Radar-derived Surface Currents Research Articles

Eddy Detection in HF Radar-Derived Surface Currents in the Gulf of Naples

Submesoscale eddies play an important role in the energy transfer from the mesoscale down to the dissipative range, as well as in tracer transport. They carry inorganic matter, nutrients and biomass; in addition, they may act as pollutant conveyors. However, synoptic observations of these features need high resolution sampling, in both time and space, making their identification challenging. Therefore, HF coastal radar were and are successfully used to accurately identify, track and describe them. In this paper we tested two already existing algorithms for the automated detection of submesoscale eddies. We applied these algorithms to HF radar velocity fields measured by a network of three radar systems operating in the Gulf of Naples. Both methods showed shortcomings, due to the high non-geostrophy of the observed currents. For this reason we developed a third, novel algorithm that proved to be able to detect highly asymmetrical eddies, often not properly identified by the previous ones. We used the results of the application of this algorithm to estimate the eddy boundary profiles and the eddy spatial distribution.

Quality Assessment of HF Radar–Derived Surface Currents Using Optimal Interpolation

AbstractThis study investigates the applicability of the optimal interpolation (OI) method proposed by Kim et al. for estimating ocean surface currents from high-frequency radar (HFR) in the northeastern Chukchi Sea, where HFR siting is dictated by power availability rather than optimal locations. Although the OI technique improves data coverage when compared to the conventional unweighted least squares fit (UWLS) method, biased solutions can emerge. The quality of the HFR velocity estimates derived by OI is controlled by three factors: 1) the number of available incorporating radials (AR), 2) the ratio of the incorporating radials from multiple contributing site locations [ratio of overlapping radial velocities (ROR) or radar geometry], and 3) the positive definiteness [condition number (CN)] of the correlation matrix. Operationally, ROR does not require knowledge of the angle covariance matrix used to compute the geometric dilution of precision (GDOP) in the UWLS method and can be computed before site selection to optimize coverage or after data processing to assess data quality when applying the OI method. The Kim et al. method is extended to examine sensitivities to data gaps in the radial distribution and the effects on OI estimates.

Coastal exposure to oil spill impacts from the Finisterre Traffic Separation Scheme

This study analyzes the coastal exposure to potential oil spills coming from the various corridors that constitute the Finisterre Traffic Separation Scheme (NW Iberia). A Lagrangian model was executed with results from a realistic configuration of an ocean model during 2012, validated here against High-Frequency (HF) radar-derived surface currents. Virtual particles were released each hour and followed during the next 4days. A series of maps summarize which regions would be impacted and when. We have learnt, for example, that Cape Finisterre is the most affected area under a wide range of scenarios and that a sensitive area such as the National Park of the Atlantic Islands would require protective actions in less than 24h if oil spills from the south eventually occurred. A complete analysis by corridor and during specific wind events is available through a web tool, which could be useful for decision makers in case of contingency.

Variability in the air–sea interaction patterns and timescales within the south-eastern Bay of Biscay, as observed by HF radar data

Abstract. Two high-frequency (HF) radar stations were installed on the coast of the south-eastern Bay of Biscay in 2009, providing high spatial and temporal resolution and large spatial coverage of currents in the area for the first time. This has made it possible to quantitatively assess the air–sea interaction patterns and timescales for the period 2009–2010. The analysis was conducted using the Barnett–Preisendorfer approach to canonical correlation analysis (CCA) of reanalysis surface winds and HF radar-derived surface currents. The CCA yields two canonical patterns: the first wind–current interaction pattern corresponds to the classical Ekman drift at the sea surface, whilst the second describes an anticyclonic/cyclonic surface circulation. The results obtained demonstrate that local winds play an important role in driving the upper water circulation. The wind–current interaction timescales are mainly related to diurnal breezes and synoptic variability. In particular, the breezes force diurnal currents in waters of the continental shelf and slope of the south-eastern Bay. It is concluded that the breezes may force diurnal currents over considerably wider areas than that covered by the HF radar, considering that the northern and southern continental shelves of the Bay exhibit stronger diurnal than annual wind amplitudes.

