| Abstract: 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
Satellite-8 (GOES-8) multispectral radiance observations by tracking cloud
and water vapor patterns from successive satellite images. A three-dimensional
optimum interpolation method is developed to assimilate the satellite winds
directly into the Geophysical Fluid Dynamics Laboratory (GFDL) hurricane
prediction 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
respects. A strength of this study is the large number of experiments performed.
Over 100 cases are examined from 11 different storms covering three seasons
(1996–98), enabling the authors to account for and examine the case-to-case
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 track error ranging
from ~5% at 12 h to ~12% at 36 h. The percentage of improved forecasts increases
following the assimilation of the satellite winds, with roughly three improved
forecasts for every two degraded ones. Inclusion of the satellite winds
also dramatically reduces the westward 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 conditions 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 accurately 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.
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