Helga S. Huntley

Ocean processes underlying surface clustering

Ageostrophic ocean processes such as frontogenesis, submesoscale mixed-layer instabilities, shelf break fronts, and topographic interactions on the continental shelf produce surface-divergent flows that affect buoyant material over time. This study examines the ocean processes leading to clustering, i.e., the increase of material density over time, on the ocean surface. The time series of divergence along a material trajectory, the Lagrangian divergence (LD), is the flow property driving clustering. To understand the impacts of various ocean processes on LD, numerical ocean model simulations at different resolutions are analyzed. Although the relevant processes differ, patterns in clustering evolution from the deep ocean and the continental shelf bear similarities. Smaller-scale ocean features are associated with stronger surface divergence, and the surface material clustering is initially dominated by these features. Over time, the effect of these small-scale features becomes bounded, as material traverses small-scale regions of both positive and negative divergence. Lower-frequency flow phenomena, however, continue the clustering. As a result, clustering evolves from initial small-scale to larger-scale patterns.

Clusters, deformation, and dilation: Diagnostics for material accumulation regions

Clusters of material at the ocean surface have been frequently observed. Such accumulations of material play an important role in a variety of applications, from biology to pollution mitigation. Identifying where clusters will form can aid in locating, for example, hotspots of biological activity or regions of high pollutant concentration. Here cluster strength is introduced as a new metric for defining clusters when all particle positions are known. To diagnose regions likely to contain clusters without the need to integrate millions of particle trajectories, we propose to use dilation, which quantifies area changes of Lagrangian patches. Material deformation is decomposed into dilation and area-preserving stretch processes to refine previous approaches based on finite-time Lyapunov exponents (FTLE) by splitting the FTLE into fundamental kinematic properties. The concepts are developed theoretically and illustrated in the context of a state-of-the-art data-assimilating predictive ocean model of the Gulf of Mexico. Regions of dilation less than one are shown to be much more likely (6 times more likely in the given example) to be visited by particles than those of dilation greater than one. While the relationship is nonlinear, dilation and cluster strength exhibit a fairly good correlation. In contrast, both stretch and Eulerian divergence are found to be uncorrelated with cluster strength. Thus, dilation maps can be used as guides for identifying cluster locations, while saving some of the computational cost of trajectory integrations.

Statistical properties of the surface velocity field in the northern Gulf of Mexico sampled by GLAD drifters

The Grand LAgrangian Deployment (GLAD) used multiscale sampling and GPS technology to observe time series of drifter positions with initial drifter separation of O(100 m) to O(10 km), and nominal 5 min sampling, during the summer and fall of 2012 in the northern Gulf of Mexico. Histograms of the velocity field and its statistical parameters are non-Gaussian; most are multimodal. The dominant periods for the surface velocity field are 1–2 days due to inertial oscillations, tides, and the sea breeze; 5–6 days due to wind forcing and submesoscale eddies; 9–10 days and two weeks or longer periods due to wind forcing and mesoscale variability, including the period of eddy rotation. The temporal e-folding scales of a fitted drifter velocity autocorrelation function are bimodal with time scales, 0.25–0.50 days and 0.9–1.4 days, and are the same order as the temporal e-folding scales of observed winds from nearby moored National Data Buoy Center stations. The Lagrangian integral time scales increase from coastal values of 8 h to offshore values of approximately 2 days with peak values of 3–4 days. The velocity variance is large, O(1)m2/s2, the surface velocity statistics are more anisotropic, and increased dispersion is observed at flow bifurcations. Horizontal diffusivity estimates are O(103)m2/s in coastal regions with weaker flow to O(105)m2/s in flow bifurcations, a strong jet, and during the passage of Hurricane Isaac. The Gulf of Mexico surface velocity statistics sampled by the GLAD drifters are a strong function of the feature sampled, topography, and wind forcing

Do Assimilated Drifter Velocities Improve Lagrangian Predictability in an Operational Ocean Model

The Lagrangian predictability of general circulation models is limited by the need for high-resolution data streams to constrain small-scale dynamical features. Here velocity observations from Lagrangian drifters deployedintheGulfofMexicoduringthesummer2012GrandLagrangianDeployment(GLAD)experiment are assimilated into the Naval Coastal Ocean Model (NCOM) 4D variational (4DVAR) analysis system to examine their impact on Lagrangian predictability. NCOM-4DVAR is a weak-constraint assimilation system using the indirect representer method. Velocities derived from drifter trajectories, as well as satellite and in situ observations, are assimilated. Lagrangian forecast skill is assessed using separation distance and angular differences between simulated and observed trajectory positions. Results show that assimilating drifter velocities substantially improvesthe model forecast shape and position of a Loop Currentring. These gains in mesoscale Eulerian forecast skill also improve Lagrangian forecasts, reducing the growth rate of separation distances between observed and simulated drifters by approximately 7.3kmday 21 on average, when compared with forecasts that assimilate only temperature and salinity observations. Trajectory angular differences are also reduced.

