT at the ESSL Research and Training Centre in Wiener Neustadt, Austria. The goal of the testbeds is to expose forecasters to the capabilities of new MTG sensors, the Flexible Combined Imager (FCI), the Lightning Imager (LI), and the Infrared Sounder (IRS) and to collect their feedback on the visualizations of the data. In each of the testbeds, three of which were held in 2022, 15 people from different EUMETSAT member states take part in a week-long activity with working conditions close to the usual working environment of a forecaster, i.e., with having a wide range of data available, including many data not from satellites, together with predefined output formats and time pressure. The task of the participating meteorologists is to produce nowcasts and probabilistic forecasts for predefined types of severe weather. The forecast region depends on the weather situation of a particular day and can shift from one part of Europe to another from day to day, depending on the active weather patterns. In 2022, before any MTG data was available, a range of products that functioned as a proxy for MTG data was used. This included data from imagers on polar-orbiting satellites mimicking the capabilities of future FCI products. These data were visualized in the ESSL Displayer, ESSL’s html interface for visualizing meteorological data. Based on the participants’ work and expert consultation on several RGBs, a novel “Low Moisture” product, and a range of products from the Nowcasting Satellite Applications Facility (NWC-SAF), direct and written feedback was collected and provided to the developers. In 2023, the focus will move away from proxy data to data collected by real MTG sensors. Actual FCI and, later, LI products will be included in the Testbed Displayer. For the hyperspectral IRS, a sensor mounted on the second MTG satellite to be launched in 2024, proxy data will be visualized.

The European Severe Storms Laboratory (ESSL) has developed logistic models (AR-CHaMo) for the occurrence of lightning and (very) large hail based on the ERA5 reanalysis, with the primary purpose of investigating long-term chance in severe weather occurrence. These models can, however, also be used in a forecasting context. We have set up a routine that uses AR-CHaMo models to post-process the output of three different NWP models, the ECMWF IFS HRES, DWD's ICON-EU, and NCEP's GFS to obtain probabilities of hail and lightning occurrence. The results were evaluated as a part of the ESSL Testbeds in 2022. Forecast maps showing the calculated probabilities for the current and following day are calculated from the average of the three models and are made available on a website. The website interface allows overlaying reports from the European Severe Weather Database, which give an impression of the quality of the forecasts and help to identify existing weaknesses. Work is underway to include ensemble forecasts, and quantitative real-time verification, and to extend the forecast horizon as part of projects supported by the Austrian Science Fund and ECMWF. We show several AR-CHaMo lightning and large hail forecasts that resulted in no hail, large hail, and very large hail and discuss their performance.

In this study we investigate convective environments and their corresponding climatological features over Europe and the United States. For this purpose, National Lightning Detection Network (NLDN) and Arrival Time Difference long-range lightning detection network (ATDnet) data, ERA5 hybrid-sigma levels, and severe weather reports from the European Severe Weather Database (ESWD) and Storm Prediction Center (SPC) Storm Data were combined on a common grid of 0.25° and 1-h steps over the period 1979–2018. The severity of convective hazards increases with increasing instability and wind shear (WMAXSHEAR), but climatological aspects of these features differ over both domains. Environments over the United States are characterized by higher moisture, CAPE, CIN, wind shear, and midtropospheric lapse rates. Conversely, 0–3-km CAPE and low-level lapse rates are higher over Europe. From the climatological perspective severe thunderstorm environments (hours) are around 3–4 times more frequent over the United States with peaks across the Great Plains, Midwest, and Southeast. Over Europe severe environments are the most common over the south with local maxima in northern Italy. Despite having lower CAPE (tail distribution of 3000–4000 J kg−1 compared to 6000–8000 J kg−1 over the United States), thunderstorms over Europe have a higher probability for convective initiation given a favorable environment. Conversely, the lowest probability for initiation is observed over the Great Plains, but, once a thunderstorm develops, the probability that it will become severe is much higher compared to Europe. Prime conditions for severe thunderstorms over the United States are between April and June, typically from 1200 to 2200 central standard time (CST), while across Europe favorable environments are observed from June to August, usually between 1400 and 2100 UTC.

