Interannual Sea Surface Salinity Research Articles

Impact of river-discharged freshwater on surface ocean environments revealed by synergistic use of satellite measurements in the East China Sea

River discharge forms a plume of low-salinity water that spreads offshore, delivering terrestrial substances into the ocean and thus plays a critical role in controlling marine environments as well as the carbon cycle. This study investigated how freshwater discharged from the Changjiang impacts the physical and biological responses and oceanic uptake of carbon dioxide (CO2) in the northern East China Sea (ECS) by combining the recently available sea surface salinity (SSS) product from the Soil Moisture Active Passive (SMAP) mission with other satellite measurements of sea surface temperature (SST) and chlorophyll-a (chl-a) concentration. The partial pressure of CO2 (pCO2) and its interannual variability were estimated using empirical regression with satellite-derived environmental variables. The bias-corrected SMAP SSS revealed that river discharge largely contributed to the distinct interannual SSS variations, with a seasonal cycle reaching a maximum in winter and a minimum in summer. Compared to the SST and chl-a anomalies, we observed an increase in SST and primary production in the region where sea surface freshening was robust. Freshwater from rivers contributes to sea surface warming by trapping heat from the atmosphere at the surface layer. Nutrient-enriched freshwater within the buoyant plume enhances phytoplankton production, which in turn enriches the ocean surface with chl-a. Simultaneously, the pCO2 was relatively low in the region where the SST and primary production were high, highlighting that the heat and riverine nutrients trapped within the buoyant plume contributed to the reduction in pCO2 by promoting the biological uptake of CO2. The estimates conducted here illustrate the synergistic utility of multiple satellite measurements for the evaluation of CO2 uptake capacity, complemented by in situ measurements of river-dominated marginal seas.

Intercomparison of Global Sea Surface Salinity from Multiple Datasets over 2011–2018

The variability in sea surface salinity (SSS) on different time scales plays an important role in associated oceanic or climate processes. In this study, we compare the SSS on sub-annual, annual, and interannual time scales among ten datasets, including in situ-based and satellite-based SSS products over 2011–2018. Furthermore, the dominant mode on different time scales is compared using the empirical orthogonal function (EOF). Our results show that the largest spread of ten products occurs on the sub-annual time scale. High correlation coefficients (0.6~0.95) are found in the global mean annual and interannual SSSs between individual products and the ensemble mean. Furthermore, this study shows good agreement among the ten datasets in representing the dominant mode of SSS on the annual and interannual time scales. This analysis provides information on the consistency and discrepancy of datasets to guide future use, such as improvements to ocean data assimilation and the quality of satellite-based data.

Seasonal and Interannual Variability of Sea Surface Salinity Near Major River Mouths of the World Ocean Inferred from Gridded Satellite and In-Situ Salinity Products

Large rivers are key components of the land-ocean branch of the global water and biogeochemical cycles. River discharges can have important influences on physical, biological, optical, and chemical processes in coastal oceans. It is, therefore, of importance to routinely monitor the time-varying dispersal patterns of river plumes. The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) and the NASA Soil Moisture Active Passive (SMAP) satellites provide Sea Surface Salinity (SSS) observations capable of characterizing the spatial and temporal variability of major river plumes. The main objective of this study is to examine the consistency of SSS products, from these two missions, and two in-situ gridded salinity products in depicting SSS variations on seasonal to interannual time scales within a few hundred kilometers of major river mouths. We show that SSS from SMOS and SMAP satellites have good consistency in depicting seasonal and interannual SSS variations near major river mouths. The two gridded in-situ products underestimate these variations substantially. This underestimation, most notably associated with the low SSS season following the high-discharge season, is attributable to the limited in-situ sampling of the river plumes when they are the most active. This work underscores the importance of using satellite SSS to study river plumes, as well as to evaluate and constrain models.

