Using statistical downscaling methods has been increased because the dynamic models are time-consuming and not cost-effective. This study has compared the results of two downscaling models i.e. CCT and SDSM in simulating the daily climatic parameters including precipitation, maximum, minimum and mean temperature in the Karganrood basin in Guilan province, Iran. The meteorological data of Bandar Anzali synoptic station during 1975-2018 was used as the observation period. Then, using the CCT downscaling model, MIROC climate model, SDSM downscaling model, CanESM2 climate model, daily precipitation, maximum, mean and minimum temperature of basin were simulated and compared with RCP2.6, RCP4.5, and RCP8.5 scenarios in 2025-2050, 2051-2075 and 2076-2100, respectively. NS, R2 and RMSE were used to study the robustness of downscaling indices. Based on NS, R² and RMSE criteria, SDSM model in the exponential microscale of maximum, mean and minimum temperature and in precipitation except RMSE factor value of RCP2.6 scenario and in the next period 2076-2051 in all cases compared to CCT model with error. The results of the Mann-Kendall test showed that the changes of precipitation and temperature simulated in future periods in the CCT model were significant with the highest significance relating to RCP8.5. The results of Mann-Kendall test also showed that in precipitation and temperature in future periods in the CCT model was more significant than the SDSM model and the highest significance was related to the maximum temperature (Z = 3.22), respectively and the minimum temperature (Z = 4.14) at 95% confidence level is related to RCP8.5.