Elaine M. Prins NOAA/NESDIS/ORA/STAR Advanced Satellite Products Branch – Madison, WI

1. Overview of GOES Fire Products and Their Applications Workshop on Air Quality Applications of Satellite Data NOAA NESDIS Center for Satellite Applications and Research (STAR), 4 May 2004 Elaine M. Prins NOAA/NESDIS/ORA/STAR Advanced Satellite Products Branch – Madison, WI Grass Valley, CA elaine.prins@ssec.wisc.edu Joleen M. Feltz Chris C. Schmidt UW-Madison Cooperative Institute for Meteorological Satellite Studies Grass Valley UW-Madison Cooperative Institute for Meteorological Satellite Studies (CIMSS) National Aeronautics and Space Administration NOAA/NESDIS/STAR/CORP Advanced Satellite Products Branch (ASPB)

2. Applications of Meteorological Satellite Fire Products • Hazards Detection and MonitoringEach year millions of acres of forest and grassland are consumed by wildfire resulting in loss of life and property with significant economic costs and environmental implications.- Although the capabilities of current operational meteorological satellites are limited, they can provide valuable regional and global fire products in near real-time, and are critical for fire detection and monitoring in remote locations and developing countries. • Global Change and Air Quality MonitoringBiomass burning is a distinct biogeochemical process that plays an important role in terrestrial ecosystem processes and global climate change- Land use and land cover change monitoring: Fire is used in the process of deforestation and agricultural management. Approximately 85% of all fires occur in the equatorial and subtropical regions and are not adequately documented.- Estimates of atmospheric emissions: Biomass burning is a major source of trace gases and an abundant source of aerosols NO, CO2 (40%), CO (32%), O3(38%), NOX, N2O, NH3, SOX, CH4(10%), NMHC (>20%) , POC (39%)- Within the Framework Convention on Climate Change (FCCC) countries need to report on greenhouse gas emissions including those from biomass burning.

3. The Basics of GOES Satellite Infrared Fire Detection p 1-p Pixel (Example from South America)

4. -160 -120 -80 -40 80 GOES-E GOES-W GOES-12 (East) Imager Characteristics Band Wavelength IGFOV Sampled Subpoint NEDT (microns) (km) Resolution (km) 1 0.53-.77 1.0x1.0 0.57x1.0 10-bit data 2 3.76-4.03 4.0x4.0 2.3x4.0 .21 K @ 300 K 3 5.77- 7.33 4.0x4.0 2.3x4.0 .16 K @ 230 K 4 10.23-11.24 4.0x4.0 2.3x4.0 .10 K @ 300 K 5 NA 6 12.96-13.72 8.0x8.0 2.3x8.0 .18 K 60 40 Satellite View Angle 80° 65° 20 0 GOES-10 (West) Imager Characteristics Band Wavelength IGFOV Sampled Subpoint NEDT (microns) (km) Resolution (km) 1 0.53-.72 1.0x1.0 0.57x1.0 10-bit data 2 3.78-4.03 4.0x4.0 2.3x4.0 .23 K @ 300 K 3 6.47-7.03 8.0x8.0 2.3x8.0 .30 K @ 230 K 4 10.2-11.2 4.0x4.0 2.3x4.0 .14 K @ 300 K 5 11.5-12.5 4.0x4.0 2.3x4.0 .26 K @ 300 K -20 -40 -60 -80 Current U.S. Geostationary Coverage and Fire Monitoring Characteristics Fire Monitoring Characteristics • Oversampling in the East/West direction with a sub-sampled res of 2.3x4.0 km • High temporal resolution: every 15 minutes over portions of North America, half-hourly elsewhere, capability for 1-minute imaging in Super Rapid Scan Operational mode. • GOES-12 band 2 has an elevated saturation temperature of ~337 K.Elevated GOES-12 band 2 saturation temperature gives improved fire characterization. GOES-10 saturates at ~322K resulting in non-fire saturation points during peak heating hours. • Fire size detectability limits with an average fire temperature of 750K:Equator: .15 ha 50°N: .32 ha

5. University of Wisconsin-Madison CIMSS/ASPT GOES-10/-12 Half-hourly Wildfire ABBA Web Distribution http://cimss.ssec.wisc.edu/goes/burn/wfabba.html Examples of Regional View Sectors Animations of Wildfire ABBA composite image products are being provided via anonymous ftp and the web every half-hour. Displays include three overviews and 35 regional views providing coverage of the entire Western Hemisphere.

6. Examples of the GOES Wildfire ABBA Monitoring System in the Western Hemisphere http://cimss.ssec.wisc.edu/goes/burn/wfabba.html

7. Rodeo/Chediski Complex in Arizona 2303 UTC 2307 UTC 2315 UTC 2320 UTC Fire Detection Using Rapid Scan Imagery Case Studies in the Western U.S. During the 2002 Fire Season Using rapid scan GOES-11 data, the WF_ABBA was able to identify several wildfires in imagery near/at the initial reported start times during the 2002 fire season in the Western U.S. Rodeo/Chediski Complex: Largest Wildfire in Arizona’s Recorded History Size: > 480,000 acres Cost: > $170 million Start Date of Rodeo Fire: 18 June 2002 Official report time by suspected arsonist: 23:11 UTC Initial detect in post-processed GOES-11 image: 23:07 UTC UW-Madison/CIMSS/ASPT

