Dataset: High Frequency Radar (HFR) observed surface currents at Palmer Deep Canyon in the coastal ocean west of the Antarctic Peninsula in 2020

Final no updates expectedDOI: 10.26008/1912/bco-dmo.917884.1Version 1 (2024-01-08)Dataset Type:Other Field Results

Principal Investigator: Joshua Kohut (Rutgers University)

Co-Principal Investigator: John M. Klinck (Old Dominion University)

Co-Principal Investigator: Matthew Oliver (University of Delaware)

Co-Principal Investigator: Hank Statscewich (Rutgers University)

Student: Jacquelyn Veatch (Rutgers University)

BCO-DMO Data Manager: Amber D. York (Woods Hole Oceanographic Institution)


Project: Collaborative Research: Physical Mechanisms Driving Food Web Focusing in Antarctic Biological Hotspots (Project SWARM)


Abstract

HFRs use doppler-shifted radio waves backscattered off the ocean surface to observe surface velocity. Signals are transmitted and received by an HFR antenna, and Bragg peaks in the measured Doppler spectra are used to calculate radial components of the surface velocity (Barrick et al., 1977). Measured radial components of the surface ocean velocity are directed towards the HFR antenna with a range resolution of 500 m horizontally and 5 degrees in azimuth. Radial components from the three HFR sta...

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Methods for this High Frequency Radar data can be found in Veatch et al. (2024) currently in revision.

High Frequency Radars use doppler-shifted radio waves backscattered off t 181 he ocean surface to observe surface velocity. Signals are transmitted and received by an HFR antenna, and Bragg peaks in the measured Doppler spectra are used to calculate radial components of the surface velocity (Barrick, Evans, and Weber 1977). Measured radial components of the surface ocean velocity are directed towards the HFR antenna with a range resolution of 500 m horizontally and 5 degrees in azimuth. Radial components from the three HFR stations are added together to construct magnitude and direction of surface current velocities using an optimal interpolation algorithm (Kohut, Roarty, and Glenn 2006) providing hourly maps of surface currents at 1km spatial resolution.

The three HFR sites collected hourly radial maps of ocean surface current component vectors over our study area, covering about 1,500 km2 more than 80% of the time. Gaps within the 80% coverage area of the HFR maps were filled using a rigorous HFR-specific method (Fredj et al. 2016).

Instruments

The three-site network included two remote locations on the Wauwermans and Joubin islands operated at a center frequency of 25 MHz and a third site at Palmer Station operated at 13 MHz. The two remote sites located beyond existing power grids used Remote Power Modules (RPMs) constructed on site. These RPMs used small-scale micro wind turbines and a photovoltaic array with a 96-hour battery backup to generate the power required by the HFR (Kohut 2014; Statscewich and Weingartner 2011). Redundancies were built in to the RPMs, including wind charging/resistive loads, solar energy, and independent battery banks. Redundancies ensured that the system could autonomously adjust power source if one component failed. RPMs consisted of a single water-tight enclosure that housed all power generating equipment and communication gear. HFR and RPMs were assembled at remote sites using shipboard support and zodiacs that lightered materials to shore. Line of sight radio modems (Freewave) were used to communicate between the two remote sites and a central site collocated with the Palmer Station HFR site. Communication equipment enabled remote site diagnostics and maintenance as well as real-time data communication.


Related Datasets

IsRelatedTo

Dataset: Relative Particle Density
Relationship Description: The "High Frequency Radar, Palmer Deep" dataset provided the observed surface currents (velocity field) from which these Relative Particle Density were calculated from.
Veatch, J., Klinck, J. M., Oliver, M., Kohut, J., Statscewich, H. (2024) Relative Particle Density (RPD) calculations using High Frequency Radar (HFR) observed surface currents around Palmer Deep Canyon from January to March of 2020. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2024-01-08 doi:10.26008/1912/bco-dmo.917926.1
IsRelatedTo

Dataset: Finite Time Lyapunov Exponent Results, Calculated from High Frequency Radar Observed Surface Currents
Relationship Description: The "High Frequency Radar, Palmer Deep" dataset provided the observed surface currents (velocity field) from which these Finite Time Lyapunov Exponent Results were calculated from.
Veatch, J., Klinck, J. M., Oliver, M., Statscewich, H., Kohut, J. (2024) Results from Finite Time Lyapunov Exponent calculations using High Frequency Radar observed surface currents around Palmer Deep Canyon from January to March of 2020. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2024-01-08 doi:10.26008/1912/bco-dmo.917914.1

Related Publications

Results

Veatch, J., Kohut, J., Oliver, M., Statscewich, H., Fredj, E. (2024) Quantifying the role of sub-mesoscale lagrangian transport features in the concentration of plankton in a coastal system ICES JMS, In Revision.
Methods

Barrick, D. E., Evans, M. W., & Weber, B. L. (1977). Ocean Surface Currents Mapped by Radar. Science, 198(4313), 138–144. https://doi.org/10.1126/science.198.4313.138
Methods

Fredj, E., Roarty, H., Kohut, J., Smith, M., & Glenn, S. (2016). Gap Filling of the Coastal Ocean Surface Currents from HFR Data: Application to the Mid-Atlantic Bight HFR Network. Journal of Atmospheric and Oceanic Technology, 33(6), 1097–1111. https://doi.org/10.1175/jtech-d-15-0056.1
Methods

Kohut, J. T., Roarty, H. J., & Glenn, S. M. (2006). Characterizing Observed Environmental Variability With HF Doppler Radar Surface Current Mappers and Acoustic Doppler Current Profilers: Environmental Variability in the Coastal Ocean. IEEE Journal of Oceanic Engineering, 31(4), 876–884. https://doi.org/10.1109/joe.2006.886095
Methods

Kohut, J., Bernard, K., Fraser, W., Oliver, M. J., Statscewich, H., Winsor, P., & Miles, T. (2014). Studying the Impacts of Local Oceanographic Processes on Adélie Penguin Foraging Ecology. Marine Technology Society Journal, 48(5), 25–34. https://doi.org/10.4031/mtsj.48.5.10