Aiming at future operational implementation, the research on assimilation of wind profiling radar (WPR) data into the GRAPES_Meso model (Global/Regional Assimilation and Prediction System) is carried out. Based on observational WPR datasets in China during July 2015, a two-step quality control (QC) procedure is developed first. The differences between the ERA-Interim reanalysis data and the WPR observational data before and after QC are calculated, respectively. Results show that the wind field errors are largely reduced after QC, and the distributions of the innovations corresponding to observations after QC are closer to a Gaussian distribution. Based on the GRAPES-3DVAR system, the WPR observations after QC were used in one-month continuous experiments as well as a real-case study to illustrate the influence of WPR observations on GRAPES_Meso model. Results show that the assimilation of WPR data can improve the initial condition of the model. Analysis errors of wind, temperature and humidity field are reduced, and the prediction skill for short-term precipitation (0-12 h) is improved. The impact of assimilating WPR data on the analysis and forecast of typhoon “Linfa” is also investigated in this study. Results show that assimilating WPR data can effectively adjust the dynamic structure and water vapor condition over the typhoon precipitation area, producing a more favorable condition for the development of convective system and improving the forecast skill of precipitation.