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Using a new measure that relates tropical cyclone (TC)-induced sea surface cooling with the strength of TCs, interannual variations in potential impacts of the upper ocean stratification on TC-induced sea surface cooling associated with the evolution of El Niño/Southern Oscillation (ENSO) are investigated in the northwestern Pacific using an ocean reanalysis product, with a special focus on haline effects. It is found that the haline stratification could suppress the sea surface cooling by as much as 20% to the south of 20°N in the peak typhoon season (July-October), and this contribution is different between their developing years (September-October) and decaying years (July-August). More specifically, the haline effects may vary up to 25% (40%) during the decaying years of El Niño (La Niña). Due to anomalous haline effects, the region to the west of 160°E is susceptible to the sea surface cooling during the developing and decaying years of El Niño, while the cooling could be suppressed in this region during the decaying years of La Niña. Although the effects of haline stratification have been found less important than those of thermal stratification, potential impacts of the upper ocean salinity on TC-induced sea surface cooling associated with the ENSO have been quantitatively estimated for the first time. Since the main focus of this paper is to present the new measure and discuss potential impacts of the upper ocean salinity stratification, further verifications need to be conducted once more observational data is accumulated or through numerical simulations. [ABSTRACT FROM AUTHOR]

Selecting an optimal subset of sensors that can accurately reconstruct the full state of the ocean can reduce the cost of themonitoring system and improvemonitoring efficiency. Typically, in data-driven sensor selection processes, the use of Euclidean distance to evaluate reconstruction error is susceptible to non-Gaussian noise and outliers present in ocean data. This paper proposes a Robust Sensor Selection (RSS) evaluation model based on the Maximum Correntropy Criterion (MCC) through subspace learning, enabling the selection of robust sensor measurement subsets and comprehensive data reconstruction. To more accurately quantify the impact of varying noise magnitudes, noise weights were incorporated into the model's objective function. Additionally, the local geometric structure of data samples is utilized to further enhance reconstruction accuracy through the selected sensors. Subsequently, the MCC_RSS algorithm is proposed, which employs the Block Coordinate Update (BCU) method to achieve the optimal solution for the proposed model. Experiments conducted using ocean temperature and salinity datasets validate the proposed MCC_RSS algorithm. The results demonstrate that the sensor selection method proposed in this paper exhibits strong robustness, outperforming comparative methods under varying proportions of outliers and non-Gaussian noise. [ABSTRACT FROM AUTHOR]

The Indonesian Throughflow (ITF) thermocline, as exclusive water source for the "warm water route" of the Atlantic Meridional Overturning Circulation (AMOC), provides waters that exit the Indian Ocean and join the AMOC upper limb via the Agulhas Leakage (AL). Hence, investigating long‐term variations in the ITF thermocline and its implications on the AL is important for understanding dynamics of the AMOC. Here, the thermohaline history of the ITF thermocline was reconstructed for the last ∼410 kyr based on δ18O and Mg/Ca of planktonic foraminifera from International Ocean Discovery Program Site U1483. By integrating the new and published records, we found that precession drives variation of the ITF thermocline through modulating the intensity of the Australian‐Indonesian winter monsoon, El Niño‐Southern Oscillation‐like states and formation of the North Pacific Tropical Water, in turn exerting a transoceanic influence on the amount of the AL and seawater temperature and salinity of the South Atlantic thermocline. Plain Language Summary: It is widely acknowledged that the Indonesian Throughflow (ITF), a key component of the global thermohaline circulation, plays an important role in the global climate and ocean circulation. However, in contrast to concentrating on the factors that shaped the ITF in the geological history, few studies considered the ITF as a factor to influence climate and ocean circulation, especially on long timescales. In this study, we utilized shell δ18O and Mg/Ca of a planktonic foraminiferal thermocline‐dwelling species from the Timor Sea, the main outflow passage of the ITF, to reconstruct the temperature and salinity changes of the ITF thermocline during the past ∼410 kyr. By integrating the new and published paleo‐oceanographic and ‐climatological records, we found that the ∼20‐kyr wobbles of the Earth's axis (precession) induced variations in the flow strength and seawater temperature and salinity of the ITF thermocline, and in turn regulated the amount of the Agulhas Leakage and seawater temperature and salinity of the South Atlantic thermocline. Our results underscore the essential role of the ITF in the connectivity among the oceans. Key Points: Precession drove variations in the ITF thermocline by modulating the intensity of the Australian‐Indonesian winter monsoon, ENSO‐like states and formation of the North Pacific Tropical WaterVariations in the ITF thermocline regulated the amount of AL and seawater temperature and salinity of South Atlantic thermocline [ABSTRACT FROM AUTHOR]

Our goal was to use the energy budget as a tool to evaluate the effects of salinity (20, 25, 30, 35 or 40‰) and ocean acidification (pH 8.0 or 7.3) in Penaeus vannamei. We assessed the energy budget a range of physiological processes (ingestion, defecation, growth, metabolism, excretion, energy substrate, hepatosomatic index, and osmoregulation). In general, salinity had an accentuated effect than pH, as it altered nearly all physiological parameters, including the energy channeled into growth (up to −56%). Reduced pH also affected the energy budget: increased energy lost in feces (25 and 40‰: +21% and 13%, respectively), excretion (25‰: +55%), and metabolism (20‰: +58%). Furthermore, acidified pH increased oxygen consumption by 60%, which may be related to higher energy expenditure. In conclusion, the energy budget can be a valuable tool for assessing the impacts of environmental stressors and the salinity has an accentuated effect than the ocean acidification predicted. [ABSTRACT FROM AUTHOR]

Seawater temperature and salinity are basic marine environmental parameters, which can be used to calculate other marine environmental parameters. However, most of the on-site observation data have the problems of uneven spatial distribution and time discontinuity, and it is difficult for remote sensing observation methods to obtain subsurface information. In this study, we proposed a deep learning model with combining remote sensing temperature and salinity as well as in-situ measured data by Argo profiles, and the nonlinear relationship was revealed. An effective and direct inversion method was realized for underwater three-dimensional thermohaline structure based on remote sensing temperature and salinity at accurate points on global scale. The SST data were obtained from the FY3C-VIRR daily sea surface temperature product, the SSS data were acquired from the SMAP Level 3 8-day running averages sea surface salinity product, and the Argo scatter data were got from the 'Global Ocean Argo Scatter Data Set'. Based on the temporal and spatial location information of the data, this paper matched the remote sensing data from 2016 to 2019 with the Argo data, 64751 valid pairing points were obtained. The deep learning model was constructed as a multilayer perceptron model with 5 hidden layers. The RMSE of temperature had a maximum value of 2.106°C in 130 m depth and a minimum value of 0.367°C in 1000 m with an average of 1.174°C for validation dataset. And the RMSE of salinity had a maximum value of 0.356 psu in 0 m and a minimum value of 0.045 psu in 1000 m with an average of 0.202 psu. Compared with other methods based on fixed mesh products, this study realized a direct inversion method at any location in the global ocean and improved the inversion accuracy, which provides a reliable data support for refined marine monitoring. [ABSTRACT FROM AUTHOR]

Local ensemble transform Kalman filter (LETKF)‐based Ocean Research Analysis (LORA) version 1.0 datasets for western North Pacific (WNP) and Maritime Continent (MC) regions (LORA‐WNP and ‐MC, respectively) are released through the JAXA‐RIKEN Ocean Analysis website. The LORA datasets are created using an eddy‐resolving LETKF‐based ocean data assimilation system with satellite sea‐surface temperature, salinity, and height data and with in‐situ temperature and salinity data assimilated daily. The LORA datasets include 128‐member ensemble analyses at the sea surface (2D), each term of mixed‐layer temperature and salinity budget equations, and the related variables (2D) such as mixed‐layer depth and heat and freshwater fluxes as well as system grid information and analysis ensemble mean and spread (3D), from August 2015 to January 2024 (as of June 2024). The LORA datasets are useful for geoscience research and practical applications, especially for particle tracking, boundary conditions of atmospheric models, and research on spatiotemporal variations in sea‐surface temperature and salinity. [ABSTRACT FROM AUTHOR]

Using seawater for flushing toilets is a potential solution to reduce freshwater consumption in Guam, an island in the Western Pacific Region. However, elevated salinity levels from seawater can affect microbial treatment efficiency in wastewater plants. To study this effect, synthetic wastewater containing 30 mg/L of ammonium-nitrogen was used to evaluate the impact of various salinity levels on ammonium removal efficiency in a continuously operated polyvinyl-alcohol gel bead bioreactor. The bioreactor was incrementally exposed to salinity levels of 0%, 20%, 30%, 50%, 70%, 80%, and 100%, where 0% represented tap water salinity and 100% was equivalent to Guam's seawater salinity. A recovery phase followed the 100% salinity exposure to assess any changes in treatment processes. The total operational period spanned 212 days. Between 0 and 30% salinity, the ammonium-nitrogen removal efficiency averaged 95.0%, indicating no inhibition of nitrification. However, at 50% salinity, the ammonium-nitrogen concentration began to decrease, and a trend that continued up to 80% salinity, resulting in over 60.0% removal efficiency. At 100% salinity, the removal efficiency rapidly dropped from 59.2% to 15.4% within ten days. When the bioreactor returned to 0% salinity, the removal efficiency quickly recovered to 93.7% within five days. This experiment identified 50% salinity as a critical threshold for nitrification efficiency, while 100% salinity was found to be unfavorable for nitrification. [ABSTRACT FROM AUTHOR]

