Articles | Volume 19, issue 16
https://doi.org/10.5194/amt-19-5525-2026
https://doi.org/10.5194/amt-19-5525-2026
Research article
 | 
27 Aug 2026
Research article |  | 27 Aug 2026

HailCam: an automated imaging system for real-time measurement of hail size distributions and fall rates

Baolei Lyu, Hui Wang, Tianlei Gao, Zhanfu Yin, Xiaofeng Lou, Yugang Duan, Yihang Huang, and Zhiqiang Zhao

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Cited articles

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Barras, H., Hering, A., Martynov, A., Noti, P.-A., Germann, U., and Martius, O.: Experiences with > 50 000 Crowdsourced Hail Reports in Switzerland, Bull. Am. Meteorol. Soc., 100, 1429–1440, https://doi.org/10.1175/BAMS-D-18-0090.1, 2019. 
Bhandari, S., Vajpayee, G., da Silva, L. L., Hinterstein, M., Franchin, G., and Colombo, P.: A review on additive manufacturing of piezoelectric ceramics: From feedstock development to properties of sintered parts, Mater. Sci. Eng.- R. Rep., 162, 100877, https://doi.org/10.1016/j.mser.2024.100877, 2025. 
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Cheng, L. and English, M.: A Relationship Between Hailstone Concentration and Size, J. Atmos. Sci., 40, 204–213, 1983. 
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Short summary
Hailstorms cause significant damage, yet measuring hail accurately remains difficult because current sensors have small sampling area and often confuse hail with rain. To solve this, we developed HailCam, a smart camera system, that counts and measures hail size every minute. Tests of the system prove that it is highly accurate and better than existing tools at ignoring rain. This technology is crucial to improve forecasts, warn communities earlier, and help scientists better understand storms.
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