Open Ocean Waters Research Articles

Diverse Genomic Traits Differentiate Sinking-Particle-Associated versus Free-Living Microbes throughout the Oligotrophic Open Ocean Water Column.

ABSTRACTBacteria and archaea are central to the production, consumption, and remineralization of dissolved and particulate organic matter and contribute critically to carbon delivery, nutrient availability, and energy transformations in the deep ocean. To explore environmentally relevant genomic traits of sinking-particle-associated versus free-living microbes, we compared habitat-specific metagenome-assembled genomes recovered throughout the water column in the North Pacific Subtropical Gyre. The genomic traits of sinking-particle-associated versus free-living prokaryotes were compositionally, functionally, and phylogenetically distinct. Substrate-specific transporters and extracellular peptidases and carbohydrate-active enzymes were more enriched and diverse in particle-associated microbes at all depths than in free-living counterparts. These data indicate specific roles for particle-attached microbes in particle substrate hydrolysis, uptake, and remineralization. Shallow-water particle-associated microbes had elevated genomic GC content and proteome nitrogen content and reduced proteome carbon content in comparison to abyssal particle-associated microbes. An inverse trend was observed for their sympatric free-living counterparts. These different properties of attached microbes are postulated to arise in part due to elevated organic and inorganic nitrogen availability inside sinking particles. Particle-attached microbes also were enriched in genes for environmental sensing via two-component regulatory systems, and cell-cell interactions via extracellular secretion systems, reflecting their surface-adapted lifestyles. Finally, particle-attached bacteria had greater predicted maximal growth efficiencies than free-living bacterioplankton at all depths. All of these particle-associated specific genomic and proteomic features appear to be driven by microhabitat-specific elevated nutrient and energy availability as well as surface-associated competitive and synergistic ecological interactions. Although some of these characteristics have been previously postulated or observed individually, we report them together here in aggregate via direct comparisons of cooccurring free-living and sinking-particle-attached microbial genomes from the open ocean.

Modeling ocean surface chlorophyll-a concentration from ocean color remote sensing reflectance in global waters using machine learning

The spatial and temporal variations of Chlorophyll-a (Chl-a) in clear and coastal waters are critical for assessing the health of the marine environment. Machine learning models have been proven to model complex relationships and provide better accuracy estimates of the derived parameters compared to traditional empirical models. The present study proposes a novel approach to derive Chl-a by using multi-layer perceptron Neural Network (MLPNN) with Resilient backpropagation method based on the four ocean color bands existent in most of the ocean color sensors. The NNs are trained on NASA's bio-optical Marine Algorithm Dataset (NOMAD) and tested on three different datasets (i) SeaWiFS and, (ii) MODIS Aqua matchup dataset, and (iii) simulated dataset for the Red Sea. These three datasets cover significant variations range in Chl-a levels under both oligotrophic and eutrophic conditions. The influence of different variations in inputs used in NN training is assessed and hyperparameter tuning of the NN is performed to obtain best NN configuration to derive Chl-a. Accuracy assessment of the present study with other global algorithms are performed by comparing the modeled and observed values of the Chl-a. The performance matrices computed from the developed model were promising. Therefore, this study provides a potential approach for the retrieval of improved Chl-a estimates in the global clear and coastal waters as compared to the traditional blue-green band ratio algorithms. Furthermore, the developed algorithm and existing algorithms are applied to SeaWiFS, MODIS, VIIRS, and Hawkeye satellite ocean color data to demonstrate how it may be utilized to accurately depict the spatial distribution of ocean color features in global waters, phytoplankton blooms and some of the physical processes in the Arabian Sea and the Red Sea. The findings of this work have potential to advance the ocean color remote sensing and biogeochemical cycles and processes in coastal and open ocean waters.

