HF Radar Research Articles

Estimating Surface Current from HIMAWARI-8 SST Data using Particle Image Velocimetry Method (Case Study in The Flores Sea)

<p class="Keywords">Four High-Frequency radar systems (HF) have been installed in Indonesia to monitor surface currents. In-situ ocean current observations are relatively expensive and limited by spatial and temporal resolution. Satellite remote sensing enables the estimate of surface current data generally from surface tracer data, including sea surface temperature (SST). Various methodologies have been developed to obtain surface currents. With Himawari-8 SST data, this study examines the accuracy of the resulting estimation. The cross-correlation fields of two identical-sized interrogation windows obtained from sequential images are employed in Particle Image Velocimetry (PIV). The HF radar in Labuan Bajo was used to validate surface current velocity estimates. RMSE, bias, and the Willmott index determined the accuracy. According to the estimates of surface currents made on July 29, 2022, the results follow a monsoon characteristic wind pattern in the Flores Sea. HF radar observations better validate the V component current estimation than the U component current estimation. A study of sea surface currents from SST data is lacking in Indonesian seas, and more repetition is required. As a result, This method has the potential can be employed to observe aquatic environments in other Indonesian areas.</p>

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.

Effect of circulation at early life stages of European anchovy in the Bay of Biscay from observational data and a Lagrangian approach

Coastal circulation influences the distribution of European anchovy (Engraulis encrasicolus) at early life stages (ELS) in the Bay of Biscay (BoB). However, how this happens is not yet fully understood. In this work, further insight is provided by performing Lagrangian diagnostics based on observations of ELS anchovies' initial distributions and currents. Surface diagnostics were obtained by using high-frequency radar (HFR) currents and were applied to analyse multiyear variability and detect the coastal processes that affect the distribution. Since ELS anchovies are also located at subsurface levels, subsurface diagnostics were obtained by using currents reconstructed from HFR and ADCP observations with a reduced order optimal interpolation (ROOI) method. The analyses included transport computations as well as the analysis of flow properties by Lagrangian Coherent Structures and chlorophyll-a satellite images.Results suggest that ELS anchovies are mostly retained over the shelf and slope, and that transport patterns highly vary across different periods. Mesoscale structures such as eddies, fronts and along-slope currents within the slope and the Capbreton canyon area, as well as strong and persistent winds, could significantly impact the distribution of ELS anchovies. In some periods, the resulting distribution might be due to a combination of these processes. Circulation can also play a key role in ELS anchovy aggregation within short time scales (20 days). This work showcases the potential of observation-based approaches and emphasizes the relevance of coastal observatories for integrated studies.

Automated Detection and Tracking of Equatorial Plasma Bubbles Utilizing Global‐Scale Observations of the Limb and Disk (GOLD) 135.6 nm Data

AbstractEquatorial plasma bubbles (EPBs) are regions of depleted plasma within the ionosphere that form during post‐sunset hours near the magnetic equator. EPBs tend to align with local geomagnetic field lines, extend hundreds of kilometers along geomagnetic longitudes, and thousands of kilometers along geomagnetic latitudes. EPBs can attenuate lower frequency radio waves, such as HF radar. Smaller features, usually 10s of meters, along the EPB's wall can interfere with centimeter scale wavelengths, such as GPS, via Bragg scattering. Statistical analysis of EPBs can further understanding of their occurrence and behavior. The current study utilizes Global‐Scale Observations of the Limb and Disk (GOLD) 135.6 nm nightglow data from 5 October 2018 to 30 September 2022. GOLD has a unique perspective from geostationary orbit, allowing consistent viewing of nightglow and structures over the Americas and Atlantic. An EPB detection method is developed and used to generate a database of occurrences. Occurrences are used to calculate EPB drift speeds and separations. All data is looked at as a whole, including any possible solar or geomagnetic disturbance periods. Seasonality in occurrence rate is evident. Occurrences peak during December solstice and minimize during June solstice for longitudes seen by GOLD. Within GOLD's view, higher occurrences are seen to the west during December solstice and to the east during June solstice. EPB drift speeds and separations show consistent distributions regardless of magnetic latitude region, geographic region, or season. This suggests EPBs behave consistently and regularly once formed, at least on spatial scales observed by GOLD.

