Abstract:Precipitation type is often complicated when the ground temperature alternates between 0℃,and the its prediction has been one of the major difficulties in weather forecasting for many years.In this paper,four diagnostic methods are used to study the precipitation types,by examining the vertical temperature structure to be encountered by a falling hydrometeor,so as to diagnose a single type when the ground is reached.The four methods are the BTC algorithm,revised BTC algorithm,Ramer algorithm and Bourgouin algorithm.According to the ability of the mini-ensemble,the results with the majority of the algorithm/s outputs and more dangerous winter weather are integrated as the final precipitation type,including rain,snow,freezing rain and hail.The GRAPES_MESO mesoscale model is used to provide the parameters that the four diagnostic algorithms require.Next,the precipitation type's products are verified by two winter precipitation cases.Compared with the observation,it is shown that the revised BTC algorithm can correct the diagnostic bias of the original BTC algorithm for snowfall,and less hail is forecasted than when using the original algorithm.The Ramer algorithm obtains a greater number of freeze-rain events than several of other algorithms.The Bourgouin algorithm is closest to the results of the synthesis algorithm.Therefore,it is shown that the four schemes can reasonably predict the boundary line of rain and snow,as well as the areas of rainfall and snowfall.However,the scheme intentionally over-predicts hail and freezing rain,viewing these two types as more dangerous varieties of winter weather.
The results are directly related to the accuracy of the forecasted temperature profiles and precipitation areas in the model.These diagnostic schemes can only determine one type of precipitation,but cannot diagnose the sleet,thus at the junction of rain and snow there are a greater number of intermediate phases such as hail and freezing rain.The final integrated precipitation type of the four schemes shows the high probability and high influence of the various precipitation types,thereby providing effective warning information for disaster prevention and mitigation.