Ocean Science
Ocean Science
OS
Articles | Volume 18, issue 5
Articles | Volume 18, issue 5
https://doi.org/10.5194/os-18-1491-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/os-18-1491-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 5
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

Data sets

The General Bathymetric Chart of the Oceans International Hydrographic Organization (IHO) and the Intergovernmental Oceanographic Commission (IOC) https://download.gebco.net/

Ssalto/Duacs multimission altimeter products CNES/CLS/European Copernicus Marine Service http://www.aviso.altimetry.fr/duacs/

SOM-HAC_Levantine_Sea Georges Baaklini https://github.com/gbaaklini/SOM-HAC_Levantine_Sea

db_med24_nc_1986_2016_kri05 Milena Menna, Riccardo Gerin, Antonio Bussani, and Pierre-Marie Poulain https://doi.org/10.6092/7a8499bc-c5ee-472c-b8b5-03523d1e73e9

Model code and software

SOM-Toolbox Esa Alhoniemi, Johan Himberg, Jukka Parviainen, and Juha Vesanto https://github.com/ilarinieminen/SOMToolbox

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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.
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