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The present work details the measurement capabilities of Wave Glider autonomous surface vehicles (ASVs) for research-grade meteorology, wave, and current data. Methodologies for motion compensation are described and tested, including a correction technique to account for Doppler shifting of the wave signal. Wave Glider measurements are evaluated against observations obtained from World Meteorological Organization (WMO)-compliant moored buoy assets located off the coast of Southern California. The validation spans a range of field conditions and includes multiple deployments to assess the quality of vehicle-based observations. Results indicate that Wave Gliders can accurately measure wave spectral information, bulk wave parameters, water velocities, bulk winds, and other atmospheric variables with the application of appropriate motion compensation techniques. Measurement errors were found to be comparable to those from reference moored buoys and within WMO operational requirements. The findings of this study represent a step toward enabling the use of ASV-based data for the calibration and validation of remote observations and assimilation into forecast models.

Fisheries management faces numerous monitoring and enforcement challenges that are becoming more complex as fish stocks are depleted; and illegal, unregulated, and unreported fishing becomes more sophisticated. For remote island nations, the challenges are compounded by a loosely understood association of pelagic stocks to the ocean environment, and the tyranny of distance in monitoring and surveilling large exclusive economic zones (EEZ). An approach to ocean conservation is establishing protected areas, with the Pacific island nation of Palau as a leader with the recently established National Marine Sanctuary, which closes 80% of their EEZ to commercial fishing in 2020. Here we present an EEZ-wide analysis of Palau commercial fishing over a 6-year period (2011–2016), and develop a system for predicting fishing activity accounting for oceanic variables, climate indices, and vessel flag. Linking pelagic habitat to fishing activity provides high-resolution decision aids for management, highlighting the need for EEZ-specific analyses in addressing fisheries.

A method based on machine learning and image processing techniques has been developed to track the surface expression of internal waves in near–real time. X-band radar scans are first preprocessed and averaged to suppress surface wave clutter and enhance the signal-to-noise ratio of persistent backscatter features driven by gradients in surface currents. A machine learning algorithm utilizing a support vector machine (SVM) model is then used to classify whether or not the image contains an internal solitary wave (ISW) or internal tide bore (bore). The use of machine learning is found to allow rapid assessment of the large dataset, and provides insight on characterizing optimal environmental conditions to allow for radar illumination and detection of ISWs and bores. Radon transforms and local maxima detections are used to locate these features within images that are determined to contain an ISW or bore. The resulting time series of locations is used to create a map of propagation speed and direction that captures the spatiotemporal variability of the ISW or bore in the coastal environment. This technique is applied to 2 months of data collected near Point Sal, California, and captures ISW and bore propagation speed and direction information that currently cannot be measured with instruments such as moorings and synthetic aperture radar (SAR).

The influence of wave–current interactions on time series of marine X-band radar backscatter maps at the mouth of the Columbia River (MCR) near Astoria, Oregon, is examined. The energetic wave environment at the MCR, coupled with the strong tidally forced currents, provides a unique test environment to explore the limitations in accurately determining the magnitude and vertical structure of upper-ocean currents from wavefield measurements. Direct observation in time and space of the wave-induced radar backscatter and supporting acoustic Doppler current profiler (ADCP) current measurements provide a rich dataset for investigating how currents shift the observed wave dispersion relationship. First, current extraction techniques that assume a specific current–depth profile are tested against ADCP measurements. These constrained solutions prove to have inaccuracies because the models do not properly account for vertical shear. A forward solution using measured current profiles to predict the wavenumber–Doppler shift relationship for the range of ocean waves sensed by the radar is introduced. This approach confirms the ocean wavefield is affected by underlying vertical current shear. Finally, a new inversion method is developed to extract current profiles from the wavenumber-dependent Doppler shift observations. The success of the inversion model is shown to be sensitive to the range of wavenumbers spanned by observed Doppler shifts, with skill exceeding 0.8 when wavenumbers span more than 0.1 rad m −1 . This agreement when observations successfully capture the broadband wavefield suggests the X-band backscatter is a viable means of remotely estimating current shear.

