ABSTRACT
Suitable global climate models (GCMs) of precipitation , maximum temperature , and minimum temperature () are evaluated for 14 grid points in Telangana State, India. Three standard statistical performance metrics (SspMetrics), namely the skill score, normalized root-mean-square deviation, and correlation coefficient are used to compare the GCMs with the observed data. Weights are calculated for each SspMetric using entropy and sensitivity analysis. The distance measure method is applied to rank the GCMs for each variable at each grid point. A combined ranking is evaluated at each grid point based on the group decision-making approach (GDMA). The following suitable ensemble climate models for each variable are identified: for , FGOALS-g2, CMCC-CMS, and INMCM4.0; for , BCC-CSM1.1(m), CanESM2, and MIROC5; for , CanESM2, BCC-CSM1-1(m), and ACCESS 1.0. The calculated net strength of each GCM is consistent with the ensemble model results. For each variable, probability density functions are plotted for three selected suitable GCMs against the observed data. The identified suitable ensemble GCMs can be used in climate-related impact assessments-based precipitation, temperature, or both.
Disclosure statement
No potential conflict of interest was reported by the authors.