The tornado outbreak of 24–25 June 1967 was the most damaging in thehistory of western Europe, producing 7F2–F5 tornadoes,232 injuries, and 15fatalities across France, Belgium and the Netherlands. Following tornadoes inFrance on 24 June, the Royal Netherlands Meteorological Institute (KNMI)issued a tornado forecast for 25 June, which became the first ever—and firstverified—tornado forecast in Europe. Fifty-two years later, tornadoes are stillnot usually forecast by most European national meteorological services, and apan-European counterpart to the NOAA/NWS/Storm Prediction Center (SPC)does not exist to provide convective outlook guidance; yet, tornadoes remainan extant threat. This article asks, “What would a modern-day forecast of the24–25 June 1967 outbreak look like?” To answer this question, a model simulation of the event is used in three ways: 20-km grid-spacing output to produceaSPC-style convective outlook provided by the European Storm Forecast Experiment (ESTOFEX), 800-m grid-spacing output to analyze simulated reflectivity and surface winds in a nowcasting analog, and 800-m grid-spacingoutput to produce storm-total footprints of updraft-helicity maxima to compare to observed tornado tracks. The model simulates a large supercell on24 June and weaker embedded mesocyclones on 25 June forming along astationary front, allowing the ESTOFEX outlooks to correctly identify thethreat. Updraft-helicity footprints indicate multiple mesocyclones on bothdays within 40–50 km and 3–4 h of observed tornado tracks, demonstratingthe ability to hindcast a large European tornado outbreak.

By 31 December 2018, 39 537 quality-controlled reports of large hail had been submitted to the European Severe Weather Database (ESWD) by volunteers and ESSL. This dataset and the NatCatSERVICE Database of Munich RE jointly allowed us to study the hail hazard and its impacts across Europe over a period spanning multiple decades. We present a spatiotemporal climatology of the ESWD reports, diurnal and annual cycles of large hail, and indicate where and how they may be affected by reporting biases across Europe. We also discuss which hailstorms caused the most injuries and present the only case with hail fatalities in recent times. Additionally, we address our findings on the relation between hail size to the type of impacts that were reported. For instance, the probability of reported hail damage to roofs, windows, and vehicles strongly increases as hail size exceeds 5 cm, while damage to crops, trees, and greenhouses is typically reported with hailstone diameters of 2–3 cm. Injuries to humans are usually reported with hail 4 cm in diameter and larger, and number of injuries increases with increasing hail size. Using the NatCatSERVICE data, we studied economic losses associated with hailstorms occurring in central Europe and looked for long-term changes. The trend in hail losses and the annual number of hail loss days since 1990 to 2018 are compared to that of meteorological conditions favorable for large hail as identified by ESSL’s Additive Regression Convective Hazards model. Both hail loss days and favorable environments show an upward trend, in particular since 2000.

We show that the frequency of damaging convective weather events including lightning, hail and severe wind gusts will likely increase over Europe until the end of this century. We apply a set of additive regression models to an ensemble of 14 regional climate simulations and find that convective instability will increase as a result of rising humidity near the earth’s surface. Even though a slight decrease in thunderstorm occurrence in southwestern and southeastern Europe is projected, the probability of severe weather will increase throughout Europe, in particular for very large hail. It might be expected that Arctic amplification would lead to a weaker jet stream and, thus lower vertical wind shear, but we find instead that the jet changes little or even increases in situations with convective instability. To cope with the rising hazard probabilities, risk models will need to be adapted, while investment in sturdier structures, like the use of hardened glass in greenhouses or solar panels, will become more cost-effective. Furthermore, the need will grow to advise the public on loss prevention by taking precautionary measures as storms approach. Damaging weather events such as lightning, hail, and severe wind gusts are likely to become more common across Europe over the next several decades. Increased global temperatures, high low-level humidity levels and a changing polar jet stream are all associated with anthropogenic climate change; however, the implications of such projected changes in relation to severe weather events are still being explored. Here, Anja Radler and colleagues use numerical simulations of regional climate to predict the severity and frequency of convective storms in Europe under projected anthropogenic climate conditions. They find that the probability of severe weather and thunderstorms are expected to increase throughout Europe, and in particular, very large hail is likely to become more common. Therefore, public warnings and precautionary measures and should be actioned as storms approach.

