Recent Developments With The Global Wild Fire Automated Biomass Burning Algorithm

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Wednesday, 5 February 2014
Hall C3 (The Georgia World Congress Center )
Jay P. Hoffman, CIMSS/Univ. of Wisconsin, Madison, WI; and C. C. Schmidt, E. M. Prins, and J. C. Brunner

Developed at the Cooperative Institute for Meteorological Satellite Studies (CIMSS), the Wild Fire Automated Biomass Burning Algorithm (WFABBA) product provides fire monitoring from a global constellation of geostationary satellites. Ongoing activities include expanding processing capabilities for both domestic and international current and next generation geostationary satellite platforms. With a fire archive of nearly two decades, reprocessing is ongoing as the detection algorithm evolves. Tools to manage the archive and also provide users with fire data in near real-time are being developed with a broad range of user communities in mind. Air quality modeling applications benefit from fire location and characterization information. New techniques capitalize on frequent imager coverage to reduce false alarms. By using a time-series of fire detection masks, a new fire age metadata field is under development to help assess fire detection confidence as a function of fire detections and number of observations over a time series. These changes will address a variety of user needs. Knowing the age of a fire has utility in better parameterizing fire emission sources in air quality modeling applications. For the hazards community it assists in distinguishing new fire detections from long-lasting fire detections.