Intense atmosphere‐ocean‐ice interactions in the Ross Sea play a vital role in global overturning circulation by supplying saline and dense shelf waters. Since the 1960s, freshening of the Ross Sea shelf water has led to a decline in Antarctic Bottom Water formation. However, during 2012–2018, salinity of the western Ross Sea has rebounded. This study adopts a global ocean‐sea ice model to investigate the causes of this salinity rebound. Model‐based surface salinity budget analysis indicates that the salinity rebound was driven by increased brine rejection from sea ice formation, triggered by nearly equal effects of local anomalous winds and surface heat flux. The local divergent wind anomalies promoted local sea ice formation by creating a thin ice area, while cooling heat flux anomaly decreased the surface temperature, increasing sea ice production as well. This highlights the importance of understanding local climate variability in projecting future dense shelf water change. Plain Language Summary: Previous research linked the recent salinity increase in the western Ross Sea to weakened easterly winds from the Amundsen Sea. However, insufficient observations limit the further investigation of the linkage and underlying mechanisms between atmospheric forcing and shelf water salinity changes. In this study, we use a global ocean‐sea ice coupled model to investigate the factors affecting the recent western Ross Sea shelf water salinity increase. Based on a surface salinity budget analysis, we show that the recent salinity increase was supplied by brine rejection induced by increased sea ice formation, triggered almost equally by local anomalous winds and surface heat flux. The local wind anomalies induced a divergent motion in sea ice, reducing sea ice thickness and promoting local sea ice formation. Meanwhile, a negative heat flux anomaly from the atmosphere cools the surface, increasing sea ice production as well. Our study highlights the impact of local climate variability on dense shelf water. Moreover, the model experiment design and salinity budget analysis undertaken here provide an essential reference for identifying the major drivers of the shelf water salinity variations. Key Points: Using a global ocean‐sea ice model, we simulate the recent rebound of Dense Shelf Water salinity in the western Ross Sea during 2012–2018A model‐based salinity budget analysis reveals increased sea ice formation as the primary driver of the observed salinity reboundExperiments indicate that this increased sea ice formation is triggered by the combined effect of local wind stress and surface heat flux [ABSTRACT FROM AUTHOR]

Since the mid-1970s, groundwater resources in Bermuda have been explored to supplement growing potable water demand on the island. Much of this work has focused on modeling the shape and size of freshwater lenses beneath the island's surface, mainly the Devonshire Lens. Less attention has been paid to how these freshwater lenses interact with surrounding coastal seawater, a process that may grow in importance as sea levels rise. Due to isotopic differences between aquifer water and seawater, these interactions can be tracked using the oxygen isotopic composition of water (δ18Ow) samples collected from coastal and subterranean areas. A pilot study found more temporal variation in coastal seawater δ18Ow along Bermuda's South Shore (the section of the coast closest to the Devonshire Lens) compared to elsewhere around the island and suggested that freshwater was discharging into coastal seawater fromthe Devonshire Lens in significant quantities. However, this study was limited by its small dataset so could not quantify the full spatial and temporal variability of δ18Ow in this area. Here, we present salinity and δ18Ow measurements from seawater samples collected around Bermuda and in wells tapping the Devonshire Lens on timescales ranging from hourly to monthly to better visualize the dynamic interaction between coastal seawater and aquifersourced freshwater. We find tight correlation between salinity and δ18Ow in well waters, indicating a simple linear mixing relationship between seawater and aquifer water in the subsurface. We confirm previous findings of larger variability in δ18Ow along the South Shore compared to elsewhere and relate observed changes to tidal height on hourly to monthly timescales. Surprisingly, South Shore seawater salinity does not vary in accordance with δ18Ow, implying additional mechanisms, such as the addition of salt spray, must be acting to mute salinity changes. These findings also demonstrate the potential in using δ18Ow to study submarine groundwater discharge, as salinity measurements alone did not detect as much variability. As sea levels rise and interactions between ocean and aquifer waters change, coastal and well water δ18Ow measurements may be helpful in tracking these processes, and in particular, changes in aquifer size. [ABSTRACT FROM AUTHOR]

Marine microbes that have for eons been adapted to stable salinity regimes are confronted with sudden decreases in salinity in the Arctic Ocean. The episodic freshening is increasing due to climate change with melting multi-year sea-ice and glaciers, greater inflows from rivers, and increased precipitation. To investigate algal responses to lowered salinity, we analyzed the responses and acclimatation over 24 h in a non-model Arctic marine alga (pelagophyte CCMP2097) following transfer to realistic lower salinities. Using RNA-seq transcriptomics, here we show rapid differentially expressed genes related to stress oxidative responses, proteins involved in the photosystem and circadian clock, and those affecting lipids and inorganic ions. After 24 h the pelagophyte adjusted to the lower salinity seen in the overexpression of genes associated with freezing resistance, cold adaptation, and salt tolerance. Overall, a suite of ancient widespread pathways is recruited enabling the species to adjust to the stress of rapid salinity change. The authors analyzed the response of an Arctic pelagophyte to lowered salinity. They observed that several ancient and widespread pathways were activated, allowing the species to adjust to the stress of rapid salinity change. [ABSTRACT FROM AUTHOR]

As our planet warms, Arctic sea ice coverage continues to decline, resulting in complex feedbacks with the climate system. The core objective of NASA's Salinity and Stratification at the Sea Ice Edge (SASSIE) mission is to understand how ocean salinity and near-surface stratification affect upper-ocean heat content and thus sea ice freeze and melt. SASSIE specifically focuses on the formation of Arctic Sea ice in autumn. The SASSIE field campaign in 2022 collected detailed observations of upper-ocean properties and meteorology near the sea ice edge in the Beaufort Sea using ship-based and piloted and drifting assets. The observations collected during SASSIE include vertical profiles of stratification up to the sea surface, air–sea fluxes, and ancillary measurements that are being used to better understand the role of salinity in coupled Arctic air–sea–ice processes. This publication provides a detailed overview of the activities during the 2022 SASSIE campaign and presents the publicly available datasets generated by this mission (available at https://podaac.jpl.nasa.gov/SASSIE , last access: 29 May 2024; DOIs for individual datasets in the "Data availability" section), introducing an accompanying repository that highlights the numerical routines used to generate the figures shown in this work. [ABSTRACT FROM AUTHOR]

Antarctic snow on sea ice can contain slush, snow ice, and stratified layers, complicating satellite retrieval processes for snow depth, ice thickness, and sea ice concentration. The presence of moist and brine-wetted snow alters microwave snow emissions and modifies the energy and mass balance of sea ice. This study assesses the impact of brine-wetted snow and slush layers on L-band surface brightness temperatures (TBs) by synergizing a snow stratigraphy model (SNOWPACK) driven by atmospheric reanalysis data and the RAdiative transfer model Developed for Ice and Snow in the L-band (RADIS-L) v1.0 The updated RADIS-L v1.1 further introduces parameterizations for brine-wetted snow and slush layers over Antarctic sea ice. Our findings highlight the importance of including both brine-wetted snow and slush layers in order to accurately simulate L-band brightness temperatures, laying the groundwork for improved satellite retrievals of snow depth and ice thickness using satellite sensors such as Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP). However, biases in modelled and observed L-band brightness temperatures persist, which we attribute to small-scale sea ice heterogeneity and snow stratigraphy. Given the scarcity of comprehensive in situ snow and ice data in the Southern Ocean, ramping up observational initiatives is imperative to not only provide satellite validation datasets but also improve process-level understanding that can scale up to improving the precision of satellite snow and ice thickness retrievals. [ABSTRACT FROM AUTHOR]

