Observed Quantile Features of Summertime Temperature Trends over China: Non-Negligible Role of Temperature Variability

Frontiers in Earth Science

Di Wang¹  Hedi Ma²  Chujie Gao³  Shanlei Sun⁴  Xiao Li⁴  Wenjian Hua⁴  Xing Li⁵ 

[1] China Meteorological Press, China Meteorological Administration, Beijing, China;Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research, Institute of Heavy Rain, China Meteorological Administration, Wuhan, China;Key Laboratory of Marine Hazards Forecasting, Ministry of Natural Resources, College of Oceanography, Hohai University, Nanjing, China;Key Laboratory of Meteorological Disaster (KLME), Ministry of Education, Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing, China;Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, College of Atmospheric Science, Chengdu University of Information Technology, Chengdu, China;

关键词: extreme temperature;    quantile trends;    variability;    China;    summertime;   

DOI  :  10.3389/feart.2021.762563

来源: DOAJ

【 摘 要 】

Changes in temperature variability can have more serious social and ecological impacts than changes in the mean state of temperature, especially when they are concurrent with global warming. The present study examines the summertime temperatures’ trends over China from the quantile perspective. Through fully investigating the quantile trends (QTs) of the maximum (Tmax) and minimum temperature (Tmin) using the homogenized observation data and quantile regression analysis, we identify evident region-specific quantile features of summertime temperature trends. In most of northern China, the QTs in Tmax and Tmin for all percentiles generally show strong uniform warmings, which are dominated by a warm shift in mean state temperatures. In contrast, the QTs of Tmax in the Yangtze River Basin show distinguishable inter-quantile features, i.e., an increasing tendency of QTs from cooling trends in the lower percentile to warming trends in the higher percentile. Further investigations show that such robust growing QTs of Tmax across quantiles are dominated by the temperature variance. Our results highlight that more attention should be paid to the region-specific dominance of temperature variability in trends and the related causes.

【 授权许可】

Unknown