Sea Level Change in the Canary Current System during the Satellite Era

Understanding the causes of global sea level rise is considered as an important goal of climate research on a regional scale, especially around islands, owing to their vulnerability to this phenomenon. In the case of the Canary Islands, these alterations entail an increase in territorial risks. The Canary Islands span the transitional zone linking the Northwest African upwelling system and the open ocean waters of the subtropical gyre. Here, we used satellite altimeter data to perform a detailed statistical analysis of sea level anomaly from 1993 to 2019. A seasonal study was carried out at two different regions and sea level anomaly was compared with temperature variability in the area. A total rise in the sea level of around 7.94 cm was obtained for the last 27 years in both areas. Sea level anomaly was strongly influenced by sea surface temperature, as expected. In addition, we found differences between the annual cycle in the open ocean and the upwelling zone, showing different patterns in both sites. The expected increase in sea level for the year 2050 in the coastal zone of the archipelago was estimated to be 18.10 cm, affecting the coastal economy of the islands, which is strongly based on the use of beaches for tourism.

Defining the Realized Niche of the Two Major Clades of Trichodesmium: A Study on the West Florida Shelf

The cyanobacterium Trichodesmium plays an essential role supporting ocean productivity by relieving nitrogen limitation via dinitrogen (N2) fixation. The two common Trichodesmium clades, T. erythraeum and T. thiebautii, are both observed in waters along the West Florida Shelf (WFS). We hypothesized that these taxa occupy distinct realized niches, where T. thiebautii is the more oceanic clade. Samples for DNA and water chemistry analyses were collected on three separate WFS expeditions (2015, 2018, and 2019) spanning multiple seasons; abundances of the single copy housekeeping gene rnpB from both clades were enumerated via quantitative PCR. We conducted a suite of statistical analyses to assess Trichodesmium clade abundances in the context of the physicochemical data. We observed a consistent coastal vs. open ocean separation of the two clades: T. erythraeum was found in shallow waters where the concentrations of dissolved iron (dFe) and the groundwater tracer Ba were significantly higher, while T. thiebautii abundance was positively correlated with water column depth. The Loop Current intrusion in 2015 with entrained Missisippi River water brought higher dFe and elevated abundance of both clades offshore of the 50 m isobath, suggesting that both clades are subject to Fe limitation on the outer shelf. Whereas, previous work has observed that T. thiebautii is more abundant than T. erythraeum in open ocean surface waters, this is the first study to examine Trichodesmium niche differentiation in a coastal environment. Understanding the environmental niches of these two key taxa bears important implications for their contributions to global nitrogen and carbon cycling and their response to global climate change.

An optical water classification and quality control model (OC_QC model) for spectral diffuse attenuation coefficient

Spectral diffuse attenuation coefficient of down-welling irradiance (Kd(λ)) is a fundamental optical parameter for water color and of significance for heat budget calculation, photosynthesis modeling and carbon sequestration. Uncertainties exist in both in situ measured and satellite derived Kd(λ), therefore, evaluation of its data quality is essential. In addition, optical water classification of Kd(λ) is still limited. To address these issues, we proposed an optical water classification and quality control model (OC_QC model) based on a globally collected high-quality in situ Kd(λ) data. The model consists of the reference Kd(λ) spectra for 7 optical water types (OWT, ranging from clear open ocean water to highly turbid water) and a scoring system. An individual Kd(λ) spectrum can be assigned an OWT and quality control score (QC score) with this model. The performance of the OC_QC model is tested with independent in situ Kd(λ) spectra from the turbid coastal water (Bohai Sea) and clear oceanic water (Indian Ocean). Questionable or erroneous Kd(λ) spectra can be identified, suggesting the model’s robustness. The model was also evaluated with the Medium Resolution Imaging Spectrometer (MERIS) Level-2 and the Moderate Resolution Imaging Spectroradiometer (MODIS) Level-3 Kd(λ) data in the Bohai Sea, Yellow Sea, East China Sea and South China Sea. Satellite derived maps clearly showed the spatial and temporal variations of OWTs and QC scores, and the regions of low-quality Kd(λ) were reasonably extracted. Global maps of Kd(λ)-based optical water types and corresponding QC scores were also obtained with OC_QC model. With the quality controlled Kd(λ) data, the retrieval accuracy of Secchi disk depth was improved. The retrieval accuracies of Chlorophyll-a concentration and total seawater absorption coefficient were also improved with the Kd(λ) optical water classification based algorithms. The OC_QC model would be valuable for evaluating Kd(λ) data (especially the operational global Kd(λ) products), investigation of water optical properties, and development and merging of bio-optical algorithms.

