Multiobjective Calibration of a Global Biogeochemical Ocean Model Against Nutrients, Oxygen, and Oxygen Minimum Zones.

Sauerland, Volkmar , Kriest, Iris , Oschlies, Andreas and Srivastav, Anand (2019) Multiobjective Calibration of a Global Biogeochemical Ocean Model Against Nutrients, Oxygen, and Oxygen Minimum Zones. Open Access Journal of Advances in Modeling Earth Systems, 11 (5). pp. 1285-1308. DOI 10.1029/2018MS001510.

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Global biogeochemical ocean models rely on many parameters, which govern the interaction between individual components, and their response to the physical environment. They are often assessed/calibrated against quasi-synoptic data sets of dissolved inorganic tracers. However, a good fit to one observation might not necessarily imply a good match to another. We investigate whether two different metrics—the root-mean-square error to nutrients and oxygen and a metric measuring the overlap between simulated and observed oxygen minimum zones (OMZs)—help to constrain a global biogeochemical model in different aspects of performance. Three global model optimizations are carried out. Two single-objective optimizations target the root-mean-square metric and a sum of both metrics, respectively. We then present and explore multiobjective optimization, which results in a set of compromise solutions. Our results suggest that optimal parameters for denitrification and nitrogen fixation differ when applying different metrics. Optimization against observed OMZs leads to parameters that enhance fixed nitrogen cycling; this causes too low nitrate concentrations and a too high global pelagic denitrification rate. Optimization against nutrient and oxygen concentrations leads to different parameters and a lower global fixed nitrogen turnover; this results in a worse fit to OMZs. Multiobjective optimization resolves this antagonistic effect and provides an ensemble of parameter sets, which help to address different research questions. We finally discuss how systematic model calibration can help to improve models used for projecting climate change and its effect on fisheries and climate gas emissions.

Document Type: Article
Keywords: global BGC model; model assessment; model calibration; multiobjective optimization; oxygen minimum zones
Research affiliation: OceanRep > GEOMAR > FB2 Marine Biogeochemistry > FB2-BM Biogeochemical Modeling
Kiel University > Kiel Marine Science
OceanRep > The Future Ocean - Cluster of Excellence
OceanRep > SFB 754
Kiel University
Refereed: Yes
Open Access Journal?: Yes
Publisher: AGU (American Geophysical Union), Wiley
Related URLs:
Projects: Future Ocean, SFB754, PalMod
Date Deposited: 05 Aug 2019 09:31
Last Modified: 31 Jan 2022 09:20

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