tropospheric co modeling using assimilated meteorology prasad kasibhatla & avelino arellano...
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TROPOSPHERIC CO MODELINGUSING ASSIMILATED METEOROLOGY
Prasad Kasibhatla & Avelino Arellano (Duke University)Louis Giglio (SSAI)
Jim Randerson and Seth Olsen (CalTech)Guido van der Werf (University of Amsterdam)
June 2, 2003
SupportNASA/EOS IDS Program
North Carolina Supercomputing Center
ACTIVITIES
• Inverse modeling of CO using CMDL surface measurements (Avelino Arellano, Prasad Kasibhatla)
• Development of satellite-derived biomass-burning products (Louis Giglio, Guido van der Werf, Jim Randerson)
• Interannual variations of biomass burning emissions (Seth Olsen, Guido van der Werf, Avelino Arellano, Prasad Kasibhatla, Jim Randerson)
• Inverse modeling of CO using MOPITT CO measurements (Avelino Arellano, Prasad Kasibhatla)
ALT82N, 63W
BMW32N, 65W
MID28N, 177W
RPB13N, 59W
ASC8S, 14W
SMO14S, 174W
CGO41S, 145E
SPO90S
CO INVERSE MODELING• CO offers a window into the levels of anthropogenic activities• Can patterns in atmospheric CO be used to constrain CO sources?
Source: NCAR MOPITT GROUP
INVERSE MODELING METHODOLOGY
• Start with a priori spatial and temporal patterns of CO sources
• Use GEOS-CHEM (GEOS DAS driven) with linearized chemistry (i.e. prescribed OH) in forward mode to calculate spatial and temporal patterns of CO concentrations from discrete source categories
• Use calculated and measured CO concentrations, and estimated model/obs error statistics to calculate scaling factors for each CO source category using a Bayesian inversion methodology
Repeat for 2000 using GEOS-3 DAS andcompare to results from1994
1994 (GEOS-1 DAS)
SOURCE CATEGORIES
• Fossil-fuel and biofuel use• FF/BF-NA; FF/BF-EU; FF/BF-AS; FF/BF-RW
• Biomass burning & forest fires• BB-NA/EU; BB-AS; BB-AF; BB-LA; BB-OC
• Oxidation of isoprene• ISOP
• Oxidation of monoterpenes• TERP
• CO from methane oxidation• Presubtracted with yield of 0.95
Biomass burning• Direct tropical emissions from deforest. & sav. burning from EDGAR 2• ‘Corrected’ direct emissions from ag. waste field burning from EDGAR 2• Direct emissions from extratropical forest fires from Cooke and Wilson (1996) estimates of area burnt • Scaled to account for CO from NMVOC• Timing of trop. & sub-trop. emissions from Galanter et al. (2000); HNH timing from Canadian fire climatology statistics
Fossil-fuel/Biofuel use• Direct emissions from EDGAR 2• Scaled to account for CO from NMVOC NMVOC emissions from EDGAR 2 CO yield of 0.6 C/C (Altshuler, 1991)
Other sources• Isop. oxidation - Guenther et al. (1995) emissions with NOx-dep yield from Miyoshi et al. (1994)• Monoterp. oxidation - Guenther et al. (1995) emissions with yield from Hatakeyama et al. (1991)
• CH4 oxidation with yield of 0.95 presubtracted from observations
a priori CO SOURCES
FF/BF (g CO m-2 y-1) BB (g CO m-2 y-1)
ISOP (g CO m-2 y-1) TERP (g CO m-2 y-1)
INVERSION RESULTS USING CMDL SURFACE MEASUREMENTS
’94 obs’94 a priori’94 a posteriori’00 obs’00 a priori’00 a posteriori
ASC8S, 14W
INVERSION RESULTS
Observed and Modeled Monthly-Mean CO in the south Atlantic
GEOS-CHEM RESULTSa priori surface CO from BB-AF
AUG 1994 BB-AF AUG 2000 BB-AF
AUG 2000-1994 BB-AF
• Differences in transport to the south Atlantic
’94 obs’94 a priori’94 a posteriori’00 obs’00 a priori’00 a posteriori
200
150
100
50
0
200
150
100
50
0
CO
– C
O f
rom
CH
4 oxi
dn. (
ppbv
)
INVERSION RESULTS
Observed and Modeled Monthly-Mean CO at high N. Lat.
