HF Radar Data Research Articles

Intercomparison of Surface Currents Obtained Using SCHISM and the HF Radar Data in Galveston Bay and Sabine Lake, Texas

Intercomparison of Surface Currents Obtained Using SCHISM and the HF Radar Data in Galveston Bay and Sabine Lake, Texas

Characterizing Non‐Phase‐Locked Tidal Currents in the California Current System Using High‐Frequency Radar

AbstractOver 9 years of hourly surface current data from high‐frequency radar (HFR) off the US West Coast are analyzed using a Bayesian least‐squares fit for tidal components. The spatial resolution and geographic extent of HFR data allow us to assess the spatial structure of the non‐phase‐locked component of the tide. In the frequency domain, the record length and sampling rate allow resolution of discrete tidal lines corresponding to well‐known constituents and the near‐tidal broadband elevated continuum resulting from amplitude and phase modulation of the tides, known as cusps. The FES2014 tide model is used to remove the barotropic component of tidal surface currents in order to evaluate its contribution to the phase‐locked variance and spatial structure. The mean time scale of modulation is 243 days for the M2 constituent and 181 days for S2, with overlap in their range of values. These constituents' modulated amplitudes are significantly correlated in several regions, suggesting shared forcing mechanisms. Within the frequency band M2 ± 5 cycles per year, an average of 48% of energy is not at the phase‐locked frequency. When we remove the barotropic model, this increases to 64%. In both cases there is substantial regional variability. This indicates that a large fraction of tidal energy is not easily predicted (e.g., for satellite altimeter applications). The spatial autocorrelation of the non‐phase‐locked variance fraction drops to zero over a distance of 150 km, a scale that is comparable to the swath width of the Surface Water and Ocean Topography altimeter.

Real-time quality assurance and quality control for a high frequency radar network

This paper recommends end to end quality assurance methods and quality control tests for High Frequency Radar Networks. We focus on the network that is operated by the Mid Atlantic Regional Association Coastal Ocean Observing System (MARACOOS). The network currently consists of 38 radars making real-time measurements of the surface currents over the continental shelf for a variety of applications including search and rescue planning, oil spill trajectory modelling and providing a transport context for marine biodiversity observing networks. MARACOOS has been delivering surface current measurements to the United States Coast Guard (USCG) since May 2009. Data quality is important for all applications; however, since the USCG uses this surface current information to plan life-saving missions, delivery of the best quality data is crucial. We have mapped the components of the HF radar data processing chain onto the data levels presented in the NASA Earth Science Reference Handbook and have applied quality assurance and quality control techniques at each data level to achieve the highest quality data. There are approximately 400 High Frequency radars (HFRs) deployed globally and the presented techniques can provide a foundation for data quality checks and standardization of the data collected by the large number of systems operating today.

Integration of microseism, wavemeter buoy, HF radar and hindcast data to analyze the Mediterranean cyclone Helios

Abstract. In this work, we study a Mediterranean cyclone, Helios, which took place during 9–11 February 2023 in the southeastern part of Sicily and Malta, by a multiparametric approach combining microseism results with sea state and meteorological data provided by wavemeter buoy, HF radar, hindcast maps and satellite SEVIRI images. The sub-tropical system Helios caused heavy rainfall, strong wind gusts and violent storm surges with significant wave heights greater than 5 m. We deal with the relationships between such a system and the features of microseism (the most continuous and ubiquitous seismic signal on Earth) in terms of spectral content, space–time variation of the amplitude and source locations tracked by means of two methods (amplitude-based grid search and array techniques). By comparing the location of the microseism sources and the area affected by significant storm surges derived from sea state data, we note that the microseism location results are in agreement with the real position of the storm surges. In addition, we are able to obtain the seismic signature of Helios using a method that exploits the coherence of continuous seismic noise. Hence, we show how an innovative monitoring system of the Mediterranean cyclones can be designed by integrating microseism information with other techniques routinely used to study meteorological phenomena.

