Subsurface Salinity Research Articles

Reconstructing ocean subsurface salinity at high resolution using a machine learning approach

Abstract. A gridded ocean subsurface salinity dataset with global coverage is useful for research on climate change and its variability. Here, we explore the feed-forward neural network (FFNN) approach to reconstruct a high-resolution (0.25∘ × 0.25∘) ocean subsurface (1–2000 m) salinity dataset for the period 1993–2018 by merging in situ salinity profile observations with high-resolution (0.25∘ × 0.25∘) satellite remote-sensing altimetry absolute dynamic topography (ADT), sea surface temperature (SST), sea surface wind (SSW) field data, and a coarse-resolution (1∘ × 1∘) gridded salinity product. We show that the FFNN can effectively transfer small-scale spatial variations in ADT, SST, and SSW fields into the 0.25∘ × 0.25∘ salinity field. The root-mean-square error (RMSE) can be reduced by ∼11 % on a global-average basis compared with the 1∘ × 1∘ salinity gridded field. The reduction in RMSE is much larger in the upper ocean than the deep ocean because of stronger mesoscale variations in the upper layers. In addition, the new 0.25∘ × 0.25∘ reconstruction shows more realistic spatial signals in the regions with strong mesoscale variations, e.g., the Gulf Stream, Kuroshio, and Antarctic Circumpolar Current regions, than the 1∘ × 1∘ resolution product, indicating the efficiency of the machine learning approach in bringing satellite observations together with in situ observations. The large-scale salinity patterns from 0.25∘ × 0.25∘ data are consistent with the 1∘ × 1∘ gridded salinity field, suggesting the persistence of the large-scale signals in the high-resolution reconstruction. The successful application of machine learning in this study provides an alternative approach for ocean and climate data reconstruction that can complement the existing data assimilation and objective analysis methods. The reconstructed IAP0.25∘ dataset is freely available at https://doi.org/10.57760/sciencedb.o00122.00001 (Tian et al., 2022).

Comparison of Machine Learning Approaches for Reconstructing Sea Subsurface Salinity Using Synthetic Data

There is a growing interest in using sparse in situ salinity data to reconstruct high-resolution three-dimensional subsurface salinity with global coverage. However, in areas with no observations, there is a lack of observation data for comparison with reconstructed fields, leading to challenges in assessing the quality and improving the accuracy of the reconstructed data. To address these issues, this study adopted the ‘resampling test’ method to establish the ‘synthetic data’ to test the performance of different machine learning algorithms. The Centre National de Recherches Meteorologiques Climate Model Version 6, and its high-resolution counterpart (CNRM-CM6-1-HR) model data was used. The key advantage of the CNRM-CM6-1-HR is that the true values for salinity are known across the entire ocean at every point in time, and thus we can compare the reconstruction result to this data. The ‘synthetic dataset’ was established by resampling the model data according to the location of in situ observations. This synthetic dataset was then used to prepare two datasets: an ‘original synthetic dataset’ with no noise added to the resampled truth value and a ‘noised synthetic dataset’ with observation error perturbation added to the resampled truth value. The resampled salinity values of the model were taken as the ‘truth values’, and the feed-forward neural network (FFNN) and light gradient boosting machine (LightGBM) approaches were used to design four reconstruction experiments and build multiple sets of reconstruction data. Finally, the advantages and disadvantages of the different reconstruction schemes were compared through multi-dimensional evaluation of the reconstructed data, and the applicability of the FFNN and LightGBM approaches for reconstructing global salinity data from sparse data was discussed. The results showed that the best-performing scheme has low root-mean-square errors (~0.035 psu) and high correlation coefficients (~0.866). The reconstructed dataset from this experiment accurately reflected the geographical pattern and vertical structure of salinity fields, and also performed well on the noised synthetic dataset. This reconstruction scheme has good generalizability and robustness, which indicates its potential as a solution for reconstructing high-resolution subsurface salinity data with global coverage in practical applications.

High spatial heterogeneity and low connectivity of bacterial communities along a Mediterranean subterranean estuary.

