Climate is a complex system that is affected by changes in climatic parameters. By predicting and examining the range of changes in meteorological parameters in the future, it is possible to adopt appropriate solutions to reduce the harmful effects of climate change. Using atmospheric general circulation models is the most reliable method. In this study, precipitation, maximum and minimum temperatures of five synoptic stations of Birjand, Qaen, Nehbandan, Ferdows and Tabas, for the base period of 1988 to 2005 as well as the outputs of six climate models of CanESM2, GFDL-CM3, CSIRO-MK3, MPI-ESM - LR, MIROC-ESM and GISS-ES-R, were collected under RCP8.5 and RCP4.5 emission scenarios for a 16-year period (2020-2035) and downscaled using the LARS-WG5.0 model. Then, using the RMSE and MAE statistical indices, the quality of the down-scale representation was evaluated. Afterwards, by calculating the climate classification indices of De Martonne and Amberger, the province was classified with the help of GIS software. De Martonne classification indicates that the climate of the province will not change in the near future compared to the base period while based on the classification of Amberger and under all six models and both scenarios, Birjand, Qaen and Ferdows cities are predicted to have temperate climate and Tabas city is expected have a hot and mild desert climate. For Nehbandan city, the GFDL-CM3, CSIRO-MK3 and GISS-ES-R models of the fifth report under the RCP4.5 scenario predicted a moderate climate and the rest of the large-scale models predicted a moderate desert climate.