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Satellite-based remote sensing has long been recognized as an important method to reconnoiter oceanic tropical cyclones due to the scarcity of in situ observations. Beyond the standard qualitative applications offered by imagery, algorithms are being developed to process the information-wealthy imagery into quantitative parameters necessary to positively impact objective analyses on which numerical track predictions are initialized. Techniques developed at the University of Wisconsin Cooperative Institute for Meteorological Satellite Studies enable the automated extraction of displacement vectors from animated imagery featuring sequential geostationary satellite multispectral observations of clouds and water vapor. Recent upgrades to these algorithms and a focused processing strategy directed toward optimizing the retrieved wind vector coverage are discussed. In combination with advanced sensing technology afforded by the National Oceanic and Atmospheric Administration’s latest generation of geostationary meteorological satellites, GOES-8, superior vector yield and quality are being realized. In this set of two papers, datasets produced during the 1995 Atlantic hurricane season are examined for their impact on tropical cyclone analyses and numerical track forecasts. In Part I, the wind retrieval methodology and data characteristics are described, along with a brief discussion of the tropical cyclones selected for study. Part II addresses the input of the GOES-8 wind information into a global data assimilation system, and the resultant impact on numerical track predictions.
Velden et al. (Fri,) studied this question.