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Iran. In this study, the temporal-spatial performances of Global Climate Models (GCMs) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) in simulating precipitation and temperature over Iran are evaluated. The simulations of 37 CMIP6 GCMs are compared to the gauge-based observational data from the University of Delaware (UDEL) at the 0.5°×0.5° spatial resolution for 1985–2014. A multi-criteria statistical approach is used to evaluate the models. In this study, the evaluation criterion for GCMs is the degree of conformity between their outputs and UDEL data. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), is used to integrate statistical test results. Results show that the ACCESS-CM2, BCC-CSM2-MR, and ACCESS-ESM1–5 models have superior performance over Iran. The Taylor diagram methodology was employed to assess the spatial agreement between GCMs and gridded observational data. The resulting correlation coefficients for rainfall and temperature variables from different models were (0.35–0.75) and (0.6–0.9), respectively, as determined by the Taylor diagram. The models that achieved higher ratings in the time performance evaluation phase, are also showed the better performance in the evaluation of their spatial pattern.
Zabihi et al. (Fri,) studied this question.