Name
Title | ||
|---|---|---|
Global Monitoring and Forecasting of Biomass-Burning Smoke: Description of and Lessons From the Fire Locating and Modeling of Burning Emissions (FLAMBE) Program |
Abstract | ||
|---|---|---|
Recently, global biomass-burning research has grown from what was primarily a climate field to include a vibrant air quality observation and forecasting community. While new fire monitoring systems are based on fundamental Earth Systems Science (ESS) research, adaptation to the forecasting problem requires special procedures and simplifications. In a reciprocal manner, results from the air quality research community have contributed scientifically to basic ESS. To help exploit research and data products in climate, ESS, meteorology and air quality biomass burning communities, the joint Navy, NASA, NOAA, and University Fire Locating and Modeling of Burning Emissions (FLAMBE) program was formed in 1999. Based upon the operational NOAA/NESDIS Wild-Fire Automated Biomass Burning Algorithm (WF_ABBA) and the near real time University of Maryland/NASA MODIS fire products coupled to the operational Navy Aerosol Analysis and Prediction System (NAAPS) transport model, FLAMBE is a combined ESS and operational system to study the nature of smoke particle emissions and transport at the synoptic to continental scales. In this paper, we give an overview of the FLAMBE system and present fundamental metrics on emission and transport patterns of smoke. We also provide examples on regional smoke transport mechanisms and demonstrate that MODIS optical depth data assimilation provides significant variance reduction against observations. Using FLAMBE as a context, throughout the paper we discuss observability issues surrounding the biomass burning system and the subsequent propagation of error. Current indications are that regional particle emissions estimates still have integer factors of uncertainty. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/JSTARS.2009.2027443 | Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of |
Keywords | Field | DocType |
aerosols,air pollution,atmospheric optics,atmospheric techniques,data assimilation,fires,remote sensing,smoke,AD 1999,Earth Systems Science research,FLAMBE program,Fire Locating and Modeling of Burning Emissions program,MODIS optical depth data assimilation,NAAPS transport model,NOAA-NESDIS WF_ABBA,Navy Aerosol Analysis and Prediction System,US Navy,University of Maryland-NASA MODIS fire products,Wild Fire Automated Biomass Burning Algorithm,air quality forecasting,air quality observation,biomass burning smoke forecasting,biomass burning smoke monitoring,continental scale,global biomass burning research,regional smoke transport mechanisms,satellite applications,smoke particle emission,smoke particle transport,synoptic scale,Aerosol forecasting,biomass burning,modeling,satellite applications | Meteorology,Optical depth,Satellite,Earth system science,Remote sensing,Operational system,Synoptic scale meteorology,Air quality index,Air pollution,Data assimilation,Mathematics | Journal |
Volume | Issue | ISSN |
2 | 3 | 1939-1404 |
Citations | PageRank | References |
5 | 1.01 | 2 |
Authors | ||
12 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jeffrey S. Reid | 1 | 7 | 5.18 |
| E. J. Hyer | 2 | 11 | 3.16 |
| Elaine M. Prins | 3 | 5 | 1.01 |
| Douglas L. Westphal | 4 | 6 | 1.78 |
| Jianglong Zhang | 5 | 7 | 2.48 |
| Jun Wang | 6 | 5 | 1.35 |
| Sundar A. Christopher | 7 | 28 | 7.81 |
| Cynthia A. Curtis | 8 | 5 | 1.01 |
| Christopher C. Schmidt | 9 | 6 | 1.85 |
| Daniel P. Eleuterio | 10 | 5 | 1.01 |
| Kim A. Richardson | 11 | 7 | 1.77 |
| Jay P. Hoffman | 12 | 5 | 1.69 |