HF Radar Data Research Articles

Variations in Flow Patterns in the Northern Taiwan Strait Observed by Satellite-Tracked Drifters

This study investigates the variations in flow patterns in the northern Taiwan Strait in summer using high-frequency (HF) radar measurements, satellite-tracked drifter trajectories and numerical models. There is an obvious interaction between intra-diurnal tides and ocean currents in northwestern Taiwan. When the tide changes between high tide and low tide, the change in direction of the nearshore flow occurs before the change in the offshore flow. Drifter trajectories show that there are three different drifting paths in the Taiwan Strait in summer. One path is along the west coast of Taiwan from the southwest coast to the northeast coast. Another path is the same as the first one but leads northward to the East China Sea instead of eastward to the northeast coast of Taiwan. The other path exists along the west coast of Taiwan, some distance out, after being deflected by the bottom ridge. The regional ocean modeling system model was used in this study to clarify the influencing factors that lead to these three paths. The results of multiple simulations and HF radar data indicate that the bifurcation of the first two drift paths in northwestern Taiwan is caused by ebb and flood tide transitions. The different routes of the latter two paths are due to the significant speed difference between the nearshore current and the offshore current approximately 45 km from the coast.

Statistical Study of Seasonal and Solar Activity Dependence of Nighttime MSTIDs Occurrence Using the SuperDARN Hokkaido Pair of Radars

AbstractWe conduct a statistical analysis on nighttime medium‐scale traveling ionospheric disturbances (MSTIDs) using the Super Dual Auroral Radar Network (SuperDARN) Hokkaido East (43.53°N, 143.61°E) high‐frequency (HF) radar data from 2009 to 2019 and the SuperDARN Hokkaido West (43.54°N, 143.61°E) HF radar data from 2016 to 2019. We analyze the line‐of‐sight Doppler velocity data, corresponding to the magnitude of the polarization electric field associated with nighttime MSTIDs. We find that the propagation direction of the nighttime MSTIDs is mainly southwestward and rotates clockwise with progressing local time. In addition, we identify a negative correlation between the nighttime MSTIDs amplitude and the solar F10.7 index. These tendencies can be explained by the Perkins instability, which is considered to be associated with the growth of nighttime MSTIDs. This study is the first to find the solar activity dependence of the polarization electric field fluctuations associated with the nighttime MSTIDs.

Direction Finding and Likelihood Ratio Detection for Oceanographic HF Radars

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.

Wind Speed Extraction From First-Order Sea Echoes Using a Small-Aperture Multifrequency High-Frequency Radar

Wind speed inversion is a challenging work in the field of ocean surface remote sensing with high-frequency (HF) radars. Recently, the wind speed inversion method based on the first-order HF radar sea echoes attracts much attention. However, most methods, which use radar data at a fixed operating frequency, provide a limited range for wind speed measurement. To overcome the drawback, a wind speed inversion method based on radar data collected with a multifrequency HF radar is proposed. This new method first fits the relationship between the wind speed and the power of the broad-beam first-order HF radar sea echoes and then combines the fit models with the multifrequency HF radar data to estimate wind speed. The proposed method makes use of the information contained in the first-order sea echoes of various operating frequencies so as to improve the performance of the wind speed measurements. Finally, a comparison between radar-estimated and anemometer-measured wind speeds is made to validate the proposed method. Compared with the anemometer data, the wind speeds estimated by the proposed method have a root-mean-square error (RMSE) of 2.27 m/s.