The mud deposit areas on continental shelf have developed in a relatively steady sedimentary condition with high sedimentation rates, thus rendering them ideal regions for exploring high-resolution paleo-sedimentary environment records. Since the sedimentary environment of the continental shelf is subject to the compound influence of multiple factors, the reconstruction of water salinity and temperature and comprehensive analysis of their response to global climate change remains challenging. Therefore, the present study characterized water salinity and temperature of the North Yellow Sea (NYS) using proxies, such as ratios of halogen elements of sediments and stable isotopic compositions of benthic foraminifera, and found the halogen elements of Cl in sediments was good proxy for water salinity. The evolutions of water salinity and temperature of the NYS for the past 3000 years were reconstructed, while the evolution stages and drivers of the sedimentary environment were explored. From approximately 3000 cal yr BP, the sea bottom salinity and temperature of the NYS were found to follow the same evolution trends predominantly consisting of the three stages: relatively low seawater salinity and temperature during 3000−2000 cal yr BP; relatively high seawater salinity and temperature during 2000−460 cal yr BP; and rapid changes of seawater salinity and temperature since 460 cal yr BP. The changes in seawater salinity and temperature of the NYS were largely driven by the East Asian winter monsoon (EAWM) as well as the influence of the Kuroshio Current. As the EAWM fluctuated, changes occurred in the flux of low temperature, low salinity coastal current water into the Yellow Sea, with concomitant changes in bottom temperature and salinity. Strengthening of the Kuroshio Current promoted the development of the Yellow Sea Warm Current, while the influx of warm, salty water into the Yellow Sea influenced the respective sea region. The abrupt global climate changes such as the "Little Ice Age" and the Medieval Warm Period first affected the East Asian monsoon, followed by the respective sea region. [ABSTRACT FROM AUTHOR]

Salinity gradient energy presents a promising opportunity for renewable energy, gaining significant interest in the sustainable power sector. This article presents an overview of the application of ion exchange membranes and reverse electrodialysis techniques to harness energy from salinity gradients in seawater, employing anthropomorphic terminology to enhance understanding. The main focus lies in the utilization of ion exchange membrane technology for power generation, with a particular emphasis on its current implementation status and underlying operational principles. The research aims to enhance readers' comprehension of salinity gradient energy in seawater and promote awareness of "energy security" through the use of descriptive language. [ABSTRACT FROM AUTHOR]

The average salinity of seawater is 3.5%, with a significant presence of corrosive ions, primarily Cl− and SO42−. In contrast to cement engineering in terrestrial natural environments, cement-reinforced structures exposed to corrosive marine environments not only endure ion erosion but also undergo periodic desiccation due to tidal variations in seawater. The coupling of these effects results in a reduction in the mechanical properties of cemented soil, inevitably leading to the degradation of cemented foundations, posing a serious threat to their safety and normal functionality. Investigating the improvement of the mechanical properties of cemented soil in corrosive coastal environments is a crucial engineering challenge in current coastal construction projects. To address this engineering challenge, this study proposes the use of Nano-SiO2 to enhance the mechanical characteristics of cemented soil, aiming to improve the strength and durability of cement-reinforced structures. Simulating the main corrosive ions in seawater by using different concentrations of SO42− ions, the study subjected cemented soil samples to dry–wet cycles to simulate the desiccation caused by tidal changes in seawater. Unconfined compressive strength tests were conducted on cemented soil and nano-cemented soil samples under coupled conditions, revealing that the incorporation of Nano-SiO2 increased the strength of cemented soil and slowed down the corrosion rate. With an ion concentration of 12.3 g/L, after 60 dry and wet cycles, the compressive strength of nano-cemented soil increased by 90% compared to conventional cemented soil, with a mass loss only half that of conventional cemented soil. XRD, SEM, and NMR tests on various cemented soil samples indicated that the addition of Nano-SiO2 filled small pores, suppressed pore development, and interacted with cement hydration products, forming a gel-like structure that improved the compactness of cemented soil. This, in turn, mitigated ion corrosion and the degradation of cemented soil under dry–wet cycles. [ABSTRACT FROM AUTHOR]

Ocean salinity plays an important role in oceanographic research as one of the fundamental parameters. An optical salinometer based on the Michelson interferometer (MI) suitable for in situ measurement in deep-sea environments is proposed in this work, and it features real-time calibration and multichannel multiplexing using the frequency modulated continuous wave (FMCW) technique. The symmetrical sapphire structure used to withstand deep-sea pressure can not only achieve automatic temperature compensation, but also counteract the changes in optical path length under deep-sea pressure. A model formula suitable for optical salinity demodulation is proposed through the nonlinear least squares fitting method. In vertical profile testing, the optical salinometer demonstrated remarkable tracking performance, achieving an error of less than 0.001 psu. The sensor displays a stable salinity demodulation error within ±0.002 psu during a three-month long-term test at a depth of 4000 m. High stability and resolution make this optical salinometer have broad development prospects in ocean observation. [ABSTRACT FROM AUTHOR]

This paper examines the viability of introducing solar thermal desalination technology as a means to supplement existing water production methods in the Republic of South Africa (RSA). The study provides an overview of the current state of desalination technology in the country. A key aspect of this study involves comparing the RSA with the Middle East and North Africa (MENA) region, using publicly available studies and reports. The focus of this comparison is to highlight the potential implementation of large-scale solar desalination in the RSA by evaluating the respective resources and environmental data that directly impact the input and output of a thermal desalination system. The study comparatively analyzes the environmental conditions and seawater salinity of the RSA and the MENA region. The RSA receives a higher solar irradiation range of 4.5–6.5 kWh/m2, whereas the MENA region experiences a range of 3.5–5.5 kWh/m2. Additionally, the salinity of the RSA's seawater ranges between 35 and 35.5 parts per thousand, which is lower than the MENA region's range of 36–40 parts per thousand. The study also reviews and proposes the adoption of an emerging thermal desalination method that has been successfully tested in the MENA region and other countries, based on its performance. [ABSTRACT FROM AUTHOR]

Salinity is an essential variable for characterizing and understanding the state of the ocean and its role in the climate system. Gridded ocean salinity products, heavily reliant on Argo float measurements since the early 2000s, are widely used in oceanographic and climate research. However, a concerning issue of instrument drift leading to spurious salinity increases ("salty drift") has been identified in a significant number of Argo floats since 2015. This study investigates the potential consequences of this "salty drift" issue on various gridded salinity products. We compare a suite of these products and evaluate their consistency, particularly from 2015 to 2019. Our analysis reveals two major issues with the gridded salinity products after 2015: a sudden increase in global mean salinity and elevated inconsistencies between gridded salinity products. In 2015–2019, the North Indian and North Atlantic Oceans emerged as regions displaying particularly large disagreements between gridded products compared to the prior period, 2010–2014. These findings highlight the substantial impact of the "salty drift" on the reliability of the gridded salinity products. They also underline the critical need for the oceanography community to address these issues to ensure the validity of future ocean and climate studies that utilize gridded salinity products. Plain Language Summary: Salinity is crucial for understanding our planet's oceans and climate. Since 2015, some Argo floats have produced inaccurate salinity measurements that drift to higher values. This study examined several widely used ocean salinity products that were produced primarily based on Argo float measurements to assess how they are affected by the "salty drift" floats. We found that between 2015 and 2019, most of the examined products showed unrealistic increases in global mean salinity and became less consistent than before. Regions most likely affected include the North Indian and North Atlantic Oceans. This "salty drift" issue can impact previous and future global and regional studies using gridded salinity products after 2015 and needs further detailed study by the oceanography and climate communities. Key Points: Multiple gridded salinity products show an unrealistic rise in global mean salinity after 2015, with increases of up to 1.3 × 10−3 per yearThe spread of global mean salinity tripled between 2015 and 2019, translating to an uncertainty of about 1 cm in halosteric sea levelAfter 2015, over 60% of the global ocean, including the North Atlantic and North Indian Oceans, exhibited increased uncertainty in salinity change [ABSTRACT FROM AUTHOR]

• Seawater salinity largely determines the interaction and cotransport of NPs and nZnO. • nZnO reduces NPs mobility at 35 PSU due to formation of secondary heteroaggregates. • NPs promote nZnO transport at 3.5 PSU due to formation of primary heteroaggregates. • In the salinity ranges of 7.1–16.4 PSU, the mobility of NPs and nZnO drops rapidly. • A key threshold is observed at 10.4 PSU, where colloidal mobility suddenly declines. The ocean serves as a repository for various types of artificial nanoparticles. Nanoplastics (NPs) and nano zinc oxide (nZnO), which are frequently employed in personal care products and food packaging materials, are likely simultaneously released and eventually into the ocean with surface runoff. Therefore, their mutual influence and shared destiny in marine environment cannot be ignored. This study examined how nanomaterials interacted and transported through sea sand in various salinity conditions. Results showed that NPs remained dispersed in brine, while nZnO formed homoaggregates. In seawater of 35 practical salinity units (PSU), nZnO formed heteroaggregates with NPs, inhibiting NPs mobility and decreasing the recovered mass percentage (M eff) from 24.52% to 12.65%. In 3.5 PSU brackish water, nZnO did not significantly aggregate with NPs, and thus barely affected their mobility. However, NPs greatly enhanced nZnO transport with M eff increasing from 14.20% to 25.08%, attributed to the carrier effect of higher mobility NPs. Cotransport from brackish water to seawater was simulated in salinity change experiments and revealed a critical salinity threshold of 10.4 PSU, below which the mobility of NPs was not affected by coexisting nZnO and above which nZnO strongly inhibited NP transport. This study highlights the importance of considering the mutual influence and shared destiny of artificial nanoparticles in the marine environment and how their interaction and cotransport are dependent on changes in seawater salinity. [Display omitted] [ABSTRACT FROM AUTHOR]

