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Ranking of CMIP5-based global climate models using standard performance metrics for Telangana region in the southern part of India

ABSTRACT Selection of suitable Global Climate Models (GCMs) for average temperature (T avg) simulation is assessed in this paper for Telangana region on the southern part of India covering 14 grid points. Five statistical performance metrics: Skill Score (SS), Correlation Coefficient (CC), Nash Sutcliffe Efficiency (NSE), Normalised Root Mean Square Deviation (NRMSD), and Absolute Normalised Mean Biased Deviation (ANMBD) are considered in this study to evaluate GCMs using historical observations. Three cases (i.e., case 1: CC-SS-NRMSD; case 2: CC-SS-ANMBD; case 3: CC-NSE-SS-NRMSD-ANMBD) were considered to evaluate the suitable models and selection of multi model ensemble for Telangana region which can be further used in climate impact assessment studies. Weights are determined for each performance metric using Entropy technique and sensitivity analysis. Compromise Programming (CP) is applied to rank GCMs based on the distance measure technique. Group decision making is employed to conclude collective ranking patterns of GCMs. The results of the study suggest that MIROC5, CNRM-CM5, Access 1.0 and BCC-CSM1.1(m) are suitable models for prediction of T avg for the Telangana region under consideration.