Diversity, Abundance, and Ecological Roles of Planktonic Fungi in Marine Environments.

Fungi are considered terrestrial and oceans are a “fungal desert”. However, with the considerable progress made over past decades, fungi have emerged as morphologically, phylogenetically, and functionally diverse components of the marine water column. Although their communities are influenced by a plethora of environmental factors, the most influential include salinity, temperature, nutrients, and dissolved oxygen, suggesting that fungi respond to local environmental gradients. The biomass carbon of planktonic fungi exhibits spatiotemporal dynamics and can reach up to 1 μg CL−1 of seawater, rivaling bacteria on some occasions, which suggests their active and important role in the water column. In the nutrient-rich coastal water column, there is increasing evidence for their contribution to biogeochemical cycling and food web dynamics on account of their saprotrophic, parasitic, hyper-parasitic, and pathogenic attributes. Conversely, relatively little is known about their function in the open-ocean water column. Interestingly, methodological advances in sequencing and omics approach, the standardization of sequence data analysis tools, and integration of data through network analyses are enhancing our current understanding of the ecological roles of these multifarious and enigmatic members of the marine water column. This review summarizes the current knowledge of the diversity and abundance of planktonic fungi in the world’s oceans and provides an integrated and holistic view of their ecological roles.

Penetration of Ultraviolet‐B Radiation in Oligotrophic Regions of the Oceans During the Malaspina 2010 Expedition

AbstractFew studies have investigated ultraviolet (UV) radiation in the open ocean besides its harmful effects on organisms and influence on biogeochemical processes. Here, we assessed UV attenuation, with particular focus on UV‐B, across the (sub)tropical ocean during the Malaspina 2010 Circumnavigation. Vertical UV radiometer profiles together with Chl‐a concentration, and UV absorption by CDOM (aCDOM(λ)) and by suspended particulate matter (ap(λ)) were measured at 117 stations. At photosynthetically active radiation (PAR) and across UV‐A and UV‐B wavelengths, the lowest downwelling attenuation coefficients (Kd) during the expedition were recorded in ultra‐oligotrophic regions at 5°–15°S (mean Kd(305 nm): 0.129 m−1, mean Kd(313 nm): 0.107 m−1) in the Indian and South Pacific Oceans. The waters here were comparatively more transparent than at 5°–15°N (mean Kd(305 nm): 0.239 m−1, mean Kd(313 nm): 0.181 m−1) where equatorial upwelling occurs. Kd was highest near the Costa Rica Dome (Kd(313 nm): 0.226 m−1) and at the confluence of the Benguela and Agulhas currents (Kd(313 nm): 0.251 m−1). The contribution of ap(λ) toward nonwater absorption (anw(λ)) was significantly lower at 305 nm than at 313 and 320 nm, suggesting the contribution of absorption by detritus and phytoplankton particles decreases compared with that of CDOM absorption as UV‐B wavelength decreases. Both aCDOM(λ) and ap(λ) at UV‐B wavelengths were lowest in the Indian Ocean whereas Kd was lowest in the South Pacific. This finding emphasizes that other factors besides absorption, such as scattering by reflective phytoplankton or inorganic particles, strongly influence UV‐B attenuation in open ocean waters.

Determining the Primary Sources of Uncertainty in Retrieval of Marine Remote Sensing Reflectance From Satellite Ocean Color Sensors