• Diatoms shaped by Si enrichment or low salinity accumulated more Cd and Cu. • Si-enriched cells under low salinity showed the highest instantaneous metal influx. • The adsorption capacity of diatoms is mediated by cell wall physicochemical traits. • Lower Si availability and salinity led to rougher cell walls with larger surface area. • Higher silicification level decreased cell surface potential with more silanol groups. Increasing nitrogen and phosphorus discharge and decreasing sediment input have made silicon (Si) a limiting element for diatoms in estuaries. Disturbances in nutrient structure and salinity fluctuation can greatly affect metal uptake by estuarine diatoms. However, the combined effects of Si and salinity on metal accumulation in these diatoms have not been evaluated. In this study, we aimed to investigate how salinity and Si availability combine to influence the adsorption of metals by a widely distributed diatom Phaeodactylum tricornutum. Our data indicate that replete Si and low salinity in seawater can enhance cadmium and copper adsorption onto the diatom surface. At the single-cell level, surface potential was a dominant factor determining metal adsorption, while surface roughness also contributed to the higher metal loading capacity at lower salinities. Using a combination of non-invasive micro-test technology, atomic force microscopy, X-ray photoelectron spectroscopy, and Fourier transform infrared spectroscopy, we demonstrate that the diversity and abundance of the functional groups embedded in diatom cell walls vary with salinity and Si supply. This results in a change in the cell surface potential and transient metal influx. Our study provides novel mechanisms to explain the highly variable metal adsorption capacity of a model estuarine diatom. [Display omitted] [ABSTRACT FROM AUTHOR]

We investigate the role of the subpolar North Atlantic (SPNA) for downstream predictability, using two decadal climate prediction systems. We use the subpolar extreme cold and fresh anomaly event developing in winter 2013/2014 as initial conditions and evaluate ensemble predictions of the two systems in the following decade. In addition, we perform ensemble pacemaker experiments where the models are forced toward observed ocean temperature and salinity anomalies in the SPNA from November 2014 through December 2019. The pacemaker experiments show improved skill along the Atlantic Water pathway, compared with the standard decadal predictions, and we therefore conclude that the correct description of the ocean in the SPNA is the key. The enhanced skill is most prominent in subsurface salinity in the form of propagating anomalies. Plain Language Summary: Observations show that ocean anomalies propagate across the North Atlantic and further north along the Norwegian coast. Anomalous ocean temperatures can modify heat exchange between ocean and atmosphere and influence the circulation of the atmosphere. Since such anomalies can persist for months, it potentially opens a door to seasonal prediction of the atmosphere. However, climate models used for seasonal and decadal prediction fail to predict these propagating anomalies. In our study we aim to find causes for this lack of predictability. We use the record low temperatures observed in the North Atlantic in 2015 as a test case. We employ two climate prediction systems and make two types of predictions: one type is a standard prediction initialized with winter 2014/2015 ocean conditions; the other type is initialized in the same way and in addition, the model is kept close to observations in the subpolar gyre during the whole prediction, in the region where the cold blob was formed. Comparing the two types of predictions, we see that keeping the model close to observations in the subpolar gyre increases the predictability along the Norwegian coast. This points to the subpolar gyre as a key area where models need to be improved. Key Points: Knowing temperature and salinity in the subpolar gyre increases skill downstream along the Atlantic Water pathwaySalinity anomalies propagate northward, while temperature anomalies are more difficult to traceA pacemaker experiment has been used for decadal predictions for the first time [ABSTRACT FROM AUTHOR]

In-situ measurements of ocean temperature and salinity are critical to ocean-related studies but are limited in space and time. Satellite retrievals provide high-resolution, globally-covered sea surface temperature (SST), salinity (SSS) and cannot directly measure the subsurface information., and height (SSH), but are limited to the ocean surface and cannot directly measure the subsurface information. Here we design a physics-informed algorithm that can reconstruct the vertical distributions of upper ocean temperature and salinity based purely on satellite observations. The algorithm stresses the tight ocean surface-subsurface coupling and the co-variability of ocean temperature and salinity. It is firstly tested with climate model simulations and then validated with actual observations by Argo floats, moored buoys and multiple ocean reanalysis datasets. The resultant satellite-based upper ocean temperature and salinity dataset has a global coverage, a high spatial resolution, and resolves ocean thermohaline structure from surface to 400 m. This dataset complements existing ocean subsurface products as an independent satellite-based observational dataset. The success of our reconstruction algorithm highlights a pressing need to maintain and advance the satellite observations of SST, SSS, and SSH. The reconstructed ocean temperature and salinity dataset can be accessed at https://doi.org/10.5281/zenodo.13145129 (Liu, 2024) and be used by researchers to study mesoscale ocean phenomena, assess the ocean heat content in various sea areas and etc. [ABSTRACT FROM AUTHOR]

The U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) version 2.1 builds on E3SMv2 with several changes, the most notable being the addition of the Fox-Kemper et al. (2011) mixed layer eddy parameterization. This parameterization captures the effect of finite-amplitude, mixed layer eddies as an overturning streamfunction and has the primary function of restratification. Herein, we outline the changes to the mean climate state of E3SM that were introduced by the addition of this parameterization. Overall, the presence of the submesoscale parameterization improves the fidelity of the v2.1 simulation by reducing the North Atlantic ocean surface biases present in v2, as illustrated by changes to the climatological sea surface temperature and salinity, as well as Arctic sea-ice extent. Other impacts include a slight shoaling of the mixed layer depths in the North Atlantic, as well as a small improvement to the Atlantic Meridional Overturning Circulation (AMOC). We note that the expected shoaling due to the parameterization is regionally dependent in our coupled configuration. In addition, we investigate why the parameterization and its impacts on mixed layer depth have little impact on the simulated AMOC: despite increased dense water formation in the Norwegian Sea, only a small fraction of the water formed makes its way south into the North Atlantic basin. Version 2.1 also exhibits small improvements in the atmospheric climatology, with smaller biases in many notable quantities and modes of variability. [ABSTRACT FROM AUTHOR]

Introduction: Salinity is a key variable in the dynamic and thermal balance of the entire climate system. To address the complexities of diverse terrains and fluctuating ocean waves, we commonly use free-surface models with quasistationary (e.g. height, pressure, or terrain following) coordinates for simulating salinity. In such models, the vertical grid dynamically adjusts with the undulation of seawater. However, this adjustment also occurs when freshwater enters or exits the ocean. Freshwater-induced salinity changes at the ocean's surface are artificially distributed to each vertical layer within a model time step. This means that the freshwater at the ocean surface instantaneously and directly affects the seafloor. This process is different from physical diffusion processes. The diffusion effects caused by the influx and outflow of freshwater have a very small impact on the seafloor. This error leads to salinity non-conservation and disrupts the vertical distribution structure of salinity. Previous studies have also addressed this issue with solutions such as the vertical Lagrangian-remap method. Method: This paper proposes a natural vertical distribution calculation scheme (NVDCS) which is different from the approaches of our predecessors. In the discrete formulation of the original ocean equations, freshwater flux is introduced to ensure salinity conservation. In each model time step, by calculating the seawater volume changes due to freshwater inflow or outflow, as well as the vertical grid changes caused by sea surface undulations, the aforementioned artificial error is eliminated from each vertical layer. Discussion: This scheme ensures that changes in the vertical coordinates of each layer result solely from internal oceanic dynamic processes, avoiding the instantaneous and directly impact of surface freshwater. Ultimately, the influence of freshwater is confined to the ocean surface. Results: This method is straightforward to implement and user-friendly. Sensitivity experiments indicate that in free-surface models, quasi-stationary coordinates introduce artificial errors. The proposed calculation scheme not only eliminates this error but also achieves a better vertical distribution structure than using virtual salt flux, while ensuring salinity conservation. [ABSTRACT FROM AUTHOR]

The residual oil left behind after water flooding in petroleum reservoirs can be mobilized by surfactant formulations that yield ultralow interfacial tension (IFT) with oil. However, finding ultralow IFT surfactant formulations is difficult for high-temperature, off-shore, carbonate reservoirs. These reservoirs are often water-flooded with seawater (with a lot of divalent ions), which is often incompatible with many surfactants at high temperatures. The goal of this research is to develop a surfactant formulation for an off-shore carbonate reservoir at 100°C previously flooded by seawater. Surfactant-oil-brine phase behavior was studied for formulations, starting from a single surfactant to mixtures of surfactants and a co-solvent. Mixtures of three surfactants and one co-solvent were needed to produce ultralow IFT formulations for the oil of interest. The surfactant system with polymer mobility control was tested in crushed reservoir rock packs. The cumulative oil recovery was >99% for the surfactant-polymer (SP) flood with an optimal salinity gradient. The constant salinity SP floods with seawater increased oil recovery significantly beyond the water flood (cumulative oil recovery >91%), even though the recovery was lower than that of the optimal salinity gradient SP flood. Our experimental work demonstrates the effectiveness of the surfactant formulation for a high-temperature carbonate reservoir at seawater salinity. [ABSTRACT FROM AUTHOR]

