tropospheric co modeling using assimilated meteorology

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