P1C.6
Radar Data Assimilation For Real-time Short term Forecasting of Snowbands
Mei Xu, NCAR, Boulder, CO; and N. A. Crook, Y. Liu, and R. M. Rasmussen
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.
Poster Session 1C, Radar Data Assimilation Poster
Wednesday, 6 August 2003, 1:30 PM-3:30 PM
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