A novel demodulation scheme for a point-type fiber sensor is designed for salinity concentration monitoring based on a Sagnac interferometer (SI) composed of a tapered polarization-maintaining fiber (TPMF) and optical time stretching technology. The SI, constructed using a PMF with a taper region of 5.92 μm and an overall length of 30 cm, demonstrated a notable enhancement in the evanescent field, which intensifies the interaction between the light field and external salinity. This enhancement allows for a direct assessment of salinity concentration changes by analyzing the variations in the SI reflection spectra and the experimental results indicate that the sensitivity of the sensor is 0.151 nm/‰. In contrast to traditional fiber optic sensors that depend on spectral demodulation with slower response rates, this work introduces a new approach where the spectral shift is translated to the time domain, utilizing a dispersion compensation fiber (DCF) with the demodulation rate reaching up to 50 MHz. The experimental outcomes reveal that the sensor exhibits a sensitivity of −0.15 ns/‰ in the time domain. The designed sensor is anticipated to play a pivotal role in remote, real-time monitoring of ocean salinity. [ABSTRACT FROM AUTHOR]

In addition to technical issues related to the instruments used, differences between soil moisture (SM) measured using ground-based methods and microwave remote sensing (RS) can be related to the main features of the study areas, which are intricately connected to hydraulic–hydrological conditions and soil properties. When long-term analysis is performed, these discrepancies are mitigated by the contribution of SM seasonality and are only evident when high-frequency variations (i.e., signal anomalies) are investigated. This study sought to examine the responsiveness of SM to seasonal variations in terrestrial ecoregions located in areas covered by the in situ Romanian Soil Moisture Network (RSMN). To achieve this aim, several remote sensing-derived retrievals were considered: (i) NASA's Soil Moisture Active and Passive (SMAP) L4 V5 model assimilated product data; (ii) the European Space Agency's Soil Moisture and Ocean Salinity INRA–CESBIO (SMOS-IC) V2.0 data; (iii) time-series data extracted from the H115 and H116 SM products, which are derived from the analysis of Advanced Scatterometer (ASCAT) data acquired via MetOp satellites; (iv) Copernicus Global Land Service SSM 1 km data; and (v) the "combined" European Space Agency's Climate Change Initiative for Soil Moisture (ESA CCI SM) product v06.1. An initial assessment of the performance of these products was conducted by checking the anomaly of long-term fluctuations, quantified using the Absolute Variation of Local Change of Environment (ALICE) index, within a time frame spanning 2015 to 2020. These correlations were then compared with those based on raw data and anomalies computed using a moving window of 35 days. Prominent correlations were observed with the SMAP L4 dataset and across all ecoregions, and the Balkan mixed forests (646) exhibited strong concordance regardless of the satellite source (with a correlation coefficient RALICE > 0.5). In contrast, neither the Central European mixed forests (No. 654) nor the Pontic steppe (No. 735) were adequately characterized by any satellite dataset (RALICE < 0.5). Subsequently, the phenological seasonality and dynamic behavior of SM were computed to investigate the effects of the wetting and drying processes. Notably, the Central European mixed forests (654) underwent an extended dry phase (with an extremely low p-value of 2.20 × 10−16) during both the growth and dormancy phases. This finding explains why the RSMN showcases divergent behavior and underscores why no satellite dataset can effectively capture the complexities of the ecoregions covered by this in situ SM network. [ABSTRACT FROM AUTHOR]

Efforts to detect long‐term changes in global mean evaporation minus precipitation over the ocean remain ambiguous. Here we define an ad hoc sea surface salinity index to assess the observed and simulated intensification of the freshwater flux pattern over the global ocean and, thus, of the overall water cycle. A recent salinity reconstruction shows a long‐term amplification of the climatological patterns, thereby supporting the popular "fresh gets fresher, salty gets saltier" paradigm. Unlike in a previous study, no systematic underestimation of this amplification is found in the latest generation of global climate models. Yet, the "fresh gets fresher" paradigm is much more robust than its "salty gets saltier" counterpart and the proposed salinity index does not yet provide a strong constraint on the model‐dependent projected intensification of the global water cycle intensification along the 21st century. Plain Language Summary: Recent changes in continental mean precipitation and evaporation remain poorly observed and thus poorly constrained in both atmospheric reanalyzes and global climate models. Here we propose a new index based on global sea surface salinity contrasts as a surrogate of changes in metric of the water cycle intensity. Overall, both observed and simulated indices support the "fresh gets fresher, salty gets saltier" paradigm, widely used to depict the overall intensification of the water cycle. Unlike in a previous study, no systematic underestimation of the observed amplification in salinity patterns is found in the latest generation of global climate models. The "salty gets saltier" response is however less robust than the "fresh gets fresher" and the proposed salinity index is not yet very useful to constrain the future intensity of the global water cycle. Key Points: Both observations and climate models evidence an amplification of the global ocean climatological contrasts in sea surface salinity (SSS)Yet, the "fresh gets fresher" paradigm is more robust than its salty counterpart, which is more sensitive to the ocean domain's definitionGlobal SSS observations do not yet provide a strong constraint on the projected intensification of the global water cycle [ABSTRACT FROM AUTHOR]

We propose interpreting the vertical structure of waters not only in space but also over time, taking into account the continuous variability of the ocean and the independence of temperature and salinity parameters. This approach allows us to consider, in real conditions, the entire spectrum of short- and long-term extrema of both characteristics, either separately or together at the same depth. Vertical distributions of temperature and salinity transform separately and independently of each other under the influence of heat and freshwater budgets, which change at different time scales. Each of the parameters has its own active layers with corresponding time scales. Changes in the signs of heat and freshwater budgets and subsequent changes in the characteristics of the surface layer cause the appearance and disappearance of separate extrema of temperature and salinity in the water column. Using a salinity field as an example, we have shown that each of the extrema, in their vertical distribution from the near-surface to the intermediate depths, is a temporary phenomenon with various lifetime scales and is located at the lower boundary of the corresponding active layers. In some areas of the ocean, temperature and salinity extrema exist together at the same depth. Volumes of water with such characteristics and explicit boundaries should be considered water masses. [ABSTRACT FROM AUTHOR]

Anthropogenic activities are driving significant changes in coastal ecological environments, increasingly spotlighting microorganisms associated with seagrass bed ecosystems. Labyrinthula is primarily recognized as a saprophytic protist associated with marine detritus, and it also acts as an opportunistic pathogen affecting marine algae, terrestrial plants and mollusks, especially in coastal environments. The genus plays a key role in the decomposition of marine detritus, facilitated by its interactions with diatoms and through the utilization of a diverse array of carbohydrate-active enzymes to decompose seagrass cell walls. However, human activities have significantly influenced the prevalence and severity of seagrass wasting disease (SWD) through factors such as climate warming, increased salinity and ocean acidification. The rise in temperature and salinity, exacerbated by humaninduced climate change, has been shown to increase the susceptibility of seagrass to Labyrinthula, highlighting the adaptability of pathogen to environmental stressors. Moreover, the role of seagrass in regulating pathogen load and their immune response to Labyrinthula underscore the complex dynamics within these marine ecosystems. Importantly, the genotype diversity of seagrass hosts, environmental stress factors and the presence of marine organisms such as oysters, can influence the interaction mechanisms between seagrass and Labyrinthula. Besides, these organisms have the potential to both mitigate and facilitate pathogen transmission. The complexity of these interactions and their impacts driven by human activities calls for the development of comprehensive multi-factor models to better understand and manage the conservation and restoration of seagrass beds. [ABSTRACT FROM AUTHOR]

Two L-band passive microwave satellite sensors, onboard the Soil Moisture and Ocean Salinity (SMOS) launched in 2009 and Soil Moisture Active Passive (SMAP) launched in 2015, are specifically designed for surface soil moisture (SM) monitoring. The first global continuous fused L-band satellite SM product based on SMOS and SMAP observations (SMOS-SMAP-INRAE-BORDEAUX, the so-called Fused-IB) was recently released to the public. Currently, the performance of Fused-IB has only been evaluated collectively over the entire data records in the study period, without specific evaluation for individual seasons. To fill this gap, this study intercompared the Fused-IB and the enhanced SMAP-L3 version 6 (SMAP-E) SM products against in situ SM data from the International Soil Moisture Network (ISMN) from 2016 to 2020 regarding the whole period and different seasons. We aim to investigate the performance of these two products at different time scales and to explore the potential ecohydrological factors (i.e., precipitation and vegetation) driving their seasonal variations. Results show that both SM products are in good agreement with the in situ measurements, demonstrating high median correlation (R) and low ubRMSD (median R = 0.70 and ubRMSD = 0.058 m³/m³ for Fused-IB vs. R = 0.68 and ubRMSD = 0.059 m³/m³ for SMAP-E) during 2016-2020. For most land use and land cover (LULC) types, Fused-IB outperformed SMAP-E with higher accuracy and lower errors, particularly in forests, partly due to the advantage of the robust SMAP-IB (SMAP-INRAE-BORDEAUX) algorithm used to generate Fused-IB in forests, which avoids the pronounced saturation effects of vegetation optical depth caused by relying on optical information. Besides, both products had superior performances across most LULC types in summer (JJA) and autumn (SON), yet increased uncertainties were observed in forests, grasslands, and croplands during spring (MAM) and winter (DJF). These uncertainties could be mainly attributed to the effects of vegetation growth in forests, grasslands and croplands, and the interception of water from rainfall events in grasslands. The results of this study can serve as a reference for algorithm developers to enhance the accuracy of SM and thus promote hydrometeorological applications that benefit from L-band radiometer soil moisture products. [ABSTRACT FROM AUTHOR]