Subterranean estuaries are biogeochemically active coastal sites resulting from the underground mixing of fresh aquifer groundwater and seawater. In these systems, microbial activity can largely transform the chemical elements that may reach the sea through submarine groundwater discharge (SGD), but little is known about the microorganisms thriving in these land-sea transition zones. We present the first spatially-resolved characterization of the bacterial assemblages along a coastal aquifer in the NW Mediterranean, considering the entire subsurface salinity gradient. Combining bulk heterotrophic activity measurements, flow cytometry, microscopy and 16S rRNA gene sequencing we find large variations in prokaryotic abundances, cell size, activity and diversity at both the horizontal and vertical scales that reflect the pronounced physicochemical gradients. The parts of the transect most influenced by freshwater were characterized by smaller cells and lower prokaryotic abundances and heterotrophic production, but some activity hotspots were found at deep low-oxygen saline groundwater sites enriched in nitrite and ammonium. Diverse, heterogeneous and highly endemic communities dominated by Proteobacteria, Patescibacteria, Desulfobacterota and Bacteroidota were observed throughout the aquifer, pointing to clearly differentiated prokaryotic niches across these transition zones and little microbial connectivity between groundwater and Mediterranean seawater habitats. Finally, experimental manipulations unveiled large increases in community heterotrophic activity driven by fast growth of some rare and site-specific groundwater Proteobacteria. Our results indicate that prokaryotic communities within subterranean estuaries are highly heterogeneous in terms of biomass, activity and diversity, suggesting that their role in transforming nutrients will also vary spatially within these terrestrial-marine transition zones.

Subsurface salinity distribution and evolution in low-permeability coastal areas after land reclamation: Field investigation

Coastal land reclamation can modify the original hydrological settings that control water salinity distribution. For low-permeability coastal lands reclaimed for agricultural use, there is an urgent need to understand the salinity distribution and evolution mechanism for a sustainable exploitation. In this study, electrical resistivity tomography (ERT) measurements at different temporal and spatial scales are combined with water stable isotope and hydrochemical analyses to investigate the distribution and evolution rules of underground salinity in a coastal reclamation zone of eastern China. The results show that the phreatic aquifer is dominated by highly saline water due to the flooding of seawater before reclamation. After being isolated from marine conditions, water salinity in the near-surface zone becomes highly variable caused by dilution effect of rainwater and salt accumulation effect driven by evaporation. Due to the low-permeability muddy flat geohydrological settings and intense evaporation, natural groundwater desalination is extremely slow and only temporarily occurs in the near-surface zone. After long-term reclamation for agricultural use, the leaching effect of freshwater input from not only precipitation but also crop farming dominates and accelerates the desalination of the upper phreatic aquifer, leading to a desalting rate of 1.6 ± 2.4 %/yr and an obvious downward migration of saline groundwater. Deeper confined aquifers are dominated by brackish or even fresh groundwater, which is minimally contaminated by upper saline water. Findings of this study provide a representative example of the salinity distribution and evolution characteristics in coastal agricultural lands reclaimed from low-permeability intertidal muddy flats.

How does salinity shape ocean circulation and ice geometry on Enceladus and other icy satellites?

Of profound astrobiological interest, Enceladus appears to have a global saline subsurface ocean, indicating water-rock reaction at present or in the past, an important mechanism in the moon’s potential habitability. Here, we investigate how salinity and the partition of heat production between the silicate core and the ice shell affect ocean dynamics and the associated heat transport—a key factor determining equilibrium ice shell geometry. Assuming steady-state conditions, we show that the meridional overturning circulation of the ocean, driven by heat and salt exchange with the poleward-thinning ice shell, has opposing signs at very low and very high salinities. Regardless of these differing circulations, heat and fresh water converge toward the equator, where the ice is thick, acting to homogenize thickness variations. Among scenarios explored here, the pronounced ice thickness variations observed on Enceladus are most consistent with heating that is predominantly in the ice shell and a salinity of intermediate range.

Sea-level rise predicted to reduce exotic mangrove distribution and biomass in coastal wetlands in southern China

The adverse effects of sea-level rise on coastal wetlands have been extensively reported, whereas the positive effects on wetland composition have tended to receive less attention. Using a coupled hydro-vegetation model, we modeled the spatial and temporal distribution of native and exotic mangroves for 120 years in a mangrove forest in southern China in scenarios with and without sea-level rise. After approximately 50 years, the self-reinforcing feedback between mangroves and subsurface salinity is expected to create a stable ecosystem. Without sea-level rise, salt-sensitive exotic species will inhibit the growth of native mangroves, potentially leading to a more fragile ecosystem. Native mangroves are predicted to grow best under moderate sea-level rise (0.5 m). If sea level rises by 1 m, exotic mangrove populations in southern China are predicted to drastically decline. Competition between salt-tolerant and salt-intolerant plants is common in coastal wetlands, and the modeling method presented in this study may be globally applicable.

