Journal articles: 'Surface salinity'

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Lago, Véronique, Susan E. Wijffels, Paul J. Durack, John A. Church, Nathaniel L. Bindoff, and Simon J. Marsland. "Simulating the Role of Surface Forcing on Observed Multidecadal Upper-Ocean Salinity Changes." Journal of Climate 29, no. 15 (July 18, 2016): 5575–88. http://dx.doi.org/10.1175/jcli-d-15-0519.1.

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Abstract The ocean’s surface salinity field has changed over the observed record, driven by an intensification of the water cycle in response to global warming. However, the origin and causes of the coincident subsurface salinity changes are not fully understood. The relationship between imposed surface salinity and temperature changes and their corresponding subsurface changes is investigated using idealized ocean model experiments. The ocean’s surface has warmed by about 0.5°C (50 yr)−1 while the surface salinity pattern has amplified by about 8% per 50 years. The idealized experiments are constructed for a 50-yr period, allowing a qualitative comparison to the observed salinity and temperature changes previously reported. The comparison suggests that changes in both modeled surface salinity and temperature are required to replicate the three-dimensional pattern of observed salinity change. The results also show that the effects of surface changes in temperature and salinity act linearly on the changes in subsurface salinity. Surface salinity pattern amplification appears to be the leading driver of subsurface salinity change on depth surfaces; however, surface warming is also required to replicate the observed patterns of change on density surfaces. This is the result of isopycnal migration modified by the ocean surface warming, which produces significant salinity changes on density surfaces.

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Atkinson, Larry. "Surface Salinity, Visualization, CD-ROMs." Oceanography 8, no. 2 (1995): 42. http://dx.doi.org/10.5670/oceanog.1995.20.

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Kalangi, Patrice NI, Kawilarang WA Masengi, Masamitsu Iwata, Fransisco PT Pangalila, and Ixchel F. Mandagi. "PROFIL SALINITAS DAN SUHU DI TELUK MANADO PADA HARI-HARI HUJAN DAN TIDAK HUJAN." JURNAL PERIKANAN DAN KELAUTAN TROPIS 8, no. 3 (December 12, 2012): 95. http://dx.doi.org/10.35800/jpkt.8.3.2012.2443.

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Pengukuran salinitas dan suhu perairan dilakukan pada hari-hari hujan dan tidak hujan di dua tempat di perairan Teluk Manado, yang memiliki lima sungai utama di pinggirannya, untuk menyelidiki profil vertikal dari salinitas dan suhu, serta ketebalan air tawar. Profil salinitas dan suhu perairan pada hari yang sama di kedua tempat adalah mirip. Pada hari-hari hujan, salinitas rata-rata lapisan permukaan perairan adalah 33,9 lebih rendah 0,3 dibandingkan pada hari-hari tidak hujan. Salinitas permukaan ini setara dengan ketebalan lapisan air tawar sebesar 0,45 m. di lapisan permukaan, profil suhu cukup mirip. Akan tetapi, pada lapisan yang lebih dalam, suhu berosilasi pada fase yang berbeda dengan bertambahnya kedalaman. Kata kunci: ketebalan lapisan air tawar, termoklin, Bunaken. Salinity and temperature measurements were carried out on rainy days and non rainy days in two locations in Manado Bay, which is the outlet of fresh water masses from five main rivers, to investigate vertical profiles of salinity and temperature, and the thickness of the fresh water layer. Same day salinity and temperature profiles in both places is similar. On rainy days, the average salinity in the surface layer was 33.9, 0.3 lower than that of non rainy days. The surface salinity is equivalent to the thickness of the freshwater layer thickness of 0.45 m. In the surface layer, the temperature profile is quite similar. However, in the deeper layers, the temperature oscillates at different phases according to the increasing depths. Keywords: freshwater thickness, thermocline, Bunaken.

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Bryan, Frank, and Scott Bachman. "Isohaline Salinity Budget of the North Atlantic Salinity Maximum." Journal of Physical Oceanography 45, no. 3 (March 2015): 724–36. http://dx.doi.org/10.1175/jpo-d-14-0172.1.

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AbstractIn this study, the salinity budget of the North Atlantic subtropical salinity maximum region for control volumes bounded by isohaline surfaces is analyzed. The authors provide closed budgets based on output from a high-resolution numerical simulation and partial budgets based on analyses of observational climatologies of hydrography and surface fluxes. With this choice of control volume, advection is eliminated from the instantaneous volume-integrated salt budget, and time-mean advection is eliminated from the budget evaluated from time-averaged data. In this way, the role of irreversible mixing processes in the maintenance and variability of the salinity maximum are more readily revealed. By carrying out the analysis with both near-instantaneous and time-averaged model output, the role of mesoscale eddies in stirring and mixing for this water mass is determined. This study finds that the small-scale mixing acting on enhanced gradients generated by the mesoscale eddies is approximately equal to that acting on the large-scale gradients estimated from climatological-mean conditions. The isohaline salinity budget can be related to water mass transformation rates associated with surface forcing and mixing processes in a straightforward manner. The authors find that the surface net evaporation in the North Atlantic salinity maximum region accounts for a transformation of 7 Sverdrups (Sv; 1 Sv ≡ 106 m3 s−1) of water across the 37-psu isohaline outcrop into the salinity maximum in the simulation, whereas the estimate based on climatological observations is 9 to 10 Sv.

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Song, Y. Tony, Tong Lee, Jae-Hong Moon, Tangdong Qu, and Simon Yueh. "Modeling skin-layer salinity with an extended surface-salinity layer." Journal of Geophysical Research: Oceans 120, no. 2 (February 2015): 1079–95. http://dx.doi.org/10.1002/2014jc010346.

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Kalangi, Patrice NI, Anselun Mandagi, Kawilarang WA Masengi, Alfret Luasunaung, Fransisco PT Pangalila, and Masamitsu Iwata. "SEBARAN SUHU DAN SALINITAS DI TELUK MANADO." JURNAL PERIKANAN DAN KELAUTAN TROPIS 9, no. 2 (August 1, 2013): 70. http://dx.doi.org/10.35800/jpkt.9.2.2013.4179.

