Vertical Profiles Of Salinity Research Articles

Spatiotemporal Variations in Upper‐Ocean Salinity Over the North Pacific in 2004–2021

AbstractInterannual variations in upper ocean salinity in the North Pacific Ocean (NP) were examined comprehensively over a period of 18 years (2004–2021) with gridded data sets considering vertical profiles of salinity. The salinity in nearly half of the basin varied in phase with a slight lag, and the rest of the basin exhibited the opposite phase on a decadal scale. The average salinity above 400 dbar prominently increased in the eastern and western mid‐latitude regions from approximately 2010 to the latter half of the 2010s, and decreased in the central subarctic and subtropics during the same period. This spatial pattern was similar to that of temperature change. While the freshening in the subtropics was remarkably above 100 dbar, salinity changes in the subarctic were large even in the subsurface. The first mode of the complex empirical orthogonal function analysis indicated the eastward (westward) propagation of salinity anomalies in the subarctic (subtropics), that is, a clockwise shift. Salinity budget analysis revealed that the changes in the 2010s were mainly caused by geostrophic advection in zonal regions around 40°N and 20°N, and the eastern NP. Precipitation also contributed to freshening in the subtropics, but not in the central subarctic. The meridional migration of salinity fronts in the subarctic and subtropics induced by wind stress, which is meridional contraction of the subtropical gyre, contributed to freshening in the central NP. It is unclear whether salinification in the eastern and western regions inevitably synchronizes and should be further examined.

Note on volume and distribution of fresh water in the Amazon River plume under low discharge conditions

In this research communication, we report the results of a field survey conducted in a part of the plume of the Amazon River between 0° and 5°N and offshore of the 28 m isobaths in November of 2022, during the low river discharge season. By comparing the observed vertical salinity profiles ‘disturbed’ by continental discharges within the plume with the virtually ‘undisturbed’ ones outside the plume, we estimated the total content of fresh water in the area covered by the measurements as 203 ± 22 km3, which equals to less than 3% of the average annual Amazon River discharge. Furthermore, we argue that the river-borne continental water was not confined to the upper mixed layer and show that about 37%, or 76 km3, of its volume was entrained into the plume-underlying layer between the mixed layer and the salinity maximum. This point is additionally supported by analysis of chromophoric dissolved organic matter (CDOM) fluorescence in water samples, demonstrating significant concentrations of terrigenous CDOM to depths up to 140 m. We also observed that there was a significant direct correlation between the volume of freshwater accumulated in the affected layer and background stratification (expressed as buoyancy frequency) in the unaffected layer below it.

Comparison of 4-dimensional variational and ensemble optimal interpolation data assimilation systems using a Regional Ocean Modeling System (v3.4) configuration of the eddy-dominated East Australian Current system

Abstract. Ocean models must be regularly updated through the assimilation of observations (data assimilation) in order to correctly represent the timing and locations of eddies. Since initial conditions play an important role in the quality of short-term ocean forecasts, an effective data assimilation scheme to produce accurate state estimates is key to improving prediction. Western boundary current regions, such as the East Australia Current system, are highly variable regions, making them particularly challenging to model and predict. This study assesses the performance of two ocean data assimilation systems in the East Australian Current system over a 2-year period. We compare the time-dependent 4-dimensional variational (4D-Var) data assimilation system with the more computationally efficient, time-independent ensemble optimal interpolation (EnOI) system, across a common modelling and observational framework. Both systems assimilate the same observations: satellite-derived sea surface height, sea surface temperature, vertical profiles of temperature and salinity (from Argo floats), and temperature profiles from expendable bathythermographs. We analyse both systems' performance against independent data that are withheld, allowing a thorough analysis of system performance. The 4D-Var system is 25 times more expensive but outperforms the EnOI system against both assimilated and independent observations at the surface and subsurface. For forecast horizons of 5 d, root-mean-squared forecast errors are 20 %–60 % higher for the EnOI system compared to the 4D-Var system. The 4D-Var system, which assimilates observations over 5 d windows, provides a smoother transition from the end of the forecast to the subsequent analysis field. The EnOI system displays elevated low-frequency (>1 d) surface-intensified variability in temperature and elevated kinetic energy at length scales less than 100 km at the beginning of the forecast windows. The 4D-Var system displays elevated energy in the near-inertial range throughout the water column, with the wavenumber kinetic energy spectra remaining unchanged upon assimilation. Overall, this comparison shows quantitatively that the 4D-Var system results in improved predictability as the analysis provides a smoother and more dynamically balanced fit between the observations and the model's time-evolving flow. This advocates the use of advanced, time-dependent data assimilation methods, particularly for highly variable oceanic regions, and motivates future work into further improving data assimilation schemes.

