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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 3, issue 2
Geosci. Model Dev., 3, 689-716, 2010
https://doi.org/10.5194/gmd-3-689-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 3, 689-716, 2010
https://doi.org/10.5194/gmd-3-689-2010
© Author(s) 2010. This work is distributed under
the Creative Commons Attribution 3.0 License.

Model description paper 15 Dec 2010

Model description paper | 15 Dec 2010

Modeling global atmospheric CO2 with improved emission inventories and CO2 production from the oxidation of other carbon species

R. Nassar*,2,1, D. B. A. Jones1, P. Suntharalingam3, J. M. Chen2, R. J. Andres4, K. J. Wecht5, R. M. Yantosca6, S. S. Kulawik7, K. W. Bowman7, J. R. Worden7, T. Machida8, and H. Matsueda9 R. Nassar et al.
  • 1Department of Physics, University of Toronto, 60 St. George Street, Toronto, Ontario, M5S 1A7, Canada
  • 2Department of Geography, University of Toronto, 45 St. George Street, Toronto, Ontario, M5S 2E5, Canada
  • 3Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, UK
  • 4Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, 37831-6335, USA
  • 5Department of Earth and Planetary Sciences, Harvard University, Pierce Hall, 29 Oxford St., Cambridge, MA, 02138, USA
  • 6School of Engineering and Applied Sciences, Harvard University, Pierce Hall, 29 Oxford St., Cambridge, MA, 02138, USA
  • 7Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA, 91109, USA
  • 8National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba-City, Ibaraki, 305-8506, Japan
  • 9Meteorological Research Institute, 1-1 Nagamine, Tsukuba-City, Ibaraki 305-0052, Japan
  • *now at: Climate Research Division, Environment Canada, 4905 Dufferin St., Toronto, Ontario, M3H 5T4, Canada

Abstract. The use of global three-dimensional (3-D) models with satellite observations of CO2 in inverse modeling studies is an area of growing importance for understanding Earth's carbon cycle. Here we use the GEOS-Chem model (version 8-02-01) CO2 mode with multiple modifications in order to assess their impact on CO2 forward simulations. Modifications include CO2 surface emissions from shipping (~0.19 Pg C yr−1), 3-D spatially-distributed emissions from aviation (~0.16 Pg C yr−1), and 3-D chemical production of CO2 (~1.05 Pg C yr−1). Although CO2 chemical production from the oxidation of CO, CH4 and other carbon gases is recognized as an important contribution to global CO2, it is typically accounted for by conversion from its precursors at the surface rather than in the free troposphere. We base our model 3-D spatial distribution of CO2 chemical production on monthly-averaged loss rates of CO (a key precursor and intermediate in the oxidation of organic carbon) and apply an associated surface correction for inventories that have counted emissions of CO2 precursors as CO2. We also explore the benefit of assimilating satellite observations of CO into GEOS-Chem to obtain an observation-based estimate of the CO2 chemical source. The CO assimilation corrects for an underestimate of atmospheric CO abundances in the model, resulting in increases of as much as 24% in the chemical source during May–June 2006, and increasing the global annual estimate of CO2 chemical production from 1.05 to 1.18 Pg C. Comparisons of model CO2 with measurements are carried out in order to investigate the spatial and temporal distributions that result when these new sources are added. Inclusion of CO2 emissions from shipping and aviation are shown to increase the global CO2 latitudinal gradient by just over 0.10 ppm (~3%), while the inclusion of CO2 chemical production (and the surface correction) is shown to decrease the latitudinal gradient by about 0.40 ppm (~10%) with a complex spatial structure generally resulting in decreased CO2 over land and increased CO2 over the oceans. Since these CO2 emissions are omitted or misrepresented in most inverse modeling work to date, their implementation in forward simulations should lead to improved inverse modeling estimates of terrestrial biospheric fluxes.

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