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Penelitian ini bertujuan untuk mendeskripsikan sebaran suhu dan salinitas di Teluk Manado, Sulawesi Utara. Pengukuran suhu dan salinitas secara vertikal dilakukan di delapan tempat di teluk. Profil vertikal suhu dan salinitas memperlihatkan keberadaan pelapisan kolom air. Secara horizontal, kontur suhu dan salinitas di permukaan memiliki dua “kolam” massa air, yakni kolam yang bersuhu tinggi tapi bersalinitas rendah di bagian timur teluk dan kolam yang bersuhu rendah tapi bersalinitas tinggi di bagian barat teluk. Pada lapisan dalam, kontur suhu dan salinitas cenderung sejajar dengan garis pantai bagian timur. Kata kunci: suhu, salinitas, air sungai, Teluk Manado. The objective of this research is to describe temperature and salinity distribution in Manado Bay, North Sulawesi. The vertical measurements of temperature and salinity were done at eight locations in the bay. The vertical profiles of temperature and salinity shows the existence of water column stratification. Horizontally, temperature and salinity contours of the surface layer have two pools, i.e. a pool of high temperature but low salinity in the eastern part of the bay and a pool of low temperature but high salinity in the western part of bay. In a deeper layer, the contours of temperature and salinity tend to be parallel to eastern coastline. Keywords: temperature, salinity, river discharge, Manado Bay.

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Reverdin, G., S. Morisset, J. Boutin, N. Martin, M. Sena-Martins, F. Gaillard, P. Blouch, et al. "Validation of Salinity Data from Surface Drifters." Journal of Atmospheric and Oceanic Technology 31, no. 4 (April 1, 2014): 967–83. http://dx.doi.org/10.1175/jtech-d-13-00158.1.

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Abstract Salinity measurements from 119 surface drifters in 2007–12 were assessed; 80% [Surface Velocity Program with a barometer with a salinity sensor (SVP-BS)] and 75% [SVP with salinity (SVP-S)] of the salinity data were found to be usable, after editing out some spikes. Sudden salinity jumps are found in drifter salinity records that are not always associated with temperature jumps, in particular in the wet tropics. A method is proposed to decide whether and how to correct those jumps, and the uncertainty in the correction applied. Northeast of South America, in a region influenced by the Amazon plume and fresh coastal water, drifter salinity is very variable, but a comparison with data from the Soil Moisture and Ocean Salinity satellite suggests that this variability is usually reasonable. The drifter salinity accuracy is then explored based on comparisons with data from Argo floats and from thermosalinographs (TSGs) of ships of opportunity. SVP-S/SVP-BS drifter records do not usually present significant biases within the first 6 months, but afterward biases sometimes need to be corrected (altogether, 16% of the SVP-BS records). Biases start earlier after 3 months for drifters not protected by antifouling paint. For the few drifters for which large corrections were applied to portions of the record, the accuracy cannot be proven to be better than 0.1 psu, and it cannot be proven to be better than 0.5 psu for data in the largest variability area off northeast South America. Elsewhere, after excluding portions of the records with suspicious salinity jumps or when large corrections were applied, the comparisons rule out average biases in individual drifter salinity record larger than 0.02 psu (midlatitudes) and 0.05 psu (tropics).

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Gordon, Arnold, Claudia Giulivi, Julius Busecke, and Frederick Bingham. "Differences Among Subtropical Surface Salinity Patterns." Oceanography 28, no. 1 (March 1, 2015): 32–39. http://dx.doi.org/10.5670/oceanog.2015.02.

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9

Kao, Hsun-Ying, Gary Lagerloef, Tong Lee, Oleg Melnichenko, Thomas Meissner, and Peter Hacker. "Assessment of Aquarius Sea Surface Salinity." Remote Sensing 10, no. 9 (August 22, 2018): 1341. http://dx.doi.org/10.3390/rs10091341.

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Aquarius was the first NASA satellite to observe the sea surface salinity (SSS) over the global ocean. The mission successfully collected data from 25 August 2011 to 7 June 2015. The Aquarius project released its final version (Version-5) of the SSS data product in December 2017. The purpose of this paper is to summarize the validation results from the Aquarius Validation Data System (AVDS) and other statistical methods, and to provide a general view of the Aquarius SSS quality to the users. The results demonstrate that Aquarius has met the mission target measurement accuracy requirement of 0.2 psu on monthly averages on 150 km scale. From the triple point analysis using Aquarius, in situ field and Hybrid Coordinate Ocean Model (HYCOM) products, the root mean square errors of Aquarius Level-2 and Level-3 data are estimated to be 0.17 psu and 0.13 psu, respectively. It is important that caution should be exercised when using Aquarius salinity data in areas with high radio frequency interference (RFI) and heavy rainfall, close to the coast lines where leakage of land signals may significantly affect the quality of the SSS data, and at high-latitude oceans where the L-band radiometer has poor sensitivity to SSS.

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10

Lagerloef, Gary. "Satellite mission monitors ocean surface salinity." Eos, Transactions American Geophysical Union 93, no. 25 (June 19, 2012): 233–34. http://dx.doi.org/10.1029/2012eo250001.

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11

Drushka, Kyla, William E. Asher, Janet Sprintall, Sarah T. Gille, and Clifford Hoang. "Global Patterns of Submesoscale Surface Salinity Variability." Journal of Physical Oceanography 49, no. 7 (July 2019): 1669–85. http://dx.doi.org/10.1175/jpo-d-19-0018.1.

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AbstractSurface salinity variability on O(1–10) km lateral scales (the submesoscale) generates density variability and thus has implications for submesoscale dynamics. Satellite salinity measurements represent a spatial average over horizontal scales of approximately 40–100 km but are compared to point measurements for validation, so submesoscale salinity variability also complicates validation of satellite salinities. Here, we combine several databases of historical thermosalinograph (TSG) measurements made from ships to globally characterize surface submesoscale salinity, temperature, and density variability. In river plumes; regions affected by ice melt or upwelling; and the Gulf Stream, South Atlantic, and Agulhas Currents, submesoscale surface salinity variability is large. In these regions, horizontal salinity variability appears to explain some of the differences between surface salinities from the Aquarius and SMOS satellites and salinities measured with Argo floats. In other words, apparent satellite errors in highly variable regions in fact arise because Argo point measurements do not represent spatially averaged satellite data. Salinity dominates over temperature in generating submesoscale surface density variability throughout the tropical rainbands, in river plumes, and in polar regions. Horizontal density fronts on 10-km scales tend to be compensated (salinity and temperature have opposing effects on density) throughout most of the global oceans, with the exception of the south Indian and southwest Pacific Oceans between 20° and 30°S, where fronts tend to be anticompensated.

