15.5 Fire Detection in the Age of GOES-R

Thursday, 26 January 2017: 2:30 PM
Conference Center: Yakima 2 (Washington State Convention Center )
Christopher C. Schmidt, CIMSS, Madison, WI

Geostationary fire detection and characterization has been available 24/7 since 2002 when the Wildfire Automated Biomass Burning Algorithm (WFABBA) was made an operational product by NOAA/NESDIS (National Oceanic and Atmospheric Administration/National Environmental Satellite, Data, and Information Service).  The WFABBA produces fire location and characterization data for all data received from current GOES, as well as Meteosat Second Generation, COMS, the formerly operational MTSAT series, and most recently the Advanced Himawari Imager (AHI) on Himawari-8.  The experience with current generation geostationary platforms informed the requirements for the Advanced Baseline Imager (ABI) on GOES-R, and the WFABBA was adapted to the instrument and is a baseline product (under the name Fire Detection and Characterization Algorithm [FDCA]).  The WFABBA’s legacy as an algorithm for multiple instruments allows for excellent continuity as we transition to the new generation of geostationary imagers represented by ABI and its fraternal twin, AHI.  AHI data has allowed for extensive testing of the WFABBA prior to the launch of ABI, which has improved the performance of the algorithm for ABI and other platforms that it runs on.  Experience with AHI has led to algorithm updates, particularly in the realm of addressing solar reflection, that address the new challenges created by the platform as well as solving some old problems that were leading to numerous false detections.  Algorithm changes due to and lessons learned from AHI, as well as validation tools developed for GOES-R, will be presented.
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