Reconstruction of Subsurface Salinity Structure in the South China Sea Using Satellite Observations: A LightGBM-Based Deep Forest Method

Accurately estimating the ocean’s interior structures using sea surface data is of vital importance for understanding the complexities of dynamic ocean processes. In this study, we proposed an advanced machine-learning method, the Light Gradient Boosting Machine (LightGBM)-based Deep Forest (LGB-DF) method, to estimate the ocean subsurface salinity structure (OSSS) in the South China Sea (SCS) by using sea surface data from multiple satellite observations. We selected sea surface salinity (SSS), sea surface temperature (SST), sea surface height (SSH), sea surface wind (SSW, decomposed into eastward wind speed (USSW) and northward wind speed (VSSW) components), and the geographical information (including longitude and latitude) as input data to estimate OSSS in the SCS. Argo data were used to train and validate the LGB-DF model. The model performance was evaluated using root mean square error (RMSE), normalized root mean square error (NRMSE), and determination coefficient (R2). The results showed that the LGB-DF model had a good performance and outperformed the traditional LightGBM model in the estimation of OSSS. The proposed LGB-DF model using sea surface data by SSS/SST/SSH and SSS/SST/SSH/SSW performed less satisfactorily than when considering the contribution of the wind speed and geographical information, indicating that these are important parameters for accurately estimating OSSS. The performance of the LGB-DF model was found to vary with season and water depth. Better estimation accuracy was obtained in winter and autumn, which was due to weaker stratification. This method provided important technical support for estimating the OSSS from satellite-derived sea surface data, which offers a novel insight into oceanic observations.

Enhancing solute transport by pressure-wave driven flow in unsaturated porous media

Solutes and their limited mobilization in heterogeneous porous media may lead to subsurface salinization and contamination evident in various environmental settings. Previous studies showed that flow and transport driven by pressure waves in porous media under saturated conditions significantly enhance solute displacement compared to drag-dominant (Darcy) flow and transport, resulting in more thorough remediation. However, experimental evidence lacks demonstration of such transport under unsaturated conditions. We investigate solute leaching in a flow cell, experimentally modeling solute displacement from an unsaturated, saline, fine-textured soil region to the surrounding coarse-textured soil. The extent of mobilization efficiency is evaluated by comparing solute breakthrough measurements between two leaching treatments, with drag-dominant continuous flux (CF) and pressure-wave pulse flux (PPF). The results indicate that the PPF treatment provided an additional 75% solute mass that leached from the fine-textured region per unit volume of water compared to the CF. The effect is partly due to the impact of the pressure waves on water imbibition into the medium. The PPF induced relatively high pressure gradients at the wetting front compared to percolation during the CF, thus wetting the media in a more spatially uniform pattern. Consequently, the PPF treatment led to higher water content at and behind the front, which increased the continuity of the water phase across the fine-textured and coarse-textured soils and enhanced transport. The study is a proof of concept for pressure-wave driven flow to enhance local wetting and solute transport in unsaturated soil.

Simulated CO2 storage efficiency factors for saline formations of various lithologies and depositional environments using new experimental relative permeability data

