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International audience; Northern Eurasia is the largest terrestrial reservoir of carbon, and its dynamics and interactions with climate are globally significant. We present five independent estimates of the contemporary carbon balance of central Siberia using three different methodologies: a landscape-ecosystem approach (LEA) that amalgamates comprehensive vegetation, soil, hydrological and morphological information into a Geographical Information System, linked to regression-based estimates of carbon flux; two Dynamic Global Vegetation Models (DGVMs); and two atmospheric inversions. Apart from one of the DGVMs, all methods produce estimates of the net biome productivity (NBP) that are consistent both amongst themselves and with a range of other estimates. They indicate the region to be a carbon sink with a NBP of 27.5 +/- 7.2 g C m-2 yr-1, which is equivalent to 352 +/- 92 Mt C yr-1 if considered representative for boreal Asia. This is comparable with fossil fuel emissions for the Russian Federation, currently estimated as 427 MtC yr-1, and implies that boreal Asia does not play the major role in the northern hemisphere land sink, typically estimated to be of magnitude 1.5-2.9 Gt C yr-1. The LEA and DGVM approaches produce very different partitioning of NBP into its component fluxes. The DGVMs find net primary production (NPP) to be nearly balanced by heterotrophic respiration, disturbance being a relatively small term pushing the system closer to equilibrium. In the LEA, heterotrophic respiration is significantly less than NPP, and disturbance plays a much larger role in the overall carbon balance. The use in the LEA of observationally based estimates of heterotrophic respiration and fire disturbance, along with a more complete description of disturbance fluxes, suggests that the partitioning derived by the LEA is more likely, and that improved process descriptions and constraints by data are needed in the DGVMs.

International audience; Large-scale carbon sources and sinks can be estimated by combining atmospheric CO2 concentration data with atmospheric transport inverse modeling. This approach has been limited by sparse spatiotemporal tropospheric sampling. CO2 estimates from space using observations on recently launched satellites (Atmospheric Infrared Sounder (AIRS)), or platforms to be launched (Infrared Atmospheric Sounding Interferometer (IASI), Orbiting Carbon Observatory (OCO)) have the potential to fill some of these gaps. Here we assess the realism of initial AIRS-based mid-to-upper troposphere CO2 estimates from European Centre for Medium-Range Weather Forecasts by comparing them with simulations of two transport models (TM3 and Laboratoire Meteorologie Dynamique Zoom (LMDZ)) forced with one data-based set of surface fluxes. The simulations agree closer with one another than with the retrievals. Nevertheless, there is good overall agreement between all estimates of seasonal cycles and north-south gradients within the latitudinal band extending from 30 degrees S to 30 degrees N, but not outside this region. At smaller spatial scales, there is a contrast in the satellite-based retrievals above continents versus above oceans that is absent in the model predictions. Hovmoeller diagrams indicate that in the models, high Northern Hemisphere winter CO2 concentrations propagate toward the tropical upper troposphere via Northern Hemisphere high latitudes, while in retrievals, elevated winter CO2 appears instantaneously throughout the Northern Hemisphere. This raises questions about lower-to-upper troposphere transport pathways. Prerequisites for use of retrievals to provide an improved constraint on surface fluxes are therefore further improvements in retrievals and better understanding/validation of lower-to-upper troposphere transport and its modeling. This calls for more independent upper troposphere transport tracer data like SF6 and CO2.