Toward Understanding the Extreme Floods over Yangtze River Valley in June−July 2020:Role of Tropical Oceans

作     者：Shaolei TANG Jing-Jia LUO Jiaying HE Jiye WU Yu ZHOU Wushan YING Shaolei TANG;Jing-Jia LUO;Jiaying HE;Jiye WU;Yu ZHOU;Wushan YING

作者机构：Institute for Climate and Application Research(ICAR)/Key Laboratory of Meteorological Disaster of Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and TechnologyNanjing 210044China 

出 版 物：《Advances in Atmospheric Sciences》 (大气科学进展（英文版）)

年 卷 期：2021年第38卷第12期

页      面：2023-2039,I0009-I0012页

核心收录：

学科分类：081504[工学-水利水电工程] 07[理学] 070601[理学-气象学] 08[工学] 0815[工学-水利工程] 0706[理学-大气科学] 

基　　金：This work is supported by National Natural Science Foundation of China(Grant No.42030605 and 42088101) National Key R&D Program of China(Grant No.2020YFA0608004) 

主　　题：summer extreme floods Middle/Lower Yangtze River El Niño Indian Ocean SST decadal warming trend 

摘      要：The extreme floods in the Middle/Lower Yangtze River Valley(MLYRV)during June−July 2020 caused more than 170 billion Chinese Yuan direct economic ***,we examine the key features related to this extreme event and explore relative contributions of SST anomalies in different tropical *** results reveal that the extreme floods over the MLYRV were tightly related to a strong anomalous anticyclone persisting over the western North Pacific,which brought tropical warm moisture northward that converged over the *** addition,despite the absence of a strong El Niño in 2019/2020 winter,the mean SST anomaly in the tropical Indian Ocean during June−July 2020 reached its highest value over the last 40 years,and 43%(57%)of it is attributed to the multi-decadal warming trend(interannual variability).Based on the NUIST CFS1.0 model that successfully predicted the wet conditions over the MLYRV in summer 2020 initiated from 1 March 2020(albeit the magnitude of the predicted precipitation was only about one-seventh of the observed),sensitivity experiment results suggest that the warm SST condition in the Indian Ocean played a dominant role in generating the extreme floods,compared to the contributions of SST anomalies in the Maritime Continent,central and eastern equatorial Pacific,and North ***,both the multi-decadal warming trend and the interannual variability of the Indian Ocean SSTs had positive impacts on the extreme *** results imply that the strong multi-decadal warming trend in the Indian Ocean needs to be taken into consideration for the prediction/projection of summer extreme floods over the MLYRV in the future.