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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 8, issue 7
Geosci. Model Dev., 8, 1899–1918, 2015
https://doi.org/10.5194/gmd-8-1899-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 8, 1899–1918, 2015
https://doi.org/10.5194/gmd-8-1899-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

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 et al.
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Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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AR: Author's response | RR: Referee report | ED: Editor decision
AR by Cosmin Safta on behalf of the Authors (04 May 2015)  Author's response
ED: Referee Nomination & Report Request started (05 May 2015) by Julia Hargreaves
RR by Anonymous Referee #1 (20 May 2015)
ED: Publish subject to minor revisions (Editor review) (21 May 2015) by Julia Hargreaves
AR by Cosmin Safta on behalf of the Authors (08 Jun 2015)  Author's response    Manuscript
ED: Publish as is (09 Jun 2015) by Julia Hargreaves
Publications Copernicus
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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.
In this paper we propose a probabilistic framework for an uncertainty quantification study of a...
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