Uncertainties in the retrieval of the remote sensing reflectance, Rrs, from Ocean Color (OC) satellite sensors have a strong impact on the performance of algorithms for the estimation of chlorophyll-a, mineral concentrations, and inherent optical properties (IOPs). The uncertainties are highest in the blue bands. The total radiance measured at the top of the atmosphere captures the instantaneous state of the atmosphere-ocean system: the in-water conditions, sky and Sun glint reflected from the wind-roughened ocean surface, as well as light scattered from molecules and aerosols in the atmosphere. Each of these components has associated uncertainties, and when combined with the additional uncertainties from the instrument noise and the atmospheric correction process, they contribute to the total uncertainty budget for the retrieved Rrs. We analyzed the contribution of each component uncertainties to the total Rrs uncertainties in SNPP-VIIRS level 2 products, taking advantage of the spectral differences between the components. We examined multiple scenes in the open ocean and coastal waters at spatial resolutions ranging from 2250 to 5250 m by comparing the retrieved Rrs to in situ measurements made at several AERONET-OC sites and at the MOBY site. It was shown that uncertainties associated with the molecular (Rayleigh) scattering play the most significant role, while the contributions of other components are usually smaller. Uncertainties in Rayleigh scattering are primarily attributed to the variability of Rayleigh optical thickness (ROT) with a standard deviation of approximately 1.5% of ROT, which can largely explain the frequency of negative Rrs retrievals as observed using the current standard atmospheric correction process employed by NASA. Variability of the sky light reflected from the ocean surface in some conditions also contributed to uncertainties in the blue; water variability proportional to Rrs had a very pronounced peak in the green at coastal sites.

Potential negative effects of ocean afforestation on offshore ecosystems.

Our scientific understanding of climate change makes clear the necessity for both emission reduction and carbon dioxide removal (CDR). The ocean with its large surface area, great depths and long coastlines is central to developing CDR approaches commensurate with the scale needed to limit warming to below 2 °C. Many proposed marine CDR approaches rely on spatial upscaling along with enhancement and/or acceleration of the rates of naturally occurring processes. One such approach is 'ocean afforestation', which involves offshore transport and concurrent growth of nearshore macroalgae (seaweed), followed by their export into the deep ocean. The purposeful occupation for months of open ocean waters by macroalgae, which do not naturally occur there, will probably affect offshore ecosystems through a range of biological threats, including altered ocean chemistry and changed microbial physiology and ecology. Here, we present model simulations of ocean afforestation and link these to lessons from other examples of offshore dispersal, including rafting plastic debris, and discuss the ramifications for offshore ecosystems. We explore what additional metrics are required to assess the ecological implications of this proposed CDR. In our opinion, these ecological metrics must have equal weight to CDR capacity in the development of initial trials, pilot studies and potential licensing.

On the Seasonal Dynamics of Phytoplankton Chlorophyll-a Concentration in Nearshore and Offshore Waters of Plymouth, in the English Channel: Enlisting the Help of a Surfer

The role of phytoplankton as ocean primary producers and their influence on global biogeochemical cycles makes them arguably the most important living organisms in the sea. Like plants on land, phytoplankton exhibit seasonal cycles that are controlled by physical, chemical, and biological processes. Nearshore coastal waters often contain the highest levels of phytoplankton biomass. Yet, owing to difficulties in sampling this dynamic region, less is known about the seasonality of phytoplankton in the nearshore (e.g., surf zone) compared to offshore coastal, shelf and open ocean waters. Here, we analyse an annual dataset of chlorophyll-a concentration—a proxy of phytoplankton biomass—and sea surface temperature (SST) collected by a surfer at Bovisand Beach in Plymouth, UK on a near weekly basis between September 2017 and September 2018. By comparing this dataset with a complementary in-situ dataset collected 7 km offshore from the coastline (11 km from Bovisand Beach) at Station L4 of the Western Channel Observatory, and guided by satellite observations of light availability, we investigated differences in phytoplankton seasonal cycles between nearshore and offshore coastal waters. Whereas similarities in phytoplankton biomass were observed in autumn, winter and spring, we observed significant differences between sites during the summer months of July and August. Offshore (Station L4) chlorophyll-a concentrations dropped dramatically, whereas chlorophyll-a concentrations in the nearshore (Bovsiand Beach) remained high. We found chlorophyll-a in the nearshore to be significantly positively correlated with SST and PAR over the seasonal cycle, but no significant correlations were observed at the offshore location. However, offshore correlation coefficients were found to be more consistent with those observed in the nearshore when summer data (June–August 2018) were removed. Analysis of physical (temperature and density) and chemical variables (nutrients) suggest that the offshore site (Station L4) becomes stratified and nutrient limited at the surface during the summer, in contrast to the nearshore. However, we acknowledge that additional experiments are needed to verify this hypothesis. Considering predicted changes in ocean stratification, our findings may help understand how the spatial distribution of phytoplankton phenology within temperate coastal seas could be impacted by climate change. Additionally, this study emphasises the potential for using marine citizen science as a platform for acquiring environmental data in otherwise challenging regions of the ocean, for understanding ecological indicators such as phytoplankton abundance and phenology. We discuss the limitations of our study and future work needed to explore nearshore phytoplankton dynamics.