Integrated approaches to track saline intrusion for fresh groundwater resource protection in the Mekong Delta

In many coastal regions, groundwater is the sole freshwater resource for drinking and irrigation. However, coastal aquifers often face saline intrusion due to excessive groundwater extraction, climate change, and sea-level rise. This study integrated approaches in geochemistry, geophysics, statistical analysis, and geographic information system (GIS) to identify groundwater salinization pathways in the Ca Mau Peninsula of the Mekong Delta for sustainable protection of the invaluable freshwater resources. We collected 31 well logging data and groundwater samples from 388 wells in the area. A geochemical analysis demonstrated significant salinization in 9% of investigated wells. Calculated entropy-weighted water quality index (EQWI) indicates that only <3% of samples have excellent water quality and about 35% of medium-to-poor water quality groundwater. High salinity is the leading cause of impaired water quality. We combined geochemical and geophysical methods to validate an approach relating well-logging data (formation resistivity) to salinity to determine high-resolution vertical salinity profiles across the aquifer systems. We demonstrated the occurrence of saline groundwater in the surficial aquifers (Holocene and upper Pleistocene) that overlay above fresh and ancient groundwater aquifers (upper middle and lower Pleistocene, and Pliocene). This fresh groundwater is mostly fossil (age >10,000 years) and cannot be recharged directly from rainfall in the area while being highly susceptible to salinization by the downward movement of saline waters from overlaying aquifers. These findings call for appropriate strategies and directives in groundwater management to protect and sustain the critical water resources in the Mekong Delta.

Reconstruction of subsurface ocean state variables using Convolutional Neural Networks with combined satellite and in situ data

Subsurface ocean measurements are extremely sparse and irregularly distributed, narrowing our ability to describe deep ocean processes and thus also limiting our understanding of the role of ocean and marine ecosystems in the Earth system. To overcome these observational limitations, neural networks combining remotely-sensed surface measurements and in situ vertical profiles are increasingly being used to retrieve high-quality three-dimensional estimates of the ocean state. This study proposes a convolutional neural network (CNN) architecture for the reconstruction of vertical profiles of temperature and salinity starting from surface observation-based data. The model is trained on satellite and in situ data collected between 2005 and 2020 in the Atlantic Ocean. Rather than using spatially gridded in situ observations, we use directly measured vertical profiles. Different combinations of surface variables are analyzed and compared in order to determine the most effective inputs for the CNN. Furthermore, the relative importance of each of these variables in the vertical reconstruction is assessed using Shapley values, originally developed in the framework of cooperative game theory. The model performance is shown to be superior to current state-of-the-art methods and the same approach can easily be extended to other basins or to the global ocean.

Improvements of Lagrangian Data Assimilation Tested in the Gulf of Mexico

Abstract This study extends initial work by Sun and Penny and Sun et al. to explore the inclusion of path information from surface drifters using an augmented-state Lagrangian data assimilation based on the local ensemble transform Kalman filter (LETKF-LaDA) with vertical localization to improve analysis of the ocean. The region of interest is the Gulf of Mexico during the passage of Hurricane Isaac in the summer of 2012. Results from experiments with a regional ocean model at eddy-permitting and eddy-resolving model resolutions are used to quantify improvements to the analysis of sea surface velocity, sea surface temperature, and sea surface height in a data assimilation system. The data assimilation system assimilates surface drifter positions, as well as vertical profiles of temperature and salinity. Data were used from drifters deployed as a part of the Grand Lagrangian Deployment beginning 20 July 2012. Comparison of experiment results shows that at both eddy-permitting and eddy-resolving horizontal resolutions Lagrangian assimilation of drifter positions significantly improves analysis of the ocean state responding to hurricane conditions. These results, which should be applicable to other tropical oceans such as the Bay of Bengal, open new avenues for estimating ocean initial conditions to improve tropical cyclone forecasting.

