Abstract: In the operation of climate forecast, scoring methods of PS, SS, ACC are widely used. Among them, SS and ACC, known as technique scores, are defined as the similarity between forecast and realistic results when comparing with non technique forecasts or the expectations of non technique forecasts equal to zero. The technique scores are basically originated from the evaluations in the forecast results from different populations and thus provide a basis for impartial comparisons. However, PS is considered as the concordance of forecast grades and are not compared with technique scores, so PS is not technique scores. In China, PS is of greater importance in climate forecasts. The PS of short term climate forecasts by each province are performed every year in the China Meteorological Administration and the ranks of monthly precipitation, mean temperature and total forecasting ability are released. The impact of present PS method used on the climate forecast is analyzed. The results show that the theoretical PS is a score of consistence rate based on accurate forecasts on the grades; the foundational requirement of the PS inter comparison is that they share the same probability distribution in ranking. Through comparisons between the present and theoretical PS method, it's also found that the present scoring method is taken as the theoretical scoring method with two modifications which makes the present PS method actually become the concordance of weighted anomalies. The first revision has extended the range of forecast accuracy assessment, in which level 1, 2, 5 and 6 have extended to three grades, level 3 and 4 have extended to four grades, and weight coefficients are added for abnormal grades. However, only two grades are forecasted in climate operational forecast after PS method performs. Based on the examples of the annual precipitation extremes occur in Shaanxi Province, the random forecasts on level 2 and 6 are evaluated and compared. The results show that 2 level forecasts can score higher, while reducing the forecast capability. Another revision is to divide the grades based on the uniform anomalies of elements, which leads to the forecast grade distributions varying between the stations and months. The distribution of forecast grades of is the dominant factor of non technique forecasting scores. Moreover, the forecasting skill is actually determined by the differences between PS and non technique prediction scores. In the cases of different non technique forecasting scores, the foundation for comparisons becomes less stable to use PS in different months and stations. Some suggestions are introduced to the prevailing PS method to solve these problems.