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www.geosci-model-dev-discuss.net/4/1513/2011/
doi:10.5194/gmdd-4-1513-2011
© Author(s) 2011. This work is distributed
under the Creative Commons Attribution 3.0 License.
Development of an ensemble-adjoint optimization approach to derive uncertainties in net carbon fluxes
1Department of Earth Sciences, University of Bristol, Wills Memorial Building, Queen's Road, Bristol, BS8 1RJ, UK
2Department of Meteorology and Climatology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Abstract. Accurate modelling of the carbon cycle strongly depends on the parametrization of its underlying processes. The Carbon Cycle Data Assimilation System (CCDAS) can be used as an estimator algorithm to derive posterior parameter values and uncertainties for the Biosphere Energy Transfer and Hydrology scheme (BETHY). However, the simultaneous optimization of all process parameters can be quite challenging, due to the complexity and non-linearity of the BETHY model. Therefore, we propose a new overall concept, which uses ensemble runs and the adjoint optimization approach of CCDAS to derive the full probability density function (PDF) for posterior soil carbon parameters and the net carbon flux at the global scale. In this way, we only optimize those parameters, which can be constrained best by atmospheric carbon dioxide CO2) data. The prior uncertainties of the remaining parameters are included in a consistent way through ensemble runs, but are not constrained by data. The final PDF for the optimized parameters and the net carbon flux are then derived by superimposing the individual PDFs for each ensemble member. We find that the optimization with CCDAS converges much faster, due to the smaller number of processes involved. Moreover, it is more likely that we find the global minimum in the reduced parameter space.
Discussion Paper (PDF, 1063 KB) Supplement (419 KB) Interactive Discussion (Closed, 4 Comments) Final Revised Paper (GMD)
Notice on Discussion StatusCitation: Ziehn, T., Scholze, M., and Knorr, W.: Development of an ensemble-adjoint optimization approach to derive uncertainties in net carbon fluxes, Geosci. Model Dev. Discuss., 4, 1513-1531, doi:10.5194/gmdd-4-1513-2011, 2011. Bibtex EndNote Reference Manager XML
