Ionospheric Clutter Suppression with an Auxiliary Crossed-Loop Antenna in a High-Frequency Radar for Sea Surface Remote Sensing

Ionospheric clutter is one of the main problems for high-frequency surface wave radars (HFSWRs), as it severely interferes with sea surface state monitoring and target detection. Although a number of methods exist for ionospheric clutter suppression, most are suitable for radars with a large-sized array and are inefficient for small-aperture radars. In this study, we added an auxiliary crossed-loop antenna to the original compact radar antenna, and used an adaptive filter to suppress the ionospheric clutter. The experimental results of the HFSWRs data indicated that the suppression factor of the ionospheric clutter was up to 20 dB. Therefore, the Bragg peaks that were originally submerged by the ionospheric clutters could be recovered, and the gaps in the current maps can, to a large extent, be filled. For an oceanographic radar, the purpose of suppressing ionospheric clutter is to extract an accurate current speed; the radial current fields that were generated by our method showed an acceptable agreement with those generated by GlobCurrent data. This result supports the notion that the ionospheric suppression technique does not compromise the estimation of radial currents. The proposed method is particularly efficient for a compact HFSWRs, and can also be easily used in other types of antennas.

High-Frequency radar measurements with CODAR in the region of Nice: improved calibration and performance

We report on the installation and first results of one compact oceanographic radar in the region of Nice for a long-term observation of the coastal surface currents in the North-West Mediterranean Sea. We describe the specific processing and calibration techniques that were developed at the laboratory to produce high-quality radial surface current maps. In particular, we propose an original self-calibration technique of the antenna patterns, which is based on the sole analysis of the database and does not require any shipborne transponder or other external transmitters. The relevance of the self-calibration technique and the accuracy of inverted surface currents have been assessed with the launch of 40 drifters that remained under the radar coverage for about 10 days.

Using Artificial Neural Networks for the Estimation of Subsurface Tidal Currents from High-Frequency Radar Surface Current Measurements

An extensive record of current velocities at all levels in the water column is an indispensable requirement for a tidal resource assessment and is fully necessary for accurate determination of available energy throughout the water column as well as estimating likely energy capture for any particular device. Traditional tidal prediction using the least squares method requires a large number of harmonic parameters calculated from lengthy acoustic Doppler current profiler (ADCP) measurements, while long-term in situ ADCPs have the advantage of measuring the real current but are logistically expensive. This study aims to show how these issues can be overcome with the use of a neural network to predict current velocities throughout the water column, using surface currents measured by a high-frequency radar. Various structured neural networks were trained with the aim of finding the network which could best simulate unseen subsurface current velocities, compared to ADCP data. This study shows that a recurrent neural network, trained by the Bayesian regularisation algorithm, produces current velocities highly correlated with measured values: r2 (0.98), mean absolute error (0.05 ms−1), and the Nash–Sutcliffe efficiency (0.98). The method demonstrates its high prediction ability using only 2 weeks of training data to predict subsurface currents up to 6 months in the future, whilst a constant surface current input is available. The resulting current predictions can be used to calculate flow power, with only a 0.4% mean error. The method is shown to be as accurate as harmonic analysis whilst requiring comparatively few input data and outperforms harmonics by identifying non-celestial influences; however, the model remains site specific.

A Novel Approach for Permittivity Estimation of Lunar Regolith Using the Lunar Penetrating Radar Onboard Chang’E-4 Rover

Accurate relative permittivity is essential to the further analysis of lunar regolith. The traditional hyperbola fitting method for the relative permittivity estimation using the lunar penetrating radar generally ignored the effect of the position and geometry of antennas. This paper proposed a new approach considering the antenna mounting height and spacing in more detail. The proposed method is verified by numerical simulations of the regolith models. Hence the relative permittivity of the lunar regolith is calculated using the latest high-frequency radar image obtained by the Yutu-2 rover within the first 24 lunar days. The simulation results show that the relative permittivity is underestimated when derived by the traditional method, especially at the shallow depth. The proposed method has improved the accuracy of the estimated lunar regolith relative permittivity at a depth of 0–3 m, 3–6 m, and 6–10 m by 35%, 14%, and 9%, respectively. The thickness of the lunar regolith at the Chang’E 4 landing site is reappraised to be 11.1 m, which improved by ~8% compared with previous studies.

