Search Results (61)

This data descriptor presents the HF radar and drifter datasets, along with the methods used to process and apply them in a previously published study on the validation of surface current measurements in a region characterized by highly variable coastal dynamics. The data were collected in the framework of a large-scale Lagrangian experiment, which included extensive drifter deployment and the generation of virtual trajectories based on HF radar-derived flow fields. Both Eulerian and Lagrangian approaches were used to assess radar performance through correlation and RMSE metrics, with additional refinement achieved via Kriging interpolation. The validation results, published in Remote Sensing, demonstrated good agreement between HF radar and drifter observations, particularly when quality control parameters were optimized. The datasets and associated methodologies described here support ongoing efforts to enhance HF radar tuning strategies and improve surface current monitoring in complex marine environments. Full article

High-frequency (HF) ocean radars have become essential tools for monitoring surface currents, offering real-time, wide-area coverage with cost-effectiveness. This study compares the compact CODAR system (MABT, 13 MHz) and the square-array phased-array radar (KNTN, 8 MHz) deployed at Cape Maobitou, Taiwan. Radial velocity measurements were evaluated against data from the Global Drifter Program (GDP), and a quality control (QC) mechanism was applied to improve the data’s reliability. The results indicated that KNTN provides broader spatial coverage, whereas MABT demonstrates higher precision in radial velocity measurements. Baseline velocity comparisons between MABT and KNTN revealed a correlation coefficient of 0.77 and a root-mean-square deviation (RMSD) of 0.23 m/s, which are consistent with typical values reported in previous radar performance evaluations. Drifter-based velocity comparisons showed an initial correlation of 0.49, with an RMSD of 0.43 m/s. In more stable oceanic regions, the correlation improved to 0.81, with the RMSD decreasing to 0.24 m/s. To clarify, this study does not include multiple environmental scenarios but focuses on cases where both radar systems operated simultaneously and where surface drifter data were available within the overlapping area. Comparisons are thus limited by these spatiotemporal conditions. Radar data may still be affected by environmental or human factors, such as ionospheric variations, interference from radio frequency management issues, or inappropriate parameter settings, which could reduce the accuracy and consistency of the observations. International ocean observing programs have developed quality management procedures to enhance data reliability. In Taiwan, the Taiwan Ocean Research Institute (TORI) has established a data quality management mechanism based on international standards for data filtering, noise reduction, and outlier detection, improving the accuracy and stability of radar-derived velocity measurements.To eliminate the effects caused by different center frequencies between MABT and KNTN, this study used the same algorithms and parameter settings as much as possible in all steps, from Doppler spectra processing to radial velocity calculation, ensuring the comparability of the data. This study highlights the strengths and limitations of compact and phased-array HF radar systems based on co-observed cases under consistent operational conditions. Future research should explore multi-frequency radar integration to enhance spatial coverage and measurement precision, improving real-time coastal current monitoring and operational forecasting. Full article

The validation of HF radar systems remains an area with significant scope for advancement, particularly in terms of linking data quality with system operational parameters, fully utilizing the potential of redundant data (e.g., overlapping radial measurements), and accurately capturing the spatiotemporal variability observed by independent devices, such as drifters. In this study, we conducted a large-scale Lagrangian measurement campaign in the Tuscan Archipelago, aimed at validating surface current data from the HF radar network. This radar network, a recent addition to the area, monitors an oceanographic region critical to Mediterranean dynamics. The validation was executed using different approaches: a Eulerian method, comparing the radial velocities measured by radar with drifter-derived velocities along radial directions; a Lagrangian method, contrasting the observed drifter trajectories with the synthetic virtual trajectories generated from radar-based flow fields; and radar-to-radar comparisons with the concurrent utilization of two radars in same point. Through fine-tuning of the quality control parameters and an analysis of the impact of different thresholds of such parameters, we assessed the radar’s ability to capture dynamic processes, identifying both strengths and limitations. Our results not only confirm the utility of HF radar in coastal monitoring but also provide a basis for improving calibration strategies, ultimately supporting more accurate, high-resolution radar observations in complex marine environments. Full article