Reconstructing High-Frequency Radar Derived Ocean Surface-Current Fields Using Spatio-Temporal Kriging

Reconstructing High-Frequency Radar Derived Ocean Surface-Current Fields Using Spatio-Temporal Kriging

Extrapolation of electromagnetic pointing error corrections for Sentinel-1 Doppler currents from land areas to the open ocean

By utilizing single-look complex data from synthetic aperture radar (SAR), the Doppler centroid anomaly method (DCA) can be employed to determine the velocity of the sea surface current field along the radar line-of-sight direction. However, due to the influence of platform or antenna perturbations, SAR Doppler shift measurements are subject to electromagnetic pointing error (EPE). These errors can typically be reduced by using echo information from land areas (including islands) within the SAR images to correct the Doppler shift. This allows the successful estimation of Doppler shifts due to sea surface factors and, in turn, the retrieval of ocean currents in the radar line-of-sight. However, in cases where SAR images lack data over land, uncorrectable EPE can result in significant inaccuracies in the retrieval of ocean currents. This study utilizes data captured by Sentinel-1A on four orbits in the Florida Strait region of the Gulf Stream from July 2020 to October 2022 to investigate the variation characteristics of EPE. To address the issues of calculating these in SAR images lacking land data, an EPE fitting method is proposed. The correction significantly reduces the error of S1A retrieved current velocity compared with line-of-sight current velocity from the HYCOM model and in situ HF radar, indicating that the proposed method provides an effective way to reduce the impact of EPE in SAR images, even when land is not directly observed.

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.

DOA Estimation of Multiple Coherent Targets Using Weight Vector Orthogonal Decomposition in TDM-MIMO HF-Radar

In recent years, MIMO high-frequency surface wave radar (MIMO-HFSWR) plays an increasingly important role in sea surveillance because of its wide-area surveillance capabilities. In signal processing, the coherent targets with the same distance and speed can only be distinguished in the angle dimension. However, HF radar’s angular resolution is poor because of the restrictions of the aperture, which causes aliasing of targets on the range–angle (RA) spectrum. Traditional super-resolution algorithms, such as MUSIC, are also inapplicable because of the targets’ coherence. Therefore, the spatial smoothing algorithm is usually used to realize the decoherence of echo at the cost of array aperture. The loss of array aperture makes the algorithm fail when there are too many targets in the echo. Aiming at this problem, this paper proposes an iterative calculation method (iterative calculation via weight vector orthogonal decomposition, IC-WORD) to estimate the angle of multiple coherent targets. Through the verification of simulation, it is proved that IC-WORD has better performance than the traditional spatial smoothing algorithm. More specifically, IC-WORD can correct spectral peak shift, improve angle measurement accuracy, and still operate stably under the condition of multiple coherent targets. This paper also uses the measured data from one of the most advanced HFSWR stations in China to validate the algorithm, which makes the paper have strong practical significance.

Two dimensional Hydrodynamic Simulation in Labuan Bajo Waters, Indonesia.

Based on its strategic location, Labuan Bajo is a golden triangle between Komodo Island and Toraja Land as a national tourism sector. This makes information about the condition of Labuan Bajo waters very important. One of the oceanographic parameters that have an important role in determining the condition of a body of water is ocean currents. Ocean currents are the movement or displacement of water masses caused by waves, wind, water density, and pressure. In their movement, currents have a direction and speed that can form ocean current patterns. One method that can see patterns of sea surface currents is two-dimensional hydrodynamic modeling. This study aims to identify patterns of surface currents and tides that occur in Labuan Bajo waters. The method used in this study is quantitative descriptive with a two-dimensional hydrodynamic modeling approach along with nested-model techniques to provide the model results with a smaller resolution to get the phenomenon that occurs in those waters. The data used is bathymetry, wind, tide, and High-Frequency Radar (HF Radar) data as current validation. The results of surface current simulation in Labuan Bajo waters have the highest current of >1.12 m/s in the Western season and the lowest speed of 0.88 m/s in the Transition I season. The wind pressure gradient in the Western season affects the current speed in that season.

