Based on the observations of daily snowfall,precipitation,temperature,relative humidity,air pressure and wind speed in China,a distinguishing method for the snowfall events based on the Logistic regression approach is constructed,and the applicability of this method and other widely used snowfall distinguishing methods is compared.Results show that the single temperature threshold and S-curve methods are relatively uncertain for snowfall simulation within the temperature range from -3 ℃ to 4 ℃.By contrast,the series of Logistic fitting methods have higher success rates in determining snowfall events,and are more robust for snowfall recognition in different regions of China,especially in the Tibetan Plateau.In the Logistic methods,temperature and relative humidity play a decisive role in determining snowfall,while the influences of air pressure and wind speed are relatively small.The Logistic wet-bulb temperature scheme (LogT_w) and the air temperature+relative humidity scheme (LogT_aH_R) can well reproduce the spatial distribution and interannual variation characteristics of snowfall,and the corresponding deviationsare smaller than other methods.On the whole,there is little difference between the two schemes for snowfall recognition.Therefore,the LogT_w or LogT_aH_R scheme can be used to identify snowfall events in China,especially the snowfall events in climate models.