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Advances in Remote Sensing of Ocean Salinity

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ocean Remote Sensing".

Deadline for manuscript submissions: closed (20 March 2025) | Viewed by 14263

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Special Issue Editor

Dr. Ebenezer Sackitey Nyadjro

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Guest Editor

1. Northern Gulf Institute, Department of Geosciences, Mississippi State University, Starkville, MS, USA
2. NOAA National Centers for Environmental Information (NCEI), Stennis Space Center, Hancock County, MS 39529, USA
Interests: ocean salinity; freshwater dynamics; variability of ocean currents; microplastics; air-sea interactions; tropical climate variability; ocean leadership and capacity building

Special Issue Information

Dear Colleagues,

Salinity plays an important role in the global ocean as it influences water mass formation, density and circulation, heat storage, air–sea interactions, and the hydrological cycle. Understanding salinity variability is, therefore, paramount in understanding global climate. In the past, salinity measurements have been sparse. The launches of the soil moisture and ocean salinity (SMOS), Aquarius, and soil moisture active passive (SMAP) satellites initiated a new era for investigating the surface salinity of global oceans, which has improved our understanding of salinity variability and dynamics, among others. The scientific value of data collected by these salinity satellites is contributing to both oceanographic and climate-related studies. These data have been further augmented by improved ocean observations from Argo floats, drifters, and gliders, along with numerical modelling and data assimilation.

The aim of this Special Issue is to highlight recent salinity studies. This includes the successes, applications, and impacts of satellite-derived sea surface salinity measurements on oceanographic research. This Special Issue also highlights several ongoing innovative, synergetic uses of other satellite-derived parameters (e.g., SST, altimetry, scatterometry, ocean color), in situ measurements, data assimilation, and numerical models to further our understanding of the global earth system, especially ocean variability, dynamics, and air–sea interactions.

The topics of interest include, but are not limited to, the following:

Salinity studies in the aquatic environment;
Inter-comparison, evaluation, and validation of salinity products ;
Successes and challenges of satellite-derived sea surface salinity missions;
Improvements in sea surface salinity retrieval and products;
Improving retrieval techniques for coastal sea surface salinity;
Effects of rain on satellite salinity retrieval;
Understanding salinity variability using satellite(s), in situ observations, and ocean models;
Ocean salinity budgets, fluxes, and transports;
Salinity-influenced stratification and air–sea interactions;
Use of salinity information in understanding freshwater plumes;
Data assimilation of salinity to improve ocean studies, climate variability, and forecasting;
Role of salinity in understanding ocean and climate change;
Using salinity products to improve understanding of the hydrological cycle;
Novel applications of satellite-derived sea surface salinity products.

Dr. Ebenezer Sackitey Nyadjro
Guest Editor

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Keywords

salinity
sea surface salinity
in situ salinity
SMAP
SMOS
Aquarius
remote sensing
data assimilation
freshwater dynamics
ocean climate

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Published Papers (7 papers)

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Research

31 pages, 17406 KiB

Open AccessArticle

Identification of Internal Tides in ECCO Estimates of Sea Surface Salinity in the Andaman Sea

by Bulusu Subrahmanyam, V. S. N. Murty, Sarah B. Hall and Corinne B. Trott

Remote Sens. 2024, 16(18), 3408; https://doi.org/10.3390/rs16183408 - 13 Sep 2024

Viewed by 1290

Abstract

We used NASA’s high-resolution (1/48° or 2.3 km, hourly) Estimating the Circulation and Climate of the Ocean (ECCO) estimates of salinity at a 1 m depth from November 2011 to October 2012 to detect semi-diurnal and diurnal internal tides (ITs) in the Andaman Sea and determine their characteristics in three 2° × 2° boxes off the Myanmar coast (box A), central Andaman Sea (box B), and off the Thailand coast (box C). We also used observed salinity and temperature data for the above period at the BD12-moored buoy in the central Andaman Sea. ECCO salinity data were bandpass-filtered with 11–14 h and 22–26 h periods. Large variations in filtered ECCO salinity (~0.1 psu) in the boxes corresponded with near-surface imprints of propagating ITs. Observed data from the box B domain reveals strong salinity stratification (halocline) in the upper 40 m. Our analyses reveal that the shallow halocline affects the signatures of propagating semi-diurnal ITs reaching the surface, but diurnal ITs propagating in the halocline reach up to the surface and bring variability in ECCO salinity. In box A, the semi-diurnal IT characteristics are higher speeds (0.96 m/s) with larger wavelengths (45 km), that are closer to theoretical mode 2 estimates, but the diurnal ITs propagating in the box A domain, with a possible source over the shelf of Gulf of Martaban, attain lower values (0.45 m/s, 38 km). In box B, the propagation speed is lower (higher) for semi-diurnal (diurnal) ITs. Estimates for box C are closer to those for box A. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of Ocean Salinity)