Characteristics of Sea Surface Current in the Bali Strait, Indonesia using HF Radar and Its Utilization in Safety Navigation

This paper was done by using the HF Radar data from 2018-2019 to study the characteristics of Sea Surface Current (SSC) in the Bali Strait. The data processing method was done by calculating the speed and SSC direction of the zonal and meridional components. Furthermore, SSC analysis was performed every hour and month by calculating the average of all data at the same hour and month. It was found that the unique SSC pattern in the Bali Strait occurred on the western side of Bali Island and the eastern side of Java Island. On the west side of the Bali Island, there was a decrease in SSC speed at 0.00-7.00 and 13.00-18.00, as well as a two-fold increase at 8.00-12.00 and 19.00-2.00, both of which were in a fluctuating speed range from 0-140 cm s-1 in the direction of dominant towards the south. On the eastern side of Java Island, SSC speed ranges from 0 to 40 cm s-1 all the time with the dominant direction heading from east to southeast. The monthly SSC pattern was also seen more clearly in this study, meanwhile during December-March the SSC rate was lower than during June-September, ranging from 0 to 20 cm s-1 and from 40 to 140 cm s-1, respectively. Furthermore, the two SSC patterns above can be simplified into two periods, namely periods of relaxation and agitation. This study also applies the device to ship accidents that occurred in the Bali Strait as case studies.

Measurement and Analysis of Ocean Current using High- Frequency (HF) Radar Observation in the Bali Strait

High-Frequency (HF) Radar is an instrument using radio waves to measure ocean currents and waves remotely. This technology has many advantages, including has unprecedented spatial and temporal resolution, can operate in any weather condition, and is not dangerous for the environment. However, HF Radar's research is still limited in Indonesia. This research aimed to analyze the tidal and residual current in the Bali Strait in July 2020. Radial velocity from two HF Radar sites is combined to obtain the total currents. Current data from HF Radar were compared with Acoustic Doppler Current Profiler (ADCP) data to investigate its accuracy. Surface current data were analyzed using harmonic analysis to separate tidal and residual currents. Comparison between HF Radar and ADCP data are in good agreement for meridional current with a very high correlation of 0.813 and a small RMSE value of 0.22 m/s. Harmonic analysis shows that the dominant currents are tidal currents. The current direction was northward (southward) at flood (ebb), with maximum northward (southward) velocities are 2.17 m/s (2.97 m/s), respectively. The residual current has a random pattern, slightly faster northward than southward, and has similar spectral with the wind.

First multi-year assessment of Sentinel-1 radial velocity products using HF radar currents in a coastal environment

Direct sensing of total ocean surface currents with microwave Doppler signals is a growing topic of interest for oceanography, with relevance to several new ocean mission concepts proposed in recent years. Since 2014, the spaceborne C-band SAR instruments of the Copernicus Sentinel-1 (S1) mission routinely acquire microwave Doppler data, distributed to users through operational S1 Level-2 ocean radial velocity (L2 OCN RVL) products. S1 L2 RVL data could produce high-resolution maps of ocean surface currents that would benefit ocean observing and modelling, particularly in coastal regions. However, uncorrected platform effects and instrument anomalies continue to impact S1 RVL data and prevent direct exploitation.In this paper, a simple empirical method is proposed to calibrate and correct operational S1 L2 RVL products and retrieve two-dimensional maps of surface currents in the radar line-of-sight. The study focuses on the German Bight where wind, wave and current data from marine stations and an HF radar instrumented site provide comprehensive means to evaluate S1 retrieved currents. Analyses are deliberately limited to Sentinel-1A (S1A) ascending passes to focus on one single instrument and fixed SAR viewing geometry. The final dataset comprises 78 separate S1A acquisitions over 2.5 years, of which 56 are matched with collocated HF radar data. The empirical corrections bring significant improvements to S1A RVL data, producing higher quality estimates and much better agreement with HF radar radial currents.Comparative evaluation of S1A against HF radar currents for different WASV corrections reveal that best results are obtained in this region when computing the WASV with sea state rather than wind vector input. Accounting for sea state produces S1 radial currents with a precision (std of the difference) around 0.3m/s at ∼1km resolution. Precision improves to ∼0.24m/s when averaging over 21×27km2, with correlations with HF radar data reaching up to 0.93. Evidence of wind-current interactions when tides and wind align and short fetch conditions call for further research with more satellite data and other sites to better understand and correct the WASV in coastal regions.Finally, 1km resolution maps of climatological S1A radial currents obtained over 2.5 years reveal strong coastal jets and fine scale details of the coastal circulation that closely match the known bathymetry and deep-water coastal channels in this region. The wealth of oceanographic information in corrected S1 RVL data is encouraging for Doppler oceanography from space and its application to observing small scale ocean dynamics, atmosphere and ocean vertical exchanges and marine ecosystem response to environmental change.

