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Moisture Origins and Transport Processes for the 2020 Yangtze River Valley Record-Breaking Mei-yu Rainfall 被引量:6

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摘要 The summer of 2020 recorded a record-breaking flood due to excessive mei-yu rain falling over the Yangtze River Valley(YRV).Using the Lagrangian model FLEXPART,this paper investigates moisture sources and transport processes behind this extreme event.Based on climate data from 1979 to 2019,the air-particle(an infinitesimally small air parcel)trajectories reaching the YRV show sectors that correspond to five main moisture sources:the Indian monsoon region(IND,27.5%of the total rainfall),the local evaporation(27.4%),the Western Pacific Ocean(WPO,21.3%),the Eurasian continent(8.5%)and Northeast Asia(4.4%).In the 2020 mei-yu season,moisture from all source regions was above normal except that from Northeast Asia.A record-breaking moisture source from the IND and WPO dominated this extreme mei-yu flood in 2020,which was 1.5 and 1.6 times greater than the climate mean,respectively.This study reveals a significant relationship between the moisture source with three moisture transport processes,i.e.,trajectory density,moisture content,and moisture uptake of air-particles.A broad anomalous anticyclonic circulation over the Indo-Northwestern Pacific(Indo-NWP)provides a favorable environment to enhance the moisture transport from the IND and WPO into the YRV.In the 2020 mei-yu season,a record-breaking Indo-NWP anomalous anticyclonic circulation contributed to a higher trajectory density as well as higher moisture content and moisture uptake of air-particles from the IND and WPO regions.This collectively resulted in unprecedented moisture transport from source origins,thus contributing to the mei-yu flood over the YRV in 2020.
出处 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2021年第12期2125-2136,共12页 大气科学进展(英文版)
基金 This paper was supported by the National Natural Science Foundation of China(Grant No.42075037) the Ministry of Science and Technology of China(Grant No.2018YFA0606501) the Program of International S&T Cooperation(Grant No.2018YFE0196000).
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