Assimilation of HF radar-derived surface currents on tidal-timescales

A surface current observation system based on high-frequency (HF) radar has been developed for Raritan Bay and the coastal waters of New York and New Jersey. An HF radar network provides synoptic surface current maps in near-real-time that can be optimally combined with ocean circulation models using data assimilation (DA) framework to obtain the best possible estimate of a three-dimensional ocean state. A nudging or Newtonian damping scheme has been developed to assimilate HF radar data into an estuarine and coastal ocean circulation model. This model, with an extensive embedded real-time observational network, is called the New York Harbour Observing and Prediction System (NYHOPS). A nudging parameter is introduced into the equations of motion which affects the model dynamics. The data is imparted to neighbouring (three-dimensional) grid points via model dynamics. The impact of HF radar DA is analysed by computing the DA skill score (DAskill) based on the mean-square-error (mse). The DAskill is computed by comparing non-assimilated and assimilated model solutions with in-situ observations of three-dimensional currents, temperature and salinity, which have not been included in the assimilation. A positive DAskill (0∼1) represents an improvement in the model performance by assimilation. HF radar data covering Raritan Bay and the New York Bight (NYB) Apex were assimilated into the NYHOPS model in the model hindcast cycle (–24h to 0h) on a daily forecast basis for a period of 40 days. The DAskill is assessed with respect to the NYHOPS model hindcasts (daily model solutions from –24h to 0h) as well as the first day forecasts (daily model solutions from 0h to 24h). HF radar DA improved the NYHOPS model performance during both the hindcast and forecast periods. The model skill metrics for the near-surface layers in the inner-NJ shelf region shows a hindcast DAskill of 24% (14%) and forecast DAskill of 18% (7%) for horizontal velocities u: east-west component (v: north-south component), and a hindcast DAskill of 33% (38%) and forecast DAskill of 25% (30%) for temperature (salinity). The nudging scheme is robust and efficient for the HF radar DA into the NYHOPS operational forecast model. The NYHOPS-HF radar DA system is capable of importing in the observations and produce useful hindcasts/forecasts with minimum computational expense.

Methodology for a regional tidal model evaluation, with application to central California

Abstract Observations from disparate observational assets, including tide gauges, moorings, and high-frequency (HF) radars, were used to depict the tidal variability, and to evaluate model tidal simulations, for a region off central California, including the Monterey Bay. For this study, the hydrodynamic model was forced only with tides derived from a large-scale model for the northeast Pacific Ocean. Homogeneous density, and initially horizontally uniform density stratification, cases were considered. The model successfully reproduced tidal sea-surface height variations within the model domain, as determined by comparisons with sea level or bottom pressure measured at six locations. To achieve tidal currents with realistic amplitudes, as determined from HF radar and moored measurements, it was found that barotropic velocity, as well as sea level, from the large-scale regional tidal model must be included in specifying the open-boundary condition. However, even with such forcing, the model with homogeneous density field under-predicted the semidiurnal and diurnal barotropic currents as estimated from depth-averaged currents measured at 11 locations. In the diurnal frequency band, the observed surface and nearshore depth-averaged currents are likely influenced by meteorological forcing, which was not included in the model. The HF radar-measured surface tidal currents, both semidiurnal and diurnal, are consistent from year to year and between the winter season and the entire year. Semidiurnal surface tidal currents derived from year-long HF radar measurements do not resemble either the modeled or measured barotropic current fields. Rather, they exhibit amplitudes and small-scale spatial variability indicative of the presence of internal tides, thus indicating that model-derived barotropic tidal currents cannot be validated over large spatial extents using long time series of HF radar-derived surface currents. With initially horizontally uniform vertical density stratification, the model produced surface currents with spatial variability and amplitude range comparable to what was derived from HF radar surface current measurements, but the point by point comparisons are not impressive for this region of complex topography. Likewise, the subsurface current comparisons, performed at four deepwater locations, show considerable model-data differences. Possible reasons for these disparities include the effects of atmospheric forcing, spatially and temporally varying stratification, remotely generated coastally trapped waves, and remotely generated internal tides.

Assimilation of HF radar-derived radials and total currents in the Monterey Bay area

Abstract Impact of HF radar surface-current assimilation on ocean circulation model predictions in the Monterey Bay area is studied and evaluated during the time frame of the Autonomous Ocean Sampling Network (AOSN-II) experiment (August–September 2003). In the first instance, a previously described method for assimilation of surface current data is applied to 33-h low-pass-filtered data and a non-tidal version of the circulation model. It is demonstrated that assimilation of surface velocity data significantly improves the surface and subsurface correlation of model currents with moored current observations. These results from the AOSN-II period illustrate that surface-current assimilation is beneficial even in cases for which very high-resolution (3 km) atmospheric forcing is utilized. The assimilation approach is also tested with hourly, unfiltered, CODAR-type HF radar-derived surface currents within a model configuration that includes tidal forcing. It is shown, that assimilation of unfiltered (with tides) surface-current observations into the model with tides improves the sub-tidal model predictions to the level comparable with the assimilation of filtered data into the non-tidal model, which is significant with respect to options for designing real-time nowcast and forecast systems. Finally, the approach is extended and evaluated for the direct assimilation of HF radar-derived radial velocity components. The model runs that included assimilation of radials from at least two HF radar sites show better correlations with observations than the non-assimilative run, especially those runs that included radials from the Santa Cruz site. Directions of radials for that site coincide with the directions of dominant southward flow during upwelling events and the northward flow during relaxation events. Direct assimilation of radial currents extends the range of influence of the data into regions covered by only one HF radar site.

