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Among severe weather events generated by deep convection, hail represents one of the most hazardous perils for agriculture, buildings, and properties. Moreover, in response to global warming, hailstorm frequency and severity are expected to increase in Europe. Therefore, a better understanding of hail hazards and risks is becoming increasingly crucial. However, major hurdles are posed by direct observations, by being heterogeneous, temporally limited, and scarce, as well as by numerical simulations, which generally lack sufficient detail to represent hailstorm dynamics properly. As a possible solution, hail likelihood can be indirectly assessed by combining multiple data sources, such as remote-sensing detections and ambient numerical predictors. The new high-resolution reanalysis SPHERA (High rEsolution ReAnalysis over Italy), developed at ARPAE, is considered to describe hail-favoring environments over Italy and nearby countries. SPHERA is dynamically downscaled from ERA5 and driven by the model COSMO at the convection-permitting resolution of 2.2 km. A set of predictors is selected and combined with Overshooting cloud Top (OT) satellite detections, constituting a reliable proxy for hail. OTs are automatically detected with a probabilistic algorithm (NASA) from geostationary Meteosat Second Generation SEVIRI infrared images. However, not all OTs are linked to hail. Hence, a filter based on their surrounding ambient conditions is developed to retain only OT occurrences with the potential for hailstorm formation. For this purpose, ESWD (European Severe Weather Database) crowdsourced hail reports are coupled with SPHERA proxies to characterize hailstorm environments. The analysis is performed over 2016-2020. Hence, the primary intent is to present the methodology rather than a comprehensive hail frequency characterization. More than a quarter of non-hailing OTs are removed, mainly over the Mediterranean sea and complex-topography areas. Maximum hail likelihood characterizes pre-Alpine regions and the northern Adriatic sea around 15 UTC in June-July, agreeing with previous European hail climatologies. The hit rate of ESWD reports with OTs exceeds 60%, i.e., ~20% more than the previous coupling of non-probabilistic OT detections with ERA-Interim over Europe. Different ambient characteristics are revealed by separating hit/miss reports for small/large hail events. Most hits present hailstones with diameters ≥3 cm, suggesting a better suitability of the method in case of severe hailstorms. Further, missed small-hail reports show peculiar environmental signatures characterized by lower instability, less wind shear, and colder atmospheric profiles. These results suggest a promising avenue to enhance hailstorm events identification. In addition, further extension of the analysis should shed more light on the climatology of hailstorms.

Hail is one of the most dangerous hazards for agriculture, infrastructures, and buildings of all severe-weather phenomena linked to deep moist convection. Due to global warming, the frequency and severity of hailstorms are expected to increase throughout Europe. It is, therefore, increasingly urgent to improve our understanding of hail hazard and risk. However, the intrinsic difficulties in systematically observing and simulating hail are still a major hurdle. While direct hail observations are heterogeneous, temporally-limited, and scarce, numerical simulations lack sufficient detail to represent the localized and rapidly-evolving hailstorm dynamics. A possible way to indirectly assess hail likelihood is through remote-sensing detections combined with numerical dynamical and thermodynamical characteristics of convective environments prone to hailstorm formation. Indeed, multiple data sources are necessary as, to date, more than a singular proxy is required to characterize hail. The new high-resolution reanalysis dataset SPHERA (High rEsolution ReAnalysis over Italy), developed at ARPAE, is considered for investigating hail-favoring environments over Italy and nearby countries. SPHERA is dynamically downscaled from ERA5, driven by the convection-permitting model COSMO (at 2.2 km grid spacing), providing meteorological data at hourly frequency. A set of parameters is extracted from SPHERA and combined with Overshooting cloud Top (OT) satellite detections, constituting a reliable proxy for hail. A probabilistic algorithm recently developed at NASA automatically detects OTs from geostationary Meteosat Second Generation SEVIRI infrared images. However, not all OTs are associated with hail formation in the storm. Hence, a filter is developed to retain only those occurrences linked to potential hailstorm formation based on the surrounding environmental conditions. To do so, ESWD (European Severe Weather Database) crowdsourced reports, representing the most reliable hail observational dataset in Europe, are coupled with SPHERA proxies to investigate convective environments nearby hailstorm events. The procedure is applied over five years (2016-2020). Hence, the primary purpose is to present the methodology rather than a sound hail frequency estimate. The resulting hailstorm characterization reveals a non-hailing OTs removal exceeding a quarter, mainly over the Mediterranean sea and complex-topography areas. The maximum hail likelihood is observed over pre-Alpine regions and the northern Adriatic sea around 15 UTC in June-July, in agreement with recent European hail climatologies. The validation against ESWD reports provides a hit rate exceeding 60%, roughly 20% more than the previous non-probabilistic OT detections coupling with ERA-Interim over Europe. Separating hit/miss reports and small/large hail reveals different characteristics of hail-prone environments. Most hit reports pertain to large hailstones (diameters ≥ 3 cm), suggesting an inclination of the method to perform better in cases of severe hail occurrences. Investigating the interrelations among SPHERA parameters quantifying the main mechanisms needed for hail formation (i.e., atmospheric instability, freezing level height, and storm organization), the leading role of thermal and thermodynamical factors over the kinetics of the storm emerges. These results suggest promising opportunities to enhance hail dynamics comprehension owing to the advancements in remote-sensing techniques and the development of convection-permitting numerical simulations. In addition, further extension of the analysis should shed more light on the climatology of hailstorms.

