[Quantitative Analysis of Spatio-temporal Evolution Characteristics of Seasonal Average Maximum Temperature and Its Influence by Atmospheric Circulation in China from 1950 to 2019].

Global warming and intensified human activities have led to regional climate instability with increasing frequency and the persistence of high-temperature climate events. Eco-environmental protection and socio-economic development have been faced with rigorous threats. Taking the monthly maximum temperatures from 1950 to 2019 as the basic data source, the spatial-temporal evolution characteristics of seasonal average maximum temperature (AMT) were discerned using the Mann-Kendall test and unary linear regression method in China from 1950 to 2019. Combined with linear correlation, partial linear correlation, and wavelet analysis, the correlation between seasonal AMT characteristics and atmospheric circulations was analyzed quantitatively. The results showed that:① the AMT in all seasons had a significant upward trend, with an increase of 1.21, 0.08, 1.81, and 0.25℃ in spring, summer, autumn, and winter, respectively. The abrupt change times of the AMT were concentrated in the 1990s to the early 21st century. ② In terms of spatial distribution, except for in summer, the average trend rates of AMT in other seasons increased gradually from south to north, although the increasing degrees were different. Among them, the AMT change rate in spring-winter was the fastest in northeast and northwest China. ③ There were complex correlations between the AMT of every season and atmospheric circulation factors, and the distribution of the interrelation energy varied significantly in different frequency domains. Specifically, the Pacific Decadal Oscillation had a significant negative correlation with AMT in summer. The North Atlantic Oscillation had an active effect on AMT changes in summer, autumn, and winter. The Arctic Oscillation had a significant positive driving effect on AMT in all seasons, and there were significant positive or negative influences on the short-or long-term changes of AMT in spring and summer due to the different EI Niño-Southern Oscillation years. These results could provide a theoretical basis and technical reference for China to formulate scientific and effective response plans of climate change.