29 November 2017

A Novel Way to Compute Ocean Mixing with Particles

Computing eddy-driven effective diffusivity using Lagrangian particles

Science

A novel Lagrangian Effectivve Diffusivity (LED) diagnostic is developed, demonstrating equivalence between different mixing metrics. Results also imply particles can be used to perform offline tracer studies, e.g., for regional tracer studies.

Impact

LED shows time-history of mixing evolution, paving wave for improved subgrid parameterization.  The study verifies and validates consistency of metrics to understand eddy mixing diagnostics for eddy-induced mixing.

Summary

Transport of heat and carbon into the ocean from the atmosphere and melting of ice sheets by ocean flows is largely mediated by ocean mixing, quantified with a diffusivity. Several methods to compute diffusivity exist; however, they differ in their ability to quantify different aspects of mixing.  Fundamentally, approaches differ based on frame of reference.  If we consider a single, unmoving point in the flow we are in the Eulerian frame of reference.  In complement, a frame of reference that moves with the flow is termed Lagrangian.  We compare two Lagrangian-based approaches derived via the unique unique Lagrangian In-situ Global High-performance particle Tracking (LIGHT) capability in Model for Prediction Across Scales Ocean (MPAS-O) with a more traditional Eulerian approach that uses standard model output.  For example, LIGHT and Eulerian data are used to compute an effective diffusivity that directly measures irreversible mixing by eddies in contrast to the simpler particle-based diffusivity metric that is not designed with this capability in mind.  All methods are found to give comparable results, validating the unity of existing metrics to measure mixing. A side-benefit of the novel computational techniques presented in this work is that Lagrangian model data can be transformed for direct comparison to the Eulerian, which opens up many doors for future scientific exploration.

Contact
Phillip J. Wolfram
Los Alamos National Laboratory
Funding
Publications