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Eddy Diffusivity Estimates from Lagrangian Trajectories Simulated with Ocean Models and Surface Drifter Data-A Case Study for the Greater Agulhas System

  • Siren Rühs
  • , Victor Zhurbas
  • , Inga Monika Koszalka
  • , Jonathan V. Durgadoo
  • , Arne Biastoch
  • extern

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

The Lagrangian analysis of sets of particles advectedwith 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.
Original languageEnglish
Pages (from-to)175-196
Number of pages22
JournalJournal of Physical Oceanography
Volume48
Issue number1
DOIs
Publication statusPublished - Jan 2018

Funding

OGCM experiments and trajectory simulations were performed at High Performance Computing Centers in Stuttgart (HLRS), Hannover (HLRN) and at the Christian-Albrechts-Universitat zu Kiel. OGCM code and data are available upon request from the corresponding author. For reproducibility of the main result figures in this study, respective data and scripts are available at http://data.geomar.de. The project received funding by the Cluster of Excellence 80 "The Future Ocean'' within the framework of the Excellence Initiative by the Deutsche Forschungsgemeinschaft (DFG) on behalf of the German federal and state governments (Siren Ruhs, Grant CP1412), by the German Federal Ministry of Education and Research (BMBF) (Arne Biastoch, Grant 03F0750A of the SPACES-AGULHAS project), and by the Helmholtz Association and the GEOMAR Helmholtz Centre for Ocean Research Kiel (Jonathan V. Durgadoo, Grants IV014 and GH018). Victor Zhurbas was supported by the Russian Science Foundation (Grant 14-50-00095) and the Russian Foundation for Basic Research (Grant 18-05-00278). The authors further wish to acknowledge the DRAKKAR group for support in model development and two anonymous reviewers for their insightful comments that helped to improve this manuscript.

FundersFunder number
Cluster of Excellence 80 "The Future Ocean''CP1412
German Federal Ministry of Education and Research (BMBF)03F0750A
???publication-publication-funding-organisation-not-added???IV014, GH018
Russian Science Foundation14-50-00095
Russian Foundation for Basic Research18-05-00278

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 13 - Climate Action
      SDG 13 Climate Action

    Keywords

    • North-atlantic
    • Thermohaline circulation
    • Southern-ocean
    • Kinetic-energy
    • Climate model
    • Indian-ocean
    • Part ii
    • Leakage
    • Statistics
    • Resolution

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