Global transport and Global transport and radiative forcing of radiative forcing of biomass burning biomass burning aerosols aerosols Yang Chen, Qinbin Li, Ralph Kahn Yang Chen, Qinbin Li, Ralph Kahn Jet Propulsion Laboratory Jet Propulsion Laboratory California Institute of Technology, Pasadena California Institute of Technology, Pasadena Evan Lyons, James Randerson Evan Lyons, James Randerson University of California, Irvine University of California, Irvine The 3rd GEOS–Chem Users' Meeting The 3rd GEOS–Chem Users' Meeting Harvard University, April 12, 2007 Harvard University, April 12, 2007
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Global transport and radiative forcing of biomass burning aerosols Yang Chen, Qinbin Li, Ralph Kahn Jet Propulsion Laboratory California Institute of Technology,
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Global transport and Global transport and radiative forcing of biomass radiative forcing of biomass
burning aerosols burning aerosols
Yang Chen, Qinbin Li, Ralph KahnYang Chen, Qinbin Li, Ralph KahnJet Propulsion LaboratoryJet Propulsion Laboratory
California Institute of Technology, PasadenaCalifornia Institute of Technology, Pasadena
Evan Lyons, James RandersonEvan Lyons, James RandersonUniversity of California, IrvineUniversity of California, Irvine
The 3rd GEOS–Chem Users' MeetingThe 3rd GEOS–Chem Users' MeetingHarvard University, April 12, 2007Harvard University, April 12, 2007
Objectives and outlineObjectives and outline Large uncertainties in the estimation of aerosol radiative forcing.Large uncertainties in the estimation of aerosol radiative forcing.
• -0.1~-0.9 W/m-0.1~-0.9 W/m22 for direct forcing (IPCC,2007). for direct forcing (IPCC,2007).• -0.3~-1.8 W/m-0.3~-1.8 W/m22 for indirect forcing. for indirect forcing.
PurposePurpose: Combine satellite observations and chemical transport models to : Combine satellite observations and chemical transport models to further constrain quantification of aerosol (particularly the biomass burning further constrain quantification of aerosol (particularly the biomass burning aerosols) radiative forcing.aerosols) radiative forcing.
First stepFirst step: Estimate the global aerosol direct radiative effect using Multi-: Estimate the global aerosol direct radiative effect using Multi-angle Imaging SpectroRadiometer (MISR) observations.angle Imaging SpectroRadiometer (MISR) observations.• Better aerosol retrievals over land.Better aerosol retrievals over land.• First attempt at estimating aerosol direct radiative effect on a global basis (over First attempt at estimating aerosol direct radiative effect on a global basis (over
both ocean and land) using satellite observation based approach.both ocean and land) using satellite observation based approach.
Ongoing modeling studyOngoing modeling study: GEOS-Chem simulations of aerosols using : GEOS-Chem simulations of aerosols using different GFEDv2 biomass burning emissions.different GFEDv2 biomass burning emissions.• Diurnal cyclesDiurnal cycles• Synoptic variationSynoptic variation• Injection heightInjection height
Introduction to MISRIntroduction to MISR Multi-angle multi-channel Multi-angle multi-channel
spectroradiometer on board spectroradiometer on board satellite TERRAsatellite TERRA
Global Mode:Global Mode:• 275 m sampling resolution for 275 m sampling resolution for
nadir camera and red band of nadir camera and red band of other camerasother cameras
• 1.1 km for the other channels1.1 km for the other channels• 400-km swath400-km swath• Global coverage: 9 days at Global coverage: 9 days at
equator, 2 days at polesequator, 2 days at poles
Continuous data retrieval since Continuous data retrieval since Feb 2000.Feb 2000.
Major products used:Major products used:• TOA albedo (2.2x2.2 kmTOA albedo (2.2x2.2 km22))• AOD (17.6x17.6 kmAOD (17.6x17.6 km22))• Cloud mask (1.1x1.1 kmCloud mask (1.1x1.1 km22))• BHRPAR (1.1x1.1 kmBHRPAR (1.1x1.1 km22))• All products are re-sampled to All products are re-sampled to
17.6x17.6 km17.6x17.6 km22 for this study for this study
MethodMethod aerosolnoaerosolwithTOAskyclear IF __
fractionCloudFF skyclearskyall _1
Albedo ~ AOD regression
TOA Broadband Albedo
(with aerosol)
Aerosol Optical Depth
Cloud mask
BHRPAR
Nadir view Cloud mask
AOD TOA albedo
1°x 1° grid
MISR observations
Global distribution of AOD, albedo, Global distribution of AOD, albedo, and BHRPAR (July, 2002)and BHRPAR (July, 2002)
26 BHRPAR bins:
0~0.1: each 0.01 interval
0.1~0.4: each 0.02 interval
Above 0.4: 1 level
Albedo~AOD correlation over oceanAlbedo~AOD correlation over oceanAlbedo~AOD correlation for 10°x5° grids. The slopes indicate
the ability of aerosols to affect TOA radiative flux.
