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《Progress in Geography》 2012-03
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Downscaling of Global Mean Annual Temperature under Different Scenairos

FAN Zemeng 1,YUE Tanxiang 1,CHEN Chuanfa 2(1.State Key Laboratory of Resources and Environment Information System,Institute of Geographic Sciences and Natural Resources Research,CAS,Beijing 100101,China;2.Geomatics College,Shandong University of Science and Technology,Qingdao 266510,China)  
One of the key issues of global change research is how to improve the simulated data resolution of Global Climate Models(GCMs) for the quantitative analysis of terrestrial ecosystems in response to the climate change at global,regional and local levels.In this paper,the statistcial transfer funcitons are developed by establishing the regression analysis of relation between mean annual temperature and latitude and elevation with the digital elevation models and climate data from global meteorological stations aton global level.The High Accuracy Surface Modelling(HASM) method integrated the statistical transfer functions,is used to downscale the simulated data of HadCM3 from a spatial resolution of 3.75° × 2.5° to 0.125° × 0.125°.The simualted results of A1Fi,A2 and B2 scenarios show that the mean annual temperature would be increasing in the 21st century,the areas in Greenland where the mean annual temperature is below 0℃ and in Antarctica below-35℃ would shrink,and the areas between north and south tropics where the mean annual temperature is higher than 40℃ would expand.The increase rate under scenario A1Fi is the highest and that under scenario B2 is slowest among three scenarios during the period from T1 to T4.The results also show that the coarse resolution data of IPCC GCMs can be availably downscaled to high resolution data by integrating the statistcial transfer funcitons and HASM methods,which could overcome the limitation that the current simulated data resolution of IPCC GCMs can not be used to explain and describe the details of climate change at regional level,especially at local level.
【Fund】: 国家自然科学基金青年基金项目(40801150);; 国家杰出青年科学基金项目(40825003);; 国家重点基础研究发展计划(973计划)项目(2009CB421105 2010CB950904);; 资源与环境信息系统国家重点实验室青年人才培养基金项目
【CateGory Index】: P423
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