On the ability of OMIP models to simulate the ocean mixed layer depth and its seasonal cycle in the Arctic Ocean

We evaluate the skills of ocean–sea ice general circulation models involved in the Ocean Modeling Intercomparison Project in simulating the ocean mixed layer depth and its seasonal cycle in the Arctic region. During summer months, all models consistently underestimate the mixed layer depth compared to observational data from the Monthly Isopycnal Mixed layer Ocean Climatology and the Ice Tethered Profilers. In fall and winter, the models exhibit great variability compared to observational data, and inter-model comparison reveals differences up to several tens of meters. We analyze the origin of the fall and winter model biases in ice-covered regions, where the seasonal cycle of the surface salinity and mixed layer depth is strongly influenced by brine rejection resulting from ocean–sea ice interactions.Focusing first on the central Arctic Ocean, defined here as the region north of 80° N, we show that all models simulate more or less the same vertical sea ice mass balance and thus similar salt fluxes into the ocean during sea ice freezing. Furthermore, the model ensemble features a strong relationship between the stratification profile in September and the mixed layer depth at the end of winter. The models whose stratification compares the best to observational data also display the most realistic values of the mixed layer depth at the end of winter. We argue that the discrepancies between models are therefore not so much linked to the surface salt balance but rather to the accuracy with which those models reproduce the vertical salinity profile. In short, a weakly stratified ocean tends to create a deep mixed layer, while strong stratification leads to a shallow mixed layer. To substantiate this conclusion, we apply a simple conceptual model, which simulates the month-to-month evolution of the mixed layer depth using as input the vertical salinity gradients and the surface salt fluxes from general circulation models. Quite surprisingly, this simplified dynamics captures very well the behavior of the general circulation models, emphasizing the role of the different vertical stratification in the control of the mixed layer depth. Furthermore, this interplay may also significantly account for the large mixed layer biases observed in other ice-covered regions of the pan-Arctic seas, even though sea–ice ocean interaction is not the only driver of mixed layer variability in fall and winter there.

How does the Niger river warm coastal waters in the northern Gulf of Guinea?

To highlight the processes by which the Niger River warms the coastal waters in the eastern part of the northern Gulf of Guinea upwelling, two simulations of the NEMO model at high resolution were used over the period 2010 - 2017. The first simulation is realistic while the second is a simulation in which the effects of the Niger River are not taken into account. The first step was to evaluate the outputs of the models, using satellite products and in situ observations. The average states of the Sea Surface Temperature, Salinity, Height, zonal current and vertical profiles of temperature and salinity showed the ability of the model to reproduce correctly the physical characteristics of the study area. The analysis of the heat balance terms of the two simulations showed that vertical diffusion and meridional advection processes are the causes of the warming induced by the Niger River. The stratification and vertical shear of the horizontal currents reveal that the river acts by inhibiting the upwelling of cold water induced by vertical diffusion. The river reinforces the stratification and prevents vertical shearing of horizontal currents at the bottom of the mixed layer.

Reconstructing three-dimensional salinity field of the South China Sea from satellite observations

High-resolution salinity information is of great significance for understanding the marine environment. We here propose a deep learning model denoted the “Attention U-net network” to reconstruct the daily salinity fields on a 1/4° grid in the interior of the South China Sea (SCS) from satellite observations of surface variables including sea surface salinity, sea surface temperature, sea level anomaly, and sea surface wind field. The vertical salinity profiles from the GLORYS2V4 reanalysis product provided by Copernicus Marine Environment Monitoring Service were used for training and evaluating the network. Results suggest that the Attention U-net model performs quite well in reconstructing the three-dimensional (3D) salinity field in the upper 1000 m of the SCS, with an average root mean square error (RMSE) of 0.051 psu and an overall correlation coefficient of 0.998. The topography mask of the SCS in the loss function can significantly improve the performance of the model. Compared with the results derived from the model using Huber loss function, there is a significant reduction of RMSE in all vertical layers. Using sea surface salinity as model inputs also helps to yield more accurate subsurface salinity, with an average RMSE near the sea surface being reduced by 16.4%. The good performance of the Attention U-net model is also validated by in situ mooring measurements, and case studies show that the reconstructed high-resolution 3D salinity field can effectively capture the evolution of underwater signals of mesoscale eddies in the SCS. The resolution and accuracy of sea surface variables observed by satellites will continue to improve in the future, and with these improvements, more precise 3D salinity field reconstructions will be possible, which will bring new insights about the multi-scale dynamics research in the SCS.

