Journal cover Journal topic
Biogeosciences An interactive open-access journal of the European Geosciences Union
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Volume 15, issue 9
Biogeosciences, 15, 2909-2930, 2018
https://doi.org/10.5194/bg-15-2909-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Special issue: The 10th International Carbon Dioxide Conference (ICDC10)...

Biogeosciences, 15, 2909-2930, 2018
https://doi.org/10.5194/bg-15-2909-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

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 Lienert1,2 and Fortunat Joos1,2 Sebastian Lienert and Fortunat Joos
  • 1Climate and Environmental Physics, Physics Institute, University of Bern, Bern, Switzerland
  • 2Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland

Abstract. A dynamic global vegetation model (DGVM) is applied in a probabilistic framework and benchmarking system to constrain uncertain model parameters by observations and to quantify carbon emissions from land-use and land-cover change (LULCC). Processes featured in DGVMs include parameters which are prone to substantial uncertainty. To cope with these uncertainties Latin hypercube sampling (LHS) is used to create a 1000-member perturbed parameter ensemble, which is then evaluated with a diverse set of global and spatiotemporally resolved observational constraints. We discuss the performance of the constrained ensemble and use it to formulate a new best-guess version of the model (LPX-Bern v1.4). The observationally constrained ensemble is used to investigate historical emissions due to LULCC (ELUC) and their sensitivity to model parametrization. We find a global ELUC estimate of 158 (108, 211)PgC (median and 90% confidence interval) between 1800 and 2016. We compare ELUC to other estimates both globally and regionally. Spatial patterns are investigated and estimates of ELUC of the 10 countries with the largest contribution to the flux over the historical period are reported. We consider model versions with and without additional land-use processes (shifting cultivation and wood harvest) and find that the difference in global ELUC is on the same order of magnitude as parameter-induced uncertainty and in some cases could potentially even be offset with appropriate parameter choice.

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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.
Deforestation, shifting cultivation and wood harvesting cause large carbon emissions, altering...
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