A global evaluation of the regional spatial variability of column integrated CO2 distributions

Satellites, such as the Orbiting Carbon Observatory (OCO), are expected to provide global measurements of column-averaged carbon dioxide (CO2) dry-air mole fraction (XCO2) with the potential of improving the scientific understanding of regional carbon cycle processes and budgets. The satellite data products, however, are expected to have large data gaps due to the satellite track and geophysical limitations (e.g., clouds and aerosols). The satellite data will also be representative of the XCO2 distribution at the spatial scale of satellite footprints, which is smaller than the resolution of typical transport or process models. Assessing the ability of the retrieved soundings to capture XCO2 variability over different regions and times, evaluating the representation error associated with using the retrieved XCO2 product to represent XCO2 at typical model resolutions, and filling data gaps while providing an estimate of the associated uncertainty all require the evaluation of the spatial variability of XCO2. In this study, the global spatial covariance structure of XCO2 is evaluated regionally using CO2 concentrations simulated using the MATCH/CASA model. Results show that regional and temporal changes in the XCO2 distribution caused by seasonal changes in surface fluxes and transport produce a spatially and temporally variable XCO2 covariance structure. The effects of model setup and the relatively low resolution of the MATCH/CASA model on the evaluated XCO2 covariance structure are assessed by comparing the MATCH/CASA results to the spatial variability inferred from the higher-resolution PCTM/GEOS-4 global model, the SiB-RAMS regional model, and aircraft campaign point observations. The comparison with the higher-resolution models and aircraft data shows good agreement with MATCH/CASA results, thus indicating that the presented results provide an adequate representation of XCO2 variability as will be measured by satellites such as OCO.