P9.14
Tracking Smoke Plumes Using GOES Imagery
Jian Zeng, ERT associated with NOAA/NESDIS/STAR, Camp Springs, MD; and S. Kondragunta
An Automated Smoke Detection and tracking Algorithm (ASDA) that automatically detects biomass burning smoke aerosols and tracks their long-range transport has been developed using satellite observations. This algorithm combines Geostationary Operational Environmental Satellite (GOES) observations of thermal enhancements due to fires with GOES Aerosol Optical Depth (AOD) imagery to identify smoke aerosol plumes produced by fires. A pattern recognition technique is applied to 30-minute GOES AOD imagery to track the smoke aerosols that are advected away from fire sources. These two steps allow separation of optical depths due to smoke aerosols from other types of aerosols. The ASDA product was applied to GOES-12 data over the contiguous United States during the 2007 fire season and to GOES-11 data in Alaska during the 2009 fire season, and evaluated using Ozone Monitoring Instrument (OMI) AOD and Aerosol Index (AI) for absorbing aerosols. Comparisons show that smoke plumes from ASDA and OMI are in agreement for large fire/smoke events with Figure of Merit in Space (FMS) greater than 20%.
Poster Session 9, Operationally-Driven Satellite Research and Application Development - Posters
Thursday, 30 September 2010, 2:30 PM-4:00 PM, ABC Pre-Function
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