The climatology of (severe) thunderstorm days is investigated on a pan-European scale for the period of 1979–2017. For this purpose, sounding measurements, surface observations, lightning data from ZEUS (a European-wide lightning detection system) and European Cooperation for Lightning Detection (EUCLID), ERA-Interim, and severe weather reports are compared and their respective strengths and weaknesses are discussed. The research focuses on the annual cycles in thunderstorm activity and their spatial variability. According to all datasets thunderstorms are the most frequent in the central Mediterranean, the Alps, the Balkan Peninsula, and the Carpathians. Proxies for severe thunderstorm environments show similar patterns, but severe weather reports instead have their highest frequency over central Europe. Annual peak thunderstorm activity is in July and August over northern, eastern, and central Europe, contrasting with peaks in May and June over western and southeastern Europe. The Mediterranean, driven by the warm waters, has predominant activity in the fall (western part) and winter (eastern part) while the nearby Iberian Peninsula and eastern Turkey have peaks in April and May. Trend analysis of the mean annual number of days with thunderstorms since 1979 indicates an increase over the Alps and central, southeastern, and eastern Europe with a decrease over the southwest. Multiannual changes refer also to changes in the pattern of the annual cycle. Comparison of different data sources revealed that although lightning data provide the most objective sampling of thunderstorm activity, short operating periods and areas devoid of sensors limit their utility. In contrast, reanalysis complements these disadvantages to provide a longer climatology, but is prone to errors related to modeling thunderstorm occurrence and the numerical simulation itself.

Convective hazards such as large hail, severe wind gusts, tornadoes, and heavy rainfall cause high economic damages, fatalities, and injuries across Europe. There are insufficient observations to determine whether trends in such local phenomena exist, however recent studies suggest that the conditions supporting such hazards have become more frequent across large parts of Europe in recent decades.We model the occurrence of these hazards using Generalized Additive Models (GAM) to investigate the existence of such long-term trends, and to enable objective probabilistic forecasts of these hazards. The models are trained with storm reports from the European Severe Weather Database (ESWD), lightning observations from the EUCLID network, and predictor parameters derived from the ERA5 reanalysis. Our work is based on the framework AR-CHaMo (Additive Regression Convective Hazard Models), previously developed at ESSL.Preliminary results include a spatial depiction of the environmental conditions giving rise to convective hazards at a higher resolution than was possible before. The skill of hail models developed using AR-CHaMo has been shown to be superior to composite parameters used by weather forecasters for the occurrence of large hail, such as the Supercell Composite Parameter (SCP) and the Significant Hail Parameter (SHP). Likewise, for tornadoes, more skillful models can be constructed using the AR-CHaMo framework than predictors such as the Significant Tornado Parameter (STP).The developed models have use both in climate studies and in medium-range severe weather forecasting. We will report on initial efforts to detect long term (1979-2019) trends of convective hazards and present how these models can be used to support severe weather forecasting using medium-range ensemble forecasts.

In the Czech Republic, tornadoes may reach an intensity of F2 and F3 on the Fujita scale, causing &ldquo, considerable&rdquo, to &ldquo, severe&rdquo, damage. Documentary evidence is sufficient to allow the creation of a chronology of such events, from the earliest recorded occurrence in 1119 CE (Common Era) to 2019, including a total of 108 proven or probable significant tornadoes on 90 separate days. Since only 11 significant tornadoes were documented before 1800, this basic analysis centers around the 1811&ndash, 2019 period, during which 97 tornadoes were recorded. Their frequency of occurrence was at its highest in the 1921&ndash, 1930, 1931&ndash, 1940, and 2001&ndash, 2010 decades. In terms of annual variations, they took place most frequently in July, June, and August (in order of frequency), while daily variation favored the afternoon and early evening hours. Conservative estimates of human casualties mention 8 fatalities and over 95 people injured. The most frequent types of damage were related to buildings, individual trees, and forests. Tornadoes of F2&ndash, F3 intensity were particularly associated with synoptic types characterized by airflow from the western quadrant together with troughs of low pressure extending or advancing over central Europe. Based on parameters calculated from the ERA-5 re-analysis for the period of 1979&ndash, 2018, most of these tornadoes occurred over a wide range of Convective Available Potential Energy (CAPE) values and moderate-to-strong vertical wind shear. The discussion herein also addresses uncertainties in tornado selection from documentary data, the broader context of Czech significant tornadoes, and the environmental conditions surrounding their origins.

