Surface current variability in the Keum River Estuary (South Korea) during summer 2002 as observed by high-frequency radar and coastal monitoring buoy

2007 ◽  
Vol 27 (1) ◽  
pp. 43-63 ◽  
Author(s):  
Young-Tae Son ◽  
Sang-Ho Lee ◽  
Chang-Soo Kim ◽  
Jae Chul Lee ◽  
Gwang-Hee Lee
Keyword(s):  
South Korea ◽  
High Frequency ◽  
River Estuary ◽  
Surface Current ◽  
Coastal Monitoring ◽  
High Frequency Radar ◽  
Keum River ◽  
Monitoring Buoy

The Integrated Ocean Observing System High-Frequency Radar Network: Status and Local, Regional, and National Applications

2010 ◽  
Vol 44 (6) ◽  
pp. 122-132 ◽  
Author(s):  
Jack Harlan ◽  
Eric Terrill ◽  
Lisa Hazard ◽  
Carolyn Keen ◽  
Donald Barrick ◽  
...  
Keyword(s):  
High Frequency ◽  
Surface Current ◽  
Water Quality Monitoring ◽  
Velocity Fields ◽  
Common Source ◽  
Integrated Network ◽  
High Frequency Radar ◽  
Radar Network ◽  
Network Status ◽  
Ocean Observing

AbstractA national high-frequency radar network has been created over the past 20 years or so that provides hourly 2-D ocean surface current velocity fields in near real time from a few kilometers offshore out to approximately 200 km. This preoperational network is made up of more than 100 radars from 30 different institutions. The Integrated Ocean Observing System efforts have supported the standards-based ingest and delivery of these velocity fields to a number of applications such as coastal search and rescue, oil spill response, water quality monitoring, and safe and efficient marine navigation. Thus, regardless of the operating institution or location of the radar systems, emergency response managers, and other users, can rely on a common source and means of obtaining and using the data. Details of the history, the physics, and the application of high-frequency radar are discussed with successes of the integrated network highlighted.

scholarly journals Investigations into Synoptic Spatiotemporal Characteristics of Coastal Upper Ocean Circulation Using High Frequency Radar Data and Model Output

2020 ◽  
Vol 12 (17) ◽  
pp. 2841
Author(s):  
Lei Ren ◽  
Nanyang Chu ◽  
Zhan Hu ◽  
Michael Hartnett
Keyword(s):  
Ocean Circulation ◽  
High Frequency ◽  
Numerical Models ◽  
Surface Current ◽  
Flow Fields ◽  
Surface Flow ◽  
Self Organizing Map ◽  
Eof Analysis ◽  
Surface Flows ◽  
High Frequency Radar

Numerical models and remote sensing observation systems such as radars are useful for providing information on surface flows for coastal areas. Evaluation of their performance and extracting synoptic characteristics are challenging and important tasks. This research aims to investigate synoptic characteristics of surface flow fields through undertaking a detailed analysis of model results and high frequency radar (HFR) data using self-organizing map (SOM) and empirical orthogonal function (EOF) analysis. A dataset of surface flow fields over thirteen days from these two sources was used. A SOM topology map of size 4 × 3 was developed to explore spatial patterns of surface flows. Additionally, comparisons of surface flow patterns between SOM and EOF analysis were carried out. Results illustrate that both SOM and EOF analysis methods are valuable tools for extracting characteristic surface current patterns. Comparisons indicated that the SOM technique displays synoptic characteristics of surface flow fields in a more detailed way than EOF analysis. Extracted synoptic surface current patterns are useful in a variety of applications, such as oil spill treatment and search and rescue. This research provides an approach to using powerful tools to diagnose ocean processes from different aspects. Moreover, it is of great significance to assess SOM as a potential forecasting tool for coastal surface currents.

Measurements of upper ocean surface current shear with high-frequency radar

1996 ◽  
Vol 101 (C12) ◽  
pp. 28615-28625 ◽  
Author(s):  
Daniel M. Fernandez ◽  
John F. Vesecky ◽  
Calvin C. Teague
Keyword(s):  
High Frequency ◽  
Surface Current ◽  
Ocean Surface ◽  
Upper Ocean ◽  
High Frequency Radar ◽  
Ocean Surface Current

scholarly journals Interoperability of Direction-Finding and Beam-Forming High-Frequency Radar Systems: An Example from the Australian High-Frequency Ocean Radar Network

2019 ◽  
Vol 11 (3) ◽  
pp. 291 ◽  
Author(s):  
Simone Cosoli ◽  
Stuart de Vos
Keyword(s):  
High Frequency ◽  
Direction Finding ◽  
Coastal Monitoring ◽  
Vector Correlation ◽  
High Frequency Radar ◽  
Pointing Errors ◽  
Radar Systems ◽  
Radar Network ◽  
Vector Correlations ◽  
Ocean Radar

