1. Elaine M. Prins NOAA/NESDIS/ORA Advanced Satellite Products Team Madison, Wisconsin elaine.prins@ssec.wisc.edu Chris C. Schmidt Joleen M. Feltz UW-Madison Cooperative Institute for Meteorological Satellite Studies Plan for GOES-9 Wildfire ABBA Fire Monitoring and Data Access For Southeast Asia GOFC-Fire S.E. Asia Regional Workshop, January 21, 2003 Fukuoka, Japan UW-Madison Cooperative Institute for Meteorological Satellite Studies (CIMSS) National Oceanic and Atmospheric Administration (NOAA) Advanced Satellite Products Team (ASPT) National Aeronautics and Space Administration

2. Activation of GOES-9 Over the Western Pacific  In April 2003 the GOES-9 will be made operational over the Western Pacific at as a replacement for GMS-5 until MTSAT-1R is launched in 2003 and activated.  GOES-9 will be located at 155ºE providing fire detection throughout the region with excellent coverage of the Western Pacific, Southeast Asia and Australia.  The final scanning schedule of the GOES-9 Imager will be determined in collaboration with the JMA. It will include at least 1 full disk per hour plus additional scans, including smaller sectors at select time periods. Imagery will be available via GVAR Direct Readout and via DOMSAT.  GOES-9 Imagery will be available via GVAR Direct Readout and via DOMSAT.

3. Timeline: Station Change of the GOES-9 DecFebMarJanMayApr G9 Return to Normal On-Orbit G9 N/S G9 Start Drift GOES9 Drift, ~0.80 deg/day (~125 days) Stop maneuver 205 W ~ third week In April Operations Start April 1 ~ 190 W Imaging via Fairbanks 21-meter WCDA (Wallops) to FCDA (Fairbanks) Handover Before 135 W FCDA GS OT&E T&C Fairbanks 13-meter Eclipse Season Imaging via Wallops Suspend imaging At ~128 deg W Transition to 13m Support (Critical commanding) T&C via Wallops Timeline courtesy of T. Renkevens NOAA/NESDIS/OSDPD

4. Satellite View Angle 80° 65° Overview of GOES-9 Fire Monitoring Capabilities for SE Asia GOES Imager Characteristics Band Wavelength IGFOV Sampled Subpoint NEDT (microns) (km) Resolution (km) 1 0.52-.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 6.47-7.02 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 WOversampling in the East/West direction with a sub-sampled res of 2.3x4.0 km provides a better opportunity to capture an entire fire within a fov. WHigh temporal resolution: every hour WGOES-8 band 2 has a saturation temperature of 324 K. This may result in numerous non-fire saturation points during peak heating hours. WFire size detectability limits with a fire temperature of 750K: Equator:.15 ha 50°N:.32 ha Fire Monitoring Characteristics

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

6. Overview of Current Wildfire Automated Biomass Burning Algorithm System A.WF_ABBA algorithm in McIDAS Environment - Automated (DELL 900 mhz dual proc., Linux, BASH scripts) Part I: Identify and log all remotely possible fire pixels - Input: - GOES multiband (vis, 4 micron, 11 micron) McIDAS areas - Aviation model forecast in McIDAS grid format - Ecosystem McIDAS area (AVHRR GLCC) - Transmittance offset lookup table ASCII file - Output: - Files (McIDAS MD and ASCII) documenting any remotely possible fires: lat., lon., T4, T11, Tb4, Tb11, ecosystem, other variables Part II: Screen/filter fire pixels, account for oversampling, temporal filtering, create output fire pixel images, and log results - Input: - Output ASCII file from Part I - GOES single band McIDAS areas - Output: - Files (McIDAS MD and ASCII) documenting processed, saturated, cloudy, and all possible fires lat., lon., T4, T11, Tb4, Tb11, estimates of fire size/temp, ecosystem type, and bookkeeping variables - McIDAS areas with fire pixels identified B. Generation of alpha-blended composite fire products - Automated (BASH scripts) - Series of McIDAS commands, programs, and scripts C. Dissemination of data and imagery via anonymous ftp and animations on the web - Automated