The European Severe Storms Laboratory (ESSL) was founded in 2006 to advance the science and forecasting of severe convective storms in Europe. ESSL was a grassroots effort of individual scientists from various European countries. The purpose of this article is to describe the 10-yr history of ESSL and present a sampling of its successful activities. Specifically, ESSL developed and manages the only multinational database of severe weather reports in Europe: the European Severe Weather Database (ESWD). Despite efforts to eliminate biases, the ESWD still suffers from spatial inhomogeneities in data collection, which motivates ESSL’s research into modeling climatologies by combining ESWD data with reanalysis data. ESSL also established its ESSL Testbed to evaluate developmental forecast products and to provide training to forecasters. The testbed is organized in close collaboration with several of Europe’s national weather services. In addition, ESSL serves a central role among the European scientific and forecast communities for convective storms, specifically through its training activities and the series of European Conferences on Severe Storms. Finally, ESSL conducts wind and tornado damage assessments, highlighted by its recent survey of a violent tornado in northern Italy.

The occurrence of environmental conditions favorable for severe convective storms was assessed in an ensemble of 14 regional climate models covering Europe and the Mediterranean with a horizontal grid spacing of 0.44°. These conditions included the collocated presence of latent instability and strong deep-layer (surface to 500 hPa) wind shear, which is conducive to the severe and well-organized convective storms. The occurrence of precipitation in the models was used as a proxy for convective initiation. Two climate scenarios (RCP4.5 and RCP8.5) were investigated by comparing two future periods (2021–50 and 2071–2100) to a historical period (1971–2000) for each of these scenarios. The ensemble simulates a robust increase (change larger than twice the ensemble sample standard deviation) in the frequency of occurrence of unstable environments (lifted index ≤ −2) across central and south-central Europe in the RCP8.5 scenario in the late twenty-first century. This increase coincides with the increase in lower-tropospheric moisture. Smaller, less robust changes were found until midcentury in the RCP8.5 scenario and in the RCP4.5 scenario. Changes in the frequency of situations with strong (≥15 m s−1) deep-layer shear were found to be small and not robust, except across far northern Europe, where a decrease in shear is projected. By the end of the century, the simultaneous occurrence of latent instability, strong deep-layer shear, and model precipitation is simulated to increase by up to 100% across central and eastern Europe in the RCP8.5 and by 30%–50% in the RCP4.5 scenario. Until midcentury, increases in the 10%–25% range are forecast for most regions. A large intermodel variability is present in the ensemble and is primarily due to the uncertainties in the frequency of the occurrence of unstable environments.

During the Deep Convective Clouds and Chemistry (DC3) experiment in summer 2012, airborne measurements were performed in the anvil inflow/outflow of thunderstorms over the Central U.S. by three research aircraft. A general overview of Deutsches Zentrum fur Luft- und Raumfahrt (DLR)-Falcon in situ measurements (CO, O3, SO2, CH4, NO, NOx, and black carbon) is presented. In addition, a joint flight on 29 May 2012 in a convective line of isolated supercell storms over Oklahoma is described based on Falcon, National Science Foundation/National Center for Atmospheric Research Gulfstream-V (NSF/NCAR-GV), and NASA-DC8 trace species in situ and lidar measurements.

The environments of severe and nonsevere thunderstorms were analyzed using 16 421 proximity soundings from December 2007 to December 2013 taken at 32 central European stations. The soundings were assigned severity categories for the following hazards: hail, wind, tornado, and rain. For each of the soundings, parameters were calculated representing the instability, vertical wind profile, and moisture of the environment. The probability of the various hazards as a function of CAPE and 0–6-km bulk shear (DLS) is quite different for each of the hazards. Large hail is most likely for high CAPE and high DLS, a regime that also supports severe wind events. A second severe wind regime exists for low CAPE and very high DLS. These events are mostly cold season events. Storms with significant tornadoes occur with much higher DLS than storms with weak or no tornadoes, but with similar CAPE. The 0–1-km bulk shear (LLS) does not discriminate better than DLS between weak and significant tornadoes. Heavy rain events occur across a wide range of DLS, but with CAPE above the median for nonsevere thunderstorms and are most likely when both absolute humidity in the boundary layer and relative humidity in the low- to midtroposphere are high. LCL height does not discriminate well between the intensity categories of tornadoes, but higher LCL heights were associated with a higher probability of severe hail. Storm relative helicity shows similar results to DLS, but with more overlap among intensity categories.