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Buongiorno Nardelli, B., R. Droghei, and R. Santoleri. "Multi-dimensional interpolation of SMOS sea surface salinity with surface temperature and in situ salinity data." Remote Sensing of Environment 180 (July 2016): 392–402. http://dx.doi.org/10.1016/j.rse.2015.12.052.

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13

Bhaskar, Tata V. S. Udaya, and Chiranjivi Jayaram. "Evaluation of Aquarius Sea Surface Salinity With Argo Sea Surface Salinity in the Tropical Indian Ocean." IEEE Geoscience and Remote Sensing Letters 12, no. 6 (June 2015): 1292–96. http://dx.doi.org/10.1109/lgrs.2015.2393894.

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14

Mannshardt, Elizabeth, Katarina Sucic, Montserrat Fuentes, and Frederick M. Bingham. "Comparison of Distributional Statistics of Aquarius and Argo Sea Surface Salinity Measurements." Journal of Atmospheric and Oceanic Technology 33, no. 1 (January 2016): 103–18. http://dx.doi.org/10.1175/jtech-d-15-0068.1.

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AbstractSalinity is an indicator of the interaction between ocean circulation and the global water cycle, which in turn affects the regulation of the earth’s climate. To thoroughly understand sea surface salinity’s connection to processes that define the hydrological cycle, such as surface forcing and ocean mixing, there is need for proper validation of remotely sensed salinity products with independent measurements, beyond central tendencies, across the entire distribution of salinity. Because of its fine spatial and temporal coverage, Aquarius presents an ideal measurement system for fully characterizing the distribution and properties of sea surface salinity. Using the first 33 months of Aquarius, version 3.0, level 2 sea surface salinity data, both central tendencies and distributional quantile characteristics across time and space are investigated, and a statistical validation of Aquarius measurements with Argo in situ observations is conducted. Several aspects are considered, including regional characteristics and temporal agreement, as well as seasonal differences by ocean basin and hemisphere. Regional studies examine the time and space scales of variability through time series comparisons and an analysis of quantile properties. Results indicate that there are significant differences between the tails of their respective distributions, especially the lower tail. The Aquarius data show longer, fatter lower tails, indicating higher probability to sample low-salinity events. There is also evidence of differences in measurement variation between Aquarius and Argo. These results are seen across seasons, ocean basins, hemispheres, and regions.

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Durack, Paul J., and Susan E. Wijffels. "Fifty-Year Trends in Global Ocean Salinities and Their Relationship to Broad-Scale Warming." Journal of Climate 23, no. 16 (August 15, 2010): 4342–62. http://dx.doi.org/10.1175/2010jcli3377.1.

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Abstract Using over 1.6 million profiles of salinity, potential temperature, and neutral density from historical archives and the international Argo Program, this study develops the three-dimensional field of multidecadal linear change for ocean-state properties. The period of analysis extends from 1950 to 2008, taking care to minimize the aliasing associated with the seasonal and major global El Niño–Southern Oscillation modes. Large, robust, and spatially coherent multidecadal linear trends in salinity to 2000-dbar depth are found. Salinity increases at the sea surface are found in evaporation-dominated regions and freshening in precipitation-dominated regions, with the spatial pattern of change strongly resembling that of the mean salinity field, consistent with an amplification of the global hydrological cycle. Subsurface salinity changes on pressure surfaces are attributable to both isopycnal heave and real water-mass modification of the temperature–salinity relationship. Subduction and circulation by the ocean’s mean flow of surface salinity and temperature anomalies appear to account for most regional subsurface salinity changes on isopycnals. Broad-scale surface warming and the associated poleward migration of isopycnal outcrops drive a clear and repeating pattern of subsurface isopycnal salinity change in each independent ocean basin. Qualitatively, the observed global multidecadal salinity changes are thus consonant with both broad-scale surface warming and the amplification of the global hydrological cycle.

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Bao, Senliang, Ren Zhang, Huizan Wang, Hengqian Yan, Yang Yu, and Jian Chen. "Salinity Profile Estimation in the Pacific Ocean from Satellite Surface Salinity Observations." Journal of Atmospheric and Oceanic Technology 36, no. 1 (January 2019): 53–68. http://dx.doi.org/10.1175/jtech-d-17-0226.1.

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AbstractA nonlinear empirical method, called the generalized regression neural network with the fruit fly optimization algorithm (FOAGRNN), is proposed to estimate subsurface salinity profiles from sea surface parameters in the Pacific Ocean. The purpose is to evaluate the ability of the FOAGRNN methodology and satellite salinity data to reconstruct salinity profiles. Compared with linear methodology, the estimated salinity profiles from the FOAGRNN method are in better agreement with the measured profiles at the halocline. Sensitivity studies of the FOAGRNN estimation model shows that, when applied to various types of sea surface parameters, latitude is the most significant variable in estimating salinity profiles in the tropical Pacific Ocean (correlation coefficient R greater than 0.9). In comparison, sea surface temperature (SST) and height (SSH) have minimal effects on the model. Based on FOAGRNN modeling, Pacific Ocean three-dimensional salinity fields are estimated for the year 2014 from remote sensing sea surface salinity (SSS) data. The performance of the satellite-based salinity field results and possible sources of error associated with the estimation methodology are briefly discussed. These results suggest a potential new approach for salinity profile estimation derived from sea surface data. In addition, the potential utilization of satellite SSS data is discussed.

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Reagan, James, Tim Boyer, John Antonov, and Melissa Zweng. "Comparison analysis between Aquarius sea surface salinity and World Ocean Database in situ analyzed sea surface salinity." Journal of Geophysical Research: Oceans 119, no. 11 (November 2014): 8122–40. http://dx.doi.org/10.1002/2014jc009961.

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18

Ono, Nobuo, and Takashi Kasai. "Surface Layer Salinity of Young Sea Ice." Annals of Glaciology 6 (1985): 298–99. http://dx.doi.org/10.3189/1985aog6-1-298-299.