Remote Sensing of Sea Surface Salinity Variability in the South China Sea

AbstractUsing newly available satellite observations of sea surface salinity (SSS), we provide, for the first time, a detailed and synoptic view of the spatiotemporal variability of SSS in the South China Sea (SCS). The results depict the SCS as a very dynamic region exhibiting variability over a broad range of time scales, from intraseasonal to interannual, with the seasonal cycle dominating (∼47% of the total SSS variance). The seasonal distribution of SSS has considerable latitudinal variations: the strongest variance across the southern SCS (∼5–12°N), weaker in the northern part of the sea (north of ∼18°N), with the weakest seasonal SSS variability in between. The factors controlling patterns of seasonal SSS distribution are closely related to both the external freshwater forcing and ocean processes over the entire SCS monsoon system. The most active interannual SSS variability is found in the northeastern and eastern parts of the SCS, as well as the adjacent western Pacific. A significant basin‐wide salinification began in summer of 2015, peaked in spring of 2016 with the averaged amplitude of up to 0.5 PSU, and maintained until the fall of 2016. Such persistent salinification during 2015–2016 following a strong El Nino event can be largely modulated by El Nino‐related atmospheric and oceanic dynamics. The intraseasonal variability was found to be surprisingly weak throughout the SCS (the standard deviation <0.2 PSU), except for a few regions near the coast where it is likely related to the intraseasonal variability in the monsoon rainfall and subsequent variations in river runoff.

Bay of Bengal Sea surface salinity variability using a decade of improved SMOS re-processing

Monsoon rain and rivers bring large freshwater input to the Northern Bay of Bengal (BoB), yielding low Sea Surface Salinity (SSS) after the monsoon. The resulting sharp upper-ocean salinity stratification is thought to influence tropical cyclones intensity and biological productivity by inhibiting vertical mixing. Despite recent progresses, the density of in situ data is far from sufficient to monitor the BoB SSS variability, even at the seasonal timescale. The advent of satellite remotely-sensed SSS (SMOS, Aquarius, SMAP) offers a unique opportunity to provide synoptic maps of the BoB SSS every ~8 days. Previous SMOS SSS retrievals did not perform well in the BoB. Here, we show that improved systematic error corrections and quality control procedures yield a much better performance of the new “debiased v4” CATDS level-3 SSS from SMOS (~0.8 correlation, 0.04 bias and 0.64 root-mean-square difference to more than 28,000 collocated in situ data points over 2010–2019). The SMOS product now performs equivalently to Aquarius, and is slightly inferior to SMAP over the BoB. In particular, SMAP and SMOS are able to capture salinity variations close to the east coast of India (r > 0.8 within 75–150 km of the coast). They thus capture the seasonal freshening there, associated with equatorward advection of the Northern BoB low-salinity water by the East Indian Coastal Current (EICC) after the summer monsoon. The 10-year long SMOS record further allows to describe the BoB interannual SSS variability, which is strongest in boreal fall in relation with the Indian Ocean Dipole (IOD). Positive IOD events induce a weakening of the southward export of freshwater by the EICC, and hence negative SSS anomalies in the Northern BoB and positive ones along the East Indian coast. This confirms results from earlier studies based on modelling, sparse in situ data, or shorter satellite records, but this time from a 10-year long SSS record. Overall, our study indicates that the new SMOS retrieval can be confidently used to monitor the BoB SSS and to study its mechanisms. We end by a brief description of the BoB SSS anomalies associated with the extreme 2019 IOD event and highlight the very good performance over the BoB of a new multi-satellite product developed by the European Space Agency merging SMOS, Aquarius and SMAP data.

Seven Years of SMOS Sea Surface Salinity at High Latitudes: Variability in Arctic and Sub-Arctic Regions

