A mesoscale, real-time four-dimensional data assimilation and short-term forecasting system (RTFDDA) has been developed at NCAR. Built upon a high-resolution MM5, the RTFDDA system continuously assimilates available observations from various sources and provides updated 3-dimensional analyses and short-term forecasts every 3 hours. The system is now being adapted for real-time, short term forecast of snowbands in the airport terminal area by adding a radar data assimilation component.

In this work, feasibility of using the RTFDDA system for snowband forecasting is investigated. Techniques that can effectively assimilate real-time radar data into MM5 are explored. Case studies are conducted for snowstorm events that occurred in northeastern U.S. Both Level 2 and Level 3 WSR-88D radar observations are assimilated. A series of forecasting experiments are conducted to search for the optimal strategies for radar data assimilation in an operational setting. Results from these experiments will be presented at the conference.