Abstract: Dynamical downscaling is widely applied in regional climate downscaling to generate regional climate fields with high spatial-temporal resolution.Using the nudging techniques based on the Weather Research and Fore-casting (WRF) model,Climate Forecast System Reanalysis (CFSR) data were dynamically downscaled over Liaoning province.The observational data from automatic weather stations were assimilated based on the observation nudging method and the large-scale reanalysis data were assimilated based on the analysis nudging method.Meteorological elements determined by different downscaling methods were compared with the observations in Liaoning province during July and October to test the accuracy of each method.The results indicated that the modelling capability of temperature at 2 m height,wind speed at 10 m height,and relative humidity at 2 m height is significantly improved using nudging methods in the regional climate downscaling process.The simulation performance be-comes even better after assimilating automatic weather station data and the large-scale reanalysis data based on the nudging methods,with the average root-mean-square error of temperature,wind speed,and relative humidity in July and October decreasing by 25%,39%,and 30% respectively.