Articles | Volume 18, issue 16
https://doi.org/10.5194/gmd-18-5291-2025
https://doi.org/10.5194/gmd-18-5291-2025
Model evaluation paper
 | 
26 Aug 2025
Model evaluation paper |  | 26 Aug 2025

Mitigating hail overforecasting in the two-moment Milbrandt–Yau microphysics scheme (v2.25.2_beta_04) in WRF (v4.5.1) by incorporating the graupel spongy wet growth process (MY2_GSWG v1.0)

Shaofeng Hua, Gang Chen, Baojun Chen, Mingshan Li, and Xin Xu

Data sets

data and code for my manuscript S. Hua https://doi.org/10.5281/zenodo.13778097

Model code and software

data and code for my manuscript S. Hua https://doi.org/10.5281/zenodo.13778097

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Short summary
Hail forecasting using numerical models remains a challenge. In this study, we found that the commonly used graupel-to-hail conversion parameterization method led to hail overforecasting in heavy rainfall cases where no hail was observed. By incorporating the spongy wet growth process, we successfully mitigated hail overforecasting. The modified scheme also produced hail in real hail events. This research contributes to a better understanding of hail formation.
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