利用CCLM高分辨率区域气候模式RCP4.5情景预估数据与淮河流域1960.2005年日尺度气象观测资料,对比分析模式在试验期(1960.2005年)和预估期(2006—2040年)的模拟能力。结果表明:①试验期模式数据能较准确地模拟流域逐月平均温度时间变化特征,相关系数达0.99(通过95%置信度检验);日均温空间分布特征相关系数达0.72;但在南部高海拔地区(安徽省霍山县和金寨县)精度不高;极端最高(低)气温的空间相关性达O.77(0.88)。②模式在试验期模拟的逐月平均降水量总体趋势与实测值变化一致,相关系数达0.63(通过95%置信度检验);对干旱的模拟与观测数据存在一定误差,但整体趋势与其一致;年均降水量和极端强降水空间分布相关系数分别达0.90和0.93,模拟效果较好;整体上,模式对温度的模拟效果要好于降水模拟。③RCP4.5情景下,空间尺度上淮河流域未来温度和降水与观测期相比变幅小,时间尺度上年均降水量无显著变化,平均气温年际变化率约0.21℃/10a,极端高温持续增长,低温持续下降。
Based on estimated data of the high-resolution simulation of climate change model under RCP4.5 (Representative Concentration Pathways) scenarios, combining with daily observed date from 1960 to 2005 in the Huaihe River basin, this paper contrasts and analyses the simulation ability of model between trial period (1960-2005) and estimated period (2006-2040). The results show that trial period data of CCLM (COSMO model in climate mode, COSMO-CLM or CCLM) can accurately simulate monthly average temperature and the correlation coefficient is 0.99 (pass the 95% confidence test); beside, the correlation coefficient of spatial distribution of average daily temperature is 0.72. However it is relatively low in the south of high altitude area (Huoshan and Jinzhai counties in Anhui province) and the spatial correlation of maximum (minimum) extreme temperature is 0.77 (0.88). Furthermore, the overall trend of monthly average precipitation is in line with the observed date and the correlation coefficient is 0.63 (pass the 95% confidence test). SPI reveals that it has errors for simulating drought, but the overall trend reaches consensus. Overall, the simulated results of temperature are better than those of the precipitation. Under RCP4.5 scenarios, the amplitude of spatial distribution of future temperature and precipitation are relatively small at spatial scale, and the annual average precipitation has no significant change at time scale. The interannual variation of average temperature is 0.21℃/10a. The threshold values of maximum and minimum temperatures show that the maximum temperature would continue to rise and the minimum temperature would decline.