Fire Detection and Monitoring with GOES-16 (301)

Chris Schmidt, CIMSS/SSEC, Madison, WI




Fire detection and characterization has been operationally available from geostationary satellites since 2002 when the Wildfire Automated Biomass Burning Algorithm (WFABBA) went into service at NOAA/NESDIS. The Fire Detection and Characterization Algorithm (FDCA), aka the WFABBA for Advanced Baseline Imager (ABI) class sensors, was a day 1 product for GOES-16. It provides six categories of detection and for the highest confidence categories it supplies fire radiative power (FRP), fire size, and fire temperature for the CONUS and full disk ABI scans. This presentation will provide a short tutorial on how satellite fire detection works and examine examples from GOES-16 of different types of fires to demonstrate the use of the product: grassland fires of the Great Plains, forest fires, fires in California, agricultural burning, and select other cases. In those examples use of the quantitative FDCA products will be compared to the use of qualitative tools like raw imagery and composites like the &ldquofire temperature RGB&rdquo to demonstrate the strengths and weaknesses of those offerings as they apply to the work of operational forecasters, broadcasters, and smoke modelers. To further understanding of what the product outputs mean, validation work will also be presented.