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Tony de Paolo and Eric Terrill

Abstract

A skill analysis of the Multiple Signal Characterization (MUSIC) algorithm used in compact-antenna-style HF radar ocean current radial velocity/bearing determination is performed using simulation. The simulation is based upon three collocated antennas (two cross loops and a monopole with ideal gain patterns) in a geometry similar to the 25-MHz SeaSonde HF radar commercially available from Coastal Ocean Dynamics Applications Radar (CODAR) Ocean Sensors, Palo Alto, California. The simulations consider wind wave/current scenarios of varying complexity to provide insight to the accuracy of surface current retrievals and the inherent limitations of the technique, with a focus on the capabilities of the MUSIC algorithm itself. The influence of second-order scatter, interference, and stationary target scatter are not considered. Simple error reduction techniques are explored and their impacts quantified to aid in operational system configuration and encourage areas of further research. Increases in skill between 55% and 100% using spatial averaging, and between 14% and 33% using temporal averaging, are realized, highlighting the utility of these techniques. When these error-flagging and averaging techniques are employed, individual range cell skill metrics are found to be as high as 0.94 for simple currents at a high signal-to-noise ratio (SNR), while more complex currents achieve a maximum skill metric of 0.72 for the same SNR. These simulations, conducted under ideal conditions, provide insight to understanding the variables, which influence the accuracy of surface currents retrieved using MUSIC.

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Eric J. Terrill and W. Kendall Melville

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The development of a broadband sound velocimeter that allows the simultaneous measurement of sound speed and attenuation over a wide range of frequencies is described. The velocimeter measures the attenuation and dispersion of a broadband acoustic pulse over frequencies ranging from 4 to 100 kHz across a fixed pathlength using a two-transducer system. The resulting data are inverted to arrive at bubble size distributions over bubble radii in the range 30–800 μm.

The instrument was tested in the large wave channel at the Hydraulics Laboratory of Scripps Institution of Oceanography. The channel can generate breaking waves of O(1 m) height using a hydraulically driven wave generator, giving bubble size distributions similar to those found in the field. The presence of the bubbles significantly changes the acoustical properties of the water. Internal consistency checks of the acoustic data and measurements of bubbles using an independent optical sizing technique support the accuracy of the acoustic system in measuring bubble size distributions.

A field test of the system was performed off Scripps Pier in water of approximately 6-m depth. Observations demonstrate that bubble transport events with significant temporal and spatial variability are associated with rip currents and introduce significant vertical gradients in the acoustical properties of the water. The performance of the system in the field was found to be comparable to that found in the laboratory.

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Sung Yong Kim, Bruce D. Cornuelle, and Eric J. Terrill
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Jeffrey Campana, Eric J. Terrill, and Tony de Paolo

Abstract

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, Δω) 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.

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Anthony R. Kirincich, Tony de Paolo, and Eric Terrill

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Estimates of surface currents over the continental shelf are now regularly made using high-frequency radar (HFR) systems along much of the U.S. coastline. The recently deployed HFR system at the Martha’s Vineyard Coastal Observatory (MVCO) is a unique addition to these systems, focusing on high spatial resolution over a relatively small coastal ocean domain with high accuracy. However, initial results from the system showed sizable errors and biased estimates of M 2 tidal currents, prompting an examination of new methods to improve the quality of radar-based velocity data. The analysis described here utilizes the radial metric output of CODAR Ocean Systems’ version 7 release of the SeaSonde Radial Site Software Suite to examine both the characteristics of the received signal and the output of the direction-finding algorithm to provide data quality controls on the estimated radial currents that are independent of the estimated velocity. Additionally, the effect of weighting spatial averages of radials falling within the same range and azimuthal bin is examined to account for differences in signal quality. Applied to two month-long datasets from the MVCO high-resolution system, these new methods are found to improve the rms difference comparisons with in situ current measurements by up to 2 cm s−1, as well as reduce or eliminate observed biases of tidal ellipses estimated using standard methods.

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Jeffrey Campana, Eric J. Terrill, and Tony de Paolo

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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.

