T-S Data Assimilation to Optimise Turbulent Viscosity: An Application to the Berre Lagoon Hydrodynamics.

The Berre lagoon (France) is a semi-enclosed basin with 6 m of mean depth and 155 km² of surface area. Due to the Durance river discharge in the north and the Mediterranean sea intrusion in the south, the hydrological situation is often strongly stratified. The vertical mixing occurs only when high wind is blowing (> 10ms[sup -1]). Modelling the basin circulation during such a process with a 3-D primitive equation model requires an accurate parameterisation of the turbulent vertical viscosity and diffusivities. A classical approach consists in using a turbulence model like the k-L or k-∈ ones. Here, an alternative approach is to consider the vertical turbulent viscosity ν[sub t] as a space and time dependent function to be fitted, under the assumption of constant Prandtl and Schmidt coefficients for the turbulent diffusivities. ν[sub t] is optimised, iteratively, for each vertical level and with a period of half an hour, in order to minimise the discrepancies between the simulation results and the salinity and temperature data profiles measured by a measurement station at the same time rate. This iterative procedure requires to solve an adjoint model to assimilate the data. This optimal control method is applied on a 3-days wind event and gives simulation results closer to the data than could be expected when using a classical k+L model without data assimilation. [ABSTRACT FROM AUTHOR]