Extremely rare events with high potential impact, like tornadoes, are of strong interest for climatology and risk assessment – especially though not only in the context of climate change – but difficult to tackle statistically. In order to widen the data basis especially for the scarcest high-end tornadoes, it is vital to study historical events. It could be speculated that a windstorm catastrophe that happened about 100 years ago is difficult to re-analyze, as the one that happened in Wiener Neustadt, Lower Austria, on 10 July 1916. The present paper demonstrates feasibility in the given case and proposes a working method for similar requirements. After presenting the methodology, a chronological description of the environmental atmospheric conditions and of the tornado itself is given, followed by results and new findings compared to a historical scientific study that was published soon after the event. Our analyses found complex thunderstorm activity in the study area and revealed an untypical tornado genesis – with only single parallels in US severe storms literature of the 20th century. For the urban area of Wiener Neustadt rich data sources allowed us to draw a detailed picture of damage tracks and hence wind strength in the tornado. Also the originally stated number of fatalities needs to be corrected upwards. In the outlook we postulate the requirement for an International Fujita Scale to rate tornadoes worldwide in a consistent way. Comparable damage indicators are required for this to be useable. We also stress the side-benefits of the given study for the field of civil protection, namely to serve as an exercise scenario and as a basis for public awareness rising.

This study focuses on 15 August 2010, when many severe convective storms occurred over parts of central and Eastern Europe, with some of these exhibiting various interesting cloud-top characteristics observed by weather satellites. The importance of the phenomena of cold-U and cold-ring features in the infrared brightness temperature enhanced imagery stems from the fact that storms exhibiting these features are very often accompanied by severe weather. Therefore, besides the general description of the atmospheric conditions in the area, we seek possible reasons for the different cloud-top appearance of these storms from the perspective of Meteosat Second Generation and polar-orbiting weather satellites. Two main issues are discussed in this paper - the unusually warm appearance of the cloud-top of the “Prague hailstorm” and the presence of cold-ring and cold-U shaped storms in close proximity to the warmer “Prague hailstorm”. Both of these issues prove that the storm top appearance is very sensitive to the upper tropospheric and lower stratospheric conditions, with the first one strongly reflecting variations in the tropopause height due to the presence of the jet-stream over the region. The second topic addresses the strength of the storm relative upper level winds as a major discriminator between the cold-U and cold-ring storm top categories. Due to the above mentioned facts, 15 August 2010 was selected as one of the prime cases of interest for the Convection Working Group.

On 25 June 2008, severe thunderstorms caused widespread damage and two fatalities in the Czech Republic. Significant features of the storms included numerous downbursts on a squall line that exhibited a bow echo reflectivity pattern, with sustained wind gusts over 32 m/s at several reporting stations. Moreover, a tornado and several downbursts of F2 intensity occurred within the convective system, collocated with the development of mesovortices within the larger scale bow echo. The extent of the event was sufficient to call it a derecho, as the windstorm had affected Eastern Germany, Southern Poland, Slovakia, Austria and Northern Hungary as well. Ahead of the squall line, several well-organized isolated cells occurred, exhibiting supercellular characteristics, both from a radar and visual perspective. These storms produced large hail and also isolated severe wind gusts. This paper deals mostly with the forecasting challenges that were experienced by the meteorologist on duty during the evolution of this convective scenario. The main challenge of the day was to identify the region that would be most affected by severe convection, especially as the numerical weather prediction failed to anticipate the extent and the progress of the derecho-producing mesoscale convective systems (MCSs). Convective storms developed in an environment conducive to severe thunderstorms, with strong wind shear confined mostly to the lower half of the troposphere. These developments also were strongly influenced by mesoscale factors, especially a mesolow centered over Austria and its trough stretching to Eastern Bohemia. The paper demonstrates how careful mesoscale analysis could prove useful in dealing with such convective situations. Remote-sensing methods are also shown to be useful in such situations, especially when they can offer sufficient lead time to issue a warning, which is not always the case.

Unique in situ measurements of CO, O3, SO2, CH4, NO, NOx, NOy, VOC, CN, and rBC were carried out with the German Deutsches Zentrum fur Luft- und Raumfahrt (DLR)-Falcon aircraft in the central U.S. thunderstorms during the Deep Convective Clouds and Chemistry experiment in summer 2012. Fresh and aged anvil outflow (9–12 km) from supercells, mesoscale convective systems, mesoscale convective complexes, and squall lines were probed over Oklahoma, Texas, Colorado, and Kansas. For three case studies (30 May and 8 and 12 June) a combination of trace species, radar, lightning, and satellite information, as well as model results, were used to analyze and design schematics of major trace gas transport pathways within and in the vicinity of the probed thunderstorms.