The near-inertial motion in ocean surface currents directly reflects the energy transported by wind towards the surface layer, playing an important role in climate regulation and energy balance. Previous studies have mainly focused on near inertial oscillations (NIOs) induced by tropical cyclones in the Taiwan Strait, with few reports on near inertial oscillations induced by monsoon onset. Using high-frequency radar observations, we detected an amplification of NIOs induced by the winter monsoon onset. While not as strong as NIOs induced by tropical cyclones, the near-inertial current (NIC) induced by winter monsoon onset in the Taiwan Strait has peak speeds reaching up to 5.2 cm/s and explaining up to 0.7% of non-tidal variance. This study presents observational results of NIOs during three monsoon onset events, and analyzes the impact of winds and temperature changes on NIOs. Temporal and spectral analysis reveals that the monsoon onset is the primary driver behind the formation of NIOs. Results indicate that near-inertial kinetic energy is relatively lower in shallower waters, such as the Taiwan Bank, compared to deeper regions. Furthermore, by integrating the air and sea surface temperature from reanalysis products, we have examined the abrupt changes in sea surface temperature (SST) before and after monsoon onset and their correlation with NIOs. The findings suggest that temperature falling favors the intensification of NICs during monsoon onset, and a lack of significant SST changes precludes the triggering of notable NICs. These insights enhance our understanding of the mechanisms driving NIOs and their roles in seawater mixing. Full article

This study provides a comprehensive analysis and intercomparison of surface currents, for Galveston Bay and Sabine Lake, Texas, obtained from High-Frequency (HF) radars and SCHISM model. We established a methodology based on qualitative and quantitative analyses to compare measured and modeled surface currents. One-month HF radar data, in April 2023, were extracted from the two newly installed HF radar networks comprising two and three HF radar stations at Sabine Lake and Galveston Bay, respectively. The extracted surface current data were compared to corresponding SCHISM-simulated currents to assess the model’s performance in predicting currents. The comparison encompassed qualitative and quantitative assessments by evaluating current vectors and the magnitude of eastward and northward velocity components from both methods. The results showed the ocean current predictive capabilities of SCHISM exemplified by their strong correlations (up to 0.94), high index of agreement (up to 0.95), and low error metrics, during the study period. The disparities in the eastward and northward current measurements across the dates underscore the complex interplay between prevailing winds, bay-ocean interactions, and regional weather patterns. This study sheds light on the intricate dynamics of the surface currents in estuaries and nearshore lakes with the underlying efficacy of both the HF radar and SCHISM surface current determinations. The findings can contribute to advancing the understanding of coastal dynamics and determining the strategies for environmental monitoring and management. Full article

The High-Frequency (HF) radar network has become an effective method for detecting coastal currents. In this study, we confirmed the effectiveness of the HF radar measurements by comparing with the Acoustic Doppler Current Profiler (ADCP) and explore the possibility of assimilating radar data into a regional coastal ocean model. A regional high-resolution model with resolution of 10 m was first built in the Pearl River Estuary (PRE). However, analysis of the Hovmöller diagrams from the model simulations in this study indicated a significant deficiency in representing Near-Inertial Oscillations (NIOs) in the PRE, particularly in the east–west direction, despite including wind fields in the input data, during the week from 3 to 8 August 2022. To overcome the model deficiency, we conducted a set of assimilation experiments and performed sensitivity analyses. The results of sensitivity experiments indicate that the model exhibits a sufficient capacity to replicate NIOs after assimilation, lasting approximately 5–6 days. To further analyze the reasons for the decay in the magnitude of the NIOs, data from the three ADCP stations were compared with model results by applying the momentum equation. The assimilated vertical diffusion term outperforms the unassimilated model in representing NIOs. These findings highlight the importance of the vertical diffusion term for simulating NIOs and the data assimilation in improving the model’s representation of physical processes. Full article

