HF Radar Research Articles

Polar mesospheric summer echo (PMSE) multilayer properties during the solar maximum and solar minimum

Abstract. Polar mesospheric summer echoes (PMSEs) are radar echoes that are measured in the upper atmosphere during the summer months and that can occur in several layers. In this study, we aimed to investigate the relationship between PMSE layers ranging from 80 to 90 km altitude and the solar cycle. We investigated 230 h of observations from the EISCAT very high frequency (VHF) radar located near Tromsø, Norway, from the years 2013, 2014 and 2015 during the solar maximum and the years 2019 and 2020 during the solar minimum and applied a previously developed classification model to identify PMSE layers. Our analysis focused on parameters such as the altitude, thickness and echo power in the PMSE layers, as well as the number of layers present. Our results indicate that the average altitude of PMSEs, the echo power in the PMSEs and the thickness of the layers are, on average, higher during the solar maximum than during the solar minimum. In the considered observations, the electron density at 92 km altitude and the echo power in the PMSEs are positively correlated with the thickness of the layers except for four multilayers at solar minimum. We infer that higher electron densities at ionospheric altitudes might be necessary to observe multilayered PMSEs. We observe that the thickness decreases as the number of multilayers increases. We compare our results with previous studies and find that similar results regarding layer altitudes were found in earlier studies using observations with other VHF radars. We also observed that the bottom layer in the different sets of multilayers almost always aligned with the noctilucent cloud (NLC) altitude reported by previous studies at 83.3 km altitude. Also, an interesting parallel is seen between the thickness of NLC multilayers and PMSE multilayers, where both NLCs and PMSEs have a similar distribution of layers greater than 1 km in thickness. Future studies that include observations over longer periods would make it possible to distinguish the influence of the solar cycle from possible other long-term trends.

High frequency radar error classification and prediction based on K-means methods

This study aims to characterize the high frequency radar and numerically simulated low-frequency filtered currents in the south-eastern Bay of Biscay (study area) using a K-means classification algorithm based on an improved Euclidean Distance calculation method that does not take missing values. The errors between observations and simulations was estimated and predicted based on this classification method. Results indicate that predominantly eastward (northward) currents over the Spanish (French) continental shelf/slope in winter and more variable currents in the west and south-west in summer. The model classification results for circulation characteristics are in relatively good agreement with HF radar results, especially for currents on the Spanish (French) shelf/slope. In addition, the probabilistic relationship between observed and modeled currents was explored, obtaining the probability of occurrence of modeled current groups when each group of observed currents occurs. Finally, predictions of model and observed current errors were made based on the classification results, and it was found that the predictions based on the classification of all data had the smallest errors, with a 17% improvement over the unclassified control experiment. This study provides a foundation for subsequent model error testing, forecast product improvement and data assimilation.

On the Growth and Evolution of Nocturnal Ionospheric Irregularities Using HF Radar Observations Along With Digisonde and GNSS Data Over Trivandrum, India

AbstractThe growth and evolution of nocturnal ionospheric plasma irregularities are analyzed over the geomagnetic equatorial station Trivandrum (8.5°N, 77°E, dip latitude 1.9°N) using multi‐instrumental techniques during various seasons of moderate and high solar activity periods. Irregularities are classified into three categories based on their structure and the vertical extent of radar backscattered echoes as Bottom Type, Top Side, and Bottom Type‐Top Side structures. The presence or absence of energy cascading across different scale sizes is identified from the presence of irregularities as Equatorial Spread F (ESF) in digisonde, scintillation in GNSS and backscattered echoes in HF radar with the signals manifesting sequentially or otherwise in these instruments. Threshold values of the duration (2.25 hr) and altitudinal extent (430 km) of ESF irregularities (observed with the digisonde) required for effective energy cascading across scale sizes are identified. The bottom type irregularity layers are observed to form in the equatorial region, Trivandrum, when the post‐sunset F region height varied within the range of 280–370 km which is broader in comparison to those observed at low latitudes. An empirical model is developed using post‐sunset ionospheric height to predict the maximum altitudinal extent of ESF irregularities. This serves as an indicator of the energy cascading process across scale sizes. The altitudinal extent of irregularities predicted by the empirical model also serves as a proxy for the occurrence of plasma bubbles, which has significant adverse implications for communication and navigation systems.