Forecasting and early warning systems are important investments to protect lives, properties and livelihood. While early warning systems are frequently used to predict the magnitude, location and timing of potentially damaging events, these systems rarely provide impact estimates, such as the expected amount and distribution of physical damage, human consequences, disruption of services or financial loss. Complementing early warning systems with impact forecasts has a two‐fold advantage: it would provide decision makers with richer information to take informed decisions about emergency measures, and focus the attention of different disciplines on a common target. This would allow capitalizing on synergies between different disciplines and boosting the development of multi‐hazard early warning systems. This review discusses the state‐of‐the‐art in impact forecasting for a wide range of natural hazards. We outline the added value of impact‐based warnings compared to hazard forecasting for the emergency phase, indicate challenges and pitfalls, and synthesize the review results across hazard types most relevant for Europe. Plain language summary Forecasting and early warning systems are important investments to protect lives, properties and livelihood. While such systems are frequently used to predict the magnitude, location and timing of potentially damaging events, they rarely provide impact estimates, such as the expected physical damage, human consequences, disruption of services or financial loss. Extending hazard forecast systems to include impact estimates promises many benefits for the emergency phase, for instance, for organising evacuations. We review and compare the state‐of‐the‐art of impact forcasting across a wide range of natural hazards, and outline opportunities and key challenges for research and development of impact forecasting.

Accurate estimates of hail risk to exposed assets, such as crops, infrastructure, and vehicles, are required for both insurance pricing and preventive measures. Here we present an event catalog to describe the hail hazard in South Africa guided by 14 years of geostationary satellite observations of convective storms. Overshooting cloud tops have been detected, grouped, and tracked to describe the spatiotemporal extent of potential hail events. It is found that hail events concentrate mainly in the southeast of the country, along the Highveld, and around the eastern slopes. Events are most frequent from mid-November through February and peak in the afternoon, between 13:00 and 17:00 UTC. Multivariate stochastic modeling of event properties yields an event catalog spanning 25 000 years, aiming to estimate, in combination with vulnerability and exposure data, hail risk for return periods of 200 years.

From 10 to 12 June 2019, severe thunderstorms affected large parts of Germany. Hail larger than golf ball size caused considerable damage, especially in the Munich area where losses amount to EUR 1 billion. This event thus ranks among the ten most expensive hail events in Europe in the last 40 years. Atmospheric blocking in combination with a moist, unstably stratified air mass provided an excellent setting for the development of severe, hail‐producing thunderstorms across the country. image, German Research Foundation http://dx.doi.org/10.13039/501100001659

Globally relevant and locally devastating, hailstorms produce significant societal impacts; despite this, our understanding of hailstorms and our ability to predict them is still limited.

Over three weeks in May and June 2018, an exceptionally large number of thunderstorms hit vast parts of western and central Europe, causing precipitation of up to 80 mm and several flash floods. During this time, the large-scale atmospheric circulation, which was characterized by a blocking situation over northern Europe, influenced atmospheric conditions relevant for thunderstorm development. Initially, the southwesterly flow on the western flank of the blocking anticyclone induced the advection of warm, moist, and unstably stratified air masses. Due to a low-pressure gradient associated with the blocking anticyclone, these air masses were trapped in western and central Europe, remained almost stationary and prevented a significant air mass exchange. In addition, the low-pressure gradient led to weak flow conditions in the mid-troposphere and thus to low vertical wind shear that prevented thunderstorms from developing into severe organized systems. Most of the storms formed as local-scale, relatively slow-moving single cells. However, due to the related weak propagation speed, several thunderstorms were able to produce torrential heavy rain that affected local-scale areas and triggered several flash floods. Atmospheric blocking also increased the upper-level cut-off low frequency on its upstream regions, which was up to 10 times higher than the climatological mean. Together with filaments of positive potential vorticity (PV), the cut-offs served as trigger mechanisms for a majority of the thunderstorms. For the 22-day study period, we found that more than 50 % of lightning strikes can be linked to a nearby cut-off low or PV filament. The exceptional persistence of low stability combined with weak wind speed in the mid-troposphere over three weeks has not been observed during the past 30 years.

