Abstract
Hailstorms rank among the most destructive extreme weather events globally, causing substantial property damage. While limited case studies suggest that cities may exacerbate hailstorms, the underlying mechanisms remain uncertain because of the complex physical processes. Here, we examine a hailstorm formation pathway associated with convective merging process using long-term observational data and high-resolution numerical simulations. This pathway helps explain the rising frequency of hailstorms across two distinct climate regimes, North America and East Asia. We find that merger hailstorms (MHs) occur approximately twice as often and tend to be more intense than non-merging normal hailstorms (NHs), which have been traditionally considered as the primary hailstorm formation mode. Favorable environmental conditions support the initiation of multiple convective cells and their subsequent merging, a tendency that may be enhanced by anthropogenic heat in large cities. Projections from a machine-learning model indicate an increase in the MH frequency and a decrease in NH frequency in North America. Together, these findings highlight an underexplored hailstorm formation pathway and suggest that climate change and human activities may play a role in shaping future hailstorm characteristics and the associated risks.
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Data availability
The mosaic radar data in North America are available at https://mesonet.agron.iastate.edu/docs/nexrad_mosaic/. The surface hail records in North America are available at https://mesonet.agron.iastate.edu/cow/. The mosaic radar data in East Asia are available at https://doi.org/10.5281/zenodo.18797046. The radar observations and retrieved wind fields for the case study are available at https://doi.org/10.5281/zenodo.18797857. The MODIS data are available at https://ladsweb.modaps.eosdis.nasa.gov/search/. The ERA5-Land and ERA5 data are available at https://cds.climate.copernicus.eu/datasets. The CMIP6 data are available at https://pcmdi.llnl.gov/CMIP6/. Source data are provided with this paper.
Code availability
The program for hailstorm tracking algorithm, convective initiation algorithm, cell merger algorithm is provided at https://doi.org/10.5281/zenodo.16036802, along with data for reference. The CatBoost model and training data are provided at https://doi.org/10.5281/zenodo.16036963. The hail trajectory model and related data are available at https://doi.org/10.5281/zenodo.18797498.
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Acknowledgements
This work is primarily supported by the programs of the National Natural Science Foundation of China (Grants 42025501, K.Z.; 42305006, A.Z.; 42230607, K.Z.), the Natural Science Foundation of Jiangsu Province (Grant BK20230800, A.Z.), the Postdoctoral Fellowship Program of China Postdoctoral Science Foundation (Grant GZC20231094, A.Z.), Fundamental and Interdisciplinary Disciplines Breakthrough Plan of the Ministry of Education of China (Grant JYB2025XDXM907, G.Y.), the Open Grants of the State Key Laboratory of Severe Weather (Grant 2024LASW-A02, A.Z.). The numerical simulations are run on the computing facilities in the High-Performance Computing Center (HPCC) of Nanjing University. We sincerely acknowledge the China Meteorological Administration for providing the meteorological data used in this study.
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K.Z. and A.Z. initiated the concept and developed the overall research framework. A.Z. performed the data processing and the analyses, generated figures, and prepared the initial manuscript draft. K.Z., J.C., and S.W. contributed to scientific interpretations and revisions.
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Zhou, A., Zhao, K., Chan, J.C.L. et al. Increased hailstorms in cities through cell merger mechanism across North America and East Asia. Nat Commun (2026). https://doi.org/10.1038/s41467-026-70826-0
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DOI: https://doi.org/10.1038/s41467-026-70826-0
