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This paper investigates the physical-layer security for water-to-air (W2A) visible light communication (VLC). The impacts of surface fluctuation and underwater scattering on the channel gain are theoretically analyzed, which is verified in a laboratory W2A-VLC link. The statistical properties of wave slope under experimental conditions are measured by image processing and the probability density function of the slope can be approximated by a logistic distribution. We observe that dynamic waves can cause information leakage and experimental results indicate that the probability of secure communication increases from 90.39% to 96.18% as the eavesdropper’s elevation increases from 1.15 m to 1.42 m, which are approximately consistent with the numerical results. To investigate the parameters affecting the secrecy performance, several secrecy performance metrics are numerically calculated under different wave intensities, eavesdropper’s locations, divergence angles of LED, underwater scattering coefficients and wavelengths of transmitted beam. It is seen that the secrecy performance is degraded as the wave intensity increases, while random scattering can mitigate the water surface fluctuations and reduce the probability of information leakage. [ABSTRACT FROM AUTHOR]

Cooperative transmission is a promising solution for reliable communication in underwater acoustic sensor networks. To fully exploit the benefits of cooperative system, efficient management of relay resources is required. However, the challenging working conditions, including imprecise channel information, limited observation feedback and dynamic underwater environment, call for an adaptive relay selection strategy for improving system capacity performance. In this paper, we present an innovative Partial Expert-based Reinforcement Adversarial Learning (PER-AL) strategy that unifies expert assisted learning and self-adjusting learning in a integral adversarial multi-armed bandit framework. The user constantly interacts with the environment and optimizes the relay decision by analyzing all gathered observation rewards, rather than relying on prior channel information. By introducing a novel expert learning mechanism into the initial learning stage, expert generator and expert learner are proposed to control the performance of experts and provide optimal expert advice to reinforce the initial relay learning for efficiency. With the deepening learning, the relay quality is then evaluated by analyzing the historical observable rewards directly through a Exp3 policy without engaging complexity too much. The proposed algorithm could automatically adapt to the underwater conditions and detect the optimal relay within a short time, significantly improving system capacity without jeopardizing the adversarial regret guarantee. Finally, extensive simulation results demonstrated the superior of PER-AL algorithm compared with recent existing CSI-based and CSI-free solution benchmarks. Particularly, PER-AL algorithm has a 28.3% improvement of the total network capacity and achieves a 44.5% decrease of implementation time. [ABSTRACT FROM AUTHOR]

In the field of physical oceanography, the temperature and pressure of seawater are important fundamental parameters. In order to realize the simultaneous measurement of the temperature and pressure in seawater, a reflective optical fiber sensor based on polydimethylsiloxane (PDMS)-sealed optical microfiber coupler combined with a sagnac loop (OMCSL) is proposed. Benefiting from the high thermo-optical coefficient and large elasticity of PDMS, and the large-scale swift field transmission characteristics of optical microfiber coupler (OMC), the sensitivity and structural stability of our sensor is largely improved. The response performance of the sensor is further analyzed by numerical simulation calculations and theoretical modeling. Experimental results show that the temperature and pressure sensitivity of the sensor could reach −2.133 nm/°C and 3.416 nm/Mpa, respectively, about one order higher than that of bare fiber OMCSL. Furthermore, via inversely calculating the cross-sensitivity matrix, the temperature and pressure sensing can be demodulated simultaneously, and the average errors of the preliminary experimental settlements are 1.61% and 5.02%, respectively. Due to the merits of compact structure, easy fabrication, high sensitivity, fast response speed and high stability, the basic performance of this dual parametric sensor is comparable to the existing electrical temperature-depth (TD) sensor, which is expected to meet the practical application requirements of marine environmental monitoring and ocean dynamics research. [ABSTRACT FROM AUTHOR]

