Articles | Volume 21, issue 2
https://doi.org/10.5194/os-21-587-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/os-21-587-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Detection and tracking of carbon biomes via integrated machine learning
GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany
Database Systems and Data Mining, Kiel University, Kiel, Germany
Lavinia Patara
GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany
Daniyal Kazempour
Database Systems and Data Mining, Kiel University, Kiel, Germany
Peer Kröger
Database Systems and Data Mining, Kiel University, Kiel, Germany
Related authors
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Nana Hocke, Lavinia Patara, John Dunne, Florian Schütte, Mariana Maia Pacheco, and Ivy Frenger
EGUsphere, https://doi.org/10.5194/egusphere-2026-4347, https://doi.org/10.5194/egusphere-2026-4347, 2026
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
We investigate how ocean eddies influence carbon dioxide and oxygen exchange between the ocean and atmosphere using a high-resolution coupled ocean–biogeochemical climate model. We find that mesoscale variability explains 6–7 % of flux variance globally, with regional contributions exceeding 30 %. Biological processes dominate globally integrated mesoscale flux anomalies, accounting for about two-thirds of the signal, while temperature-driven effects become more important under warming.
Chia-Te Chien, Jonathan V. Durgadoo, Dana Ehlert, Ivy Frenger, David P. Keller, Wolfgang Koeve, Iris Kriest, Angela Landolfi, Lavinia Patara, Sebastian Wahl, and Andreas Oschlies
Geosci. Model Dev., 15, 5987–6024, https://doi.org/10.5194/gmd-15-5987-2022, https://doi.org/10.5194/gmd-15-5987-2022, 2022
Short summary
Short summary
We present the implementation and evaluation of a marine biogeochemical model, Model of Oceanic Pelagic Stoichiometry (MOPS) in the Flexible Ocean and Climate Infrastructure (FOCI) climate model. FOCI-MOPS enables the simulation of marine biological processes, the marine carbon, nitrogen and oxygen cycles, and air–sea gas exchange of CO2 and O2. As shown by our evaluation, FOCI-MOPS shows an overall adequate performance that makes it an appropriate tool for Earth climate system simulations.
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Short summary
Climate change impacts the ocean carbon cycle, demanding methods to monitor ocean carbon uptake. We developed a machine learning tool applied to a global ocean biogeochemistry model to identify and track marine carbon biomes both seasonally and from 1958 to 2018. Distinct carbon biomes with varied ocean dynamics were detected. Changes in biome coverage revealed responses to seasonal and long-term shifts, offering insights into the impacts of climate change.
Climate change impacts the ocean carbon cycle, demanding methods to monitor ocean carbon uptake....