Cross-Shelf Exchange in the Southwestern Atlantic Shelf: Climatology and Extreme Events

The variability and drivers of the cross-shelf exchanges between the Southwestern Atlantic shelf and the open ocean from 30 to 40°S are analyzed using a high-resolution ocean model reanalysis at daily resolution. The model's performance was first evaluated using altimetry data, and independent mooring and hydrographic data collected in the study area. Model transports are in overall good agreement with all other estimates. The record-mean (1993–2018) cross-shore transport is offshore, 2.09 ± 1.60 Sv. 73% of the shelf-open ocean exchange occurs in the vicinity of Brazil-Malvinas Confluence (~38°S) and 20% near 32°S. This outflow is mostly contributed by northward alongshore transport through 40°S (63%) and the remaining by southward transport through 30°S (37%). The cross-shore flow presents weak seasonal variations, with a maximum in austral summer, and high variability at subannual and weekly time scales. The latter is mainly associated with abrupt wind changes generated by synoptic atmospheric systems. Alongshore wind variations set up sea-level changes in the inner shelf which in turn drive large anomalies in the associated geostrophic alongshore flow. The difference in inner shelf sea-level anomalies at 30 and 40°S is a good indicator of cross-shelf exchange at seasonal and shorter time scales. Episodes of extreme offshore transport that reach up to 9.45 Sv and last about 2 days are driven by convergence of these alongshore flows over the shelf. Large exports of shelf waters lead to freshening of the upper open ocean as revealed by in-situ and satellite observations. In contrast, onshore extreme events drive open ocean water intrusions of up to 6.53 Sv and last <4 days. These inflows, particularly the subtropical waters from the Brazil Current, induce a substantial salinification of the outer shelf.

Overlooked and widespread pennate diatom-diazotroph symbioses in the sea

Persistent nitrogen depletion in sunlit open ocean waters provides a favorable ecological niche for nitrogen-fixing (diazotrophic) cyanobacteria, some of which associate symbiotically with eukaryotic algae. All known marine examples of these symbioses have involved either centric diatom or haptophyte hosts. We report here the discovery and characterization of two distinct marine pennate diatom-diazotroph symbioses, which until now had only been observed in freshwater environments. Rhopalodiaceae diatoms Epithemia pelagica sp. nov. and Epithemia catenata sp. nov. were isolated repeatedly from the subtropical North Pacific Ocean, and analysis of sequence libraries reveals a global distribution. These symbioses likely escaped attention because the endosymbionts lack fluorescent photopigments, have nifH gene sequences similar to those of free-living unicellular cyanobacteria, and are lost in nitrogen-replete medium. Marine Rhopalodiaceae-diazotroph symbioses are a previously overlooked but widespread source of bioavailable nitrogen in marine habitats and provide new, easily cultured model organisms for the study of organelle evolution.

Wavelet transform approach for denoising and decomposition of satellite-derived ocean color time-series: Selection of optimal mother wavelet