Oceanic eddy is the ubiquitous ocean flow phenomenon, which has been the key factor in the transportation of ocean energy and materials. Consequently, oceanographic understanding can be enhanced by the intelligent identification of eddy. State-of-the-art deep learning technologies are gradually improving identification methods. This letter proposes the pyramid split attention (PSA) eddy detection U-Net architecture (PSA-EDUNet) that targets oceanic eddy identification from ocean remote sensing imagery. As for the PSA-EDUNet, its inspiration comes from U-Net, which contains encoder and decoder parts, making the integration of inferior and senior features efficient and ensuring the feature information will not be lost in large quantities through nonlinear connection mode. Meanwhile, the PAS module is introduced to enhance feature extraction. In terms of the fusion data, the sea surface feature is the main criterion of eddy identification, including sea surface temperature (SST) and sea level anomaly (SLA). The experiments are implemented on the Kuroshio Extension (KE) and the South Atlantic regions, the results demonstrate that the proposed method can outperform other methods, especially for eddy edges and small-scale eddies. [ABSTRACT FROM AUTHOR]

This article presents a simulated and experimental analysis of the effects of the evaporation duct on microwave propagation in the Irish Sea. The evaporation duct is a phenomenon that occurs almost permanently over all the world’s oceans and allows electromagnetic waves to travel beyond the horizon. Weather data logged over several years from four buoys off the east coast of Ireland has been analyzed to find the probability and strength of the evaporation duct. Signal propagation in the evaporation duct has been simulated using the parabolic equation model and compared to results obtained from an experimental setup in the Irish Sea. The best antenna heights and frequencies to maximize signal propagation at this location are also found. Results show that the evaporation duct can be used to provide high bandwidth communications beyond the horizon with an uptime of approximately 40%, and that weather data from buoys can be used to predict the performance of the communications link. While this method of communication is not one that can be relied on all the time, it could be useful to reduce dependency on expensive satellite links or provide nontime critical communications. [ABSTRACT FROM AUTHOR]

This study explores the degradation of the reactive Remazol Blue RR (RBRR) as a model textile effluent upon its exposure to non-thermal atmospheric pressure plasma. An extensive comparative study of different combinations of the following plasma/solution treatment environments was conducted: 1) Ar plasma jet (Ar-PJ) alone; 2) Ar/O2 and Ar/N2 plasmas; 3) Ar plasma with O2 or N2 injected (INJ) in the bulk of the Ar plasma afterglow; and 4) Ar plasma with O2 or N2 bubbling (BB) in the RBRR solution. In all conditions, plasma treatment was carried out at a fixed applied voltage of 31 kV and treatment time of 10 min. The degradation efficiency of RBRR in the different plasma-treated solutions was evaluated using UV–visible spectroscopy. Optical emission spectroscopy (OES) was used to examine the generation of excited species in plasma during the degradation processes. Moreover, the concentration of plasma-induced reactive hydroxyl radicals (OH•) and hydrogen peroxide (H2O2) was determined spectroscopically. To further corroborate the results, the pH, conductivity, and total organic carbon (TOC) of the plasma-treated RBRR solutions were assessed. Overall, the results showed that the highest degradation efficiency (45%) was obtained upon exposure of RBRR aqueous solution to Ar plasma with N2 bubbling in the solution. The non-toxic nature of all plasma-treated solutions was confirmed by non-inhibition of bacterial growth (Escherichia coli and Staphylococcus aureus). Overall, plasma treatment in general and Ar plasma accompanied with N2 bubbling in particular constitute an eco-friendly and very promising techniques to degrade/decolorize textile effluent. [ABSTRACT FROM AUTHOR]

Investigations of the effects of clouds on Earth’s radiation budget demand accurate representations of cloud top parameters, which can be efficiently obtained by large-scale satellite remote sensing approaches. However, the insufficient utilization of multiband information is one of the major sources of uncertainty in cloud top products derived from geostationary satellites. In this study, we developed a new algorithm to estimate Cloud, Atmospheric Radiation and renewal Energy application (CARE) version 1.0 cloud top properties [cloud top height (CTH), cloud top pressure (CTP), and cloud top temperature (CTT)]. The algorithm is constructed from ten thermal spectral measurements in Himawari-8 observations by using the random forest (RF) method to comprehensively consider the contribution of each band to the cloud top parameters. We chose the highly accurate Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) products in 2018 as the true values. The sensitivity analysis demonstrated that the products can be fully reproduced by using multiple Himawari-8 channels with the addition of the digital elevation model (DEM) data. The validation results of the 2019 CALIOP data confirm that the new algorithm shows an effective performance, with correlation coefficients ($R$) of 0.89, 0.89, and 0.90 for CTH, CTP, and CTT, respectively. Moreover, a significant improvement in the ice cloud estimation is achieved, in which the CTT $R$ value increased from 0.46 to 0.70, as well as an improvement in the sea area, where the CTT $R$ value increased from 0.71 to 0.84 compared with the Himawari-8 products of the Japan Aerospace Exploration Agency (JAXA) P-tree system. The further analyses performed here capture the diurnal cycle of cloud top parameters well in different temporal scales over the Asia–Pacific region. [ABSTRACT FROM AUTHOR]