Ocean convergence and the dispersion of flotsam

Significance Ocean currents move material released on the ocean surface away from the release point and, over time, spread it over an increasingly large area. However, observations also show high concentrations of the material even after significant spreading. This work examines a mechanism for creating such concentrations: downwelling of water at the boundaries of different water masses concentrates floating material at this boundary. Hundreds of satellite-tracked drifters were released near the site of the 2010 Deepwater Horizon oil spill. Surprisingly, most of these gathered into a single cluster less than 100 m in size, dramatically demonstrating the strength of this mechanism. Floating oil, plastics, and marine organisms are continually redistributed by ocean surface currents. Prediction of their resulting distribution on the surface is a fundamental, long-standing, and practically important problem. The dominant paradigm is dispersion within the dynamical context of a nondivergent flow: objects initially close together will on average spread apart but the area of surface patches of material does not change. Although this paradigm is likely valid at mesoscales, larger than 100 km in horizontal scale, recent theoretical studies of submesoscales (less than ∼10 km) predict strong surface convergences and downwelling associated with horizontal density fronts and cyclonic vortices. Here we show that such structures can dramatically concentrate floating material. More than half of an array of ∼200 surface drifters covering ∼20 × 20 km2 converged into a 60 × 60 m region within a week, a factor of more than 105 decrease in area, before slowly dispersing. As predicted, the convergence occurred at density fronts and with cyclonic vorticity. A zipperlike structure may play an important role. Cyclonic vorticity and vertical velocity reached 0.001 s−1 and 0.01 ms−1, respectively, which is much larger than usually inferred. This suggests a paradigm in which nearby objects form submesoscale clusters, and these clusters then spread apart. Together, these effects set both the overall extent and the finescale texture of a patch of floating material. Material concentrated at submesoscale convergences can create unique communities of organisms, amplify impacts of toxic material, and create opportunities to more efficiently recover such material.

Research Overview of the Consortium for Advanced Research on Transport of Hydrocarbon in the Environment (CARTHE)

ABSTRACT CARTHE (http://carthe.org/) is a Gulf of Mexico Research Initiative (GoMRI) consortium established through a competitive peer-reviewed selection process. CARTHE comprises 26 principal inve...

An Optimization Approach to Modeling Sea Ice Dynamics. Part 1: Lagrangian Framework

A new model for the dynamics of sea ice is proposed. The pressure field, instead of being derived from a local rheology as in most existing models, is computed from a global optimization problem. Here the pressure is seen as emerging not from an equation of state but as a Lagrange multiplier that enforces the ice’s resistance to compression while allowing divergence. The resulting variational problem is solved by minimizing the pressure globally throughout the domain, constrained by the equations of momentum and mass conservation, as well as the limits on ice concentration (which has to stay between 0 and 1). This formulation has an attractive mathematical elegance while being physically motivated. Moreover, it leads to an analytic formulation that is also easily implemented in a numerical code, which exhibits marked stability and is suited to capturing discontinuities. In order to test the theory, the equations for a one‐dimensional model are cast in terms of Lagrangian mass coordinates. The solution to ...

An Optimization Approach to Modeling Sea Ice Dynamics, Part 2: Finite Ice Strength Effects

The effects of a finite ice strength on a new model for sea ice dynamics, deriving the internal pressure field from a global optimization problem, rather than a local rheology, are examined. Building on the promising results from the one‐dimensional Lagrangian model described previously, here we add one of the key properties of sea ice. In order to investigate the behavior of the model under ice yielding, the equations are cast in an Eulerian framework, now allowing for variable thickness. The model is first tested under conditions of infinite ice strength, to ensure that the numerics behave as desired. A finite ice strength is incorporated into the model as a second optimization step, minimizing the change in ice thickness necessary to satisfy the upper bound on the pressure, whereby ice strength is taken to be a linear function of thickness, following typical parameterizations in the literature. The theory is implemented numerically, and several test cases are discussed, which show good agreement with p...

Emergence of Coherent Clusters in the Ocean

Why does material tend to congregate in long coherent clusters at the surface of the ocean when it is well known that the ocean is dispersive? Here we review some recent research that addresses this question. A standard diagnostic for discerning transport pathways in incompressible 2D flows is the finite time Lyapunov exponent (FTLE). The FTLE can be expressed as the average of two rarely evaluated Lagrangian objects: the dilation and stretch rates. The stretch rate accounts for the ability of fluid shear to change the shape of fluid blobs, and for incompressible fluids it is the FTLE. However, in the real ocean and especially at submesoscales, the horizontal divergence is not negligible. This is quantified by the dilation rate, which is identically zero in 2D incompressible flow. Our analysis demonstrates that the combination of fluid dilation and stretch enhances accumulation of buoyant material along thin clusters in an otherwise dispersing ocean.

Drogue-Loss Detection for Surface Drifters during the Lagrangian Submesoscale Experiment (LASER)

AbstractThe Lagrangian Submesoscale Experiment (LASER) was designed to study surface flows during winter conditions in the northern Gulf of Mexico. More than 1000 mostly biodegradable drifters were...