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References

  • Balgovind, R., A. Dalcher, M. Ghil, and E. Kalnay (1983), A stochastic-dynamic model for the spatial structure of forecast error statistics, Mon. Weather Rev., 111, 701722.
  • Bocquet, M. (2009), Towards optimal choices of control space representation for geophysical data assimilation, Mon. Weather Rev., 137, 23312348.
  • Bocquet, M., and L. Wu (2011), Bayesian design of control space for optimal assimilation of observations. II: Asymptotic solutions, Q. J. R. Meteorol. Soc., 137, 13571368.
  • Bocquet, M., L. Wu, and F. Chevallier (2011), Bayesian design of control space for optimal assimilation of observations. I: Consistent multiscale formalism, Q. J. R. Meteorol. Soc., 137, 13401356.
  • Bousquet, P., P. Peylin, P. Ciais, C. L. Quéré, P. Friedlingstein, and P. P. Tans (2000), Regional changes in carbon dioxide fluxes of land and oceans since 1980, Science, 290(5495), 13421346.
  • Carouge, C., P. J. Rayner, P. Peylin, P. Bousquet, F. Chevallier, and P. Ciais (2010) What can we learn from European continuous atmospheric CO2 measurements to quantify regional fluxes – Part 2: Sensitivity of flux accuracy to inverse setup, Atmos. Chem. Phys., 10(6), 31193129.
  • Chevallier, F., N. Viovy, M. Reichstein, and P. Ciais (2006), On the assignment of prior errors in Bayesian inversions of CO2 surface fluxes, Geophys. Res. Lett., 33, L13802, doi:10.1029/2006GL026496.
  • Chevallier, F., F.-M. Bréon, and P. J. Rayner (2007), Contribution of the orbiting carbon observatory to the estimation of CO2 sources and sinks: Theoretical study in a variational data assimilation framework, J. Geophys. Res., 112, D09307, doi:10.1029/2006JD007375.
  • Enting, I. G. (2002), Inverse Problems in Atmospheric Constituent Transport, Cambridge Univ. Press, Cambridge, U. K.
  • Fan, S., M. Gloor, J. Mahlman, S. Pacala, J. Sarmiento, T. Takahashi, and P. Tans (1998), A large terrestrial carbon sink in North America implied by atmospheric and oceanic carbon dioxide data and models, Science, 282(5388), 442446.
  • Gerbig, C., J. C. Lin, S. C. Wofsy, B. C. Daube, A. E. Andrews, B. B. Stephens, P. S. Bakwin, and C. A. Grainger (2003), Toward constraining regional-scale fluxes of CO2 with atmospheric observations over a continent: 2. Analysis of COBRA data using a receptor-oriented framework, J. Geophys. Res., 108(D24), 4757, doi:10.1029/2003JD003770.
  • Gerbig, C., J. C. Lin, J. W. Munger, and S. C. Wofsy (2006), What can tracer observations in the continental boundary layer tell us about surface-atmosphere fluxes? Atmos. Chem. Phys., 6(2), 539554.
  • Gourdji, S. M., A. I. Hirsch, K. L. Mueller, A. E. Andrews, and A. M. Michalak (2010), Regional-scale geostatistical inverse modeling of North American CO2 fluxes: A synthetic data study, Atmos. Chem. Phys., 10, 61516167.
  • Kaminski, T., P. J. Rayner, M. Heimann, and I. G. Enting (2001), On aggregation errors in atmospheric transport inversions, J. Geophys. Res., 106(D5), 47034715.
  • Lauvaux, T., et al. (2008), Mesoscale inversion: first results from the ceres campaign with synthetic data, Atmos. Chem. Phys., 8(13), 34593471.
  • Lauvaux, T., O. Pannekoucke, C. Sarrat, F. Chevallier, P. Ciais, J. Noilhan, and P. J. Rayner (2009a), Structure of the transport uncertainty in mesoscale inversions of CO2 sources and sinks using ensemble model simulations, Biogeosciences, 6(6), 10891102.
  • Lauvaux, T., et al. (2009b), Bridging the gap between atmospheric concentrations and local ecosystem measurements, Geophys. Res. Lett., 36, L19809, doi:10.1029/2009GL039574.