An Analysis of Surface Ocean Currents from HF Radar Measurements in the Bali Strait and the Flores Sea, Indonesia

<p class='IJASEITAbtract'>Analyze Surface Ocean Currents (SOCs) with one year of HF Radar data (2018-2019) for each season to determine the characteristics of the SOC direction and speed of the crossing route and its control factors carried out in the Bali Strait and the Flores Sea. Method of data analysis by computing the SOC speed and direction of the zonal and meridional components. The results showed that the SOC pattern in the Bali Strait affects the season where its speed in the DJF season is lower than the JJA season. Moreover, the SOC direction in the Bali Strait is dominant towards the south due to the influence of bathymetry. Meanwhile, the SOC pattern in the Flores Sea has a random pattern every season for the influence of topography in the form of small islands that influence the SOC dominant pattern. Furthermore, the SOC characteristics on the Bali Strait crossing route throughout the month are divided into two patterns: random on the eastern side of East Java Island and dominant towards the south on the west side of Bali Island with a maximum speed of 83 cm/s. Meanwhile, the crossing route in the Flores Sea is random, with a maximum speed of 32 cm/s. Whereas, based on the normal cross-correlation method, the SOC control factors in the Bali Strait tend to be influenced by tides, while the factors in the Flores Sea are less influential based on the distribution of zonal and meridional currents of HF Radar.

Optimisation of Parameters in a German Bight Circulation Model by 4DVAR Assimilation of Current and Water Level Observations

Uncertain parameters in a 3D barotropic circulation model of the German Bight are estimated with a variational optimisation approach. Surface current measurements from a high frequency (HF) radar are used in combination with acoustic Doppler current profiler (ADCP) and tide gauge observations as input for a 4DVAR assimilation scheme. The required cost function gradients are estimated using an adjoint model code. The focus of the study is on systematic errors of the model with the control vector including parameters of the bathymetry, bottom roughness, open boundary forcing, meteorological forcing as well as the turbulence model. The model uses the same bathymetry, open boundary forcing, and metereological forcing as the operational model run at the Federal Maritime and Hydrographic Agency (BSH). The baroclinic BSH model is used as a reference to put the performance of the optimised model into perspective. It is shown that the optimised model has better agreement with HF radar data and tide gauge observations both within the fortnight training period and the test period 1 month later. Current profile measurements taken at two platforms indicate that both models have comparable error magnitudes at those locations. The optimised model was also compared with independent drifter data. In this case, drifter simulations based on the BSH model and the respective operational drift model including some surface wave effects were used as a reference. Again, these comparison showed very similar results overall, with some larger errors of the tuned model in very shallow areas, where no observations were used for the tuning and surface wave effects, which are only explicitly considered in the BSH model, play a more important role. The tuned model seems to be slightly more dissipative than the BSH model with more energy entering through the western boundary and less energy leaving toward the north. It also became evident that the 4DVAR cost function minimisation process is complicated by momentum advection, which leads to non-differentiable dependencies of the model with respect to the control vector. It turned out that the omission of momentum advection in the adjoint code still leads to robust estimates of descent directions.

