Application of entropy weighted TOPSIS method for selection of general circulation models

The Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method is widely used in resolving the multi-objective and multi-indicator decision making problems in published literature. In this study ,TOPSIS was applied to evaluate the performance of precipitation simulations obtained from 18 General Circulation Models (GCMs) over the upper reaches of the Heihe River Basin. Firstly, six indicators, such as mean value, normalized root mean square error, coefficient of variation, Mann-Kenda ll trend analysis statistic value, coefficient of inhomogeneity and Pearson correlation coefficient were used in the evaluation process. Secondly, the weight of each indicator was determined by using the entropy approach, and finally GCMs were ranked based on the entropy weighted TOPSIS method. The result showed that CSIRO-Mk3.6.0 ranked 1st, and therefore was selected as the best alternative selection in precipitation simulation during the period of 1960-2005 over the study area. BNU-ESM ranked the last and was the worst alt ernative selection. The result was quitecomparable with the traditional method of the rank score. Compared with the observations during the period of 2006 to 2015, CSIRO-Mk3.6.0 model also performed the best and BNU-ESM performed the worst in predicting the precipitation for the same period. Thus, it was concluded that the TOPSIS method could be applied in the similar studies since it has arigorous theoretical basis, no requirement for data sample size, no loss of information in the calculation process, and easy to calculate.

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