Enhancement of the Daytime MODIS Based Aircraft Icing Potential Algorithm Using Mesoscale Model Data
NAVAL POSTGRADUATE SCHOOL MONTEREY CA
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In this thesis, MM5 mesoscale model data are examined to determine its utility in enhancing satellite based aircraft icing analysis. The algorithm by Alexander 2005 was used to process MODIS imagery on four separate storms in January 2006, and his algorithm was validated using 133 positive and negative pilot reports PIREPs. MM5 mesoscale model soundings were then analyzed to determine the temperature T and dewpoint temperature Td at the altitude and location of each PIREP. Relative humidity RH was calculated, and fuzzy logic used to determine the aircraft icing potential associated with the T and RH model based parameters through the use of operational Current Icing Potential CIP T and RH interest maps, and the T interest map used in Alexanders algorithm. Model icing potential was calculated using 16 different methods, and it was found that weighting RH more in the calculation added the most value to the MODIS based algorithm. It was also found that the Alexanders T interest map added value to the MODIS based algorithm in every case, while the CIP based T interest map only added value when RH was weighted higher.
- Military Aircraft Operations
- Safety Engineering