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Harnessing ocean kinetic energy has emerged as a promising renewable energy solution in recent years. However, identifying optimal locations for extracting this energy remains a significant challenge. This study presents a novel scheme to estimate the total surface current (TSC) as permanent surface current by integrating geodetic data and in-situ measurements. The TSC is typically a combination of the geostrophic current, derived from dynamic topography, and the Ekman current. We utilize NOAA's Ekman current data to complement the geostrophic current and obtain the TSC. To further enhance the accuracy of the TSC estimates, we employ a 3DVAR data assimilation method, incorporating local current meter observations. The results are verified against two control current meter stations. The data-assimilation process resulted in an improvement of 4 to 15 cm/s in the precision of calculated TSC. Using the assimilated TSC data, we then assess the kinetic energy potential and identify six regions with the most significant promise for marine kinetic energy extraction. This innovative approach can assist researchers and policymakers in targeting the most suitable locations for harnessing renewable ocean energy. [ABSTRACT FROM AUTHOR]

The recurring occurrence of green tides as an ecological disaster has been reported annually in the Yellow Sea. While remote sensing technology effectively tracks the scale, extent, and duration of green tide outbreaks, there is limited research on the underlying driving mechanisms of green tide drift transport and the determination of the leeway coefficient. This study investigates the green tide transport mechanism and evaluates the feasibility of estimating the leeway coefficient by analyzing green tide drift velocities obtained from Geostationary Ocean Color Imager-II (GOCI-II) images using the maximum cross-correlation (MCC) technique and leeway method across various time intervals alongside ocean current and wind speed data. The results reveal the following: (1) Significant spatial variations in green tide movement, with a distinct boundary at 34°40′N. (2) Short-term green tide transport is primarily influenced by tidal forces, while wind and ocean currents, especially the combined Ekman and geostrophic current component, predominantly govern net transport. (3) Compared to 1, 3, and 7 h intervals, estimating the leeway coefficient with a 25 h interval is feasible for moderate-resolution geostationary images, yielding values consistent with previous studies. This study offers new insights into exploring the transport mechanisms of green tides through remote sensing-driven velocity. [ABSTRACT FROM AUTHOR]

In order to address the issue of limited common coverage and high cost in mapping ocean surface vector current by two (or more) high-frequency surface wave radars, this paper proposes a single-station surface wave radar vector current inversion algorithm. The feasibility of this algorithm has been validated in the Taiwan Strait. Based on the ocean dynamic characteristics of the Taiwan Strait, the algorithm utilizes the radial current obtained from a high-frequency surface wave radar (HFSWR) in Fujian Province to invert the ocean surface vector current. The surface vector current can be decomposed into three primary dynamic components: tidal currents, wind-driven currents, and geostrophic currents. Firstly, tidal current forecasting models and Ekman and Stokes theories are used to calculate the tidal and wind-driven currents in the Taiwan Strait, respectively. Subsequently, the directions of geostrophic currents in the Taiwan Strait are determined with sea surface height data, and the magnitudes of the geostrophic currents are constrained using the radial current from the single HFSWR. Finally, the three components are added together to obtain the vector current. Comparative results demonstrate that the efficacy of the algorithm has been validated through field experiments (with two HFSWRs and two drifting buoys) conducted in the southwestern of the Taiwan Strait. Further research is needed on the applicability of this algorithm to other sea areas and monitoring systems. [ABSTRACT FROM AUTHOR]

