1. Shobha Kondragunta and Ivan Csiszar NOAA/NESDIS Amy Huff Pennsylvania State University Hai Zhang and Pubu Ciren IMSG at NOAA Xiaoyang Zhang South Dakota State University February 24, 2015 Tracking the impact of wildfires on exo-urban regions using high resolution SNPP VIIRS aerosol products Image courtesy of king5.com

2. 2 This presentation focuses on Aerosol Optical Thickness (AOT) Smoke mask Fire hotspots VIIRS Products Carlton complex fires San Diego fires Funny River fires Case Studies enhanced Infusing satellite Data into Environmental Applications eIDEAGOES-R/JPSS synergy 1 2

3. 3 Wildfires have detrimental effect on human health and economy www.nifc.gov

4. 4 VIIRS fire and aerosol products are validated and ready for operational use

5. 5 Washington state Carlton Complex fires

6. 6 Alaska Funny River fire smoke mask Thick SmokeThin Smoke Data artifacts

7. 7 San Diego fires Fire hotspots 750 m to 1.2 km High resolution display of AOD pixels at city road/neighborhood (750 m to 1.2 km) scale High aerosol concentrations Low aerosol concentrations

8. 8 Enhancements to IDEA (eIDEA) – proxy burned area California Rim Fire 2013: Landsat TM Burned Scar with VIIRS hotspots overlaid Fire hot spots tend to correlate with burned area

9. 9 Enhancements to IDEA (eIDEA) – proxy burned area Sq. km per hot spot

10. 10 Enhancements to IDEA (eIDEA) – smoke exposure AOTPM2.5 Relative Risk Factors Burnett et al., EHP, 2014

11. 11 Enhancements to IDEA (eIDEA) – fire category Adapt Ichoku et al (RSE, 2008) methodology that uses Fire Radiative Power (FRP) to classify fires into five different categories MODIS FRP Range (MW)Category < 1001 100 - 5002 500 - 10003 1000 - 15004 >15005 Individual fire hot spots can be of different categories within a fire complex Real time information can help with resource allocation (manpower) in suppressing fires Numbers for VIIRS TBD

12. Key features of eIDEA…to deploy as NWS Western region demo Access to high resolution VIIRS aerosol and fire products 1 Fire category 2 Burned area Mortality risk factors for smoke exposure 4 3 Information accessible on web and any portable device of choice to aid fire managers in short-term resource allocation planning and long-term assessment of land management policies Pixel level AOT

13. ABIVIIRS GOES-R ABI and JPSS VIIRS aerosol product synergy Algorithm for AOT is/can be similar. Algorithm for smoke/dust mask different. ABI does not have deep blue channel. Product applications are similar. IDEA will showcase GOES-R strengths (5-min snapshots of CONUS). Huff et al., EM, 2014 documents first ever near real time experiment AQPG did with simulated ABI aerosol products disseminated to air quality forecasters as if GOES-R was in orbit. Questions remain about applications for aerosol particle size parameter (aka Angstrom Exponent) – next slide

14. Aerosol Particle Size Parameter Ground-based AERONET Data SNPP VIIRS smoke haze ABI aerosol particle size parameter will have limited ability to separate different types of aerosols

15. Summary SNPP VIIRS aerosol products available through IDEA website to air quality forecasters and other users. Latency is 2 hours. Goal is 20 minutes. eIDEA website to provide value-added fire and smoke information for real time monitoring. VIIRS fire and aerosol products have the potential to contribute to air quality and land management policies.