Arctic sea-ice thickness and salinity retrievals are simulated to explore the performance of nadir-observing microwave radiometry operating with up to 16 frequency channels in the 0.5–2-GHz frequency range. A radiative transfer model is used to create lookup tables of the circularly polarized thermal emissions of first-year (FY) and multiyear (MY) sea ice, and the performance of two distinct retrieval methods is examined. The first method retrieves only sea-ice thicknesses, while the second retrieves both ice thickness and ice salinity. Retrieval errors are simulated for both FY and MY sea ice as a function of ice thickness, salinity, and temperature to investigate the impact of radiometric uncertainty, the frequency channels used, and any errors in ancillary information. To gain further insight into Arctic scale retrieval performance, a simulated brightness temperature dataset is produced for Arctic sea ice for the period October 2020–March 2021 using sea-ice thicknesses from the SMOS-CryoSat-2 algorithm. Compared to existing sea-ice thickness retrievals obtained from 1.4-GHz microwave radiometers, the results demonstrate that 0.5–2-GHz radiometry can achieve higher sensitivity to a sea-ice thickness within the range 0.5–1.5 m for FY sea ice and enable the retrieval of multiple sea-ice parameters (thickness and salinity) simultaneously. [ABSTRACT FROM AUTHOR]

The development of more electric aircraft (MEA) has accelerated in recent years. Power converter systems for MEA require higher reliability compared with the conventional power converter systems as well as higher energy efficiency. A power device at high altitude might break down at a certain rate because of cosmic rays. Thus, it is necessary to carefully consider the reliability of single event burnout together with the converter design. This study examines a failure in time (FIT) rate comparison among three different inverter configurations using 3.3-kV and 6.5-kV full SiC power modules (FSPMs) under several operating conditions. It presents module and inverter configuration selection criteria in consideration of the FIT rate. In addition, the transitions of FIT rates during the flight are calculated using actual flight data to help the power converter system designers understand how the FIT rate should be considered. Furthermore, this study verifies a high-frequency switching operation at various bus voltages for a 6.5-kV FSPM and the power loss calculation for MEA applications. [ABSTRACT FROM AUTHOR]

Due to the continuous intensification of human activities in the ocean, the frequent outbreaks of red tide have caused great harm to the marine environment and ecology. Thus, the rapid detection and monitoring of red tide become particularly important. At present, the main monitoring methods depend on artificial and buoy data, as well as optical satellite remote sensing. However, these methods may not be able to effectively deal with the characteristics of red tide bloom, such as suddenness and unpredictability. The global navigation satellite system-reflectometry (GNSS-R) is an emerging technology that makes use of navigation signals as a remote sensing opportunity to obtain Earth surface information. GNSS-R has already been proved to be capable of retrieving sea surface parameters (e.g., dielectric constant and sea surface roughness) closely related to the outbreak of a red tide. In this article, we proposed a new method to estimate red tide density, which utilizes an all-new model associating GNSS-R observations with sea surface red tide density. This method can remove the weather influence and greatly decrease the revisit period, which is much longer for optical red tide remote sensing methods. The Landsat-8 near-infrared data and TechDemoSat-1 (TDS-1) GNSS-R data of a red tide outbreak in the sea off the Tsingtao coast in China are used to build and test the proposed method. The results demonstrate that the correlation coefficient is 0.73, and the root mean square error of retrieved red tide density is 2.84%, which shows that the GNSS-R technology shows great potential to perform the rapid and preliminary red tide monitoring and judgment. [ABSTRACT FROM AUTHOR]

