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.

Georges Baaklini et al.

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

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

Georges Baaklini et al.

Georges Baaklini et al.

Viewed

Total article views: 328 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
268 52 8 328 6 5
  • HTML: 268
  • PDF: 52
  • XML: 8
  • Total: 328
  • BibTeX: 6
  • EndNote: 5
Views and downloads (calculated since 26 Apr 2022)
Cumulative views and downloads (calculated since 26 Apr 2022)

Viewed (geographical distribution)

Total article views: 291 (including HTML, PDF, and XML) Thereof 291 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 29 Sep 2022
Download
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.