NOAA NESDIS satellite products for fire risk assessment Peter Romanov 1,2

1. NOAA NESDIS satellite products for fire risk assessment Peter Romanov1,2 1NOAA Cooperative Remote Sensing Science and Technology Center (CREST), City College of City University of New York (CUNY) 2 Center for Satellite Applications and Research, NOAA/NESDIS

2. BACKGROUND • NESDIS does not operationally monitor fire risk or fire danger • Several NESDIS environmental products can be used for assess fire potential/danger • Our presentation gives a review of these products, their accuracy and availability

3. FIRE DANGER/RISK INDICES • Indices used (partial list) • Keetch-Byram Drought Index, KBDI (USA, Canada) • Nesterov, NI (Russia) • Zhdanko, ZhI (Russia) • McArthur Forest Fire Danger Index, FFDI (Australia) • Primary input to indices calculation • Temperature, rainfall, humidity, wind speed • Duration of adverse weather conditions leading to drought/fires (cumulative dryness) • Additional information that may be used • Vegetation cover condition, soil moisture, snow cover

4. BACKGROUND

5. FIRE INDICES AND FIRE STATISTICS From Groisman et al, 2007

6. PRECIPITATION PRODUCTS • Vis/IR -based • Microwave-based • Combined All products are derived at daily or shorter time step Coverage is continental to global

7. ACCURACY OF PRECIPITATION ESTIMATES

8. SOIL MOISTURE BASICS Physics: Soil moisture is related to surface microwave emissivity • Few instruments have sufficiently low frequencies (≤10 GHz) to have the desired sensitivity: • AMSR-E: 6.9 and 10.7 GHz • TRMM Microwave Imager (TMI): 10.7 GHz • WindSatCoriolis: 6.8 and 10.8 GHz • ESA SMOS MIRAS: 1.4 GHz • Higher frequencies less sensitive to soil wetness, have smaller penetration depth. • Soil moisture retrievals over heavily vegetated areas (e.g., rain forest) are very limited

9. Soil Moisture Products and Data • The Soil Moisture Operational Processing System (SMOPS) is being developed at NOAA to provide operational real-time soil moisture products at 6-hour and daily time scales on a 0.25-degree lat/lon grid. • SMOPS will combine soil moisture retrievals from several sensors SMOS, AMSR-E, and ASCAT. • Operational deployment is planned for August 2011.

10. SNOW COVER • Daily snow cover maps are derived daily at 4 km spatial resolution • Two type of techniques: interactive and automated • Both visible infrared and microwave observations are used for snow mapping • Rate of agreement to surface snow cover estimates is about 90% Global automated snow/ice maps http://www.star.nesdis.noaa.gov/smcd/emb/snow/HTML/multisensor_global_snow_ice.html NH Interactive snow/ice maps http://www.natice.noaa.gov/ims/

11. SNOW SEASON VS FIRE SEASON • Fire season starts ~2 weeks after snow melt • Earlier snow melt in 1980s as compared to 1970s translated into earlier start of fire season.

12. SURFACE TEMPERATURE AND NDVI • AVHRR-based • Smoothed • Weekly, global • 4 km resolution • Available since 1982 • Used to identify drought conditions

13. DROUGHT IDENTIFICATION • Temperature much above average • NDVI much below average • Drought condition • Compare current temperature and NDVI with average historical values for the same week of the year

14. FIRE RISK • Duration of persistent drought conditions • Fire risk • Week 34, 2009 • Week 34, 2010 • Climatology-based approach for fire risk assessment is less efficient in areas where fires occur every year (e.g., Turkey)

15. VEGETATION COVER LINK • Climatology-based approach for fire risk assessment is less efficient in areas where fires occur every year (e.g., Turkey) • Only occasional qualitative validation of the fire risk products is performed • http://www.star.nesdis.noaa.gov/smcd/emb/vci/VH/vh_browse.php

16. SUMMARY • Products are global or large scale. Therefore their application has most advantages in large-scale fire-related assessments. • - • Satellites do not provide all information needed to calculate standard fire danger indices.

17. THANK YOU