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

Chien, Chia-Te , Pahlow, Markus, Schartau, Markus and Oschlies, Andreas (2020) Optimality-Based Non-Redfield Plankton-Ecosystem Model (OPEMv1.0) in the UVic-ESCM 2.9. Part II: Sensitivity Analysis and Model Calibration. Open Access Geoscientific Model Development Discussions . DOI 10.5194/gmd-2019-324.

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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.

Document Type: Article
Research affiliation: OceanRep > GEOMAR > FB2 Marine Biogeochemistry > FB2-BM Biogeochemical Modeling
OceanRep > SFB 754
Refereed: No
Open Access Journal?: Yes
DOI etc.: 10.5194/gmd-2019-324
ISSN: 1991-962X
Projects: PalMod, SFB754, Dynatrait
Date Deposited: 10 Feb 2020 12:37
Last Modified: 10 Feb 2020 12:37
URI: http://oceanrep.geomar.de/id/eprint/48962

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