LatMix: Studies of Submesoscale Stirring and Mixing

Description:

Stirring and lateral mixing by submesoscale processes are believed to play an important role in setting the distribution of energy, vorticity, momentum, and tracers in the ocean, and their transfer from one scale to another. But an inadequate understanding of the underlying processes has limited our ability to reliably include their effects in general circulation models. The ONR Departmental Research Initiative, Scalable Lateral Mixing and Coherent Turbulence (LatMix), aimed to address this gap through intensive observations and modeling of these processes. The initiative included two field efforts in the vicinity of the Gulf Stream. In the first field campaign (June, 2011) three ships and an airborne LIDAR system examined processes in the seasonal pycnocline of the mesoscale eddy field just to the southeast of the Gulf Stream during relatively quiescent early summer conditions. The second campaign (February-March, 2012) was conducted from two ships in the core of the Gulf Stream in very dynamic late-winter conditions. Detailed field observations, along with high-resolution numerical modeling and remote sensing data, revealed a host of intricate mesoscale and submesoscale structures. Data analysis, theoretical work, and numerical simulations continue to elucidate a range of processes at scales of 0.1 to 10 km that lead to lateral mixing and energy transfer. This AMS special collection brings together papers presenting many of the results from this project. The overview article for this collection can be found here.

Collection organizers:
James R. Ledwell, Applied Ocean Physics and Engineering, Woods Hole Oceanographic Institution
Gualtiero Badin, Institute of Oceanography, University of Hamburg
Amala Mahadevan, Department of Physical Oceanography, Woods Hole Oceanographic Institution
Andrey Shcherbina, Applied Physics Laboratory, University of Washington, Seattle
Miles A. Sundermeyer, School for Marine Science and Technology, University of Massachusetts, Dartmouth

LatMix: Studies of Submesoscale Stirring and Mixing

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Jeffrey J. Early
and
Adam M. Sykulski

Abstract

A comprehensive method is provided for smoothing noisy, irregularly sampled data with non-Gaussian noise using smoothing splines. We demonstrate how the spline order and tension parameter can be chosen a priori from physical reasoning. We also show how to allow for non-Gaussian noise and outliers that are typical in global positioning system (GPS) signals. We demonstrate the effectiveness of our methods on GPS trajectory data obtained from oceanographic floating instruments known as drifters.

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Angelique C. Haza
,
Tamay M. Özgökmen
,
Annalisa Griffa
,
Andrew C. Poje
, and
M.-Pascale Lelong

Abstract

To develop methodologies to maximize the information content of Lagrangian data subject to position errors, synthetic trajectories produced by both a large-eddy simulation (LES) of an idealized submesoscale flow field and a high-resolution Hybrid Coordinate Ocean Model simulation of the North Atlantic circulation are analyzed. Scale-dependent Lagrangian measures of two-particle dispersion, mainly the finite-scale Lyapunov exponent [FSLE; λ(δ)], are used as metrics to determine the effects of position uncertainty on the observed dispersion regimes. It is found that the cumulative effect of position uncertainty on λ(δ) may extend to scales 20–60 times larger than the position uncertainty. The range of separation scales affected by a given level of position uncertainty depends upon the slope of the true FSLE distribution at the scale of the uncertainty. Low-pass filtering or temporal subsampling of the trajectories reduces the effective noise amplitudes at the smallest spatial scales at the expense of limiting the maximum computable value of λ. An adaptive time-filtering approach is proposed as a means of extracting the true FSLE signal from data with uncertain position measurements. Application of this filtering process to the drifters with the Argos positioning system released during the LatMix: Studies of Submesoscale Stirring and Mixing (2011) indicates that the measurement noise dominates the dispersion regime in λ for separation scales δ < 3 km. An expression is provided to estimate position errors that can be afforded depending on the expected maximum λ in the submesoscale regime.

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