4.3 Article

Atmospheric carbon dioxide retrieved from the Greenhouse gases Observing SATellite (GOSAT): Comparison with ground-based TCCON observations and GEOS-Chem model calculations

Journal

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1029/2012JD018087

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Funding

  1. NERC
  2. NCEO
  3. RCUK fellowship
  4. NASA [NNX11AG01G]
  5. DOE/ARM [C01X0204, CO1X0406]
  6. Bialystok and Orleans TCCON sites from the Senate of Bremen and EU
  7. Natural Environment Research Council [earth010004, NE/G01115X/1, earth010003] Funding Source: researchfish
  8. NERC [earth010003, NE/G01115X/1, earth010004] Funding Source: UKRI

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We retrieved column-averaged dry air mole fractions of atmospheric carbon dioxide (X-CO2) from backscattered short-wave infrared (SWIR) sunlight measured by the Japanese Greenhouse gases Observing SATellite (GOSAT). Over two years of X-CO2 retrieved from GOSAT is compared with X-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-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-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-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-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.

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