Large hail has become a major loss driver in several regions around the globe. In 2023, for instance, severe convective storms, accompanied by large hail, caused economic losses of US$ 76 billion, which is about one-third of all damage by natural hazards. Despite the large damage, hail is still under-researched, mainly because of the lack of comprehensive, long-term observations. Pressing questions concern the impact of climate change on the intensity and frequency of hailstorms, the most effective methods for estimating hail hazard and risk, enhancements of hail detection and forecasting techniques, and optimal strategies for mitigating hail damage and hail risk.

Hail research endeavors have yielded important advancements in recent years, leveraging dedicated field campaigns, improved numerical weather prediction models, and the burgeoning domain of machine learning techniques. Despite these strides forward, our understanding of the underlying drivers of hailstorms, hail growth processes, regional probabilities of hail occurrence, and the associated risks remains incomplete. This knowledge gap underscores the importance of continued collaborative research efforts to enhance our ability to anticipate and mitigate the impacts of hailstorms.

The European Hail Workshop, held in March 2024 at Karlsruhe, Germany, aimed to foster the exchange of information on the current state of hail research and to discuss existing deficits and possible solutions in hail modeling and analysis to go a step beyond in understanding various processes related to hail. It also seeked to promote networking among scientists and experts in the fields of atmospheric research, weather services, insurance, economics, and agriculture.

This Research Topic summarizes our current understanding of hail formation, hail forecasting, and hail hazard and risk. Contributions are welcome for the following topics (sessions of the European hail workshop):
● Convection and hail in a changing climate (changes and trends for past and future periods)
● Hail damage and damage prevention (e.g., damage assessment, forensic analysis, hail-resistant materials)
● Hail climatology, risk, and loss (e.g., hail frequency or risk assessments, hail damage or risk models, insurance)
● Hail detection and forecasting (e.g., detection by remote sensing instruments, numerical weather prediction models on different time scales, nowcasting, hailpad instruments, crowdsourcing)
● Microphysics and dynamics of hailstorms (e.g., initial condition and cloud physics perturbations, wind tunnel experiments, model experiments, isotopic analysis, hail trajectories)
● Hail research and AI/ML (all aspects of hail modeling)
● Field campaigns (investigation of processes related to hail, ambient conditions, and hail growth, hailstone analysis)

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Frontiers in Environmental Science

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