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

Tsunami Early Warning Using High-Frequency Ocean Radar System in the Kii Channel, Japan

Abstract The tsunami of the 2011 Tohoku earthquake was monitored by the high-frequency (HF) ocean radar system in the Kii Channel, Japan. In this study, we conducted a retrospective analysis of tsunami early warning based on HF radar observations. First, we synthesized the surface current velocity using observation data of two radar land stations: Minato and Saikazaki. After vector synthesis, the time series of current velocity showed high consistency with the results of forward simulation. Then, we used the time series starting from 08:00 (UTC), 11 March 2011, as the input for data assimilation, reconstructing the tsunami wavefield in the Kii Channel. Comparison with actual observations at Kobe showed that our approach can accurately forecast coastal tsunami waveforms at least 50 min prior to tsunami arrival. The normalized prediction error decreased over time, indicating a progressively improving forecast accuracy. This is the first study on tsunami data assimilation using HF radar for the early warning of an actual seismogenic tsunami. We also discussed the limitations of the current HF radar system in the Kii Channel and made suggestions regarding the deployment of future radar land stations.

Estimating Scattering Patch Area for a Direction Finding HF Radar

Estimating Scattering Patch Area for a Direction Finding HF Radar

Kuroshio path variability inferred from satellite-derived sea surface topography in the northwestern Pacific

The Kuroshio has a fundamental impact on the regional oceanography of the northwestern Pacific. But identification of the Kuroshio path (KP), an abstraction of the course along which the Kuroshio mainstream moves, has not yet been established in a systematic manner. We optimally track the KP and study its variability in the northwestern Pacific south of ~31°N, where eddy activity is rich. An automatic contour method based on maximum surface geostrophic velocity along a given satellite-derived dynamic topographic isoline is applied and its performance is evaluated. Our results are robust and can be further used to derive kinematical, statistical, and spectral properties of the flow field of the Kuroshio upstream. We improve the identification method by tracing two separate KPs in different subdomains. The existence of an alignment or mismatch of these two retrieved KPs hints at the arrival of an approaching eddy. The highly variable and distorted KP east of Luzon Strait and Taiwan is due to eddy impingement. Most of the variability along the KP stems from energy with time scales of ~30–200 days and 1 year. A more consistent KP is seen north of ~26°N, with increasing surface currents of up to ~1 m s−1 before entering through the Tokara Strait. Such regional differences result from the various impacts of impinging mesoscale eddies on the Kuroshio, mainly due to blockage by the Ryukyu Islands. Our optimally determined KP is in line with the historical shipborne subsurface velocity measurements revealing the Kuroshio velocity core and observations of strong surface currents of > ~0.5 m s−1 by shore-based high-frequency radar (HFR) from locations along the east coast of Taiwan. Supportive evidence of concurrent KP distortion shows that HFR-derived vortex-like flow patterns are related to mesoscale eddies impinging from regions east of the radar footprint. Our work has value as a supplement to the data from radar operational routines, and will help interpret and diagnose these complicated HFR observations east of Taiwan.

Analysis of Nearshore Near-Inertial Oscillations Using Numerical Simulation with Data Assimilation in the Pearl River Estuary of the South China Sea

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.

Estimating effects of wind and waves on the Doppler centroid frequency shift for the SAR retrieval of ocean currents

Estimating the effects of wind and waves (EWW) on the Doppler centroid frequency shift is a key step in the Synthetic Aperture Radar (SAR) retrieval of ocean currents. However, available models for estimating EWW may exhibit errors as they fail to fully consider the wave and current effects or uncorrected electromagnetic pointing errors. In this study, we corrected the electromagnetic pointing error of Sentinel-1A. In particular, by matching the current data provided by the high-frequency (HF) radar, we accurately obtained the EWW from July 2020 to June 2023. By using the wind and wave parameters provided by the European Centre for Medium-Range Weather Forecasts (ECMWF), the variation characteristics of EWW were analyzed and four geophysical model functions (GMFs) were established using different wave parameters. The application of these GMFs to the retrieval of currents was validated using the HF radar. The optimal current retrieval accuracy in terms of the time series and statistical results was then achieved using the model containing the most comprehensive wave parameters, with a bias of 0.01 m/s and a root mean square error of 0.19 m/s. The proposed model demonstrates the ability to retrieve 100 km scale eddy currents in the Gulf Stream, exhibiting a high agreement with HYbrid Coordinate Ocean Model (HYCOM) reanalysis data, with a bias and root mean square error of approximately −0.03–0.13 m/s and 0.2–0.32 m/s, respectively. The results fully demonstrate that the GMFs established in this study can facilitate the improvement of the SAR retrievals of ocean currents. Moreover, the ability of the proposed model to capture the velocity variations of subscale eddy currents is proved, providing an important tool for oceanographic research.

