Extended Abstract:
Introduction:Climate change is considered one of the main and important threats to the environmental, economic and social. Climate change has been occurring all over the world without taking necessary measures to reduce greenhouse gas emissions and in recent years has left disastrous effects in many countries. The increase in greenhouse gases in the atmosphere due to the development of industry and increased use of fossil fuels and changes in land use in the last few decades has caused a constant eating of climate variables especially global warming. The negative consequences of this phenomenon for mankind can be destructive to the extent that among the ten threatening factors for mankind in the 21^st century, the climate change phenomenon has taken the first place.This study aims to investigate the extreme temperature and precipitation changes using the Statistical Downscaling Model to downscale the output of the MPI-ESM1-2-HR model from the GCM report under three scenarios SSP1-2.6, SSP2-4.5 and SSP5-8.5 for the next three periods of the near future, the average future and the far future in the Todeshk watershed in Isfahan.                                    
Materials and methods: In this study, to evaluate the performance of the general circulation model of MPI-ESM1-2-HR in the downscaling of maximum and minimum temperature parameters and precipitation of the Naein synoptic station in Isfahan province during 1989-2014 were used as the base period. In this model, data from 1989 to 2006 were used as the calibration and data of 2007 to 2014 were used as model validation. First, using linear regression test in SPSS software, among 26 variables of ECMWF historical data, variables that had the highest correlation with dependent variables were extracted as independent variables. Also in order to evaluate the performance of the model, goodness of fit correlation coefficient, root mean square error, nash-sutcliffe, kling gupta efficiency and taylor diagrams were used.
Results and Discussion: The results of the goodness of fit coefficient R, RMSE, NSE and KGE in the calibration and validation of the MPI-ESM1-2-HR model with the SDSM downscaling model to estimate the precipitation variables, maximum temperature and the minimum temperature of the Naein synoptic station were 0.97, 0.42, 0.96 and 0.87 respectively, which implies the high performance and accuracy of the model in modeling of climatic variables. The results showed that the output of the MPI-ESM1-2-HR model and the SDSM statistical model have high and medium performance for downscaling of maximum and minimum temperature and precipitation variable in the Naein synoptic station, respectively, and the high and average conformity between the scenario of the maximum and minimum values of the maximum and minimum temperature and the precipitation variable under scenarios SSP1-2.6 and SSP2-4.5 and SSP5-8.5 for the time periods 2015-2042, 2043-2070 and 2071-2100. The results also showed that in the MPI-ESM1-2-HR model, the average monthly precipitation amounts in the time periods 2015-2042, 2043-2070 and 2071-2100 have been reduced to 0.21, 0.22 and 0.24 mm, respectively, and the average maximum temperature values were 1.49, 1.5 and 1.52 ^oC and the mean temperature of minimum temperature will increase 0.51, 0.53 and 0.54 ^oC under scenarios SSP1-2.6, SSP2-4.5 and SSP5-8.5 respectively.
Conclusion: Since the current conditions of the world show the spread of climate change in all countries and in all continents and risks of sustainable development, international community needs to move toward environmentally compatible environments, use of clean and non-renewable energy and implementation of international standards for sustainable development including reduction of greenhouse gases. Therefore, it seems reasonable that among the scenarios evaluated in this research, the average scenario SSP2-4.5 is considered as a decision criterion for planning in order to propose a solution to deal with climate change in policy agenda of policy makers and planners.