8. Animation of GOES-11 Rapid Scan Visible Imagery (1 km) Time Period: 22:07, 9 June 2002 – 00:50, 10 June 2002 Example of plume-driven fire GOES-11 Rapid Scan Visible Imagery Highlights the Hayman Fire Denver WebCam: Blue Skies over Denver Date: 9 June 2002 Time: 9:06 am (15:06 UTC) Denver WebCam: Decreased visibility due to smoke Date: 9 June 2002 Time: 3:06 pm (21:06 UTC) CSU/CIRA/RAMM Team

9. Los Angeles San Diego GOES WF_ABBA Diurnal Monitoring of Wildfires In the Western U.S. GOES-10 WF_ABBA Alpha-Blended Imagery (GOES Visible, IR, WF_ABBA, USGS GLCC) • Half-hourly GOES alpha-blended imagery provide insight into diurnal variation in fire and weather • Currently products are available on-line within half-hour of image receipt • Goal is to provide fire products within 5 minutes for regional sectors in rapid scan mode this year. Rapid scan mode can be requested by the fire weather community. 26 October – 29 October 2003

10. Applications of the GOES Wildfire ABBA for Land-Use/Land-Cover Change Studies Throughout the Western Hemisphere GOES Wildfire Automated Biomass Burning Algorithm (WF_ABBA) trend analyses are providing insight into biomass burning activity associated with land-use and land-cover applications for climate change and carbon cycle studies. GOES-8 Wildfire ABBA Composite Fire Product for Western Amazonia in Acre, Brazil Date: June – October, 2002 In 2002 a validation effort was conducted in the new frontier of Acre, Brazil. The GOES-8 WF_ABBA identified 84% of the 88 fires that were monitored by on-site survey teams; the majority of the fires not detected with the GOES WF_ABBA were cloud-covered. Most of the fires were less than 10 hectares in size. (Cost share with NASA ESE and LBA funding)

11. Wildfires and Agricultural Burning Show Strong Diurnal Cycle

12. 2002ValidationStudy in Quebec Quebec Red markers indicate fires first detected by the WF_ABBA. Filled red circles are fire pixels that were only detected by the WF_ABBA Courtesy of Michel Moreau Environment Canada, Meteorological Ser vices, Quebec Region In one case, the WF_ABBA detected a fire 17 days in advance of the first fire agency report. This fire eventually burned more than 55,000 hectares. This fire was located in Northern Quebec where there is no need for systematic daily detection by SOPFEU

13. WF_ABBA Results for the 2002 Quebec Fire Season Unfiltered 78%confirmed 2%possible 20%false (primarily low poss.) Filtered 96% confirmed 1% possible 3% false (primarily low poss.)

14. Real-time Assimilation of the Wildfire ABBA Fire Products into the NAAPS Model

15. Applications of the GOES Wildfire ABBA in Modeling Programs Real-time Assimilation into the Naval Research Laboratory Navy Aerosol Analysis and Prediction System (NAAPS) Real-time Assimilation at the University of Sao Paulo and CPTEC/INPE into the RAMS model RAMS CO Product RAMS PM2.5 Product GOES-8 WF_ABBA Fire Product GOES WF_ABBA Fire Product 22 August 2003 at 17:45 UTC NAAPS Smoke Optical Depth 22 August 2003 at 18:00 UTC Point Sources for 13 August 2002 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 • 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 • Climate Modeling at NASA/GSFC: Assimilation into the GOCART model Intermediate Deforestation Scenario Predicted increase in future regional fire activity: 22% Number of Fire Pixels Complete Deforestation Scenario Predicted increase in future regional fire activity: 123%

16. Comparison between WF_ABBA Fire Observations and MOPITT CO ProductPacific Northwest United States MOPITT Total Column CO: 25–27 August 2000 Smoke and cumulus from large fires MOPITT CO Max. NorthDakota Montana Idaho GOES-10 WF_ABBA Detected Fires: 20–27 August 2000 MOPITT carbon monoxide composite is courtesy of J. Warner (NCAR) and the MOPITT Science team

17. ABI Bands Band 7: Saturation temperature of 400K MSG/AVHRR/Sounder(s) MODIS/MTG/ Aircraft, etc Current GOES Imagers

18. GOES-R and GOES-I/M Simulations of Southern California Fires Using MODIS Data: 27-October-2003 at 0950 UTC GOES-12 Simulated 3.9 micron Data Padua/Grand Prix Fires Date: 27-Oct-03 Time: 09:50 UTC GOES-R Simulated 3.9 micron Data Padua/Grand Prix Fires Date: 27-Oct-03 Time: 09:50 UTC Brightness Temperature (K)

19. Overview and Future Plans • Current international environmental meteorological satellites were not specifically designed for fire monitoring and have limitations in this application. • In the Western Hemisphere GOES WF_ABBA fire products are providing new insights into diurnal, spatial, seasonal and interannual biomass burning activity with applications in hazards, global change, and emissions monitoring. • The International Global Observing Strategy GOFC/GOLD Fire Program has recommended development and operational implementation of a consistent global geostationary fire product utilizing GOES/MSG/MTSAT. Demonstration in 2005. • Future plans - Implement a Rapid Scan WF_ABBA for hazards applications, with products available within 5 minutes - Go Global: Adapt GOES WF_ABBA to GOES-9, MSG, MTSAT-1R - Transfer global WF_ABBA to NESDIS Operations - Participate in multi-sensor validation and intercomparison studies - Get ready for the next generation geostationary platform (ABI)