Saline formations are attractive geologic reservoirs for permanent carbon dioxide (CO2) storage. The U.S. Department of Energy's National Energy Technology Laboratory (DOE-NETL) has worked to develop and refine methods and tools for the calculation of CO2 storage potential in subsurface reservoirs. DOE-NETL's CO2-SCREEN provides an online tool for executing these storage methods. CO2 storage efficiency terms are input parameters in DOE-NETL's methods and equations embedded in the CO2-SCREEN, which assesses pore space available for CO2 storage. In this work, a modeling workflow was initiated to refine two CO2 storage efficiency terms - volumetric displacement (EV) and microscopic displacement (Ed). The models are based on new experimental relative permeability data that are specific to homogenous lithology and depositional environments of key subsurface saline formations targeted for CO2 storage. In future work, heterogenous features will be added to this initial modeling effort to update efficiency factors as described in DOE-NETL's methods and CO2-SCREEN tool. EVaccounts for the volume utilized in the reservoir under the areal plume, while Ed accounts for saturation values in the plume to assess efficiency of CO2 storage at the pore scale. The results of this work are significant in that prior values were based on a limited geologically non-specific relative permeability data set that were collected prior to 2009. Specifically, we applied numerical simulations using TOUGH3 models to update CO2 storage efficiency values for supercritical CO2 injection into brine-saturated reservoirs for three lithologies (clastics, limestone, dolomite) and six depositional environments (Marginal Marine, Strand Plain, Deltaic Complex Fluvial, Aeolian, Shallow Marine, and Reef) that have a high potential for geologic CO2 storage. Experimental relative permeability data in cores from these environments were utilized in the models with corresponding rock type/sedimentary environment. Results of this study showed that dolomite followed by limestone generated higher ranges of storage efficiency compared to clastics. The updated values provided a tighter efficiency range for clastics, lower P10 but higher P90 range for limestone, and higher P10 and P90 for dolomite. In general, tighter reservoirs with relatively low permeability and porosity were associated with higher EV and Ed, showing efficient reservoir and pore utilization in these scenarios. High reservoir pressure and temperature associated with increasing depth increased the EV, and high CO2 injection rates resulted in increases in EV and Ed, while the impact of permeability anisotropy was minimal after the 30-year injection period.

Subtropical Contribution to Sub‐Antarctic Mode Waters

AbstractSub‐Antarctic Mode Waters (SAMW) form to the north of the Antarctic Circumpolar Current (ACC) through deep winter mixing. SAMW connect the atmosphere with the oceanic pycnocline, transferring heat and carbon into the ocean interior and supplying nutrients to the northern ocean basins. The processes controlling SAMW ventilation and properties remain poorly understood. Here, we investigate the significance and origin of a ubiquitous feature of SAMW formation regions: The seasonal build‐up of a subsurface salinity maximum. With biogeochemical Argo floats, we show that this feature influences SAMW mixed‐layer dynamics, and that its formation is associated with a decline in preformed nutrients comparable to biological drawdown in surface waters (∼0.15 mol m−2 y−1). Our analysis reveals that these features are driven by advection of warm, salty, nutrient‐poor waters of subtropical origin along the ACC. This influx represents a leading‐order term in the SAMW physical and biogeochemical budgets, and can impact large‐scale nutrient distributions.

Inversion of Ocean Subsurface Temperature and Salinity Fields Based on Spatio-Temporal Correlation

Ocean observation is essential for studying ocean dynamics, climate change, and carbon cycles. Due to the difficulty and high cost of in situ observations, existing ocean observations are inadequate, and satellite observations are mostly surface observations. Previous work has not adequately considered the spatio-temporal correlation within the ocean itself. This paper proposes a new method—convolutional long short-term memory network (ConvLSTM)—for the inversion of the ocean subsurface temperature and salinity fields with the sea surface satellite observations (sea surface temperature, sea surface salinity, sea surface height, and sea surface wind) and subsurface Argo reanalyze data. Given the time dependence and spatial correlation of the ocean dynamic parameters, the ConvLSTM model can improve inversion models’ robustness and generalizability by considering ocean variability’s significant spatial and temporal correlation characteristics. Taking the 2018 results as an example, our average inversion results in an overall normalized root mean square error (NRMSE) of 0.0568 °C/0.0027 PSS and a correlation coefficient (R) of 0.9819/0.9997 for subsurface temperature (ST)/subsurface salinity (SS). The results show that SSTA, SSSA SSHA, and SSWA together are valuable parameters for obtaining accurate ST/SS estimates, and the use of multiple channels in shallow seas is effective. This study demonstrates that ConvLSTM is superior in modeling the subsurface temperature and salinity fields, fully taking global ocean data’s spatial and temporal correlation into account, and outperforms the classic random forest and LSTM approaches in predicting subsurface temperature and salinity fields.