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The high-salinity surface layer of young sea ice was subjected to field and laboratory experiments. Artificial pools, in which young ice was formed, were opened within a fast-ice sheet in the Saroma lagoon, Hokkaido, in February of 1983 and 1984. The salinity of 1 mm thick surface layer of the young ice was observed as high as 42.4‰, which exceeds the seawater salinity of 31‰. The surface salinity increased with rising surface temperature. When a load was placed on the fast ice near the pool, seeped brine of salinity 72.5‰ was observed on the surface of the young ice; and when the load was removed, the brine disappeared. Meanwhile, brine permeabilities, both upward and downward, were measured in the laboratory, Both permeabilities decreased logarithmically with lowering surface temperature. A remarkable anisotropy was observed: the upward permeability was greater than downward, and the ratio of upward to downward premeability increased with lowering surface temperature from 5 at -3 °C to 33 at -5°C. Upward and downward permeabilities in ms-1 were respectively 1x10-4 and 2x10-5 at -3°C, 2x10-5 and 6x10-7 at -5°C, and at -10°C upward permeability was 3x10-7.

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Ono, Nobuo, and Takashi Kasai. "Surface Layer Salinity of Young Sea Ice." Annals of Glaciology 6 (1985): 298–99. http://dx.doi.org/10.1017/s0260305500010697.

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The high-salinity surface layer of young sea ice was subjected to field and laboratory experiments. Artificial pools, in which young ice was formed, were opened within a fast-ice sheet in the Saroma lagoon, Hokkaido, in February of 1983 and 1984. The salinity of 1 mm thick surface layer of the young ice was observed as high as 42.4‰, which exceeds the seawater salinity of 31‰. The surface salinity increased with rising surface temperature. When a load was placed on the fast ice near the pool, seeped brine of salinity 72.5‰ was observed on the surface of the young ice; and when the load was removed, the brine disappeared. Meanwhile, brine permeabilities, both upward and downward, were measured in the laboratory, Both permeabilities decreased logarithmically with lowering surface temperature. A remarkable anisotropy was observed: the upward permeability was greater than downward, and the ratio of upward to downward premeability increased with lowering surface temperature from 5 at -3 °C to 33 at -5°C. Upward and downward permeabilities in ms-1 were respectively 1x10-4 and 2x10-5 at -3°C, 2x10-5 and 6x10-7 at -5°C, and at -10°C upward permeability was 3x10-7.

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Sun, Jingru, Gabriel Vecchi, and Brian Soden. "Sea Surface Salinity Response to Tropical Cyclones Based on Satellite Observations." Remote Sensing 13, no. 3 (January 26, 2021): 420. http://dx.doi.org/10.3390/rs13030420.

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Multi-year records of satellite remote sensing of sea surface salinity (SSS) provide an opportunity to investigate the climatological characteristics of the SSS response to tropical cyclones (TCs). In this study, the influence of TC winds, rainfall and preexisting ocean stratification on SSS evolution is examined with multiple satellite-based and in-situ data. Global storm-centered composites indicate that TCs act to initially freshen the ocean surface (due to precipitation), and subsequently salinify the surface, largely through vertical ocean processes (mixing and upwelling), although regional hydrography can lead to local departure from this behavior. On average, on the day a TC passes, a strong SSS decrease is observed. The fresh anomaly is subsequently replaced by a net surface salinification, which persists for weeks. This salinification is larger on the right (left)-hand side of the storm motion in the Northern (Southern) Hemisphere, consistent with the location of stronger turbulent mixing. The influence of TC intensity and translation speed on the ocean response is also examined. Despite having greater precipitation, stronger TCs tend to produce longer-lasting, stronger and deeper salinification especially on the right-hand side of the storm motion. Faster moving TCs are found to have slightly weaker freshening with larger area coverage during the passage, but comparable salinification after the passage. The ocean haline response in four basins with different climatological salinity stratification reveals a significant impact of vertical stratification on the salinity response during and after the passage of TCs.

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Yan, Youfang, Eric P. Chassignet, Yiquan Qi, and William K. Dewar. "Freshening of Subsurface Waters in the Northwest Pacific Subtropical Gyre: Observations and Dynamics." Journal of Physical Oceanography 43, no. 12 (December 1, 2013): 2733–51. http://dx.doi.org/10.1175/jpo-d-13-03.1.

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Abstract Subsurface salinity anomalies propagating between mid- and low latitudes along isopycnal surfaces have been shown to play an important role in modulating ocean and climate variability. In this study, a sustained freshening and southwestward propagation of subsurface salinity anomalies in the northwest Pacific subtropical gyre and its dynamical mechanism are investigated using observations, numerical outputs, and a predictive model. Analyses of the observations show a pronounced subsurface freshening with salinity decreasing about 0.25 PSU near the 24.5-σθ surface in the northwest Pacific subtropical gyre during 2003–11. This freshening is found to be related to the surface forcing of salinity anomalies in the outcrop zone (25°–35°N, 130°–160°E). A predictive model based on the assumption of salinity conservation along the outcrop isopycnals is derived and used to examine this surface-forcing mechanism. The resemblance between the spatial structures of the subsurface salinity derived from the predictive model and from observations and numerical outputs suggests that subsurface salinity anomalies are ventilated over the outcrop zone. A salinity anomaly with an amplitude of about 0.25 PSU generated by the surface forcing is subducted in the outcrop zone and then propagates southwestward, accompanied by potential vorticity anomalies, to the east of Luzon Strait (~15°N) in roughly one year. When the anomalies reach 15°N, they turn and move gradually eastward toward the central Pacific, associated with an eastward countercurrent on the southern subtropical gyre.

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Boutin, J., N. Martin, N. Kolodziejczyk, and G. Reverdin. "Interannual anomalies of SMOS sea surface salinity." Remote Sensing of Environment 180 (July 2016): 128–36. http://dx.doi.org/10.1016/j.rse.2016.02.053.

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Boyer, Tim P., and Sydney Levitus. "Harmonic analysis of climatological sea surface salinity." Journal of Geophysical Research: Oceans 107, no. C12 (October 16, 2002): SRF 7–1—SRF 7–14. http://dx.doi.org/10.1029/2001jc000829.

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Supply, A., J. Boutin, J. ‐L Vergely, N. Martin, A. Hasson, G. Reverdin, C. Mallet, and N. Viltard. "Precipitation Estimates from SMOS Sea‐Surface Salinity." Quarterly Journal of the Royal Meteorological Society 144, S1 (August 7, 2017): 103–19. http://dx.doi.org/10.1002/qj.3110.

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Grodsky, Semyon A., Nicolas Reul, Bertrand Chapron, James A. Carton, and Frank O. Bryan. "Interannual surface salinity on Northwest Atlantic shelf." Journal of Geophysical Research: Oceans 122, no. 5 (May 2017): 3638–59. http://dx.doi.org/10.1002/2016jc012580.