Advancements in global satellite missions have revolutionized the assessment of Surface Soil Moisture (SSM) at global to local scales. However, spatio-temporal data discontinuities in specific regions remain a challenge. This study proposes a Machine Learning (ML)-based framework to extend the Soil Moisture Ocean Salinity (SMOS) SSM product both in the spatial and temporal domains, over Canada. In the first phase of the proposed framework, ML models based on Random Forest (RF) and Convolutional Neural Networks (CNN) are trained and validated with SMOS SSM as target and SSM-relevant climatic variables and geophysical variables, obtained from fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data (ERA5), for the 2011–2020 period, as predictors. Developed models, when tested on unseen data for the years 2021–2022, suggest slightly better performance of the RF model compared to CNN, with root mean square error (RMSE) of 0.033 and 0.056 respectively; prediction biases mostly noted for regions with large inter-annual variability. The spatial filling of SSM for grid cells that were excluded during the training process, with similar land types as those in the SMOS training data, yields reasonable performance, with RF (RMSE = 0.013) performing better than CNN (RMSE = 0.064). In the second phase, the RF model is selected to extend the SMOS dataset for the 2008–2010 period. The temporal correlation between extended SMOS and ASCAT (Advanced Scatterometer) SSM demonstrates a reasonable association, with correlation coefficient exceeding 0.6. Additionally, spatial correlation analysis reveals similar patterns between the two datasets, with smaller values for the summer season owing to the importance of local processes on SSM during this period. However, extending SMOS SSM spatially for surface types that were not included in the training process such as peatlands, remains a challenge warranting additional studies. The developed framework is robust and can address spatio-temporal discontinuities in other SSM products. [ABSTRACT FROM AUTHOR]

Salinity is a very important parameter from an environmental perspective, and therefore, efficient and accurate systems are required for marine environmental monitoring and productive industries. A plasmonic sensor based on doubly deposited tapered optical fibers (DLUWTs—double-layer uniform-waist tapers) for the measurement of salinity is presented. The physical principle of the sensor, as well as its structure, is discussed, and its performance is experimentally demonstrated, obtaining very good sensitivities. The possibility of shifting towards higher wavelength measuring ranges associated with DLUWTs is also exploited. At the same time, we have considered the necessity of an extensive characterization of the behavior of the refractive index of salty water, both with variations in temperature and the composition of the salts dissolved. This is important due to the somehow changing reality of salinity measurements and the possibility of establishing new approaches for the determination of absolute salinity as opposed to practical salinity based on electrical conductivity measurements. The results obtained, which show high sensitivity and a good performance in general without the need for the use of semi-empirical algorithms, permit, in our opinion, an advance in the tendency towards refractometric determination of salinity with optical sensors apt for in situ, real-time, accurate measurements in realistic measuring conditions. [ABSTRACT FROM AUTHOR]

Sampling was done over a year (December 2020–November 2021) to study the distribution and species composition of phytoplankton in the southwestern Caspian Sea. Sea water from various depths was collected along four transects: Lisar, Anzali, Sefidrood and Chaboksar, with a total of 12 stations. A comparison was then made with the data collected in 1996 to look at the long-term changes. The increase in sea water temperature and salinity, especially in summer, was observed in the present study, which was possibly due to global warming and climate change. Amongst 48 identified phytoplankton species, Bacillariophyta (80.0%) and Cyanophyta (11.0%) were dominant. Phytoplankton abundance was measured as 99,775 ± 30,200 cell L−1 on average. The highest abundance was a non-native species Pseudo-nitzschia seriata (H. Peragallo 1900) from Bacillariophyta with more than 17,000 cell L−1, followed by another toxic species Nodularia spumigena (Mertens ex Bornet and Flahault 1888) from Cyanophyta. The N. spumigena species had the highest abundance as 5,000,000 cell L−1 in July 2021 at the Anzali region. Nutrient increase of more than threefold in 2020–2021 has caused a sevenfold increase of chlorophyll-a as compared to that in 1996. The increases in nutrients levels, sea surface temperature (> 30 °C) and salinity are generally regarded as important factors to cause variations in phytoplankton abundance and composition. The sevenfold increase of phytoplankton abundance between 1996 and 2020–2021 and change of trophic state from oligotroph to mesotroph, indicated the increase of stress and pressure on the native phytoplankton community. [ABSTRACT FROM AUTHOR]

In contrast to fairly good knowledge of seasonal and interannual variability in North Atlantic salinity, its long-term historical changes remain poorly characterized, making it difficult to assess the current state and possible future changes. To fill this gap, we present the results of applying a non-parametric method of regression analysis (quantile regression) to assess long-term changes in North Atlantic salinity (0°–70° N, 8°–80° W) based on multiple datasets. The features of quantile trends in monthly salinity for a median value in two periods (1948–2018 and 1961–2011) are considered. In 1948–2018, salinization was generally detected in North Atlantic tropical and subtropical latitudes, while desalination was found in subpolar latitudes. For the 71-year period under consideration, the median monthly salinity in subtropical latitudes increased by 0.07 ± 0.02 PSU. Over the period 1961–2011, pronounced long-term changes in the North Atlantic salinity are difficult to identify based on the datasets used. A consistency analysis of significant salinity trends across the most used datasets allowed us to detect five small areas with pronounced positive trends in the upper ocean salinity. These include the Guiana Current, the vicinity of 12° N, 48° W, the Canary upwelling area, the region of the Gulf Stream transition to the North Atlantic Current and the western part of the North Atlantic Subpolar Gyre. In these areas, over a 51-year period, salinity in the 10–400 m layer increased by an average of 0.10 ± 0.04 PSU. [ABSTRACT FROM AUTHOR]

High-resolution three-dimensional (3D) variations in ocean temperature and salinity fields are of great significance for ocean environment monitoring. Currently, AI-based 3D temperature and salinity field predictions rely on expensive 3D data, and as the prediction period increases, the stacking of high-resolution 3D data greatly increases the difficulty of model training. This paper transforms the prediction of 3D temperature and salinity into the prediction of sea surface elements and the inversion of subsurface temperature and salinity using sea surface elements, by leveraging the relationship between sea surface factors and subsurface temperature and salinity. This method comprehensively utilizes multi-source ocean data to avoid the issue of data volume caused by stacking high-resolution historical data. Specifically, the model first utilizes 1/4° low-resolution satellite remote sensing data to construct prediction models for sea surface temperature (SST) and sea level anomaly (SLA), and then uses 1/12° high-resolution temperature and salinity data as labels to build an inversion model of subsurface temperature and salinity based on SST and SLA. The prediction model and inversion model are integrated to obtain the final high-resolution 3D temperature and salinity prediction model. Experimental results show that the 20-day prediction results in the two sea areas of the coastal waters of China and the Northwest Pacific show good performance, accurately predicting ocean temperature and salinity in the vast majority of layers, and demonstrate higher resource utilization efficiency. [ABSTRACT FROM AUTHOR]

The presence of biota in the Black Sea is mostly determined by seawater temperature and salinity. The consensus of many scientists doing research on global warming is that in 2100, the average air temperature will be increase than today's values. With climate changing, precipitation rates will change due to the Black Sea water temperature and the changing atmospheric regime, causing an unbalanced entry of nutrients into the sea, and as a result, excessive plankton proliferation may occur. This may mean that the habitats of the species in the Black Sea are further limited. The increases in sea levels may not be serious, but there is no doubt that there will be some increases. These increases will affect the coastal ecosystem, especially the rich living life in the region where the waves hit the shore, which we call the wave zone, will be adversely affected. These predictions should be followed up with regular scientific monitoring studies and it should be investigated how biota from invertebrates to fish are affected by the changes. This review explored and discussed the long-term changes and causes of biota communities on the southern coast of the Black Sea. [ABSTRACT FROM AUTHOR]

