Reliable numerical forecasts of hurricane tracks are dependent upon having accurate wind observations to initialize the model. Recently, advances in remote sensing techniques have led to increased volumes of wind observations over oceanic areas void of conventional data. In particular, efforts have focussed on deriving wind vectors in hurricane environments from tracking atmospheric motions in GOES multispectral imagery. This study examines the impact of the GOES wind observations on the GFDL hurricane model track forecasts for selected cases in the 1995-1997 Atlantic seasons.
A series of experimental forecasts were performed in which the GOES winds were directly assimilated into the model analysis using a 3-dimensional optimal interpolation. Forecasts of these integrations are compared to operational forecasts in which the high-density GOES winds were not being assimilated.
Preliminary results show the direct assimilation of the GOES winds leads to reduced track forecast errors, particularly for the later forecast periods. The reductions in track forecast error increase linearly from nearly 5 percent at 12-24 hours to over 25 percent at 72 hours. The greater improvement at longer forecast intervals suggests that the influence of the GOES wind data on the analysis is most beneficial to resolving the storm environment. The winds helping to define the near storm circulation may require special treatment and this will be further investigated. Results from a more extensive investigation covering the 1995-1997 seasons will be presented at the conference