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This Special Issue gathers papers reporting research on various aspects of remote sensing of Sea Surface Salinity (SSS) and the use of satellite SSS in oceanography. It includes contributions presenting improvements in empirical or theoretical radiative transfer models; mitigation techniques of external interference such as RFI and land contamination; comparisons and validation of remote sensing products with in situ observations; retrieval techniques for improved coastal SSS monitoring, high latitude SSS and the assessment of ocean interactions with the cryosphere; and data fusion techniques combining SSS with sea surface temperature (SST). New instrument technology for the future of SSS remote sensing is also presented.

n/a --- satellite salinity --- one-dimensional (1D) aperture synthesis radiometer --- smos --- Gulf of Maine --- retrieval errors --- Aquarius --- combined active/passive SSS retrieval algorithm --- ocean surface roughness --- upwelling --- salt transport --- quality assessment --- sea ice --- SMOS --- microwave radiometry --- Arctic Gateways --- Aquarius satellite --- validation --- sea surface temperature --- water transport --- forward model --- river discharge --- sea surface salinity --- remote sensing --- retrieval algorithm --- Water Cycle Observation Mission (WCOM) --- SMAP --- microwave remote sensing --- alboran sea --- surface velocity --- Arctic Ocean --- sea surface salinity (SSS) --- coastal --- brightness temperature (TB) --- interferometric microwave imager (IMI) --- Scotian Shelf --- MICAP --- different instrument configurations --- bias characteristics --- mediterranean sea --- Gulf of Mexico --- calibration --- retroflections --- Arctic ocean --- salinity --- Sea Surface Salinity --- Arctic rivers --- Argo --- data processing --- aquarius --- ocean salinity --- Aquarius Validation Data System (AVDS)

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Ocean satellite remote sensing plays important roles in the observations of physical, biological and biogeochemical features in inland, coastal, and global ocean waters, with high temporal and spatial resolution. The satellite-measured ocean products are used for near-real-time ocean monitoring and climate data records to understand short-/long-term variabilities in marine environments and ecosystems as well as for decision making tools to manage social, economic, and environmental benefits. Validation/evaluation including a combination of field measurements and inter-satellite comparison is an essential step in providing more accurate satellite-derived ocean products. In this Special Issue, 14 papers have been published and include research on validation/evaluation, retrieval algorithms of ocean geophysical and biogeochemical parameters, and application of the satellite ocean products in the regional and global ocean. Subjects treated include: Sea Surface Temperature; Sea Ice Surface Temperature from VIIRS thermal infrared sensor; Sea Ice Detection from Spectroradiometer; Sea Surface Winds from HY-2A Scatterometer and GNSS—Reflectometry; Wave Height from Sentinel-3A SAR; Retrievals of Sea Surface Salinity, Chlorophyll-a, Particulate Organic Carbon, Particulate Backscattering, Marine Fishery resource, and Submesoscale Eddies from multiple Ocean Colour sensors.

sea ice --- ice surface temperature --- Suomi NPP --- JPSS --- remote sensing --- leads --- MODIS --- ocean color --- algorithm --- chlorophyll --- HPLC --- fluorometry --- particulate organic carbon --- southern ocean --- ocean colour --- satellite-derived chlorophyll-a concentration --- algorithm evaluation --- Northwest Atlantic --- Northeast Pacific --- Japanese common squid --- Todarodes pacificus --- habitat suitability index (HSI) --- the Yellow Sea --- the South Sea of South Korea --- spaceborne GNSS-R --- DDM --- ocean surface wind speed --- GMF --- CYGNSS --- HY-2A --- scatterometer --- sea surface wind field --- evaluation --- satellite altimetry --- significant wave height --- SAR --- wave buoy observations --- validation --- southwest England --- coastal altimetry --- Sentinel-3A --- SRAL --- particulate optical backscattering --- Raman scattering --- QAA algorithm --- ESA OC-CCI --- steric height --- sea level variability --- interferometric altimeter validation --- high-frequency radar --- MODIS ocean color patterns --- submesoscale eddies --- sea surface salinity estimation --- Changjiang diluted water --- neural network --- GOCI application --- sea surface temperature --- global gridded dataset --- Yellow Sea --- bias correction --- chlorophyll-a --- phytoplankton --- East/Japan Sea

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The tendency for climate to change has been one of the most surprising outcomes of the study of Earth's history. Marine geoscience can reveal valuable information about past environments, climates, and biota just before, during and after each climate perturbation. Particularly, certain intervals of geological records are windows to key episodes in the climate history of the Earth–life system. Ιn this regard, the detailed analyses of such time intervals are challenging and rewarding for environmental reconstruction and climate modelling, because they provide documentation and better understanding of a warmer-than-present world, and opportunities to test and refine the predictive ability of climate models. Marine geological dynamics such as sea-level changes, hydrographic parameters, water quality, sedimentary cyclicity, and (paleo)climate are strongly related through a direct exchange between the oceanographic and atmospheric systems. The increasing attention paid to this wide topic is also motivated by the interplay of these processes across a variety of settings (coastal to open marine) and timescales (early Cenozoic to modern). In order to realize the full predictive value of these warm (fresh)/cold (salty) intervals in Earth's history, it is important to have reliable tools (e.g., integrated geochemical, paleontological and/or paleoceanographic proxies) through the application of multiple, independent, and novel techniques (e.g., TEX86, UK’37, Mg/Ca, Na/Ca, Δ47, and μCT) for providing reliable hydroclimate reconstructions at both local and global scales.

