Development of a Discriminant Analysis Mixed Precipitation (DAMP) forecastmodel for mid-Atlantic winter storms

The frequency of "wintry mix'' precipitation-freezing rain and ice pellets- is considerable in the mid-Atlantic region of the United States. Despite th e fact that the general conditions necessary to support the various winter precipitation types have been known for years, in that region, the proper f orecast of type and duration of winter precipitation is one of the most dif ficult challenges in operational meteorology, with extensive public safety and economic ramifications. The purpose of this project is to report on an improved methodology for winter precipitation forecasts. This study analyzed precipitation type and surface temperature data from NO AA's hourly surface airway observations and temperatures and heights for al l mandatory and significant levels from NOAA's Radiosonde Data of North Ame rica from Washington Dulles International Airport, Virginia (1962-95), and Greensboro, North Carolina (1948-95). Precipitation that occurred within 2 h of a sounding for the months November through March was used for analysis . The upper-air data were combined to create vertical temperature profiles for each observation of precipitation type-rain, freezing rain mix, ice pel lets, and snow. Those profiles were then categorized by the number of freez ing levels (i.e., the number of times the sounding crossed the 0 degreesC i sotherm) and examined to determine if they could be used to isolate specifi c precipitation types and as a result segregate winter precipitation scenar ios by forecasting difficulty. Four basic temperature profiles were found for both Greensboro and Washingt on Dulles Airport during winter-zero, one, two, and three or more freezing level(s). Each of these profiles produced characteristic types of precipita tion (snow, freezing rain, freezing rain mix, and rain); for each profile, either climatology or discriminant analysis was used to statistically deter mine precipitation type. The results of these analyses were used to develop the site-specific Discri minant Analysis Mixed Precipitation (DAMP) models for Greensboro and Washin gton Dulles Airport. The variables required to run the model are the height ( s) of the freezing level( s) and critical temperature( s) from a modeled or observed sounding. The DAMP models are easy for the forecaster to use an d understand and provide probability guidance in situations that are diffic ult to resolve. The overall classification results showed that the models were very effecti ve for predicting precipitation type. Probabilities of detection were 98.4% , 85.8%, and 92.6% for rain, freezing rain mix, and snow, respectively, for Washington Dulles Airport, and 98.7%, 87.1%, and 89.7% for Greensboro.