An inventory of salty and warm subsurface intrusions in the South Brazil Bight

Subsurface intrusions of salty and warm waters onto the shelf can potentially impact the thermodynamics and biogeochemistry of these relatively shallow water environments. Such thermohaline intrusions are usually associated with double diffusive processes and can enhance the vertical and lateral fluxes. In this work, we characterized subsurface intrusions of Tropical Waters (TW) at the South Brazil Bight (SBB) - a mid-latitude continental shelf, which were detected based on salinity vertical profiles from a historical dataset. We found the intrusions tend to follow the pycnocline and are relatively common year-round, occurring at 27% of the dataset, with a maximum salinity highly correlated with the maximum stratification. Intrusions have different along-shelf characteristics, varying with the shelf width and depth. North of São Sebastião Island (SSI) – at the central portion of the SBB –, intrusions were thicker, saltier, and shallower than the ones found at the south of SSI. These differences could be related to the variations of the Coastal Water (CW) and South Atlantic Central Water (SACW) volume along the shelf and throughout the year. We found that intrusions’ thickness presents an inverse correlation with stratification, resulting in thinner intrusions in more stratified environments. This inverse correlation suggests double-diffusively driven intrusions. We apply the Turner Angle method to investigate whether the environment is susceptible to double diffusive processes. This analysis suggests that thermohaline intrusions in the SBB might not be primarily double diffusive. However, the dominance of different double diffusion processes - diffusive convection (salt fingering) at the upper (lower) layer - suggests that these processes influence intrusion growth, steady-state, and erosion. Nonetheless, the mechanism responsible for the initial density perturbation remains unknown and further studies are needed to explore the relationship between the Brazil Current dynamics and thermohaline warm and salty subsurface intrusions.

High-Resolution Model of Clew Bay—Model Set-Up and Validation Results

Clew Bay is an important aquaculture production area in Ireland. In this study, we focused on a high-resolution simulation of the Clew Bay region based on a regional ocean modeling system (ROMS). Freshwater discharges from eight rivers are included in the model and a wetting–drying scheme has been implemented. The Clew Bay model simulation was validated and calibrated with available observations (e.g., acoustic Doppler current profiler (ADCP), vertical salinity and temperature profiles, and a tide gauge) in the geographic area of the model domain. High correlations were found between the model data and observed temperature, salinity and water levels, along with small root mean square errors. This indicates that the model is able to reproduce the oceanographic phenomena in the study area. The Taylor diagram analysis showed a high correlation coefficient (R = 0.99) between the observed bottom temperature in the Inner Bay and Clew Bay model, along with a small centered root mean square error (RMSD = 0.5 °C). High correlation coefficients (R &gt; 0.80) were found between the model and the two ADCPs for the zonal current component. There was a resemblance in structure between the model and the observed salinity profiles, indicating that freshwater was correctly implemented in the model. Moreover, the correlation coefficient between the model and the tidal sea surface height (SSH) was 0.99, with an RMSD of 0.09 m. We discovered that wind direction and speed had a significant impact on the bay’s water inflow rate. The model outputs can be used to provide scientists, fishermen, and decision-makers with hydrodynamic information on ocean conditions in the bay.

Ocean responses to Shaheen, the first cyclone to hit the north coast of Oman in 2021

On October 3rd, 2021, cyclone Shaheen made landfall on the northeast coast of Oman as a first-category cyclone after crossing the Sea of Oman. It is the first time in more than 130 years that a storm has made such extraordinary landfall on the northeast coast of Oman. This study intends to examine the effects of cyclone Shaheen on ocean cooling and biological response in the Sea of Oman (SO) and the the Arabian Sea (AS) using satellite remote sensing data, an Argo float, and the HYCOM model. The validation analysis of the HYCOM model and the Argo float showed strong correlations between vertical temperature profiles (R = 0.99) and vertical salinity profiles (R = 0.89). Furthermore, winds during the cyclone caused mixing and upwelling leading to Sea Surface Temperatures (SST) dropping 2.5 °C along southern Iranian coastlines, decreasing 5 °C along northern Oman's coastlines, and rising 1 °C across the Arabian Sea. As a result of the exitance of the cyclonic eddies in the Sea of Oman, a significant drop of 5 °C in SST was observed along the coastline of Oman caused by cold upwelled water from southern Iranian coastlines. Cyclone Shaheen's heavy rainfall caused the Sea Surface Salinity (SSS) in the Sea of Oman to drop from 36.7 to 36.8 psu. According to the results, Ekman pumping and upwelling processes predominated along the southern Iranian coast resulting in nutrient uplift and phytoplankton blooms (3 mg/m3). In contrast, strong stratification near the coast of Oman prevented nutrient uplift and led to low Chl-a concentrations. Due to the unique nature of cyclone Shaheen, it is essential to examine the complex dynamic and interaction between the ocean and atmosphere in the Sea of Oman and the Arabian Sea.

