Evaluation of CMIP6 models in estimating temperature in Iran with emphasis on equilibrium climate sensitivity (ECS) and transient climate response (TCR)

Global warming is a gradual increase in the Earth's temperature generally due to the greenhouse effect caused by increased levels of carbon dioxide. Global warming has had significant consequences for human life, significantly affecting agricultural production, ecosystems, and water resources. The climate system of the Earth responds to a perturbation to the top of the atmosphere radiative balance through a change in temperature. This imbalance constitutes a radiative forcing of the climate system, and the magnitude of the response is determined by the strength of the forcing and the net radiative feedback. Equilibrium Climate Sensitivity (ECS) is an estimate of the eventual steady-state global warming at double CO2 and Transient Climate Response (TCR) is the mean global warming predicted to occur around the time of doubling CO2 in GCM and ESM runs for which atmospheric CO2 concentration is prescribed to increase at 1% per year.   This study aimed to evaluate the performance of Climate Model Intercomparison Project Phase 6 (CMIP6) models by selecting 30 models considering TCR and ECS and to investigate temperature spatial distribution and annual trends in Iran. The performance of these models has been investigated with data from Iran’s fifty-one synoptic stations for the historical period (1980-2014) using the Taylor diagram and box plot. The results showed that most CMIP6 models have good performance in simulating spatial temperature patterns. However, in the area-averaged, 73% of the selected models have estimated the temperature of the country as less than the station data. In general, more than 56% of the models showed a correlation higher than 0.5 compared to station data in the area-averaged temperature of Iran. Four models including CanESM5, INM-CM5-0, TaiESM1, and UKESM1-0-LL have shown the highest performance in estimating the temperature in Iran. The area-averaged annual temperature trend, which was examined by the modified Mann-Kendall test, showed that the temperature trend of CMIP6 models is increasing along with the observational data for all models. Most CMIP6 models, however, have simulated higher warming rates in the historical period, which differs from station data. These differences cannot be explained by internal climate variability (ICV), and the equilibrium climate sensitivity of most CMIP6 models has created a greater rate of warming in the models. For example, models such as CanESM5 and UKESM1-0-LL, which showed the highest trend, had the highest ECS and TCR among all.