Articles | Volume 8, issue 7
https://doi.org/10.5194/gmd-8-1899-2015
https://doi.org/10.5194/gmd-8-1899-2015
Methods for assessment of models
 | 
01 Jul 2015
Methods for assessment of models |  | 01 Jul 2015

Global sensitivity analysis, probabilistic calibration, and predictive assessment for the data assimilation linked ecosystem carbon model

C. Safta, D. M. Ricciuto, K. Sargsyan, B. Debusschere, H. N. Najm, M. Williams, and P. E. Thornton

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Short summary
In this paper we propose a probabilistic framework for an uncertainty quantification study of a carbon cycle model and focus on the comparison between steady-state and transient simulation setups. We study model parameters via global sensitivity analysis and employ a Bayesian approach to calibrate these parameters using NEE observations at the Harvard Forest site. The calibration results are then used to assess the predictive skill of the model via posterior predictive checks.