Articles | Volume 9, issue 1
Biogeosciences, 9, 457–475, 2012
Biogeosciences, 9, 457–475, 2012

Research article 25 Jan 2012

Research article | 25 Jan 2012

North American CO2 exchange: inter-comparison of modeled estimates with results from a fine-scale atmospheric inversion

S. M. Gourdji1,*, K. L. Mueller1,**, V. Yadav1,***, D. N. Huntzinger1,****, A. E. Andrews2, M. Trudeau2, G. Petron2, T. Nehrkorn3, J. Eluszkiewicz3, J. Henderson3, D. Wen4, J. Lin4, M. Fischer5, C. Sweeney2, and A. M. Michalak1,*** S. M. Gourdji et al.
  • 1Department of Civil & Environmental Engineering, University of Michigan, Ann Arbor, MI, 48108, USA
  • 2Global Monitoring Division, Earth System Research Laboratory, National Oceanic & Atmospheric Administration, Boulder, CO 80305, USA
  • 3Atmospheric and Environmental Research, Inc., Lexington, MA, 02421, USA
  • 4Department of Earth & Environmental Sciences, University of Waterloo, Waterloo, ON, N2L 3G1, Canada
  • 5Lawrence Berkeley National Lab, Berkeley, CA, 94720, USA
  • *now at: Department of Environmental Earth System Science, and Center on Food Security and the Environment, Stanford University, Stanford, CA 94305, USA
  • **now at: American Association for the Advancement of Science Policy Fellow, Washington, DC, 20515, USA
  • ***now at: Department of Global Ecology, Carnegie Institution for Science, Stanford, CA 94305, USA
  • ****now at: School of Earth Sciences and Environmental Sustainability, Northern Arizona University, Flagstaff, AZ, 86011, USA

Abstract. Atmospheric inversion models have the potential to quantify CO2 fluxes at regional, sub-continental scales by taking advantage of near-surface CO2 mixing ratio observations collected in areas with high flux variability. This study presents results from a series of regional geostatistical inverse models (GIM) over North America for 2004, and uses them as the basis for an inter-comparison to other inversion studies and estimates from biospheric models collected through the North American Carbon Program Regional and Continental Interim Synthesis. Because the GIM approach does not require explicit prior flux estimates and resolves fluxes at fine spatiotemporal scales (i.e. 1° × 1°, 3-hourly in this study), it avoids temporal and spatial aggregation errors and allows for the recovery of realistic spatial patterns from the atmospheric data relative to previous inversion studies. Results from a GIM inversion using only available atmospheric observations and a fine-scale fossil fuel inventory were used to confirm the quality of the inventory and inversion setup. An inversion additionally including auxiliary variables from the North American Regional Reanalysis found inferred relationships with flux consistent with physiological understanding of the biospheric carbon cycle. Comparison of GIM results with bottom-up biospheric models showed stronger agreement during the growing relative to the dormant season, in part because most of the biospheric models do not fully represent agricultural land-management practices and the fate of both residual biomass and harvested products. Comparison to earlier inversion studies pointed to aggregation errors as a likely source of bias in previous sub-continental scale flux estimates, particularly for inversions that adjust fluxes at the coarsest scales and use atmospheric observations averaged over long periods. Finally, whereas the continental CO2 boundary conditions used in the GIM inversions have a minor impact on spatial patterns, they have a substantial impact on the continental carbon budget, with a difference of 0.8 PgC yr−1 in the total continental flux resulting from the use of two plausible sets of boundary CO2 mixing ratios. Overall, this inter-comparison study helps to assess the state of the science in estimating regional-scale CO2 fluxes, while pointing towards the path forward for improvements in future top-down and bottom-up modeling efforts.

Final-revised paper