This paper aims to present and assess the quality of seven years (2011–2017) of 25 km nine-day Soil Moisture and Ocean Salinity (SMOS) Sea Surface Salinity (SSS) objectively analyzed maps in the Arctic and sub-Arctic oceans ( 50 ∘ N– 90 ∘ N). The SMOS SSS maps presented in this work are an improved version of the preliminary three-year dataset generated and freely distributed by the Barcelona Expert Center. In this new version, a time-dependent bias correction has been applied to mitigate the seasonal bias that affected the previous SSS maps. An extensive database of in situ data (Argo floats and thermosalinograph measurements) has been used for assessing the accuracy of this product. The standard deviation of the difference between the new SMOS SSS maps and Argo SSS ranges from 0.25 and 0.35. The major features of the inter-annual SSS variations observed by the thermosalinographs are also captured by the SMOS SSS maps. However, the validation in some regions of the Arctic Ocean has not been feasible because of the lack of in situ data. In those regions, qualitative comparisons with SSS provided by models and the remotely sensed SSS provided by Aquarius and SMAP have been performed. Despite the differences between SMOS and SMAP, both datasets show consistent SSS variations with respect to the model and the river discharge in situ data, but present a larger dynamic range than that of the model. This result suggests that, in those regions, the use of the remotely sensed SSS may help to improve the models.

Delayed and Quasi‐Synchronous Response of Tropical Atlantic Surface Salinity to Rainfall

AbstractZonally elongated patterns of tropical Atlantic rainfall variability associated with the Atlantic meridional (dipole) and the El Niño‐Southern Oscillation (ENSO) modes extend over the ocean and adjacent land and lead to a complex sea surface salinity (SSS) response. SSS response to local ocean rainfall is quasi‐instantaneous, while SSS response to land rainfall is delayed through river hydrology. Amazon rainfall associated with the Atlantic meridional mode concentrates over coastal north‐east Brazil and results in a fast Amazon response. In contrast, ENSO rainfall occupies vast inland areas and results in 3‐ to 7‐month delayed Amazon discharge response. Although ocean profile analyses represent well interannual SSS forced by open ocean rainfall, they miss interannual SSS in the plume. Including thermosalinograph transect data improves the representation of plume SSS, but its dynamic is better captured by ocean reanalyses. In Simple Ocean Data Assimilation, the plume SSS anomaly persists several months following the peak of land rainfall and is mixed out by seasonally accelerating winds in boreal winter. Its discharge‐correlated magnitude is only a modest few tenths of PSU. Perhaps, such weak projection of continental discharge variations on simulated SSS is not surprising due to other factors contributing in this dynamically active western boundary area. Significant transient variability in local currents not associated with rainfall/discharge variability is a factor explaining why ocean analyses based on occasional profile observations fail in resolving the rain‐induced SSS in the Amazon plume.

Climatic Influences on Southern Makassar Strait Salinity Over the Past Century

AbstractThe Indonesian Throughflow (ITF) is a globally important ocean current that fuels heat and buoyancy fluxes throughout the Indo‐Pacific and is known to covary in strength with the El Niño Southern Oscillation at interannual time scales. A climate system with a less well‐quantified impact on the ITF is the East Asian Winter Monsoon (EAWM), which drives less saline surface waters from the South China Sea (SCS) into the Makassar Strait, obstructing surface ITF flow. We present a subannually resolved record of sea surface salinity (SSS) from 1927 to 2011 based on coral δ18O from the Makassar Strait that reveals variability in the relative contributions of different source waters to the surface waters of the Makassar Strait during the boreal winter monsoon. We find that the EAWM (January–March) strongly influences interannual SSS variability during boreal winter over the twentieth century (r = 0.54, p << 0.0001), impacting surface water circulation in the SCS and Indonesian Seas.

A modeling study of processes controlling the Bay of Bengal sea surface salinity interannual variability

Recent observational studies provided preliminary insights on the interannual variability of Bay of Bengal (BoB) Sea Surface Salinity (SSS), but are limited by the poor data coverage. Here, we describe the BoB interannual SSS variability and its driving processes from a regional eddy-permitting ocean general circulation model forced by interannually varying air-sea fluxes and altimeter-derived discharges of major rivers over the past two decades. Simulated interannual SSS variations compare favourably with both in-situ and satellite data and are largest in boreal fall in three regions: the northern BoB, the coastal region off east India and the Andaman Sea. In the northern BoB these variations are independent from those in other regions and mostly driven by summer-fall Ganga-Brahmaputra runoff interannual variations. In fall, remote forcing from the Indian Ocean Dipole results in anti-clockwise anomalous horizontal currents that drive interannual SSS variations of opposite polarity along the east coast of India and in the Southern Andaman Sea. From winter onward, these anomalies are damped by vertical mixing in the northern BoB and along the east coast of India and by horizontal advection in the Southern Andaman Sea. While river runoff fluctuations locally play a strong role near the Ganga-Brahmaputra river mouth, wind-driven interannual current anomalies are responsible for a large fraction of SSS interannual variability in most of the basin. This article is protected by copyright. All rights reserved.

