The GOES-R ABI Wild Fire Automated Biomass Burning Algorithm development activities at CIMSS

Work continues at the Cooperative Institute for Meteorological Satellite Studies (CIMSS) to continue and enhance the legacy of the Wild Fire Automated Biomass Burning Algorithm (WF_ABBA) by adapting it to utilize the capabilities of GOES-R ABI. At CIMSS, GOES-R ABI fire product development focuses on active fire detection and sub-pixel characterization, including fire radiative power (FRP) and instantaneous fire size and temperature. Cases of simulated data from MODIS data reprojected to simulate ABI have been generated and processed with the GOES-R WF_ABBA. Ongoing work at CIMSS and collaborations with CIRA (Cooperative Institute for Research in the Atmosphere) have resulted in model simulated ABI proxy fire data sets. Various complex issues regarding fire detection and characterization are being addressed at CIMSS. Defining precision and accuracy requirements on fire detection and fire characterization is a fundamental challenge in fire validation because even when model ground-truth exists, point-spread function effects drive the error budget. Another area of pioneering work is the study of signal bias as an artifact of pixel saturation that occurs in high intensity simulated fires.