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Yu, Lisan. "Sea‐surface salinity fronts and associated salinity‐minimum zones in the tropical ocean." Journal of Geophysical Research: Oceans 120, no. 6 (June 2015): 4205–25. http://dx.doi.org/10.1002/2015jc010790.

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Meissner, Thomas, Frank J. Wentz, and David M. Le Vine. "The Salinity Retrieval Algorithms for the NASA Aquarius Version 5 and SMAP Version 3 Releases." Remote Sensing 10, no. 7 (July 15, 2018): 1121. http://dx.doi.org/10.3390/rs10071121.

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The Aquarius end-of-mission (Version 5) salinity data set was released in December 2017. This article gives a comprehensive overview of the main steps of the Level 2 salinity retrieval algorithm. In particular, we will discuss the corrections for wind induced surface roughness, atmospheric oxygen absorption, reflected galactic radiation and side-lobe intrusion from land surfaces. Most of these corrections have undergone major updates from previous versions, which has helped mitigating temporal and zonal biases. Our article also discusses the ocean target calibration for Aquarius Version 5. We show how formal error estimates for the Aquarius retrievals can be obtained by perturbing the input to the algorithm. The performance of the Aquarius Version 5 salinity retrievals is evaluated against salinity measurements from the ARGO network and the HYCOM model. When stratified as function of sea surface temperature or sea surface wind speed, the difference between Aquarius Version 5 and ARGO is within ±0.1 psu. The estimated global RMS uncertainty for monthly 100 km averages is 0.128 psu for the Aquarius Version 5 retrievals. Finally, we show how the Aquarius Version 5 salinity retrieval algorithm is adapted to retrieve salinity from the Soil-Moisture Active Passion (SMAP) mission.

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Hieronymus, Magnus, Johan Nilsson, and Jonas Nycander. "Water Mass Transformation in Salinity–Temperature Space." Journal of Physical Oceanography 44, no. 9 (September 1, 2014): 2547–68. http://dx.doi.org/10.1175/jpo-d-13-0257.1.

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Abstract This article presents a new framework for studying water mass transformations in salinity–temperature space that can, with equal ease, be applied to study water mass transformation in spaces defined by any two conservative tracers. It is shown how the flow across isothermal and isohaline surfaces in the ocean can be quantified from knowledge of the nonadvective fluxes of heat and salt. It is also shown how these cross-isothermal and cross-isohaline flows can be used to form a continuity equation in salinity–temperature space. These flows are then quantified in a state-of-the-art ocean model. Two major transformation cells are found: a tropical cell driven primarily by surface fluxes and dianeutral diffusion and a conveyor belt cell where isoneutral diffusion is also important. Both cells are similar to cells found in earlier work on the thermohaline streamfunction. A key benefit with this framework over a streamfunction approach is that transformation due to different diabatic processes can be studied individually. The distributions of volume and surface area in S–T space are found to be useful for determining how transformations due to these different processes affect the water masses in the model. The surface area distribution shows that the water mass transformations due to surface fluxes tend to be directed away from S–T regions that occupy large areas at the sea surface.

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Boutin, J., Y. Chao, W. E. Asher, T. Delcroix, R. Drucker, K. Drushka, N. Kolodziejczyk, et al. "Satellite and In Situ Salinity: Understanding Near-Surface Stratification and Subfootprint Variability." Bulletin of the American Meteorological Society 97, no. 8 (August 1, 2016): 1391–407. http://dx.doi.org/10.1175/bams-d-15-00032.1.

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Abstract Remote sensing of salinity using satellite-mounted microwave radiometers provides new perspectives for studying ocean dynamics and the global hydrological cycle. Calibration and validation of these measurements is challenging because satellite and in situ methods measure salinity differently. Microwave radiometers measure the salinity in the top few centimeters of the ocean, whereas most in situ observations are reported below a depth of a few meters. Additionally, satellites measure salinity as a spatial average over an area of about 100 × 100 km2. In contrast, in situ sensors provide pointwise measurements at the location of the sensor. Thus, the presence of vertical gradients in, and horizontal variability of, sea surface salinity complicates comparison of satellite and in situ measurements. This paper synthesizes present knowledge of the magnitude and the processes that contribute to the formation and evolution of vertical and horizontal variability in near-surface salinity. Rainfall, freshwater plumes, and evaporation can generate vertical gradients of salinity, and in some cases these gradients can be large enough to affect validation of satellite measurements. Similarly, mesoscale to submesoscale processes can lead to horizontal variability that can also affect comparisons of satellite data to in situ data. Comparisons between satellite and in situ salinity measurements must take into account both vertical stratification and horizontal variability.

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30

Guan, Bin, Tong Lee, Daria J. Halkides, and Duane E. Waliser. "Aquarius surface salinity and the Madden-Julian Oscillation: The role of salinity in surface layer density and potential energy." Geophysical Research Letters 41, no. 8 (April 17, 2014): 2858–69. http://dx.doi.org/10.1002/2014gl059704.

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Aretxabaleta, A. L., K. W. Smith, and J. Ballabrera-Poy. "Regime changes in global sea surface salinity trend." Ocean Science Discussions 12, no. 3 (June 3, 2015): 983–1011. http://dx.doi.org/10.5194/osd-12-983-2015.

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Abstract. Recent studies have shown significant sea surface salinity (SSS) changes at scales ranging from regional to global. In this study, we estimate global salinity means and trends using historical (1950–2014) SSS data from the UK Met. Office Hadley Centre objectively analyzed monthly fields and recent data from the SMOS satellite (2010–2014). We separate the different components (regimes) of the global surface salinity by fitting a Gaussian Mixture Model to the data and using Expectation–Maximization to distinguish the means and trends of the data. The procedure uses a non-subjective method (Bayesian Information Criterion) to extract the optimal number of means and trends. The results show the presence of three separate regimes: Regime A (1950–1990) is characterized by small trend magnitudes; Regime B (1990–2009) exhibited enhanced trends; and Regime C (2009–2014) with significantly larger trend magnitudes. The salinity differences between regime means were around 0.01. The trend acceleration could be related to an enhanced global hydrological cycle or to a change in the sampling methodology.

