Research Progress on Statistical Downscaling Methods
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Abstract:
Statistical downscaling method is one of the methods that transform the meteorological data with low resolution GCMs output to the basin scale data, and this method has been studied in depth and widely used in the area of climatology. In this paper, the basic principles of the statistical downscaling method were introduced, including the basic assumptions, main steps, and key points. The statistical downscaling methods can be classified into the transfer function method, weather typing method, and weather generator model, and the applications of each method were also introduced. The uncertainty analysis of the statistical downscaling method was briefly introduced. Moreover, the future study of the statistical downscaling method should focus on its applicable conditions and range and the improvement of precision of precipitation simulation. Finally, it was pointed out that the coupling approach of statistical and dynamic downscaling methods is one of the main development directions of the downscaling study.
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