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| Titel |
Regional CO2 flux estimates for 2009–2010 based on GOSAT and ground-based CO2 observations |
| VerfasserIn |
S. Maksyutov, H. Takagi, V. K. Valsala, M. Saito, T. Oda, T. Saeki, D. A. Belikov, R. Saito, A. Ito, Y. Yoshida, I. Morino, O. Uchino, R. J. Andres, T. Yokota |
| 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. 18 ; Nr. 13, no. 18 (2013-09-17), S.9351-9373 |
| Datensatznummer |
250085704
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| Publikation (Nr.) |
 copernicus.org/acp-13-9351-2013.pdf |
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| Zusammenfassung |
| We present the application of a global carbon cycle
modeling system to the estimation of monthly regional CO2
fluxes from the column-averaged mole fractions of CO2
(XCO2) retrieved from spectral observations made by the
Greenhouse gases Observing SATellite (GOSAT). The regional flux
estimates are to be publicly disseminated as the GOSAT Level 4 data
product. The forward modeling components of the system include an
atmospheric tracer transport model, an anthropogenic emissions
inventory, a terrestrial biosphere exchange model, and an oceanic
flux model. The atmospheric tracer transport was simulated using
isentropic coordinates in the stratosphere and was tuned to
reproduce the age of air. We used a fossil fuel emission inventory
based on large point source data and observations of nighttime
lights. The terrestrial biospheric model was optimized by fitting
model parameters to observed atmospheric CO2 seasonal cycle,
net primary production data, and a biomass distribution map. The
oceanic surface pCO2 distribution was estimated with a 4-D
variational data assimilation system based on reanalyzed ocean
currents. Monthly CO2 fluxes of 64 sub-continental regions,
between June 2009 and May 2010, were estimated from GOSAT FTS SWIR
Level 2 XCO2 retrievals (ver. 02.00) gridded to
5° × 5° cells and averaged on a monthly
basis and monthly-mean GLOBALVIEW-CO2 data. Our result
indicated that adding the GOSAT XCO2 retrievals to the
GLOBALVIEW data in the flux estimation brings changes to fluxes of
tropics and other remote regions where the surface-based data are
sparse. The uncertainties of these remote fluxes were reduced by as
much as 60% through such addition. Optimized fluxes estimated for
many of these regions, were brought closer to the prior fluxes by
the addition of the GOSAT retrievals. In most of the regions and
seasons considered here, the estimated fluxes fell within the range
of natural flux variabilities estimated with the component models. |
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