Abstract

Abstract. Within the framework of the EGITTO/EGYPT programs, the spatial structure and the temporal variability of the surface circulation in the eastern basin of the Mediterranean Sea was studied with satellite-tracked drifters. A total of 97 drifters drogued to 15-m nominal depth were released between September 2005 and March 2007, regularly along ship-of-opportunity routes in the Sicily Channel and within specific structures during dedicated campaigns in the Levantine sub-basin. This study complements previous ones in the former and in the Ionian, but it is the first one in the latter. After editing and low-pass filtering, the drifter trajectories were used to estimate pseudo-Eulerian statistics: mean current, variance ellipses, mean and eddy kinetic energies. A statistical analysis was also performed dividing the dataset in two extended seasons (winter and summer). A branching behaviour of the surface water after passing through the Sicily Channel is evidenced, together with a seasonal variability inducing a reversal of the circulation in the southern part of the Ionian. In the Levantine, the surface circulation describes an eastward flow along the Libyan and Egyptian slopes (the Libyo-Egyptian Current: LEC) that continues in a cyclonic circuit along the Middle East and Turkish slopes. This general alongslope circuit can be perturbed locally and temporally by the numerous anticyclonic eddies that co-exist in the Levantine, mainly created by the instability of the LEC in the south (Libyo-Egyptian Eddies: LEEs), but also by the wind (Ierapetra and Pelops), and by the topography (over the Eratosthenes Seamount and off Latakia). The most frequent perturbation is the entrainment of part of the flow seaward: the LEEs close to the slope can interact with the LEC, which then spreads more or less around them, so that a series of contiguous LEEs (paddle-wheel effect) can possibly result in an eastward offshore transport (the so-called Mid Mediterranean Jet). Additionally, when LEEs are close enough to the slope, most of the surface flow is spread seaward. Along the slope the current is then induced by the LEEs southern side which results in a westward current. Locally and temporally the circulation along the slope can thus be reversed.

Highlights

  • The surface circulation in the eastern basin of the Mediterranean Sea is principally that of the water of Atlantic origin (AW): we do not differentiate the various types of AW specified in the literature

  • We present the results of the investigation of the spatial and temporal variability of the surface circulation in the basin using satellite-tracked drifters

  • The drifters were deployed in this area (Fig. 1) mainly from ships of opportunities, and the strategy was constrained by the limited shiptime available (EGITTO-1 cruise on R/V OGS-Explora in November 2005 (Poulain et al, 2006); EGYPT-0 cruise on R/V L’Atalante in February 2006; EGYPT-2 cruise on R/V Le Suroıt in March 2007)

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Summary

Introduction

The surface circulation in the eastern basin of the Mediterranean Sea is principally that of the water of Atlantic origin (AW): we do not differentiate the various types of AW specified in the literature. Surface water flow, called the Libyo-Egyptian Current (LEC), is unstable and generates anticyclonic eddies (Libyo-Egyptian Eddies: LEEs) evolving in time and space These LEEs have diameters of 100–150 km, lifetimes of several months (up to more than one year), and propagate downstream (eastward) along the slope at 1–3 km/d. “Mersa Matruh” and “Shikmona” are no longer described as permanent or recurrent eddies, but as areas where (anticyclonic) eddies tend to accumulate and/or merge These authors explained that the so-called MMJ was the part of the flow carried offshore around the (successive) northern edges of both the eddies generated by the LEC and IE, and disconnected from the main alongslope path (POEM only sampled offshore and did not considered the historical data available to the south).

Drifter characteristics
Strategy of deployments
Data and processing
Mean wind pattern
Total dataset
Seasonal variability
Discussion and conclusions
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