【摘要】 目前大部分全球气候模式(GCM)空间分辨率比较低,很难对区域尺度气候变化做出合理预测。降尺度方法的广泛运用弥补了GCM在这方面的不足。采用主成分分析和逐步回归相结合的统计降尺度方法对1980—2011年1月和7月长江中下游地区气温变化进行统计降尺度处理,并对该地区未来温度的变化进行预估。首先采用ECMWF的ERA-Interim再分析资料和实测资料建立逐月的统计降尺度模型,然后将建立的统计降尺度模型运用到CMIP5资料中,从而生成长江中下游地区各个测站未来气温变化序列。研究结果表明:(1)统计降尺度方法模拟1月和7月的温度与实测温度一致性都很好;(2)在21世纪末的时候气温在不同排放情景下都高于目前温度2～3℃,并且7月份的增温幅度要大于1月份。更多还原

【Abstract】 It is difficult to make reasonable predictions of climate change on regional scale by Global Climate Models(GCM) due to low spatial resolution. Now downscaling method has been widely used to make up for these defects of GCM. The temperature changes in the future in Yangtze River middle and lower reaches were predicted based on the temperature data in January and July from 1980 to 2011 statistic treatments with downscaling method combining stepwise linear regression(SLR) and principal component analysis(PCA). A monthly statistical downscaling model was formulated based on gridded data of ERA_interim from ECMWF reanalysis data and observed data, then apply it to the CMIP5 data to generate the series of temperature changes in future in the middle and lower reaches of the Yangtze River. The results showed that:(1) the simulated January and July temperature with statistical downscaling method was in good agreement with the observed temperature;(2) By the end of the 21 st century, temperatures in January and July will both increase by 2-3℃ and the latter warm more intense under the different scenarios, and the increment of temperature of July will greater than that of January.更多还原