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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Cited articles

Barr, A., Hollinger, D., and Richardson, A. D.: CO2 Flux Measurement Uncertainty Estimates for NACP, AGU Fall Meeting, December 2009, abstract number B54A-04B, 2009.
Barr, A., Ricciuto, D. M., Schaefer, K., Richardson, A., Agarwal, D., Thornton, P. E., Davis, K., Jackson, B., Cook, R. B., Hollinger, D. Y., van Ingen, C., Amiro, B., ans M. A. Arain, A. A., Baldocchi, D., Black, T. A., Bolstad, P., Curtis, P., Desai, A., Dragoni, D., Flanagan, L., Gu, L., Katul, G., Law, B. E., Lafleur, P., Margolis, H., Matamala, R., Meyers, T., McCaughey, H., Monson, R., Munger, J. W., Oechel, W., Oren, R., Roulet, N., Torn, M., and Verma, S.: NACP Site: Tower Meteorology, Flux Observations with Uncertainty, and Ancillary Data, available at: http://daac.ornl.gov (last access: 10 June 2015) from Oak Ridge National Laboratory Distributed Active Archive Center, https://doi.org/10.3334/ORNLDAAC/1178, 2013.
Braswell, B. H., Sacks, W. J., Linder, E., and Schimel, D. S.: Estimating diurnal to annual ecosystem parameters by synthesis of a carbon flux model with eddy covariance net ecosystem exchange observations, Global Change Biol., 11, 335–355, https://doi.org/10.1111/j.1365-2486.2005.00897.x, 2005.
Campolongo, F., Saltelli, A., Sørensen, T., and Tarantola, S.: Hitchhiker's Guide to Sensitivity Analysis, in: Sensitivity Analysis, edited by: Saltelli, A., Chan, K., and Scott, E., Wiley, Chicester, 2000.
Fox, A., Williams, M., Richardson, A. D., Cameron, D., Gove, J. H., Quaife, T., Ricciuto, D. M., Reichstein, M., Tomelleri, E., Trudinger, C. M., and Wijk, M. T. V.: The REFLEX project: Comparing different algorithms and implementations for the inversion of a terrestrial ecosystem model against eddy covariance data, Agric. For. Meteorol., 149, 1597–1615, https://doi.org/10.1016/j.agrformet.2009.05.002, 2009.
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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.
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