Science Goals for a High-Frequency Radar and Radio Imaging Array

Science Goals for a High-Frequency Radar and Radio Imaging Array

4D-Var data assimilation and observation impact on surface transport of HF-Radar derived surface currents in the North-Western Mediterranean Sea

We investigated the effect of the assimilation of surface velocities from two HF-Radars (HFRs) and satellite sea surface temperature (SST) into an ocean circulation model, implemented on the North-Western Mediterranean Sea, using the ROMS 4D-Var Data Assimilation (DA) System. A three months period from September to November 2020 is analysed. A model free run is used as reference simulation to quantify the impact of the data assimilation procedure on the surface circulation. The DA framework consists of a sequence of 3-day windows during which the observations are assimilated into the model, followed by forecast simulations, starting from the last time step of the analysis run. The comparison of simulated velocities and SST against the assimilated observations shows that both forecast and analysis runs improve the solution as compared to the freerun, with error reduction up to the 47% and doubling of correlation values. If SST is not assimilated, the simulated sea surface temperature slightly degrades as a result of the DA procedure. Furthermore, we used surface velocities from Lagrangian drifters to test the model against independent observations. The results show that both the forecast and the analysis simulate surface circulation better than the free run within the areas covered by HFR observations, with error reduction ranging from 10% to 50%, and increase in correlation from 5% to more than doubled. Nevertheless, farther afield, outside the area covered by HFRs, improvements and degradations of the solution due to the DA procedure balance each other. The impact of assimilated observation on the alongshore transport of the upper 50 m is analysed along three transects adjacent to the two HFR areas and along a section in between. The transport increment is significant where the surface velocities are assimilated whereas it is negligible elsewhere. The effect of SST is to modify the velocity distribution along the transects, while keeping the transport increment unchanged. Modifications to the initial conditions have the most significant effect on the alongshore transport, whereas the corrections to boundary conditions and atmospheric forcing have different importance according to the analysed transects. The assimilation of surface velocities and SST affects more the ageostrophic component of the surface velocity field, rather than the geostrophic one.

Analysis of internal soliton signals and their eastward propagation in the Alboran Sea: exploring the effect of subinertial forcing and fortnightly variability

Internal waves are commonly observed in oceans and lakes where high stratification exists. In the present study in the Strait of Gibraltar, we analyse internal soliton signals recorded in different locations in their eastward propagation from their release point (Camarinal Sill) to the continental slope of the northwestern Alboran Sea. Moreover, the effect of subinertial forcing on the release of solitons is also explored. The internal soliton activity was assessed from different approaches: (i) in-situ data (i.e., current and temperature measurements or High-Frequency Radar), (ii) numerical modelling, and (iii) an analytical approach. The arrival of solitons over the continental slope of the north-western Alboran Sea showed fortnightly variability in both number (occurrence) and amplitude during spring tides when compared with during neap tides. The observed arrival times of the solitons oscillated between 14 (spring tides) and 20 h (neap tides). Nevertheless, to provide a comprehensive explanation for the fluctuations in travel times, it is necessary to consider the subinertial variability driven by atmospheric forcing, which impacts both the flow in the Strait of Gibraltar and the mesoscale patterns in the Alboran Sea (e.g., the Coastal Cyclonic Gyre).

