oaioai:eprints.soton.ac.uk:360171

Observed and Modeled Global Ocean Turbulence Regimes as Deduced from Surface Trajectory Data

Abstract

A large-scale tool for systematic analyses of the dispersal and turbulent properties of ocean currents and the subsequent separation of dynamical regimes according to the prevailing trajectories taxonomy in a certain area was proposed by Rupolo. In the present study, this methodology has been extended to the analysis of model trajectories obtained by analytical computations of the particle advection equation using the Lagrangian open-source software package Tracing the Water Masses of the North Atlantic and the Mediterranean (TRACMASS), and intercomparisons have been made between the surface velocity fields from three different configurations of the global Nucleus for European Modelling of the Ocean (NEMO) ocean/sea ice general circulation model. Lagrangian time scales of the observed and synthetic trajectory datasets have been calculated by means of inverse Lagrangian stochastic modeling, and the influence of the model field spatial and temporal resolution on the analyses has been investigated. In global-scale ocean modeling, compromises are frequently made in terms of grid resolution and time averaging of the output fields because high-resolution data require considerable amounts of storage space. Here, the implications of such approximations on the modeled velocity fields and, consequently, on the particle dispersion, have been assessed through validation against observed drifter tracks. This study aims, moreover, to shed some light on the relatively unknown turbulent properties of near-surface ocean dynamics and their representation in numerical models globally and in a number of key regions. These results could be of interest for other studies within the field of turbulent eddy diffusion parameterization in ocean models or ocean circulation studies involving long-term coarse-grid model experiments

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oaioai:eprints.soton.ac.uk:360171Last time updated on 2/20/2015

This paper was published in e-Prints Soton.

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