Articles | Volume 19, issue 21
https://doi.org/10.5194/bg-19-5079-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-19-5079-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Nov 2022
Research article |
| 07 Nov 2022
| 07 Nov 2022
Influence of GEOTRACES data distribution and misfit function choice on objective parameter retrieval in a marine zinc cycle model
Claudia Eisenring
CORRESPONDING AUTHOR
Department of Earth Sciences, Institute of Geochemistry and Petrology, ETH Zurich, Clausiusstrasse
25, 8092 Zurich, Switzerland
Sophy E. Oliver
Department of Earth Sciences, University of Oxford, South Parks Road,
Oxford, OX1 3AN, UK
National Oceanography Centre, Southampton, SO14 3ZH, UK
Samar Khatiwala
Department of Earth Sciences, University of Oxford, South Parks Road,
Oxford, OX1 3AN, UK
Gregory F. de Souza
Department of Earth Sciences, Institute of Geochemistry and Petrology, ETH Zurich, Clausiusstrasse
25, 8092 Zurich, Switzerland
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EGUsphere, https://doi.org/10.5194/egusphere-2026-3378, https://doi.org/10.5194/egusphere-2026-3378, 2026
This preprint is open for discussion and under review for Climate of the Past (CP).
Short summary
Short summary
This paper uses a state-of-the-art climate model to investigate the role of elevated CO2 on rapid changes to ocean biogeochemistry in much hotter world. We find that circulation has to potential to dramatically change as a result of rapid warming, resulting in poor ocean ventilation but surprisingly limited oxygen loss in the deep ocean.
Sophy Oliver, Coralia Cartis, Iris Kriest, Simon F. B Tett, and Samar Khatiwala
Geosci. Model Dev., 15, 3537–3554, https://doi.org/10.5194/gmd-15-3537-2022, https://doi.org/10.5194/gmd-15-3537-2022, 2022
Short summary
Short summary
Global ocean biogeochemical models are used within Earth system models which are used to predict future climate change. However, these are very computationally expensive to run and therefore are rarely routinely improved or calibrated to real oceanic observations. Here we apply a new, fast optimisation algorithm to one such model and show that it can calibrate the model much faster than previously managed, therefore encouraging further ocean biogeochemical model improvements.
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Short summary
Given the sparsity of observational constraints on micronutrients such as zinc (Zn), we assess the sensitivities of a framework for objective parameter optimisation in an oceanic Zn cycling model. Our ensemble of optimisations towards synthetic data with varying kinds of uncertainty shows that deficiencies related to model complexity and the choice of the misfit function generally have a greater impact on the retrieval of model Zn uptake behaviour than does the limitation of data coverage.
Given the sparsity of observational constraints on micronutrients such as zinc (Zn), we assess...
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