For the past 20 years, Global Navigation Satellite System reflectometry (GNSS-R) technology has successfully shown its potential for remote sensing of the Earth's surface, including ocean and land surfaces. It is a multistatic radar that uses the GNSS signals reflected from the Earth's surface to extract land and ocean characteristics. Because of its numerous advantages such as low cost, multiple signal sources, and all-day/weather and high-spatiotemporal-resolution observations, this new technology has attracted the attention of many researchers. One of its most promising applications is GNSS-R ocean altimetry, which can complement existing techniques such as tide gauging and radar satellite altimetry. Since this technology for ocean altimetry was first proposed in 1993, increasing progress has been made including diverse methods for processing reflected signals (such as GNSS interferometric reflectometry, conventional GNSS-R, and interferometric GNSS-R), different instruments (such as an RHCP antenna with one geodetic receiver, a linearly polarized antenna, and a system of simultaneously used RHCP and LHCP antennas with a dedicated receiver), and different platform applications (such as ground-based, air-borne, or space-borne). The development of multi-mode and multi-frequency GNSS, especially for constructing the Chinese BeiDou Global Navigation Satellite System (BDS-3), has enabled more free signals to be used to further promote GNSS-R applications. The GNSS has evolved from its initial use of GPS L1 and L2 signals to include other GNSS bands and multi-GNSS signals. Using more advanced, multi-frequency, and multi-mode signals will bring new opportunities to develop GNSS-R technology. In this paper, studies of GNSS-R altimetry are reviewed from four perspectives: (1) classifications according to different data processing methods, (2) different platforms, (3) development of different receivers, and (4) our work. We overview the current status of GNSS-R altimetry and describe its fundamental principles, experiments, recent applications to ocean altimetry, and future directions. [ABSTRACT FROM AUTHOR]

The coastal ocean off western Patagonia is one of the main coastal regions with high freshwater inputs from rivers, rain, and glaciers in the Southern Hemisphere. This study conducts an analysis of the seasonal and interannual variations in sea surface salinity and meridional geostrophic transports, specifically focusing on the Cape Horn Current, using improved satellite-derived data of sea surface salinity (SSS) and geostrophic velocities spanning an ∼11-year period (September 2011–August 2022). Our results reveal a clear salinity minimum in a coastal band between 42–54°S associated with the highest freshwater content. The average geostrophic currents are stronger south of 49°S, in line with the location of the Cape Horn Current. The average salinity minimum tends to disappear south of 54°S, with salinity values increasing slightly southward. The seasonal cycle of salinity shows the most pronounced minimum in summer (∼33.2–33.4). The greatest variability in salinity (standard deviation of salinity fields) occurs in the southern region of the Cape Horn Current. Hovmöller plots reveal two cores of minimum salinity observed in spring and summer (∼33.3–33.4). The freshwater off the Gulf of Penas contributes to the northern core. The meridional geostrophic transport differs between the northern and southern sections, with transports predominantly towards the Equator (Pole) north (south) of about 47–48°S during spring–summer. There is a marked seasonal variability in the magnitude and northern limit of the southward-flowing Cape Horn Current, being extended further north during winter and with a maximum average magnitude during summer–fall (about − 2 × 10 4 m2 s−1). On the interannual scale, a major drop in surface salinity occurred off northern and central Patagonia during 2018–2019. Finally, a potential long-term freshening trend is observed in the coastal area off southern Patagonia (south of 52°S), although prolonged data records are essential to confirm this pattern. [ABSTRACT FROM AUTHOR]

We present a study on the ocean surface currents reconstruction by merging Level-4 (L4, gap-free) altimeter-derived geostrophic currents and satellite sea surface temperature. Building upon past studies on the multi-variate reconstruction of geostrophic currents from satellite observations, we regionalized and optimized an algorithm to improve the altimeter-derived surface circulation estimates in the North Atlantic Ocean. A ten-year-long time series (2010–2019) is presented and validated by means of in situ observations. The newly optimized algorithm allowed us to improve the currents estimate along the main axis of the Gulf Stream and in correspondence of well-known upwelling areas in the North Eastern Atlantic, with percentage improvements of around 15% compared to standard operational altimetry products. [ABSTRACT FROM AUTHOR]

We present a study on the ocean surface currents reconstruction by merging Level-4 (L4, gap-free) altimeter-derived geostrophic currents and satellite sea surface temperature. Building upon past studies on the multi-variate reconstruction of geostrophic currents from satellite observations, we regionalized and optimized an algorithm to improve the altimeter-derived surface circulation estimates in the North Atlantic Ocean. A ten-year-long time series (2010–2019) is presented and validated by means of in situ observations. The newly optimized algorithm allowed us to improve the currents estimate along the main axis of the Gulf Stream and in correspondence of well-known upwelling areas in the North Eastern Atlantic, with percentage improvements of around 15% compared to standard operational altimetry products.