Satellite-derived ocean surface winds in recent years have provided an unprecedented view of oceanic storms. While some ocean surface wind data are being used operationally (SSMI, QuikSCAT) in global and regional models, the relative impact of these data sets is still largely unexplored for many data assimilation systems and forecast models, particularly for newer instruments, like WindSat, that are not yet used operationally. In this study, coordinated assimilation experiments examine the impact of ocean surface winds on hurricane forecasting by both global and regional models (GEOS5 and WRF, respectively) to examine the impact of these data sets on hurricane forecasting.

Cycling data assimilation experiments using combinations of ocean surface wind data sets with GEOS5 are used to supply first guess fields and lateral boundary conditions for regional assimilation and forecast experiments with the WRF. Specifically, we have examined impacts on forecasts of hurricanes Katrina and Ophelia (2005). Katrina is a forecast challenge for storm intensity, whereas Ophelia moved erratically at times and is a forecast challenge for storm track. We will compare and contrast results from the global experiments (GEOS5) and the regional experiments (WRF), using forecast hurricane track and intensity errors as the primary metrics to assess the relative impacts of SSMI, QuikSCAT and WindSat data. We also examine the effect of these data on the physical structure of hurricanes in the analyses and forecasts. Early results indicate that ocean surface winds, assimilated into a global model, can exert considerable influence on regional hurricane forecasts through the influence on the regional model's lateral boundary conditions.