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.
•We have reviewed more than 400 articles and sources on hail research in Europe.•Climatological hail information is discussed for each country.•Combined hail frequency maps illustrate the hail distribution in Europe.•Tables summarize hail frequency and major hail event information.•Challenges include better coordination of hail research activities.
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The 1st European Hail workshop took place in Bern in June 2014. The workshop was organized into five topical session i) Convection and hail in a changing climate, ii) Microphysics and dynamics of ...hailstorms, iii) Hail damage and hail damage prevention, iv) Local probabilities and long-term statistics of hail, and v) Nowcasting and forecasting of hail. This report summarizes the scientific contributions presented and the open scientific questions discussed at the workshop.
Conference Chair Prof. Mário S. Ming Kong, University Lisbon, Portugal Program Chair Dr. Andrea Deaconescu, Transilvania University of Brasov, Romania Dr. İlhan Asiltürk, Selcuk University, Turkey ...Dr. Serhat İkizoğlu, Istanbul Technical University, Turkey Dr. Osman Adiguzel, Firat University, Department of Physics, Turkey Dr. Wen. Z. Cui, Chongqing University, China Technical Committee Prof. João C. O. Matias, University of Aveiro, Portugal Dr. Emin Taner ELMAS, Forent Energy Co., İzmir / TURKEY Dr. Mehdi Jafari Vardanjani, University of Tehran, Iran Dr. Ahmed Maher Mohammed, University of Portsmouth, UK Dr. Wan Ahmad Yusmawiza Wan Yusoff, Hail University, Kingdom of Saudi Arabia Dr. Ergin Kilic, Suleyman Demirel University, Turkey Dr. Alireza Araee, University of Tehran, Iran Dr. Erik Prada, Slovak joint stock research company, Slovak Dr. Eng. Ivan Virgala, Technical University of Košice, Slovak Dr. Chien-Chih Wang, Ming Chi University of Technology, Taiwan Dr. Kuentai Chen, Ming Chi University of Technology, Taiwan Dr. K. K. Soundrapandian, Pdpm-Indian Institute Of Information Technology Design And Manufacturing, Jabalpur, India Dr. Tzu-An Chiang, National Taipei University of Business, Taiwan Dr. Mohd Omar bin Ab Kadir, Universiti Sains Malaysia (Usm), Malaysia Dr. Noor Aziah Serri, Universiti Sains Malaysia (Usm), Malaysia
This study analyzed the hail climatology across Croatia using data from a national network of 199 stations, which recorded a total of 8551 hail cases. The spatio-temporal analyses were made for: (i) ...several different periods, (ii) five additional 121 year long data series and (iii) investigation of the connection between weather types and occurrence of hail. Due to high complexity of Croatian territory (which includes the northern lowland, the central mountainous area and the long Adriatic coast with numerous islands and the Istrian peninsula), the spatial and temporal variability of hail as well as the limited number of hail data, three types of stations were defined. The types represent sets of stations with similar annual cycles of hail occurrence. Trend analysis using Mann–Kendall trend significance tests with Theil–Sen trend estimates was performed for three periods: from 1900 to 2020, from 1964 to 2019, and from 1995 to 2019. The first two periods showed a negative and significant trend in the number of hail days, while the most recent one, 25-year-long trend showed a change in sign toward a positive but not significant trend.
The northernmost parts of the coast (i.e., inner Istria) and lowland of Croatia had greater hail activity during summer. In contrast, along the southern and central Croatian coast, the highest hail activity was present in the colder part of the year. There was also a transitional area located in between, that recorded the most hail in spring and fall. Diurnal cycle of hail showed a shift in the daily maximum from morning to afternoon hours from the coast toward Croatian lowland.
The coastal part of Croatia generally recorded higher hail frequencies than the continental part. The climatology of hail duration revealed a log-normal distribution pattern, further suggesting that most hail cases last between 1 and 5 min with peek duration of about 4 min. The most dominant air masses (over 80% of time) responsible for hail come from the SW, W and NW directions, and 83% of hail is associated with cyclonic influence in the region.
•Negative trend of hail is observed on the 121 and 55 year long time series.•Three different patterns of annual and diurnal cycle were identified.•Hail duration in Croatia follows log-normal distribution.•In Croatia 60% of hail cases is related to southwesterly synoptic flow.
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Hail has long caused extensive damage and economic loss in places inhabited by humans. Climate change is expected to lead to different types of damage due to the geographic characteristics of each ...continent. Under changing environment, hail is becoming increasingly unstable and is causing damage that is difficult to repair, making it essential to study the occurrence of hail and hail-damage. Hail formation has been studied at the micro- and macrophysical scales as well as thermal and dynamical scales. Hail forms in various sizes, and the scale of damage varies with size. Hail precipitation occurs suddenly and is localized, making it is difficult to observe and predict. Nonetheless, techniques to measure and forecast hail precipitation are improving in accuracy. Hail-damage management and financial compensation systems are used to mitigate the severe economic losses caused by hail fallen in rural and urban areas. This review most comprehensively considers hail research, focusing on the mechanisms, observation and prediction methods, damage, social compensation systems for hail damage, and hail-disaster prevention, suggesting future study directions briefly.