Multi-instrument study of a spread-F event at Arecibo linked to solar wind variations

Using five diverse data sets, we demonstrate that apparently local ionospheric spread-F activity, observed with an HF radar and the Arecibo Observatory (AO) Incoherent Scatter Radars (ISR) under geomagnetically quiet conditions, is likely the local manifestation of a mesoscale or larger ionospheric response to relatively weak solar wind activity. The solar wind activity included a weak pressure pulse and Interplanetary Magnetic Field (IMF) realignment events. The mid-latitude spread-F activity was observed with a 4.42 MHz radar located near AO and the dual-beam 430 MHz AO ISRs. Additionally, the Coupling, Energetics and Dynamics of Atmospheric Regions (CEDAR) Madrigal Global Navigation Satellite System-Total Electron Content (GNSS-TEC), the NASA OMNI, and the SuperMAG datasets were used to establish the (mesoscale/global) wide-context of the local, deep-context radar results. While the ISR event appears to be “classical” local spread-F, often attributed to Perkins-like plasma instabilities, the HF radar reveals large ionospheric structures coincident with the ISR event. However, that the apparently AO-local event was part of a very dynamic mesoscale event that lasted for over ten hours, is shown via independent AO-sector and AO-conjugate sector keograms constructed using detrended vertical TEC (delta-vTEC) data. The keograms reveal a prominent F-region feature that appears to propagate from west-to-east and then back to the west passing over AO twice. The ISR manifestation of this mesoscale event is indistinguishable from decades of similar ISR results which were assumed to be strictly “local”. The strong non-local (mesoscale) properties revealed by the delta-vTEC keograms suggest a possible space weather influence. Study of the relevant NASA OMNI solar wind and superMAG magnetometer data points to modest solar wind features including IMF realignment that may have electrodynamically launched, with little time delay, the observed mesoscale ionospheric events. Given the apparent rapid ionospheric response to the solar wind features, we suggest that limited latitudinal scale, prompt penetration electric fields (PPEF), associated with highly-localized partial ring current activity, be considered in the system-of-systems context of our observations. In any case, the need to examine magnetospheric/ionospheric electrodynamics across a wide range of instruments and data sets is demonstrated.

Designing Theoretical Shipborne ADCP Survey Trajectories for High-Frequency Radar Based on a Machine Learning Neural Network

A machine learning neural network-based design for shipborne ADCP navigation is proposed to improve the quality of high-frequency radar measurements. In traditional inversion algorithms for HF radars, sea surface velocity is directly extracted from electromagnetic echoes without constraints from oceanographic processes. Hence, we incorporated oceanographic information from observational data into seabed radar inversion results via an LSTM neural network model to enhance data accuracy. Through a series of numerical simulation experiments, we showed improved data accuracy and feasibility by incorporating both fixed-point and navigation observational data. The results indicate a significant reduction in (related) errors. This study has implications for guiding future navigation observations.

Quantitative Assessment of Sea Surface Salinity Estimates Using a High-Frequency Radar in Ise Bay, Japan

Changes in sea surface salinity (SSS) caused by the discharge of freshwater plumes from rivers affect the marine environment in estuaries; therefore, monitoring SSS is essential for understanding the changes in physical phenomena within coastal ecosystems induced by river plume discharge. Previous studies showed that salinity could be estimated using a very-high-frequency radar; however, this method was only validated over a short period and few qualitative evaluations were performed. Therefore, to verify quantitative assessments of SSS estimates for practical use, we estimated SSS using the Doppler spectrum of a 24.5-MHz phased-array high-frequency (HF) radar installed in Ise Bay, Japan, and data of approximately 1 year were used for verification. The radar-estimated SSS map was consistent with the velocity field and salinity distribution reported in previous studies. The root mean square error (RMSE) of the SSS estimate for 1-h radar data compared with in situ observations was 4.42 psu when the effect of wind on the received power was removed and 5.04 psu when it was not. For the daily (25-h) average, the RMSE when the effect of wind was considered was 3.32 psu. These results were considered sufficiently applicable in closed coastal areas such as Ise Bay, where the SSS decreases rapidly by 10 psu or more due to river flooding. The results revealed that the HF radar, which can continuously measure sea surface velocity and SSS with a high spatiotemporal resolution, can be a useful tool for providing a deeper understanding of the physical and environmental phenomena that are greatly affected by river water discharge.

