长江中下游夏季极端降水事件频次的统计降尺度模拟与预估

利用CMIP5三个耦合模式的历史模拟及不同情景预测结果、NCEP/NCAR再分析资料和长江中下游观测降水资料,采用统计降尺度方法对长江中下游夏季极端降水频次进行模拟和预估。首先,通过计算相关的方法,获取建立统计降尺度预测模型所需的预测因子。提取的预测因子同时满足既是观测环流要素场影响极端降水的关键区域,又是模式要素场预报的高技巧区域两个条件;然后,结合挑选出的预测因子,利用多元线性回归方法建立长江中下游极端降水的统计降尺度预测模型,并对模型性能进行检验。交叉检验结果表明,此种统计降尺度方法能对过去长江中下游极端降水变化有较好的再现能力,且多个降尺度模型结果的集合能进一步提高降尺度方法的模拟技巧;最后,将建立的统计降尺度模型应用于CMIP5未来3种不同的排放情景来对极端降水进行未来预估,并对多模式结果进行集合。结果显示,统计降尺度模型预估未来几个年代际长江中下游夏季极端降水频次相对于1986~2005年呈增加趋势,21世纪中、后期高排放情景下极端降水频次增加幅度高于低排放情景。

SIMULATION AND ESTIMATION OF EXTREME PRECIPITATION EVENT FREQUENCY IN THE MIDDLE-LOWER REACHES OF YANGTZE RIVER USING STATISTICAL DOWNSCALING METHOD

Using historical and scenario simulation results from three CIMP5 climate models,NCEP/NCAR reanalysis data and observed precipitation data over Yangtze River Basin,the summer extreme precipitation event frequency over the middle-lower reaches of Yangtze River (YRF) has been simulated and estimated by using the statistical downscaling method.First,the predictors that significantly influence YRF have been extracted by correlation analysis.The predictors with high predictive power were selected from high correlations between observation YRF and other variables.Then the downscaling models were established by using the multi-linear regression method.Cross-validation test showed that the downscaling models have high skill for YRF and ensemble results of three downscaling models can further improve the simulation skill.Finally,the statistical downscaling model was applied to three scenarios of CMIP5 to construct future climate change of YRF.For future climate change scenarios,the YRF increases during following several decades,and the increased amplitude for high emission scenarios is higher than that of low emission scenarios during middle and later 21th centuries.