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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2019-324
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-324
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: model evaluation paper 10 Feb 2020

Submitted as: model evaluation paper | 10 Feb 2020

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This preprint is currently under review for the journal GMD.

Optimality-Based Non-Redfield Plankton-Ecosystem Model (OPEMv1.0) in the UVic-ESCM 2.9. Part II: Sensitivity Analysis and Model Calibration

Chia-Te Chien, Markus Pahlow, Markus Schartau, and Andreas Oschlies Chia-Te Chien et al.
  • GEOMAR Helmholtz Centre for Ocean Research, Kiel, Germany

Abstract. We analyse 400 perturbed-parameter simulations for two configurations of an optimality-based plankton-ecosystem model (OPEM), implemented in the University of Victoria Earth-System Climate Model (UVic-ESCM), using a Latin-Hypercube sampling method for setting up the parameter ensemble. A likelihood-based metric is introduced for model assessment and selection of the model solutions closest to observed distributions of NO3, PO43−, O2, and surface chlorophyll a concentrations. According to our metric the optimal model solutions comprise low rates of global N2 fixation and denitrification. These two rate estimates turned out to be poorly constrained by the data. For identifying the “best” model solutions we therefore also consider the model’s ability to represent current estimates of water-column denitrification. We employ our ensemble of model solutions in a sensitivity analysis to gain insights into the importance and role of individual model parameters as well as correlations between various biogeochemical processes and tracers, such as POC export and the NO3 inventory. Global O2 varies by a factor of two and NO3 by more than a factor of six among all simulations. Remineralisation rate is the most important parameter for O2, which is also affected by the subsistence N quota of ordinary phytoplankton (QN0,phy) and zooplankton maximum specific ingestion rate. QN0,phy is revealed as a major determinant of the oceanic NO3 pool. This indicates that unraveling the driving forces of variations in phytoplankton physiology and elemental stoichiometry, which are tightly linked via QN0,phy, is a prerequisite for understanding the marine nitrogen inventory.

Chia-Te Chien et al.

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Status: open (until 06 Apr 2020)
Status: open (until 06 Apr 2020)
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Chia-Te Chien et al.

Model code and software

UVic-updates-opem: Optimality-based Plankton Ecosystem Model (OPEM v1.0) for the UVic-ESCM. M. Pahlow https://doi.org/10.3289/SW_1_2020

Chia-Te Chien et al.

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Latest update: 23 Feb 2020
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Short summary
We demonstrate sensitivities of tracers to parameters of a new optimality-based plankton-ecosystem model (OPEM) in the UVic-ESCM. We find that changes in phytoplankton subsistence nitrogen quota strongly impact the nitrogen inventory, nitrogen fixation, as well as elemental stoichiometry of ordinary phytoplankton and diazotrophs. We introduce a new likelihood-based metric for model calibration and it shows the capability of constraining globally averaged oxygen, nitrate and DIC concentrations.
We demonstrate sensitivities of tracers to parameters of a new optimality-based...
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