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Uncertainty Estimates for SeaSonde HF Radar Ocean Current ObservationsAbstract
HF radars typically produce maps of surface current velocities without estimates of the measurement uncertainties. Many users of HF radar data, including spill response and search and rescue operations, incorporate these observations into models and would thus benefit from quantified uncertainties. Using both simulations and coincident observations from the baseline between two operational SeaSonde HF radars, we demonstrate the utility of expressions for estimating the uncertainty in the direction obtained with the Multiple Signal Classification (MUSIC) algorithm. Simulations of radar backscatter using surface currents from the Regional Ocean Modeling System show a close correspondence between direction of arrival (DOA) errors and estimated uncertainties, with mean values of 15° at 10 dB, falling to less than 3° at 30 dB. Observations from two operational SeaSondes have average DOA uncertainties of 2.7° and 3.8°, with a fraction of the observations (10.5% and 7.1%, respectively) having uncertainties of >10°. Using DOA uncertainties for data quality control improves time series comparison statistics between the two radars, with
Abstract
HF radars typically produce maps of surface current velocities without estimates of the measurement uncertainties. Many users of HF radar data, including spill response and search and rescue operations, incorporate these observations into models and would thus benefit from quantified uncertainties. Using both simulations and coincident observations from the baseline between two operational SeaSonde HF radars, we demonstrate the utility of expressions for estimating the uncertainty in the direction obtained with the Multiple Signal Classification (MUSIC) algorithm. Simulations of radar backscatter using surface currents from the Regional Ocean Modeling System show a close correspondence between direction of arrival (DOA) errors and estimated uncertainties, with mean values of 15° at 10 dB, falling to less than 3° at 30 dB. Observations from two operational SeaSondes have average DOA uncertainties of 2.7° and 3.8°, with a fraction of the observations (10.5% and 7.1%, respectively) having uncertainties of >10°. Using DOA uncertainties for data quality control improves time series comparison statistics between the two radars, with
Abstract
Frontal instabilities were observed along a density front on the cyclonic boundary of an upwelling filament that formed north of Pt. Arguello, California in October 1983. Observations of the instabilities were conducted using satellite sea surface temperature images and in situ sampling. The instabilities formed on the southern (cyclonic) boundary of the filament at a wavelength of about 20 km and consisted of two lobes, one warm and one cool, each with a width of about 4 km. The time scale for formation of the instabilities is about 1 day. Near-surface distributions of temperature, salinity, and density within the cool lobes of the instabilities are consistent with local upwelling at the rate of about 30 m d−1. A simple model based on conservation of potential vorticity is presented, which accounts for the observed upwelling. Based on isopycnal displacements and the distribution of salinity, the signature of the instabilities appears to be confined to the upper 50 m of the water column.
Abstract
Frontal instabilities were observed along a density front on the cyclonic boundary of an upwelling filament that formed north of Pt. Arguello, California in October 1983. Observations of the instabilities were conducted using satellite sea surface temperature images and in situ sampling. The instabilities formed on the southern (cyclonic) boundary of the filament at a wavelength of about 20 km and consisted of two lobes, one warm and one cool, each with a width of about 4 km. The time scale for formation of the instabilities is about 1 day. Near-surface distributions of temperature, salinity, and density within the cool lobes of the instabilities are consistent with local upwelling at the rate of about 30 m d−1. A simple model based on conservation of potential vorticity is presented, which accounts for the observed upwelling. Based on isopycnal displacements and the distribution of salinity, the signature of the instabilities appears to be confined to the upper 50 m of the water column.
Abstract
A system for spatial mapping of the temperature variance dissipation rate χ based on conductivity micro-structure measurements from a towyo platform is described. The spatial response of the microconductivity probe is approximately that of a one-pole spatial filter with a −3 dB wavenumber of 100 cycles m−1. The microconductivity system is used in conjunction with a CTD that maps the large-scale temperature, salinity and density fields along with gradient quantities such as the buoyancy frequency N. The primary use of the towyo microstructure system is the acquisition of high resolution synoptic maps of small-scale dissipative processes in relation to evolving larger scale oceanic flows.
Abstract
A system for spatial mapping of the temperature variance dissipation rate χ based on conductivity micro-structure measurements from a towyo platform is described. The spatial response of the microconductivity probe is approximately that of a one-pole spatial filter with a −3 dB wavenumber of 100 cycles m−1. The microconductivity system is used in conjunction with a CTD that maps the large-scale temperature, salinity and density fields along with gradient quantities such as the buoyancy frequency N. The primary use of the towyo microstructure system is the acquisition of high resolution synoptic maps of small-scale dissipative processes in relation to evolving larger scale oceanic flows.
