Articles | Volume 24, issue 4
https://doi.org/10.5194/nhess-24-1079-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-24-1079-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Apr 2024
Research article |
| 03 Apr 2024
| 03 Apr 2024
Climatology of large hail in Europe: characteristics of the European Severe Weather Database
Faye Hulton
CORRESPONDING AUTHOR
Centre for Atmospheric Science, Department of Earth and Environmental Sciences, University of Manchester, Manchester, M13 9PL, UK
now at: MetDesk, Aylesbury, HP22 6NJ, UK
David M. Schultz
Centre for Atmospheric Science, Department of Earth and Environmental Sciences, University of Manchester, Manchester, M13 9PL, UK
Centre for Crisis Studies and Mitigation, University of Manchester, Manchester, M13 9PL, UK
Viewed
Total article views: 8,656 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 15 Feb 2023)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 5,885 | 2,378 | 393 | 8,656 | 371 | 469 |
- HTML: 5,885
- PDF: 2,378
- XML: 393
- Total: 8,656
- BibTeX: 371
- EndNote: 469
Total article views: 4,854 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 03 Apr 2024)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 3,610 | 966 | 278 | 4,854 | 254 | 293 |
- HTML: 3,610
- PDF: 966
- XML: 278
- Total: 4,854
- BibTeX: 254
- EndNote: 293
Total article views: 3,802 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 15 Feb 2023)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,275 | 1,412 | 115 | 3,802 | 117 | 176 |
- HTML: 2,275
- PDF: 1,412
- XML: 115
- Total: 3,802
- BibTeX: 117
- EndNote: 176
Viewed (geographical distribution)
Total article views: 8,656 (including HTML, PDF, and XML)
Thereof 8,343 with geography defined
and 313 with unknown origin.
Total article views: 4,854 (including HTML, PDF, and XML)
Thereof 4,576 with geography defined
and 278 with unknown origin.
Total article views: 3,802 (including HTML, PDF, and XML)
Thereof 3,767 with geography defined
and 35 with unknown origin.
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
1
Cited
18 citations as recorded by crossref.
- Hailstorms That Produce Very Large Hail: What Are the Differences with Other Thunderstorms? T. Rigo https://doi.org/10.3390/atmos17050436
- Lightning jump as precursor of very large hail occurrence: first evidence in the Italian territory F. Vermi et al. https://doi.org/10.1007/s42865-025-00104-2
- Experimental Study on the Effect of Wind Speed on Hail Impacts Y. Dai et al. https://doi.org/10.3390/app15095120
- Intercomparison of Machine Learning and Ingredient-Based Approaches for Identifying Hail-Prone Weather Conditions over Russia P. Blinov et al. https://doi.org/10.3103/S002713492570287X
- From manual classification to transformer-based language models: assessing the quality and consistency of historical convective event records F. Schätz & R. Glaser https://doi.org/10.5194/cp-22-1833-2026
- Extreme weather risks for European agriculture (1981–2020): A quantitative review using the E3CI L. Lakatos & K. Csabai https://doi.org/10.1016/j.scitotenv.2025.180641
- Lightning Activity Accompanying Hail Events in Russia in 2016–2024 K. Pustovalov et al. https://doi.org/10.1007/s00024-025-03878-w
- Future changes in severe hail across Europe, including regional emergence of warm-type thunderstorms A. Kahraman et al. https://doi.org/10.1038/s41467-025-62780-0
- Experimental and Numerical Analysis of Hail Impact on Sheet Molding Compounds A. Kapshammer et al. https://doi.org/10.4028/p-i6QjdU
- Performance assessment of drone-based photogrammetry coupled with machine-learning for the estimation of hail size distributions on the ground J. Portmann et al. https://doi.org/10.3389/fenvs.2025.1602917
- Do urban areas intensify hail? S. Pryor et al. https://doi.org/10.1088/1748-9326/ae6880
- Hailstorm prediction and loss assessment using high-resolution hazard and claims data M. Fonseca-Cerda et al. https://doi.org/10.1016/j.atmosres.2025.108501
- A climatology of hail in Europe (2014–2024) based on GPM-DPR sensor data L. Rivero-Ordaz et al. https://doi.org/10.1016/j.atmosres.2026.108965
- Agroforestry protects arable crops from climate shock during critical early-season phenological stages C. Tosh et al. https://doi.org/10.1007/s13593-026-01129-3
- Evaluation of the WRF-HAILCAST Modelling System to Forecast Hail Episodes During August 2022 over Catalonia (Spain) R. Arasa-Agudo et al. https://doi.org/10.3390/hydrometeorology1020008
- High-resolution atmospheric data cubes from the WegenerNet 3D Open-Air Laboratory for Climate Change Research A. Kvas et al. https://doi.org/10.5194/essd-18-1165-2026
- Insights into thunderstorm characteristics from geostationary lightning jump and dive observations F. Erdmann & D. Poelman https://doi.org/10.5194/nhess-25-1751-2025
- Divergent European hail projections from machine learning and physically based models under global warming M. Chericoni et al. https://doi.org/10.1038/s44304-026-00218-3
18 citations as recorded by crossref.
