Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/38353
Title: Atmospheric carbon dioxide retrieved from the Greenhouse gases Observing SATellite (GOSAT): Comparison with ground-based TCCON observations and GEOS-Chem model calculations
Authors: Cogan, A. J.
Boesch, H.
Parker, R. J.
Feng, L.
Palmer, P. I.
Blavier, J-F. L.
Deutscher, N. M.
Macatangay, R.
Notholt, J.
Roehl, C.
Warneke, T.
Wunch, D.
First Published: 1-Nov-2012
Publisher: American Geophysical Union (AGU), Wiley
Citation: Journal of Geophysical Research: Atmospheres, 2012, 117, pp. ?-? (17)
Abstract: We retrieved column-averaged dry air mole fractions of atmospheric carbon dioxide (X[SUBSCRIPT CO2]) from backscattered short-wave infrared (SWIR) sunlight measured by the Japanese Greenhouse gases Observing SATellite (GOSAT). Over two years of X [SUBSCRIPT CO2] retrieved from GOSAT is compared with X [SUBSCRIPT CO2] inferred from collocated SWIR measurements by seven ground-based Total Carbon Column Observing Network (TCCON) stations. The average difference between GOSAT and TCCON X [SUBSCRIPT CO2] for individual TCCON sites ranges from −0.87 ppm to 0.77 ppm with a mean value of 0.1 ppm and standard deviation of 0.56 ppm. We find an average bias between all GOSAT and TCCON X [SUBSCRIPT CO2] retrievals of −0.20 ppm with a standard deviation of 2.26 ppm and a correlation coefficient of 0.75. One year of X [SUBSCRIPT CO2] was retrieved from GOSAT globally, which was compared to global 3-D GEOS-Chem chemistry transport model calculations. We find that the latitudinal gradient, seasonal cycles, and spatial variability of GOSAT and GEOS-Chem agree well in general with a correlation coefficient of 0.61. Regional differences between GEOS-Chem model calculations and GOSAT observations are typically less than 1 ppm except for the Sahara and central Asia where a mean difference between 2 to 3 ppm is observed, indicating regional biases in the GOSAT X [SUBSCRIPT CO2] retrievals unobserved by the current TCCON network. Using a bias correction scheme based on linear regression these regional biases are significantly reduced, approaching the required accuracy for surface flux inversions.
DOI Link: 10.1029/2012JD018087
ISSN: 2169-897X
eISSN: 2169-8996
Links: http://onlinelibrary.wiley.com/doi/10.1029/2012JD018087/abstract
http://hdl.handle.net/2381/38353
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: Archived with reference to SHERPA/RoMEO and publisher website.
Appears in Collections:Published Articles, Dept. of Physics and Astronomy

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