source: NASA, AFP. Modeling of Biomass burning with the NASA GEOS-5 modeling and data assimilation system. Anton Darmenov , Arlindo da Silva GMAO Research Meeting, 31 March 2011. Outline. Biomass burning emissions Background The QFED v2.1 fire emissions inventory Fire weather index
source: NASA, AFP
Modeling of Biomass burningwith the NASA GEOS-5 modeling and data assimilation system
Anton Darmenov, ArlindodaSilva
GMAO Research Meeting, 31 March 2011
Ex = EFx M
Ex – emission load of species x
EFx – emission factor for species x for the specific vegetation type/biome
M – biomass burned
M = A * B * β
A– area burned
B– biomass load/density
β– combustion completeness / fraction of available fuel burned
Etot = Erad + Econv + Econd + Evapor
Erad ~ Etot
pk– fractional area of the k-th fire component
Tk– temperature of the k-th fire component
FRPMIR ~ FRPtrue
QFED uses the IGBP vegetation map and four types of biomes – tropical and extra-tropical forests, savanna and grassland.
The independent calibration of MODIS Terra and Aqua FRPs provides redundancy in case of data loss from one of the satellites.
Time series of GFED and QFED global monthly mean CO emissions for the period of 2003-2007.
Global Land Surface Temperature Anomalies, July 2010
Drought and Air Quality, August 2010
The fire emissions are likely underestimated in the Central Region.
time averaged AOT: 20 Jul – 20 Aug, 2010
time averaged AOT:
20 Jul – 20 Aug, 2010
time averaged PM2.5: 20 Jul – 20 Aug, 2010
Assimilating AOT also improves the surface PM2.5 concentrations.
Moscow – Visibility [km]
reported VIS < 1000m
The GEOS-5/GAAS visibility is overestimated (higher than the measured values), which suggests that the PM2.5 are underestimated.
GEOS-5/GOCART tends to underpredict the AOT in the areas affected by biomass burning.
AOT = (AOTDU + AOTSS + AOTXX+αBBAOTBB + αANAOTAN
αBB = 3.4
αAN = 0.01
αBB = 2.5
αAN = 0.3
αBB = 1.8
αAN = 1.1