Resolving the discrepancies between NEE estimates based upon (1) ground studies and (2) atmospheric inversion results, demands increasingly sophisticated techniques. In this paper we present a high-resolution inversion based upon a regional meteorology model (RAMS) and an un-derlying biosphere (SiB3) model, both running on an identical 40 km grid over most of North Amer-ica. Current operational systems like CarbonTracker as well as many previous global inversions 5 including the Transcom suite of inversions have utilized inversion regions formed by collapsing biome-similar grid cells into larger aggregated regions. An extreme example of this might be where corrections to NEE correction imposed on forested regions on the east coast of the United States might be the same as that imposed on forests on the west coast of the United States while, in reality, there likely exist subtle differences in the two areas, both natural and anthropogenic. Our current 10 inversion framework utilizes a combination of previously employed inversion techniques while al-lowing carbon flux corrections to be biome independent. Temporally and spatially high-resolution results utilizing biome-independent corrections provide insight into carbon dynamics in North Amer-ica. In particular, we analyze hourly CO 2 mixing ratio data from a sparse network of eight towers in North America for 2004. A prior estimate of carbon fluxes due to gross primary productivity 15 (GPP) and ecosystem respiration (ER) is constructed from the SiB3 biosphere model on a 40 km grid. A combination of transport from the RAMS and the parameterized chemical transport model (PCTM) models is used to forge a connection between upwind biosphere fluxes and downwind ob-served CO 2 mixing ratio data. A Kalman filter procedure is used to estimate weekly corrections to biosphere fluxes based upon observed CO 2 . RMSE-weighted annual NEE estimates, over an ensem-20 ble of potential inversion parameter sets, show a mean estimate 0.57 Pg/yr sink in North America. 1 We perform the inversion with two independently derived boundary inflow conditions and calculate jackknife-based statistics to test the robustness of the model results. We then compare final results to estimates obtained from the CarbonTracker inversion system and at the Southern Great Plains flux site. Results are promising, showing the ability to correct carbon fluxes from the biosphere 25 models over annual and seasonal time scales, as well as over the different GPP and ER components. Additionally, the correlation of an estimated sink of carbon in the South Central United States with regional anomalously high precipitation in an area of managed agricultural and forest lands provides interesting hypotheses for future work.