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Variability of microphysical characteristics in the “21·7” Henan extremely heavy rainfall event 被引量:11

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摘要 In this study, significant rainfall microphysical variability is revealed for the extremely heavy rainfall event over Henan Province in July 2021(the “21·7” Henan EHR event) using a dense network of disdrometers and two polarimetric radars.The broad distributions of specific drop size distribution(DSD) parameters are identified in heavy rainfall from the disdrometer observations, indicating obvious microphysical variability on the surface. A K-means clustering algorithm is adopted to objectively classify the disdrometer datasets into separate groups, and distinct DSD characteristics are found among these heavy rainfall groups. Combined with the supporting microphysical structures obtained through radar observations, comprehensive microphysical features of the DSD groups are derived. An extreme rainfall group is dominantly formed in the deep convection over the plain regions, where the high number of concentrations and large mean sizes of surface raindrops are underpinned by both active ice-phase processes and efficient warm-rain collision-coalescence processes in the vertical direction. Convection located near orographic regions is characterized by restricted ice-phase processes and high coalescence efficiency of liquid hydrometeors, causing the dominant DSD group to comprise negligible large raindrops. Multiple DSD groups can coexist within certain precipitation episodes at the disdrometer stations, indicating the potential microphysical variability during the passage of convective system on the plain regions.
出处 《Science China Earth Sciences》 SCIE EI CAS CSCD 2022年第10期1861-1878,共18页 中国科学(地球科学英文版)
基金 jointly supported by the National Natural Science Foundation of China (Grant Nos. 42025501, 42005009, 41875053, U2142203) the National Key Research and Development Program of China (Grant No. 2017YFC1501703) the Basic Research Fund of CAMS (Grant No. 2021Z003) the Open Research Program of the State Key Laboratory of Severe Weather (Grant No. 2020LASW-A01)。
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