The Spatio-temporal Variation Characteristics and Climate Attributions of Summer Precipitation in the Qinling Mountains
Exploring the summer precipitation and its atmospheric attributions in the Qinling Mountains has research value and significance for studying the response of the regional environment to global climate change.Based on data from 32 meteorological stations and 15 atmospheric circulation indices in the Qinling Mountains of Shaanxi Province from 1959 to 2022,univariate linear regression method and wavelet transform analysis(CWT)are used to study the temporal and spatial evolution characteristics of summer precipitation in the Qinling Mountains over the past 64 years,as well as its relationship with large-scale circulation indices.The conclusions obtained are as follows:summer precipitation in the Qinling Mountains has shown an insignificant upward trend in the past 64 years from 1959 to 2022,and the change rates of the univariate linear regression method is 10.81 mm/10 a.It was found that the precipitation change rate at Shangnan Station on the southern slope of the Qinling Mountains is the highest,with a change rate of 19.3 mm/10 a.The average summer precipitation in the Qinling Mountains region has been 344.34 mm.Ziyang County,located on the southern slope of the Qinling Mountains,has the highest precipitation,approximately 469.35 mm.Huayin County,located on the northern slope of the Qinling Mountains,has the lowest precipitation,approximately 216.51 mm.The summer precipitation on the southern slope of the Qinling Mountains has been significantly higher than that on the northern slope,with a precipitation of approximately 107.68 mm.The average summer precipitation on the south slope is about 377.99 mm,and the average summer precipitation on the north slope is about 270.31 mm,both of which have not passed the significance test.The 64 year summer precipitation in the Qinling Mountains has a strong positive correlation with SOI,SAODI,and SWACI,while a negative correlation with EASMI,SCSMI and SASMI.
万方数据
维普
