Lagrangian Velocity Distributions in a High-Resolution Numerical Simulation of the North Atlantic

Abstract

The statistical properties of Lagrangian velocities in a high-resolution numerical simulation of the North Atlantic Ocean are analyzed and discussed in the framework of particle dispersion parameterizations. Consistent with previous analyses of float trajectories, the modeled velocity distribution is shown to be non-Gaussian, both at the surface and at 1500 m. These results can have significant implications on oceanographic research, as they suggest that current parameterizations of particle dispersion by linear stochastic processes or eddy-diffusivity approaches may be incorrect, since they assume Gaussian velocity distributions. The results also indicate the need for empirical parameterizations of particle dispersion based on nonlinear stochastic processes. It is shown that, even for a truly non-Gaussian dataset, a Gaussian probability distribution function can be spuriously recovered when the sampling density is too low. The best compromise between data sampling and space averaging when a limited amount of data are available, as is the case in most field observations, is then identified.