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Geophysical models make predictions relying on parameter values to be estimated from data. However, existing methods are costly because they require either many runs of the complex geophysical model or to implement an adjoint model. Here, we propose an alternative approach based on optimal control theory which is the simultaneous perturbations stochastic approximation (SPSA). This gradient‐descent method is generic and easy to implement, and its computational cost does not increase with the number of parameters to optimize. This study aims at highlighting the potential of SPSA for parameter identification in geophysical models. Through the example of vertical turbulent mixing in the upper ocean, we show with twin experiments that the method could successfully identify parameter values that minimize model‐data discrepancy. The efficient and easy‐to‐get results provided by SPSA in this study should pave the way for a broader use of parameter identification in the complex and embedded models commonly used in geophysical sciences. Plain Language Summary: Predictions on the past and future state of geophysical systems are made through mathematical models, which rely on numerous constant values (parameters) to be calibrated from prior knowledge and available data. Fine‐tuning those parameter values is one of the major means of improving the accuracy of model predictions. To achieve that goal for complex geophysical models in which multiple scales and processes are nested, existing methods are limited by either (a) an important computational cost or (b) an important cost in terms of development and implementation of an adjoint model. Here, we highlight a method from optimal control theory, called simultaneous perturbations stochastic approximation (SPSA). This generic method is easy to implement, and its computational cost is comparatively low. To show the potential of SPSA for parameter identification in geophysical science, we apply it to the example of wind‐induced turbulent mixing near the ocean surface. Using the approach of twin experiments, we show that the method can successfully tune the parameter values to minimize the discrepancy between model predictions and empirical data. The efficient and easy‐to‐get results provided by SPSA in this study pave the way for a broader use of parameter identification in the complex models commonly used in geophysical sciences. Key Points: Parameters identification is a key to reduce model uncertainty in geophysical modelsWe present a method from optimal control called simultaneous perturbations stochastic approximation (SPSA) that is easy to implement and fast to runWe illustrate the potential of SPSA with a simplified example of turbulent mixing in the ocean [ABSTRACT FROM AUTHOR]

Abstract: Marine circulation above the northern Brazilian continental shelf is subject to energetic forcing factors of various origins: high water buoyancy fluxes induced by the Amazon River freshwater discharge, a strong coastal current associated with a mesoscale current (North Brazil Current (NBC)), a forcing by semidiurnal tide and by Northeast or Southeast trade winds according to the season. Using a three-dimensional (3-D) hydrodynamic numerical model (MOBEEHDYCS), and realistic bathymetry and coastline of the northern Brazilian shelf, this paper aims at studying the influence of some specific physical processes on the morphology of the Amazon plume. The very large volume discharge (180000m3/s on average) and the weak effect of Coriolis force are additional characteristics of the studied system, which induce a particular dynamics. The various forcing factors are successively introduced into the model in order to simulate and to determine their respective influences upon the plume extent and the hydrodynamics at the shelf scale. Simulation reveal that the coastal current is at the origin of the permanent northwestward Amazon plume extension while wind effect can either reinforce or moderate this situation. The tide intervenes also to modify the position of the salinity front: a horizontal migration of salinity front is observed under its action. [Copyright &y& Elsevier]

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]

A high-resolution 2D barotropic tidal model was developed for the Gulf of Gabes and used to characterise hydrodynamic processes and tidal dynamics. The model is based on the Regional Ocean Modelling System. It is forced at the open boundaries by the semidiurnal M2 and S2 astronomical components while meteorological forcing has been neglected. The model results show good agreement with observations confirming that it reproduces the gulf's main tidal characteristics reasonably well. In fact, the simulated semidiurnal tidal components M2 and S2 generate important sea level variations and coastal currents. Tidal propagation is directed to the gulf's western sector while tidal resonance occurs in its inner sector where the M2 and S2 amplitudes are about 50 and 36 cm, respectively. Phase maxima (170°–185°) are located inside Boughrara Lagoon for both the simulated M2 and S2 tides. The strongest currents are found in shallow coastal regions and at the lagoon's western inlet. During spring tides, currents are around 10–20 cm s −1 in the gulf center and up to 50 cm s −1 inside the lagoon. [ABSTRACT FROM AUTHOR]