surface salinity
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2022 ◽  
Author(s):  
Verónica González-Gambau ◽  
Estrella Olmedo ◽  
Antonio Turiel ◽  
Cristina González-Haro ◽  
Aina García-Espriu ◽  
...  

Abstract. This paper presents the first Soil Moisture and Ocean Salinity (SMOS) Sea Surface Salinity (SSS) dedicated products over the Baltic Sea. The SSS retrieval from L-band brightess temperature (TB) measurements over this basin is really challenging due to important technical issues, such as the land-sea and ice-sea contamination, the high contamination by Radio-Frequency Interferences (RFI) sources, the low sensitivity of L-band TB at SSS changes in cold waters and the poor characterization of dielectric constant models for the low SSS and SST ranges in the basin. For these reasons, exploratory research in the algorithms used from the level 0 up to level 4 has been required to develop these dedicated products. This work has been performed in the framework of the European Space Agency regional initiative Baltic+ Salinity Dynamics. Two Baltic+ SSS products have been generated for the period 2011–2019 and are freely distributed: the Level 3 (L3) product (daily generated 9-day maps in a 0.25° grid, https://doi.org/10.20350/digitalCSIC/13859) (González-Gambau et al., 2021a) and the Level 4 (L4) product (daily maps in a 0.05° grid, https://doi.org/10.20350/digitalCSIC/13860) (González-Gambau et al., 2021b)), that are computed by applying multifractal fusion to L3 SSS with Sea Surface Temperature (SST) maps. The accuracy of L3 SSS products is typically around 0.7–0.8 psu. The L4 product has an improved spatio-temporal resolution with respect to the L3 and the accuracy is typically around 0.4 psu. Regions with the highest errors and limited coverage are located in Arkona and Bornholm basins and Gulfs of Finland and Riga. The impact assessment of Baltic+ SSS products has shown that they can help in the understanding of salinity dynamics in the basin. They complement the temporally and spatially very sparse in situ measurements, covering data gaps in the region and they can also be useful for the validation of numerical models, particularly in areas where in situ data are very sparse.


Author(s):  
Cong Guan ◽  
Feng Tian ◽  
Michael J. McPhaden ◽  
Fan Wang ◽  
Shijian Hu ◽  
...  

2021 ◽  
Vol 14 (1) ◽  
pp. 71
Author(s):  
Sarah B. Hall ◽  
Bulusu Subrahmanyam ◽  
James H. Morison

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.


Abstract The distribution and interannual variation in the winter halocline in the upper layers of the world ocean were investigated via analyses of hydrographic data from the World Ocean Database 2013 using a simple definition of the halocline. A halocline was generally observed in the tropics, equatorward portions of subtropical regions, subarctic North Pacific and Southern Ocean. A strong halocline tended to occur in areas where the sea surface salinity (SSS) was low. The interannual variation in halocline strength was correlated with variation in SSS. The correlation coefficients were usually negative: the halocline was strong when the SSS was low. However, in the Gulf of Alaska in the northeastern North Pacific, the correlation coefficient was positive. There, halocline strength was influenced by interannual variation in Ekman pumping.


2021 ◽  
Vol 13 (24) ◽  
pp. 5120
Author(s):  
Thomas Meissner ◽  
Andrew Manaster

Sea-ice contamination in the antenna field of view constitutes a large error source in retrieving sea-surface salinity (SSS) with the spaceborne Soil Moisture Active Passive (SMAP) L-band radiometer. This is a major obstacle in the current NASA/Remote Sensing Systems (RSS) SMAP SSS retrieval algorithm in regards to obtaining accurate SSS measurements in the polar oceans. Our analysis finds a strong correlation between 8-day averaged SMAP L-band brightness temperature (TB) bias and TB measurements from the Advanced Microwave Scanning Radiometer (AMSR2) in the C-through Ka-band frequency range for sea-ice contaminated ocean scenes. We show how this correlation can be employed to develop: (1) a discriminant analysis that is able to reliably flag the SMAP observations for sea-ice contamination and (2) subsequently remove the sea-ice contamination from the SMAP observations, which results in significantly more accurate SMAP SSS retrievals near the sea-ice edge. We provide a case study that evaluates the performance of the proposed sea-ice flagging and correction algorithm. Our method is also able to detect drifting icebergs, which go often undetected in many available standard sea-ice products and thus result in spurious SMAP SSS retrievals.


