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Bias correction method of extreme precipitation data in global climate model using mixture distributions
Bias correction method of extreme precipitation data in global climate model using mixture distributions
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机译:基于混合分布的全球气候模式极端降水数据的偏差校正方法
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摘要
The present invention relates to a method of correcting errors in extreme precipitation data of a global climate model using a mixed distribution type. The error correction method of the extreme precipitation data of the global climate model using the mixed distribution type according to the present invention comprises the steps of: setting a climate scenario of the global climate model (GCM) or regional climate model (RCM) (QM) to adjust the probability distribution of the variables of the regional climate model (RCM) to the probability distribution of the observed data, to correct deviations of the global climate model (GCM) or regional climate model (RCM) ; Testing models of multiple mixed distribution functions for evaluation of climate change impacts based on a probability distribution of variables of the adjusted regional climate model (RCM); Estimating parameters of the mixed distribution function models using a meta-heuristic maximum likelihood (MHML) technique; Among the plurality of mixed distribution function models tested, the result data obtained by a model of the best mixed distribution function having the best ability to produce a distribution pattern closest to the distribution pattern of the observation data without producing an ideal value and the estimated parameters Performing shift correction based on the correction; And correcting the error of the extreme precipitation data of the climate model by reflecting the result of the correction to the extreme precipitation data of the climate model.
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