Evaluation of the Accuracy of CMIP6 Models in Estimating the Temperature and Precipitation of Iran Based on a Network Analysis

Climate change is one of the most important factors affecting the world's climate. Due to the importance of estimating these effects, it is necessary to use appropriate tools and models to estimate the effects of climate change on climatic variables (especially temperature and precipitation). For this purpose, the use of Atmosphere-Ocean General Circulation Models (AOGCMs) as the most common of these tools, has found a lot of use in studies related to climate change. In this regard, the aim of this study was to evaluate the accuracy of the latest AOGCMs related to the sixth IPCC assessment report of IPCC in in different regions of Iran. For this purpose, the historical outputs of 10 AOGCMs in the period 1980 to 2014 were extracted from the IPCC database and compared with the ERA5 reanalysis data of the ECMWF center. This comparison was based on RMSE, Pearson correlation coefficient and Kling-Gupta combined index (KGE). The results showed that different models do not have the same accuracy in estimating the temperature and precipitation of Iran in different months of the year. The variability of the model errors in precipitation estimation were more than the variability of these errors in temperature estimation. On the annual scale, the results showed that the IPSL-CM6A-LR model had the best performance in estimating temperature and the HadGEM3-GC31-LL model had the best performance in estimating annual precipitation. Also, the results showed that the error rate of these models was lower in central and eastern regions of Iran than the other regions.