Natural gas flaring (GF) is a longstanding problem for the oil industry. Recent estimates indicate that this phenomenon has increased to levels recorded a full decade earlier. While in 2020 there was a decline in global GF due to COVID-19 pandemic, data suggest that GF continues to be a persistent issue, with solutions remaining difficult or uneconomical in certain countries. Nighttime satellite products are widely used to map and monitor GF affected areas, partially filling the general lack of information from oil companies and/or national reporting. In this work, we assess the potential of daytime infrared satellite observations at high spatial resolution from operational land imager (OLI) and multispectral instrument (MSI) sensors, respectively, onboard Landsat-8 (L8) and Sentinel-2 (S2) satellites, in monitoring GF activity. The normalized hotspot indices (NHI) algorithm is used for this purpose, testing its performance over six different GF sites. Results show the NHI capability in providing accurate information about GF-related thermal (e.g., 100% of detections offshore; up to 92% onshore), despite some limitations due to clouds and smoke. They open challenging scenarios regarding the possibility of quantifying the volume of emitted gas from daytime S2-MSI and L8-OLI data, integrating information from well-established nighttime operational systems. [ABSTRACT FROM AUTHOR]

The objective of this work is the statistical characterization of the angle of arrival (AoA) at the receiver due to scattering from a random sea surface. The sea surface is represented using the sum of sinusoids (SoS) and modeled using the JOint North Sea WAve Project (JONSWAP) sea wave spectrum. The random behavior of potential scatterers along the sea surface, surface wave height, and their impact on the distribution of AoA is evaluated. For coherent scattering, initially, the scatterer distribution is computed for a single realization of the SoS, i.e., a sinusoidal surface. The result obtained is averaged to evaluate the characteristics of the ensemble-averaged SoS surface. For incoherent scattering, the acute randomness of the sea surface leads to every point along the SoS surface acting as a potential scatterer. The overall scattering for any given channel state would be an appropriate combination of coherent and incoherent components. A similar effect manifests itself in the distribution of the overall AoA. Further, the impact of factors such as acoustic signal frequency, wind speed, and the underwater (UW) channel geometry on the parameters of the overall AoA has been studied. The AoA model proposed in this work is general and widely applicable. [ABSTRACT FROM AUTHOR]

This study proposes an experimental implementation of temperature sensing system to study the enhanced Vernier effect using two polydimethylsiloxane (PDMS)-cavity Fabry-Perot interferometers (FPIs) arranged in parallel. However, these devices exhibited opposite responses to temperature; that is, with an increase (or decrease) in temperature, the two FPIs shifted in red and blue wavelength directions, respectively. This indicated that the sensitivity amplification of their parallel configuration was considerably larger than that generated by the traditional Vernier effect. Experimental results showed that the temperature sensitivities of the two FPIs were −0.42 and 1.36 nm/°C while that of their parallel structure was −14.6 nm/°C corresponding to an amplification factor of 10.7, which was much larger than that (8.2) of the traditional Vernier effect. [ABSTRACT FROM AUTHOR]

This article explores the effects of system frequency on electromagnetic (EM) remote sensing of atmospheric refractivity. A frequency range of 2–40 GHz covering S- to Ka-bands is analyzed. A multifrequency inversion algorithm is developed to estimate the evaporation duct heights using a parabolic wave equation propagation model. The capabilities of a theoretical multifrequency system are explored for high and low signal-to-noise ratios for varying numbers of frequencies and bands. Experimental data were collected using the lower atmospheric propagation ultrawideband (LATPROP-UWB) system deployed during the Coupled Air-Sea Processes and EM Ducting Research (CASPER) East Campaign. Range-dependent propagation loss measurements at 53 frequencies ranging from 2 to 40 GHz were made. The evaporation duct refractivity profiles estimated from the multifrequency LATPROP-UWB data were compared to the profiles inferred from the concurrent meteorological and oceanographic measurements. Inversion results show that the optimal refractivity retrieval can be achieved using ten frequencies and results in a fourfold reduction in the estimation RMSE compared to a single-frequency inversion. [ABSTRACT FROM AUTHOR]