Simplified Extraction of Peak Wave Period From HF-Radar Data

Simplified Extraction of Peak Wave Period From HF-Radar Data

Interoperable Access and Interactive Exploration of HF Radar Data

Interoperable Access and Interactive Exploration of HF Radar Data

Developments in Scope and Availability of HF Radar Wave Measurements and Robust Evaluation of Their Accuracy

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.

A Quality Control Method for High Frequency Radar Data Based on Machine Learning Neural Networks

We propose a quality control method based on machine learning neural networks to enhance the quality of high-frequency (HF) radar data. Unlike traditional quality control methods that rely on radar signals as indicators and involve extensive data manipulation in specialized software, our approach employs a Bi-LSTM neural network model. This method aims to improve data quality and streamline the quality control process. Through a series of analyses, we demonstrate the feasibility of using machine learning techniques to enhance radar data quality.

Study of Driving Force and Surface Current Patterns in Labuan Bajo from High Frequency Radar data from October to December 2018

Surface ocean current data in Labuan Bajo from October to December 2018 for determine the characteristics of the surface current and identify the influence of wind and tides in generating surface current. The current data set is derived from measurements of high frequency (HF) radar, which operates on the electromagnetic wave spectrum at high frequency or short wave. Method of data analysis by processing surface current velocity and direction of the zonal and meridional into spatial and temporal graphs. The result showed the average current speed in October was 0.13 m/s, the average current speed in November was 0.12 m/s, and the average current speed in December was 0.09 m/s. The empirical orthogonal function (EOF) Mode 1 has a variance of 56.2% because of the tides, Mode 2 has a variance of 26.6% because of bi-weekly variability, and Mode 3 has a variance of 17.2% because of the intra-seasonal period. This shows that tides have a greater influence on the study region than any other driving force. These results are intended to be useful to the public, particularly in terms of sustainable coastal marine management in Labuan Bajo. Especially in terms of preventing boat accidents caused by ocean currents.

Extraction of the significant wave height from synthetic HF radar data acquired on a floating platform

AbstractThe usual procedure for extracting ocean surface information from data acquired from a high‐frequency surface wave radar transmitting from a floating platform is to first compensate for the motion of the antenna in the acquired motion‐contaminated Doppler spectrum and then extract the ocean wave parameters from the motion‐compensated result. The authors propose a new real‐time method to estimate the significant wave height directly from the antenna's received electric field in the time‐domain without requiring prior knowledge of the motion parameters or performing motion compensation. Based on the relation between the ocean surface displacement and the received electric field, this method calculates the significant wave height from the windowed variance of the upper envelope of the received electric field. A preliminary calibration is required, which can be carried out either by the deployment of a wave buoy or by analysing the data over a time period during which the sea state varies. The results from this simple proposed technique show that it may be used to estimate the significant wave height with a root‐mean‐square error (RMSE) between 10 and 14 cm over a wide range of significant wave height values.

Calibration and validation of high frequency coastal radar waves exploiting in-situ observations and modelled data in the south-west Sicily

ABSTRACT This paper describes a calibration procedure for a non-optimally configured High Frequency Radar (HFR) for the period 1 April 2021, to 31 March 2022, to assess sea waves characteristics. The HFR system, a 16.5 MHz WEllen RAdar (WERA), is part of an innovative network for monitoring the state of the sea. The system is installed in the western part of Sicily (Italy) where a wave buoy is positioned. HFR data underestimate the spectral significant wave heights (Hm0), in particular for Hm0 > 2 m, highlighting the need for calibration of the HFR system to ensure its optimal performance for operational purposes. The calibration was performed with both in-situ and modelled data provided by the Copernicus Marine Service. The best results were obtained when the buoy data were used as reference. Encouraging results were achieved as demonstrated by the improvement of the quantitative metrics after the calibration. Indeed, the RMSE decreased from 0.60 to 0.36 m; the correlation R increased slightly from 0.86 to 0.88, the slope from 0.48 to 0.8; whereas intercept from 0.11 to 0.31 m. Moreover, waves higher than > 2 m are well reproduced by the calibrated HFR time series with the RMSE decreasing from 1.3 to 0.53 m.

