High-resolution satellite data assimilation and its role in tropical cyclone prediction

Results from the recently completed High-resolution Hurricane test (HRH) indicate that improving tropical cyclone intensity forecasts will require somewhat more than a simple increase in a model's horizontal resolution. Indeed, increased vertical resolution, improved model physics and data assimilation all will likely play roles in overcoming current barriers to forecast improvement. In this study, we turn our attention to the latter. In particular, we focus on the role of high-resolution satellite data from both geostationary and low-earth orbiting platforms. We use the University of Wisconsin Nonhydrostatic Modeling System (UW-NMS) and an ensemble Kalman filter (EnKF) to assimilate conventional, aircraft and satellite observations for hurricane Rita over its entire life cycle. We examine the relative impact of the various data types and demonstrate the crucial importance of high-resolution satellite data in obtaining optimal representation of the hurricane vortex and its environment. These results will be compared to results obtained from the UW-NMS during HRH. The implications for hurricane prediction in a probabilistic framework will be discussed.