The North Equatorial Current (NEC) transports water westward around numerous islands and over submarine ridges in the western Pacific. As the currents flow over and around this topography, the central question is: how are momentum and energy in the incident flow transferred to finer scales? At the south point of Peleliu Island, Palau, a combination of strong NEC currents and tides flow over a steep, submarine ridge. Energy cascades suddenly from the NEC via the 1 km scale lee waves and wake eddies to turbulence. These submesoscale wake eddies are observed every tidal cycle, and also in model simulations. As the flow in each eddy recirculates and encounters the incident flow again, the associated front contains interleaving temperature (T) structures with 1–10 m horizontal extent. Turbulent dissipation (ε) exceeds 10−5 W kg−1 along this tilted and strongly sheared front. A train of such submesoscale eddies can be seen at least 50 km downstream. Internal lee waves with 1 km wavelengths are also observed over the submarine ridge. The mean form drag exerted by the waves (i.e., upward transport of eastward momentum) of about 1 Pa is sufficient to substantially reduce the westward NEC, if not for other forcing, and is greater than the turbulent bottom drag of about 0.1 Pa. The effect on the incident flow of the form drag from only one submarine ridge may be similar to the bottom drag along the entire coastline of Palau. The observed ε is also consistent with local dissipation of lee wave energy. The circulation, including lee waves and wake eddies, was simulated by a datadriven primitive equation ocean model. The model estimates of the form drags exerted by pressure drops across the submarine ridge and due to wake eddies were found to be about 10 times higher than the lee wave and turbulent bottom drags. The ridge form drag was correlated to both the tidal flow and winds while the submesoscale wake eddy drag was mainly tidal.

The cross-shore evolution of nonlinear internal waves (NLIWs) from 8-m depth to shore was observed by a dense thermistor array and ADCP. Isotherm oscillations spanned much of the water column at a variety of periods. At times, NLIWs propagated into the surfzone, decreasing temperature by ≈1°C in 5 min. When stratification was strong, temperature variability was strong and coherent from 18- to 6-m depth at semidiurnal and harmonic periods. When stratification weakened, temperature variability decreased and was incoherent between 18- and 6-m depth at all frequencies. At 8-m depth, onshore coherently propagating NLIW events had associated rapid temperature drops (Δ T ) up to 1.7°C, front velocity between 1.4 and 7.4 cm s −1 , and incidence angles between −5° and 23°. Front position, Δ T , and two-layer equivalent height z IW of four events were tracked upslope until propagation terminated. Front position was quadratic in time, and normalized Δ T and z IW both decreased, collapsing as a linearly decaying function of normalized cross-shore distance. Front speed and deceleration are consistent with two-layer upslope gravity current scalings. During NLIW rundown, near-surface cooling and near-bottom warming at 8-m depth coincide with a critical gradient Richardson number, indicating shear-driven mixing.

Complex interactions between open ocean and nearshore environments pose a predictability problem. Basin-scale ocean models are typically run at grid scales that do not accurately resolve individual islands, and model output is assessed mostly using observations of the open ocean. Thus, model ability to replicate island forereef oceanic variability has gone largely untested. Here, an eight-year regional state estimate covering 2009–2017 is compared to bottom temperature observations at the western Pacific islands of Palau and Pohnpei, and is found to reproduce the observed seasonal to interannual variability. Because of their steep bathymetry, these islands can act as moorings. Sea surface variables, such as temperature (SST) and height (SSH), have been shown to predict upper ocean thermal structure in the region, but the spatial structure of the relationship has gone unexplored. The state estimate was used to examine the multivariate predictability of temperature at depths to about 200 m both at the island boundaries and throughout the domain. The results show that the best multiple linear regression (MLR) skill was found near Palau, but useful skill (>0.6) was available through much of the region within the anticyclonic gyre driven by positive wind-stress curl. Point SSH measurements offered prediction skill for areas extending a few hundred kilometers zonally and perhaps 100 km meridionally. The insights into the additional information contained in surface variables in this region could aid in advancement of ocean modeling as well as predictions of ecological patterns and stressors.