Impact of Coastal Marsh Eco‐Geomorphologic Change on Saltwater Intrusion Under Future Sea Level Rise

AbstractCoastal saltwater intrusion (SWI) is one key factor that affects the hydrology, ecology, and biogeochemistry of coastal ecosystems. Future climate change, especially intensified sea level rise (SLR), is expected to trigger SWI to encroach on coastal freshwater aquifers more intensively. Numerous studies have investigated decadal/century scale SWI under SLR by assuming a static coastal landscape topography. However, coastal landscapes are highly dynamic in response to SLR, and the impact of coastal landscape evolution on SWI has received very little attention. Thus, this study used a coastal marsh landscape as an example and investigated how coastal marsh evolution affects future SWI with a physically‐based coastal hydro‐eco‐geomorphologic model, Advanced Terrestrial Simulator. Our numerical experiments showed that it is very likely that the marsh elevation increases with future SLR due to sediment deposition, and a depression zone is formed due to different marsh accretion rates between the ocean boundary and the inland. We found that marsh accretion may significantly reduce the surface saltwater inflow at the ocean boundary, and the evolved topographic depression zone may prolong the residence time of surface ponded saltwater, affecting subsurface salinity distribution differently. We also predicted that marshlands may become more sensitive to upland freshwater supply under future SLR, compared with previous predictions without marsh evolution. This study demonstrates the importance of coastal evolution to coastal freshwater‐saltwater interaction. The eco‐geomorphologic effect may not be ignored when evaluating coastal SWI under SLR at decadal or century scales.

Spatial patterns of soil salinity in the central Argentinean Dry Chaco

The Dry Chaco is a semi-arid ecoregion in South America that hosts one of the largest dry forests in the world, but expansion of dryland agriculture and cattle ranching led to gradual conversion of native vegetation to anthropogenic land cover. The potential impact of these newly established agricultural lands on the surrounding environment is of great concern. Local studies have shown that deforestation leads to changes in the soil-water balance, and can expedite groundwater rise and mobilization of water-soluble salts to the surface affecting plant growth and crop productivity. This study is a regional assessment of soil salinity and salinization processes in the central Argentinean Dry Chaco. It is based on extensive dataset of 492 surface and 142 subsurface samples taken along east-west transects across the Dry Chaco. Soil electrical conductivity (EC) was used as an indicator of salinity, and supplementary information on salt crusts was derived from Google Earth imagery. Subsurface salinity (i.e., measured at 100 cm depth) showed clear regional patterns in natural soil salinity that are related to the annual water budget and topography. Besides primary salinization due to arrested drainage and landscape stagnation, anthropogenic activities increased secondary salinization, especially in the agricultural areas with shallow groundwater tables and irrigated croplands. In addition, the study demonstrated that remotely-sensed vegetation indices such as the seasonal variation in the density of green vegetation are particularly suitable to monitor regional variation in soil salinity. Our results show that the extent of future dryland salinization in the Dry Chaco will mainly depend on whether areas prone to natural soil salinity are further protected from deforestation, and the magnitude and rate of groundwater rise after deforestation as conditioned by local climate and geomorphology. This better understanding of soil salinity patterns and how they are affected as a result of anthropogenic activities is important for the implementation of appropriate and effective measures to prevent severe salinization.

Indian Ocean Subtropical Underwater and the Interannual Variability in Its Annual Subduction Rate Associated with the Southern Annular Mode

Abstract In this study, the Indian Ocean Subtropical Underwater (IOSTUW) was investigated as a subsurface salinity maximum using Argo floats (2000–20) for the first time. It has mean salinity, potential temperature, and potential density values of 35.54 ± 0.29 psu, 17.91° ± 1.66°C, and 25.56 ± 0.35 kg m−3, respectively, and mainly extends between 10° and 30°S along the isopycnal surface in the subtropical south Indian Ocean. The annual subduction rate of the IOSTUW during the period of 2004–19 was investigated based on a gridded Argo dataset. The results revealed a mean value of 4.39 Sv (1 Sv ≡ 106 m3 s−1) with an interannual variability that is closely related to the southern annular mode (SAM). The variation in the annual subduction rate of the IOSTUW is dominated by the lateral induction term, which largely depends on the winter mixed layer depth (MLD) in the sea surface salinity (SSS) maximum region. The anomalies of winter MLD are primarily determined by SAM-related air–sea heat flux and zonal wind anomalies through modulation of the buoyancy. As a result, the annual subduction rate of the IOSTUW generally increased when the SAM index showed negative anomalies and decreased when the SAM index showed positive anomalies. Exceptional cases occurred when the wind anomaly within the SSS maximum region was weak or was dominated by its meridional component. Significance Statement The Indian Ocean Subtropical Underwater (IOSTUW) is characterized as a subsurface salinity maximum in the subtropical south Indian Ocean, and it has potential contribution to regional sea level change and interoceanic salinity exchange. The purpose of this work is to give a more precise description of the IOSTUW and to better understand the formation process of this water mass. Our results shine new light on hydrological characteristics of the IOSTUW based on an observational dataset collected during the past two decades. In addition, the formation of the IOSTUW was found to be closely related to the leading mode of variability in the atmospheric circulation of the Southern Hemisphere though air–sea heat flux and surface wind anomaly.

