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Titel |
Evaluation of a new middle-lower tropospheric CO2 product using data assimilation |
VerfasserIn |
A. Tangborn, L. L. Strow, B. Imbiriba, L. Ott, S. Pawson |
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 ; 13, no. 9 ; Nr. 13, no. 9 (2013-05-02), S.4487-4500 |
Datensatznummer |
250018621
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Publikation (Nr.) |
copernicus.org/acp-13-4487-2013.pdf |
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Zusammenfassung |
Atmospheric CO2 retrievals with peak sensitivity in the mid- to lower
troposphere from the Atmospheric Infrared Sounder (AIRS) have been
assimilated into the GEOS-5 (Goddard Earth Observing System Model, Version 5) constituent assimilation system for the period
1 January 2005 to 31 December 2006. A corresponding model simulation, using
identical initial conditions, circulation, and CO2 boundary fluxes was
also completed. The analyzed and simulated CO2 fields are compared with
surface measurements globally and aircraft measurements over North America.
Surface level monthly mean CO2 values show a marked improvement due to
the assimilation in the Southern Hemisphere, while less consistent
improvements are seen in the Northern Hemisphere. Mean differences with
aircraft observations are reduced at all levels, with the largest decrease
occurring in the mid-troposphere. The difference standard deviations are
reduced slightly at all levels over the ocean, and all levels except the
surface layer over land. These initial experiments indicate that the used
channels contain useful information on CO2 in the middle to lower
troposphere. However, the benefits of assimilating these data are reduced
over the land surface, where concentrations are dominated by uncertain local
fluxes and where the observation density is quite low. Away from these
regions, the study demonstrates the power of the data assimilation technique
for evaluating data that are not co-located, in that the improvements in
mid-tropospheric CO2 by the sparsely distributed partial-column
retrievals are transported by the model to the fixed in situ surface
observation locations in more remote areas. |
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