Enhancement of the daytime GOES-based aircraft icing potential algorithm using MODIS
Alexander, Jeremy Brandon
Durkee, Philip A.
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In this thesis, a fuzzy logic algorithm is developed for the detection of potential aircraft icing conditions using the Moderate-Resolution Imaging Spectroradiometer (MODIS). The fuzzy MODIS algorithm is developed in a manner similar to the cloud mask currently used to process MODIS imagery. The MODIS icing potential detection algorithm uses thresholds for 8 channels in a series of 12 tests to determine the probability of icing conditions being present within a cloud. The MODIS algorithm results were compared to results of the GOES icing potential detection algorithm run on MODIS imagery for 4 cases. When compared to positive and icing pilot reports for the cases, the MODIS algorithm identified regions where icing was encountered more effectively than the GOES algorithm. Furthermore, the use of fuzzy thresholds on MODIS rather than the hard thresholds of the GOES algorithm allowed for less restrictive coverage of potential icing conditions, making the MODIS algorithm more reasonable in assessing all cloud regions for icing potential. The results found here are preliminary, as further statistical analysis with a larger validation dataset would be more effective. Algorithm details are provided in the appendix for reference.
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