HF Radar Wind Direction: Multiannual Analysis Using Model and HF Network

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.

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.

A THz Slot Antenna Design Using Analytical Techniques

Slot antennas are very popular microwave antennas, and slotted waveguides are used for high frequency radar systems. A thin slot in an infinite ground plane is the complement to a dipole in free space. This was described by H.G. Booker, who extended Babinet’s principle from optics to show that the slot will have the same radiation pattern as a dipole such that the E and H fields are swapped. As a result, the polarization is rotated, so that radiation from the vertical slot is polarized horizontally. In this work, we show how this straightforward analytical technique can be used for the design of high-frequency THz slot antennas. The analysis is then corroborated by using a numerical simulation which validates the performance parameters predicted by the analytical technique. We show by simulation that, despite the simplicity of our classical approach, we obtained useful results, even at THz frequencies. We show that gradually moving the slot position from the centerline improves the antenna’s performance.

Multi-Target CFAR Detection Method for HF Over-The-Horizon Radar Based on Target Sparse Constraint in Weibull Clutter Background

High frequency radar has a wide monitoring range and low range resolution. It may contain multiple targets or outlier interference phenomena in different clutter regions of the range–Doppler (RD) spectrum in detected background. The key to the performance of target detection in multi target backgrounds is the ability to determine the attributes of targets or outliers. Our previous research shows that the number of targets belongs to an absolute minority compared to the number of background units. In this paper, we propose a new method for multi-target detection building on the ordered statistics constant false alarm detector (OS-CFAR). The new method fully utilizes the sparse characteristics of the target and uses the idea of introducing regularization processing to eliminate interfering targets, and obtain an estimate of shape parameters for target detection. To further improve the performance of the algorithm, a correction method is proposed for the inaccurate selection of the k value. Upon estimating the distribution parameters, the detection threshold is calculated, and the target’s constant false alarm detection is completed. Simulation and measured data show that our algorithm can effectively counter the interference of multiple targets and maintain a constant false alarm characteristic under different conditions, providing a reliable target detection method.

Impact of assimilating wind retrievals from high‐frequency radar on COAMPS forecasts in the Chesapeake Bay

AbstractWind retrievals from high‐frequency radars (HFRs) provide high‐density, hourly wind estimates over the ocean near the coast. These wind retrievals are a promising new source of near‐surface wind estimates in coastal regions where it is difficult to deploy large networks of buoys and where scatterometers cannot observe because of land contamination. In addition to improving ocean monitoring, these wind retrievals are also useful in numerical weather prediction. The wind estimates are retrieved from the HFR Doppler spectra in conjunction with the Simulating WAves Nearshore (SWAN) model, HFR forward model, and HFR adjoint model. In this work, wind retrievals were generated from three Coastal Ocean Dynamics Applications Radar (CODAR) SeaSonde HFR sites located near the mouth of the Chesapeake Bay in August 2017 and assimilated in the Coupled Ocean/Atmosphere Mesoscale Prediction System® (COAMPS) model. The impact of the assimilated HFR wind retrievals on near‐surface weather forecasts is measured with adjoint‐derived forecast sensitivity observation impact (FSOI) and a comparison to forecasts from a data‐denial observing system experiment (OSE). The FSOI measurement indicates the HFR winds had neutral impact on the 12‐h forecast while the OSE comparison suggests a small improvement in the 10‐m u and v winds at lead times up to 36 h. Compared to a similar study in the Southern California Bight, the small impact on the forecast seen in this Chesapeake Bay study could be related to there being a smaller number of wind retrievals in a smaller region during a period where the HFR wind retrievals were already similar to the background wind field. We suggest that HFR wind retrievals used for numerical weather prediction may be more beneficial when generated for long swaths of coastlines rather than small, isolated areas.