Ranking of CMIP5-based global climate models for India using compromise programming

Abstract

Thirty-six Coupled Model Intercomparison Project-5-based global climate models (GCMs) are explored to evaluate the performance of maximum (T max) and minimum (T min) temperature simulations for India covering 40 grid points. Three performance indicators used for evaluating GCMs are correlation coefficient (CC), normalised root mean square error (NRMSE) and skill score (SS). Entropy method is applied to compute the weights of the three indicators employed. However, equal weights are also considered as part of sensitivity analysis studies. Compromise programming (CP), a distance-based decision-making technique, is employed to rank the GCMs. Group decision-making approach is used to aggregate the ranking patterns obtained for individual grid points. A simple but effective ensemble approach is also suggested.