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  • Author or Editor: Charles C. Eriksen x
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Jacob M. Steinberg and Charles C. Eriksen


Idealized simulations of autonomous underwater glider sampling along sawtooth vertical–horizontal paths are carried out in two high-resolution ocean numerical models to explore the accuracy of isopycnal vertical displacement and geostrophic velocity profile estimates. The effects of glider flight speed, sampling pattern geometry, and measurement noise on velocity profile accuracy are explored to interpret recent full-ocean-depth Deepglider observations and provide sampling recommendations for glider missions. The average magnitude of velocity error profiles, defined as the difference between simulated glider-sampled geostrophic velocity profile estimates and model velocity profiles averaged over the spatial and temporal extent of corresponding simulated glider paths, is less than 0.02 m s−1 over most of the water column. This accuracy and the accuracy of glider geostrophic shear profile estimates are dependent on the ratio of mesoscale eddy to internal wave velocity amplitude. Projection of normal modes onto full-depth vertical profiles of model and simulated glider isopycnal vertical displacement and geostrophic velocity demonstrates that gliders are capable of resolving barotropic and baroclinic structure through at least the eighth baroclinic mode.

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Noel A. Pelland, James S. Bennett, Jacob M. Steinberg, and Charles C. Eriksen


Automated feature tracking and vehicle navigation have the potential to facilitate autonomous surveys of ocean eddies by increasing sampling quality and/or decreasing operator workload. During an observational campaign in late 2013 and early 2014, methods for automated tracking were used to direct multiple ocean gliders during persistent surveys of a California Undercurrent eddy in Washington and British Columbia, Canada, coastal waters over a 3-month period. Glider observations of depth-averaged currents in the ocean’s upper kilometer and vertical separation of selected isopycnals were assimilated into a simple model describing eddy position, size, strength, and background flows using an extended Kalman filter. Though differing in detail from observations, results show the assumed eddy structure was sufficient to describe its essential characteristics and stably estimate eddy position through time. Forecast eddy positions and currents were used to select targets automatically to guide multiple gliders along transects through the eddy center as it translated. Transects performed under automated navigation had comparable or better straightness and distance from the eddy center when compared to navigation based on manual interpretation of the eddy scale and position. The tracking results were relatively insensitive to model choices at times when the eddy was well sampled, but they were more sensitive during sampling gaps and redundancies or rapid eddy translation. Overall, the results provide evidence that automated tracking and navigation are feasible with potential for widespread application in autonomous eddy surveys.

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Eleanor Frajka-Williams, Charles C. Eriksen, Peter B. Rhines, and Ramsey R. Harcourt


Vertical velocities in the world’s oceans are typically small, less than 1 cm s−1, posing a significant challenge for observational techniques. Seaglider, an autonomous profiling instrument, can be used to estimate vertical water velocity in the ocean. Using a Seaglider’s flight model and pressure observations, vertical water velocities are estimated along glider trajectories in the Labrador Sea before, during, and after deep convection. Results indicate that vertical velocities in the stratified ocean agree with the theoretical Wentzel–Kramers–Brillouin (WKB) scaling of w; and in the turbulent mixed layer, scale with buoyancy, and wind forcing. It is estimated that accuracy is to within 0.5 cm s−1. Because of uncertainties in the flight model, velocities are poor near the surface and deep apogees, and during extended roll maneuvers. Some of this may be improved by using a dynamic flight model permitting acceleration and by better constraining flight parameters through pilot choices during the mission.

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James S. Bennett, Frederick R. Stahr, Charles C. Eriksen, Martin C. Renken, Wendy E. Snyder, and Lora J. Van Uffelen


Seagliders are buoyancy-driven autonomous underwater vehicles whose subsurface position estimates are typically derived from velocities inferred using a flight model. We present a method for computing velocities and positions during the different phases typically encountered during a dive–climb profile based on a buoyancy-driven flight model. We compare these predictions to observations gathered from a Seaglider deployment on the acoustic tracking range in Dabob Bay (200 m depth, mean vehicle speeds ~30 cm s−1), permitting us to bound the position accuracy estimates and understand sources of various errors. We improve position accuracy estimates during long vehicle accelerations by numerically integrating the flight model’s fundamental momentum-balance equations. Overall, based on an automated estimation of flight-model parameters, we confirm previous work that predicted vehicle velocities in the dominant dive and climb phases are accurate to <1 cm s−1, which bounds the accumulated position error in time. However, in this energetic tidal basin, position error also accumulates due to unresolved depth-dependent flow superimposed upon an inferred depth-averaged current.

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