Using CO2 spatial variability to quantify representation errors of satellite CO2 retrievals

Satellite measurements of column-averaged CO2 dryair mole fraction (XCO2) will be used in inversion and data assimilation studies to improve the precision and resolution of current estimates of global fluxes of CO2. Representation errors due to the mismatch in spatial scale between satellite retrievals and atmospheric transport models contribute to the uncertainty associated with flux estimates. This study presents a statistical method for quantifying representation errors as a function of the underlying spatial variability of XCO2 and the spatial distribution of retrieved soundings, without knowledge of the true XCO2 distribution within model gridcells. Representation errors are quantified globally using regional XCO2 spatial variability inferred using the PCTM/GEOS-4 model and a hypothetical atmospheric transport model with 1° × 1° resolution, 3 km2 retrieval footprints, and two different sounding densities.