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Sung Yong Kim, Bruce D. Cornuelle, and Eric J. Terrill

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Analysis of coastal surface currents measured off the coast of San Diego for two years suggests an anisotropic and asymmetric response to the wind, probably as a result of bottom/coastline boundary effects, including pressure gradients. In a linear regression, the statistically estimated anisotropic response explains approximately 20% more surface current variance than an isotropic wind–ocean response model. After steady wind forcing for three days, the isotropic surface current response veers 42° ± 2° to the right of the wind regardless of wind direction, whereas the anisotropic analysis suggests that the upcoast (onshore) wind stress generates surface currents with 10° ± 4° (71° ± 3°) to the right of the wind direction. The anisotropic response thus reflects the dominance of alongshore currents in this coastal region. Both analyses yield wind-driven currents with 3%–5% of the wind speed, as expected. In addition, nonlinear isotropic and anisotropic response functions are considered, and the asymmetric current responses to the wind are examined. These results provide a comprehensive statistical model of the wind-driven currents in the coastal region, which has not been well identified in previous field studies, but is qualitatively consistent with descriptions of the current response in coastal ocean models.

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Peter Rogowski, Mark Otero, Joel Hazard, Thomas Muschamp, Scott Katz, and Eric Terrill

Abstract

Accurate surface meteorological (MET) observations reported reliably and in near–real time remain a critical component of on-scene environmental observation systems. Presented is a system developed by Scripps Institution of Oceanography that allows for rapid, global deployment of ground-based weather observations to support both timely decision-making and collection of high-quality weather time series for science or military applications in austere environments. Named the Expeditionary Meteorological (XMET), these weather stations have been deployed in extreme conditions devoid of infrastructure ranging from tropical, polar, maritime, and desert environments where near continuous observations were reported. To date, over 1 million weather observations have been collected during 225 deployments around the world with a data report success rate of 99.5%. XMET had its genesis during Operation Iraqi Freedom (OIF), when the U.S. Marine Corps 3rd Marine Aircraft Wing identified an immediate capability gap in environmental monitoring of their operation area due to high spatiotemporal variability of dust storms in the region. To address the sensing gap, XMET was developed to be a portable, expendable, ruggedized, self-contained, bidirectional, weather observation station that can be quickly deployed anywhere in the world to autonomously sample and report aviation weather observations. This paper provides an overview of the XMETs design, reliability in different environments, and examples of unique meteorological events that highlight both the unit’s reliability and ability to provide quality time series. The overview shows expeditionary MET sensing systems, such as the XMET, are able to provide long-term continuous observational records in remote and austere locations essential for regional spatiotemporal MET characterization.

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Gregory Sinnett, Falk Feddersen, Andrew J. Lucas, Geno Pawlak, and Eric Terrill

Abstract

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 (ΔT) 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, ΔT, and two-layer equivalent height z IW of four events were tracked upslope until propagation terminated. Front position was quadratic in time, and normalized ΔT 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.

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Carter Ohlmann, Peter White, Libe Washburn, Brian Emery, Eric Terrill, and Mark Otero

Abstract

Dense arrays of surface drifters are used to quantify the flow field on time and space scales over which high-frequency (HF) radar observations are measured. Up to 13 drifters were repetitively deployed off the Santa Barbara and San Diego coasts on 7 days during 18 months. Each day a regularly spaced grid overlaid on a 1-km2 (San Diego) or 4-km2 (Santa Barbara) square, located where HF radar radial data are nearly orthogonal, was seeded with drifters. As drifters moved from the square, they were retrieved and replaced to maintain a spatially uniform distribution of observations within the sampling area during the day. This sampling scheme resulted in up to 56 velocity observations distributed over the time (1 h) and space (1 and 4 km2) scales implicit in typical surface current maps from HF radar. Root-mean-square (RMS) differences between HF radar radial velocities obtained using measured antenna patterns, and average drifter velocities, are mostly 3–5 cm s−1. Smaller RMS differences compared with past validation studies that employ current meters are due to drifter resolution of subgrid-scale velocity variance included in time and space average HF radar fields. Roughly 5 cm s−1 can be attributed to sampling on disparate time and space scales. Despite generally good agreement, differences can change dramatically with time. In one instance, the difference increases from near zero to more than 20 cm s−1 within 2 h. The RMS difference and bias (mean absolute difference) for that day exceed 7 and 12 cm s−1, respectively.

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