Assessment of OMA Gap-Filling Performances for Multiple and Single Coastal HF Radar Systems: Validation with Drifter Data in the Ligurian Sea

Assessment of OMA Gap-Filling Performances for Multiple and Single Coastal HF Radar Systems: Validation with Drifter Data in the Ligurian Sea

Coastal current convergence structures in the Bay of Biscay from optimized high-frequency radar and satellite data

The southeastern Bay of Biscay has been described as a “dead end” for floating marine litter, often accumulating along small-scale linear streaks. Coastal Current Convergence Structures (CCS), often associated with vertical motions at river plume edges, estuarine fronts, or other physical processes, can be at the origin of the accumulation. Understanding the formation of CCS and their role in the transport of marine litter is essential to better quantify and to help mitigate marine litter pollution. The Lagrangian framework, used to estimate the absolute dispersion, and the finite-size Lyapunov exponents (FSLE), have proved very effective for identifying CCS in the current velocity field. However, the quality of CCS identification depends strongly on the Eulerian fields. Two surface current velocity data sets were used in the analysis: the remotely sensed velocities from the EuskOOS High-Frequency Radar (HFR) network and velocities from three-dimensional model outputs. They were complemented by drifting buoy velocity measurements. An optimization method, involving the fusion of drifting buoys and HFR velocities is proposed to better reconstruct the fine-scale structure of the current velocity field. Merging these two sources of velocity data reduced the mean Lagrangian error and the Root Mean Square Error (RMSE) by 50 % and 30 % respectively, significantly improving velocity reconstruction. FSLE ridgelines obtained from the Lagrangian analysis of optimized velocities were compared with remotely sensed concentrations of Chlorophyll-a. It was shown that ridgelines control the spatial distribution of phytoplankton. They fundamentally represent the CCS which can potentially affect marine litter aggregation. Analysis of the absolute dispersion revealed large stirring in the alongshore direction which was also confirmed by spatial distribution of FSLE ridgelines. The alignment between FSLE ridgelines and patterns of high Chlorophyll-a concentration was observed, often determining the limits of river plume expansion in the study area.

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.

Estimation of the Wind Field with a Single High-Frequency Radar

Estimation of the Wind Field with a Single High-Frequency Radar

Combined Coherent and Non-Coherent Long-Time Integration Method for High-Speed Target Detection Using High-Frequency Radar

Combined Coherent and Non-Coherent Long-Time Integration Method for High-Speed Target Detection Using High-Frequency Radar

Doppler variations in radar observations of resident space objects: Likely ionospheric Pc1 plasma waves