Interpretation of Coastal HF Radar–Derived Surface Currents with High-Resolution Drifter Data

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.

Submesoscale Coastal Ocean Flows Detected by Very High Frequency Radar and Autonomous Underwater Vehicles

Over a 29-day time series in July 1999, an ocean surface current radar (OSCR) in very high frequency (VHF) mode mapped the surface velocity field at 250-m resolution at 700 cells off Fort Lauderdale, Florida. During the experiment, autonomous underwater vehicles (AUVs), equipped with upward- and downward-looking 1.2MHz acoustic Doppler current profilers (ADCPs), measured subsurface current structure over four to six radar cells during two mixed layer patterns on 9 and 27 July 1999. As these AUV sampling patterns were conducted over 500 m 3 500 m and 500 m 3 750 m areas, these missions required about 80‐90 min (four radar sample intervals) to form four and seven synoptic snapshots, respectively. Based on autocorrelation analyses of the profiler data, along-AUV-track subsurface profiles were averaged at 10-s intervals, mapped to a surface from 1.5‐6.5 m, and compared to surface currents at more than 500 points for each snapshot. Comparisons between the surface and subsurface currents from the AUV revealed spatially averaged differences ranging from 4 to 26 cm s21 during these two experiments. The largest differences occurred when the surface and subsurface current vectors were orthogonal; otherwise, differences were O(10 cm s21). Scatterplots between 2-m and radar-derived surface currents indicated a consistent relationship with mooring data. From the seven spatial snapshots acquired during the second experiment, current profiles suggested a timedependent oscillation that was corroborated by radar and moored ADCP data. Least squares fits of these profiles from sequential AUV snapshots to a simple model isolated an ;9.2 6 1 h oscillation where the along-shelf current was O(50 cm s21). Spatially averaged current profiles from four and seven snapshots were subsequently time averaged to form a mean profile from each experiment. In the downwind directions, these mean profiles were compared to a winddriven, logarithmic layer profile in the upper 6.5 m based on a 10-m surface winds. Regression analyses suggest a slope of 1.16 between the theoretical and observed mean profiles with a bias of about 3 cm s21. In this context, the averaged winds played a role in driving the coastal ocean circulation. These results further suggest that the spatial averaging by the radar is consistent when subsurface current variations are averaged over similar time and space scales.

A Modeling Study of the Three-Dimensional Continental Shelf Circulation off Oregon. Part II: Dynamical Analysis

Abstract Sixty-day simulations of the subinertial continental shelf circulation off Oregon are performed for a hindcast study of summer 1999. In Part I, the model results are shown to compare favorably with in situ currents and hydrographic measurements obtained from an array of moored instruments and field surveys and high-frequency radar–derived surface currents. In this paper, the modeled three-dimensional, time-varying circulation and dynamical balances are analyzed, providing a detailed synoptic description of the continental shelf circulation off Oregon for summer 1999. The circulation is clearly wind driven and strongly influenced by alongshore variations in shelf topography. In the region of the coast where the alongshore topographic variations are small the upwelling circulation is consistent with standard conceptual models for two-dimensional across-shore circulation. In the regions where the alongshore topographic variations are greater, the upwelling circulation is highly three-dimensional. Ov...

Comparison of over‐the‐horizon radar surface‐current measurements in the Gulf of Mexico with simultaneous sea truth

On June 14, 1995, the U.S. Navy's Relocatable Over‐the‐Horizon Radar (ROTHR) west of Corpus Christi, Texas, mapped the radial component of ocean surface current with 15‐km resolution over a 230,000‐km2area in the Gulf of Mexico. Concurrently, an oceanographic research vessel measured near‐surface currents within part of the area illuminated by the radar, providing an opportunity to compare radarderived surface currents with in situ sea truth. The R/VGyre, operated by Texas A&M University, twice traversed the Gulf of Mexico Loop Current while measuring current vectors with an acoustic Doppler current profiler (ADCP). We compared radar‐derived currents with currents measured in the uppermost ADCP bin (centered at 10‐m depth). If only radar data exceeding a quality threshold are considered, the rms difference in the radial currents measured by the two techniques is 27 cm s−1. This difference most likely reflects the different sampling employed by these instruments, as well as unremoved ionospheric biases in the radar measurements.