Submit to Special Issue Submit Abstract to Special Issue Review for Remote Sensing Propose a Special Issue

Journal Browser

► Journal Browser

Special Issue "Satellite-Based Sea Surface Salinity for Ocean Observation"

Special Issue Editors
Special Issue Information
Keywords
Published Papers

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

Deadline for manuscript submissions: 1 January 2024 | Viewed by 2864

Share This Special Issue

Special Issue Editor

Dr. Ebenezer Sackitey Nyadjro

E-Mail Website
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 including water mass formation, density and circulation, heat storage, air–sea interactions, and the hydrological cycle. Understanding salinity variability is therefore paramount toward understanding global climate. In the past, salinity measurements have been sparse. The launch of the Soil Moisture and Ocean Salinity (SMOS), Aquarius, and Soil Moisture Active Passive (SMAP) satellites opened up a new era for providing global oceans’ surface salinity observations, which have improved our understanding of salinity variability and dynamics, among others. The scientific value of data collected by these salinity satellites is fostering both oceanographic and climate-related studies.

The aim of this Special Issue is to highlight the successes, applications, and impacts of satellite-derived sea surface salinity measurements on oceanographic research. It also highlights several ongoing innovative, synergetic uses of other satellite-derived parameters (e.g., SST, altimetry, scatterometry, ocean color), in situ measurements and numerical models to further our understanding of the global earth system, especially ocean variability, dynamics, and air–sea interactions. In this Special Issue, we welcome papers exploring all areas in remote sensing of salinity.

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

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;
Comparison, evaluation, and validation of satellite-derived sea surface salinity;
Sea surface 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 satellite-derived sea surface salinity in understanding freshwater plumes;
Data assimilation of satellite-derived sea surface salinity to improve ocean studies and forecasting;
Role of satellite-derived sea surface salinity in understanding ocean and climate change;
Using satellite-derived sea surface salinity products to improve understanding of the hydrological cycle;
Novel applications of satellite-derived sea surface salinity products.

Dr. Ebenezer Sackitey Nyadjro
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

sea surface salinity
SMAP
SMOS
Aquarius
remote sensing
data assimilation
freshwater dynamics

Published Papers (3 papers)

Download All Papers

Research

Open AccessArticle

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

and

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

Viewed by 1017

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 Satellite-Based Sea Surface Salinity for Ocean Observation)

► Show Figures

Figure 1

Open AccessArticle

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

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

Viewed by 442

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 Satellite-Based Sea Surface Salinity for Ocean Observation)

► Show Figures

Figure 1

Open AccessArticle

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

Xuewei Zhang

Ning Zhao

and

Zhen Han

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

Viewed by 1010

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 Satellite-Based Sea Surface Salinity for Ocean Observation)

► Show Figures

Graphical abstract

Journal Menu

Journal Browser

Special Issue "Satellite-Based Sea Surface Salinity for Ocean Observation"

Share This Special Issue

Special Issue Editor

Special Issue Information

Keywords

Published Papers (3 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI