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

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

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In this study,a regional Parsivel OTT disdrometer network covering urban Zhengzhou and adjacent areas is em-ployed 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 1500-1600 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(Kdp)and differential reflectivity(Zdr)near surface over Zhengzhou Station from 1500 to 1600 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 estima-tion(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 vari-ations of rain microphysics during the Zhengzhou extreme rainfall event and warrants the promise of using reflectiv-ity-grouped fitting Z-R relationships for radar QPE of such events.

extreme rainfallraindrop size distributionradarquantitative precipitation estimation(QPE)

Liman CUI、Haoran LI、Aifang SU、Yang ZHANG、Xiaona LYU、Le XI、Yuanmeng ZHANG

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Henan Key Laboratory of Agrometeorological Support and Applied Technique,China Meteorological Administration,Zhengzhou 450003

State Key Laboratory of Severe Weather,Chinese Academy of Meteorological Sciences,China Meteorological Administration,Beijing 100081

Henan Meteorological Observatory,Zhengzhou 450003

National Key Research and Development Program of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaScience and Technology Innovation Project for Ecosystem Construction of Zhengzhou Supercomputing Center in Henan ProvinceMeteorological Joint Project of Henan Provincial Science and TechnologyMeteorological Joint Project of Henan Provincial Science and TechnologyBasic Research Fund of Chinese Academy of Meteorological SciencesBasic Research Fund of Chinese Academy of Meteorological Sciences

2022YFC300390142305087421051412014002108002221038100942321038100914514902023Z008

2024

气象学报(英文版)
中国气象学会

气象学报(英文版)

CSTPCD
影响因子:0.57
ISSN:0894-0525
年,卷(期):2024.38(3)