Interpretation of Subsurface Salinity EOFs on Southern ECS Shelf Using SODA Reanalysis: Large‐Scale Patterns and Seasonal to Interannual Variations

AbstractIn the southern East China Sea (ECS), low‐salinity shelf water is distinguished from high‐salinity Kuroshio water. Neutral density solution of subsurface salinity in southern ECS with Empirical Orthogonal Function (EOF) analysis of Simple Ocean Data Assimilation (SODA) reanalysis data (1958‐2008) is presented. This study focuses on seasonal to interannual variations of large‐scale patterns. We choose isopycnal 24.5 as the representative of subsurface layers, which is the deepest of the Kuroshio subsurface that can outcrop to sea surface during winter and early spring. We conducted EOF both including and excluding the seasonal signal. The results show that annual cycles dominate the first two leading EOF modes, EOF‐1 representing inner‐shelf oscillation, and EOF‐2 outer‐shelf oscillation. However, EOF‐2 also shows significant interannual variability. To this end, we removed the seasonal signal from the dataset and recalculated EOF. We found that the interannual EOF‐1 is of cross‐shelf in spatial pattern and shows significant interannual variability. This suggests that seaward penetration of the shelf water and shelfward intrusion of the Kuroshio that mainly occur in winter and early spring are a pair of contradictions in the two‐way intrusions, which are modulated by significant interannual variability. We also found that the isopycnal extending abnormally northward and outcropping in early spring corresponds to significant non‐intrusions of the Kuroshio. In the underlying dynamics, oceanic stratification, besides topography uplifting, plays an important role in the subsurface intrusion of Kuroshio off northeast Taiwan.

Sedimentation in the adjacencies of a southwestern Atlantic giant carbonate ridge

The continental margin off the southeastern Brazilian coast is punctuated by a series of geological-geomorphological features, such as subsurface saline diapirs and pockmarks at the seafloor interface, which evidence the abundant presence of oil and gas in the region. In several of these sites, hydrocarbons can be naturally released into the water column, areas are cold seep areas. These are marked by the presence of oil- and gas-dependent ecosystems, where specific organisms are able to fix carbon from hydrocarbon chemosynthesis. In addition, light hydrocarbon fluid flow through the sediment may build up authigenic carbonates that can be further colonized by cold-water corals, generating large carbonate mounds over geological time, normally positioned at the border of these pockmark features. The present work reports on a multidisciplinary oceanographic cruise carried out in the Santos Basin, SW Atlantic, to seek, map, and collect geological, chemical, and biological data from different deep-sea habitats. The cruise occurred in November 2019 on the R/V Alpha Crucis of the Oceanographic Institute of the University of São Paulo (IOUSP). We intended to discover and detail different geomorphological features, characterize free-living and symbiotic microorganisms, determine the chemosynthetic rates in relation to heterotrophic microbial production, and characterize the fauna and study their ecological and evolutionary links within and across ocean basins. All discoveries made during the cruise and their respective results will be presented separately in several papers that comprise this special volume.

Impacts of the Scale of Representation of Heterogeneity on Simulated Salinity and Saltwater Circulation in Coastal Aquifers