Assessment of NEMO simulated surface current with HF radar along Andhra Pradesh coast

Simulating upper layer of Bay of Bengal through three-dimensional ocean circulation models is a challenging task. In this study, the surface current from the Nucleus European Modelling of Ocean (NEMO) based global ocean assimilation system is assessed against the high frequency (HF) radar data along the Andhra Pradesh coast on a daily scale during southwest monsoon 2016. The temporal variation of NEMO simulated surface current with HF radar data shows that the NEMO model captures the zonal current better than the meridional current. Both NEMO and HF radar show that the mean surface current average over latitude (15.8°–16.3°N) is westward for zonal surface current and southward for meridional current with maximum at 40–60 km away from the coast. Further, the monthly mean HF radar derived surface current indicates the strong south-westward flow of surface current dominated during July 2016 with speed more than 50 cm/s which is also well simulated by NEMO analysis. It also captures the cold core eddy during 15–25 July 2016 with very small north-eastward shift with respect to HF radar. The scatter plot of collocated surface zonal and meridional current average over the box (81.5–82.5°E; 15.5–16.5°N) clearly shows that NEMO analysis has the correlation of more than 0.5 for both zonal and meridional current.

High-Frequency Radar Ocean Current Mapping at Rapid Scale With Autoregressive Modeling

In this article, we use an autoregressive (AR) approach combined with a maximum entropy method (MEM) to estimate radial surface currents from coastal high-frequency radar (HFR) complex voltage time-series. The performances of this combined AR-MEM model are investigated with synthetic HFR data and compared with the classical Doppler spectrum approach. It is shown that AR-MEM drastically improves the quality and the rate of success of the surface current estimation for short integration time. To confirm these numerical results, the same analysis is conducted with an experimental data set acquired with a 16.15-MHz HFR in Toulon. It is found that the AR-MEM technique is able to provide high-quality and high-coverage maps of surface currents even with very short integration time (about 1 min) where the classical spectral approach can only fulfill the quality tests on a sparse coverage. Further useful application of the technique is found in the tracking of surface current at high-temporal resolution. Rapid variations of the surface current at the time scale of the minute are unveiled and shown consistent with an f <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-5/3</sup> decay of turbulent spectra.

Gaps Filling in HF Radar Sea Surface Current Data Using Complex Empirical Orthogonal Functions

The knowledge of speed and direction of coastal ocean currents are critical for carrying out search and rescue at sea, to respond to the hazardous marine oil spills, to estimate the dispersal pattern of pollutants, to issue warnings against tsunamis and cyclones etc. Such operations need uninterrupted observational data of sea surface currents over wide area with high spatial and temporal resolution. The High frequency (HF) radars installed at the shore, sense the surface of ocean using electromagnetic waves, and provide the speed and direction of ocean currents over a specific spatial domain at high temporal resolution. However, the frequent gaps in the data are a concern for its usage. The gaps arise due to its dependence on the roughness of the sea other electromagnetic interferences from environment sources and due to data acquisition failures. Hence, it is necessary to fill the gaps for successful usage of HF radar data. The present work describes a method to fill the gaps in the HF radar data using complex empirical orthogonal functions (CEOF). Before filling the missing data, HF radar data is assessed with available observations. The CEOFs are calculated iteratively using singular value decomposition. The number of statistically significant CEOFs required to construct the missing HF radar currents data accurately along the Indian coast are obtained through a cross-validation procedure. The proposed method is first validated for various rates of synthetic data gaps created in synthetic data and in model derived cyclonic wind fields and comparisons are illustrated, the reconstructed data and the original data are in good match

On the vector plasma drift measurements over Equatorial Ionosphere using HF Doppler radar – A brief review

Background/ Objective: University of Kerala, Thiruvananthapuram ( 8.5◦N ,77◦E, dip 0.5◦N ) in India had a lively Space Physics research group since 1982, owing to proximity of the location to the geomagnetic dip equator. In 1982, a single frequency HF Doppler radar, operational at 5.5 MHz was installed in the University which provided many invaluable scientific results regarding the night time ionospheric F region. In 2003, it was upgraded to a new multifrequency HF Doppler Radar thereby enabling detailed examination of vertical plasma drift measurements at three different altitudes of F-region, in a nearsimultaneous manner. Methods: This study is basically a brief review of major results of F –region electrodynamics over Indian longitudinal sector obtained exclusively using HF Radar data. Findings: This review brings all the scientific results obtained using HF Radar about vertical drift studies over equatorial latitude and found that nearly about 40 research papers have been published in reputed national and international journals using the Radar data. Novelty: In a complementary point of view, this gives an opportunity to revisit and remember the important contributions of many of the earlier Indian scientists, who enriched ionospheric science using this unique facility. Keywords: HF Doppler Radar; Ionosphere; Vertical drift

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

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.