A 10-yr geostationary (GEO) overshooting cloud-top (OT) detection database using Multifunction Transport Satellite (MTSAT) Japanese Advanced Meteorological Imager (JAMI) observations has been developed over the Australian region. GEO satellite imagers collect spatially and temporally detailed observations of deep convection, providing insight into the development and evolution of hazardous storms, particularly where surface observations of hazardous storms and deep convection are sparse and ground-based radar or lightning sensor networks are limited. Hazardous storms often produce one or more OTs that indicate the location of strong updrafts where weather hazards are typically concentrated, which can cause substantial impacts on the ground such as hail, damaging winds, tornadoes, and lightning and to aviation such as turbulence and in-flight icing. The 10-yr OT database produced using an automated OT detection algorithm is demonstrated for analysis of storm frequency, diurnally, spatially, and seasonally relative to known features such as the Australian monsoon, expected regions of hazardous storms along the southeastern coastal regions of southern Queensland and New South Wales, and the preferential extratropical cyclone track along the Indian Ocean and southern Australian coast. A filter based on atmospheric instability, deep-layer wind shear, and freezing level was used to identify OTs that could have produced hail. The filtered OT database is used to generate a hail frequency estimate that identifies a region extending from north of Brisbane to Sydney and the Goldfields–Esperance region of eastern Western Australia as the most hail-prone regions.

At the end of July 2013, a series of severe thunderstorms associated with heavy rainfall, severe wind gusts, and large hail affected parts of Germany. On 28 July 2013, two supercells formed almost simultaneously in southern Germany, from which only the more southerly cell produced hailstones up to 10 cm in diameter on a hailswath approximately 120 km long and 15–20 km wide. For the insurance industry, this event with losses of more than EUR 1 billion was one of the most expensive natural disasters that has ever occurred in Germany. This paper investigates the creation, temporal evolution, and effects of the most severe supercell that day by considering and merging radar and satellite data, eyewitness reports, insurance loss data, and numerical model studies. Observations of hail at ground level fit very well with a cold–ring-shaped structure in the cloud top brightness temperature observed by a geostationary satellite imager. Various simulations conducted with the convection-permitting COnsortium for Small-scale MOdeling (COSMO) revealed that the track of the hailstorm could be reproduced only when convection was triggered artificially by two warm bubbles that produced single cells that were precursors of the supercell. The model results suggested that the supercell developed near a pre-existing single cell through low-level flow convergence in an environment with moderate CAPE, but substantial wind shear and storm-relative helicity, both of which persisted for several hours in the area in which the supercell moved.

This article presents a hail frequency estimation based on the detection of cold overshooting cloud tops (OTs) from the Meteosat Second Generation (MSG) operational weather satellites, in combination with a hail-specific filter derived from the ERA-INTERIM reanalysis. This filter has been designed based on the atmospheric properties in the vicinity of hail reports registered in the European Severe Weather Database (ESWD). These include Convective Available Potential Energy (CAPE), 0–6-km bulk wind shear and freezing level height, evaluated at the nearest time step and interpolated from the reanalysis grid to the location of the hail report. Regions highly exposed to hail events include Northern Italy, followed by South-Eastern Austria and Eastern Spain. Pronounced hail frequency is also found in large parts of Eastern Europe, around the Alps, the Czech Republic, Southern Germany, Southern and Eastern France, and in the Iberic and Apennine mountain ranges.

Hagel verursacht regelmäßig immense Schäden. Daher ist es wichtig, Hagelrisiken besser abschätzen zu können.

Severe thunderstorms associated with large hail are among the most important perils in several European regions. Due to the local-scale extent of hail-affected areas and a lack of appropriate observing systems in most regions, hailstorms are not captured accurately and comprehensively, which makes statistical analysis of their frequency or climatology more difficult. Various studies have been conducted so far to describe and analyze the frequency of hailstorms or related impacts. These studies, however, refer to a wide range of spatial scales and consider different time periods, investigation methods, or hailstone diameters. This article will give a comprehensive overview and review of the present state of knowledge on hail hazard and hail frequency over recent decades up to centuries across Europe and is intended as a reference for future studies. We attempted to summarize and synthesize the various prevailing studies with the objective to identify regions that are most prone to hail hazard. Another focus is put on mechanisms that may explain spatial variability and inhomogeneities in hail frequency observed across various spatial scales.

