Elevation gradient dependence of extreme climate indices on Yunnan Plateau, China. (1st April 2022)

• Record Type: Journal Article
• Authors: Yan, Wenbo; He, Yunling; Qu, Xinxing
• Is Part Of: International journal of climatology. Volume 42:Number 12(2022)
• Page Start: 6072
• Page End: 6091
• Publication Date: 2022-04-01
• Subjects: elevation interval -- extreme climate -- mutation time -- Rclimdex1.0; Climatology -- Periodicals; Climat -- Périodiques; Climatologie -- Périodiques; 551.605
• DOI: 10.1002/joc.7578
• Languages: English
• ISSNs: 0899-8418

Abstract

Abstract: The acceleration of global warming leads to frequent extreme weather events. The sensitivity of high‐elevation regions to global warming makes their extremes more prominent. Based on the software Rclimdex1.0, 15 extreme climate indices from 120 meteorological stations in Yunnan from 1960 to 2019 were calculated. Trend analysis, correlation analysis, and cross‐correlation analysis were used to investigate the spatiotemporal variation characteristics of these extreme climate indices. The results showed that, except CDD, other extreme precipitation indices were negatively correlated with the increase of elevation. The extreme warming indices (SU25, WSDI, TX90p, TN90p) showed an increasing trend with the increase of elevation, while the extreme cold indices (CSDI, FD0, TX10p, TN10p) showed a decreasing trend with the increase of elevation. The rate of nocturnal warming at high elevations is higher than that at low elevations. The change rate of extreme warmth indices (SU25, WSDI, TX90p, TN90p) and extreme cold indices (FD0, CSDI, TX10p, TN10p) was negatively correlated ( p < .05) in all elevation ranges, and this correlation was most significant in the elevation range of 1, 500–2, 000 m. These results highlight that the rate of drying and warming at higher elevations is higher than that at lower elevations, providing case support and scientific basis for sensitivity of high‐altitude regions to extreme climate. Abstract : (1)–(6) represents the temporal change, M–K abrupt change analysis, spatial change, mean value of extreme climate indices at different elevations, trend of extreme climate indices at different elevations, and correlation between extreme climate indices, respectively.