  • Lauvaux, T., A. E. Schuh, M. Uliasz, S. Richardson, N. Miles, L. I. Diaz, D. Martins, P. Shepson, and K. J. Davis (2011), Constraining the CO2 budget of the corn belt: exploring uncertainties from the assumptions in a mesoscale inverse system, Atmos. Chem. Phys. Discuss., 11, 20,85520,898.
  • Law, R. M., P. J. Rayner, L. P. Steele, and I. G. Enting (2003), Data and modelling requirements for CO2 inversions using high-frequency data, Tellus, Ser. B, 55(2), 512521.
  • Lin, J. C., C. Gerbig, S. C. Wofsy, A. E. Andrews, B. C. Daube, K. J. Davis, and C. A. Grainger (2003), A near-field tool for simulating the upstream influence of atmospheric observations: The stochastic time-inverted Lagrangian transport (STILT) model, J. Geophys. Res., 108(D16), 4493, doi:10.1029/2002JD003161.
  • Lokupitiya, E., et al. (2009), Incorporation of crop phenology in simple biosphere model (SiBcrop) to improve land-atmosphere carbon exchanges from croplands, Biogeosciences, 6, 969986.
  • Michalak, A., L. Bruhwiler, and P. Tans (2004), A geostatistical approach to surface flux estimation of atmospheric trace gases, J. Geophys. Res., 109, D14109, doi:10.1029/2003JD004422.
  • Peters, W., et al. (2007), An atmospheric perspective on North American carbon dioxide exchange: Carbontracker, Proc. Natl. Acad. Sci. U. S. A., 104(48), 18,92518,930.
  • Peylin, P., P. Bousquet, and P. Ciais (2001), Inverse modeling of atmospheric carbon dioxide fluxes - Response, Science, 294(5550), 22922292.
  • Peylin, P., P. J. Rayner, P. Bousquet, C. Carouge, F. Hourdin, P. Heinrich, P. Ciais, and AEROCARB contributors (2005), Daily CO2 flux estimates over Europe from continuous atmospheric measurements: 1. Inverse methodology, Atmos. Chem. Phys., 5(12), 31733186.
  • Pickett-Heaps, C. A., et al. (2011), Atmospheric CO2 inversion validation using vertical profile measurements: Analysis of four independent inversion models, J. Geophys. Res., 116, D12305, doi:10.1029/2010JD014887.
  • Rödenbeck, C., S. Houweling, M. Gloor, and M. Heimann (2003), CO2 flux history 1982–2001 inferred from atmospheric data using a global inversion of atmospheric transport, Atmos. Chem. Phys., 3, 19191964.
  • Rodgers, C. D. (2000), Inverse Methods for Atmospheric Sounding, World Sci., Hoboken, N. J.
  • Saide, P., M. Bocquet, A. Osses, and L. Gallardo (2011), Constraining surface emissions of air pollutants using inverse modeling: method intercomparison and a new two-step two-scale regularization approach, Tellus, Ser. B, 63, 360370.
  • Schuh, A. E., A. S. Denning, K. D. Corbin, I. T. Baker, M. Uliasz, N. Parazoo, A. E. Andrews, and D. E. J. Worthy (2010), A regional high-resolution carbon flux inversion of North America for 2004, Biogeosciences, 7(5), 16251644.
  • Seibert, P., and A. Frank (2004), Source-receptor matrix calculation with a Lagrangian particle dispersion model in backward mode, Atmos. Chem. Phys., 4(1), 5163.
  • Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, W. Wang, and J. G. Powers (2005), A description of the advanced research WRF version 2, Tech. Rep. 468+STR, NCAR, Boulder, Colo.
  • Tans, P. P., I. Y. Fung, and T. Takahashi (1990), Observational constraints on the global atmospheric carbon dioxide budget, Science, 247(4949), 14311438.
  • Tolk, L. F., A. G. C. A. Meesters, A. J. Dolman, and W. Peters (2008), Modelling representation errors of atmospheric CO2 mixing ratios at a regional scale, Atmos. Chem. Phys., 8(22), 65876596.
  • Uliasz, M. (1994), Lagrangian particle dispersion modeling in mesoscale applications, in Environmental Modeling II, edited by P. Zannetti, pp. 71102, Comput. Mech., Southampton, U. K.