Analysis of extreme temperature events based on estimated 1-km daily near-surface air temperature

Abstract

Nowadays, the intensification of global warming leads to the increased frequency of extreme temperature events. Many studies reported that different regions are facing the threat of extreme hot and cold temperature in some degree. The Qinghai-Tibet Plateau Transportation Project is a major project in China, and it is beneficial for public to study the extreme temperature events along the railway and avoid the risk induced by the extreme temperature. This study estimated the daily maximum, minimum and average near-surface air temperature along the railway. Sixteen extreme temperature indices defined by ETCCDI (the Expert Team on Climate Change Detection and Indicators) were used to represent the extreme temperature events, and Mann-Kendall trend test and Sen's slope estimation method were employed to explore the spatial-temporal variation trends of the extreme temperature along the Qinghai-Tibet Plateau Transportation Corridor from 1981 to 2019. In addition, the response of extreme temperature events to altitude was discussed.The results show that the climate becomes warming along the Qinghai-Tibet Plateau Transportation Corridor from 1981 to 2019, and the extreme hot events are detected in most areas, while the extreme cold events mainly occurs in the east and southwest part. The significant increasing trend is found according to the indices representing the hot events (SU25, TR20, TX90p, TN90p, TXx, TXn, TNx, TNn and WSDI), while the indices representing the cold events (FD0, ID15, TX10p, TN10p and CSDI) show a significant decreasing trend in most areas over the past nearly 40 years. Besides, the extreme temperature events is highly related to altitude variations. Compared with the middle altitude zones, extreme high temperature events tend to occur in the lower altitude zones and the higher altitude zones. It is of great significant to schedule the train in advance and reduce the disasters by investigating the long-term variation trends of extreme temperature events along the Qinghai-Tibet Plateau Transportation Corridor.