Hailstones are a natural hazard that pose a significant threat to property and are responsible for significant economic losses each year in the United States. Detailed understanding of their ...characteristics is essential to mitigate their impact. Identifying the dynamic and physical factors contributing to hail formation and hailstone sizes is of great importance to weather and climate prediction and policymakers. In this study, we have analyzed the temporal and spatial variabilities of severe hail occurrences over the U.S. southern Great Plains (SGP) states from 2004 to 2016 using two hail datasets: hail reports from the Storm Prediction Center and the newly developed radar-retrieved maximum expected size of hail (MESH). It is found that severe and significant severe hail occurrences have a considerable year-to-year temporal variability in the SGP region. The interannual variabilities have a strong correspondence with sea surface temperature anomalies over the northern Gulf of Mexico and there is no outlier. The year 2016 is identified as an outlier for the correlations with both El Niño–Southern Oscillation (ENSO) and aerosol loading. The correlations with ENSO and aerosol loading are not statistically robust to inclusion of the outlier 2016. Statistical analysis without the outlier 2016 shows that 1) aerosols that may be mainly from northern Mexico have the largest correlation with hail interannual variability among the three factors and 2) meteorological covariation does not significantly contribute to the high correlation. These analyses warrant further investigations of aerosol impacts on hail occurrence.
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The growth trajectory of hailstones in clouds determines the ground intensity and spatial distribution of hailfall. A systematic study of hail trajectories can help improve the current scientific ...understanding of the mechanisms by which hail forms in semi-arid regions of China and, in doing so, improve the quality of hail forecasts and warnings and help to prevent and mitigate disasters. In this study, the WRFv3.7.1 model was employed to provide the background field to drive the hailstone trajectory model. Cluster analysis was then used to classify hail trajectories to investigate the characteristics of different types of hail trajectories and the microphysical characteristics of hail formation. The differences in hail trajectories might be mainly due to differences in the background flow fields and microphysical fields of hail clouds in different regions. Comparative analysis revealed that as the maximum particle size of ground hailfall increased, the maximum supercooled cloud water content and the maximum updraft velocity for the formation and growth of hailstone increased. The larger the size when the hailstone reaches its maximum height, the larger the ground hailstone formed. Overall, the formation and growth of hailstone are caused by the joint action of the dynamical flow field and cloud microphysical processes. The physical processes of hailstone growth and main growth regions differ for different types of hail trajectories. Therefore, different catalytic schemes should be adopted in artificial hail prevention operations for different hail clouds and trajectories due to differences in hail formation processes and ground hailfall characteristics.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Staring at a hailstone helps to determine various characteristics, such as shape or size. However, from the physics point of view, one of the most important characteristic is the type of growth. Each ...of the stone’ elements (nucleus, lobes, rings) is conductive to explaining the environmental behaviour of its formation and development stages. The thermodynamic variables derived from the upper-air soundings or the numerical weather prediction simulations can help us understand the differences between the different growth modes. In this way, the hail type has been analyzed according to its shape and size. The study has comprised 151 hailstorms that occurred in Catalonia (NE of the Iberian Peninsula) between 2017 and 2020. We have characterized the events according to different properties. The size of the stones (small, large and, huge), the shape (embryo, spherical, and irregular), and, the season of occurrence (spring, summer, and autumn) are the selected characterizing elements. Maximum vertical updraft velocity, vertical wind shear, and precipitable water content are the variables that explain better the behaviour of each category.
•Knowing the hail shape in the future hours facilitates improving the nowcasting of hailstone properties.•The research has consisted of combining ground-based observations with simulated thermodynamic atmospheric profiles.•The analysis has been made dividing the hail dataset into different categories, based on season, size, height, and shape.•Shape and size present a good correlation, but no significant trend was found regarding to the stone’s height collection.•Combining thermodynamic parameters (max. estimated vertical velocity and precipitable water content), improves nowcasting.
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Serbia is located in the mid‐latitudes of the Northern Hemisphere and is exposed to frequent hailfall. Consequently, a hail suppression system was gradually developed during the last 54 years. In ...this study, data from densely distributed hail suppression stations were used to better understand the hail characteristics. Two data subsets are differentiated: the first from the territory of Serbia, excluding the northern province of Vojvodina, during 1981–2015 (P1) and the second from the entire territory of Serbia during 2002–2015 (P2). The distribution of hail size shifted to smaller diameters in P2 compared to P1. The hailfall lasted less than 5 min in about 75% of events while the duration was greater than or equal to 10 min in only 8%. The influence of Serbia's complex orography on hailfall is reflected in the greater average annual number of days with hailfall in mountainous areas, with a maximum mean value of 1.2 in the southwestern part of Serbia, while the maximum number was 2.7. Hail and small hail occurred mainly in the afternoon and evening, with 92.24% of cases being observed from 12:00 to 21:00 local time (UTC + 1). A positive monotonic trend in the annual number of days with hailfall was observed. In both subsets, there was no statistically significant trend in hail frequency. The average seasonal duration of hail and small hail falls showed a decreasing trend in P1. Results showed that the first occurrence of hail falls did not appear earlier in the season.
Evaluation of the hail characteristics, climatology, and trends in Serbia based on large set of data covering warm season during 35 years showed no trend in number of hail days nor in hail/small hail frequency. A monotonic increasing trend is detected at 6.7% significance level for the smallest hailstones (smaller than corn size). Larger hailstones had no trend. In the analysed period (1981–2015), the first precipitation of the hail and small hail did not occur earlier in the season. The duration of the hailfalls decreased in the period. We detected the regions most vulnerable to hail, which can help to optimize the operative hail suppression system.
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