资源环境科技发展态势分析平台

This study compared statistical downscaling model (SD) and dynamical downscaling model (DD) for changes in extreme temperature and precipitation indices, driven by the same global climate model output, in the 1.5 and 2 degrees C warmer climates in China. Simple bias correction (BC) methods were used to correct the climatology of temperature and precipitation in both models. After BC, both models show comparable performance in reproducing the spatial distributions of the extreme temperature and precipitation indices. Corrected model data were used to analyze future changes. Changing patterns of the extreme temperature indices are similar in the two models. Compared with the 2 degrees C warmer climate, warming 0.5 degrees C less can help reduce about 6% of summer day (SU) and 11% of tropical night (TR) increases (relative to 1986-2005) in China. Specifically, the reduced values of TR in northwest and northeast China are larger than 30% and 70%, respectively, in both models. Extreme wet indices will increase in most parts of China in the warmer climates. In DD, 5-day maximum precipitation (RX5day) will increase by approximately 10% and 14% in the 1.5 and 2 degrees C warmer climates, respectively, with maximal values (17% and 28%, respectively) occurring in north China. In SD, differences in extreme wet indices between the two warmer climates are small, and RX5day will increase more than 20% in northeast China. In DD, specific humidity will increase, and the East Asian summer monsoon will be enhanced in the warmer climates, favoring a larger increase in wet extremes in north China compared to other parts of east China.