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Shoup, Casey G., Bulusu Subrahmanyam, and Heather L. Roman‐Stork. "Madden‐Julian Oscillation‐Induced Sea Surface Salinity Variability as Detected in Satellite‐Derived Salinity." Geophysical Research Letters 46, no. 16 (August 19, 2019): 9748–56. http://dx.doi.org/10.1029/2019gl083694.

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Nilsson, Johan, and Heiner Körnich. "A Conceptual Model of the Surface Salinity Distribution in the Oceanic Hadley Cell." Journal of Climate 21, no. 24 (December 15, 2008): 6586–98. http://dx.doi.org/10.1175/2008jcli2284.1.

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Abstract A conceptual model of the salinity distribution in the oceanic Hadley cell is presented. The model pertains to the region of tropical easterly surface winds, where the surface salinity increases poleward from a local salinity minimum near the equator to a subtropical salinity maximum. A fundamental constraint is that the meridional freshwater transports in the atmosphere and the ocean have the same magnitude but opposite directions. A key assumption is that the strength of the meridional overturning cells in the atmosphere and the ocean is proportional and set by the surface layer Ekman transport. It is further assumed that, to the lowest order of approximation, the zonal-mean Ekman transports accomplish the meridional freshwater transports, that is, eddy fluxes and gyre-induced transports are ignored. The model predicts that the salinity variation in the oceanic cell is directly proportional to the specific humidity of the near-surface air, but independent of the meridional mass transport (as long as the atmospheric and oceanic mass transports remain proportional). If the relative humidity of the near-surface air is constant, the salinity variation in the oceanic Hadley cell varies essentially with the surface temperature according to the Clausius–Clapeyron expression for the saturation vapor pressure. Further, the model is compared to observations and a global warming simulation and found to give a leading-order description of the tropical surface salinity range.

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Cherniavskaia, Ekaterina A., Ivan Sudakov, Kenneth M. Golden, Courtenay Strong, and Leonid A. Timokhov. "Observed winter salinity fields in the surface layer of the Arctic Ocean and statistical approaches to predicting large-scale anomalies and patterns." Annals of Glaciology 59, no. 76pt2 (April 23, 2018): 83–100. http://dx.doi.org/10.1017/aog.2018.10.

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AbstractSignificant salinity anomalies have been observed in the Arctic Ocean surface layer during the last decade. Our study is based on an extensive gridded dataset of winter salinity in the upper 50 m layer of the Arctic Ocean for the periods 1950–1993 and 2007–2012, obtained from ~20 000 profiles. We investigate the interannual variability of the salinity fields, identify predominant patterns of anomalous behavior and leading modes of variability, and develop a statistical model for the prediction of surface-layer salinity. The statistical model is based on linear regression equations linking the principal components of surface-layer salinity obtained through empirical orthogonal function decomposition with environmental factors, such as atmospheric circulation, river runoff, ice processes and water exchange with neighboring oceans. Using this model, we obtain prognostic fields of the surface-layer salinity for the winter period 2013–2014. The prognostic fields generated by the model show tendencies of surface-layer salinification, which were also observed in previous years. Although the used data are proprietary and have gaps, they provide the most spatiotemporally detailed observational resource for studying multidecadal variations in basin-wide Arctic salinity. Thus, there is community value in the identification, dissemination and modeling of the principal modes of variability in this salinity record.

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Mu, Ziyao, Weimin Zhang, Pinqiang Wang, Huizan Wang, and Xiaofeng Yang. "Assimilation of SMOS Sea Surface Salinity in the Regional Ocean Model for South China Sea." Remote Sensing 11, no. 8 (April 16, 2019): 919. http://dx.doi.org/10.3390/rs11080919.

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Ocean salinity has an important impact on marine environment simulations. The Soil Moisture and Ocean Salinity (SMOS) mission is the first satellite in the world to provide large-scale global salinity observations of the oceans. Salinity remote sensing observations in the open ocean have been successfully applied in data assimilations, while SMOS salinity observations contain large errors in the coastal ocean (including the South China Sea (SCS)) and high latitudes and cannot be effectively applied in ocean data assimilations. In this paper, the SMOS salinity observation data are corrected with the Generalized Regression Neural Network (GRNN) in data assimilation preprocessing, which shows that after correction, the bias and root mean square error (RMSE) of the SMOS sea surface salinity (SSS) compared with the Argo observations can be reduced from 0.155 PSU and 0.415 PSU to −0.003 PSU and 0.112 PSU, respectively, in the South China Sea. The effect is equally significant in the northwestern Pacific region. The preprocessed salinity data were applied to an assimilation in a coastal region for the first time. The six groups of assimilation experiments set in the South China Sea showed that the assimilation of corrected SMOS SSS can effectively improve the upper ocean salinity simulation.

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Vinogradova, Nadya T., and Rui M. Ponte. "Assessing Temporal Aliasing in Satellite-Based Surface Salinity Measurements." Journal of Atmospheric and Oceanic Technology 29, no. 9 (September 1, 2012): 1391–400. http://dx.doi.org/10.1175/jtech-d-11-00055.1.

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Abstract The Aquarius/Satelite de Aplicaciones Cientificas-D (SAC-D) salinity remote sensing mission is intended to provide global mapping of sea surface salinity (SSS) fields over the next few years. Temporal and spatial averages of the satellite salinity retrievals produce monthly mean fields on 1° grids with target accuracies of 0.2 psu. One issue of relevance for the satellite-derived products is the potential for temporal aliasing of rapid fluctuations into the climate (monthly averaged) values of interest. Global daily SSS fields from a data-assimilating, eddy-resolving Hybrid Coordinate Ocean Model (HYCOM) solution are used to evaluate whether the potential aliasing error is large enough to affect the accuracy of the SSS retrievals. For comparison, salinity data collected at a few in situ stations over the tropical oceans are also used. Based on the HYCOM daily series, over many oceanic regions, a significant part of the total salinity variability is contributed by rapid fluctuations at periods aliased in the satellite retrievals. Estimates of the implicit aliasing error in monthly mean salinity estimates amount to 0.02 psu on average and >0.1 psu in some coastal, tropical, western boundary current, and Arctic regions. Comparison with in situ measurements suggests that HYCOM can underestimate the effect at some locations. While local aliased variance can be significant, the estimated impact of aliasing noise on the overall Aquarius system noise is negligible on average, when combined with effects of other instrument and geophysical errors. Effects of aliased variance are strongest at the shortest periods (<6 months) and become negligible at the annual period.