In this study, a novel algorithm to retrieve the current speed along the range direction under extreme sea states is developed from C-band synthetic aperture radar imagery. To this aim, a Sentinel-1 (S-1) dual-polarized synthetic aperture radar (SAR) dataset consisting of 2300 images is collected during 200 tropical cyclones (TCs). The dataset is complemented with collocated wave simulations from the Wavewatch-III (WW3) model and reanalysis currents from the HYbrid Coordinate Ocean Model (HYCOM). The corresponding TC winds are officially released by IFRMER, while the Stokes drift following the wave propagation direction is estimated from the waves simulated by WW3. In this study, first the dependence of wind, Stokes drift, and range current on the Doppler centroid anomaly is investigated, and then the extreme gradient boosting (XGBoost) machine learning model is trained on 87% of the S-1 dataset for range current retrieval purposes. The rest of the dataset is used for testing the retrieval algorithm, showing a root mean square error (RMSE) and a correlation coefficient (r) of 0.11 m/s and 0.97, respectively, with the HYCOM outputs. A validation against measurements collected from two high-frequency (HF) phased-array radars is also performed, resulting in an RMSE and r of 0.12 m/s and 0.75, respectively. Those validation results are better than the 0.22 m/s RMSE and 0.28 r achieved by the empirical CDOP model. Hence, the experimental results confirm the soundness of the XGBoost, exhibiting a certain improvement over the empirical model. Full article

High-frequency radars (HFRs) provide remote information on ocean surface velocity in extended coastal areas at high resolutions in space ($\mathcal{O}$(km)) and time ($\mathcal{O}$(h)). They directly produce radial velocities (in the radar antenna’s direction) combined to provide total vector velocities in areas covered by at least two radars. HFRs are a key element in ocean observing systems, with several important environmental applications. Here, we provide an assessment of the HFR-TirLig network in the NW Mediterranean Sea, including results from the gap-filling open-boundary modal analysis (OMA) using in situ velocity data from drifters. While the network consists of three radars, only two were active during the assessment experiment, so the test also includes an area where the radial velocities from only one radar system were available. The results, including several metrics, both Eulerian and Lagrangian, and configurations, show that the network performance is very satisfactory and compares well with the previous results in the literature in terms of both the radial and total combined vector velocities where the coverage is adequate, i.e., in the area sampled by two radars. Regarding the OMA results, not only do they perform equally well in the area sampled by the two radars but they also provide results in the area covered by one radar only. Even though obviously deteriorated with respect to the case of adequate coverage, the OMA results can still provide information regarding the velocity structure and speed as well as virtual trajectories, which can be of some use in practical applications. A general discussion on the implications of the results for the potential of remote sensing velocity estimation in terms of HFR network configurations and complementing gap-filling analysis is provided. Full article

Over several decades, high-frequency (HF) radars have been employed for remotely measuring various ocean surface parameters, encompassing surface currents, waves, and winds. Wind direction and speed are usually estimated from both first-order and second-order Bragg-resonant scatter from two or more HF radars monitoring the same area of the ocean surface. This limits the observational domain to the common area where second-order scatter is available from at least two radars. Here, we propose to estimate wind direction and speed from the first-order scatter of a single HF radar, yielding the same spatial coverage as for surface radial currents. Wind direction is estimated using the ratio of the positive and negative first-order Bragg peaks intensity, with a new simple algorithm to remove the left/right directional ambiguity from a single HF radar. Wind speed is estimated from wind direction and de-tided surface radial currents using an artificial neural network which has been trained with in situ wind speed observations. Radar-derived wind estimations are compared with in situ observations in the Lower Saint-Lawrence Estuary (Quebec, Canada). The correlation coefficients between radar-estimated and in situ wind directions range from $0.84$ to $0.95$ for Wellen Radars (WERAs) and from $0.79$ to $0.97$ for Coastal Ocean Dynamics Applications Radars (CODARs), while the root mean square differences range from 8° to 12° for WERAs and from 10° to 19° for CODARs. Correlation coefficients between the radar-estimated and the in situ wind speeds range from $0.89$ to $0.93$ for WERAs and from $0.81$ to $0.93$ for CODARs, while the root mean square differences range from 1.3 m.s⁻¹ to 2.3 m.s⁻¹ for WERAs and from 1.6 m.s⁻¹ to 3.9 m.s⁻¹ for CODARs. Full article