Wavelet Transform (WT) has remarkable advantages for feature extraction and denoising of satellite-derived ocean color time series datasets. The selection of mother wavelet (MWT) is the main challenging issue in the wavelet transform analysis of ocean color time series, since different MWT applied to the same dataset may produce different results. In this study, 57 MWTs were investigated to find the optimal wavelet functions for WT analysis of ocean color time series datasets with particular emphasis on the quantitative approaches. The daily, weekly, and monthly averaged of MODIS Level-3 Chlorophyll-a (Chl-a) series were denoised and decomposed by Discrete Wavelet Transform (DWT) using different MWTs. The seasonal trends of all datasets were extracted using the Seasonal Trend decomposition procedure based on LOcally wEighted Scatterplot Smoothing (LOESS) (STL) and Census X-11 methods, used as references. The statistical Cross Correlation Function (CCF), Signal to Noise Ratio (SNR), and Mean Standard Error (MSE), indexes, plus a Magnitude-Shape quantitative model were used to calculate the correlation and similarity between original and corresponding decomposed and denoised reference Chl-a signals. The similarity indexes were analyzed to evaluate the similarity and correlation between reconstructed denoised signals with original Chl-a series, and between DWT seasonal components with the reference seasonal trends. For a more assessment, two different weekly averaged Chl-a series of SeaWiFS satellite sensor over Bermuda-Atlantic region (open ocean waters) and Chesapeake Bay (coastal waters) were evaluated using SeaBASS in situ measurements, and seasonal trends in comparison with corresponding DWT components. The results revealed that the “db10” and “db5” from Daubechies wavelet family were respectively the best options for denoising and decomposition of Chl-a series using WT methods. Also MWTs from Biorthogonal and Reverse biorthogonal wavelet families gave a poor performance, and therefore these functions are not recommended to use in DWT denoising and decomposition of Chl-a signals.

Seasonal variation and deposition of atmospheric organophosphate esters in the coastal region of Shanghai, China

The coastal megacity Shanghai is located in the center of the Yangtze River Delta, a dominant flame retardants (FRs) production region in China, especially for organophosphate esters (OPEs). This prompted us to investigate occurrence and seasonal changes of atmospheric OPEs in Shanghai, as well as to evaluate their sources, environmental behavior and fate as a case study for global coastal regions. Atmospheric gas and particle phase OPEs were weekly collected at two coastal sites - the emerging town Lingang New Area (LGNA), and the chemical-industry zone Jinshan Area (JSA) from July 2016–June 2017. Total atmospheric concentrations of the observed OPEs were significantly higher in JSA (median of 1800 pg m−3) than LGNA (median of 580 pg m−3). Tris(1-chloro-2-propyl) phosphate (TCPP) was the most abundant compound, and the proportion of three chlorinated OPEs were higher in the particle phase (55%) than in the gas phase (39%). The year-round median contribution of particle phase OPEs was 33%, which changed strongly with seasons, accounting for 10% in summer in contrast to 62% in winter. Gas and particle phase OPEs in JSA exhibited significant correlations with inverse of temperature, respectively, indicating the importance of local/secondary volatilization sources. The estimated fluxes of gaseous absorption were almost 2 orders of magnitude higher than those of particle phase deposition, which could act as sources of organic phosphorus to coastal and open ocean waters.

Modeling the Growth Potential of the Kelp Saccharina Latissima in the North Atlantic

It has recently been proposed that macroalgae (e.g., kelp) could be grown in the open ocean as a CO2 removal strategy. Most macroalgae naturally grow in shallow coastal waters, and their ability to grow in open ocean conditions is largely untested. Here we quantify macroalgae growth potential in the North Atlantic using an established model of Saccharina latissima forced by an ocean state estimate. In the relatively clear open ocean waters, we find that growth is possible to depths of up to 50 m across most of the region, with the maximum depth-integrated growth potential between 40 and 50°N. The model exhibits a large carbon to nitrogen ratio at the southern end of the growth range. The ratio of kelp carbon to phytoplankton biomass is also relatively high in the southeastern portion of the growth range. Using a sensitivity analysis, we find that the position of the southern limit of the growth range is largely modulated by temperature tolerance on the western side of the basin in the Gulf Stream and low nitrate on the eastern side of the basin. We also find a statistically significant reduction in the kelp growth potential over the period from 2002 to 2019, reflecting the warming of the surface ocean over this period.

