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《Chinese Journal of Atmospheric Sciences》 2007-05
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Estimation of Local Temperature Change Scenarios in North China Using Statistical Downscaling Method

FAN Li-Jun1,4,FU Cong-Bin1,and CHEN De-Liang2,31 Key Laboratory of Regional Climate-Environment Research for Temperate East Asia,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 1000292 Earth Sciences Centre,Gteborg University,40530 teborg,Sweden3 Laboratory for Climate Studies/National Climate Center,China Meteorological Administration,Beijing 1000814 College of Atmospheric Sciences,Lanzhou University,Lanzhou 730000  
Coupled Atmosphere-Ocean General Circulation models(AOGCMs) are widely used as an important tool for projecting global climate change.However,their resolution is too coarse to provide the regional scale information required for regional impact assessments.Therefore,downscaling methods for extracting regional scale information from output of AOGCMs have been developed.Regional climate models nested in AOGCMs,and statistical downscaling are usually used for downscaling.In this paper,the focus is placed on estimating local temperature changes at the 49 meteorological stations of North China using a statistical method to derive local scale monthly mean temperatures from large-scale atmospheric predictors.Empirical relationships are derived among selected variables from the NCEP re-analyses and observed data,tested by using cross-validation method.Statistical downscaling technique based on Multiple Linear Regression(MLR) of predictor principal components(PCs) is applied.A stepwise screening procedure is adopted for selecting skilful PCs as predictors used in the regression equation.For the January temperature of North China,the best predictor is the combination of sea level pressure and 850 hPa temperature and the best predictor for the temperature in July is the combination of 850 hPa height and 850 hPa temperature.Subsequently the statistical models are applied to the HadCM3 output under present climate.Finally,the statistical downscaling model is applied to HadCM3 SRES A2 and B2 to construct local future climate change scenarios.For the present-day climate simulation,it is shown that in both January and July,the downscaled temperatures match the observations well,though the estimated values are slightly underestimated at almost all the stations.For future climate change scenarios at the local scale,the monthly mean temperature has a significant increase at almost all the stations in both January and July.The estimated mean temperature increase is found to be smaller in July than in January;the estimated mean temperature increase using HadCM3 SRES A2 is found to be larger than HadCM3 SRES B2.
【Fund】: 国家重点基础研究发展规划项目2006CB400500;; 中国科学院海外杰出学者基金项目2001-2-10;; 中国气象局气候变化专项项目CCSF2006-6-1;; 瑞典STINT基金会和Sida资助项目
【CateGory Index】: P457.3
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