Ocean-surface wind impacts on hurricane forecasting, regional and global

Satellite-derived ocean surface winds provide the most complete view of winds around tropical cyclones for operational use. Some of these ocean surface wind data are used operationally (SSMI, QuikSCAT, ASCAT) in global and regional forecast models, but the impact of these data sets is known to be variable from one case to the next. In this study, coordinated assimilation experiments examine the impact of ocean surface wind data on forecasting hurricanes by both global and regional models (GEOS5 and WRF, respectively).

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 Gustav, Hanna and Ike (2008). 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 data impacts. Our results show considerable variation case by case, and we focus our analysis on the merits of the improved cases and the causes of the poorer performance in the degraded cases. Through this analysis, we seek to improve the routine use of these valuable data sets in global and regional models.