Satellite derived cloud products for use in aviation safety applications

The Advanced Satellite Aviation weather Products (ASAP) initiative represents a collaboration between NASA, the FAA Aviation Weather Research Program (AWRP) Product Development Teams (PDTs), the University of Alabama-Huntsville (UAH), and the University of Wisconsin Cooperative Institute for Meteorological Satellite Studies (UW-CIMSS). This initiative has sought to make satellite derived cloud and weather products available to the PDTs for integration into forecasting algorithms for the aviation community. This paper will describe, specifically, the satellite derived cloud products currently being produced by CIMSS for this purpose. Cloud amount, cloud top temperature, and cloud top pressure are available over the CONtinental United States (CONUS) at high temporal resolution. These are derived using geostationary data from the Geostationary Operational Environmental Satellite (GOES) 10 (Western United States) and 12 (Eastern United States) imager and sounder instruments. The products are derived using a multi-spectral approach, utilizing the specific spectral information provided by each instrument. A validation study will be presented that compares these satellite derived products to in-situ aircraft data from the Atlantic THORPEX Observing Systems Test (ATOST).

In addition to the CONUS cloud products, cloud amount and cloud top pressure are also available globally, and are derived using data from a suite of meteorological satellites including GOES, METEOSAT (Meteorological Operational Satellite), GMS (Geostationary Meteorological Satellite), AVHRR (Advanced Very High Resolution Radiometer), and MODIS (Moderate Resolution Imaging Spectroradiometer). High temporal resolution geostationary data are used in the tropics and mid-latitudes, while AVHRR and MODIS are used to complete coverage over the polar regions. This product uses a single wavelength (11 micron) to determine cloud/no cloud classifications globally. This technique is particularly useful for sensing clouds at high and mid-levels, however, may miss low clouds and fog. Cloud top height is determined by comparing the 11 micron brightness temperature to a model temperature profile. These data are expected to have the greatest utility over oceanic regions, where the lack of ground based data is prohibitive to aviation forecasting.