Interference Patterns Observed in the Indian Coastal Ocean Radar Network

Suseentharan, V.; Arunraj, K.S.; Jena, B.K.; Ramana Murthy, M.V., and Tushar K., 2020. Interference patterns observed in the Indian coastal ocean radar network. In: Sheela Nair, L.; Prakash, T.N.; Padmalal, D., and Kumar Seelam, J. (eds.), Oceanic and Coastal Processes of the Indian Seas. Journal of Coastal Research, Special Issue No. 89, pp. 63-66. Coconut Creek (Florida), ISSN 0749-0208.Indian Coastal Ocean Radar Network (ICORN) runs 10 shore- based High-Frequency Radar (HFR) systems for measuring 2D surface currents and waves, which cover four coastal states and the Andaman Islands. These coastal remote sensing systems are subjected to various interferences. This paper discusses the periodic interference patterns observed in the network and the possible causes for these patterns. The radial data file size from the HFR sites is used as a proxy to identify these patterns. Similarly, vertical Total Electron Content (TEC) is used to identify the influence of Ionosphere on HFR data. The Fast Fourier Transform (FFT) on these data sets showed a strong correlation between HFR and TEC data at diurnal and semi-diurnal frequencies as well as at 8, 6 and 4.8 hours periods. However; low pass filter HFR data does not show any seasonal or intra-seasonal pattern, except at the Andaman Islands, where it showed fortnightly and monthly patterns.

Spatial and Temporal Evolution of Different‐Scale Ionospheric Irregularities in Central and East Siberia During the 27–28 May 2017 Geomagnetic Storm

AbstractWe present a multi‐instrumental study of ionospheric irregularities of different scales (from tens of centimeters to few kilometers) observed over the Central and East Siberia, Russia, during a moderate‐to‐strong geomagnetic storm on 27–28 May 2017. From high‐frequency (HF) and ultrahigh‐frequency (UHF) radar data, we observed an intense auroral backscatter developed right after the initial phase of the geomagnetic storm. Additionally, we examined variations of Global Positioning System (GPS)‐based ROT (rate of TEC changes, where TEC is total electron content) for available GPS receivers in the region. Ionosondes, HF, and UHF radar data exhibited a presence of intense multi‐scale ionospheric irregularities. We revealed a correlation between different‐scale Auroral/Farley‐Buneman ionospheric irregularities of the E layer during the geomagnetic storm. The combined analysis showed that an area of intense irregularities is well connected and located slightly equatorward to field‐aligned currents (FACs) and auroral oval at different stages of the geomagnetic storm. An increase and equatorward displacement of Region 1 (R1)/Region 2 (R2) FACs leads to appearance and equatorward expansion of ionospheric irregularities. During downward (upward) R1 FAC and upward (downward) R2 FAC, the eastward and upward (westward and downward) E × B drift of ionospheric irregularities occurred. Simultaneous disappearance of UHF/HF auroral backscatter and GPS ROT decrease occurred during a prolonged near noon reversal of R1 and R2 FAC directions that accompanied by R1/R2 FAC degradation and disappearance of high‐energy auroral precipitation.