Schwere Hagelstürme in Deutschland und Europa: Schwere Hagelstürme können innerhalb von nur wenigen Minuten erhebliche Schäden in Milliardenhöhe an Gebäuden, landwirtschaftlichen Kulturen oder Fahrzeugen verursachen. Hagel entsteht in Gewitterwolken aus der Interaktion verschiedener Prozesse auf unterschiedlichen Raum- und Zeitskalen. Diese reichen von wolkenmikrophysikalischen Vorgängen im Nanometerbereich über die Entstehung von Gewitterwolken im Bereich von einigen Kilometern bis hin zu geeigneten Großwetterlagen, die sich über rund 1000 km erstrecken. Die räumliche Ausdehnung der Hagelzüge und folglich auch die Schadenflächen sind dagegen sehr stark begrenzt. Aus diesem Grund liegen nur sehr wenige zuverlässige, qualitativ hochwertige Hagelbeobachtungen über längere Zeiträume vor. Um die lokale Hagelhäufigkeit, die beispielsweise für die Quantifizierung des Hagelrisikos von Versicherungen benötigt wird, zu bestimmen, werden Hagelsignale meist indirekt aus Datensätzen verschiedener Fernerkundungssysteme (z.B. Radare, Satelliten) abgeleitet. Diesbezügliche Untersuchungen zeigen eine sehr hohe räumliche Variabilität der Hagelereignisse, die sowohl von der großräumigen Klimatologie als auch von lokalen topografischen Eigenschaften bestimmt ist. Basierend auf verschiedenen, für die Entstehung von Hagel relevanten meteorologischen Größen aus Beobachtungs- oder Modelldaten zeigen alle Studien, dass die Wahrscheinlichkeit von Hagelstürmen über Deutschland und Mitteleuropa in den vergangenen Jahren vor allem durch die Zunahme der Konvektionsenergie in der Atmosphäre angestiegen ist und in der Zukunft wohl weiter ansteigen wird. Severe Hailstorms in Germany and Europe: Within only a few minutes, severe hailstorms can cause significant damage running into billions to buildings, agricultural crops or vehicles. Hail forms inside of thunderstorm clouds due to the interaction of different processes on different spatial and temporal scales. These range from cloud microphysics on the nanometer scale to the formation of storm clouds on the kilometer scale to large-scale weather conditions that extend to around 1000 kilometers. The spatial extent of the hailstreaks and, consequently, also the damage patterns are spatially very limited. For this reason, there is a significant lack of reliable, high-quality observational hail data over longer periods. In order to determine the local hail frequency, which is needed, for example, by the insurance industry to quantify the hail risk, hail signals are usually determined indirectly using datasets from remote sensing instruments such as radars or satellites. Related examinations reveal a very high spatial variability of the hail events, which is determined by both the large-scale climatology and local-scale topographic characteristics. Based on various meteorological parameters relevant to the formation of hailstorms gained from observations or model data, studies show that the probability of hailstorms over Germany and central Europe has increased over recent years, above all due to the increase in convective energy in the atmosphere, and likely will continue to increase over future decades.

Hailstorms represent one of the major sources of damage and insurance loss to residential, commercial, and agricultural assets in several parts of Central Europe. However, there is little knowledge of hail risk across Europe beyond local historical damage reports due to the relative rarity of severe hail events and the lack of uniform detection methods. Here we present a new stochastic catalog of hailstorms for Europe. It is based on satellite observations of overshooting cloud tops (OT) that indicate very strong convective updrafts and hail reports from the European Severe Weather Database (ESWD). Historic hail events are defined based on OT detections from satellite infrared brightness temperatures between 2004 and 2011 for the warm seasons (April–September). The satellite-based historical event properties are complemented by hailstone observations from ESWD to stochastically simulate more than 1 million individual events with an event footprint resolution of 10 km. The final hail event catalog presented in this paper is the first one with a spatial event distribution that is based on a single homogeneous observation source over Europe. Areas of high hail probability or hail risk are found over Central and Southern Europe, including mountainous regions such as the Alps or the Pyrenees. Another region of relatively high hail risk is present over central Eastern Europe.

The analyses specific threshold of lightning discharges density and thunderstorms days for different type of landscape and level of altitudes were determinate. For Central Europe from 9° W to 20° E and from 42° to 56° N (11° x 14° sectors) for April–September period from 2001 to 2014 were investigated. For Europe for the altitude range from 10 m below sea level (bsl) to 200 m above sea level (asl) the highest lightning discharge density is associated with the forest, shrub and wet, urban areas. For the altitude range 200–1000 m asl the highest lightning discharges density is associated with water (river, lakes), urban and forest areas. For the altitude range level from 1000 m asl to 2000 m asl the highest lightning discharges density is associated with the water, forest and grass types. A dense forest on the track of the flow of a moist air mass can promote the rise of air and the formation of convective clouds and lightning strokes. The effect of rives, channels and large lakes on moisture and development of thunderstorm clouds may account for impact on cloud-to-ground (CG) lightning activity. For three flat 3° x 5° areas with similar meteorological and synoptic conditions, increased CG lightning activity is possible if there is a difference in altitude between different types of landscapes. The altitude difference further contributes to the development of convective clouds producing lightning.