A sea surface salinity dipole mode in the tropical Indian Ocean

Based on the 10 years sea surface salinity (SSS) data from Argo, we identified a salinity dipole mode in the tropical Indian Ocean, termed S-IOD: a pattern of interannual SSS variability with anomalously low-salinity in the central equatorial and high-salinity in the southeastern tropical Indian Ocean. The S-IOD matures in November–December, lagging the Indian Ocean dipole (IOD) mode derived from sea surface temperature (SST) by 2 months. For the period of observations, the S-IOD persists longer than the IOD, until the following September–October. Oscillations of the two S-IOD poles are governed by different processes. Ocean advection associated with equatorial current variability dominates the SSS anomalies of the northern pole, while surface freshwater flux variability plays a key role in the SSS anomalies of the southern pole, where anomalous precipitation is sustained by preformed sea surface temperature anomalies. The S-IOD concurs with the strong IOD, reflecting an ocean–atmosphere coupling through the SST-precipitation-SSS feedback.

Nineteen-year changes in surface salinity in the Southern Ocean south of Australia

A 19-year time series of underway sea surface salinity (SSS) data from the SURVOSTRAL line between Hobart, Australia and Adelie Land, Antarctica has revealed the distinct patterns of seasonal and interannual variability in two key zones of the Southern Ocean: in the Subantarctic Zone and in the Antarctic Zone. Both regions show a weak seasonal freshening of the surface waters over the summer months, with surface waters becoming shallower, warmer and fresher during the summer heating cycle.In the region north of the Subantarctic Front, interannual variations in the summer SSS signature are linked to the latitudinal movements of the Subtropical Front. When this front shifts southward, more high salinity subtropical waters are brought into the domain. Rather than responding to local wind stress forcing, the interannual SSS variability is strongly linked to southward flow from eastern Tasmania (the Tasman outflow), whose decadal variability responds with a 2–3year delay to remote wind forcing in the South Pacific (Hill et al., 2008). Over this period, variations in the local surface freshwater forcing make a minor contribution to the SURVOSTRAL SSS signature. There appears to be a regime shift in the surface forcing and the SSS response, before and after the large perturbation in 2001–2002.In the Antarctic Zone, the summer SSS signature shows distinct biannual variations that are correlated with upstream sea-ice coverage in the preceding spring. There is no significant correlation between local precipitation changes and the SURVOSTRAL SSS time series. Rather, the integrated effects of upstream sea-ice melt dominate the interannual variations in SSS at the SURVOSTRAL line. Finally, a simple 2D Lagrangian particle analysis shows that in some years the surface waters circulate for a longer time in the northern part of the domain, where their freshwater content may be reduced by mixing with the surrounding waters.

Indian Ocean sea surface salinity variations in a coupled model

The variability of the sea surface salinity (SSS) in the Indian Ocean is studied using a 100-year control simulation of the Community Climate System Model (CCSM 2.0). The monsoon-driven seasonal SSS pattern in the Indian Ocean, marked by low salinity in the east and high salinity in the west, is captured by the model. The model overestimates runoff into the Bay of Bengal due to higher rainfall over the Himalayan–Tibetan regions which drain into the Bay of Bengal through Ganga–Brahmaputra rivers. The outflow of low-salinity water from the Bay of Bengal is too strong in the model. Consequently, the model Indian Ocean SSS is about 1 less than that seen in the climatology. The seasonal Indian Ocean salt balance obtained from the model is consistent with the analysis from climatological data sets. During summer, the large freshwater input into the Bay of Bengal and its redistribution decide the spatial pattern of salinity tendency. During winter, horizontal advection is the dominant contributor to the tendency term. The interannual variability of the SSS in the Indian Ocean is about five times larger than that in coupled model simulations of the North Atlantic Ocean. Regions of large interannual standard deviations are located near river mouths in the Bay of Bengal and in the eastern equatorial Indian Ocean. Both freshwater input into the ocean and advection of this anomalous flux are responsible for the generation of these anomalies. The model simulates 20 significant Indian Ocean Dipole (IOD) events and during IOD years large salinity anomalies appear in the equatorial Indian Ocean. The anomalies exist as two zonal bands: negative salinity anomalies to the north of the equator and positive to the south. The SSS anomalies for the years in which IOD is not present and for ENSO years are much weaker than during IOD years. Significant interannual SSS anomalies appear in the Indian Ocean only during IOD years.

