4.6 Article

An intercomparison of inverse models for estimating sources and sinks of CO2 using GOSAT measurements

Journal

JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES
Volume 120, Issue 10, Pages 5253-5266

Publisher

AMER GEOPHYSICAL UNION
DOI: 10.1002/2014JD022962

Keywords

carbon cycle; carbon dioxide; inverse modeling; model intercomparison; satellite remote sensing

Funding

  1. ESA via the GHG-CCI project
  2. Natural Environment Research Council [nceo020005, nceo020004] Funding Source: researchfish
  3. NERC [nceo020004, nceo020005] Funding Source: UKRI

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This study presents the outcome of an inverse modeling intercomparison experiment on the use of total column CO2 retrievals from Greenhouse Gas Observing Satellite (GOSAT) for quantifying global sources and sinks of CO2. Eight research groups submitted inverse modeling results for the first year of GOSAT measurements. Inversions were carried out using only GOSAT data, a combination of GOSAT and surface measurements, and using only surface measurements. As expected, the most robust flux estimates are obtained at large scales (e.g., within 20% of the annual flux at the global scale), and they quickly diverge toward the scale of the subcontinental TRANSCOM regions and beyond (to >100% of the annual flux). We focus our analysis on a shift in the CO2 uptake over land from the Tropics toward the Northern Hemisphere Extra tropics of approximate to 1 PgC/yr when GOSAT data are used in the inversions. This shift is largely driven by TRANSCOM regions Europe and Northern Africa, showing, respectively, an increased uptake and release of 0.7 and 0.9 PgC/yr. Inversions using GOSAT data show a reduced gradient between midlatitudes of the Northern Hemisphere and the Tropics, consistent with the latitudinal shift in carbon uptake. However, the reduced gradients degrade the agreement with background aircraft and surface measurements. To narrow the range of inversion-derived flux, estimates will require further efforts to understand the differences not only between the retrieval schemes but also between inverse models, as their contributions to the overall uncertainty are estimated to be of similar magnitude.

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