Articles | Volume 15, issue 9
https://doi.org/10.5194/bg-15-2909-2018
https://doi.org/10.5194/bg-15-2909-2018
Research article
 | 
16 May 2018
Research article |  | 16 May 2018

A Bayesian ensemble data assimilation to constrain model parameters and land-use carbon emissions

Sebastian Lienert and Fortunat Joos

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AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (13 Apr 2018) by Christoph Heinze
AR by Sebastian Lienert on behalf of the Authors (13 Apr 2018)  Author's response    Manuscript
ED: Publish as is (25 Apr 2018) by Christoph Heinze
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Short summary
Deforestation, shifting cultivation and wood harvesting cause large carbon emissions, altering climate. We apply a dynamic global vegetation model in a probabilistic framework. Diverse observations are assimilated to establish an optimally performing model and a large ensemble of model versions. Land-use carbon emissions are reported for individual countries, regions and the world. We find that parameter-related uncertainties are on the same order of magnitude as process-related effects.
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