This study explores the near-surface dispersion mechanisms of contaminants in coastal waters, leveraging a comprehensive method that includes using dye and drifters as tracers, coupled with diverse observational platforms like drones, satellites, in situ sampling, and HF radar. The aim is to deepen our understanding of surface currents’ impact on contaminant dispersion, thereby improving predictive models for managing environmental incidents such as pollutant releases. Rhodamine WT dye, chosen for its significant fluorescent properties and detectability, along with drifter data, allowed us to investigate the dynamics of near-surface physical phenomena such as the Ekman current, Stokes drift, and wind-driven currents. Our research emphasizes the importance of integrating scalar tracers and Lagrangian markers in experimental designs, revealing differential dispersion behaviors due to near-surface vertical shear caused by the Ekman current and Stokes drift. During slow-current conditions, the elongation direction of the dye patch aligned well with the direction of a depth-averaged Ekman spiral, or Ekman transport. Analytical calculations of vertical shear, based on the Ekman current and Stokes drift, closely matched those derived from tracer observations. Over a 7 h experiment, the vertical diffusivity near the surface was first observed at the early stages of scalar mixing, with a value of $1.9\times {10}^{-4} {\mathrm{m}}^2/\mathrm{s}$, and the horizontal eddy diffusivity of the dye patch and drifters reached the order of 1 ${\mathrm{m}}^2/\mathrm{s}$ at a 1000 $\mathrm{m}$ length scale. Particle tracking models demonstrate that while HF radar currents can effectively predict the trajectories of tracers near the surface, incorporating near-surface currents, including the Ekman current, Stokes drift, and windage, is essential for a more accurate prediction of the fate of surface floats. Full article

This paper proposes an algorithm based on the long short-term memory (LSTM) network to improve the quality of high-frequency surface wave radar current measurements. In order to address the limitations of traditional high-frequency radar inversion algorithms, which solely rely on electromagnetic inversion and disregard physical oceanography, this study incorporates a bottom-mounted acoustic Doppler current profiler (ADCP) and towed ADCP into LSTM training. Additionally, wind and tidal oceanography data were included as inputs. This study compared high-frequency radar current data before and after calibration. The results indicated that both towed and bottom-mounted ADCP enhanced the quality of HF radar monitoring data. By comparing two methods of calibrating radar, we found that less towed ADCP data input is required for the same high-frequency radar data calibration effect. Furthermore, towed ADCP has a significant advantage in calibrating high-frequency radar data due to its low cost and wide calibration range. However, as the location of the calibrated high-frequency radar data moves further away from the towing position, the calibration error also increases. This article conducted sensitivity studies on the times and different positions of using towed ADCP to calibrate high-frequency radar data, providing reference for the optimal towing path and towing time for future corrections of high-frequency radar data. Full article

The performance of a high-frequency (HF) radar network situated within the Pearl River Estuary from 17 July to 13 August 2022 is described via a comparison with seven acoustic Doppler current profilers (ADCPs). The radar network consists of six OSMAR-S100 compact HF radars, with a transmitting frequency of 13–16 MHz and a direction-finding technique. Both the radial currents and vector velocities showed good agreement with the ADCP results (coefficient of determination r²: 0.42–0.78; RMS difference of radials: 11–21.6 $\mathrm{c}\mathrm{m} {\mathrm{s}}^{-1}$; bearing offset $\Delta \theta$: $-4.8°$–$16.1°$; complex correlation coefficient $\gamma$: 0.62–0.96; and phase angle $\alpha$: −24.3$°–$17.8$°$). For these radars, the $\Delta \theta$ values are not constant but vary with azimuthal angles. The relative positions between the HF radar and ADCPs, as well as factors such as the presence of island terrain obstructing the signal, significantly influence the errors. The results of spectral analysis also demonstrate a high level of consistency and the capability of HF radar to capture diurnal and semidiurnal tidal frequencies. The tidal characteristics and the Empirical Orthogonal Function (EOF) results measured by the HF radars also resemble the ADCPs and align with the characteristics of the estuarine current field. Full article