Forecast Sensitivity-based Observation Impact (FSOI) in an analysis–forecast system of the California Current Circulation

Forecast Sensitivity-based Observation Impacts (FSOI) in an analysis–forecast​ system of the California Current System (CCS) are quantified using an adjoint-based approach. The analysis–forecast system is based on the Regional Ocean Modeling System (ROMS) and a 4-dimensional variational (4D-Var) data assimilation approach. FSOI was applied to four different metrics of forecast skill that target important features of the CCS circulation along the central California coast. A particular focus of the FSOI analysis is the impact of assimilation of measurements of the radial component of surface currents from a network of high frequency (HF) radars since this is a new data stream in the near-real-time system considered here. On average, ∼50–60% of all observations assimilated into the model yielded improvements in the forecast skill. Conversely, the remaining ∼40–50% of data degrade the forecasts, in line with similar findings in numerical weather prediction systems. Much of the improvement in forecast skill arises from remotely sensed observations, including HF radar data; on average only ∼50% of in situ measurements contribute to a reduction in forecast error. This is partly due to the large volume of remote sensing observations compared to in situ observations. However, in situ observations are an order of magnitude more impactful than remotely sensed data when viewed in terms of the average impact per observation.

Breakdown of Near-Surface Sea Current from High-Frequency Radar Data

Abstract To assess the contribution of wind drag and Stokes drift on the near-surface circulation, a methodology to isolate the geostrophic surface current from high-frequency radar data is developed. The methodology performs a joint analysis utilizing wind field and in situ surface currents along with an unsupervised neuronal network. The isolation method seems robust in the light of comparisons with satellite altimeter data, presenting a similar time variability and providing more spatial detail of the currents in the coastal region. Results show that the wind-induced current is around 2.1% the wind speed and deflected from the wind direction in the range [18°, 23°], whereas classical literature suggests higher values. The wave-induced currents can represent more than 13% of the ageostrophic current component as function of the wind speed, suggesting that the Stokes drift needs to be analyzed as an independent term when studying surface sea currents in the coastal zones. The methodology and results presented here could be extended worldwide, as complementary information to improve satellite-derived surface currents in the coastal regions by including the local physical processes recorded by high-frequency radar systems. The assessment of the wave and wind-induced currents have important applications on Lagrangian transport studies.

Swell and wind-sea partitioning of HF radar directional spectra

ABSTRACT Partitioning is a process used to separate wind-sea and swell contributions in an ocean wave directional spectrum to simplify, and hence make more useful, the interpretation of the spectrum for users of wave data. HF radar systems can measure the wave spectrum over regions of the coastal ocean from the coast to over 100 km offshore with good spatial and temporal resolution depending on the operating frequency and bandwidth. Such systems can measure hundreds of directional spectra across the field of view of the radar, so there is very strong motivation to reduce the dimensionality of the data set for practical applications using partitioning. For similar reasons partitioning methods are increasingly being used for wave model and satellite-measured spectra. A partitioning method, which extends the method of Waters J, Wyatt LR, Wolf J, Hines A. [2013. Data assimilation of partitioned HF radar wave data into Wavewatch III. Ocean Model. 72:17–31.] for HF radar data, is described, assessed using buoy data and used to demonstrate the spatial variability of both swell and wind waves in three coastal regions. The results are very encouraging. HF radar systems could therefore provide very useful data for wave model and satellite partitioning validations in coastal waters where model and satellite measurements are most challenged by wave-current interactions, coastal topography and bathymetry.