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Qu, Ke, Shengchun Piao, Jianbo Zhou, and Fengqin Zhu. "Analysis of Surface Sound Duct in the Northern Shelf of the South China Sea." Shock and Vibration 2018 (2018): 1–12. http://dx.doi.org/10.1155/2018/2409761.

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The northern shelf of the South China Sea (NSSCS) is characterized by surface low-salinity water due to discharge from the Pearl River. In such an environment, the surface sound duct (SSD) is the most important duct for near-surface sonar applications. Nevertheless, the mechanism of SSD formation is very complicated and is influenced by salinity, temperature at the air-sea interface, and various additional marine phenomena. In this study, an 8-year conductivity-temperature-depth (CTD) profile of the NSSCS was used to analyze the SSD formation. An advanced diagrammatic method is proposed to provide a quantitative analysis of the contribution of salinity, temperature, and hydrostatic pressure on SSD formation. Large salinity gradient (0.25 psu/m) was shown to play a crucial role in SSD formation when a mixed layer exists. As representative examples, the sea under cold surges, typhoon genesis, and low-salinity lenses were studied. Conversely, the absence of SSDs in low-salinity water was also observed in upwelling regions. This study further showed that highly negative temperature gradients affect SSD formation even in low-salinity water. Furthermore, although the duct depth of a low-salinity SSD is usually less than 10 meters, it still can serve as an effective duct for acoustic propagation.

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38

Lagerloef, Gary, Calvin Swift, and David Le Vine. "Sea Surface Salinity: The Next Remote Sensing Challenge." Oceanography 8, no. 2 (1995): 44–50. http://dx.doi.org/10.5670/oceanog.1995.17.

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Drushka, Kyla, William Asher, Andrew Jessup, Elizabeth Thompson, Suneil Iyer, and Dan Clark. "Capturing Fresh Layers with the Surface Salinity Profiler." Oceanography 32, no. 2 (June 1, 2019): 76–85. http://dx.doi.org/10.5670/oceanog.2019.215.

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Aretxabaleta, Alfredo, Keston Smith, and Tarandeep Kalra. "Regime Changes in Global Sea Surface Salinity Trend." Journal of Marine Science and Engineering 5, no. 4 (November 27, 2017): 57. http://dx.doi.org/10.3390/jmse5040057.

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41

Sévellec, Florian, Mahdi Ben Jelloul, and Thierry Huck. "Optimal Surface Salinity Perturbations Influencing the Thermohaline Circulation." Journal of Physical Oceanography 37, no. 12 (December 1, 2007): 2789–808. http://dx.doi.org/10.1175/2007jpo3680.1.

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Abstract Optimal surface salinity perturbations influencing the meridional overturning circulation maximum are exhibited and interpreted on a stable steady state of a 2D latitude–depth ocean thermohaline circulation model. Despite the stability of the steady state, the nonnormality of the dynamics is able to create some transient growth and variability through stimulation by optimal perturbations. Two different measures are compared to obtain the optimum—one associated with the departure from steady state in terms of density, and the other with the overturning circulation intensity. It is found that such optimal analysis is measure dependent; hence, the latter measure is chosen for studying the following physical mechanisms. The response to the optimal initial sea surface salinity perturbation involves a transient growth mechanism leading to a maximum modification of the circulation intensity after 67 yr; the amplification is linked to the most weakly damped linear eigenmode, oscillating on a 150-yr period. Optimal constant surface salinity flux perturbations are also obtained, and confirm that a decrease in the freshwater flux amplitude enhances the circulation intensity. At last, looking for the optimal stochastic surface salinity flux perturbation, it is established that the variance of the circulation intensity is controlled by the weakly damped 150-yr oscillation. Two approaches are tested to consider extending such studies in more realistic 3D models. Explicit solutions (versus eigenvalue problems) are found for the overturning circulation measure (except for the stochastic optimal); a truncation method on a few leading eigenmodes usually provides the optimal perturbations for analyses on long time scales.

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42

Bingham, Frederick M., Stephan D. Howden, and Chester J. Koblinsky. "Sea surface salinity measurements in the historical database." Journal of Geophysical Research: Oceans 107, no. C12 (December 2002): SRF 20–1—SRF 20–10. http://dx.doi.org/10.1029/2000jc000767.

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Asher, William E., Andrew T. Jessup, Ruth Branch, and Dan Clark. "Observations of rain-induced near-surface salinity anomalies." Journal of Geophysical Research: Oceans 119, no. 8 (August 2014): 5483–500. http://dx.doi.org/10.1002/2014jc009954.

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44

Yin, Xiaobin, Jacqueline Boutin, Gilles Reverdin, Tong Lee, Sabine Arnault, and Nicolas Martin. "SMOSSea Surface Salinity signals of tropical instability waves." Journal of Geophysical Research: Oceans 119, no. 11 (November 2014): 7811–26. http://dx.doi.org/10.1002/2014jc009960.

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45

Abe, Hiroto, and Naoto Ebuchi. "Evaluation of sea-surface salinity observed by Aquarius." Journal of Geophysical Research: Oceans 119, no. 11 (November 2014): 8109–21. http://dx.doi.org/10.1002/2014jc010094.

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46

Santos-Garcia, Andrea, Maria Marta Jacob, and W. Linwood Jones. "SMOS Near-Surface Salinity Stratification Under Rainy Conditions." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 9, no. 6 (June 2016): 2493–99. http://dx.doi.org/10.1109/jstars.2016.2527038.

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47

Valjarević, Aleksandar, Dejan Filipović, Miško Milanović, and Dragana Valjarević. "New Updated World Maps of Sea-Surface Salinity." Pure and Applied Geophysics 177, no. 6 (January 15, 2020): 2977–92. http://dx.doi.org/10.1007/s00024-019-02404-z.

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Rathore, Saurabh, Nathaniel L. Bindoff, Caroline C. Ummenhofer, Helen E. Phillips, Ming Feng, and Mayank Mishra. "Improving Australian Rainfall Prediction Using Sea Surface Salinity." Journal of Climate 34, no. 7 (April 2021): 2473–90. http://dx.doi.org/10.1175/jcli-d-20-0625.1.