HF radar systems form part of many operational coastal monitoring systems providing near-real-time surface currents for many useful applications. Although wave measurements have been possible with these systems for many years, they have not yet been adopted widely for operational monitoring because they have not been thought to be sufficiently accurate or reliable. However, the value of such data is beginning to be appreciated, and this is motivating more work on wave measurement with HF radar systems with many more papers on accuracy assessment and data availability appearing in the literature. In this paper, the wave measurement capability, limitations, and differences between different radar types are reviewed, and methods to assess accuracy are discussed and applied to phased array HF radar data obtained from the University of Plymouth WERA radars using the Seaview Software inversion method during April and November 2012 compared with directional buoy data. Good accuracy over a range of different wave parameters will be demonstrated. Newly available single-radar inversions are shown to be less accurate than dual-radar inversions, although they still provide useful data, and ways to improve performance are discussed. Swell and wind–sea components in the directional spectra are identified, and qualitative agreement with buoy peak parameters is demonstrated. Recommendations are given on statistical methods for the validation of wave parameters. Full article

HF radar systems have the potential to measure the wind direction, in addition to surface currents and wave fields. However, studies on HF radar for wind direction determination are rare in the scientific literature. Starting with the results presented in Saviano et al. (2021), we here expand on the reliability of the multiannual wind direction data retrieved over two periods, from May 2008 to December 2010 and from January to December 2012, by a network of three SeaSonde high-frequency (HF) radars operating in the Gulf of Naples (Central Tyrrhenian Sea, Western Mediterranean Sea). This study focuses on the measurements obtained by each antenna over three range cells along a coast–offshore transect, pointing to any potential geographically dependent measurement. The scarcity of offshore wind measurements requires the use of model-generated data for comparative purposes. The data here used are obtained from the Mediterranean Wind–Wave Model, which provides indications for both wave and wind parameters, and the ERA5@2km wind dataset obtained by dynamically downscaling ERA5 reanalysis. These data are first compared with in situ data and subsequently with HF-retrieved wind direction measurements. The analysis of the overall performance of the HF radar network in the Gulf of Naples confirms that the HF radar wind data show the best agreement when the wind speed exceeds a 5 m/s threshold, ensuring a sufficiently energetic surface wave field to be measured. The results obtained in the study suggest the necessity of wind measurements in offshore areas to validate the HF radar wind measurements and to improve the extraction algorithms. The present work opens up further investigations on the applications of wind data from SeaSonde HF radars as potential monitoring platforms, both in coastal and offshore areas. Full article

We describe results from coastal radar systems that observed anomalous current flows generated by the volcanic eruption in the Tongan archipelago on 15 January 2022 UTC, reporting the first radar detection of a volcanic tsunami. The eruption caused small tsunamis along the western U.S. Coast, generating some damage in a few harbors. The highest tsunami signal in U.S. tide gauge data from the California coast occurred at Arena Cove, with significant heights detected at Port San Luis and Crescent City. We analyze correlated wave orbital velocity detections by High Frequency (HF) radars along the coast between Gerstle Cove and Santa Barbara. Signals observed by the radars indicate that the event had two phases, each with its own distinct genesis: an initial weak surface disturbance, most likely generated by the wave of atmospheric pressure that moved outward from the blast source at just below the speed of sound, followed by a stronger disturbance that arrived approximately 3.5 h later, matching the arrival time for a wave moving entirely through the water from the volcano to the U.S. West Coast. We conclude that this phase consists of a conventional water wave tsunami and weaker waves generated by the pulse. We also report the detection of a small pulse-generated event off the west coast of Florida. Radar observations are compared with water level measurements at nearby tide gauges and a DART buoy, and with observations of barometric pressure. We point out that a Proudman near-resonance at the Tonga Trench is unlikely to explain the second phase observations. Comparison with tide gauge signals at San Francisco, generated by the Krakatoa eruption in 1883, support our conclusions. Full article