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Understanding variations in the received power levels for land‐based high frequency radar (HFR) systems is critical to advancing radar‐based estimates of winds and waves. We use a long‐term record of one‐way HFR power observations to explore the key factors controlling propagation losses over the ocean. Observed propagation loss was quantified using an 8‐month record of radio frequency power from a shore‐based transmitter, received at two locations: an offshore tower and a nearby island. Observations were compared to environmental factors such as wind speed and air temperature as well as models of path loss incorporating smooth and rough surface impedances and varying atmospheric properties. Significant differences in the observations at the two sites existed. One‐way path loss variations at the tower, a wavelength above mean sea level, were closely related to atmospheric forcing, while variations at the distant island site were dominated by wind‐driven surface gravity wave variability. Seasonal variability in ocean conductivity had no significant effect on over‐ocean path losses. Simplistic analytical models of path loss were found to have more skill than either ground wave propagation models or more complex numerical models of field strength in matching the observations, due in part to under‐observation of the atmosphere but also the differences in rough surface impedance between models of ocean waves.

 

Abstract Previous work with simulations of oceanographic high-frequency (HF) radars has identified possible improvements when using maximum likelihood estimation (MLE) for direction of arrival; however, methods for determining the number of emitters (here defined as spatially distinct patches of the ocean surface) have not realized these improvements. Here we describe and evaluate the use of the likelihood ratio (LR) for emitter detection, demonstrating its application to oceanographic HF radar data. The combined detection–estimation methods MLE-LR are compared with multiple signal classification method (MUSIC) and MUSIC parameters for SeaSonde HF radars, along with a method developed for 8-channel systems known as MUSIC-Highest. Results show that the use of MLE-LR produces similar accuracy, in terms of the RMS difference and correlation coefficients squared, as previous methods. We demonstrate that improved accuracy can be obtained for both methods, at the cost of fewer velocity observations and decreased spatial coverage. For SeaSondes, accuracy improvements are obtained with less commonly used parameter sets. The MLE-LR is shown to be able to resolve simultaneous closely spaced emitters, which has the potential to improve observations obtained by HF radars operating in complex current environments. Significance Statement We identify and test a method based on the likelihood ratio (LR) for determining the number of signal sources in observations subject to direction finding with maximum likelihood estimation (MLE). Direction-finding methods are used in broad-ranging applications that include radar, sonar, and wireless communication. Previous work suggests accuracy improvements when using MLE, but suitable methods for determining the number of simultaneous signal sources are not well known. Our work shows that the LR, when combined with MLE, performs at least as well as alternative methods when applied to oceanographic high-frequency (HF) radars. In some situations, MLE and LR obtain superior resolution, where resolution is defined as the ability to distinguish closely spaced signal sources. 

This study examines the spatial and temporal variability of eddy kinetic energy over the Northeast Shelf using observations of surface currents from a unique array of six high frequency radar systems. Collected during summer and winter conditions over three consecutive years, the horizontal scales present were examined in the context of local wind and hydrographic variability, which were sampled concurrently from moorings and autonomous surface vehicles. While area‐averaged mean kinetic energy at the surface was tightly coupled to wind forcing, eddy kinetic energy was not, and was lower in magnitude in winter than summer in all areas. Kinetic energy wavenumber spectral slopes were generally near k^−5/3, but varied seasonally, spatially, and between years. In contrast, wavenumber spectra of surface temperature and salinity along repeat transect lines had sharpk⁻³spectral slopes with little seasonal or inter‐annual variability. Radar‐based estimates of spectral kinetic energy fluxes revealed a mean transition scale of energy near 18 km during stratified months, but suggested much longer scales during winter. Overall, eddy kinetic energy was unrelated to local winds, but the up‐ or down‐scale flux of kinetic energy was tied to wind events and, more weakly, to local density gradients.

 

While land-based high-frequency (HF) radars are the only instruments capable of resolving both the temporal and spatial variability of surface currents in the coastal ocean, recent high-resolution views suggest that the coastal ocean is more complex than presently deployed radar systems are able to reveal. This work uses a hybrid system, having elements of both phased arrays and direction finding radars, to improve the azimuthal resolution of HF radars. Data from two radars deployed along the U.S. East Coast and configured as 8-antenna grid arrays were used to evaluate potential direction finding and signal, or emitter, detection methods. Direction finding methods such as maximum likelihood estimation generally performed better than the well-known multiple signal classification (MUSIC) method given identical emitter detection methods. However, accurately estimating the number of emitters present in HF radar observations is a challenge. As MUSIC’s direction-of-arrival (DOA) function permits simple empirical tests that dramatically aid the detection process, MUSIC was found to be the superior method in this study. The 8-antenna arrays were able to provide more accurate estimates of MUSIC’s noise subspace than typical 3-antenna systems, eliminating the need for a series of empirical parameters to control MUSIC’s performance. Code developed for this research has been made available in an online repository.

 

Circulation patterns over the inner continental shelf can be spatially complex and highly variable in time. However, few studies have examined alongshore variability over short scales of kilometers or less. To observe inner‐shelf bottom temperatures with high (5‐m) horizontal resolution, a fiber‐optic distributed temperature sensing system was deployed along a 5‐km‐long portion of the 15‐m isobath within a larger‐scale mooring array south of Martha's Vineyard, MA. Over the span of 4 months, variability at a range of scales was observed along the cable over time periods of less than a day. Notably, rapid cooling events propagated down the cable away from a tidal mixing front, showing that propagating fronts on the inner shelf can be generated locally near shallow bathymetric features in addition to remote offshore locations. Propagation velocities of observed fronts were influenced by background tidal currents in the alongshore component and show a weak correlation with theoretical gravity current speeds in the cross‐shore component. These events provide a source of cold, dense water into the inner shelf. However, differences in the magnitude and frequency of cooling events at sites separated by a few kilometers in the alongshore direction suggest that the characteristics of small‐scale variability can vary dramatically and can result in differential fluxes of water, heat, and other tracers. Thus, under stratified conditions, prolonged subsurface observations with high spatial and temporal resolution are needed to characterize the implications of three‐dimensional circulation patterns on exchange, especially in regions where the coastline and isobaths are not straight.

 

The rapid growth of offshore wind energy requires accurate modeling of the wind resource, which can be depleted by wind farm wakes. Turbulence dissipation rate (ϵ) governs the accuracy of model predictions of hub‐height wind speed and the development and erosion of wakes. Here we assess the variability of turbulence kinetic energy andϵusing 13 months of observations from a profiling lidar deployed on a platform off the Massachusetts coast. Offshore,ϵis 2 orders of magnitude smaller than onshore, with a subtle diurnal cycle. Wind direction influences the annual cycle of turbulence, with larger values in winter when the wind flows from the land, and smaller values in summer, when the wind flows from open ocean. Because of the weak turbulence, wind plant wakes will be stronger and persist farther downwind in summer.