On Updates to the ABI Fire Detection and Characterization Algorithm and GOES-17 Mitigation

Since the launch of GOES-16, the Advanced Baseline Imager (ABI) Fire Detection and Characterization Algorithm (FDCA) has been undergoing algorithm refinement and validation. The FDCA was initially based on the Wildfire Automated Biomass Burning Algorithm (WFABBA) that processes data from the generation of geostationary satellites prior to GOES-R. The algorithms allow for characterization of the highest confidence fires as well as providing other confidence levels for those with a higher tolerance for false alarms. The refinement of the algorithm has greatly improved performance in terms of reducing false alarms and validation of the fire characteristics, specifically fire radiative power (FRP), has been proceeding. Additionally, the algorithm is being adapted to manage the challenges posed by the lack of active cooling on GOES-17. Validation of ABI FDCA FRP data is complicated by the lack of ground truth data, so comparisons are made to the polar orbiting satellites that provide FRP, specifically those carrying the VIIRS and MODIS instruments. Those comparisons need to account for viewing angles and conditions, and adjust for the particular characteristics of ABI radiance data. Case studies of both well-known fires and run-of-the-mill situations processed with the latest algorithm updates will be presented.