Best Practices on High Frequency Radar Deployment and Operation for Ocean Current Measurement

High Frequency Radar (HFR) technology refers to land based remote sensing instruments capable of measuring surface currents and ocean waves at ranges up to 200 km or more. HFR technology is widely acknowledged as a cost-efficient tool to monitor coastal regions and has potential use to monitor coastal regions all over the world. Globally, the number of HFR stations is steadily increasing. Regional networks provide real-time data in support of operational activities such as search and rescue operations, fast response in case of maritime accidents and spill of pollutants, and resource management. Each operator needs a general understanding of the working principles in order to ensure that instruments are managed properly. A set of harmonized quality assurance and quality control procedures is recommended, along with an effective approach to HFR data discovery and dissemination, to provide high quality measurements to the end users. Different documents providing best practices for operation and maintenance have emerged in the past years. They are oriented either to Direction Finding (DF) or Beam Forming (BF) systems, or to specific manufacturer’s radar systems. The main objective of this paper is to offer a comprehensive “Best Practices” document in an effort of ensuring consistency between different deployments and harmonized operations of HFR systems. This, regardless of system manufacturer, antenna design and setup. A homogeneous approach is given when possible, general concepts and definitions are introduced in order to provide a framework for both data processing and management steps. Examples are also given from the European HFR users with focus on Near Real Time data flow suitable for operational services.

Measuring the Directional Ocean Spectrum from Simulated Bistatic HF Radar Data

HF radars are becoming important components of coastal operational monitoring systems particularly for currents and mostly using monostatic radar systems where the transmit and receive antennas are colocated. A bistatic configuration, where the transmit antenna is separated from the receive antennas, offers some advantages and has been used for current measurement. Currents are measured using the Doppler shift from ocean waves which are Bragg-matched to the radio signal. Obtaining a wave measurement is more complicated. In this paper, the theoretical basis for bistatic wave measurement with a phased-array HF radar is reviewed and clarified. Simulations of monostatic and bistatic radar data have been made using wave models and wave spectral data. The Seaview monostatic inversion method for waves, currents and winds has been modified to allow for a bistatic configuration and has been applied to the simulated data for two receive sites. Comparisons of current and wave parameters and of wave spectra are presented. The results are encouraging, although the monostatic results are more accurate. Large bistatic angles seem to reduce the accuracy of the derived oceanographic measurements, although directional spectra match well over most of the frequency range.

Two New Methods for the Extraction of Significant Wave Heights From Received HF-Radar Time Series

For close to half a century, the usual procedure to determine ocean surface information from HF-radar data has been to first form the Doppler spectrum from the received time series, and then process the result to extract important wave parameters, such as significant wave height, primary wave period, principal wave direction, or even the full directional ocean wave spectrum. In the current work, we bypass the calculation of the Doppler spectrum and still calculate the significant wave height ( $H_{s}$ ) from the received radar data using two related proposed methods. The first calculates $H_{s}$ from the variances of the short-time Fourier transform coefficients of the first-order received field. The second uses the estimated variance of the received electrical field signal to determine $H_{s}$ . Both methods require an initial external calibration stage, which can be either performed analytically from the data or by deploying a wave buoy. The validity of the proposed methods is tested with field data from which a significant correlation with the values of $H_{s}$ measured independently by a wave buoy is obtained.

Sea Ice Observation With Oceanographic HF Radar

High-frequency (HF) ocean radar has the potential to observe sea ice, but this application has not been thoroughly investigated. In this article, we explore sea ice observation with HF radar (HFR) and develop a corresponding signal processing procedure. We derived sea ice radial velocities from raw HFR data and determined angular positions using the MUltiple SIgnal Classification (MUSIC) algorithm. Sea ice velocities were evaluated by comparison with measurements from moored acoustic Doppler current profilers (ADCPs) and a drifting buoy. The root-mean-square (rms) differences between the sea ice velocities obtained by HFR and the ADCPs decreased with increasing radar signal-to-noise ratio (SNR), implying that a high SNR was associated with accurate measurement of sea ice velocity. These results agree with previous validations of HFR ocean current observations. The sea ice pattern mapped by HFR is consistent with the simultaneous C-band microwave radar observations. In particular, the HFR captured the approach of the sea ice edge toward the coast. Sharp attenuation of the HF signal over high concentration sea ice resulted in missing and/or low-SNR data at ranges beyond the front edge of pack ice, in qualitative agreement with model estimates of attenuation.