Characterizing Residual Current Circulation and Its Response Mechanism to Wind at a Seasonal Scale Based on High-Frequency Radar Data

Residual current characteristics are indicators for the net transports of sediments, nutrients, and pollutants, and for the dilution and diffusion of soluble substances in coastal areas, yet their driving mechanisms remain poorly understood. Here, we studied the characteristics of surface residual currents along the west coast of the island of Ireland, as well as the response mechanisms to wind at a seasonal scale based on the continuous observation data of high-frequency radar (HFR) for one year. Our analyses indicate that wind has a significant effect on generating surface residual currents, with correlation coefficients of 0.6–0.8 between wind speeds and residual current speeds at both annual and seasonal scales. However, the correlation between the directions of residual currents and the wind was not as significant as speed, likely because the directions of residual currents were not only affected by sea surface wind, but also by land boundary conditions in the research area. Moreover, the residual currents had a significant eastward flow trend identical to the wind direction at the maximum wind speed time, during which the effect of the tide on residual currents was relatively weak. Additionally, when compared with wind fields, HFR surface flow fields and surface residual current fields show that wind is the dominant driver of the variations of surface and residual flow fields. These findings shed light on coastal ecological and environmental management and can assist in the prevention and mitigation of marine disasters, by providing helpful information for improving the ability and accuracy of forecasting coastal currents.

Spatial Analysis of a Rapid Intrusion Event of the East Australian Current Using High Frequency Radar Data

The East Australian Current (EAC) is a highly dynamic western boundary current of the South Pacific Gyre. The EAC frequently encroaches shoreward, drives upwelling, changes coastal bio-physical dynamics, and thus exerts significant impacts on coastal marine ecosystems. In this study, with high frequency (HF) radar and mooring data, for the first time accurate daily mapping and tracking of a rapid EAC intrusion event was conducted and the impacts of the EAC intrusion on the shelf water off Coffs Harbor were monitored. The results show that, during the event, the EAC was highly dynamic with a mean daily onshore/offshore movement of ~5 km/day. In addition, we found that the bottom ocean temperature and the surface current speed on the shelf varied linearly with the EAC-to-coast distance. This study thus demonstrates the value of HF remotely sensed data for the ongoing quantitative monitoring of the highly dynamic EAC fluctuations.

Gulf of Naples Advanced Model (GNAM): A Multiannual Comparison with Coastal HF Radar Data and Hydrological Measurements in a Coastal Tyrrhenian Basin

High-resolution modelling systems have increasingly become an essential requirement to investigate ocean dynamics over a wide range of spatial and temporal scales, and to integrate the punctual ocean observations. When applied in coastal areas, they also have the potential to provide a detailed representation of transport and exchange processes at the sub-basin scale. This paper presents a validation exercise between the surface fields generated by the regional ocean modeling system (ROMS), developed for the Tyrrhenian Sea and downscaled for the Gulf of Naples (GNAM Gulf of Naples advanced model), and a 4 year-long (2009–2012) record of high-frequency radar (HFR) data. The comparison between hourly and seasonal model results and HFR surface fields is focused on the Gulf of Naples (GoN), where an observational network of three HFR sites has been operational since 2004, and on a specific subdomain characterized by the presence of the Sarno river, a long-term ecological research station (LTER-MC) and one important canyon area. An evaluation on a transect delimiting inshore–offshore zones in the GoN is also presented. The GNAM model was also compared with in situ hydrological parameters of temperatures and salinities retrieved at the LTER-MC fixed monitoring station. According to the skill metrics, basic circulation features are accurately reproduced by the circulation model, despite some model drawbacks in terms of increment of energy content in the surface current field occurring during specific seasonal events. The results allow us to identify potential model errors and to suggest useful improvements, the outcome also confirms the unique capability of HF radar systems to provide fine-scale measurements for the validation of numerical models and to counterbalance the lack of high-resolution measurements in coastal areas.

