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A set of physically based retrieval algorithms has been developed to derive from multispectral satellite imagery a variety of cloud properties that can be used to diagnose icing conditions when upper-level clouds are absent. The algorithms are being applied in near-real time to the Geostationary Operational Environmental Satellite (GOES) data over Florida, the Southern Great Plains, and the midwestern USA. The products are available in image and digital formats on the world-wide web. The analysis system is being upgraded to analyze GOES data over the CONUS. Validation, 24-hour processing, and operational issues are discussed.

Recent studies have found that high mass concentrations of ice particles in regions of deep convective storms can adversely impact aircraft engine and air probe (e.g. pitot tube and air temperature) performance. Radar reflectivity in these regions suggests that they are safe for aircraft penetration, yet high ice water content (HIWC) is still encountered. The aviation weather community seeks additional remote sensing methods for delineating where ice particle (or crystal) icing conditions are likely to occur, including products derived from geostationary (GEO) satellite imagery that is now available in near-real time at increasingly high spatio-temporal detail from the global GEO satellite constellation.