Raindrop Size Distributions in the Zhengzhou Extreme Rainfall Event on 20 July 2021: Temporal–Spatial Variability and Implications for Radar QPE

• Published in: Journal of Meteorological Research Vol. 38; no. 3; pp. 489 - 503
• Main Authors: Cui, Liman, Li, Haoran, Su, Aifang, Zhang, Yang, Lyu, Xiaona, Xi, Le, Zhang, Yuanmeng
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2024
• Subjects: Atmospheric Protection/Air Quality Control/Air Pollution; Atmospheric Sciences; Earth and Environmental Science; Earth Sciences; Geophysics and Environmental Physics; Meteorology; Original Paper; radar; extreme rainfall; quantitative precipitation estimation (QPE); raindrop size distribution
• ISSN: 2095-6037; 2198-0934
• DOI: 10.1007/s13351-024-3119-9

In this study, a regional Parsivel OTT disdrometer network covering urban Zhengzhou and adjacent areas is employed to investigate the temporal–spatial variability of raindrop size distributions (DSDs) in the Zhengzhou extreme rainfall event on 20 July 2021. The rain rates observed by disdrometers and rain gauges from six operational sites are in good agreement, despite significant site-to-site variations of 24-h accumulated rainfall ranging from 198.3 to 624.1 mm. The Parsivel OTT observations show prominent temporal–spatial variations of DSDs, and the most drastic change was registered at Zhengzhou Station where the record-breaking hourly rainfall of 201.9 mm over 1600–1700 LST (local standard time) was reported. This hourly rainfall is characterized by fairly high concentrations of large raindrops, and the mass-weighted raindrop diameter generally increases with the rain rate before reaching the equilibrium state of DSDs with the rain rate of about 50 mm h −1 . Besides, polarimetric radar observations show the highest differential phase shift ( K dp ) and differential reflectivity ( Z dr ) near surface over Zhengzhou Station from 1600 to 1700 LST. In light of the remarkable temporal–spatial variability of DSDs, a reflectivity-grouped fitting approach is proposed to optimize the reflectivity–rain rate ( Z–R ) parameterization for radar quantitative precipitation estimation (QPE), and the rain gauge measurements are used for validation. The results show an increase of mean bias ratio from 0.57 to 0.79 and a decrease of root-mean-square error from 23.69 to 18.36 for the rainfall intensity above 20.0 mm h −1 , as compared with the fixed Z–R parameterization. This study reveals the drastic temporal–spatial variations of rain microphysics during the Zhengzhou extreme rainfall event and warrants the promise of using reflectivity-grouped fitting Z–R relationships for radar QPE of such events.