The potential for advanced data assimilation techniques to improve model analyses at the mesoscale is gaining broad acceptance. Currently, one of the greatest challenges facing numerical weather prediciton at this scale is the problem of tropical cyclone intensity and rainfall prediction. The Wisconsin ENsemble Data Assimilation System (WENDAS) has been created to address this problem. With WENDAS we seek to assimilate not only conventional observations, but those from spaceborne platforms as well, including all geostationary and most low-earth orbiting satellites.

Here we employ an ensemble Kalman filter (EnKF) to examine the impact of microwave satellite observations on the analysis and subsquent forecasts of two Gulf of Mexico hurricanes, Rita and Wilma (2005). In particular, the impact on intensity and rainfall prediction will be assessed by performing sets of experiments both with and without the microwave data and then comparing the forecast fields with observed intensity and rainfall metrics from reconnaissance aircraft, satellite and ground-based stations.