Optical detection is an indispensable part of microfluidic systems for nutrient determination in seawater. Coupling total internal reflection capillaries with microfluidic chips is a practical alternative to increase the optical path length for high-sensitivity and a low detection limit in colorimetric assays, which has not been applied in microfluidic devices for seawater nutrients. Here, we present an online microfluidic system which integrated a total internal reflection capillary made of Teflon AF 2400 for the high-sensitivity detection of nitrite and nitrate in seawater. The off-chip capillary lengthens the optical path without changing the internal flow path of the microfluidic chip, enhancing the sensitivity, reducing the detection limit and widening the dynamic range of the system, which significantly improves the performance of the microfluidic system based on wet-chemistry. The detection limit for nitrite is 0.0150 μM using an external 20 cm capillary and 0.0936 μM using an internal 5 cm absorption cell, providing an over 6-fold improvement. Laboratory analysis of surface seawater samples collected from the South China Sea with this system and a one-month online deployment of an autonomous analyzer developed based on this system at a station revealed correlations between the nitrite and nitrate with tide, salinity and chlorophyll over slight variations and narrow ranges, demonstrating the high-sensitivity of this method. [ABSTRACT FROM AUTHOR]

The Above Ground Biomass (AGB) is an essential component of the Earth carbon cycle. Yet, large uncertainties remain on its spatial distribution and temporal evolution. Improving the accuracy of the AGB estimates requires precise and regular monitoring. Satellite remote sensing offers such capabilities. In particular, the L-Band (1.41 GHz) Vegetation Optical Depth (VOD) derived from the SMOS (Soil Moisture and Ocean Salinity mission) multi-angle brightness temperatures is a good AGB proxy. Averaging the SMOS L-VOD over a year and linking it to a pre-existing AGB map is a well-established method to derive a spatial relationship between both quantities. After temporal extrapolation of this relation, global AGB time series are derived from the L-VOD, allowing to retrieve vegetation biomass values up to 300 Mg ha-1 from 2011 onwards. This study focuses on this protocol to produce a harmonized AGB dataset from the L-VOD and analyses the impact of three factors on the AGB/VOD calibration. First, the influence of the orbit type (ascending or descending) on the estimation is quantified. Second, the relevance of using a single global spatial calibration or several regional ones is thoroughly discussed for the first time. Third, the AGB time series from this new dataset are compared against other published AGB time series to assess the validity of extrapolating a spatial relationship over time. These comparisons highlight that the produced dataset has more inter-annual variability than the other available time series and presents globally lower AGB estimates, particularly over the equatorial part of Africa. These two limitations are inherent to the input data and method used. Overall, the resulting AGB is coherent with the AGB map from the CCI Biomass version 4 and can be used in AGB studies. The freely accessible AGB dataset has been produced from the level 2 SMOS products, mixing ascending and descending orbits altogether and using a single global relationship between the AGB and the VOD. The spatial bias associated with the AGB estimates is also provided in the files. The AGB dataset is open access and the NetCDF files are available at: https://doi.org/10.12770/95f76ff0-5d89-430d-80db-95fbdd77f543 (Boitard et al., 2024). [ABSTRACT FROM AUTHOR]

This research aims to investigate the effects of seawater parameters like salinity, pH, and temperature on the external corrosion behaviour and microhardness of offshore oil and gas carbon steel pipes. The immersion tests were performed for 28 days following ASTM G-1 standards, simulating controlled artificial marine environments with varying pH levels, salinities, and temperatures. Besides, Field emission scanning electron microscopy (FESEM) analysis is performed to study the corrosion morphology. Additionally, a Vickers microhardness tester was used for microhardness analysis. The results revealed that an increase in salinity from 33.18 to 61.10 ppt can reduce the corrosion rate by 28%. In contrast, variations in seawater pH have a significant effect on corrosion rate, with a pH decrease from 8.50 to 7 causing a 42.54% increase in corrosion rate. However, the temperature of seawater was found to be the most prominent parameter, resulting in a 76.13% increase in corrosion rate and a 10.99% reduction in the microhardness of offshore pipelines. Moreover, the response surface methodology (RSM) modelling is used to determine the optimal seawater parameters for carbon steel pipes. Furthermore, the desirability factor for these parameters was 0.999, and the experimental validation displays a good agreement with predicted model values, with around 4.65% error for corrosion rate and 1.36% error for microhardness. [ABSTRACT FROM AUTHOR]

An area of ocean centered on 179°E, 46°S has warmed to full depth since 2006, with surface warming around 5 times the global rate. This Subtropical Front area is associated with a confluence of warm, salty, subtropical water from the north carried in a western boundary current and cold, fresh, subantarctic water from the south carried in the northernmost branch of the Antarctic Circumpolar Current. Temperature and salinity changes observed from Argo floats indicate that the Subtropical Frontal Zone has moved west ∼120 km, creating this area of strong warming analogous to changes in extension regions of other western boundary currents. The warming is a result of changes in the local flows of subantarctic water, evident in satellite altimeter data and 1,000 m Argo trajectories, which in turn likely result from changes in meridional ocean heat content and winds. The warming has placed this biologically‐significant region in almost perpetual marine heatwave conditions. Plain Language Summary: An area of ocean east of New Zealand has warmed strongly since 2006 through the full ocean depth. The warming has been driven by a change in Southern Ocean currents, which, in turn appear to result from changes in the ocean heat content gradient between mid and high latitudes and changes in wind. The change is occurring in a biologically highly‐productive area of importance to Orange Roughy and Hoki fisheries. Key Points: There has been strong, full‐depth ocean warming since 2006 in a region south of Chatham Islands, New ZealandSouth of Chatham Islands, the Subtropical Frontal Zone has moved 120 km westThe warming is a result of diminished Subantarctic Water flows along northern Campbell Plateau and around Bounty Trough [ABSTRACT FROM AUTHOR]

Accurate satellite measurements of the thickness of Antarctic sea ice are urgently needed but pose a particular challenge. The Antarctic data presented here were produced using a method to derive the sea ice thickness from 1.4 GHz brightness temperatures previously developed for the Arctic, with only modified auxiliary data. The ability to observe the thickness of thin sea ice using this method is limited to cold conditions, meaning it is only reasonable during the freezing period, typically March to October. The Soil Moisture and Ocean Salinity (SMOS) level-3 sea ice thickness product contains estimates of the sea ice thickness and its uncertainty up to a thickness of about 1 m. The sea ice thickness is provided as a daily average on a polar stereographic projection grid with a sample resolution of 12.5 km , while the SMOS brightness temperature data used have a footprint size of about 35–40 km in diameter. Data from SMOS have been available since 2010, and the mission's operation has been extended to continue until at least the end of 2025. Here we compare two versions of the SMOS Antarctic sea ice thickness product which are based on different level-1 input data (v3.2 based on SMOS L1C v620 and v3.3 based on SMOS L1C 724). A validation is performed to generate a first baseline reference for future improvements of the retrieval algorithm and synergies with other sensors. Sea ice thickness measurements to validate the SMOS product are particularly rare in Antarctica, especially during the winter season and for the valid range of thicknesses. From the available validation measurements, we selected datasets from the Weddell Sea that have varying degrees of representativeness: Helicopter-based EM Bird (HEM), Surface and Under-Ice Trawl (SUIT), and stationary Upward-Looking Sonars (ULS). While the helicopter can measure hundreds of kilometres, SUIT's use is limited to distances of a few kilometres and thus only captures a small fraction of an SMOS footprint. Compared to SMOS, the ULS are point measurements and multi-year time series are necessary to enable a statistically representative comparison. Only four of the ULS moorings have a temporal overlap with SMOS in the year 2010. Based on selected averaged HEM flights and monthly ULS climatologies, we find a small mean difference (bias) of less than 10 cm and a root mean square deviation of about 20 cm with a correlation coefficient R > 0.9 for the valid sea ice thickness range between 0 and about 1 m. The SMOS sea ice thickness showed an underestimate of about 40 cm with respect to the less representative SUIT validation data in the marginal ice zone. Compared with sea ice thickness outside the valid range, we find that SMOS strongly underestimates the real values, which underlines the need for combination with other sensors such as altimeters. In summary, the overall validity of the SMOS sea ice thickness for thin sea ice up to a thickness of about 1 m has been demonstrated through validation with multiple datasets. To ensure the quality of the SMOS product, an independent regional sea ice extent index was used for control. We found that the new version, v3.3, is slightly improved in terms of completeness, indicating fewer missing data. However, it is worth noting that the general characteristics of both datasets are very similar, also with the same limitations. Archived data are available in the PANGAEA repository at https://doi.org/10.1594/PANGAEA.934732 and operationally at https://doi.org/10.57780/sm1-5ebe10b. [ABSTRACT FROM AUTHOR]

The establishment of a global ocean assimilation system is of great significance for the utilization of observational data. In this study, a new global ocean assimilation system was established using the EAKF assimilation module and the MPI-OM global ocean circulation model with a grid refining the South China Sea (SCS) and part of Pacific region. Considering computational cost, static ensemble was utilized as the background ensemble. To assess the role of static ensembles, three different static ensembles were selected to compare assimilation experiments. The assimilation of sea surface temperature (SST) and sea surface salinity (SSS), as well as Argo profiling data, was conducted. Firstly, the model performance of the assimilation system on a global scale was evaluated using the profile data, which can reduce the temperature and salinity biases by approximately 50%, resulting in a decrease of the globally-averaged temperature and salinity biases to 0.4 ℃ and 0.1 PSU, respectively. Considering about the specific of the grid, we focus on the SCS and the equatorial region. Comparison of buoy data with the model results indicates that assimilation significantly improves the simulation of the tropical thermocline, with correlation coefficients suggesting that the assimilation with seasonal static ensemble yields the best results. Secondly, the impact of different ensembles on the SCS where significant monsoon influence exists was investigated, revealing distinct differences in current field among the three assimilation experiments. For the experiments with background ensembles include information on seasonal variations, the assimilation improves the model's ability in reproducing the intrusion of the Kuroshio Current into the SCS. [ABSTRACT FROM AUTHOR]