Abstract
Temperture and salinity (T–S) finestructure on vertical scales of 10 db and larger is examined in a 500 by 500 km grid located southeast of the Azores in the North Atlantic. The convergence of several water masses dominated by the Mediterranean Water (MW) at mid-depth (1000 m) leads to variety of T–S finestructure which is unstable to double diffusive processes. By forming histograms of the density ratio R ρ, a fundamental parameter in controlling double diffusive processes, it is found that 71% of the volume is unstable to salt fingering while only 5% is unstable to diffusive layering, the other double diffusive instability. In about 24% of the volume, R ρ is less than 2 in the salt fingering sense and at these low values salt fingers grow rapidly. This suggests that salt fingering may be an important diapycnal mixing process in much of the region. Two primary salt fingering regions are found: a near-surface region from about 100 to 500 db with a modal R ρ of 2.0 and a deeper region from about 1000 to 1500 db (the maximum depth of the CTD survey) with a modal R ρ of 1.3 A horizontal map of R ρ in the lower region shows that on average the lowest values (R ρ≤1.25) are found under the MW pool, although other, isolated regions of low R ρ are found to the south. A map of the rms R ρ fluctuation ΔR ρrms in the lower region shows that the most vertically uniform R ρ profiles also occur under the MW pool. High levels of ΔR ρrms are found within a region containing a strong cyclonic meander described by Käse and Zenk and may result from increased isopycnal mixing activity. To examine the occurrence of thermohaline staircase structures which have been found previously in the Mediterranean Outflow, a “steppiness index” is defined which detects step and layer finestructure on vertical scales of 20 db and larger. Staircase structures on these scales are found most frequently to the south of the Azores Current in the inner gyre waters. These structures are generally not found above 1500 db under the MW pool.
Abstract
Temperture and salinity (T–S) finestructure on vertical scales of 10 db and larger is examined in a 500 by 500 km grid located southeast of the Azores in the North Atlantic. The convergence of several water masses dominated by the Mediterranean Water (MW) at mid-depth (1000 m) leads to variety of T–S finestructure which is unstable to double diffusive processes. By forming histograms of the density ratio R ρ, a fundamental parameter in controlling double diffusive processes, it is found that 71% of the volume is unstable to salt fingering while only 5% is unstable to diffusive layering, the other double diffusive instability. In about 24% of the volume, R ρ is less than 2 in the salt fingering sense and at these low values salt fingers grow rapidly. This suggests that salt fingering may be an important diapycnal mixing process in much of the region. Two primary salt fingering regions are found: a near-surface region from about 100 to 500 db with a modal R ρ of 2.0 and a deeper region from about 1000 to 1500 db (the maximum depth of the CTD survey) with a modal R ρ of 1.3 A horizontal map of R ρ in the lower region shows that on average the lowest values (R ρ≤1.25) are found under the MW pool, although other, isolated regions of low R ρ are found to the south. A map of the rms R ρ fluctuation ΔR ρrms in the lower region shows that the most vertically uniform R ρ profiles also occur under the MW pool. High levels of ΔR ρrms are found within a region containing a strong cyclonic meander described by Käse and Zenk and may result from increased isopycnal mixing activity. To examine the occurrence of thermohaline staircase structures which have been found previously in the Mediterranean Outflow, a “steppiness index” is defined which detects step and layer finestructure on vertical scales of 20 db and larger. Staircase structures on these scales are found most frequently to the south of the Azores Current in the inner gyre waters. These structures are generally not found above 1500 db under the MW pool.
Direction Finding and Likelihood Ratio Detection for Oceanographic HF RadarsAbstract
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.
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.
Abstract
A simple model of the conductivity gradient spectrum is developed and used to interpret oceanic conductivity microstructure observations. A principal goal is to estimate the correction factor E for inferring the temperature variance dissipation rate χ r′, over a wide range of temperature and salinity gradients. The correction factor is defined as E≡χ c′/χ r′, where χ c′, is the temperature variance dissipation rate inferred directly by integrating the measured conductivity spectrum. Three spectral forms of temperature and salinity fluctuations are used to model E: the Batchelor spectrum, a white dissipation spectrum, and a growing salt finger spectrum. Model results show that E depends on 1) the local temperature-salinity (T−S) relation m=ds/dT, 2) the spatial response function of the conductivity probe, 3) the degree of T−S correlation at high wavenumbers, 4) the forms of temperature and salinity spectra, and 5) the kinetic energy dissipation rate ε. Results also indicate that E can diverge significantly from unity, particularly when m is negative, ε is large, and temperature and salinity gradients are stable. For example. when m=−0.3 psu°C−1 and ε=10−6m2 s−3,E is in the range 0.05–0.6, depending on the spectral form and T−S correlation. For growing salt finger spectra, E is in the range 1.2–2,4 over the range of density ratio 1.2≤R ρ≤2.0, based on parameters from the area of the North Atlantic Tracer Release Experiment (NATRE). A general method is outlined for determining E from observations of conductivity microstructure and is applied to a dataset obtained during NATRE using the Cartesian diver profiler. Observed profiles exhibit high variability in T, S, m, and conductivity microstructure on vertical scales of a few meters. Because conductivity microstructure. at the NATRE site can result from either shear-driven turbulence or double-diffusive processes, a wide variety of spectral shapes is possible. These physical uncertainties lead to alternative possible estimates of E, hence χ r′, which vary by factors of 10–20 for a few profile segments. However, χ r′, is more typically constrained to within a factor of 2.
