In this study, precipitation simulated annual and seasonal in East and North-East of Iran ,in 1987-2011, by using RegCM4 dynamic model in two case; with and without using post-processing technique. The required data for RegCM4 model with NetCDf format, received from ICTP center. For the implementation of the main dynamic model, Convective precipitation test scheme and the horizontal resolution, performed for 2007. According to the test, Kuo Schema had less error than Emmanuel and Gurl schemes in Precipitation and region temperature modeling. Horizontal resolution selected 30 Km. After model implementation with Gurl schema and 30 Km horizontal resolution, Precipitation and temperature output post- processed using MA model. According to results, in the study area, during 2006-2011 verification period, average annual rainfall raw bias of RegCM4 model was calculated and post-processed equal to 8.3 millimeter and 61.04 respectively. Briefly in the annual time scale, in 75% of studied stations, post-processing is effective and MA model is more efficient. In seasonal scale, bias error of average precipitation is equal to 54.99 millimeter in the winter, 27011 millimeters in the spring, -3.6 millimeter in the summer and 7.21 millimeter in the fall. Simulation of the temperature data in the stations using RegCM4 and MA model in north-east of Iran, revealed high performance. Bias error of average temperature is equal to -2.78 for RegCM4 model and post-processed equal to -0.05. In all stations, modeled Annual temperature and observational data has difference less than 0/1 ° C. In seasonal scale, the mean bias error range according ° C is equal to -4.1 in the winter, -4.09 in the spring, -1.8 in the summer and -1.5 in the fall.