长江流域气候变化高分辨率模拟与RCP4.5情景下的预估

基于长江流域142个气象站1986—2005年月降水和气温数据，评估由MPI-ESM-LR模式驱动的CCLM区域气候模式对长江流域气温和降水的模拟能力，并采用EDCDF法对气温和降水预估数据进行偏差校正。结果表明：该区域气候模式能较好地模拟出长江流域平均气温的季节变化和空间分布特征，但模拟值无论在季节还是年际尺度上均高于观测值。对降水而言，该模式不能较好地模拟出降水的季节分布特征，导致春季、冬季及年模拟值高于观测值，而夏季和秋季模拟值低于观测值。总体而言，该模式对气温的模拟效果相对较好。偏差校正后的预估结果表明：在RCP4.5情景下，长江流域未来（2016—2035年）平均气温相对于基准期（1986—2005年）将升高0.66℃，年降水量将减少2.2%。

Simulation and Projection of Climate Changes Under the RCP4.5 Scenario in the Yangtze River Basin Based on CCLM

Based on monthly precipitation and temperature dataset (1986-2005) of 142 stations in the Yangtze River basin, the capability of the COSMO model in Climate Mode (CCLM) to reproduce the spatial and temporal variability of the observed precipitation and temperature was examined. The bias between simulation and observation was corrected by the equidistant cumulative distribution functions (EDCDF). The analysis shows that the spatial changes of simulated annual precipitation and mean temperature are broadly comparable with the observations. CCLM tends to overestimate temperature at both seasonal and annual time scales. CCLM fails to simulate the monsoon precipitation, thereby to underestimate precipitation in summer and autumn, and overestimate it in winter and spring. On the whole, temperature is better simulated than precipitation. Based on the bias-corrected projection, annual mean temperature over the whole basin will increase 0.66℃, while annual precipitation will reduce 2.2% in 2016-2035 under the RCP4.5 scenario, relative to the observations of 1986-2005.