For precipitation forecast products with different methods and time, a large number of evaluation results often exist together. At present, we’re still lacking effective measures on how to analyze comprehensively and systematically these results. In this study, the agglomerative hierarchical cluster analysis is introduced to classify and analyze the different evaluation results of different forecast products, based on a grid precipitation forecast dataset of each member of the national forecast technology and method competition of CMA from June to September 2019, the central station guide forecast (SCMOC) of the National Meteorological Center, the seamless analysis and forecasting leading-edge system forecast of Chinese Academy of Meteorological Sciences and objective forecast products of 31 provinces (municipalities and autonomous regions)， the global modelforecast of ECMWF (European Centre for Medium-Range Weather Forecasts) and NCEP (National Centers for Environmental Prediction). The results show that the agglomerative hierarchical clustering results can clearly distinguish their similarities and differences between different forecast products. The different evaluation indicators lead to different clustering results, but the forecast products with high similarity are still divided into a same subclass. The identification effect of four different inter-class similarity measurement methods on categories characteristics was different, and the Ward method was followed by Complete, Average and Single method from clear to fuzzy. In addition, the precipitation prediction ability for different administrative regions and forecast products was different, the accuracy of rain probability forecast in North China and East China was better than that in other regions, and most objective forecasts to rain probability and precipitation relative error were better than model forecast of ECMWF, while they to heavy precipitation were worse than ECMWF model, there are still greater difficulties in interpretation to heavy precipitation forecast.

The dates of the first soaking rainfalls in the south and middle parts of Ningxia were forecasted statistically by using the optimal subset regression method, the forecast equation was set up and it king rainfall in the regions in recent 30 years was discussed in detail effect was analyzed, and the(hange of the dates of the first soarainfall is 23.3% in April, 23.3% in May, and 33 Results show 3 %  in .Tune that the occurrence in Yinc;huan region
probability of the first soaking ，during the last 30 years the dates of the first dates of the first Apri1,20% and tinn fnr the dates   in March, 20% soaking rainfalls were later in 1970x, earlier in 1980x, and medium in 1990s between that in 1970s and 1980x.  The soaking rainfall(onc;entrated relatively in southern mountain areas of Ningxia, the probability of o<(urrenc;e is 53% in 17% in May and Marc;h,and only 10% in June, and it is found that there is a slight trend of postponing with fluc;tuaof the first soaking rainfalls in this region in recent 30 years. The effect of forecast using the optimal subset regression method for the date of the first soaking rainfall is good in  Ningxia