microfacies types --- Pantokrator Limestones --- Vigla Formation --- Senonian calciturbidites --- Eocene brecciated limestones --- carbonate porosity --- petroleum prospectivity --- stratigraphic correlations --- marine biogenic carbonates --- depositional environment --- paleoceanographic evolution --- planktonic foraminifera --- pteropods --- stable isotopes --- sea surface temperature (SST) --- stratification --- productivity --- sapropel S1 --- Aegean Sea --- Late Quaternary --- shell weight --- climate variability --- sea surface density --- carbonate production --- X-ray microscopy (μCT) --- δ18O and Mg/Ca analyses --- offshore groundwater exploration --- coastal aquifers --- salt-/fresh-water relationship --- Mediterranean Sea --- Attica-Greece --- cleaning protocol --- unconsolidated core sediments --- climate reconstruction --- synchrotron X-ray microtomography (SμCT) --- foraminiferal-based proxies --- BTEX natural attenuation --- hydro-stratigraphy --- multi-layered aquifer --- Thriassion Plain --- confined and unconfined aquifer --- coastal aquifer --- Gulf of Eleusis --- ocean paleodensity --- Atlantic Meridional Circulation (AMOC) --- planktonic foraminiferal biogeography --- surface sediments --- morphometrics --- shell size --- environmental biomonitoring --- ecological optimum conditions --- primary productivity --- depth habitat preference --- cryptic speciation --- central Mediterranean hydrodynamics --- sea level fluctuations --- soluble substances --- coastal environment change --- diatom --- geochemical elements --- n/a

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Storm tides, surges, and waves associated with typhoons/tropical cyclones/hurricanes are the most severe threats to coastal zones, nearshore waters, and navigational safety. Therefore, predicting typhoon/tropical cyclone/hurricane-induced storm tides, surges, waves, and coastal erosion is essential for reducing the loss of human life and property and mitigating coastal disasters. There is still a growing demand for novel techniques that could be adopted to resolve the complex physical processes of storm tides, surges, waves, and coastal erosion, even if many studies on the hindcasting/prediction/forecasting of typhoon-driven storm tides, surges, waves, and also morphology evolution have been carried out through numerical models in the last decade. This Special Issue intends to collect the latest studies on storm tide, surge, and wave modeling and analysis utilizing dynamic and statistical models and artificial intelligence approaches to improve our simulating and analytic capabilities and our understanding of storm tides, surges, and waves. Five high-quality papers have been accepted for publication in this Special Issue; these papers cover the application and development of many high-end techniques for storm tides, surges, waves, and on-site investigation of coastal erosion and accretion.

typhoon wave --- sea surface temperature --- WAVEWATCH-III --- sbPOM --- depth-induced wave breaking --- wave-breaking formulation --- wave-breaking criterion --- shallow nearshore waters --- three-dimensional Bragg resonance --- regular waves --- random waves --- high-order spectral (HOS) method --- Gaussian spectrum --- V-shaped undulating bottom --- multivariate extreme value --- coastal modeling --- SWAN --- SWASH-2DH --- Corsica --- return level --- total water level --- erosion and accretion --- cross-shore profile evolution --- Lanyang River estuary --- limit of estuarine sediment transport --- northeastern coastal waters of Taiwan --- n/a

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Uncertainty quantification (UQ) is a mainstream research topic in applied mathematics and statistics. To identify UQ problems, diverse modern techniques for large and complex data analyses have been developed in applied mathematics, computer science, and statistics. This Special Issue of Mathematics (ISSN 2227-7390) includes diverse modern data analysis methods such as skew-reflected-Gompertz information quantifiers with application to sea surface temperature records, the performance of variable selection and classification via a rank-based classifier, two-stage classification with SIS using a new filter ranking method in high throughput data, an estimation of sensitive attribute applying geometric distribution under probability proportional to size sampling, combination of ensembles of regularized regression models with resampling-based lasso feature selection in high dimensional data, robust linear trend test for low-coverage next-generation sequence data controlling for covariates, and comparing groups of decision-making units in efficiency based on semiparametric regression.

Kullback–Leibler divergence --- geometric distribution --- accuracy --- AUROC --- allele read counts --- mixture model --- low-coverage --- entropy --- gene-expression data --- SCAD --- data envelopment analysis --- LASSO --- high-throughput --- sandwich variance estimator --- adaptive lasso --- semiparametric regression --- ?1 lasso --- Laplacian matrix --- elastic net --- feature selection --- sea surface temperature --- gene expression data --- Skew-Reflected-Gompertz distribution --- lasso --- next-generation sequencing --- BH-FDR --- stochastic frontier model --- ?2 ridge --- geometric mean --- resampling --- Gompertz distribution --- adapative lasso --- group efficiency comparison --- sensitive attribute --- MCP --- probability proportional to size (PPS) sampling --- randomization device --- SIS --- Yennum et al.’s model --- ensembles