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| Titel |
The zonal structure of tropical O3 and CO as observed by the Tropospheric Emission Spectrometer in November 2004 – Part 1: Inverse modeling of CO emissions |
| VerfasserIn |
D. B. A. Jones, K. W. Bowman, J. A. Logan, C. L. Heald, J. Liu, M. Luo, J. Worden, J. Drummond |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 9, no. 11 ; Nr. 9, no. 11 (2009-06-03), S.3547-3562 |
| Datensatznummer |
250007351
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| Publikation (Nr.) |
 copernicus.org/acp-9-3547-2009.pdf |
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| Zusammenfassung |
| We conduct an inverse modeling analysis of measurements of atmospheric CO
from the TES and MOPITT satellite instruments using the GEOS-Chem global
chemical transport model to quantify emissions of CO in the tropics in
November 2004. We also assess the consistency of the information provided by
TES and MOPITT on surface emissions of CO. We focus on the tropics in
November 2004, during the biomass burning season, because TES observations
of CO and O3 and MOPITT observations of CO reveal significantly greater
abundances of these gases than simulated by the GEOS-Chem model during that
period. We find that both datasets suggest substantially greater emissions
of CO from sub-equatorial Africa and the Indonesian/Australian region than
in the climatological emissions in the model. The a posteriori emissions
from sub-equatorial Africa based on TES and MOPITT data were 173 Tg CO/yr
and 184 Tg CO/yr, respectively, compared to the a priori of 95 Tg CO/yr.
In the Indonesian/Australian region, the a posteriori emissions inferred from
TES and MOPITT data were 155 Tg CO/yr and 185 Tg CO/yr, respectively,
whereas the a priori was 69 Tg CO/yr. The differences between the a
posteriori emission estimates obtained from the two datasets are generally
less than 20%. The a posteriori emissions significantly improve the
simulated distribution of CO, however, large regional residuals remain, and
are likely due to systematic errors in the analysis. Reducing these
residuals and improving the accuracy of top-down emission estimates will
require better characterization of systematic errors in the observations and
the model (chemistry and transport). |
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