Radars performing observations of resident space objects (RSO) measure Doppler variations in wave events of several minutes duration, with frequencies in the 0.2–1 Hz range peaking near 0.5–0.7 Hz, consistent with variations in electron density induced by waves in the intervening ionosphere. The two mid-latitude radars used were a Very High Frequency (VHF) radar operating at 55 MHz, and a High Frequency (HF) radar operating at 30 MHz, both in southern Australia.The VHF radar wave observations exibited a peak in wave occurrence in the post-dawn sector (0600–1200 local solar time). The seasonal occurrence of the waves had a strong minimum during winter compared with the other seasons. Comparison between observations in 2018/19 (near solar minimum) and 2021/22 (mid-rise to cycle 25 peak) suggests wave occurrence is anti-correlated with sunspot number and hence with EUV and ionospheric strength. Generally the waves had higher frequencies during night than day, and low sunspot number than mid solar cycle, when there was a weaker ionosphere.Given the oscillation frequency of the wave events, the most likely geophysical phenomena that is consistent with the observations are electro-magnetic ion cyclotron (EMIC) plasma waves in the Pc1 (0.2–5 Hz) frequency range. No other candidate geophysical disturbance appears to fit the wave characteristics. The majority of geomagnetic field-guided transverse Pc1 EMICWs project from the outer magnetosphere down onto the polar ionosphere, where they can convert to compressional fast-mode waves propagating parallel to the Earths surface in the ionospheric F2 layer waveguide, both equatorwards to mid-latitudes and polewards. It is likely the majority of the Doppler oscillations in the Pc1 frequency range observed by the radars at mid-latitudes are these ducted compressional waves. However, sources of transverse EMICWs from the magnetosphere onto the mid-latitude ionosphere do exist, and these may cause some of the observed oscillations. The micro-physics of these compressional waves causing Doppler oscillations in radio observations is not inconsistent with the history of ionospheric Doppler measurements and theory, although the radar trans-ionospheric radio propagation and the observed waves being higher frequency than previous studies is different.If the observed Doppler oscillations are compressional EMICW in the ionospheric waveguide then several of the statistical results can be explained. The anti-correlation of the wave occurrence with sunspot number (and resultant ionospheric strength) can be attributed to lower ionospheric attenuation at the higher latitudes, between where geomagnetically field-guided transverse EMIC waves initially enter the high-latitude ionospheric waveguide from the magnetosphere above, and their observation at mid-latitudes. The observation of higher frequency waves during low sunspot number may also be explained by a source effect in the magnetosphere that preferentially selects the higher frequency field-guided transverse EMIC waves to propagate down to the ionosphere.Comparisons will be shown with results from ground and space based magnetometers of compressional waves in the waveguide, highlighting consistent results and areas where the measurement techniques differ. Theory suggests the radar Doppler measurements are far more sensitive to variations in in-situ ionospheric electron density than magnetic field variations. This agrees with existing literature which highlights the very strong contribution from the compressional component. Theory also suggests that the Doppler sensitivity of a radar to ionospheric electron density variations is frequency dependent, with lower frequencies being more sensitive. This is borne out by the measurements, with the HF radar being more sensitive than the VHF radar.

Near-Surface Dispersion and Current Observations Using Dye, Drifters, and HF Radar in Coastal Waters

Near-Surface Dispersion and Current Observations Using Dye, Drifters, and HF Radar in Coastal Waters

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.

0511 High Frequency Radar for Non-Contact Detection of Respiratory Signals During Sleep

0511 High Frequency Radar for Non-Contact Detection of Respiratory Signals During Sleep

Meagre (Argyrosomus regius) move westward with favourable flows along the south coast of Portugal

Based on acoustic detections from a network of five stations along the south coast of Portugal, 25 transits of tagged meagre were identified between 2019 and 2020, mostly in summer. Comparisons with hourly current measurements from a moored Acoustic Doppler current Profiler and an High Frequency Radar system indicate that meagre move westward with favourable alongshore flows at a confidence level >90% (while eastward transits observations were too few to be significant). Several similar transits of different individuals occurred within two days suggesting a species response to environmental changes. The analysis of surface seawater temperature from ERA5 shows that meagre always swam westward towards colder water, despite their warm water affinities. As such, they reached food-rich upwelling areas when the water temperature was higher than usual (due to the westward advection of warm water), probably optimizing their feeding ability. The demonstrated alongshore meagre movements in response to temperature variations induced by the mesoscale coastal circulation is particularly relevant for the management of this high economic value species in southern Portugal.

Quantifying the role of submesoscale Lagrangian transport features in the concentration of phytoplankton in a coastal system

Abstract Food resources in the ocean are often found in low densities, and need to be concentrated for efficient consumption. This is done in part by oceanographic features transporting and locally concentrating plankton, creating a highly patchy resource. Lagrangian approaches applied to ocean dynamics can identify these transport features, linking Lagrangian transport and spatial ecology. However, little is known about how Lagrangian approaches perform in ageostrophic coastal flows. This study evaluates two Lagrangian Coherent Structure metrics against the distribution of phytoplankton; Finite Time Lyapunov Exponents (FTLE) and Relative Particle Density (RPD). FTLE and RPD are applied to High Frequency Radar (HFR) observed surface currents within a biological hotspot, Palmer Deep Canyon Antarctica. FTLE and RPD identify different transport patterns, with RPD mapping single particle trajectories and FTLE tracking relative motion of paired particles. Simultaneous measurements of circulation and phytoplankton were gathered through the integration of vessel and autonomous glider surveys within the HFR footprint. Results show FTLE better defined phytoplankton patches compared to RPD, with the strongest associations occurring in stratified conditions, suggesting that phytoplankton congregate along FTLE ridges in coastal flows. This quantified relationship between circulation and phytoplankton patches emphasizes the role of transport in the maintenance of coastal food webs.