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AbstractThis study uses sea surface salinity (SSS) as an additional precursor for improving the prediction of summer [December–February (DJF)] rainfall over northeastern Australia. From a singular value decomposition between SSS of prior seasons and DJF rainfall, we note that SSS of the Indo-Pacific warm pool region [SSSP (150°E–165°W and 10°S–10°N) and SSSI (50°–95°E and 10°S–10°N)] covaries with Australian rainfall, particularly in the northeast region. Composite analysis that is based on high or low SSS events in the SSSP and SSSI regions is performed to understand the physical links between the SSS and the atmospheric moisture originating from the regions of anomalously high or low, respectively, SSS and precipitation over Australia. The composites show the signature of co-occurring La Niña and negative Indian Ocean dipole with anomalously wet conditions over Australia and conversely show the signature of co-occurring El Niño and positive Indian Ocean dipole with anomalously dry conditions there. During the high SSS events of the SSSP and SSSI regions, the convergence of incoming moisture flux results in anomalously wet conditions over Australia with a positive soil moisture anomaly. Conversely, during the low SSS events of the SSSP and SSSI regions, the divergence of incoming moisture flux results in anomalously dry conditions over Australia with a negative soil moisture anomaly. We show from the random-forest regression analysis that the local soil moisture, El Niño–Southern Oscillation (ENSO), and SSSP are the most important precursors for the northeast Australian rainfall whereas for the Brisbane region ENSO, SSSP, and the Indian Ocean dipole are the most important. The prediction of Australian rainfall using random-forest regression shows an improvement by including SSS from the prior season. This evidence suggests that sustained observations of SSS can improve the monitoring of the Australian regional hydrological cycle.

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Amri, Khairul. "ANALISIS HUBUNGAN KONDISI OSEANOGRAFI DENGAN FLUKTUASI HASIL TANGKAPAN IKAN PELAGIS DI SELAT SUNDA." Jurnal Penelitian Perikanan Indonesia 14, no. 1 (February 6, 2017): 55. http://dx.doi.org/10.15578/jppi.14.1.2008.55-65.

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Tujuan riset ini adalah mengkaji hubungan antara kondisi oseanografi musiman (sebaran suhu permukaan laut, konsentrasi klorofil-a, pola arus, dan salinitas hasil pengukuran in situ dan data penginderaan jauh multi temporal tahun 2000, 2001, 2002, dan 2004) dengan hasil tangkapan ikan pelagis. Analisis dilakukan secara visual dan digital untuk mendapatkan gambaran dinamik kondisi oseanografi musiman perairan Selat Sunda. Hasil menunjukkan, nilai sebaran suhu permukaan laut Selat Sunda bervariasi sepanjang tahun, berkisar 27,0 sampai dengan 30,5°C. Salinitas berkisar 31,0 sampai dengan 33,7‰ dengan nilai terendah (31,0‰) pada musim barat sementara salinitas tertinggi (32,7 sampai dengan 33,7‰) ditemukan pada musim peralihan 2. Sebaran klorofil-a berkisar 0,1 sampai dengan 2,0 mg m 3. Musim barat merupakan musim dengan kandungan klorofil-a terendah (0,1 mg m-3) dan musim timur merupakan musim dengan tingkat kesuburan tertinggi (1,5 sampai dengan 2,0 mg m-3). Diduga peningkatan produktivitas primer yang sangat tinggi pada musim timur, selain akibat aliran massa air yang kaya nutrien dari Laut Jawa juga akibat upwelling pada mulut selat bagian selatan. Terdapat korelasi yang kuat antara peningkatan kosentrasi kesuburan perairan (klorofil-a tinggi 1,0 sampai dengan 1,5 mg m-3) akibat terjadi upwelling pada musim timur yang didukung oleh kondisi suhu permukaan laut hangat (29,0 sampai dengan 30,5°C) dan salinitas tinggi (32,7 sampai dengan 33,7‰) dengan diikuti peningkatan hasil tangkapan ikan. The current research aims to study the dynamic of the seasonal oceanography condition (sea surface temperature, chlorophyll-a concentration, sea surface height anomaly, and salinity by using in situ data and satellite multi temporal images until 2000, 2001, 2002, and 2004) in the Sunda Straits waters. The oceanographic data were analyzed by using visual and digital analyze to find the dynamic features. Results show that sea surface temperature was fluctuated with seasons. The values ranging from 27.0 to 30.5°C were higher than in situ measurement. The Surface salinity varied fluctuated from 31.0 to 33.7‰. Lower salinity (31.0‰) was found on the west monsoon, higher salinity (33.7‰) on the inter monsoon 2. The Concentration of chlorophyll-a ranged between 0.1 to 2.0 mg m-3 of which high abundance occurred with east monsoon. The high concentration of chlorophyll-a in east monsoon might be correlated to the nutrient transport impact from Java Sea and also contribution of upwelling process in southern mouth of Sunda Strait. The result shows that the catch of pelagic fish had strong linear correlation with the primery productivity (chlorophyll-a with high abundance 1.0 to 1.5 mg m-3) on upwelling process in east monsoon near south mouth of Sunda Straits with suported by warm water mass (sea surface temperature 29.0 to 30.5°C) and high salinity (32.7 to 33.7‰).

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Le Vine, David M., and Emmanuel P. Dinnat. "The Multifrequency Future for Remote Sensing of Sea Surface Salinity from Space." Remote Sensing 12, no. 9 (April 27, 2020): 1381. http://dx.doi.org/10.3390/rs12091381.

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Passive microwave remote sensing of sea surface salinity from space is done with measurements in the 27 MHz wide spectral window at 1.413 GHz (L-band) which is protected for passive use only. The frequency, 1.413 GHz, is near the peak in sensitivity to changes in salinity and modern L-band instruments, such as the radiometers on SMOS and Aquarius, have demonstrated the feasibility of monitoring surface salinity from space. They have also demonstrated the need for better accuracy, especially in cold water. Proposals to improve accuracy have largely involved adding more frequencies. For example, adding higher frequencies to improve the correction for sea surface temperature and lower frequencies to improve the sensitivity to salinity in cold water. These strategies involve trade-offs, some obvious such as the effects of interference outside the protected band and loss of spatial resolution at lower frequencies, but some are more subtle because of the interdependence of the measurement on other parameters of the ocean surface, in particular, the interdependence of salinity, water temperature and roughness (wind speed). The objective of this manuscript is to describe these interdependencies in a quantitative way with documented assumptions to support the design of future instruments for remote sensing of salinity.

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Journal articles on the topic 'Surface salinity'

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