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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 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
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)
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
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
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
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
INVERSION RESULTS USING CMDL SURFACE MEASUREMENTS
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
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
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
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
OTHER GEOS-CHEM RESULTS Heald et al., 2003
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 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)
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) 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
VIRS FIRE EMISSIONS PRODUCT calibration % area burned CASA biogeochemical model CO2 emissions (van der Werf et al., Global Change Biology, 2003
INTERANNUAL VARIATIONS OF BIOMASS-BURNING EMISSION • Need for consistent multi-year met. fields
CO INVERSE MODELING USING USING MOPITT MEASUREMENTS
MOPITT RETRIEVAL OF COLUMN CO 2000 1018 molecules cm-2
MOPITT RETRIEVAL OF COLUMN CO FROM MODEL 2000 1018 molecules cm-2
RATIO MODEL/MOPITT Model and measurement biases? Availability of updated OH fields
SURFACE CO IN SH ASC K94 bb new BB obs SMO EIC CGO