The temporal variation of received clutter and noise at a pair of oceanographic high frequency radars (HFR) operating near the geomagnetic equator in the Republic of Palau is investigated. Oceanographic HFRs process range-gated Doppler spectra from groundwave signals that are backscattered from the ocean’s surface to derive maps of ocean currents. The range performance of the radars exhibited a regular diurnal signal which is determined to be a result of both ionospheric clutter and noise. The increased Clutter plus Noise Floor (C+NF) decreases the Signal to Clutter plus Noise Ratio (SCNR) which, in turn, reduces the range and quality of ocean surface current measurement. Determining the nature and origin of this degradation is critical to QA/QC of existing HFR deployments as well as performance predictions of future installations. Nighttime impacts are most severe and negatively affect ocean surface current measurements as low SCNR is found to extend across the Doppler spectra at all ranges, challenging the ability of HFR to map the ocean surface current. Daytime degradation is less severe and presents itself in a way consistent with independent observations of ionospheric clutter, specifically the diurnal temporal pattern and range where the C+NF features occur. A timeseries analysis of SCNR and C+NF is pursued to understand this relationship using received range-dependent Doppler spectra and C+NF features using image segmentation techniques. Clutter plus noise features are classified into daytime, nighttime, and no-noise feature types. The diurnal structure and variability of these features are examined, and the occurrences of each feature type are calculated. The occurrences are compared with space weather indices including a measure of geomagnetic activity, namely the EE (Equatorial Electro Jet) index (determined from magnetometers measuring the earth’s magnetic field), as well as solar impacts using the F10.7 solar radio clutter index to assess the relationship of ionospheric conditions with HFR ocean surface current measurement.

A new method for estimating current-depth profiles from observations of wavenumber-dependent Doppler shifts of the overlying ocean wave field is presented. Consecutive scans of marine X-band backscatter provide wave field measurements in the time–space domain that transform into the directional wavenumber–frequency domain via a 3D fast Fourier transform (FFT). Subtracting the linear dispersion shell yields Doppler shift observations in the form of ( k x , k y , Δ ω ) triplets. A constrained linear regression technique is used to extract the wavenumber-dependent effective velocities, which represent a weighted depth average of the Eulerian currents (Stewart and Joy). This new method estimates these Eulerian currents from the effective velocities via the inversion of the integral relationship, which was first derived by Stewart and Joy. To test the effectiveness of the method, the inverted current profiles are compared to concurrent ADCP measurements. The inversion method is found to successfully predict current behavior, with a depth-average root-mean-square (RMS) error less than 0.1 m s −1 for wind speeds greater than 5 m s −1 and a broad wave spectrum. The ability of the inversion process to capture the vertical structure of the currents is assessed using a time-average RMS error during these favorable conditions. The time-averaged RMS error is found to be less than 0.1 m s −1 for depths shallower than 20 m, approximately twice the depth of existing methods of estimating current shear from wave field measurements.

The interaction of large-scale oceanic flows with remote island chains can lead to turbulent wakes, enhanced vorticity production, and significant increases in biological productivity. This study showcases the range of flow conditions captured by surface current mapping high-frequency (HF) radar systems deployed around the main island group of Palau in the western Pacific. The radar array captures strong tidal and inertial flows, both near- and offshore, as well as the spatial and temporal variability associated with the synoptic geostrophic flow interacting with the island group. Surface currents measured by HF radar are significantly correlated to currents in the upper 100 m of the ocean water column, as observed with a concurrent mooring, such that the resulting surface spatial maps provide insight on the wake flows of the island across a significant portion of the upper ocean. Composite averages of eastward and westward incident flow show flow-splitting and reconnection 60 km upstream and downstream of the island group, respectively. Surface current variability observed by the radar array includes topographically blocked flow, flow separation and acceleration through passages in the island chain, eddy dipole structure, and coastal eddies with Rossby numbers of 5. The range of variability near the island chain is reflective of the complex incident flow, which encounters Palau from all directions and changes on timescales of hours to weeks. A high-resolution model qualitatively agrees with the HF radar observations and shows vorticity filaments generated downstream of the island passages.