Abstract
A simple model of the conductivity gradient spectrum is developed and used to interpret oceanic conductivity microstructure observations. A principal goal is to estimate the correction factor E for inferring the temperature variance dissipation rate χ r′, over a wide range of temperature and salinity gradients. The correction factor is defined as E≡χ c′/χ r′, where χ c′, is the temperature variance dissipation rate inferred directly by integrating the measured conductivity spectrum. Three spectral forms of temperature and salinity fluctuations are used to model E: the Batchelor spectrum, a white dissipation spectrum, and a growing salt finger spectrum. Model results show that E depends on 1) the local temperature-salinity (T−S) relation m=ds/dT, 2) the spatial response function of the conductivity probe, 3) the degree of T−S correlation at high wavenumbers, 4) the forms of temperature and salinity spectra, and 5) the kinetic energy dissipation rate ε. Results also indicate that E can diverge significantly from unity, particularly when m is negative, ε is large, and temperature and salinity gradients are stable. For example. when m=−0.3 psu°C−1 and ε=10−6m2 s−3,E is in the range 0.05–0.6, depending on the spectral form and T−S correlation. For growing salt finger spectra, E is in the range 1.2–2,4 over the range of density ratio 1.2≤R ρ≤2.0, based on parameters from the area of the North Atlantic Tracer Release Experiment (NATRE). A general method is outlined for determining E from observations of conductivity microstructure and is applied to a dataset obtained during NATRE using the Cartesian diver profiler. Observed profiles exhibit high variability in T, S, m, and conductivity microstructure on vertical scales of a few meters. Because conductivity microstructure. at the NATRE site can result from either shear-driven turbulence or double-diffusive processes, a wide variety of spectral shapes is possible. These physical uncertainties lead to alternative possible estimates of E, hence χ r′, which vary by factors of 10–20 for a few profile segments. However, χ r′, is more typically constrained to within a factor of 2.
Abstract
The performance of a network of five CODAR (Coastal Ocean Dynamics Application Radar) SeaSonde high-frequency (HF) radars, broadcasting near 13 MHz and using the Multiple Signal Classification (MUSIC) algorithm for direction finding, is described based on comparisons with an array of nine moorings in the Santa Barbara Channel and Santa Maria basin deployed between June 1997 and November 1999. Eight of the moorings carried vector-measuring current meters (VMCMs), the ninth had an upward-looking ADCP. Coverage areas of the HF radars and moorings included diverse flow and sea-state regimes. Measurement depths were ∼1 m for the HF radars, 5 m for the VMCMs, and 3.2 m for the ADCP bin nearest to the surface. Comparison of radial current components from 18 HF radar–mooring pairs yielded rms speed differences of 7–19 cm s−1 and correlation coefficients squared (r 2) in the range of 0.39–0.77. Spectral analysis showed significant coherence for frequencies below 0.1 cph (periods longer than 10 h). At higher frequencies no significant coherence was found, and noise levels corresponding to 6 cm s−1 rms were evident in the radar data. Errors in the radar bearing determination were found in 10 out of 18 comparisons, with a typical magnitude of 5°–10°, and a maximum of 19°. The effects of bearing errors on total vector currents were evaluated using a simple flow field and measured bearing errors, showing up to 15% errors in computed flow speeds, and up to ∼9° errors in flow directions.