- Hailstorms That Produce Very Large Hail: What Are the Differences with Other Thunderstorms? T. Rigo https://doi.org/10.3390/atmos17050436
- Lightning jump as precursor of very large hail occurrence: first evidence in the Italian territory F. Vermi et al. https://doi.org/10.1007/s42865-025-00104-2
- Experimental Study on the Effect of Wind Speed on Hail Impacts Y. Dai et al. https://doi.org/10.3390/app15095120
- Intercomparison of Machine Learning and Ingredient-Based Approaches for Identifying Hail-Prone Weather Conditions over Russia P. Blinov et al. https://doi.org/10.3103/S002713492570287X
- From manual classification to transformer-based language models: assessing the quality and consistency of historical convective event records F. Schätz & R. Glaser https://doi.org/10.5194/cp-22-1833-2026
- Extreme weather risks for European agriculture (1981–2020): A quantitative review using the E3CI L. Lakatos & K. Csabai https://doi.org/10.1016/j.scitotenv.2025.180641
- Lightning Activity Accompanying Hail Events in Russia in 2016–2024 K. Pustovalov et al. https://doi.org/10.1007/s00024-025-03878-w
- Future changes in severe hail across Europe, including regional emergence of warm-type thunderstorms A. Kahraman et al. https://doi.org/10.1038/s41467-025-62780-0
- Experimental and Numerical Analysis of Hail Impact on Sheet Molding Compounds A. Kapshammer et al. https://doi.org/10.4028/p-i6QjdU
- Performance assessment of drone-based photogrammetry coupled with machine-learning for the estimation of hail size distributions on the ground J. Portmann et al. https://doi.org/10.3389/fenvs.2025.1602917
- Do urban areas intensify hail? S. Pryor et al. https://doi.org/10.1088/1748-9326/ae6880
- Hailstorm prediction and loss assessment using high-resolution hazard and claims data M. Fonseca-Cerda et al. https://doi.org/10.1016/j.atmosres.2025.108501
- A climatology of hail in Europe (2014–2024) based on GPM-DPR sensor data L. Rivero-Ordaz et al. https://doi.org/10.1016/j.atmosres.2026.108965
- Agroforestry protects arable crops from climate shock during critical early-season phenological stages C. Tosh et al. https://doi.org/10.1007/s13593-026-01129-3
- Evaluation of the WRF-HAILCAST Modelling System to Forecast Hail Episodes During August 2022 over Catalonia (Spain) R. Arasa-Agudo et al. https://doi.org/10.3390/hydrometeorology1020008
- High-resolution atmospheric data cubes from the WegenerNet 3D Open-Air Laboratory for Climate Change Research A. Kvas et al. https://doi.org/10.5194/essd-18-1165-2026
- Insights into thunderstorm characteristics from geostationary lightning jump and dive observations F. Erdmann & D. Poelman https://doi.org/10.5194/nhess-25-1751-2025
- Divergent European hail projections from machine learning and physically based models under global warming M. Chericoni et al. https://doi.org/10.1038/s44304-026-00218-3
Saved (final revised paper)
Latest update: 29 Oct 2026
Short summary
Large hail devastates crops and property and can injure and kill people and livestock. Hail reports are collected by individual countries, so understanding where and when large hail occurs across Europe is an incomplete undertaking. We use the European Severe Weather Database to evaluate the quality of reports by year and by country since 2000. Despite its short record, the dataset appears to represent aspects of European large-hail climatology reliably.
Large hail devastates crops and property and can injure and kill people and livestock. Hail...
Altmetrics
Final-revised paper
Preprint