In this study, the relative trend in temperature change in China from 1951 to 2017 was used to construct a probability density function and exceedance probability based on long-term correlation of relevant data. The confidence limit of this trend, belonging to natural variability, was studied and calculated under a certain confidence level. We sought to determine whether the relative change trend was caused by unnatural factors (whether the temperature increase was significant), and explore the threshold values of temperature change caused by unnatural factors in different regions, corresponding transition time periods, and evolutionary trends. The results showed that: (1) 10% of the site temperatures at 160 stations were overestimated when using traditional linear regression methods to calculate trend significance. These sites were mainly located in the northwest, southwest and eastern coastal areas of China. (2) From the perspective of spatial distribution of temperature trends in the country, except for the cooling trend in the central and western regions of Xinjiang, the other regions all showed warming trends. Relative temperature changes in Shanxi, Inner Mongolia, parts of Ningxia, southwestern Xinjiang, Yangtze River Delta, and southwestern Yunnan were relatively large. Unnatural trends in Northeast China, Inner Mongolia, and the northern Shanxi Province were large, and the temperature increase was significant. (3) From the spatial evolution of the significant inter-decadal warming areas, the northern and northeastern regions of China took the lead in increasing temperature, a trend that gradually expanded to the south and west. During the period of 1966–2001, most regions in China showed an increase in unnatural factors; for 1971–2006, temperatures in the northeastern and northeastern Inner Mongolia regions began to gradually decrease, while significant warming in southwestern China began to gradually expand. The number of significant warming sites was largest during 1976–2011; from 1981 to 2016, the significant warming sites were mainly concentrated in the Yellow River and Yangtze River Basins in southern China. In summary, there were prominent inter-decadal spatial and temporal transitions in significant warming areas in China caused by unnatural factors. This paper may provide new perspectives and new ways for the attribution and prediction of temperature change in China, and strengthen the linkage of climate change research and short-term climate prediction.
王瑜,钱忠华,颜鹏程,封国林.非自然因素引起的增温趋势的时空分布特征.大气科学,2020,44(3):565~574 WANG Yu, QIAN Zhonghua, YAN Pengcheng, FENG Guolin. Temporal and Spatial Distribution Characteristics of an Increasing Temperature Trend Caused by Unnatural Factors. Chinese Journal of Atmospheric Sciences (in Chinese),2020,44(3):565~574复制