Articles | Volume 20, issue 20
Atmos. Chem. Phys., 20, 12063–12091, 2020
https://doi.org/10.5194/acp-20-12063-2020
Atmos. Chem. Phys., 20, 12063–12091, 2020
https://doi.org/10.5194/acp-20-12063-2020

Research article 26 Oct 2020

Research article | 26 Oct 2020

The regional European atmospheric transport inversion comparison, EUROCOM: first results on European-wide terrestrial carbon fluxes for the period 2006–2015

Guillaume Monteil et al.

Data sets

EUROCOM ensemble of inversion results for 2006-2015 Guillaume Monteil, Grégoire Broquet, Marko Scholze, Matthew Lang, Christoph Gerbig, Franz-Thomas Koch, Naomi Smith, Rona Thompson, Ingrid T. Luijkx, and Emily White https://doi.org/10.18160/G068-1T09

FLEXINVERT inversion results for 2006-2015 for EUROCOM inversion intercomparison Rona Thompson https://doi.org/10.18160/KNWQ-9397

CarboScope - Regional inversion results for 2006-2015 for EUROCOM inversion intercomparison Franz-Thomas Koch and Christoph Gerbig https://doi.org/10.18160/A7M2-TM1V

LUMIA inversion results for 2006-2015 for EUROCOM inversion intercomparison Guillaume Monteil https://doi.org/10.18160/RF8X-8RJ2

NAME-HB inversion results for 2011-2015 for EUROCOM inversion intercomparison Emily White, Matthew Rigby, Anita Ganesan, and Alistait Manning https://doi.org/10.18160/6179-A02U

PYVAR-CHIMERE inversion results for 2006-2015 for EUROCOM inversion intercomparison Matthew Lang and Grégoire Broquet https://doi.org/10.18160/3YGA-X0HR

CarbonTracker Europe inversion results for 2006-2015 for EUROCOM inversion intercomparison Naomi Smith, Ingrid T. van der Laan-Luijkx, and Wouter Peters https://doi.org/10.18160/ZA4Q-MHF4

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Short summary
The paper presents the first results from the EUROCOM project, a regional atmospheric inversion intercomparison exercise involving six European research groups. It aims to produce an estimate of the net carbon flux between the European terrestrial ecosystems and the atmosphere for the period 2006–2015, based on constraints provided by observed CO2 concentrations and using inverse modelling techniques. The use of six different models enables us to investigate the robustness of the results.
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