The change in the precipitation pattern, along with the temperature changes, is one of the most important changes in climate change. The first step in climate change studies is to estimate the prospects of climatic and hydrological data such as temperature and precipitation in the future period (climate scenarios). The most important issue is the spatial mismatch of the outputs of these models with the modern scale of the areas. The difference in accuracy of downscaling methods can cause differences in simulation results. This provides the opportunity to check the accuracy of the downscaling methods. In this research, the GCM and CanESM5 models from the sixth report of the International Panel on Climate Change (IPCC) and the two downscaling models SDSM and the statistical bias correction method (BSCD) The purpose of exponential micro-scale and simulation of minimum and maximum temperature is used to know in advance the amount of changes of these parameters under two scenarios of SSP2.45 and SSP5.85 for the period of 1990-2020. The results showed that the SDSM model has a better performance than the BCSD method in simulating the minimum and maximum temperatures. The comparison of annual minimum and maximum temperature changes shows that the minimum annual temperature will increase in the future period under each scenario compared to the base period (1990-2023), and the maximum temperature will also increase in most years in the future period compared to the base period. The average minimum monthly temperature in all months in the future period will increase compared to the base period. Also, the maximum monthly temperature changes in all months except April, September and November are incremental