Spatiotemporal Changes of Extreme Precipitation and Its Teleconnection Analysis with Climate Circulation Indices in Three Gorges Reservoir Area in Recent 60 Years - ZENG Huiqi; TENG Shunlin; SHAO Meng; ZHANG Lu; WANG Yuefeng (Renmin Zhujiang)
Analyzing the correlation between large-scale climate circulation and extreme precipitation is of great significance for regional flood and drought warnings and extreme weather management.Previous studies have well revealed the influence of a single climate circulation index,while the influence characteristics of multiple climate circulation indices are still unclear.According to the daily precipitation in 21 meteorological stations in Three Gorges Reservoir Area (TGRA) from 1960 to 2019,eight extreme precipitation indices (CDD,CWD,R10,R20,Rx1d,Rx5d,R95p,and R99p) were constructed in terms of precipitation duration and absoluteness,and Mann-Kendall (M-K) trend test,Spearman correlation analysis,and multiple linear regression (MLR) were used to analyze the spatiotemporal changes during extreme precipitation in the TGRA.Then the correlation between extreme precipitation and climate circulation was revealed in terms of single and multiple factors.The results showed that:①The R10,R20,Rx1d,Rx5d,R95p,and R99p in the TGRA spatially decreased from northwest to southeast from 1960 to 2019,which was similar to the spatial trend of multi-year average precipitation;②the CWD,CDD,R10,and Rx5d generally decreased,while R20,Rx1d,R95p,and R99p increased.The duration of continuous precipitation events in the TGRA shortened,but the frequency and intensity of short-term strong precipitation events increased;③in terms of teleconnection analysis of extreme precipitation and climate circulation index,the multiple factor regression analysis could better explain the extreme precipitation index than the single factor regression analysis.Specifically,the combination of the East Asian Summer Monsoon Index (EASMI) and the South Asian Summer Monsoon Index (SASMI) had the best performance in explaining the extreme precipitation index.This study can provide a scientific basis for coping with extreme climate change and weather disaster prediction and warning in the TGRA.