GCMs (general circulation models) are main tools for generating climate projections for climate change research in hydrology and water resources. Accordingly, evaluating the performance of these models in simulating future climate is very important for choice of proper models. In this study, performance of 20 Coupled Model Intercomparison Project Phase 5 (CMIP5) model series was assessed using a technique for order performance by similarity to ideal solution (TOPSIS)-based approach together with normalized root mean square error (NRMSE), the Taylor skill score (STaylor), and two probability density function (PDF) skill scores. Precipitation and temperature data during 1976 to 2005 from three river basins including Zard River (ZR), Bakhtegan (BKH), and Ghareso (GH) in west and southwest Iran were used to select the best model. In general, models showed superiority in simulating temperature over precipitation. Based on the GCM ranking results for the ZR Basin, MIROC-ESM and IPSL-CM5A-LR were selected as the best and the weakest model, respectively. For the BKH Basin, the best model was BCC-CSM1.1 and the weakest IPSL-CM5A-MR and CCSM4. In other words, BCC-CSM1.1 had the maximum relative closeness to ideal solution. Based on the TOPSIS results, BCC-CSM1.1 and CanESM2 were the best models and IPSL-CM5A-MR the weakest model with a minimum relative closeness to the ideal solution in simulating temperature and precipitation for the GH basin. The approach presented in this study can be utilized to select appropriate climate models in other regions for future studies of climate change.
Subject classification (UKÄ)
- Oceanography, Hydrology, Water Resources