Advances and challenges in hail research: report from the 4th European hail workshop 2024

Hailstorms cause substantial damage to buildings, crops, vehicles, and infrastructure in many regions worldwide. Despite notable progress in recent years, hail remains insufficiently understood and poorly represented in numerical weather prediction models and risk assessments. The 4th European Hail Workshop (2024) showcased advances in detection, forecasting, climatology, and impact assessment of hail, while highlighting key challenges that remain. Progress in remote sensing, weather prediction, and seamless forecasting has improved early detection of hail events, extended forecast lead times, and enhanced warning capabilities. Field campaigns and laboratory experiments are yielding new insights into hailstone characteristics, hail formation processes, and impacts. Studies of storm dynamics and microphysics emphasized the complex interactions of processes involved across a wide range of temporal and spatial scales. Finally, artificial intelligence and machine learning are opening new avenues for hail detection, prediction, and risk modeling, marking a shift toward more integrated and innovative approaches in hail research.

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Publication Details

Journal
Frontiers in Environmental Science
Published
2025-11-14
DOI
https://doi.org/10.3389/fenvs.2025.1699216
Citations
1
Primary Topic
Meteorological Phenomena and Simulations
Type
article
Field-Weighted Citation Impact
1.30

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article

Advances and challenges in hail research: report from the 4th European hail workshop 2024

Katharina Schröer, Susanna Mohr, Olivia Martius, Michael Kunz et al.
1 citations
Frontiers in Environmental Science
Meteorological Phenomena and Simulations
1.30
article

Advances and challenges in hail research: report from the 4th European hail workshop 2024

Katharina Schröer, Susanna Mohr, Olivia Martius, Michael Kunz, Alessandro Hering
article en
1 citations

Abstract

Hailstorms cause substantial damage to buildings, crops, vehicles, and infrastructure in many regions worldwide. Despite notable progress in recent years, hail remains insufficiently understood and poorly represented in numerical weather prediction models and risk assessments. The 4th European Hail Workshop (2024) showcased advances in detection, forecasting, climatology, and impact assessment of hail, while highlighting key challenges that remain. Progress in remote sensing, weather prediction, and seamless forecasting has improved early detection of hail events, extended forecast lead times, and enhanced warning capabilities. Field campaigns and laboratory experiments are yielding new insights into hailstone characteristics, hail formation processes, and impacts. Studies of storm dynamics and microphysics emphasized the complex interactions of processes involved across a wide range of temporal and spatial scales. Finally, artificial intelligence and machine learning are opening new avenues for hail detection, prediction, and risk modeling, marking a shift toward more integrated and innovative approaches in hail research.

Frontiers in Environmental ScienceVol. 13
Karlsruhe Institute of Technology (DE), University of Bern (CH), Oeschger Centre for Climate Change Research (CH), Federal Office of Meteorology and Climatology MeteoSwiss (CH), University of Freiburg (DE)
National Science Foundation, Joachim Herz Stiftung, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Openalex Percentile: Top 16%
Meteorological Phenomena and Simulations
1.30
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Advances and challenges in hail research: report from the 4th European hail workshop 2024 — Katharina Schröer, Susanna Mohr, et al. · Frontiers in Environmental Science (2025) | TGRS Research Map | TGRS