Accurate digitization of synoptic ocean features is crucial for climate studies and the operational forecasting of ocean and coupled ocean–atmosphere systems. Today, for some North Atlantic operational regional models, skilled human experts visualize and extract the gulf stream and rings (warm and cold eddies) through an extensive and knowledge-based manual process. To automate this task, we develop a dynamics-inspired deep learning system that extracts the Gulf Stream and rings from concurrent satellite images of sea surface temperature (SST) and sea surface height (SSH). We pose the above problem as a multilabel semantic image segmentation problem. A novel deep convolutional neural network architecture named W-Net, with two parallel encoder–decoder branches, is developed to perform the segmentation. The W-Net’s one branch is the SST branch (accepts SST image as input) and another is the SSH branch (accepts SSH as input), and the final output is a segmentation of gulf stream, warm rings, and cold rings. A dataset consisting of SST, SSH, and manual feature annotation (ground truth) from 2014 to 2018 is used for training. For gulf stream, we obtain 82.7% raw test accuracy and a low error of 4.39% in the detected path length. For the Rings, we obtain more than 71% raw eddy detection accuracy. A detailed ablation study and an examination of both SST and SSH parts of the network are presented to understand how the deep neural network learns to segment the gulf stream’s meandering path and Rings accurately. [ABSTRACT FROM AUTHOR]

Sea surface nitrate (SSN) is an important parameter to characterize physical and biogeochemical processes, particularly to quantify oceanic new primary production, yet its remote estimation from satellite has been difficult due to the complex relationships between environmental variables and SSN. In the central and southern sections of the California Current System (CSCCS), this challenge is attempted through modeling, validation, and extensive tests in different oceanic scenarios. Specifically, using extensive SSN datasets collected by many cruises spanning 40 years (1978–2018) and Moderate Resolution Imaging Spectroradiometer (MODIS) estimated sea surface temperature (SST) and chlorophyll-a (Chl), a stacking random forest (SRF) model of SSN has been developed and validated with a spatial resolution of ~4 km. The model showed an overall performance of root mean square difference (RMSD) $=0.83\,\,\mu $ mol/kg, with coefficient of determination ($R^{2}) =0.87$ , mean bias $= -0.11\,\,\mu $ mol/kg, and mean ratio = 1.15 for SSN ranging between 0.05 and $19.90~\mu $ mol/kg ($N =1034$). Furthermore, tests of the model with its original parameterization for the upwelling period, oceanic period, and winter period all showed satisfactory performance with an overall RMSD of 1.95 $\mu $ mol/kg. The sensitivity of the SRF model to uncertainties of MODIS SST and Chl was examined, with induced uncertainties of $\le 2.22~\mu $ mol/kg. The extensive evaluation and sensitivity tests indicated the robustness of the SRF model in estimating SSN in the study area of the CSCCS, and it could serve as a robust approach for other regions once sufficient in situ SSN data are available for model calibration. [ABSTRACT FROM AUTHOR]

For the first time the vertical variation in light quality in the global ocean is quantified with a single parameter—the hue angle ($\alpha _{E}$ , in degree) in chromaticity of downwelling irradiance. For oceanic waters, $\alpha _{E}$ is ~140° at surface, but it becomes ~230° at the bottom of the euphotic zone; $\alpha _{E}$ changes rapidly near the surface, and we term this layer of rapid change in light quality as chromocline, analogous to the thermocline or pycnocline in oceanography. The 3-D variations in light quality are further highlighted with data from satellite ocean color measurements, where global distributions of $\alpha _{E}$ for depths of 99%, 37%, and 1% of surface photosynthetically available radiation (PAR) are presented. As an example to demonstrate the importance to consider the change in light quality, the relationship between the light quality and the ratio of phytoplankton absorbed light to PAR is presented where this ratio may vary by a factor of 3 or more under different chlorophyll-a concentrations; otherwise, the ratio would be constant vertically. We advocate quantitative measurement and report the light quality in the upper ocean with such a single and objective parameter to accompany the routine measurement and report the light intensity, which will greatly improve our understanding of light-related processes and further bridge ocean optics and oceanography. [ABSTRACT FROM AUTHOR]