Synchronous Assimilation of Tidal Current-Related Data Obtained Using Coastal Acoustic Tomography and High-Frequency Radar in the Xiangshan Bay, China

To accurately reconstruct large-area three-dimensional current fields in coastal regions, simultaneous observations with ten coastal acoustic tomography (CAT) stations and two high-frequency radar (HFR) stations were performed in the Xiangshan Bay (XSB) on 4–5 December 2020. The section-averaged velocity that was observed by CAT and the radial velocity that was observed by HFR were, for the first time, synchronously assimilated into a three-dimensional barotropic ocean model. Compared with acoustic Doppler current profile data, the velocities of the model assimilating both CAT and HFR data had the highest accuracy according to root mean square differences (RMSDs), ranging from 0.05 to 0.08 m/s for all the vertical layers. For the models individually assimilating CAT and HFR, the values in the vertical layers ranged from 0.07 to 0.12 m/s and 0.08 to 0.13 m/s, respectively. A harmonic analysis of the model grid data showed that the spatial mean amplitudes of the M2, M4, and residual currents were 0.66, 0.14, and 0.09 m/s, respectively. Furthermore, the standing wave characteristics of the M2 current and M4 associated-oscillation in the inner XSB, mouth of the Xiangshan fjord, were better captured by the model assimilating both CAT and HFR. Our study demonstrates the advances in three-dimensional tidal current analysis using a model that assimilates both CAT and HFR data, especially in regions with complex coastal geography.

Comparisons of Tidal Currents in the Pearl River Estuary between High-Frequency Radar Data and Model Simulations

High-frequency (HF) radar data, derived from a pair of newly developed radar stations in the Pearl River Estuary (PRE) of China, were validated through comparison with in situ surface buoys, ADCP measurements, and model simulations in this study. Since no in situ observations are available in the radar observing domain, a regional high-resolution ocean model covering the entire PRE and its adjacent seas was first established and validated with in situ measurements, and then the HF radar data quality was examined against the model simulations. The results show that mean flows and tidal ellipses derived from the in situ buoys and ADCP were in very good agreement with the model. The model–radar data comparison indicated that the radar obtained the best data quality within the central overlapping area between the two radar stations, with the errors increasing toward the coast and the open ocean. Near the coast, the radar data quality was affected by coastlines and islands that prevent HF radar from delivering high-quality information for determining surface currents. This is one of the major drawbacks of the HF radar technique. Toward the open ocean, where the wind is the only dominant forcing on the tidal currents, we found that the poor data quality was most likely contaminated by data inversion algorithms from the Shangchuan radar station. A hybrid machine-learning-based inversion algorithm including traditional electromagnetic analysis and physical oceanography factors is needed to develop and improve radar data quality. A new radar observing network with about 10 radar stations is developing in the PRE and its adjacent shelf, this work assesses the data quality of the existing radars and identifies the error sources, serving as the first step toward the full deployment of the entire radar network.

First Observations of E‐Region Near Range Echoes Partially Modulated by F‐Region Traveling Ionospheric Disturbances Observed by the Same SuperDARN HF Radar

AbstractWe present the first observations from SuperDARN HF radar data of E‐region Near Range Echoes (NREs) whose amplitudes are partially modulated by Medium‐Scale Traveling Ionospheric Disturbances (MSTIDs) propagating in the F‐region overhead that have been observed by the same radar in the far ranges. SuperDARN NREs occur normally ∼180–315 km downrange from the radar at ∼95–125 km altitude. Selected observations of TID‐modulated NREs are presented from SANAE and Zhongshan Antarctic SuperDARN radars for both summer and winter seasons as well as geomagnetic active and quiet times. We show that the most likely mechanism is partial modulation of the Gradient Drift Instability (GDI), which is responsible for producing the NREs. GDI is driven by the velocity difference between neutrals and ions and may appear in the E‐region ionosphere wherever suitable plasma density gradients exist. GDI already present in the E‐region can be partially modulated by an MSTID passing overhead in the F‐region via the additional MSTID polarization electric field mapped down in altitude along the equipotential magnetic field lines, thereby partially modulating the NRE amplitudes as observed.