Journal
GEOSCIENTIFIC MODEL DEVELOPMENT
Volume 8, Issue 7, Pages 1899-1918Publisher
COPERNICUS GESELLSCHAFT MBH
DOI: 10.5194/gmd-8-1899-2015
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Funding
- Office of Biological and Environmental Research in the DOE Office of Science
- Scientific Discovery through Advanced Computing (SciDAC) program - US DOE, Office of Science, Advanced Scientific Computing Research
- NERC National Centre for Earth Observation
- US Department of Energy's National Nuclear Security Administration [DE-AC04-94-AL85000]
- UT-BATTELLE for DOE [DE-AC05-00OR22725]
- Natural Environment Research Council [NE/K002619/1, nceo020005, nceo020004] Funding Source: researchfish
- NERC [nceo020005, nceo020004, NE/K002619/1] Funding Source: UKRI
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In this paper we propose a probabilistic framework for an uncertainty quantification (UQ) study of a carbon cycle model and focus on the comparison between steady-state and transient simulation setups. A global sensitivity analysis (GSA) study indicates the parameters and parameter couplings that are important at different times of the year for quantities of interest (QoIs) obtained with the data assimilation linked ecosystem carbon (DALEC) model. We then employ a Bayesian approach and a statistical model error term to calibrate the parameters of DALEC using net ecosystem exchange (NEE) observations at the Harvard Forest site. The calibration results are employed in the second part of the paper to assess the predictive skill of the model via posterior predictive checks.
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