Interannual sea surface salinity changes in the western Pacific from 1954 to 2000 based on coral isotope analysis

[1] Changes in sea surface salinity (SSS) in the western Pacific warm pool (WPWP) provide information on the variability of the El Niño Southern Oscillation (ENSO) because SSS reflects the balance between evaporation and precipitation. We reconstructed the long-term variability of SSS at the northwestern edge of the WPWP from oxygen isotope analysis of annual coral bands. The estimated SSS corresponded well with in situ observations, demonstrating that isotopic records from coral can be used as a paleo-salinometer. Estimated SSS between 1954 and 2000 peaked during the El Niños of 1972–73, 1982–83, and 1997–98. These SSS peaks were caused by anomalously low precipitation accompanying the eastward shift in the WPWP.

Sea surface salinity interannual variability in the western tropical Atlantic: An ocean general circulation model study

Interannual variability of sea surface salinity in the northwest tropical Atlantic is investigated in several ocean general circulation model eddy‐permitting simulations using different air‐sea freshwater forcing. The only simulation able to reproduce some features of the observed variability from 1989 to 1993, in particular in the northwest South American region up to 20°N, east of the Lesser Antilles, is one with no relaxation to a salinity climatology. The model variability results from advection of freshwater originating from the large South American continental shelf river runoff and has a seasonal cycle associated with the displacement of the intertropical convergence zone: Anomalies develop from March to May and then propagate to a larger area within the next months with the horizontal currents (where both geostrophic and Ekman currents contribute). Later on, from July to October, the anomalies are damped through entrainment across the mixed layer base. The vertical diffusion through the mixed layer base does not weaken when anomalously fresh surface water is present (i.e., no barrier layer effect). According to the European Centre for Medium‐Range Weather Forecasts ERA15 reanalysis, air‐sea freshwater fluxes have little impact on the large (over 0.5 practical salinity scale) sea surface salinity (SSS) variability in this region. In the model, eddy variability plays little role in the interannual SSS variability, maybe because of inadequate resolution resulting in too weak and too few North Brazil Current eddies.

Interannual sea surface salinity and temperature changes in the western Pacific warm pool during 1992–2000

Sea surface salinity (SSS) and sea surface temperature (SST) in the western Pacific warm pool (130–180°E; 10°N–10°S) are analyzed for the period 1992–2000 taking advantage of complementary data from the ship of opportunity program and the Tropical Atmosphere‐Ocean (TAO)‐Triangle Trans‐Ocean Buoy Network (TRITON) array of moored buoys. Covariability of these variables with surface wind stress, surface zonal currents, evaporation, precipitation, and barrier layer thickness is also examined. These fields all go through large oscillations related to the El Niño Southern Oscillation (ENSO) cycle, most notably during the record breaking 1997–1998 El Niño and subsequent strong 1998–2000 La Niña. East of about 160°E, during El Niño, precipitation minus evaporation increases in the equatorial band, in conjunction with anomalous increases in westerly winds, eastward surface currents, SST, and decreases in SSS. Opposite tendencies are evident during La Niña. Peak to peak 2°N–2°S averaged variations reached as much as 1.2 m s−1 for zonal currents and 1.5 practical salinity units (psu) for SSS. West of about 160°E, SST cools during El Niño and warms during La Niña, opposite to what occurs further east. To understand these SST tendencies west of 160°E, a proxy indicator for barrier layer formation is developed in terms of changes in the zonal gradient of SSS (∂S/∂x). Zonal SSS gradients have been shown in modeling studies to be related to barrier layer formation via subduction driven by converging zonal currents in the vicinity of the salinity front at the eastern edge of the warm pool. Correlation between changes in ∂S/∂x and changes in SST a few degrees longitude to the west is significantly nonzero, consistent with the idea that increased barrier layer thickness is related to warmer SSTs during periods of westward surface flow associated with La Niña, and vice versa during El Niño. Direct evidence of barrier layer thickness variations in support of this hypothesis is also presented.

