Spatiotemporal variation characteristics of local synchronous correlation between temperature and precipitation in China
Using the temperature and precipitation data of 2419 stations in China from 1958 to 2017,the local correlation relationship between them in different seasons and their temporal and spatial variation characteristics were explored.The study found that the local contemporaneous correlation of temperature and precipitation in China has obvious seasonal differences and interdecadal variation characteristics.The local contemporaneous correlations of the four seasons in the first 30 years(1958-1987)and the last 30 years(1988-2017)in China are mostly negative correlations,with the weakest in autumn and the strongest in summer.Compared with the previous 30 years,in the next 30 years,the negative correlation in winter and autumn is enhanced,the negative correlation in spring is decreased,and the stability of station correlation is low;the negative correlation in summer is decreased,and the stability of station correlation varies with regions.Further analysis found that in summer,there are areas with significant changes in the correlation between temperature and precipitation over the same period in the Jianghuai region and the Northeast region,while there are similar regions in the Northeast region and East China region in winter.The results of the Wilcoxon rank sum test show that in the winter of the first and last 30 years,the temperature in Northeast China has changed significantly,and the temperature and precipitation in East China have changed significantly,and in the summer of the first and last 30 years,the temperature in the northeast region changed significantly,and the precipitation in the Jianghuai region changed significantly.And these significant changes in temperature and precipitation lead to an interdecadal turning point in the correlation between temperature and precipitation in winter and summer in these regions.
Temperature and precipitationClimate changeCorrelationInterdecadal change
NETL
NSTL
万方数据