Upper Ocean Responses to the Tropical Cyclones Ida and Felicia (2021) in the Gulf of Mexico and the Eastern North Pacific

Tropical cyclones (TCs) are a significant component of ocean–atmosphere interactions and the climate system. These interactions determine both the development and strength of TCs, as well as various biogeochemical processes in the upper oceans, including vertical mixing and primary production. We investigated the impact of the TCs Felicia and Ida that emerged in 2021 in the eastern North Pacific and the Gulf of Mexico, respectively, using satellite observations of sea-surface temperature (SST) and surface chlorophyll a (chl-a) concentrations, and vertical profiles of temperature and salinity derived from Argo floats. Observations differed between the two study areas. Cooling of SST associated with TC Ida was observed throughout the Gulf of Mexico (&lt;0.5 °C), except for warming in a region off the Mexican coast east of Ida’s track (by about 0.5 °C). The passing of TC Felicia cooled SST in the eastern region (15°N, 115°W) and a central region (15°N, 125°W) by 0.5 °C and 0.36 °C, respectively. The passing of the TCs caused enhanced vertical mixing of the upper ocean layer in the Gulf of Mexico, with a deepening of the mixed layers from 38 m to 68 m (TC Ida). In contrast, the mixed layer in the eastern North Pacific decreased from 50 m to 20 m. For the eastern North Pacific, mixing could be related to an increase in surface chl-a and thus enhanced phytoplankton biomass was observed for 2 months after the passing of TC Felicia with a chl-a increase of 0.15 mg m−3. In the Gulf of Mexico, however, TC Ida caused the injection of a coastal phytoplankton bloom into the open Gulf, resting for more than a month after the cyclone had passed. Our findings contribute to the understanding of potential SST cooling, destratification, and enhanced primary production due to the passage of TCs in two distinct ocean regions, i.e., the open eastern North Pacific and the semi-enclosed Gulf of Mexico.

Lateral Variation of Tidal Mixing Asymmetry and Its Impact on the Longitudinal Sediment Transport in Turbidity Maximum Zone of Salt Wedge Estuary

The lateral bathymetry in the estuary results in different degrees of tidal mixing asymmetry, which has significant impacts on the longitudinal sediment transport by changing the temporal variation of vertical eddy diffusion. This study focus on the lateral variation of tidal mixing asymmetry and longitudinal sediment transport at the landward boundary of turbidity maximum zone in the North Channel of Yangtze estuary, which is a typical time-dependent salt wedge estuary. A transect survey was carried out in December, 2018; five vertical profiles of flow velocity, salinity and suspended sediment concentration were simultaneously measured covering a spring tidal cycle. Analysis of the data revealed that, after the maximum ebb, the stratification in the main and secondary channel was stronger than that on the shoal. In the channel, during ebb tide, the stronger stratification restrained the turbulent mixing induced by vertical shear, vertical mixing during the flood tide was stronger than that during ebb tide and vertical mixing coefficients ranged from 0.06 to 0.12, showing regular tidal mixing asymmetry over a flood–ebb tidal cycle. Therefore, stronger eddy diffusion caused by vertical mixing resulted in higher suspended sediment concentrations during flood tide, the larger landward tidally averaged sediment transport rate was induced by tidal pumping with the transportation of flood tidal current and the net sediment transport over a flood–ebb tidal cycle in the channel was landward. Meanwhile, on the shoal, under the effect of vertical shear, the vertical mixing during flood tide was weaker than that during ebb tide; vertical mixing coefficients ranged from −0.27 to −0.02, showing the reversed tidal mixing asymmetry. Higher suspended sediment concentration was transported seaward by the ebb current, the tidally averaged sediment transport rate by both tidal pumping and advection was seaward and the net sediment transport was seaward. Furthermore, large river discharge increased the seaward advection sediment flux on the surface layer in the main channel, resulting in the seaward tidally averaged sediment flux. Strong resuspension increased the seaward advection sediment flux near the bottom in the main and secondary channel, resulting in the seaward tidally averaged sediment flux.