Surface salinity variability in the northern North Atlantic during recent decades

[1] The sea surface salinity (SSS) variability in the North Atlantic is investigated using numerical model simulations for the last 50 years based on atmospheric forcing variability from the Comprehensive Atmosphere Ocean Data Set (COADS) and National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis. The focus here is the SSS variability in the subpolar region. The seasonality of the subpolar surface salinity variability is prominent with the maximum standard deviation (SD) occurring in the summer/fall period so that the amplitude of the summer SSS anomalies far exceed those of the wintertime. The interannual SSS variability in the subpolar gyre can be attributed mainly to excess ice melt, while the longer-term (decadal) variability is associated with meridional overturning variability. In these two hindcasts, the deep mixing (which drives overturning changes) is forced by heat flux variability so that weak subpolar heat loss and subsequent weak overturning are usually manifested in fresh surface conditions in the subpolar gyre within 2 years. This is because the role of deep convection is to mix down the net fresh water input received by the high latitudes. Hence, at the lack of widespread deep mixing, a signal of slowing down overturning, the fresh water input that would be expected based on climatology would accumulate at the surface.

Seasonal and interannual variations of sea surface salinity in the tropical Pacific Ocean

Sea surface bucket measurements, obtained through a ship‐of‐opportunity program, are used to describe the sea surface salinity (SSS) field for the tropical Pacific during the period 1969–1988. Emphasis is placed upon the mean SSS distribution and the seasonal and interannual SSS variability occurring along four well‐sampled shipping tracks. These tracks extend from New Zealand to Japan, from New Zealand to Hawaii, from Tahiti to California, and from Tahiti to Panama. They cross the equator at 155°E, 160°W, 140°W, and 100°W, respectively. Along each track, the mean SSS distribution is characterized by SSS minima which are 4°–6° further poleward than the axes of maximum precipitation associated with the Intertropical Convergence Zone (ITCZ) and South Pacific Convergence Zone (SPCZ). It is suggested that these SSS minima owe their existence mainly to heavy rainfall and poleward Ekman salt transport associated with the trade winds. The role of zonal salt advection was found negligible for these SSS minima. Except along the eastern track, maximum seasonal SSS variations are located in the ITCZ and SPCZ regions, with minimum SSS in September‐October and March‐April, respectively. On the basis of precipitation island stations, it is demonstrated that the maximum seasonal SSS variations are closely related to the rainfall regimes of the ITCZ and SPCZ (rainfall maximum 3 months before SSS minimum; rainfall amount sufficient to account for SSS changes). Along the eastern track, a strong annual SSS cycle is found from about 4°S (110°W) to the Panama coast (minimum SSS in February–March), reflecting the combined effects of rainfall, salt advection, and vertical mixing. Notable interannual SSS variability concerns only the western half of the tropical Pacific Ocean where El Niño‐Southern Oscillation (ENSO) related SSS changes are strongly related to ENSO‐related precipitation changes. During ENSO periods, the SSS field west of about 150°W is characterized by fresher‐than‐average SSS within about 8°N to 8°S, and conversely saltier‐than‐average SSS poleward of 8° latitudes. These modifications in the SSS field are thought to result mainly from an eastward displacement in the ascending branch of the Walker and Hadley cells which induces unusually high rainfall over the western and central equatorial Pacific region bordered on all sides by rainfall deficits. Reproducing the actual SSS changes at seasonal and interannual time scales would be a very stringent test for model capability.