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- A review of the LATEX project: mesoscale to submesoscale processes in a coastal environment doi link

Auteur(s): Petrenko A., Doglioli A., Nencioli F., Kersale M., Hu Z., D'Ovidio Francesco

(Article) Publié: Ocean Dynamics, vol. 24 p.513-533 (2017)


Ref HAL: hal-01505797_v1
DOI: 10.1007/s10236-017-1040-9
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Résumé:

The main objective of the LAgrangian Transport EXperiment (LATEX) project was to study the influence of coastal mesoscale and submesoscale physical processes on circulation dynamics, cross-shelf exchanges and biogeochemistry in the western continental shelf of the Gulf of Lion, Northwestern Mediterranean Sea. LATEX was a five-year multidisciplinary project based on the combined analysis of numerical model simulations and multi-platform field experiments. The model component included a ten-year realistic 3D numerical simulation, with a 1 km horizontal resolution over the gulf, nested in a coarser 3 km resolution model. The in situ component involved four cruises, including a large-scale multidisciplinary campaign with two research vessels in 2010. This review concentrates on the physics results of LATEX, addressing three main subjects: 1) the investigation of the mesoscale to submesoscale processes. The eddies are elliptic, baroclinic and anticyclonic; the strong thermal and saline front is density-compensated. Their generation processes are studied; 2) the development of sampling strategies for their direct observations. LATEX has implemented an adaptive strategy Lagrangian tool, with a reference software available on the web, to perform offshore campaigns in a Lagrangian framework; 3) the quantification of horizontal mixing and cross-shelf exchanges. Lateral diffusivity coefficients, calculated in various ways including a novel technique, are in the range classically encountered for their associated scales. Cross-shelf fluxes have been calculated, after retrieving the near-inertial oscillation contribution. Further perspectives are discussed, especially for the ongoing challenge of studying submesoscale features remotely and from in situ data.