Effect of the complex air–sea interface on a hybrid atmosphere-underwater optical wireless communications system

Wireless optical communication (WOC) through the atmosphere–ocean system is fundamentally complex because of the diversity, concentration, types and vertical thickness of the constituents and poses a major challenge from the optical characteristics of bubbles at the air–sea interface and water constituents (phytoplankton, suspended sediments, and dissolved organic matter), and stratification (medium inhomogeneity). The present study aims to analyse the effects of atmospheric aerosols (their intensity, diversity, and vertical thickness), waves/bubbles at the air–sea interface, seawater constituents (phytoplankton, suspended sediments, and dissolved organic matter), and medium inhomogeneity along the path between a laser transmitter in the airborne platform and a receiver in the underwater platform using Monte Carlo technique. For the first time, our analysis showed that for a homogeneous atmosphere–ocean channel (7 km in the atmosphere column and 42 m in the ocean medium), the estimated normalized received power reduced to 17 dB and the time delay spread increased to 1.01 ns (considering a receiver of 7” and an aperture FOV of 180°) when compared to those values for a stratified atmosphere–ocean channel. The bubbles (both clean and coated) relative to the particulates in open oceanic water under high wind speeds have a significant impact on the spatio-temporal spread of the laser beam. There is also a well pronounced effect of coated bubbles on the received signal power in open ocean water. In contrast, the particulates have a higher impact on the received signal power than the clean/coated bubbles in turbid coastal water. These results suggest that the normalized received power when calculated for the cases of dense bubble populations under high wind speeds (at a wind speed 18 ms−1) reduced to 8–9 dB and increased to 0.0025 scintillation index. The coated bubbles at the air–water interface reduced the normalized received power by 1.41 dB compared to the clean bubbles. Further, our analysis indicated that the expansion of beam width and the reduction of beam divergence angle can be utilized to mitigate the performance degradation (power loss) caused by bubbles at the air–sea interface. These results and analyses will be helpful for a system designer to accurately define/decide the system parameters and build a functional communication system for the inhomogeneous atmosphere–ocean system.

Enhanced Sea Surface Salinity Estimates Using Machine-Learning Algorithm With SMAP and High-Resolution Buoy Data

Despite the recent advances in satellite-based L-band microwave radiometry and retrieval algorithms to provide a unique capability to measure sea surface salinity (SSS) from space and explore its utility for understanding mesoscale dynamics, global ocean circulation, vertical mixing, evaporation rates and climate oscillations, SSS retrieval from L-band microwave radiometric data from the NASA-SMAP (Soil Moisture Active Passive) mission is often biased with systematic errors on larger temporal, spatial scales and random errors on short-time and length scales. To improve the SSS retrieval from SMAP data, we developed a robust algorithm based on a machine-learning approach with high-resolution in-situ data from the Ocean Moored Buoy Network in the Northern Indian Ocean (OMNI), which includes the Arabian Sea (AS) and Bay of Bengal (BoB)). The new algorithm was rigorously trained, tested and validated using the in-situ SSS time series measurements from the AS and BoB. Several sensitive variables were examined and used to improve the SSS estimates – such as radiometric and ancillary data from the satellite observations, sea-surface wind and precipitation from the ERA5 data, and SSS/ SST from the OMNI buoy measurements. The OMNI time-series measurements provided the spatially averaged satellite products to characterize the variability and gross features of SSS in BoB and AS waters on weekly, monthly, seasonal and annual time scales. The systematic validation of SMAP SSS products on a range of spatio-temporal scales showed that the new algorithm improved the SSS estimates by more than 15% in open ocean waters and 25% in river-discharge and precipitation-dominated regions in BoB and AS, when compared to the standard (operational) algorithm. Further analysis demonstrated that the new algorithm reduced clear biases and significant anomalies in SMAP SSS retrievals in the regions of river runoff, surface-freshened ocean and intense tropical cyclones, and captured synoptic/mesoscale SSS features and their seasonal variations in the North Indian Ocean.

