Error statistics of Bayesian CO2 flux inversion schemes as seen from GOSAT


Corresponding author: F. Chevallier, Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, Gif-sur-Yvette, France. (


[1] Statistical modeling is at the root of CO2 atmospheric inversion systems, but few studies have focused on the quality of their assigned probability distributions. In this paper, we assess the reliability of the error models that are in input and in output of a specific CO2 atmospheric inversion system when it assimilates surface air sample measurements. We confront these error models with the mismatch between 4D simulations of CO2 and independent satellite retrievals of the total CO2 column. Taking all sources of uncertainties into account, it is shown that both prior and posterior errors are consistent with the actual departures, to the point that the theoretical error reduction brought by the surface measurements on the simulation of the Greenhouse gases Observing SATellite (GOSAT) total column measurements (15%) corresponds to the actual reduction seen over the midlatitude and tropical lands and over the tropical oceans.