In this paper, we use a new workflow to substantiate the characterization of a prominent, deep sediment conductor in the hyperextended Bjørnøya Basin (SW Barents Sea) previously identified in smooth resistivity models from 3-D deterministic inversion of magnetotelluric data. In low-dimensionality environments like layered sedimentary basin, 1-D Bayesian inversion can be advantageous for a thorough exploration of the solution space, but the violation of the 1-D assumption has to be efficiently handled. The primary geological objectives of this work is therefore preceded by a secondary task: the application of a new machine learning approach for handling the 1-D violation assumption for 21 MT field stations in the Barents Sea. We find that a decision tree can adequately learn the relationship between MT dimensionality parameters and the 1-D–3-D residual response for a training set of synthetic models, mimicking typical resistivity structures of the SW Barents Sea. The machine learning model is then used to predict the dimensionality compensation error for MT signal periods ranging of 1–3000 s for 21 receivers located over the Bjørnøya Basin and Veslemøy High. After running 1-D Bayesian inversion, we generated a posterior resistivity distribution for an ensemble of 6000 1-D models fitting the compensated MT data for each 21 field stations. The proportion of 1-D models showing ρ < 1 Ω·m is consistently beyond 80 per cent and systemically reaches a maximum of 100 per cent in the Early Aptian–Albian interval in the Bjørnøya Basin. In hyperextended basins of the SW Barents Sea, the dimensionality compensation workflow has permitted to refine the characterization of the deep basin conductor by leveraging the increased vertical resolution and optimal used of MT data. In comparison, the smooth 3-D deterministic models only poorly constrained depth and lateral extent of the basin anomaly. The highest probability of finding ρ < 1 Ω·m is robustly assigned to the syn-tectonic Early Aptian–Albian marine shales, now buried at 6–8 km depth. Based on a theoretical two phase fluid-rock model, we show that the pore fluid of these marine shales must have a higher salinity than seawater to explain the anomaly ρ < 1 Ω·m. Therefore, the primary pore fluid underwent mixing with a secondary brine during rifting. Using analogue rift systems in palaeomargins, we argue that two possible secondary brine reservoir may contribute to deep saline fluid circulation in the hyperextended basin: (1) Permian salt-derived fluid and, (2) mantle-reacted fluid from serpentinization. [ABSTRACT FROM AUTHOR]

To effectively remove n-propylbenzene (n-PBZ) and isopropylbenzene (i-PBZ) leaked into seawater using Rhinomonas reticulata S6A (a newly isolated marine microalga), the effects of three inorganic nutrients and four environmental factors on their degradation were determined after 7 d of inoculation. Results show that NaNO3 at 300 mg/L caused a higher removal efficiency of both n-PBZ and i-PBZ (44.79% and 39.26%), while for NaH2PO4H2O, greater removal rates of two PBZs (47.30% and 42.23%) were achieved at 30 and 20 mg/L, respectively. NaHCO3 supplementation (500–750 mg/L) resulted in a large reduction (43.67%–45.04%) in i-PBZ concentration. The change in seawater pH (from 6 to 9) did not affect the elimination of n-PBZ and i-PBZ. The most suitable salinity and temperature were 30 and 25–30 °C, respectively, leading to the PBZs removal of ~40%. Light intensity exhibited significant influence on elimination of PBZs, and the maximum removal efficiencies of 56.07% (n-PBZ) and 55.00% (i-PBZ) were recorded under 200 and 600 µmol/(m2·s), respectively. In addition, the microalga could still remove PBZs when it failed to grow well due to darkness, strong light, low temperature, or low salinity, which might mean that good growth of alga is not always a necessary condition for PBZs removal. Therefore, attention should be paid to the suitability of nutrient levels and environmental conditions (excluding pH) in seawater when using microalgae for bioremediating PBZs-contaminated seawater. [ABSTRACT FROM AUTHOR]

The chloride channel 7 gene (CLC7) of the Hong Kong oyster Crassostrea hongkongensis was cloned and named ChCLC7. The cDNA was 2 572 bp in length, with a 5′ non-coding region containing 25 bp, a 3′ non-coding region containing 327 bp, and an open reading frame of 2 298 bp. ChCLC7 has 96.8% and 92.1% homology with CLC7 of Crassostrea gigas and Crassostrea virginica, respectively, and it was clustered with CLC7 of C. gigas and C. virginica. QRT-PCR showed that ChCLC7 was expressed in all eight tissues, with the highest in adductor muscle and second in gill. The ChCLC7 expression pattern in gill was altered significantly under high salinity stress with an overall upward and then downward trend. After RNA interference, the expression of ChCLC7 and survival rate of oyster under high salinity stress was reduced significantly, and so did the concentration of hemolymph chloride ion in 48–96 h after RNA interference. We believed that ChCLC7 could play an important role in osmoregulation of C. hongkongensis by regulating Cl− transport. This study provided data for the analysis of molecular mechanism against oyster salinity stress. [ABSTRACT FROM AUTHOR]

A 110-year ensemble simulation of an ocean general circulation model (OGCM) was analyzed to identify the modulation of salinity interdecadal variability on El Niño-Southern Oscillation (ENSO) amplitude in the tropical Pacific during 1901–2010. The simulating results show that sea surface salinity (SSS) variation in the region exhibits notable and coherent interdecadal variability signal, which is closely associated with the Interdecadal Pacific Oscillation (IPO). As salinity increases or reduces, the SSS modulations on ENSO amplitude during its warm/cold events vary asymmetrically with positive/negative IPO phases. Physically, salinity interdecadal variability can enhance or reduce ENSO-related conditions in upper-ocean stratification, contributing noticeably to ENSO variability. Salinity anomalies associated with the mixed layer depth and barrier layer thickness can modulate ENSO amplitude during positive and negative IPO phases, resulting in the asymmetry of sea surface temperature (SST) anomaly in the tropical Pacific. During positive IPO phases, SSS interdecadal variability contributes positively to El Niño amplitude but negatively to La Niña amplitude by enhancing or reducing SSS interannual variability, and vice versa during negative IPO phases. Quantitatively, the results indicate that the modulation of the ENSO amplitude by the SSS interdecadal variability is −15%–28% during negative IPO phases and −30%–20% during positive IPO phases, respectively. Evidently, the SSS interdecadal variability associated with IPO and its modulation on ENSO amplitude in the tropical Pacific are among factors essentially contributing ENSO diversity. [ABSTRACT FROM AUTHOR]

Salinity is a crucial property of water body and is essential for the restoration of paleoecology and paleoenvironment. However, the theoretical method of application of elemental geochemical proxies to paleosalinity reconstruction is still underdeveloped. Moreover, accurate determination and reconstruction of paleosalinity and its variation in an offshore lacustrine basin have been extremely challenging thus far. This study presents detailed elemental geochemical investigations from the Zhanhua Sag in the southern Bohai Bay Basin to reconstruct the salinity variation in the Paleogene Eocene Shahejie Formation (50.8–33.9 Ma). Based on the variation of strontium barium ratio (Sr/Ba) and boron gallium ratio (B/Ga), we determined three typical salinity types of water body: salty water (Sr/Ba>0.5, B/Ga>6), brackish water (0.2

In this study, we employ a Random Forest approach to estimate sea ice thickness (SIT) using Fengyun-3E (FY-3E) and Soil Moisture Ocean Salinity (SMOS) data. This method relies on four input parameters: incidence angle (θ), reflectivity (Γ), sea ice salinity (S), and sea ice temperature (T). In addition, FY-3E can receive both Global Positioning System (GPS) and Beidou Navigation Satellite System (BDS) reflected signals. Evaluation for the Arctic region based on data spanning from October 2022 to April 2023 reveals that the proposed models trained on GPS and BDS signals from FY-3E achieve high consistency and low error. Take GPS signals as an example, coefficients of determination are 0.97 and 0.91 and mean absolute errors are 0.019 m and 0.032 m for the training and test sets, respectively. In general, SIT inversion based on GPS signals slightly exhibits a higher accuracy than that based on BDS signals, but both approaches display high performances. The areas with the highest accuracy of SIT estimation based on GPS and BDS signals are the Shelikhov Bay and the Okhotsk Sea, followed by the Bering Sea and the Bering Strait. We conclude that machine learning and data fusion are effective for SIT estimation. [ABSTRACT FROM AUTHOR]