Classification of precipitation types during transitional winter weather using the RUC model and polarimetric radar retrievals

Dual-polarization radar observations have great potential for nowcasting of winter storms as this type of radar has the ability to distinguish between precipitation types. Yet, the operational version of the hydrometeor classification algorithm accepted for polarimetric WSR-88D is primarily focused on warm season weather and was tested mainly for summer-type storms. There is a need to modify and generalize the existing classification routine to address the issues of transitional winter weather such as detection of freezing rain and discrimination between rain, ice pellets / sleet, and different types of snow.

In this study, an experimental version of a winter precipitation classifier is developed and tested for a high-impact storm on 11/30/2006 in central Oklahoma. The storm produced a sequence of convective rain, freezing rain, and ice pellets, followed by wet and dry snow with variable density.

The algorithm uses a combination of high-resolution, operational numerical model analyses of temperature and humidity and vertical profiles of reflectivity, differential reflectivity, and cross-correlation coefficient measured by the S-band KOUN radar operated by NSSL. Results of the precipitation classification are validated and confirmed with the data recorded by surface ASOS stations and 2D video disdrometer.

The algorithm performed well and was especially useful in areas where the melting level was below the lowest beam elevation: a location where radar data alone are insufficient to determine precipitation type.