Direction-finding SeaSonde (4.463 MHz; 5.2625 MHz) and phased-array WEllen RAdar WERA (9.33 MHz; 13.5 MHz) High-frequency radar (HFR) systems are routinely operated in Australia for scientific research, operational modeling, coastal monitoring, fisheries, and other applications. Coverage of WERA and SeaSonde HFRs in Western Australia overlap. Comparisons with subsurface currents show that both HFR types agree well with current meter records. Correlation (R), root-mean-squares differences (RMSDs), and mean bias (bias) for hourly-averaged radial currents range between R = (−0.03, 0.78), RMSD = (9.2, 30.3) cm/s, and bias = (−5.2, 5.2) cm/s for WERAs; and R = (0.1, 0.76), RMSD = (17.4, 33.6) cm/s, bias = (0.03, 0.36) cm/s for SeaSonde HFRs. Pointing errors (θ) are in the range θ = (1°, 21°) for SeaSonde HFRs, and θ = (3°, 8°) for WERA HFRs. For WERA HFR current components, comparison metrics are RU = (−0.12, 0.86), RMSDU = (12.3, 15.7) cm/s, biasU = (−5.1, −0.5) cm/s; and, RV = (0.61, 0.86), RMSDV = (15.4, 21.1) cm/s, and biasV = (−0.5, 9.6) cm/s for the zonal (u) and the meridional (v) components. Magnitude and phase angle for the vector correlation are ρ = (0.58, 0.86), φ = (−10°, 28°). Good match was found in a direct comparison of SeaSonde and WERA HFR currents in their overlap (ρ = (0.19, 0.59), φ = (−4°, +54°)). Comparison metrics at the mooring slightly decrease when SeaSonde HFR radials are combined with WERA HFR: scalar (vector) correlations for RU, V, (ρ) are in the range RU = (−0.20, 0.83), RV = (0.39, 0.79), ρ = (0.47, 0.72). When directly compared over the same grid, however, vectors from WERA HFR radials and vectors from merged SeaSonde–WERA show RU (RV) exceeding 0.9 (0.7) within the HFR grid. Despite the intrinsic differences between the two types of radars used here, findings show that different HFR genres can be successfully merged, thus increasing current mapping capability of the existing HFR networks, and minimising operational downtime, however at a likely cost of slightly decreased data quality.

Optimizing and Validating High-Frequency Radar Surface Current Measurements in the Mona Passage

2011 ◽  
Vol 45 (3) ◽  
pp. 49-58 ◽  
Author(s):  
Jorge E. Corredor ◽  
Andre Amador ◽  
Miguel Canals ◽  
Samuel Rivera ◽  
Jorge E. Capella ◽  
...  
Keyword(s):  
High Frequency ◽  
Surface Current ◽  
Acoustic Doppler Current Profiler ◽  
The United States ◽  
Repeated Measurements ◽  
Surface Velocity ◽  
High Frequency Radar ◽  
Detection And Tracking ◽  
Current Profiler ◽  
Mona Island

AbstractThe Mona Passage is a major shipping lane to the Panama Canal and a key route for illegal traffic into the United States. We have emplaced two high-frequency radar (HFR) stations on the west coast of Puerto Rico intended to allow mapping of the ocean surface velocity field of the eastern Mona Passage and to explore its performance in vessel detection and tracking. The array provides coverage of the southeastern quadrant of the Passage extending west to Mona Island and north to Rincon. Hourly results are posted online in near-real time. To optimize our results, we twice measured the antenna beam patterns and applied these corrections to the resulting radial returns. To assess the basic capability of the Mona Passage HFR array to measure surface currents in this tropical environment, we undertook validation measurements, including repeated deployment of Lagrangian drifters, deployment of an acoustic Doppler current profiler, and comparison with modeled tidal currents. Our experimental measurements showed good agreement to both modeled and in situ data lending confidence to the area-wide surface current maps generated by this system. Repeated measurements showed limited temporal variability of antenna distortion patterns, demonstrating that these are in large part the product of the surrounding environment. Comparison between a numerical particle tracking algorithm and experimental Lagrangian trajectories showed mixed results, with better agreement during periods of low intrahour variability in current direction than during periods of rapid tidal reversal.

scholarly journals Surface currents in the Alderney Race from high-frequency radar measurements and three-dimensional modelling

2020 ◽  
Vol 378 (2178) ◽  
pp. 20190494 ◽  
Author(s):  
G. Lopez ◽  
A.-C. Bennis ◽  
Y. Barbin ◽  
A. Sentchev ◽  
L. Benoit ◽  
...  
Keyword(s):  
High Frequency ◽  
Current Model ◽  
Three Dimensional ◽  
Surface Current ◽  
Tidal Energy ◽  
Phase Lag ◽  
Surface Currents ◽  
Entire Study ◽  
High Frequency Radar ◽  
Radar Measurements

Two weeks of high-frequency radar measurements collected at the Alderney Race are compared with the results of a three-dimensional fully coupled wave–current model. Spatial current measurements are rare in this site, otherwise well investigated through modelling. Thus, the radar measurements offer a unique opportunity to examine the spatial reliability of numerical results, and can help to improve our understanding of the complex currents in the area. Comparison of observed and modelled surface current velocities showed a good agreement between the methods, represented by root mean squared errors ranging from 14 to 40 cm s −1 and from 18 to 60 cm s −1 during neap and spring tides, respectively. Maximum errors were found in shallow regions with consistently high current velocities, represented by mean neap and spring magnitudes of 1.25 m s −1 and 2.7 m s −1 , respectively. Part of the differences between modelled and observed surface currents in these areas are thought to derive from limitations in the k-epsilon turbulence model used to simulate vertical mixing, when the horizontal turbulent transport is high. In addition, radar radial currents showed increased variance over the same regions, and might also be contributing to the discrepancies found. Correlation analyses yielded magnitudes above 0.95 over the entire study area, with better agreement during spring than during neap tides, probably because of an increase in the phase lag between radar and model velocities during the latter. This article is part of the theme issue ‘New insights on tidal dynamics and tidal energy harvesting in the Alderney Race’.

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