Influence of transport uncertainty on annual mean and seasonal inversions of atmospheric CO2 data

[1] Inversion methods are often used to estimate surface CO2 fluxes from atmospheric CO2 concentration measurements, given an atmospheric transport model to relate the two. The published estimates disagree strongly on the location of the main sources and sinks, however. Are these differences due to the different time spans considered, or are they artifacts of the method and data used? Here we assess the uncertainty in such estimates due to the choice of time discretization of the measurements and fluxes, the spatial resolution of the fluxes, and the transport model. A suite of 27 Bayesian least squares inversions has been run, given by varying the number of flux regions solved for (7, 12, and 17), the time discretization (annual/annual, annual/monthly, and monthly/monthly for the fluxes/data), and the transport model (TM2, TM3, and GCTM), while holding all other inversion details constant. The estimated fluxes from this ensemble of inversions for the land + ocean sum are stable over large zonal bands, but the spread in the results increases when considering the longitudinal flux distribution inside these bands. On average for 1990– 1994 the inversions place a large CO2 uptake north of 30 N (3.2 ± 0.3 GtC yr ), mostly over the land regions, with more in Eurasia than North America. The ocean fluxes are generally smaller than given by Takahashi et al. [1999], especially south of 15 S and in the global total, where they are less than half as large. A small uptake is found for the tropical land regions, suggesting that growth more than compensates for deforestation there. The results for the different transport models are consistent with their known mixing properties; the longitudinal pattern of their land biosphere rectifier, in particular, strongly influences the regional partitioning of the flux in the north. While differences between the transport models contribute significantly to the spread of the results, an equivalent or even larger spread is due to the time discretization method used: Solving for annual mean fluxes with monthly mean measurements tended to give spurious land/ocean flux partition in the north. We suggest then that this time discretization method be avoided. Overall, the uncertainty quoted for the estimated fluxes should include not only the random error calculated by the inversion equations but also all the systematic errors in the problem, such as those addressed in this study.