2021 ◽  
Vol 13 (24) ◽  
pp. 5014
Author(s):  
Dmitry Frey ◽  
Alexander Osadchiev

Satellite altimetry is an efficient instrument for detection dynamical processes in the World Ocean, including reconstruction of geostrophic currents and tracking of mesoscale eddies. Satellite altimetry has the potential to detect large river plumes, which have reduced salinity and, therefore, elevated surface level as compared to surrounding saline sea. In this study, we analyze applicability of satellite altimetry for detection of the Ob–Yenisei plume in the Kara Sea, which is among the largest river plumes in the World Ocean. Based on the extensive in situ data collected at the study area during oceanographic surveys in 2007–2019, we analyze the accuracy and efficiency of satellite altimetry in reproducing, first, the outer boundary of the plume and, second, the internal structure of the plume. We reveal that the value of positive level anomaly within the Ob–Yenisei plume strongly depends on the vertical plume structure and is prone to significant synoptic and seasonal variability due to wind forcing and mixing of the plume with subjacent sea. As a result, despite generally high statistical correlation between the ADT and surface salinity, straightforward usage of ADT for detection of the river plume is incorrect and produces misleading results. Satellite altimetry could provide correct information about spatial extents and shape of the Ob–Yenisei plume only if it is validated by synchronous in situ measurements.


2021 ◽  
Vol 944 (1) ◽  
pp. 012061
Author(s):  
A Chowdhury ◽  
A Naz ◽  
S Bhattacharyya ◽  
P Sanyal

Abstract Sundarban is the world’s largest transboundary contiguous mangrove ecosystem and home of the mangrove dwelling tigers. Sea level rise is destabilizing this ecosystem which is experiencing a rising salinity in surface and ground waters (shallow aquifer). In this study ground water salinity was investigated across Sundarbans and surface water seasonal salinity changes has been investigated along East-west gradient in the region. Statistically significant seasonal as well as spatial variations has been observed in the surface water salinity pattern across this gradient. The post monsoon average surface water salinity was 10.58 ppt while in pre-monsoon it was 27.31 ppt. Ground water salinity was lowest (0.95 ppt) in monsoon while highest in the pre-monsoon season (7.4 ppt). There was a clear east-west gradient in the surface salinity distribution across the delta, indicating a source of fresh water in the eastern corner, bordering Bangladesh. Increasing salinity indicate impact on mangrove diversity with salinity sensitive species (Heritiera fomes, Nypa fruticans) limited to the eastern corner while salinity resilient species (Avicennia marina and Phoenix paludosa) were dominating the western and central part of the Indian Sundarbans. Mangrove associate Acanthus ilicifolius and Heliotropium currasavicum were abundant in the forests under anthropogenic disturbances.


2021 ◽  
Vol 944 (1) ◽  
pp. 012068
Author(s):  
H Ramadhan ◽  
D Nugroho ◽  
I W Nurjaya ◽  
A S Atmadipoera

Abstract This study investigates the effect of river discharge in transport and tidal processes in the Java Sea using the Coastal and Regional Ocean Community (CROCO) hydrodynamic model. The model has 20 vertical layers and a horizontal resolution of 1/18 degrees. The oceanic and atmospheric forcing of this model is taken from the global Copernicus Marine Environment Monitoring Service (CMEMS) model and the fifth generation ECMWF atmospheric reanalysis (ERA5) hourly data. Daily Global Flood Awareness System (GloFAS) data has been successfully implemented as river flow data for this study. Two scenarios have been applied, namely, with and without river discharge. This study shows that the two scenarios and the satellite observational data agree in terms of water level with Root Mean Square Difference RMSD) about 4 cm, Sea Surface Temperature with RMSD about 0.29 °C, and Sea Surface Salinity with RMSD about 0.39 psu. The model was also validated using seven tide gauges and produced a good agreement. River discharge increase eastward transport in the eastern part of the Java Sea up to 0.1 Sv (1 Sv= 106 m3s−1). Both scenarios produce similar tidal amplitude and phase and agree well with previous studies and other tidal data sources.


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