Preprints
https://doi.org/10.5194/egusphere-2022-202
https://doi.org/10.5194/egusphere-2022-202
 
26 Apr 2022
26 Apr 2022

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

Georges Baaklini1,2, Roy El Hourany3, Milad Fakhri2, Julien Brajard4, Leila Issa5, Gina Fifani1,2, and Laurent Moriter1 Georges Baaklini et al.
  • 1Sorbonne University, UPMC Univ Paris 06 CNRS-IRD-MNHN, LOCEAN Laboratory, 4 place Jussieu,75005 Paris, France
  • 2National Centre for Marine Sciences-CNRSL, P.O. Box 189, Jounieh, Lebanon
  • 3Univ. Littoral Côte d’Opale, Cnrs, Univ. Lille, UMR 8187, Laboratoire d’Océanologie et de Géoscience (LOG), Wimereux, France
  • 4Nansen Environmental and Remote Sensing Center, Bergen, Norway
  • 5Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon

Abstract. The Eastern Mediterranean surface circulation is highly energetic, composed of structures interacting stochastically. However, some main features are still debated, and the behavior of some fine-scale dynamics and their role in shaping the general circulation is yet unknown. In the following paper, we use an unsupervised neural network clustering method to analyze the long-term variability of the different mesoscale structures. We decompose 26 years of altimetric data into clusters reflecting different circulation patterns of weak and strong flows with either strain or vortex-dominated velocities. The vortex-dominated cluster is more persistent in the western part of the basin, which is more active than the eastern part due to the strong flow along the coast, interacting with the extended bathymetry and engendering continuous instabilities. The cluster that reflects a weak flow dominated the middle of the basin, including the Mid-Mediterranean Jet (MMJ) pathway. However, the temporal analysis shows a frequent and intermittent occurrence of a strong flow in the middle of the basin, which could explain the previous contradictory assessment of MMJ existence using in-situ observations. Moreover, we prove that the Levantine Sea is becoming more and more energetic as the activity of the main mesoscale features is showing a positive trend.

Journal article(s) based on this preprint

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
Ocean Sci., 18, 1491–1505, https://doi.org/10.5194/os-18-1491-2022,https://doi.org/10.5194/os-18-1491-2022, 2022
Short summary

Georges Baaklini et al.

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-202', Anonymous Referee #1, 31 May 2022
  • RC2: 'Comment on egusphere-2022-202', Anonymous Referee #2, 01 Jun 2022

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-202', Anonymous Referee #1, 31 May 2022
  • RC2: 'Comment on egusphere-2022-202', Anonymous Referee #2, 01 Jun 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Georges Baaklini on behalf of the Authors (16 Jul 2022)  Author's response    Author's tracked changes
ED: Referee Nomination & Report Request started (12 Aug 2022) by Aida Alvera-Azcárate
RR by Anonymous Referee #2 (24 Aug 2022)
RR by Anonymous Referee #1 (07 Sep 2022)
ED: Publish subject to minor revisions (review by editor) (13 Sep 2022) by Aida Alvera-Azcárate
AR by Georges Baaklini on behalf of the Authors (19 Sep 2022)  Author's response    Author's tracked changes    Manuscript
ED: Publish subject to technical corrections (28 Sep 2022) by Aida Alvera-Azcárate
AR by Georges Baaklini on behalf of the Authors (29 Sep 2022)  Author's response    Manuscript

Journal article(s) based on this preprint

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
Ocean Sci., 18, 1491–1505, https://doi.org/10.5194/os-18-1491-2022,https://doi.org/10.5194/os-18-1491-2022, 2022
Short summary

Georges Baaklini et al.

Georges Baaklini et al.

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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.

Short summary
We use machine learning to analyze the long-term variation of the surface currents in the Eastern Mediterranean, precisely in the Levantine Sea. We decompose the circulation into groups based on their physical characteristics, then analyze their spatial and temporal variability. We show that most structures of the Levantine Sea are becoming more energetic with time, even though those of the western part remain the most dominant due to the complex bathymetry and the strong currents.