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Estimation of global CO2 fluxes using ground-based and satellite (GOSAT) observation data with empirical orthogonal functions

Abstract

An inverse problem of atmospheric transport has been solved as applied to the estimation of monthly average surface CO2 fluxes for 2009 using ground-based observation data and GOSAT data beginning from June, 2009. Corrections to the flux fields for each kind of sources are represented as a linear combination of main flux components of the corresponding surface gas-exchange fields. To calculate the atmospheric transport, the coupled Eulerian-Lagrangian model (GELCA) is used. A large array of observation data is used (3000–5000 observations per month); therefore, the Fix-Lag Kalman Smoother is used, which allows monthly fluxes to be estimated sequentially, according to a chosen size of assimilation window. The calculation results are represented in the form of 2D fields of monthly average flux fields, and recalculated for chosen regions. The calculations show a significant decrease in the posterior flux uncertainty when using GOSAT observations.

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Original Russian Text © R.V. Zhuravlev, A.V. Ganshin, Sh.Sh. Maksyutov, S.L. Oshchepkov, B.V. Khattatov, 2013, published in Optica Atmosfery i Okeana.

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Zhuravlev, R.V., Ganshin, A.V., Maksyutov, S.S. et al. Estimation of global CO2 fluxes using ground-based and satellite (GOSAT) observation data with empirical orthogonal functions. Atmos Ocean Opt 26, 507–516 (2013). https://doi.org/10.1134/S1024856013060158

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  • DOI: https://doi.org/10.1134/S1024856013060158

Keywords

  • Empirical Orthogonal Function
  • Satellite Observation
  • Atmospheric Transport
  • Lagrangian Model
  • Empirical Orthogonal Function