Lagrangian transport in realistic simulations of ocean submesoscale turbulence
Ocean flows at scales larger than few tens of km are quasi-horizontal due to the pronounced stratification of
seawater and Earth’s rotation and are characterized by quasi-2D turbulence. Mesoscale (O(100) km) vortices
contain most of the kinetic energy and are key for ocean dynamics at climatic scales. Submesoscale flows
(scales below O(10) km), instead, display smaller and faster eddies, and filaments associated with strong
gradients (e.g. of temperature) and intense vertical transport, which play an important role in both physical
and biogeochemical budgets. Mesoscale and submesoscale flows also shape the physical and chemical
environment that conditions the development of marine life. Direct global observations of submesoscale
surface velocity fields at global scale are still not possible but should be achieved in the near future thanks to
the satellite SWOT (NASA-CNES, launch in late 2022).
To compute large-scale horizontal transport, surface energy exchanges or global estimates of other
quantities, it is crucial to assess how well the horizontal velocities provided by the satellite compare to actual
surface currents and down to what length scale. For this purpose, Lagrangian approaches provide an ideal
framework, as, unlike standard Eulerian approaches, they integrate in time the signal. As a consequence, they
may allow a clear separation between fast (ageostrophic) processes, that could contaminate the satellite-
derived velocity, and slower (geostrophic) ones.
In this internship, funded by CNES, we will explore Lagrangian transport in surface ocean turbulence by
means of state-of-the-art realistic numerical simulations. The analysis will rely on the comparison of different
statistical indicators of Lagrangian dispersion in the full flow and in some of its subcomponents such as the
geostrophic one, which should be measured by the satellite. One aim is to determine the effect of high-
frequency, ageostrophic motions on dispersion features. In particular, this study should allow the
identification of a threshold length scale above which the approximate velocity field is accurate enough, at
least in a statistical sense, as well as an estimate of the kinetic energy of the missing small scales.
We look for a candidate having good knowledge of fluid mechanics or dynamical systems and an interest for
numerical methods; education: Fluid Mechanics, Physics, Geophysical Fluid Dynamics, Applied Mathematics.
Knowing Python will be needed. Good knowledge of oral and written English is required.
Interested candidates should send their CV, a letter of motivation, transcripts of notes, and possibly contact
information of one reference.
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