This study investigates the anisotropic properties of the eddy-induced material transport in the near-surface North Atlantic from two independent datasets, one simulated from the sea surface height altimetry and one derived from real-ocean surface drifters, and systematically examines the interactions between the mean- and eddy-induced material transport in the region. The Lagrangian particle dispersion, which is widely used to characterize the eddy-induced tracer fluxes, is quantified by constructing the “spreading ellipses.” The analysis consistently demonstrates that this dispersion is spatially inhomogeneous and strongly anisotropic. The spreading is larger and more anisotropic in the subtropical than in the subpolar gyre, and the largest ellipses occur in the Gulf Stream vicinity. Even at times longer than half a year, the spreading exhibits significant nondiffusive behavior in some parts of the domain. The eddies in this study are defined as deviations from the long-term time-mean. The contributions from the climatological annual cycle, interannual, and subannual (shorter than one year) variability are investigated, and the latter is shown to have the strongest effect on the anisotropy of particle spreading. The influence of the mean advection on the eddy-induced particle spreading is investigated using the “eddy-following-full-trajectories” technique and is found to be significant. The role of the Ekman advection is, however, secondary. The pronounced anisotropy of particle dispersion is expected to have important implications for distributing oceanic tracers, and for parameterizing eddy-induced tracer transfer in non-eddy-resolving models.

Every year, hundreds of people die at sea because of vessel and airplane accidents. A key challenge in reducing the number of these fatalities is to make Search and Rescue (SAR) algorithms more efficient. Here, we address this challenge by uncovering hidden TRansient Attracting Profiles (TRAPs) in ocean-surface velocity data. Computable from a single velocity-field snapshot, TRAPs act as short-term attractors for all floating objects. In three different ocean field experiments, we show that TRAPs computed from measured as well as modeled velocities attract deployed drifters and manikins emulating people fallen in the water. TRAPs, which remain hidden to prior flow diagnostics, thus provide critical information for hazard responses, such as SAR and oil spill containment, and hence have the potential to save lives and limit environmental disasters.

The Great East Japan Earthquake and tsunami that caused a loss of power at the Fukushima nuclear power plants (FNPP) resulted in emission of radioactive isotopes into the atmosphere and the ocean. In June of 2011, an international survey measuring a variety of radionuclide isotopes, including ¹³⁷Cs, was conducted in surface and subsurface waters off Japan. This paper presents the results of numerical simulations specifically aimed at interpreting these observations and investigating the spread of Fukushima-derived radionuclides off the coast of Japan and into the greater Pacific Ocean. Together, the simulations and observations allow us to study the dominant mechanisms governing this process, and to estimate the total amount of radionuclides in discharged coolant waters and atmospheric airborne radionuclide fallout. The numerical simulations are based on two different ocean circulation models, one inferred from AVISO altimetry and NCEP/NCAR reanalysis wind stress, and the second generated numerically by the NCOM model. Our simulations determine that > 95% of ¹³⁷Cs remaining in the water within ~600 km of Fukushima, Japan in mid-June 2011 was due to the direct oceanic discharge. The estimated strength of the oceanic source is 16.2 ± 1.6 PBq, based on minimizing the model-data mismatch. We cannot make an accurate estimate for the atmospheric source strength since most of the fallout cesium had left the survey area by mid-June. The model explained several key features of the observed ¹³⁷Cs distribution. First, the absence of ¹³⁷Cs at the southernmost stations is attributed to the Kuroshio Current acting as a transport barrier against the southward progression of ¹³⁷Cs. Second, the largest ¹³⁷Cs concentrations were associated with a semi-permanent eddy that entrained ¹³⁷Cs-rich waters, collecting and stirring them around the eddy perimeter. Finally, the intermediate ¹³⁷Cs concentrations at the westernmost stations are attributed to younger, and therefore less Cs-rich, coolant waters that continued to leak from the reactor in June of that year.

It is argued that the complexity of fluid particle trajectories provides the basis for a new method, referred to as the Complexity Method (CM), for estimation of Lagrangian coherent structures in aperiodic flows that are measured over finite time intervals. The basic principles of the CM are explained and the CM is tested in a variety of examples, both idealized and realistic, and in different reference frames. Two measures of complexity are explored in detail: the correlation dimension of trajectory, and a new measure – the ergodicity defect. Both measures yield structures that strongly resemble Lagrangian coherent structures in all of the examples considered. Since the CM uses properties of individual trajectories, and not separation rates between closely spaced trajectories, it may have advantages for the analysis of ocean float and drifter data sets in which trajectories are typically widely and non-uniformly spaced.

A data-driven procedure for identifying the dominant transport barriers in a time-varying flow from limited quantities of Lagrangian data is presented. Our approach partitions state space into coherent pairs, which are sets of initial conditions chosen to minimize the number of trajectories that “leak” from one set to the other under the influence of a stochastic flow field during a pre-specified interval in time. In practice, this partition is computed by solving an optimization problem to obtain a pair of functions whose signs determine set membership. From prior experience with synthetic, “data rich” test problems, and conceptually related methods based on approximations of the Perron-Frobenius operator, we observe that the functions of interest typically appear to be smooth. We exploit this property by using the basis sets associated with spectral or “mesh-free” methods, and as a result, our approach has the potential to more accurately approximate these functions given a fixed amount of data. In practice, this could enable better approximations of the coherent pairs in problems with relatively limited quantities of Lagrangian data, which is usually the case with experimental geophysical data. We apply this method to three examples of increasing complexity: The first is the double gyre, the second is the Bickley Jet, and the third is data from numerically simulated drifters in the Sulu Sea.