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Volume 18, issue 4
Atmos. Chem. Phys., 18, 3047–3064, 2018
https://doi.org/10.5194/acp-18-3047-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Data assimilation in carbon/biogeochemical cycles: consistent...

Atmos. Chem. Phys., 18, 3047–3064, 2018
https://doi.org/10.5194/acp-18-3047-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 02 Mar 2018

Research article | 02 Mar 2018

Atmospheric CO2 inversions on the mesoscale using data-driven prior uncertainties: quantification of the European terrestrial CO2 fluxes

Panagiotis Kountouris1, Christoph Gerbig1, Christian Rödenbeck1, Ute Karstens1,a, Thomas F. Koch2, and Martin Heimann1 Panagiotis Kountouris et al.
  • 1Department of Biogeochemical Systems, Max Planck Institute for Biogeochemistry, Jena, Germany
  • 2Meteorological Observatory Hohenpeissenberg, Deutscher Wetterdienst, Germany
  • anow at: ICOS Carbon Portal, Lund University, Lund, Sweden

Abstract. Optimized biogenic carbon fluxes for Europe were estimated from high-resolution regional-scale inversions, utilizing atmospheric CO2 measurements at 16 stations for the year 2007. Additional sensitivity tests with different data-driven error structures were performed. As the atmospheric network is rather sparse and consequently contains large spatial gaps, we use a priori biospheric fluxes to further constrain the inversions. The biospheric fluxes were simulated by the Vegetation Photosynthesis and Respiration Model (VPRM) at a resolution of 0.1° and optimized against eddy covariance data. Overall we estimate an a priori uncertainty of 0.54 GtC yr−1 related to the poor spatial representation between the biospheric model and the ecosystem sites. The sink estimated from the atmospheric inversions for the area of Europe (as represented in the model domain) ranges between 0.23 and 0.38 GtC yr−1 (0.39 and 0.71 GtC yr−1 up-scaled to geographical Europe). This is within the range of posterior flux uncertainty estimates of previous studies using ground-based observations.

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