The impact of satellite winds on experimental GFDL hurricane model forecasts

A series of experimental forecasts are performed to evaluate the impact of enhanced satellite-derived winds on numerical hurricane track predictions. The winds are derived from Geostationary Operational Environmental Satellit e-8 (GOES-8) multispectral radiance observations by tracking cloud and wate r vapor patterns from successive satellite images. A three-dimensional opti mum interpolation method is developed to assimilate the satellite winds dir ectly into the Geophysical Fluid Dynamics Laboratory (GFDL) hurricane predi ction system. A series of parallel forecasts are then performed, both with and without the assimilation of GOES winds. Except for the assimilation of the satellite winds, the model integrations are identical in all other resp ects. A strength of this study is the large number of experiments performed . Over 100 cases are examined from 11 different storms covering three seaso ns (1996-98), enabling the authors to account for and examine the case-to-c ase variability in the forecast results when performing the assessment. On average, assimilation of the GOES winds leads to statistically significant improvements for all forecast periods, with the relative reductions in trac k error ranging from similar to5% at 12 h to similar to 12% at 36 h. The pe rcentage of improved forecasts increases following the assimilation of the satellite winds, with roughly three improved forecasts for every two degrad ed ones. Inclusion of the satellite winds also dramatically reduces the wes tward bias that has been a persistent feature of the GFDL model forecasts, implying that much of this bias may be related to errors in the initial con ditions rather than a deficiency in the model itself. Finally, a composite analysis of the deep-layer flow fields suggests that the reduction in track error may be associated with the ability of the GOES winds to more accurat ely depict the strength of vorticity gyres in the environmental flow. These results offer compelling evidence that the assimilation of satellite winds can significantly improve the accuracy of hurricane track forecasts.