ALT82N, 63W
ZEP79N, 12E
BRW71N, 157W
ICE63N, 20W
CBA55N, 163W
SHM53N, 174E
1 2 5 10 20 30 40 50 60 1 2 5 10 20 30 40 50 60
-50 -20 -10 -5 0 5 10 20 50
AUG 1994 BB-NA/EU AUG 2000 BB-NA/EU
AUG 2000-1994 BB-NA/EU
• Greater poleward transport of emissions in 2000
GEOS-CHEM RESULTSa priori surface CO from BB-NA/EU
Heald et al., 2003
OTHER GEOS-CHEM RESULTS
INVERSION RESULTS USING CMDL SURFACE MEASUREMENTS
• Need for consistent multi-year met. fields with biases well-characterized• Need for ‘accurate’ source patterns
VIRS ACTIVE-FIRE PRODUCTLouis Giglio
• TRMM satellite: low-inclination (38S-38N) orbit
• Observations over entire diurnal cycle during month
• Raw fire counts from mid and thermal IR channels
• Gridded statistical summary product
• 0.5o spatial resolution; monthly temporal resolution
• Corrected (account for variable coverage, multiple fire observations
due to repeated overpasses, and variable cloud cover) fire counts
• Multiple-data layers including predominant land-cover class
• Continuous archive since January 1998
• http://daac.gsfc.nasa.gov/CAMPAIGN_DOCS/hydrology/TRMM_VIRS_Fire.shtml
• (Giglio et al., Int. J. Rem. Sens., in press)
VIRS ACTIVE-FIRE PRODUCT
fire counts
mean cloud fraction
Predominant fire-pixel land type
VIRS Monthly Active Fire Product
(Giglio/Kendall)
MODIS Burned Area Estimates
(Giglio)
Other Burned Area Estimates
Calibration (van der Werf/Giglio)
Monthly Burned Area Estimates
(van der Werf/Giglio)
CASA Fuel Load(van der Werf et al.)
Monthly Pyrogenic CO Estimates
Emission Factors(Andreae et al.)
Ancillary Data
VIRS ACTIVE-FIRE PRODUCTEric Van der Werf and Louis Giglio
Net PrimaryProduction
Allocation=f (treecover)
AbovegroundBiomass C
BelowgroundBiomass C
Combustion
BelowgroundLitter C
AbovegroundLitter C
f(A,E,M) f(A,E)
Respiration
Respiration(Fire Induced
Mortality)
AbovegroundBurned Litter C
BelowgroundFire-Mortality C
f(A,1-E,M)
f(A,M)
Fuelwoodcollection
Herbivoreconsumption
f(A,E)
VIRS FIRE EMISSIONS PRODUCT
% area burned
CASA biogeochemical model
calibration
CO2 emissions
(van der Werf et al., Global Change Biology, 2003
• Need for consistent multi-year met. fields
INTERANNUAL VARIATIONS OF BIOMASS-BURNING EMISSION
CO INVERSE MODELING USING USING MOPITT MEASUREMENTS
1018 molecules cm-2
MOPITT RETRIEVAL OF COLUMN CO 2000
1018 molecules cm-2
MOPITT RETRIEVAL OF COLUMN CO FROM MODEL2000
RATIO MODEL/MOPITT
Model and measurement biases?Availability of updated OH fields
ASC
EIC CGO
obsK94 bbnew BB
SURFACE CO IN SH
SMO