Elucidating sources of mercury in the west coast of Korea and the Chinese marginal seas using mercury stable isotopes

Nearshore systems play an important role as mercury (Hg) sources to the open ocean and to human health via fish consumption. The nearshore system along East Asia is of particular concern given the rapid industrialization, which contributes to significant anthropogenic Hg emissions and releases. We used Hg stable isotopes to characterize Hg sources in the sediment and fish along the west coast of Korea, located at the northeast of the East China Sea. The Hg isotope ratios of the west coast sediments (δ202Hg; −0.89 to −0.27‰, Δ199Hg; −0.04 to 0.14‰) were statistically similar with other nearshore sediments (δ202Hg; −0.99 to −0.30‰, Δ199Hg; −0.04 to 0.19‰) and overlapped with the industrial Hg source end-member (δ202Hg; −0.5‰, Δ199Hg; 0.01‰) estimated from the Chinese marginal seas. Using a ternary mixing model, we estimated that industrial Hg sources contribute 83–97% in the west coast of Korea, and riverine and atmospheric Hg sources play minor roles in the Korean west coast and the Chinese marginal seas. The comparison between Hg isotope ratios of the sediment and nearshore fish revealed that the fish in the most west coast sites are exposed to MeHg produced in the sediment. At a few southwest coast sites, external MeHg produced in rivers and the open ocean water column appears to be more important as a source in fish. This is supported by much higher δ202Hg (0.74‰; similar to oceanic fish) and lower δ202Hg (−0.71‰; similar to riverine sources) compared to fish collected from other west coast sites influenced by sedimentary MeHg. The substantial Hg contributions from industrial activities suggest the national policies regulating anthropogenic Hg releases can directly mitigate human Hg exposure originating via local fish consumption. This study contributes to the growing regional and global inventories of Hg fluxes and sources exported into coastal oceans.

Potential of spaceborne Brillouin scattering lidar for global ocean optical profiling

The potential of spaceborne Brillouin scattering lidar for generating global ocean optical profiles was studied herein. We analyzed the global distributions of the maximum detectable depths and corresponding optimum wavelengths for spaceborne Brillouin scattering lidar during the day and night, simulated the global vertical profile distributions of the seawater sound speed and Brillouin scattering frequency shift, and discussed the effects of the system parameters and water environment parameters in Case II water on the lidar detection performance and proportion of Brillouin scattering lidar penetrating the upper mixed layer on the global scale. The laser emission wavelength of 490 nm is suitable for detecting open ocean waters, and 540 nm is suitable for detecting coastal waters. The detection depth of the Brillouin scattering lidar operating at night is approximately 10 m greater than that during the day. The vertical profile distributions of the seawater sound and the Brillouin scattering frequency shift decrease as the depth increases from 0 to 200 m in the mid-low latitude regions. The proportions of spaceborne Brillouin scattering lidar penetrating the upper mixed layer in January-February-March, April-May-June, July-August-September, and October-November-December are 75.15%, 76.80%, 59.12%, and 73.10%, respectively. The results indicate that spaceborne Brillouin scattering lidar has great potential for the wide-range and long-term monitoring of upper-ocean water bodies, which would be a good complement to passive satellite ocean color remote sensing technology and the traditional measurement methods of Argo floats, gliders, XBT, and AUV.

Chlorophyll-a concentration inversion based on the modified Quasi-Analytical Algorithm and Sentinel-3 OLCI in Daihai Lake, China

Abstract The Quasi-Analytical Algorithm (QAA) is effective in retrieving water inherent optical properties (IOPs) from remote sensing spectral reflectance and has wider applications in studies of the open ocean and coastal waters than of inland waters. This research aimed to modify the QAA model based on measured field spectral reflectance and absorption coefficients to render it applicable to studies of Daihai Lake, China. The improvements mainly included the reference wavelength selection, the power index of the particle backscattering coefficient and the exponential slope of the absorption coefficient of the colored detrital matter estimation. The average relative error between the inverse and measured absorption coefficients was less than 20%. A linear model was established between the phytoplankton absorption coefficient at a wavelength of 674 nm (aph(674)) and the chlorophyll-a (Chl-a) concentration, with a determination coefficient of 0.88. Additionally, the modified Quasi-Analytical Algorithm (MQAA) model was applied to the Ocean and Land Color Instrument (OLCI) data aboard the Sentinel-3 satellite. Finally, a spatial distribution map for the Chl-a concentrations in Daihai Lake on August 10, 2017, was drawn and the mid-eutrophication area was found to occur in the north and border.