The top Lyapunov exponent for a stochastic flow modeling the upper ocean turbulence

A stochastic model is proposed for multiparticle Lagrangian motion in the upper ocean. The model is based on hydrodynamics equations with random forcing, includes a few well interpreted and well estimated parameters, and implies a common description of the one-particle motion via a Langevin equation for the particle velocity. The dependence of the top Lyapunov exponent on the model parameters is studied as a part of a Lagrangian predictability problem. In particular, it is found that the Coriolis effect can radically improve the prediction of a Lagrangian particle position based on observations of other particles.