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

Viewed

Total article views: 596 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
491 81 24 596 17 37
  • HTML: 491
  • PDF: 81
  • XML: 24
  • Total: 596
  • BibTeX: 17
  • EndNote: 37
Views and downloads (calculated since 12 Feb 2025)
Cumulative views and downloads (calculated since 12 Feb 2025)

Viewed (geographical distribution)

Total article views: 596 (including HTML, PDF, and XML) Thereof 595 with geography defined and 1 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 30 Aug 2025
Download
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.
Share