The precipitation neighborhood ensemble probability method is a new method to deal with the uncertainty of high-resolution ensemble forecast. Based on the 24 h accumulated precipitation data of May to July 2017 of GRAPES (Global and Regional Assimilation and Prediction Enhanced System) regional ensemble forecast system, experiments of precipitation neighborhood ensemble probability method were carried out. Moreover, aiming at the equal weight and neighborhood scale problems of the neighborhood probabilistic method, two kinds of weight correction schemes (weight correction neighborhood scheme and binary weight correction neighborhood scheme) were designed. Meanwhile, the grids correlation and sensitivity experiments of four groups of precipitation probability forecasts were implemented using the ensemble probability forecast, equal weight neighborhood ensemble probability method, weight correction neighborhood ensemble probability method, and binary weight correction neighborhood ensemble probability method. The results of precipitation probability prediction were verified by multiple probability scores, which showed that: (1) The precipitation probability scores of the neighborhood calculation scheme are superior to the original ensemble probability forecast method. The precipitation probability scores of the three neighborhood ensemble probability methods have their own advantages and disadvantages. For example, the relative operating characteristic area (AROC) score of the equal weight neighborhood ensemble probability method is slightly better; however, the higher reliability of precipitation probability prediction is determined by the weight correction neighborhood ensemble probability method and the binary weight correction neighborhood ensemble probability method. (2) The forecast skill of the precipitation neighborhood ensemble probability methods is very sensitive to the neighborhood scale. The optimal neighborhood radius is 5-8 times the horizontal grid scale of the model. (3) The two neighborhood ensemble probability methods combined with weight correction largely improved the forecast skill of the threshold by over 10 mm in 24 hours and provided more objective probability forecast results. Generally, the precipitation neighborhood ensemble probability method has good application values. By selecting the appropriate neighborhood probability method and the neighborhood radius, more objective prediction results can be obtained.