Biogeosciences
Biogeosciences
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Articles | Volume 23, issue 1
Articles | Volume 23, issue 1
https://doi.org/10.5194/bg-23-315-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-23-315-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 23, issue 1
Research article
 | 
12 Jan 2026
Research article |  | 12 Jan 2026

Hybrid machine learning data assimilation for marine biogeochemistry

Ieuan Higgs, Ross Bannister, Jozef Skákala, Alberto Carrassi, and Stefano Ciavatta

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Short summary
We explored how machine learning can improve computer models that simulate ocean ecosystems. These models help us understand how the ocean works, but they often struggle due to limited observations and complex processes. Our approach uses machine learning to better connect the parts of the system we can observe with those we cannot. This leads to more accurate and efficient predictions, offering a promising way to improve future ocean monitoring and forecasting tools.
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