248 Climatological assessment of aircraft icing conditions and associated cloud properties derived from satellite data and icing PIREPS

Monday, 7 January 2013
Exhibit Hall 3 (Austin Convention Center)
Cecilia Fleeger, SSAI, Hampton, VA; and W. L. Smith Jr., P. Minnis, D. A. Spangenberg, R. Palikonda, and F. L. Chang

Handout (3.8 MB)

An algorithm to determine the flight icing threat to aircraft has been developed for application to cloud parameters retrieved from operational satellite data. Cloud optical and microphysical properties derived from Geostationary Operational Environmental Satellite (GOES) data for up to two cloud layers are used to determine the probability for icing in two intensity categories. Icing altitude boundaries are also determined from satellite estimates of cloud top height and base, and knowledge of the freezing level obtained from numerical weather analyses. Two version of the algorithm are run routinely at NASA Langley Research Center. One, works for low-level single layer clouds, while the other works in some multi-layered cloud conditions, namely the cases where high thin clouds overlap lower level boundary layer clouds. More information can be derived during the daytime using solar reflectance methods than at night with infrared channels alone. The purpose of this study is to perform a climatological summary of icing conditions derived from satellite data in single and multi-layered cloud systems and to compare that assessment with one derived from icing PIREPS. One year of GOES data are analyzed over the CONUS, and the results stratified by day/night. We also correlate the icing PIREPS with the satellite analyses to characterize the cloud properties associated with icing PIREPS and to help quantify the accuracy and utility of the satellite icing analyses under various cloud conditions. The results should help improve our understanding of the benefits and limitations associated with current satellite-based icing diagnoses, and help guide future improvements, particularly for advanced satellite sensors, such as the GOES-R Advanced Baseline Imager, scheduled for operational use in 2017.
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