Affiliation:
1. GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany
2. Shirshov Institute of Oceanology, Moscow, Russia
3. GEOMAR Helmholtz Centre for Ocean Research Kiel, and Christian-Albrechts University of Kiel, Kiel, Germany
Abstract
AbstractThe Lagrangian analysis of sets of particles advected with the flow fields of ocean models is used to study connectivity, that is, exchange pathways, time scales, and volume transports, between distinct oceanic regions. One important factor influencing the dispersion of fluid particles and, hence, connectivity is the Lagrangian eddy diffusivity, which quantifies the influence of turbulent processes on the rate of particle dispersal. Because of spatial and temporal discretization, turbulence is not fully resolved in modeled velocities, and the concept of eddy diffusivity is used to parameterize the impact of unresolved processes. However, the relations between observation- and model-based Lagrangian eddy diffusivity estimates, as well as eddy parameterizations, are not clear. This study presents an analysis of the spatially variable near-surface lateral eddy diffusivity estimates obtained from Lagrangian trajectories simulated with 5-day mean velocities from an eddy-resolving ocean model (INALT01) for the Agulhas system. INALT01 features diffusive regimes for dynamically different regions, some of which exhibit strong suppression of eddy mixing by mean flow, and it is consistent with the pattern and magnitude of drifter-based eddy diffusivity estimates. Using monthly mean velocities decreases the estimated diffusivities less than eddy kinetic energy, supporting the idea that large and persistent eddy features dominate eddy diffusivities. For a noneddying ocean model (ORCA05), Lagrangian eddy diffusivities are greatly reduced, particularly when the Gent and McWilliams parameterization of mesoscale eddies is employed.
Funder
Deutsche Forschungsgemeinschaft
Bundesministerium für Bildung und Forschung
Helmholtz-Gemeinschaft
GEOMAR Helmholtz-Zentrum für Ozeanforschung Kiel
Russian Science Foundation
Russian Foundation for Basic Research
Publisher
American Meteorological Society
Cited by
18 articles.
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