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12 pages, 8263 KiB

Open AccessCommunication

Global Wavenumber Spectra of Sea Surface Salinity in the Mesoscale Range Using Satellite Observations

by Daling Li Yi and Peng Wang

Remote Sens. 2024, 16(10), 1753; https://doi.org/10.3390/rs16101753 - 15 May 2024

Cited by 1 | Viewed by 1359

Abstract

Sea surface salinity (SSS) variability at mesoscales has become an important research topic in recent decades, thanks to satellite missions enabling observations of SSS with global capacity and mesoscale resolution. Here, we analyze the near-global data of the Aquarius/SAC-D along-track SSS, focusing on the slopes of SSS variance spectra in the mesoscale range from 180 to 430 km. In the vast extratropics, the spectral slope is close to −2, indicating a dynamical regime for the inverse cascade of depth-integrated energy identified by the surface quasi-geostrophic theory. However, the spectral slopes in regions near the mouths of the largest rivers are steeper than −2, reaching −3, possibly due to the large river freshwater flux. In addition, data from high-resolution thermosalinograph are used to validate satellite measurements and show good consistency in terms of SSS variance spectral slopes. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of Ocean Salinity)

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31 pages, 17222 KiB

Open AccessArticle

Salinity Fronts in the South Atlantic

by Igor M. Belkin and Xin-Tang Shen

Remote Sens. 2024, 16(9), 1578; https://doi.org/10.3390/rs16091578 - 29 Apr 2024

Cited by 1 | Viewed by 1706

Abstract

Monthly climatology data for salinity fronts in the South Atlantic have been created from satellite SMOS sea surface salinity (SSS) measurements taken from 2011–2019, processed at the Barcelona Expert Center of Remote Sensing (BEC), and provided as high-resolution (1/20°) daily SSS data. The SSS fronts have been identified with narrow zones of enhanced horizontal gradient magnitude (GM) of SSS, computed using the Belkin–O’Reilly algorithm (BOA). The SSS gradient fields generated by the BOA have been log-transformed to facilitate feature recognition. The log-transformation of SSS gradients markedly improved the visual contrast of gradient maps, which in turn allowed new features to be revealed and previously known features to be documented with a monthly temporal resolution and a mesoscale (~100 km) spatial resolution. Monthly climatologies were generated and analyzed for large-scale open-ocean SSS fronts and for low-salinity regions maintained by the Rio de la Plata discharge, Magellan Strait outflow, Congo River discharge, and Benguela Upwelling. A 2000 km-long triangular area between Africa and Brazil was found to be filled with regular quasi-meridional mesoscale striations that form a giant ripple field with a 100 km wave length. South of the Tropical Front, within the subtropical high-salinity pool, a trans-ocean quasi-zonal narrow linear belt of meridional SSS maximum (Smax) was documented. The meridional Smax belt shifts north–south seasonally while retaining its well-defined linear morphology, which is suggestive of a yet unidentified mechanism that maintains this feature. The Subtropical Frontal Zone (STFZ) consists of two tenuously connected fronts, western and eastern. The Brazil Current Front (BCF) extends SE between 40 and 45°S to join the subantarctic front (SAF). The STFZ trends NW–SE across the South Atlantic, seemingly merging with the SAF/BCF south of Africa to form a single front between 40 and 45°S. In the SW Atlantic, the Rio de la Plata plume migrates seasonally, expanding northward in winter (June–July) from 39°S into the South Brazilian Bight, up to Cabo Frio (23°S) and beyond. The inner Plata front moves in and out seasonally. Farther south, the Magellan Strait outflow expands northward in winter (June–July) from 53°S up to 39–40°S to nearly join the Plata outflow. In the SE Atlantic, the Congo River plume spreads radially from the river mouth, with the spreading direction varying seasonally. The plume is often bordered from the south by a quasi-zonal front along 6°S. The diluted Congo River water spreads southward seasonally down to the Angola–Benguela Front at 16°S. The Benguela Upwelling is delineated by a meridional front, which extends north alongshore up to 20°S, where the low-salinity Benguela Upwelling water forms a salinity front, which is separate from the thermal Angola–Benguela Front at 16°S. The high-salinity tropical water (“Angola water”) forms a wedge between the low-salinity waters of the Congo River outflow and Benguela Upwelling. This high-salinity wedge is bordered by salinity fronts that migrate north–south seasonally. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of Ocean Salinity)

