Abstract
Climate change has led to significant changes in weather elements in recent years, which, affect the various aspects of human life, including water supply, food security, and so on. In this research, the effects of climate change on the Kor basin in Fars province under different climate scenarios for four parameters of minimum and maximum temperature, mean temperature and precipitation using Beijing Climate Center Climate System Model (BCC-CSM 1.1), Centro Euro-Mediterraneo per Cambiamenti Climatici (CMCC-CM) and Community Earth System Model Contributors CESM-BGC models (Fifth assessment report Intergovernmental Panel on Climate Change, IPCC) is investigated. In the present study, the method of micrometric factor conversion for the period 1979 to 2005 for calibration of these models and from 2006 to 2017 to measure the accuracy of the models is used. In the following, these models are used to predict the parameters of precipitation and temperature in the upcoming period (up to 2100). Among these models, BCC-CSM 1.1 has four climatic scenarios including Representative Concentration Pathways (RCPs) RCP 2.6, RCP 4.5 and RCP 6.0 and RCP 8.5, and CMCC-CM and CESM1-BGC models have two RCP 4.5 and RC P6.0 scenarios. According to the IPCC's fifth report, each of these scenarios has different concentrations of greenhouse gases in predicting the future climate. The results show that the BCC-CSM 1.1 model with a mean absolute relative error (MARE) of 2.619 has the best performance in rainfall estimation and the CESM1-BGC model with MARE of 1.467 has the best performance in evaluation of the minimum temperature and CMCC-CM model with MARE equal to 0.287 and, 0.115 showed the best performance in estimation of the average and maximum temperature. Considering that the issue of climate change and its impact on all climatic parameters such as precipitation and temperature can affect different aspects of human life, by using these models and determining the efficiency of each in estimating its specific climatic component of the model can be useful step by step in planning and managing the region.
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