Fire Products Training Workshop in Partnership with BAAQMD Santa Clara, CA September 10 – 12, 2013 Applied Remote SEnsing Training (ARSET) – Air Quality.

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Fire Products Training Workshop in Partnership with BAAQMD Santa Clara, CA September 10 – 12, 2013 Applied Remote SEnsing Training (ARSET) – Air Quality A project of NASA Applied Sciences

Fire Products Summary HMS - NOAA Hazard Mapping System ABBA – NOAA GOES Wildfire Automated Biomass Burning Algorithm AFM – USDA Forest Service Active Fire Mapping Program MTBS – USDA&DOI Monitoring Trends in Burn Severity Project FIRMS – NASA Fire Information for Resource Management System

Product Integrates Satellite Data Automated Fire Detection Algorithms Ancillary Data Layers NOAA Hazard Mapping System (HMS) Operational daily fire and smoke analysis for North America Automated Fire Detection and Human Input Analysts review fire detections and retain or delete them Analysts can add hotspots that the algorithms have not detected.

NOAA Hazard Mapping System Fire and Smoke Product Fire Information from AVHRR, MODIS and GOES, Complied by NOAA

Google Earth display

NOAA Hazard Mapping System (HMS) Satellite Sensor SWIR nominal resolution Refresh Rate Geographic coverage Automated detection algorithm GEOSTATIONARY GOES-East GOES-West 4km15 minutes CONUS/Canada/ Central AmericaWFABBA Western half of CONUS/Alaska/Hawaii POLAR NOAA-15/17/18 MODIS Terra MODIS Aqua 1km Twice/day low/mid latitudes More frequent at high latitudes Most of North/Central America except NOAA- 15 which does not cover Western US FIMMA MODIS

The GOES Wildfire Automated Biomass Burning Algorithm (WF_ABBA) WF_ABBA fire product includes: fire location (lat./lon.), estimates of fire size and temperature, 3.9 and 10.7 micron observed brightness temperatures, background brightness temperatures, albedo statistics, ecosystem type, and a flag for non-processed fire pixels to indicate the reason for not processing. ftp://satepsanone.nesdis.noaa.gov/FIRE/ABBA/Binary Data: - Automatically locates and characterizes sub-pixel fires in GOES imagery in the Western Hemisphere - The product is run every 30 minutes Product includes: - Fire Location (lat./lon.) - Estimates of Fire Size and Temperature - Ecosystem Type. WF_ABBA fire product available as: - ASCII text files, AREA files - Alpha-blended composite imagery

Displays include three overviews and 35 regional views of the Western Hemisphere. Examples of Regional View Sectors University of Wisconsin-Madison CIMSS/ASPT GOES-10/-12 Half-hourly Wildfire ABBA Web Distribution

Example of the GOES Wildfire ABBA Monitoring System in the Western Hemisphere

GOES-8 Wildfire ABBA Summary Composite of Filtered Half-Hourly Fire Observations for the Western Hemisphere Time Period: September 1, 2001 to August 31, 2002 The composite shows the much higher incidence of burning in Central and South America, primarily associated with deforestation and agricultural management. Fire Pixel Distribution North America (30-70°N): 12% Central America (10-30°N): 11% South America (70°S-10°N): 77% Processed Saturated Cloudy High Possibility Medium Possibility Fire Pixel Category The base map for this composite image is derived from the Global Land Cover Characteristics database provided by the USGS

Applications of the GOES Wildfire ABBA in Modeling Programs Collaborations result in submission/publication of 3-peer reviewed publications in FY03 Real-time Assimilation at the University of Sao Paulo and CPTEC/INPE into the RAMS model Point Sources for 13 August 2002 RAMS CO Product RAMS PM2.5 Product GOES-8 WF_ABBA Fire Product Real-time Assimilation into the Naval Research Laboratory Navy Aerosol Analysis and Prediction System (NAAPS) GOES WF_ABBA Fire Product 22 August 2003 at 17:45 UTC NAAPS Smoke Optical Depth 22 August 2003 at 18:00 UTC GOES-8 ABBA Fire and MACADA Cloud Products Used in Study to Model and Predict Future Fire Activity at UNH Collaboration with Univ. of New Hampshire Inst. for Study of Earth, Oceans, and Space Other Modeling Efforts and Collaborations  Climate Modeling at NASA/GSFC: Assimilation into the GOCART model  Real-time Air Quality Modeling at NASA/Langley: Real-time assimilation into the RAQMS model as part of IDEA (Infusing satellite Data into Environmental Applications)  Fire Emissions and Regional Air Quality Modeling at NCAR: Assimilation into the U.S. EPA Community Multiscale Air Quality model in support of the 2002 SMOCC campaign in Brazil Intermediate Deforestation Scenario Predicted increase in future regional fire activity: 22% Complete Deforestation Scenario Predicted increase in future regional fire activity: 123% Number of Fire Pixels