Dispersal of a small wave-protected river plume from drifter observations

Using low-cost surface drifters, this study investigates the influence of the Buranhém River plume on the coastal region of the city of Porto Seguro (in the state of Bahia). The results highlight the importance of small river plumes on the coastal region and their possible influence on tourist beaches and high biodiversity regions. Three drifters, mounted with GPS receivers and temperature and salinity sensors, were simultaneously released into the mouth of the river in six experiments between December 2019 and December 2020, during ebbing spring tides. In each experiment, vertical salinity profiles were measured hourly at the position of the central drifter for 5 h, in order to investigate the along-track stratification of the plume. Results show that there are two distinct dispersion patterns in the Buranhém River plume, and that they are controlled mainly by wind and river discharge. Southward (northward) dispersion with curvilinear shape forced by northeasterly (south and southwesterly) winds were observed during the experiments. The maximum vertical salinity gradient confirmed the shallow character of the river plume (< 3 m in depth), more highly stratified during high river discharge and northward dispersion than in the opposite situation of northeasterly winds and low and medium river discharge. The results suggest that the Buranhém River plume has a larger influence over the northern beaches of Porto Seguro, with its reach being defined by the river discharge. Beaches to the south of the river inlet are less influenced by the river plume. Such unprecedented findings form the background for future studies and for management of this highly visited tourist area in Brazil.

Observation of Abrupt Changes in the Sea Surface Layer of the Adriatic Sea

We observed interannual changes in the temperature and salinity of the surface layer of the Adriatic Sea when measured during the period 2005–2020. We observed non-stationarity and a positive linear trend in the series of mixed layer depth, heat storage, and potential energy anomalies. This non-stationarity was related to the climate regime that prevailed between 2011 and 2017. We observed significant changes in the interannual variability of salinity above and below the mixed layer depth and a positive difference in the surface barrier layer. In an effort to reconstruct the cause of this phenomenon, a multi-stage investigation was conducted. The first suspected culprit was the change in wind regime over the Mediterranean and Northeast Atlantic regions in September. Using the growing neural gas algorithm, September wind fields over the past 40 years were classified into nine distinct patterns. Further analysis of the CTD data indicated an increase in heat storage, a physical property of the Adriatic Sea known to be strongly influenced by the inflow of warm water masses controlled by the bimodal oscillating system (BiOS). The observed increase in salinity confirmed the assumption that BiOS activity affects heat storage. Unexpectedly, this analysis showed that an inverse vertical salinity profile was present during the summer months of 2015, 2017, and 2020, which can only be explained by salinity changes being a dominant factor. In addition, the aforementioned wind regime caused an increase in energy loss through latent energy dissipation, contributing to an even larger increase in salinity. While changes in the depth of the mixed layer in the Adriatic are usually due to temperature changes, this phenomenon was primarily caused by abrupt changes in salinity due to a combination of BiOS and local factors. This is the first record of such an event.

Global Gridded Argo Dataset Based on Gradient-Dependent Optimal Interpolation

The international Argo Program was launched at the turn of the millennium. It has since collected over 2 million vertical profiles of temperature and salinity from the upper 2000 m of the global ocean. Gridded interpolation is a technology that gives full play to the advantages of these profiles because they are scattered. This study develops a global gridded Argo dataset, called GDCSM-Argo, by using an improved gradient-dependent correlation scale method. The dataset is theoretically verified, its error-related statistics are recorded, and it is compared with other datasets to establish its reliability. The results show that the maximum mean RMSEs are 0.8 °C for temperature and 0.1 for salinity, and more than 90% of the analysis results are reliable under the statistical probability of 95%. Not only can GDCSM-Argo adequately preserve large-scale signals in the ocean but also retain more mesoscale features than other gridded Argo datasets. Preliminary applications also verify that GDCSM-Argo can systematically describe the spatio-temporal features of multiple elements in the global ocean, and is a useful tool in many areas of research.

