A coarse grid three-dimensional global inverse model of the atmospheric transport - 2. Inversion of the transport of CO2 in the 1980s

Models of atmospheric transport can be used to interpret spatiotemporal dif ferences in the observed concentrations of CO2 in terms of its surface exch ange fluxes, Inversion of the atmospheric transport is the systematic searc h for both a flux field that yields an optimal match between modeled and ob served concentrations and, equally importantly, the uncertainties in this i nferred flux field. The present inversion study combines observations of th e CO2 concentration at the global station network of the NOAA/CMDL in the 1 980s with a representation of the atmospheric transport model TM2 by its Ja cobian matrix, which has been previously computed by the adjoint model of T M2, This Jacobian matrix maps monthly fluxes on the approximately 8 degrees latitude by 10 degrees longitude horizontal model grid onto the resulting changes in the monthly CO2 concentration at every station. Since the number of observational sites is much smaller than the number of grid cells, the inverse problem is highly underdetermined. A unique solution is determined by including a priori information on the surface exchange fluxes derived fr om output of high-resolution models of both the terrestrial biosphere and t he ocean, combined with statistics of fossil fuel burning and land use chan ge. Performing a Bayesian synthesis inversion, for a target period in the 1 980s, the average seasonal cycle and the mean annual magnitude of CO2 surfa ce fluxes on the TM2 grid are inferred. The resulting simulated concentrati on compares well with independent observations. On a global scale, an ocean ic sink of 1.5 +/- 0.4 gigatons of carbon (GtC) is estimated. This sink is stronger in the northern than in the southern hemisphere. On a regional sca le, however, the inferred exchange fluxes exhibit high uncertainty, indicat ing a low capacity of the global observational network to monitor regional trace gas emissions. These findings are relatively insensitive to the year of meteorological driving data, suggesting interannual changes in concentra tion should primarily result from source not transport changes.