Abstract
The performance of a network of five CODAR (Coastal Ocean Dynamics Application Radar) SeaSonde high-frequency (HF) radars, broadcasting near 13 MHz and using the Multiple Signal Classification (MUSIC) algorithm for direction finding, is described based on comparisons with an array of nine moorings in the Santa Barbara Channel and Santa Maria basin deployed between June 1997 and November 1999. Eight of the moorings carried vector-measuring current meters (VMCMs), the ninth had an upward-looking ADCP. Coverage areas of the HF radars and moorings included diverse flow and sea-state regimes. Measurement depths were ∼1 m for the HF radars, 5 m for the VMCMs, and 3.2 m for the ADCP bin nearest to the surface. Comparison of radial current components from 18 HF radar–mooring pairs yielded rms speed differences of 7–19 cm s−1 and correlation coefficients squared (r 2) in the range of 0.39–0.77. Spectral analysis showed significant coherence for frequencies below 0.1 cph (periods longer than 10 h). At higher frequencies no significant coherence was found, and noise levels corresponding to 6 cm s−1 rms were evident in the radar data. Errors in the radar bearing determination were found in 10 out of 18 comparisons, with a typical magnitude of 5°–10°, and a maximum of 19°. The effects of bearing errors on total vector currents were evaluated using a simple flow field and measured bearing errors, showing up to 15% errors in computed flow speeds, and up to ∼9° errors in flow directions.
Measurement of Antenna Patterns for Oceanographic Radars Using Aerial DronesAbstract
A new method is described employing small drone aircraft for antenna pattern measurements (APMs) of high-frequency (HF) oceanographic radars used for observing ocean surface currents. Previous studies have shown that accurate surface current measurements using HF radar require APMs. The APMs provide directional calibration of the receive antennas for direction-finding radars. In the absence of APMs, so-called ideal antenna patterns are assumed and these can differ substantially from measured patterns. Typically, APMs are obtained using small research vessels carrying radio signal sources or transponders in circular arcs around individual radar sites. This procedure is expensive because it requires seagoing technicians, a vessel, and other equipment necessary to support small-boat operations. Furthermore, adverse sea conditions and obstacles in the water can limit the ability of small vessels to conduct APMs. In contrast, it is shown that drone aircraft can successfully conduct APMs at much lower cost and in a broader range of sea states with comparable accuracy. Drone-based patterns can extend farther shoreward, since they are not affected by the surfzone, and thereby expand the range of bearings over which APMs are determined. This simplified process for obtaining APMs can lead to more frequent calibrations and improved surface current measurements.
Abstract
A new method is described employing small drone aircraft for antenna pattern measurements (APMs) of high-frequency (HF) oceanographic radars used for observing ocean surface currents. Previous studies have shown that accurate surface current measurements using HF radar require APMs. The APMs provide directional calibration of the receive antennas for direction-finding radars. In the absence of APMs, so-called ideal antenna patterns are assumed and these can differ substantially from measured patterns. Typically, APMs are obtained using small research vessels carrying radio signal sources or transponders in circular arcs around individual radar sites. This procedure is expensive because it requires seagoing technicians, a vessel, and other equipment necessary to support small-boat operations. Furthermore, adverse sea conditions and obstacles in the water can limit the ability of small vessels to conduct APMs. In contrast, it is shown that drone aircraft can successfully conduct APMs at much lower cost and in a broader range of sea states with comparable accuracy. Drone-based patterns can extend farther shoreward, since they are not affected by the surfzone, and thereby expand the range of bearings over which APMs are determined. This simplified process for obtaining APMs can lead to more frequent calibrations and improved surface current measurements.
Abstract
The design, calibration, and deployment of a buoy and gas-capture assembly for measuring bubbling gas flux in oceans and lakes are described. The assembly collects gas in a chamber while continuously measuring the position of the gas–water interface that forms as gas accumulates. Interface position is determined from the differential pressure between the chamber and ambient seawater. A spar buoy provides flotation and stability to reduce vertical motion from surface waves. The gas-collection assembly and spar, referred to as a flux buoy, is suitable for deployment from small boats under conditions of light wind and small waves. The flux buoy is being used to determine the spatial distribution of natural hydrocarbon seepage off the south-central California coast. Hydrocarbon seepage from continental shelves may be an important source of atmospheric methane.
Abstract
The design, calibration, and deployment of a buoy and gas-capture assembly for measuring bubbling gas flux in oceans and lakes are described. The assembly collects gas in a chamber while continuously measuring the position of the gas–water interface that forms as gas accumulates. Interface position is determined from the differential pressure between the chamber and ambient seawater. A spar buoy provides flotation and stability to reduce vertical motion from surface waves. The gas-collection assembly and spar, referred to as a flux buoy, is suitable for deployment from small boats under conditions of light wind and small waves. The flux buoy is being used to determine the spatial distribution of natural hydrocarbon seepage off the south-central California coast. Hydrocarbon seepage from continental shelves may be an important source of atmospheric methane.
Improving Surface Current Resolution Using Direction Finding Algorithms for Multiantenna High-Frequency RadarsAbstract
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.
Abstract
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.
