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TROPOSPHERIC CO MODELING USING ASSIMILATED METEOROLOGY

TROPOSPHERIC CO MODELING USING 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 Support NASA/EOS IDS Program

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TROPOSPHERIC CO MODELING USING ASSIMILATED METEOROLOGY

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  1. TROPOSPHERIC CO MODELING USING 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 Support NASA/EOS IDS Program North Carolina Supercomputing Center

  2. 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)

  3. ALT 82N, 63W ASC 8S, 14W BMW 32N, 65W SMO 14S, 174W MID 28N, 177W CGO 41S, 145E RPB 13N, 59W SPO 90S 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

  4. 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 1994 (GEOS-1 DAS) Repeat for 2000 using GEOS-3 DAS and compare to results from 1994

  5. 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

  6. 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) • 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) • 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 • 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

  7. INVERSION RESULTS USING CMDL SURFACE MEASUREMENTS

  8. INVERSION RESULTS Observed and Modeled Monthly-Mean CO in the south Atlantic ’94 obs ’94 a priori ’94 a posteriori ’00 obs ’00 a priori ’00 a posteriori ASC 8S, 14W

  9. GEOS-CHEM RESULTS a 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

  10. INVERSION RESULTS Observed and Modeled Monthly-Mean CO at high N. Lat. 200 150 100 50 0 BRW 71N, 157W ALT 82N, 63W ZEP 79N, 12E 200 150 100 50 0 CO – CO from CH4 oxidn. (ppbv) ICE 63N, 20W CBA 55N, 163W SHM 53N, 174E ’94 obs ’94 a priori ’94 a posteriori ’00 obs ’00 a priori ’00 a posteriori

  11. GEOS-CHEM RESULTS a priori surface CO from BB-NA/EU 30 30 40 40 50 50 60 60 5 5 10 10 20 20 1 1 2 2 AUG 1994 BB-NA/EU AUG 2000 BB-NA/EU AUG 2000-1994 BB-NA/EU 5 10 20 50 -50 -20 -10 -5 0 • Greater poleward transport of emissions in 2000

  12. OTHER GEOS-CHEM RESULTS Heald et al., 2003

  13. INVERSION RESULTS USING CMDL SURFACE MEASUREMENTS • Need for consistent multi-year met. fields with biases well-characterized • Need for ‘accurate’ source patterns

  14. VIRS ACTIVE-FIRE PRODUCT Louis 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)

  15. VIRS ACTIVE-FIRE PRODUCT fire counts mean cloud fraction Predominant fire-pixel land type

  16. VIRS Monthly Active Fire Product (Giglio/Kendall) MODIS Burned Area Estimates (Giglio) Other Burned Area Estimates Calibration (van der Werf/Giglio) Ancillary Data Monthly Burned Area Estimates (van der Werf/Giglio) Monthly Pyrogenic CO Estimates Emission Factors (Andreae et al.) CASA Fuel Load (van der Werf et al.) VIRS ACTIVE-FIRE PRODUCT Eric Van der Werf and Louis Giglio

  17. VIRS FIRE EMISSIONS PRODUCT calibration % area burned CASA biogeochemical model CO2 emissions (van der Werf et al., Global Change Biology, 2003

  18. INTERANNUAL VARIATIONS OF BIOMASS-BURNING EMISSION • Need for consistent multi-year met. fields

  19. CO INVERSE MODELING USING USING MOPITT MEASUREMENTS

  20. MOPITT RETRIEVAL OF COLUMN CO 2000 1018 molecules cm-2

  21. MOPITT RETRIEVAL OF COLUMN CO FROM MODEL 2000 1018 molecules cm-2

  22. RATIO MODEL/MOPITT Model and measurement biases? Availability of updated OH fields

  23. SURFACE CO IN SH ASC K94 bb new BB obs SMO EIC CGO

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