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13 pages, 20131 KiB

Open AccessCommunication

Satellite-Derived Variability of Sea Surface Salinity and Geostrophic Currents off Western Patagonia

by Gonzalo S. Saldías, Pedro A. Figueroa, David Carrasco, Diego A. Narváez, Iván Pérez-Santos and Carlos Lara

Remote Sens. 2024, 16(9), 1482; https://doi.org/10.3390/rs16091482 - 23 Apr 2024

Cited by 2 | Viewed by 1535

Abstract

The coastal ocean off western Patagonia is one of the main coastal regions with high freshwater inputs from rivers, rain, and glaciers in the Southern Hemisphere. This study conducts an analysis of the seasonal and interannual variations in sea surface salinity and meridional geostrophic transports, specifically focusing on the Cape Horn Current, using improved satellite-derived data of sea surface salinity (SSS) and geostrophic velocities spanning an ∼11-year period (September 2011–August 2022). Our results reveal a clear salinity minimum in a coastal band between 42–54°S associated with the highest freshwater content. The average geostrophic currents are stronger south of 49°S, in line with the location of the Cape Horn Current. The average salinity minimum tends to disappear south of 54°S, with salinity values increasing slightly southward. The seasonal cycle of salinity shows the most pronounced minimum in summer (∼33.2–33.4). The greatest variability in salinity (standard deviation of salinity fields) occurs in the southern region of the Cape Horn Current. Hovmöller plots reveal two cores of minimum salinity observed in spring and summer (∼33.3–33.4). The freshwater off the Gulf of Penas contributes to the northern core. The meridional geostrophic transport differs between the northern and southern sections, with transports predominantly towards the Equator (Pole) north (south) of about 47–48°S during spring–summer. There is a marked seasonal variability in the magnitude and northern limit of the southward-flowing Cape Horn Current, being extended further north during winter and with a maximum average magnitude during summer–fall (about

- 2 \times 10^{4}

m² s⁻¹). On the interannual scale, a major drop in surface salinity occurred off northern and central Patagonia during 2018–2019. Finally, a potential long-term freshening trend is observed in the coastal area off southern Patagonia (south of 52°S), although prolonged data records are essential to confirm this pattern. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of Ocean Salinity)

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25 pages, 6796 KiB

Open AccessArticle

Comparison of Freshwater Content and Variability in the Arctic Ocean Using Observations and Model Simulations

by Emma L. Hoffman, Bulusu Subrahmanyam, Corinne B. Trott and Sarah B. Hall

Remote Sens. 2023, 15(15), 3715; https://doi.org/10.3390/rs15153715 - 25 Jul 2023

Cited by 1 | Viewed by 2748

Abstract

Freshwater content (FWC), generally characterized in the Arctic Ocean by salinities lower than 34.8 psu, has shifted in both quantity and distribution in recent decades in the Arctic Ocean. This has been largely driven by changes in the volume and salinity of freshwater sources and the direction and magnitude of major currents. In this study, we analyze the variability in FWC and other physical oceanographic variables from 1993 to 2021 in the Arctic Ocean and Beaufort Gyre (BG) using in situ and remote sensing observations and five ocean models and reanalysis products. Generally, ocean models and reanalysis products underestimate FWC in the BG when compared with observations. Modeled FWC and sea surface height (SSH) in the BG are well correlated during the time period and are similar to correlations of the observational data of these variables. ORAS5 compares best to EN4 salinity over the entire study period, although GLORYS12 agrees well pre-2007 and SODA post-2007. Outside the BG, consistency between modeled SSH, FWC, and limited observations varies between models. These comparisons help identify discrepancies in ocean model and reanalysis products while highlighting areas where future improvements are necessary to further our understanding of Arctic FWC. As observations are scarce in the Arctic, these products and their accuracy are important to studying this dynamic and vulnerable ocean. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of Ocean Salinity)

