Atmospheric Chemistry and Physics Discussions
www.atmos-chem-phys-discuss.net
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9
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2009
10.5194/acpd-9-19967-2009
http://www.atmos-chem-phys-discuss.net/9/19967/2009/
http://www.atmos-chem-phys-discuss.net/9/19967/2009/acpd-9-19967-2009.html
http://www.atmos-chem-phys-discuss.net/9/19967/2009/acpd-9-19967-2009.pdf
19967
20018
2009-09-24
Global estimates of CO sources with high resolution by adjoint inversion of multiple satellite datasets (MOPITT, AIRS, SCIAMACHY, TES)
M. Kopacz
mkopacz@princeton.edu
D. J. Jacob
J. A. Fisher
J. A. Logan
L. Zhang
I. A. Megretskaia
R. M. Yantosca
K. Singh
D. K. Henze
J. P. Burrows
M. Buchwitz
I. Khlystova
W. W. McMillan
J. C. Gille
D. P. Edwards
A. Eldering
V. Thouret
P. Nedelec
School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA
Department of Computer Science, Virginia Polytechnic Institute, Blacksburg, VA, USA
Department of Mechanical Engineering, University of Colorado at Boulder, CO, USA
Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany
Department of Physics, University of Maryland Baltimore County, Baltimore, MD, USA
National Center for Atmospheric Research, Boulder, Colorado, USA
Jet Propulsion Laboratory, Pasadena, CA, USA
Universite de Toulouse, Toulouse, France
CNRS, LA (Laboratoire d'Aérologie), 31400 Toulouse, France
now at: Woodrow Wilson School of International and Public Affairs, Princeton University, Princeton, NJ, USA
We combine CO column measurements from the MOPITT, AIRS, SCIAMACHY,
and TES satellite instruments in a full-year (May 2004–April 2005)
global inversion of CO sources at
4°×5° spatial resolution and
monthly temporal resolution. The inversion uses the GEOS-Chem chemical
transport model (CTM) and its adjoint applied to MOPITT, AIRS, and
SCIAMACHY. Observations from TES, surface sites (NOAA/GMD), and
aircraft (MOZAIC) are used for evaluation of the a posteriori
solution. Global intercomparison of the different satellite datasets
using GEOS-Chem as a common intercomparison platform shows consistency
between the satellite datasets and with the in situ data. The majority
of the differences between the datasets can be explained by different
averaging kernels and a priori information. The global CO emission
from combustion as constrained in the inversion is
1350 Tg a<sup>−1</sup>, with an additional 217 Tg a<sup>−1</sup>
from oxidation of co-emitted VOCs. This is much higher than current
bottom-up emission inventories. Consistent with both the satellite and
in situ data, a large fraction of the correction results from
a seasonal underestimate of CO sources at northern mid-latitudes and
suggests a larger-than-expected CO source from vehicle cold starts and
residential heating. A posteriori emissions also indicate a general
underestimation of biomass burning relative to the GFED2
inventory. However, the tropical biomass burning constraints are not
consistent across the different datasets. Although the datasets reveal
regional inconsistencies over tropical biomass burning regions, we
find the global emission estimates to be a balance of information from
all three instruments.
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