Seasonally extreme temperature events accelerate in arid northwestern China during 1979-2018

The arid northwestern China is the most vulnerable region to climate change, where the variability of seasonally extreme temperature events has profound implications for both its hydrological, ecological, and human systems. In this study, we applied 15 indicators of extreme temperature to analyze the spatial and temporal variation of its occurrence in arid northwestern China for a recent 40-year period (1979 to 2018). These extreme temperature event dynamics were then combined with atmospheric and oceanic circulation to explore their response mechanisms. Our results revealed the following: (1) Over the 40-year period, the annual average temperature in this arid zone increased at a rate of 0.4 degrees C/decade (p = 0.09), exceeding the national average rate (0.28 degrees C/decade). Apart from a few indicators, extreme temperature events (TXx, TNx, TXn and TNn) generally increased at least twice as fast as average temperature during the four seasons, especially in spring, when TNn (0.98 degrees C/decade) rose five times faster than did the average temperature (0.2 degrees C/decade). (2) Spatially, except for the Kunlun Mountains and Tarim Basin, seasonal warming occurred in most parts of the studied arid zone, being most prominent in the summer. In this season, the average number of warm nights increased (3.23 days/decade), while the average number of cold nights decreased (2.69 days/decade). (3) After the 1990s, extreme temperature events accelerated significantly. The Cold Spell Duration Indicator decreased 42% in spring and the Warm Spell Duration Indicator increased 300% in summer, from 1979 -1998 to 1999-2018, which may hasten the formation of snow and glacier melt flooding events in the spring and summer. Spatiotemporal variability in seasonally extreme temperature events was closely related to atmospheric and oceanic circulation, particularly for the AMO (r = 0.8). Altogether, these findings enhance our understanding of how to better assess shifts in extreme temperature events in response to a changing climate in arid zones.