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33 pages, 9857 KiB

Open AccessArticle

Characteristics of Internal Tides from ECCO Salinity Estimates and Observations in the Bay of Bengal

by Bulusu Subrahmanyam, V.S.N. Murty and Sarah B. Hall

Remote Sens. 2023, 15(14), 3474; https://doi.org/10.3390/rs15143474 - 10 Jul 2023

Cited by 1 | Viewed by 1538

Abstract

Internal waves (IWs) are generated in all the oceans, and their amplitudes are large, especially in regions that receive a large amount of freshwater from nearby rivers, which promote highly stratified waters. When barotropic tides encounter regions of shallow bottom-topography, internal tides (known as IWs of the tidal period) are generated and propagated along the pycnocline due to halocline or thermocline. In the North Indian Ocean, the Bay of Bengal (BoB) and the Andaman Sea receive a large volume of freshwater from major rivers and net precipitation during the summer monsoon. This study addresses the characteristics of internal tides in the BoB and Andaman Sea using NASA’s Estimating the Circulation and Climate of the Ocean (ECCO) project’s high-resolution (1/48° and hourly) salinity estimates at 1 m depth (hereafter written as ECCO salinity) during September 2011–October 2012, time series of temperature, and salinity profiles from moored buoys. A comparison is made between ECCO salinity and NASA’s Soil Moisture Active Passive (SMAP) salinity and Aquarius salinity. The time series of ECCO salinity and observed salinity are subjected to bandpass filtering with an 11–14 h period and 22–26 h period to detect and estimate the characteristics of semi-diurnal and diurnal period internal tides. Our analysis reveals that the ECCO salinity captured well the surface imprints of diurnal period internal tide propagating through shallow pycnocline (~50 m depth) due to halocline, and the latter suppresses the impact of semi-diurnal period internal tide propagating at thermocline (~100 m depth) reaching the sea surface. The semi-diurnal (diurnal) period internal tides have their wavelengths and phase speeds increased (decreased) from the central Andaman Sea to the Sri Lanka coast. Propagation of diurnal period internal tide is dominant in the northern BoB and northern Andaman Sea. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of Ocean Salinity)

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18 pages, 14895 KiB

Open AccessArticle

A Modified U-Net Model for Predicting the Sea Surface Salinity over the Western Pacific Ocean

by Xuewei Zhang, Ning Zhao and Zhen Han

Remote Sens. 2023, 15(6), 1684; https://doi.org/10.3390/rs15061684 - 21 Mar 2023

Cited by 6 | Viewed by 2875

Abstract

The prediction of oceanic features is always an important issue in oceanography, where deep learning has been proven to be a useful tool. In this study, we applied the improved U-net model to predict the monthly sea surface salinity (SSS) over the western Pacific (WP) Ocean, and the model was designed to use the SSSs from six consecutive months to predict the SSS in the next month. The monthly satellite-based SSSs in 2015–2020 were used for model training, and the data collected after January 2021 were used to evaluate the model’s predictive abilities. The results showed that the predicted SSSs represented the general patterns of SSSs over the WP region. However, the small-scale features were smoothed out in the model, and the temporal variations were also not well captured, especially over the East China Sea and Yellow Sea (ECS&YS) region. To further evaluate the potential of the U-net model, a more specific model was conducted for the ECS&YS region (Domain 2), which successfully predicted both spatial and temporal variations in the SSSs, including the spreading and retreating of the low-salinity tongue. Based on the comparison between the two domains and sensitivity experiments, we found that the prediction biases were contributed by the spatial distributions of the SSSs, the domain size, and the filter numbers. In addition, further multi-step prediction experiments suggested that our U-net model could also be used for long-time prediction, and we have examined up to five months. Overall, this study demonstrated the great ability and potential of the U-net model for predicting SSS, even though only a few trainable data are available. Full article

(This article belongs to the Special Issue Advances in Remote Sensing of Ocean Salinity)

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