Articles | Volume 18, issue 5
https://doi.org/10.5194/os-18-1491-2022
https://doi.org/10.5194/os-18-1491-2022
Research article
 | 
20 Oct 2022
Research article |  | 20 Oct 2022

Surface circulation properties in the eastern Mediterranean emphasized using machine learning methods

Georges Baaklini, Roy El Hourany, Milad Fakhri, Julien Brajard, Leila Issa, Gina Fifani, and Laurent Mortier

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Cited articles

Alhammoud, B., Béranger, K., Mortier, L., Crépon, M., and Dekeyser, I.: Surface circulation of the Levantine Basin: comparison of model results with observations, Prog. Ocean., 66, 299–320, 2005. a, b, c
Alhoniemi, E., Himberg, J., Parviainen, J., and Vesanto, J.: SOM-Toolbox, Github [code], https://github.com/ilarinieminen/SOM-Toolbox (last access: 25 November 2021), 2012. a
Amitai, Y., Lehahn, Y., Lazar, A., and Heifetz, E.: Surface circulation of the eastern Mediterranean Levantine basin: Insights from analyzing 14 years of satellite altimetry data, J. Geophys. Res.-Oceans, 115, C10, https://doi.org/10.1029/2010JC006147, 2010. a, b, c
Amores, A., Jordà, G., and Monserrat, S.: Ocean eddies in the Mediterranean Sea from satellite altimetry: Sensitivity to satellite track location, Front. Mar. Sci., 6, 703, https://doi.org/10.3389/fmars.2019.00703, 2019. a, b
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Short summary
We use machine learning to analyze the long-term variation of the surface currents in the Levantine Sea, located in the eastern Mediterranean Sea. We decompose the circulation into groups based on their physical characteristics and analyze their spatial and temporal variability. We show that most structures of the Levantine Sea are becoming more energetic over time, despite those of the western area remaining the most dominant due to their complex bathymetry and strong currents.