Articles | Volume 21, issue 6
https://doi.org/10.5194/os-21-3541-2025
https://doi.org/10.5194/os-21-3541-2025
Research article
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18 Dec 2025
Research article | Highlight paper |  | 18 Dec 2025

Estimating the AMOC from Argo profiles with machine learning trained on ocean simulations

Yannick Wölker, Willi Rath, Matthias Renz, and Arne Biastoch

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Cited articles

Argo: Argo float data and metadata from Global Data Assembly Centre (Argo GDAC) – Snapshot of Argo GDAC of August 2025, SEANOE [data set], https://doi.org/10.17882/42182#110199, 2025. a, b
Baker, J. A., Bell, M. J., Jackson, L. C., Vallis, G. K., Watson, A. J., and Wood, R. A.: Continued Atlantic overturning circulation even under climate extremes, Nature, 638, 987–994, https://doi.org/10.1038/s41586-024-08544-0, 2025. a
Behrens, E., Biastoch, A., and Böning, C. W.: Spurious AMOC trends in global ocean sea-ice models related to subarctic freshwater forcing, Ocean Modelling, 69, 39–49, https://doi.org/10.1016/j.ocemod.2013.05.004, 2013. a
Biastoch, A., Böning, C. W., Getzlaff, J., Molines, J.-M., and Madec, G.: Causes of Interannual–Decadal Variability in the Meridional Overturning Circulation of the Midlatitude North Atlantic Ocean, Journal of Climate, 21, 6599–6615, https://doi.org/10.1175/2008JCLI2404.1, 2008. a
Biastoch, A., Schwarzkopf, F. U., Getzlaff, K., Rühs, S., Martin, T., Scheinert, M., Schulzki, T., Handmann, P., Hummels, R., and Böning, C. W.: Regional imprints of changes in the Atlantic Meridional Overturning Circulation in the eddy-rich ocean model VIKING20X, Ocean Sci., 17, 1177–1211, https://doi.org/10.5194/os-17-1177-2021, 2021. a, b, c, d, e, f, g, h, i
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Co-editor-in-chief
This is an important contribution to the science surrounding the Atlantic Meridional Overturning Circulation (known as AMOC), in particular with regard to observations and methods. This work may have strategic relevance for planning observations in the future. It also represents an interesting effort at incorporating artificial intelligence (AI) technology into obtaining optimal results from observational data analysis.
Short summary
The Atlantic Meridional Overturning Circulation (AMOC) is a large current system that helps regulating Earth's climate. Monitoring the AMOC relies on fixed instruments anchored to the seafloor. This study explores, in a high-resolution model, whether data from Argo floats, autonomous drifters collecting hydrographic profiles, can be used to monitor the AMOC cost-effectively with the help of Machine Learning. Results suggest that Argo floats can extend AMOC monitoring beyond current fixed arrays.
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