资源环境科技发展态势分析平台

Understanding the dynamic changes of climatic extremes is important to predict the occurrences of extreme climate events and to take measures to reduce their associated impacts. Based on daily maximum and minimum temperature data collected from 1899 meteorological stations in China and 8 metrics of large-scale circulation patterns from 1961 to 2015, the spatiotemporal trends in temperature extremes and their associations with circulation patterns were analyzed. The linear trend analysis and Mann-Kendall method were applied to examine the trends, and Pearson correlation analysis was used to identify the relationship between temperature indices and circulations. Results indicated that the increases in tropical nights (TR20), summer days (SU25), warm days (TX90p) and warm nights (TN90p), concurrent with the decreases in frost days (FDO), ice days (IDO), cool days (TX10p) and cool nights (TN10p) were highly pronounced in China as a whole. Spatially, SU25, TN90p and TX90p had increased at rates of 1.5-5.0 days, 0-4.0% and 0-3.0% per decade, while FDO, TN10p and TX10p had decreased at rates of 1.5-6.0 days, 0.5-4.5% and 0-2.1% per decade respectively in almost all of China. The increase of TR20 at rates of 0-6.0 days per decade occurred in most of China except for Qinghai-Tibet Plateau and the northern part of northeastern China, and the decreases of IDO at rates of 0-6.0 days per decade were appeared mainly in northeastern China, northern China, the middle and lower reaches of the Yangtze river and Qinghai-Tibet Plateau. Changes in temperature extremes were associated with some oceanic and atmospheric circulations, of which Atlantic multidecadal oscillation (AMO) and dipole mode index (DMI) had the highest correlation with temperature indices in China. The correlations between temperature indices and AMO were significant in most of China and those between temperature indices and DIM and East Atlantic/Westem Russia (EA/WR) were also significant in some parts of China. The variations of all cold extremes were also negatively related to Arctic oscillation (AO) in northeastern China, northern Xinjiang, the northern parts of northern China and eastern China, and those of TN90p and TX90p were positively related to AO in northeastern China. These findings will provide useful information in forecasting extreme climate events and evaluating climate models.