Petroleum hydrocarbons in Brazilian Northeast continental shelf waters: baseline values

Water quality on the continental shelf off the eastern Brazilian Northeast region was investigated in two oceanographic campaigns during winter and summer, when vertical profiles of salinity, temperature, turbidity, chlorophyll and dissolved oxygen were recorded. Dissolved / dispersed petroleum hydrocarbons (DDPH) were also analyzed in sub-superficial water samples using fixed wavelength fluorescence spectroscopy methods. Shelf waters are dominated by Tropical Waters, with high salinity (> 36.5 g kg-1) and temperature (> 26 °C) and little continental influence. Turbidity was higher during winter, which may be due to the higher continental contribution and/or higher wave action. Chlorophyll was mostly < 1 µg L-1 and dissolved oxygen saturation was predominantly high (> 90%), but innermost costal stations were influenced by the Capibaribe estuary. Median DDPH concentrations were as low as 0.07 and 0.04 µg L-1 Carmópolis oil equivalents during winter and summer respectively, and 0.02 µg L-1 chrysene equivalent for both periods. An exception was observed off Suape Harbor (0.35 µg L-1 Carmópolis oil equiv. and 0.13 µg L-1 chysene equiv.), suggesting navigation activities as the main local source. The overall DDPH median of 0.06 μg L-1 Carmópolis oil equivalents and 0.02 μg L-1 chrysene equivalents are proposed as the baseline concentration for non-polluted coastal water for the tropical western Atlantic Ocean margin.

Barrier Effect of the Pearl River Estuarine Plume on Wind‐Induced Coastal Upwelling of Nutrients

AbstractCoastal upwelling caused by winds seasonally occurs in summer in the Northern South China Sea. The alongshore prevailing southwest winds, induced by East Asia Summer Monsoon, exert a uniform Coriolis force to drive the surface water offshore, which in turn pushes the deeper coastal water upward. The common view is that coastal upwelling brings up nutrients from deep water. The presence of a buoyance layer such as the riverine or estuarine plumes damps the Ekman effect and hence upwelling. However, the semi‐quantitative analysis of reduced upwelled nitrate amount due to plume (barrier) effect during this interactive process is rare. To examine the dynamics of water masses and nutrient upward transport process in the coastal waters in summer, vertical profiles of temperature, salinity, and nitrate were taken along the transects from the Pearl River estuary to 150 km offshore in July cruise of 2002 in the northern South China Sea. The results show a three‐layer structure resulting from the three water masses under the impact of a large buoyant plume: high‐nutrient plume water in the surface layer, undetectable‐nutrient offshore surface water in the middle layer, and low‐nutrient deep water in the bottom layer. This structure indicates that this middle layer was the offshore surface water entrained underneath the estuarine plume and hence, weakened the intensity of upwelling. Upwelled nitrate amount is reduced by ∼30%–35% from the deep water to the surface layer due to the middle layer based on our estimate. The finding suggests that the presence of estuarine plumes plays an important role as a barrier to weaken upwelling of deep water and subsequently reduce the upward transport of nutrients by wind‐induced coastal upwelling and therefore, such the barrier effect should be considered in estimating budgets of nutrients and subsequent carbon fixation in coastal waters.

Winter observations alter the seasonal perspectives of the nutrient transport pathways into the lower St. Lawrence Estuary

Abstract. The St. Lawrence Estuary connects the Great Lakes with the Atlantic Ocean. The accepted view, based on summer conditions, is that the estuary's surface layer receives its nutrient supply from vertical mixing processes. This mixing is caused by the estuarine circulation and tides interacting with the topography at the head of the Laurentian Channel. During winter when ice forms, historical process-based studies have been limited in scope. Winter monitoring has been typically confined to vertical profiles of salinity and temperature as well as near-surface water samples collected from a helicopter for nutrient analysis. In 2018, however, the Canadian Coast Guard approved a science team to sample in tandem with its ice-breaking and ship escorting operations. This opportunistic sampling provided the first winter turbulence observations, which covered the largest spatial extent ever measured during any season within the St. Lawrence Estuary and the Gulf of St. Lawrence. The nitrate enrichment from tidal mixing resulted in an upward nitrate flux of about 30 nmol m−2 s−1, comparable to summer values obtained at the same tidal phase. Further downstream, deep nutrient-rich water from the gulf was mixed into the subsurface nutrient-poor layer at a rate more than an order of magnitude smaller than at the head. These fluxes were compared to the nutrient load of the upstream St. Lawrence River. Contrary to previous assumptions, fluvial nitrate inputs are the most significant source of nitrate in the estuary. Nitrate loads from vertical mixing processes would only exceed those from fluvial sources at the end of summer when fluvial inputs reach their annual minimum.