Alternative method: do global regression for each solar zenith angle.
a e
fb c
d
g
Albedo~AOD correlation over landAlbedo~AOD correlation over land
A
East US
A
B
C
B
Central Africa
C
Saharan desert
Global correlation
Albedo~AOD correlation for 10°x5° grids
Aerosol direct radiative effectAerosol direct radiative effect
(a) (b)
(a) Clear-sky and (b) all-sky aerosol direct radiative effect (W/m2) for July 2002.
Aerosol direct radiative effectAerosol direct radiative effect
Direct ARE (Clear sky) Direct ARE (Clear sky) (W/m(W/m22))
Direct ARE (All sky) Direct ARE (All sky) (W/m(W/m22))
GlobalGlobal -4.70-4.70 -1.49-1.49
Over oceanOver ocean -4.54-4.54 -1.95-1.95
Over landOver land -4.88-4.88 -1.18-1.18
SourceSource Direct ARE (W/mDirect ARE (W/m22)) Spatial coverageSpatial coverage Temporal coverageTemporal coverage Satellite data sourceSatellite data source
Zhang and Zhang and Christopher, 2005Christopher, 2005
UncertaintiesUncertainties Satellite retrieval of aerosol, albedo and surface Satellite retrieval of aerosol, albedo and surface
properties.properties.
Cloud contamination.Cloud contamination.
Diurnal variability.Diurnal variability.
TOA albedo narrow-to-broadband conversion.TOA albedo narrow-to-broadband conversion.
Surface heterogeneity.Surface heterogeneity.
Diurnal cycle effect on Diurnal cycle effect on GEOS-Chem aerosol simulationGEOS-Chem aerosol simulation
07/2004
Ongoing modeling studyOngoing modeling study
Simulation conditions
• Model: GEOS-Chem v7-03-06
• Meteorology: GEOS-4
• Simulation type: Offline aerosol simulation
• Simulation period: 06/2004 ~ 08/2004
• Biomass burning emissions: Global Fire Emissions Database version 2 (GFEDv2) with 8 day time interval
• with diurnal cycle
• without diurnal cycle
Diurnal cycle effect on Central AfricaDiurnal cycle effect on Central AfricaOngoing modeling studyOngoing modeling study
With diurnal cycle, major emissions occur when the PBL is high. The vertical mixing causes faster dilution and the dissipation of pollutants. The accumulation of aerosols during local night is weaker.
Diurnal cycle effect on Alaska and Northern CanadaDiurnal cycle effect on Alaska and Northern CanadaEmissions from source:
BCPI concentration in nearby grid:
Ongoing modeling studyOngoing modeling study
When the biomass burning emission is very strong and PBL is low, the dissipation effect is weaker. For some regions near the strong source, the transport is more important than the local emission.
Conclusions and future workConclusions and future work ConclusionsConclusions
• By using MISR datasets, first satellite-based attempt to estimate global By using MISR datasets, first satellite-based attempt to estimate global aerosol direct radiative effect over both ocean and land has been aerosol direct radiative effect over both ocean and land has been made.made.
• Aerosols have different impacts on TOA albedo in different regions due Aerosols have different impacts on TOA albedo in different regions due to different aerosol properties and surface types.to different aerosol properties and surface types.
• Global mean result of aerosol radiative effect over ocean is well in the Global mean result of aerosol radiative effect over ocean is well in the range of other studies in literature.range of other studies in literature.
• By including diurnal cycle of biomass burning emissions in GEOS-Chem By including diurnal cycle of biomass burning emissions in GEOS-Chem simulation, aerosol concentrations at surface may increase or simulation, aerosol concentrations at surface may increase or decrease, depending on the source type and intensity, the boundary decrease, depending on the source type and intensity, the boundary layer height, and the relative importance of transport and local layer height, and the relative importance of transport and local emissions.emissions.
Future workFuture work• Extend the satellite-based estimation of aerosol direct radiative effect Extend the satellite-based estimation of aerosol direct radiative effect
to include seasonal and inter-annual variability.to include seasonal and inter-annual variability.• Study how synoptic variability of biomass burning emissions and the Study how synoptic variability of biomass burning emissions and the
inclusion of smoke injection height will affect the global distribution of inclusion of smoke injection height will affect the global distribution of aerosols, and the implication to the aerosol radiative forcing.aerosols, and the implication to the aerosol radiative forcing.
AcknowledgmentAcknowledgment MISR dataMISR data were obtained from the NASA Langley were obtained from the NASA Langley
Atmospheric Sciences Data Center (Atmospheric Sciences Data Center (http://eosweb.larc.nasa.gov/http://eosweb.larc.nasa.gov/).).
We used We used Global Fire Emissions Database version2Global Fire Emissions Database version2 (van (van der Werf et al.,2006) resampled to an 8day time step using der Werf et al.,2006) resampled to an 8day time step using MODIS fire hot spots (Giglio et al., 2003).MODIS fire hot spots (Giglio et al., 2003).
GEOS-Chem modelGEOS-Chem model is managed by the Atmospheric is managed by the Atmospheric Chemistry Modeling Group at Harvard University. Chemistry Modeling Group at Harvard University.