The present invention relates to an error correction method of extreme precipitation data of a global climate model using a mixed distribution model. According to the present invention, the error correction method of extremal precipitation data of a global climate model using a mixed distribution model comprises: a step of setting up climate scenarios for global climate model (GCM) or regional climate model (RCM) calculations by implementing an algorithm; a step of adjusting a probability distribution of variables of the regional climate model (RCM) with respect to a probability distribution of observation data by using quantile mapping (QM) to correct a deviation of the global climate model (GCM) or regional climate model (RCM) calculations; a step of testing models of a plurality of mixed distribution functions to evaluate a climate change effect based on the adjusted probability distribution of variables of the regional climate model (RCM); a step of estimating parameters of the mixed distribution function models by using a meta-heuristic mathematics (MHML) technique; a step of performing bias correction based on the estimated parameters and result data obtained by a model of a mixed distribution function showing optimum performance among the mixed distribution function models tested; and a step of correcting an error of extreme precipitation data of the climate model by reflecting the result of the bias correction to the extreme precipitation data of the climate model.
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