AbstractNumerical models of variable‐density groundwater flow and salt transport are a primary tool for predicting salinity distributions in coastal aquifers and estimating submarine groundwater discharge (SGD). Models are particularly useful to estimate the saline component of SGD, which can occur far offshore and is difficult to measure directly. Depending on the system and application, the level of geologic detail represented can range from homogeneous or layered to fully heterogeneous hydraulic conductivity fields. These features strongly affect model results, limiting understanding of subsurface salinity distributions and associated density‐driven saltwater circulation along coasts worldwide. In this study, the impact of the scale of representation of heterogeneity on salinity distributions and SGD was investigated using numerical simulations. Upscaling hydraulic conductivity can significantly modify salinity distributions and flow paths, resulting in unpredictable variations in simulated SGD, though the values for homogeneous fields with equivalent hydraulic conductivity show consistent trends. Simulated density distributions control both the rate and direction of subsurface saltwater circulation. The length of the mixing zone perimeter, a measure of salinity distribution complexity, is shown to correlate with both the rate of subsurface saltwater circulation and the amount of groundwater circulating in the reverse direction from homogeneous cases. Overall, the results demonstrate a strong dependence of salinity distributions and saltwater circulation on the scale and distribution of geologic heterogeneity represented in numerical models. This suggests that numerical models with simplified geologic structure may substantially underestimate saltwater circulation, and attempts to calibrate them using salinity distributions or SGD measurements may be problematic.

Intercomparison of Salinity Products in the Beaufort Gyre and Arctic Ocean

Salinity is the primary determinant of the Arctic Ocean’s density structure. Freshwater accumulation and distribution in the Arctic Ocean have varied significantly in recent decades and certainly in the Beaufort Gyre (BG). In this study, we analyze salinity variations in the BG region between 2012 and 2017. We use in situ salinity observations from the Seasonal Ice Zone Reconnaissance Surveys (SIZRS), CTD casts from the Beaufort Gyre Exploration Project (BGP), and the EN4 data to validate and compare with satellite observations from Soil Moisture Active Passive (SMAP), Soil Moisture and Ocean Salinity (SMOS), and Aquarius Optimally Interpolated Sea Surface Salinity (OISSS), and Arctic Ocean models: ECCO, MIZMAS, HYCOM, ORAS5, and GLORYS12. Overall, satellite observations are restricted to ice-free regions in the BG area, and models tend to overestimate sea surface salinity (SSS). Freshwater Content (FWC), an important component of the BG, is computed for EN4 and most models. ORAS5 provides the strongest positive SSS correlation coefficient (0.612) and lowest bias to in situ observations compared to the other products. ORAS5 subsurface salinity and FWC compare well with the EN4 data. Discrepancies between models and SIZRS data are highest in GLORYS12 and ECCO. These comparisons identify dissimilarities between salinity products and extend challenges to observations applicable to other areas of the Arctic Ocean.

Southeastern Tropical Atlantic Changing From Subtropical to Tropical Conditions

A warming and freshening trend of the mixed layer in the upper southeastern tropical Atlantic Ocean (SETA) is observed by the Argo float array during the time period of 2006–2020. The associated ocean surface density reduction impacts upper-ocean stratification that intensified by more than 30% in the SETA region since 2006. The initial typical subtropical stratification with a surface salinity maximum is shifting to more tropical conditions characterized by warmer and fresher surface waters and a subsurface salinity maximum. During the same period isopycnal surfaces in the upper 200 m are shoaling continuously. Observed wind stress changes reveal that open ocean wind curl-driven upwelling increased, however, partly counteracted by reduced coastal upwelling due to weakened alongshore southerly winds. Weakening southerly winds might be a reason why tropical surface waters spread more southward reaching further into the SETA region. The mixed layer warming and freshening and associated stratification changes might impact the marine ecosystem and pelagic fisheries in the Angolan and northern Namibian upwelling region.

Precession cycles of the El Ni\xf1o/Southern oscillation-like system controlled by Pacific upper-ocean stratification

Modern observations have presented linkages between subsurface waters of the western Pacific warm pool and both El Niño/Southern Oscillation-related and extratropic-controlled upper-ocean stratification on interannual timescales. Moreover, studies have showed that such controls may operate on orbital cycles, although the details remain unclear. Here we present paired temperature and salinity reconstructions for the surface and thermocline waters in the central western Pacific warm pool over the past 360,000 years, as well as transit modeling results from an Earth system model. Our results show that variations in subsurface temperature and salinity in the western Pacific warm pool have consistently correlated with the shallow meridional overturning cell over the past four glacial-interglacial cycles, and they vary on eccentricity and precession cycles. The shallow meridional overturning cell regulates subsurface waters of the western Pacific warm pool by changing subtropical surface water density and thus equatorial upper-ocean stratification, acting as an El Niño/Southern Oscillation-like process in the precession band. Therefore, the western Pacific warm pool is critical in connecting the austral shallow meridional overturning cell to the Earth’s climate system on orbital timescales.