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Statistical Downscaling Of Local And Regional Climate Scenarios Over China

Posted on:2007-08-18Degree:DoctorType:Dissertation
Country:ChinaCandidate:L J FanFull Text:PDF
GTID:1100360185994767Subject:Science of meteorology
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Although General Circulation models (GCMs) represent the main features of the global atmospheric circulation reasonably well, their ability in reproducing regional scale climatic details is rather limited because of their low-resolution. As a result, there is a need to develop tools for downscaling GCM predictions of climate change to regional and local scales. High-resolution GCMs, regional climate models nested in GCMs, and statistical downscaling are the three main tools for downscaling. Many studies have been made to statistically downscale large scale climatic information to regional level in Europe and the United States. However, studies and application of statistical downscaling technique is very few in China. This study focuses on research of statistical downscaling technique and its application of projecting future local and regional climate scenarios over China.The predictands used in this research include the monthly temperature data obtained at 562 observation station and rainfall data at 533 stations in January and July from 1961 to 2000, which are provided by china Meteorological Administration and the large-scale climatic predictors used are derived from the NCEP/NCAR reanalysis data with a resolution of 2.5o in latitude and longitude in January and July from 1961 to 2000. 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. Subsequently, the statistical downscaling models are applied to HadCM3 SRES A2 and B2 scenarios to construct local future climate change scenarios. Finally, statistical downscaling temperature scenarios in China based on a multi-model ensemble are carried out.
Keywords/Search Tags:statistical downscaling, future climate change scenarios, China, multi-model ensemble, cross-validation
PDF Full Text Request
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