THE IMPACT OF MULTISPECTRAL GOES-8 WIND INFORMATION ON ATLANTIC TROPICAL CYCLONE TRACK FORECASTS IN 1995 - PART I - DATASET METHODOLOGY, DESCRIPTION, AND CASE ANALYSIS

Satellite-based remote sensing has long been recognized as an importan t 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 info rmation-wealthy imagery into quantitative parameters necessary to posi tively impact objective analyses on which numerical track predictions are initialized. Techniques developed at the University of Wisconsin C ooperative Institute for Meteorological Satellite Studies enable the a utomated extraction of displacement vectors from animated imagery feat uring sequential geostationary satellite multispectral observations of clouds and water vapor. Recent upgrades to these algorithms and a foc used processing strategy directed toward optimizing the retrieved wind vector coverage are discussed. In combination with advanced sensing t echnology afforded by the National Oceanic and Atmospheric Administrat ion's latest generation of geostationary meteorological satellites, GO ES-8, superior vector yield and quality are being realized. In this se t 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 a nd data characteristics are described, along with a brief discussion o f the tropical cyclones selected for study. Part II addresses the inpu t of the GOES-R wind information into a global data assimilation syste m, and the resultant impact on numerical track predictions.