7. Implementation of a Real-Time Geostationary Diurnal Fire Product for the Western Pacific  Prior to the activation of GOES-9 in April 2003, UW-Madison CIMSS will modify the GOES- 8/-10 WF_ABBA for application with GOES-9 using GOES-9 data collected during the December 2001 – January 2002 checkout period.  Once GOES-9 is activated over the Western Pacific at 155ºE, further modifications will be made to the GOES-9 WF_ABBA taking into consideration the biomes within the operational domain. The GOES-9 WF_ABBA fire product will be compared with other regional fire products and available ground truth.  The GOES-8/GOES-10 WF_ABBA processing system will be revised to allow automated GOES-9 image processing and fire product data distribution.  GOES-9 multi-spectral Imager data will be acquired from the UW-Madison SSEC Data Center in GVAR format in real-time.  UW-Madison CIMSS will provide half-hourly GOES WF_ABBA fire products via the web and anonymous ftp in real time for the duration of the GOES-9 activation over the Western Pacific.  This activity will help to prepare for the implementation of a MTSAT-1R fire product and a global geostationary fire monitoring system.

8. GOES-EGOES-WMSGMTSAT 0-40-80-120-16040 80120160 80 60 40 20 0 -20 -40 -60 -80 Satellite View Angle 80° 65° 322 International Global Geostationary Active Fire Monitoring: Geographical Coverage

9. The GOES-9 Wildfire ABBA Processing System will provide fire products similar to those currently produced in real time with the GOES-8/-10 data for North, Central, and South America Examples and applications are provided from the GOES-8/-10 WF-ABBA in the following slides.

10. Animations of Wildfire ABBA composite image products are being provided via anonymous ftp and the web every half-hour at: http://cimss.ssec.wisc.edu/goes/burn/wfabba.html Displays include three overviews and 35 regional views providing coverage of the entire Western Hemisphere. Examples of Regional View Sectors GOES-8/-10 Half-hourly Wildfire Automated Biomass Burning Algorithm (WF_ABBA) Web Distribution Online Since September 2000

11. The GOES WF_ABBA Monitored the Rapid Intensification of Wildfires During the 2002 Fire Season in the Western U.S.

12. 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

13. NOAA/NESDIS/ORA ASPT UW-Madison CIMSS GOES-8 Wildfire ABBA Filtered Fire Pixel Difference Composite For the Western Hemisphere Yellow indicates fire pixels only detected in the first year: September 2000 – August 2001 Red indicates fire pixels only detected in the second year: September 2001 – August 2002

14. Comparisons of Agricultural Burning and Wildfires in Argentina in Austral Summer 2001 and 2002 Fires 1 December 2001 through 31 January 2002 1 December 2000 through 31 January 2001

15. MOPITT CO composite is courtesy of the MOPITT team: John Gille (NCAR), James Drummond (University of Toronto), David Edwards (NCAR) EOS MOPITT identifies elevated carbon monoxide associated with biomass burning detected with the GOES ABBA GOES-8 South American ABBA Composite Fire Product September 7, 2000 Comparison of GOES ABBA Fire Observations and the EOS MOPITT CO Product

16. GOES-8 WF_ABBA Detected Fires: 1–7 January 2001 MOPITT CO Max Smoke Pall Comparison between WF_ABBA Fire Observations and MOPITT CO Product Argentina Cerrado Fires MOPITT Total Column CO: 1–3 January 2001 MOPITT carbon monoxide composite is courtesy of J. Warner (NCAR) and the MOPITT Science team

17. Real-time Assimilation of the Wildfire ABBA Fire Products into the NAAPS Model To Diagnose and Predict Aerosol Extent and Transport

18. GOES WF_ABBA Fire Product Point Sources for 13 August 2002 Emissions based on WF_ABBA (kg [CO]/m2 sec) Modeled CO at surface for 13 August 2002 at 12 UTC Modeled PM2.5 (int. column) for 13 August 2002 at 12 UTC Real-Time Model Assimilation of the GOES-8 Wildfire ABBA (WF_ABBA) Fire Product at the University of Sao Paulo, Brazil In South America, GOES-8 WF_ABBA fire products are assimilated into the Regional Atmospheric Modeling System (RAMS, CSU-USA) in real-time to diagnose the transport of biomass burning emissions of carbon monoxide and PM2.5. (Freitas and Longo, University of Sao Paulo) Imagery courtesy of S. Freitas and K. Longo, USP