The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) was launched to the International Space Station (ISS) on June 29, 2018, and currently provides the highest spatial resolution thermal infrared (TIR) data (38 m $\times \,\, 69$ m) available from space. In this study, we validated the ECOSTRESS level-2 Land Surface Temperature (LST) and emissivity product at fourteen global sites to Stage-1 status. Two primary methods are recommended for the validation of LST data: Temperature-based (T-based) and Radiance-based (R-based) methods. The T-based method requires calibrated measurements of the ground leaving radiance concurrent with the satellite overpass. In contrast, the R-based method uses a radiative closure simulation with external atmospheric profiles and an $a$ priori knowledge of surface emissivity. Using these standard methods, we validated 1139 ECOSTRESS clear-sky observations between August 1, 2018, and March 31, 2020. For LST, the results show good agreement with ground-based measurements with an average root mean square error (RMSE) of 1.07 K, mean absolute error (MAE) of 0.40 K, and $r^{2}>0.988$ at all sites. However, a cold bias of ~0.75 K was identified for temperatures below 295 K linked to calibration issues that will be addressed in future reprocessing of the data. Retrieved emissivity comparisons with laboratory spectra had an RMSE of 0.023 (2.3%) for all bands on average. With the decommissioning of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on Terra in 2023, the multispectral and high-spatial-resolution characteristics of ECOSTRESS data serve as a pathfinder to the National Aeronautics and Space Administration’s (NASA) Surface Biology and Geology (SBG) designated observable with an expected launch in 2026. [ABSTRACT FROM AUTHOR]

We investigate the impacts of one of the strongest recorded hurricanes to have hit the Florida Panhandle, Hurricane Michael (2018), on the upper ocean using a suite of satellite data, in situ profiles, and outputs from the HYbrid Coordinate Ocean Model (HYCOM). Strong, low-level cyclonic winds associated with the hurricane generated strong Ekman suction that propagated ahead of the hurricane and caused changes in the surface and subsurface ocean. Following the passage of Hurricane Michael, a 3 °C drop in sea surface temperature (SST) was accompanied with a 4–5 mg $\text{m}^{-3}$ increase in chlorophyll-a concentration. In the subsurface, a $\sim 15$ m mixed layer deepening preceded upward displacements of the isotherms and cooling of the mixed layer. The impact of hurricane conditions on sea surface salinity (SSS) was localized and influenced by competing processes, with upwelling of salty subsurface water increasing SSS and enhanced precipitation decreasing SSS. During the peak of the hurricane, the impact of upwelling was greater than that of enhanced precipitation and, thus, SSS increased. Further away from the upwelling centers, hurricane-influenced precipitation, and river runoff freshened SSS. [ABSTRACT FROM AUTHOR]

A 2-year data set from Indian Space Research Organizations (ISRO’s) scatterometer mission (SCATSAT-1) has been used to investigate the impact of ocean surface current on the derived winds in the Bay of Bengal. For this purpose, wind speed residuals obtained between Ku-band SCATSAT-1 and buoy were regressed with buoy measured ocean surface currents. Results show a good agreement between wind residuals and surface current under stable air–sea interaction conditions for the region signifying a considerable impact of currents on the radar backscatter. A further analysis was carried out to ascertain the quantitative impact of currents on the C-band ASCAT derived winds and Ka-band SARAL/AltiKa derived wind speed. This study showed that impact of surface current is much higher on Ka-band altimeter-derived wind speed when compared to C-band and Ku-band scatterometer-derived wind speed. The correlation coefficient so obtained is found to be −0.34 in the case of Ka-band and nearly −0.26 for C-band and Ku-band scatterometer-derived winds. Higher correlation magnitude in the case of Ka-band suggests that surface current impact is slightly more for Ka-band when compared to C- and Ku-bands. These statistics suggest that wind speed retrieved from radar systems are indeed current relative and not fixed earth relative. Basin scale analysis for the Bay of Bengal indicates that surface current feedback in the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA-COARE) flux formulation results in 5%–15% reduction in the mechanical energy input to the ocean. [ABSTRACT FROM AUTHOR]

The non-line-of-sight (NLOS) underwater communication can offer a viable route in signal propagation and coverage, thus mitigating the pointing, acquisition, and tracking difficulties in line-of-sight optical communication. However, implementing the NLOS link is non-trivial. While the NLOS technique relies on light scattering, i.e., channel turbulence can facilitate NLOS communication, the associated path-loss (PL) can be significant. Signal fading can degrade link robustness, which arises due to ocean water temperature and salinity fluctuation and gradients. To evaluate the robustness of NLOS in natural waters, we systematically measure the link metrics, such as the bit error ratio, PL, and signal-to-noise ratio (SNR), of water bodies of uniform and nonuniform vertical salinity ranging from 30–40‰ (part-per-thousand). We found that salinity-induced turbulence can establish NLOS communication with PL reduction of 2.35 dB/m and SNR increase by 32.5 $\%$ for dynamic water. Furthermore, a strong correlation was obtained between the strength of signal fluctuations and the received SNR. Finally, we obtained a Gaussian distribution of the statistical scintillation behavior. These results demonstrated the benefit of using the NLOS regime for underwater wireless sensor networks for aiding designers and engineers. [ABSTRACT FROM AUTHOR]

