Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Geosci. Model Dev., 10, 127-154, 2017
http://www.geosci-model-dev.net/10/127/2017/
doi:10.5194/gmd-10-127-2017
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Methods for assessment of models
09 Jan 2017
Calibrating a global three-dimensional biogeochemical ocean model (MOPS-1.0)
Iris Kriest1, Volkmar Sauerland2, Samar Khatiwala3, Anand Srivastav2, and Andreas Oschlies1 1GEOMAR Helmholtz-Zentrum für Ozeanforschung Kiel, Düsternbrooker Weg 20, 24105 Kiel, Germany
2Institut für Informatik, Christian-Albrechts-Universität zu Kiel, Christian-Albrechts-Platz 4, 24098 Kiel, Germany
3Department of Earth Sciences, University of Oxford, South Parks Road, Oxford OX1 3AN, UK
Abstract. Global biogeochemical ocean models contain a variety of different biogeochemical components and often much simplified representations of complex dynamical interactions, which are described by many ( ≈ 10 to  ≈ 100) parameters. The values of many of these parameters are empirically difficult to constrain, due to the fact that in the models they represent processes for a range of different groups of organisms at the same time, while even for single species parameter values are often difficult to determine in situ. Therefore, these models are subject to a high level of parametric uncertainty. This may be of consequence for their skill with respect to accurately describing the relevant features of the present ocean, as well as their sensitivity to possible environmental changes.

We here present a framework for the calibration of global biogeochemical ocean models on short and long timescales. The framework combines an offline approach for transport of biogeochemical tracers with an estimation of distribution algorithm (Covariance Matrix Adaption Evolution Strategy, CMA-ES). We explore the performance and capability of this framework by five different optimizations of six biogeochemical parameters of a global biogeochemical model, simulated over 3000 years. First, a twin experiment explores the feasibility of this approach. Four optimizations against a climatology of observations of annual mean dissolved nutrients and oxygen determine the extent to which different setups of the optimization influence model fit and parameter estimates. Because the misfit function applied focuses on the large-scale distribution of inorganic biogeochemical tracers, parameters that act on large spatial and temporal scales are determined earliest, and with the least spread. Parameters more closely tied to surface biology, which act on shorter timescales, are more difficult to determine. In particular, the search for optimum zooplankton parameters can benefit from a sound knowledge of maximum and minimum parameter values, leading to a more efficient optimization. It is encouraging that, although the misfit function does not contain any direct information about biogeochemical turnover, the optimized models nevertheless provide a better fit to observed global biogeochemical fluxes.


Citation: Kriest, I., Sauerland, V., Khatiwala, S., Srivastav, A., and Oschlies, A.: Calibrating a global three-dimensional biogeochemical ocean model (MOPS-1.0), Geosci. Model Dev., 10, 127-154, doi:10.5194/gmd-10-127-2017, 2017.
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Global biogeochemical ocean models are subject to a high level of parametric uncertainty. This may be of consequence for their skill with respect to accurately describing features of the present ocean and their sensitivity to possible environmental changes. We present the first results from a framework that combines an offline biogeochemical tracer transport model with an estimation of distribution algorithm, calibrating six biogeochemical model parameters against observed oxygen and nutrients.
Global biogeochemical ocean models are subject to a high level of parametric uncertainty. This...
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