Calibrating a global three-dimensional biogeochemical ocean model (MOPS-1.0).

Kriest, Iris , Sauerland, Volkmar, Khatiwala, Samar, Srivastav, Anand and Oschlies, Andreas (2017) Calibrating a global three-dimensional biogeochemical ocean model (MOPS-1.0). Open Access Geoscientific Model Development, 10 . pp. 127-154. DOI 10.5194/gmd-10-127-2017.

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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–≈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 time scales. The framework combines an offline approach for transport of biogeochemical tracers with an Estimation of Distribution Algorithm (Covariance Matrix Adaption Evolution Strategy, CMAES). We explore the performance and capability of this framework by five different optimizations of six biogeochemical parameters of a global biogeochemical model. 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's 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 time scales, 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.

Document Type: Article
Research affiliation: OceanRep > GEOMAR > FB2 Marine Biogeochemistry > FB2-BM Biogeochemical Modeling
OceanRep > The Future Ocean - Cluster of Excellence > FO-R05
Kiel University > Kiel Marine Science
OceanRep > The Future Ocean - Cluster of Excellence
OceanRep > SFB 754
OceanRep > SFB 754 > B1
OceanRep > The Future Ocean - Cluster of Excellence > FO-R11
OceanRep > SFB 754 > B8
Kiel University
Refereed: Yes
Open Access Journal?: Yes
DOI etc.: 10.5194/gmd-10-127-2017
ISSN: 1991-9603
Projects: SFB754, Future Ocean, PalMod in-kind
Date Deposited: 19 Jul 2016 07:45
Last Modified: 06 Feb 2020 09:10

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