High-resolution High-frequency Research Articles

Spatio-temporal variability of coastal upwelling using high resolution remote sensing observations in the Bay of Bengal

The work investigated the tempo-spatial variability of coastal upwelling through high-resolution High-Frequency (HF) radar-derived ocean current and other remote sensing observations on the northwest coast of the Bay of Bengal in 2018. Sea Surface Temperature (SST) showed a coastal upwelling signature only during April and May despite upwelling-favorable winds throughout the southwest monsoon. Stratified coastal water and coastal-trapped downwelling Kelvin waves suppressed the upwelling on the western coast from June. Improved fidelity was available from sea surface temperature (SST) and cross-shore surface current (CSSC) components of HF radar-derived ocean surface current, which showed strong consistency in detecting actual coastal upwelling from April to the first week of June. Coastal upwelling events consisted of six phases; three active phases and each followed by three break phases. The active phases of the coastal upwelling from SST lasted for about 15, 6, and 9 days, with a horizontal extension of 105 km, 75 km, and 140 km. The horizontal extension of strong positive CSSC during the first and third phases was over 135 km, while being 75 km during the second active phase. The duration of the active phase and the strong CSSC directly influence the horizontal extension of the upwelled colder water. High resolution (6.25 km) swath data helps to show that the weakening of wind shear near the coast started two days before the start of the second break phase in SST, which could not be captured in 25 km gridded winds. The altimetry track data of sea level anomalies obtained from different sensors for different days also captured the different upwelling phases. A large concentration of Chl-a near the coast, as observed in the chlorophyll-a monthly mean result, suggested the occurrence of coastal upwelling. However, the temporal variability could not be elucidated due to the low temporal coverage of Chl-a data. The active and break phases of the coastal upwelling are explained by associated air-sea interactions. This study suggests that HF radar data is beneficial for monitoring the high spatio-temporal variability of coastal upwelling, and high resolution swath data from the scatterometer is crucial for understanding the variability of coastal upwelling.

Infrared image super-resolution using auxiliary convolutional neural network and visible image under low-light conditions

Convolutional neural networks (CNN) have been successfully applied to visible image super-resolution (SR) methods. In this study, we propose a CNN-based SR algorithm for up-scaling near-infrared (NIR) images under low-light conditions, using corresponding visible images. Our algorithm first extracts high-frequency (HF) components from the up-scaled low-resolution (LR) NIR image and its corresponding high-resolution (HR) visible image, and then takes them as multiple inputs of the CNN. Next, the CNN outputs the HR HF component of the input NIR image. Finally, an HR NIR image is synthesized by adding the HR HF component to the up-scaled LR NIR image. The simulation results show that the proposed algorithm outperforms the state-of-the-art methods, in terms of both qualitative and quantitative aspects.

Kuroshio variations in the upstream region as seen by HF radar and satellite altimetry data

Variations of the position and speed of the Kuroshio are studied by a combination of high‐resolution high‐frequency (HF) ocean radar data and wide‐coverage altimetry data. The speed of the Kuroshio and its position are determined along 123.35° E northeast of Taiwan from daily maps of surface geostrophic velocity estimated from HF radar data from August 2001 to February 2005. These two are found to be well correlated for mesoscale variations with periods of a few months, as the Kuroshio tends to be faster (or slower) when its axis moves south (or north). This tendency is significant in summer when the Kuroshio is seasonally intensified and well‐defined in the HF radar data. By taking correlation with the sea surface dynamic height anomaly observed by satellite altimeters, these Kuroshio variations in the East China Sea are found to be induced by merging of mesoscale eddies from the east at 21° N and by coincident Kuroshio meanders east of Taiwan.

Ship detection with high-resolution HF skywave radar

This paper presents an overview of ship detection by high-frequency (HF) skywave backscatter over-the-horizon radar (OTHR). Ships have been detected at ranges of 2000 km or more by OTHR that uses sufficient resolution in the radar spatial and Doppler frequency domains. The HF sea-echo Doppler spectrum limits the target signal-to-clutter ratio (SCR), as a function of the ocean wave-height distribution, wind direction, radio frequency, and ship target radial velocity. Maximum sea-clutter spectrum purity, and hence larger SCR, is achieved with the use of stable single-mode ionospheric propagation. Real-time measurement and interpretation of ionospheric propagation features therefore must guide the choice of OTHR operating frequency. Experimental data recorded at the ONR/SR1 Wide Aperture Research Facility (WARF) bistatic OTHR in central California demonstrate reliable ship detection in the Northeast Pacific Ocean. WARF transmits 1-MW average effective radiated power, using a linear frequency-modulated continuous-wave (FMCW) waveform, and receives with a 2.55-km broadside array of vertical monopole element pairs. Swept bandwidths as high as 200 kHz have been used. Sufficient spectral resolution is achieved with a coherent integration time (CIT) of 12.8 s. Longer CIT, and autoregressive (AR) spectral analysis techniques such as Marple's algorithm, have been used to improve Doppler resolution.