A ring-shaped structure based on polymer coated no-core fiber (NCF) is presented for simultaneous temperature and pressure measurements. The sensing structure is fabricated by splicing the partially coated NCF between single-mode fibers and bending it into a loop. The anti-resonance effect is formed in the NCF and the resonant dips have wavelength shift responses to the temperature and displacement variations. It should be noted that the increase of temperature leads to a decrease in the polymer coating refractive index and changes the displacement measurement sensitivity, thus, the compensation algorithm is required to resolve this cross-sensitivity problem. Combining the ring-shaped structure with the elastic diaphragm encapsulation can convert seawater pressure into structural deformation displacement to achieve pressure measurement. The experimental and simulation results show that this sensor offers a high temperature sensitivity of −5.098 nm/°C with the resolution of $2\times 10^{-4}$ °C and a pressure sensitivity of −2.368 nm/MPa with the resolution of $0.4\times 10^{-3}$ MPa. In addition, the sensing performances could be changed by adjusting the NCF size and the ring-shaped structure diameter, which enables this sensing structure to have a broader application potential for seawater parameter measurement. [ABSTRACT FROM AUTHOR]

Globally gridded sea surface temperatures (SSTs) provide key data for long-term monitoring of the stability of satellite data. Despite apparent limitations, accurate hyperspectral data can provide useful independent information to critique the stability of global SST products on the annual-to-decadal time scale. We compared data from atmospheric infrared sounder (AIRS) on EOS Aqua and Crosstrack Interferometer Sounder (CrIS) on SNPP with the SST products from NOAA/NESDIS [real time global (RTG)], the Canadian Meteorological Centre (CMC), and the U.K. Met Office [Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA)]. For the 2013–2019 period, the overall standard deviation of the difference between AIRS and the RTG was 0.55 K, with an increasing trend over time. In contrast, the standard deviation of the difference between the AIRS, the CMC, and the OSTIA dropped steadily to below 0.4 K, a level previously seen only in SST products relative to independent buoy data. Unexplained biases between the observed and the gridded SSTs at the 100-mK level are consistent with the already existing estimates of the AIRS and CrIS absolute calibration accuracy. However, the AIRS and CrIS observations both show artifacts in all three SST products, increasing with distance from the equator, with the CMC artifacts being the smallest. Even with the CMC, a trend of 4 mK per year relative to AIRS and CrIS was observed between 2013 and 2019 for the 30S–30N oceans. Investigation of the underlying causes of the observed discrepancies requires further work. [ABSTRACT FROM AUTHOR]

Fronts between Arctic- and Atlantic-origin waters are characterized by strong lateral gradients in temperature and salinity. Ocean processes associated with fronts are complex with considerable space and time variability. Therefore, resolving the processes in frontal zones by observation is challenging but important for understanding the associated physical–biological interactions and their impact on the marine ecosystem. The use of autonomous robotic vehicles and in situ data-driven sampling can help improve and augment the traditional sampling practices, such as ships and profiling instruments. Here, we present the development and results of using an autonomous agent for detection and sampling of an Arctic front, integrated on board an autonomous underwater vehicle. The agent is based on a subsumption architecture implemented as behaviors in a finite-state machine. Once a front is detected, the front tracking behavior uses observations to continuously adapt the path of the vehicle to perform transects across the front interface. Following successful sea trials in the Trondheimsfjord, the front-tracking agent was deployed to perform a full-scale mission near 82 $^{\circ}$ N north of Svalbard, close to the sea ice edge. The agent was able to detect and track an Arctic frontal feature, performing a total of six crossings while collecting vertical profiles in the upper 90 m of the water column. Measurements yield a detailed volumetric description of the frontal feature with high resolution along the frontal zone, augmenting ship-based sampling that was run in parallel. [ABSTRACT FROM AUTHOR]