Observations of Surface Currents and Tidal Variability Off of Northeastern Taiwan from Shore-Based High Frequency Radar

A network of high-frequency radars (HFRs) has been deployed around Taiwan. The wide-area data coverage is dedicated to revealing near real-time sea-surface current information. This paper investigates three primary objectives: (1) describing the seasonal current synoptic variability; (2) determining the influence of wind forcing; (3) describing the tidal current field pattern and variability. Sea surface currents derived from HFR data include both geostrophic components and wind-driven components. This study explored vector complex correlations between the HFR time series and wind, which was sufficient to identify high-frequency components, including an Ekman balance among the surface currents and wind. Regarding the characteristics of mesoscale events and the tidal field, a year-long high-resolution surface dataset was utilized to observe the current–eddy–tide interactions over four seasons. The harmonic analysis results derived from surface currents off of northeastern Taiwan during 2013 are presented. The results agree well with the tidal parameters estimated from tide-gauge station observations. The analysis shows that this region features a strong, mixed, mainly semidiurnal tide. Continued monitoring by a variety of sensors (e.g., satellite and HFR) would improve the understanding of the circulation in the region.

Evaluating high-frequency radar data assimilation impact in coastal ocean operational modelling

The impact of the assimilation of HFR (high-frequency radar) observations in a high-resolution regional model is evaluated, focusing on the improvement of the mesoscale dynamics. The study area is the Ibiza Channel, located in the western Mediterranean Sea. The resulting fields are tested against trajectories from 13 drifters. Six different assimilation experiments are compared to a control run (no assimilation). The experiments consist of assimilating (i) sea surface temperature, sea level anomaly, and Argo profiles (generic observation dataset); the generic observation dataset plus (ii) HFR total velocities and (iii) HFR radial velocities. Moreover, for each dataset, two different initialization methods are assessed: (a) restarting directly from the analysis after the assimilation or (b) using an intermediate initialization step applying a strong nudging towards the analysis fields. The experiments assimilating generic observations plus HFR total velocities with the direct restart provide the best results, reducing by 53 % the average separation distance between drifters and virtual particles after the first 48 h of simulation in comparison to the control run. When using the nudging initialization step, the best results are found when assimilating HFR radial velocities with a reduction of the mean separation distance by around 48 %. Results show that the integration of HFR observations in the data assimilation system enhances the prediction of surface currents inside the area covered by both antennas, while not degrading the correction achieved thanks to the assimilation of generic data sources beyond it. The assimilation of radial observations benefits from the smoothing effect associated with the application of the intermediate nudging step.

Frontal Waves in the East of the Tsugaru Strait Revealed by the High-Frequency Radar Observation

Surface velocity observations of the eastern part of the Tsugaru Strait made by the high-frequency radar revealed frequent occurrence of frontal waves along the axis of the Tsugaru Warm Current in 2017–2019. The current axis (maximum of the zonal velocity in the meridional direction) disturbed in the north–south direction with period of ~ 13.7 days that is dominant timescale of tide modulation in the strait, in addition to that of ~ 27.3 days. The amplitude of the axis fluctuation increased in the downstream direction, from the eastern neck of the channel (~ 141.0°E) to the outlet of the strait adjacent to the Pacific Ocean (~ 141.5°E). The propagation speed of the disturbance was slower than that due to surface advection especially in the seasons when the stratification was developed, and agreed well with that estimated from the theory based on the two-layer baroclinic instability model except for winter. The north–south modulation of the axis at the outlet of the strait (~ 141.5°E) could cause short-term (from 20 days to 1 month) variations of an anticyclonic gyre of the Tsugaru Warm Current that is developed in the east of the outlet from summer to autumn reported by the previous studies.