Interannual Sea Surface Salinity Variability Research Articles

Interannual Variation of Summer Sea Surface Salinity in the Dotson–Getz Trough, West Antarctica

In this study, we explore the interannual variability of Sea Surface Salinity (SSS) in the Dotson–Getz Trough located in West Antarctica, focusing on the month of February. Utilizing the oceanic analysis product EN4, we first validate the EN4 SSS with data from a singular ship-based survey, and then delve into potential factors that may influence SSS, with a particular emphasis on surface freshwater flux, sea ice concentration (SIC), and also the surface stress curl, which will induce upwelling via Ekman transport to affect the SSS. Our findings primarily indicate a link between SSS and sea ice concentration, showcasing a negative correlation where the peak (average) coefficient is around −0.6 (−0.4), further affirming the substantial interannual variability of SSS in this region.

Sea surface salinity variability in the western subpolar North Atlantic based on satellite observations

Sea surface salinity (SSS) variability during the recent decade in the western subpolar North Atlantic is investigated using three satellite salinity products, Aquarius, SMAP and SMOS, as well as in-situ observations. Satellite datasets successfully resolve the large scale SSS pattern but are significantly biased near the western boundary regions. Freshwater flux induced by sea ice formation/melting plays a dominant role in shaping the SSS annual cycle in the coastal regions of the western Labrador Sea, but data gaps and uncertainties prevent satellite products from accurately resolving the seasonality in the Labrador Shelf. On the other hand, seasonal fluctuations near the Grand Banks are reasonably captured in satellite data. They are essentially driven by both local freshwater flux associated with ice and advective signals from the north. The interannual variability of SSS is detectable in both in-situ observations and Aquarius. During the low salinity period in 2011–2012, interannual anomalies are no longer controlled by ice formation/melting. Instead, they are mostly determined by oceanic advection, which moves low salinity water around the Labrador Sea in a cyclonic direction. In addition, the Data Interpolating Empirical Orthogonal Function (DINEOF) is applied to satellite datasets to weed out noise and fill data gaps. The resulting reconstructed datasets show apparent bias reduction and better performances in depicting seasonal cycles in both coastal region and deep ocean. DINEOF does not improve the capability of SMAP and SMOS in resolving the interannual anomalies as their original fields do not include such signals.

Tropical Instability Waves in the Atlantic Ocean: Investigating the Relative Role of Sea Surface Salinity and Temperature From 2010 to 2018

AbstractWe identify and analyze tropical instability waves (TIWs) in the equatorial Atlantic Ocean during 2010–2018 using satellite derived observations of sea surface salinity (SSS), sea surface temperature (SST), sea level anomaly, and Argo profiles. In particular, the weekly 50‐km resolution SSS time series from the climate change initiative project provides an unprecedented opportunity to observe the salinity structure at a scale closer to the SST scale. We examine the relative contributions of SSS and SST to the horizontal surface density gradient on seasonal and interannual time scales and how they contribute to the TIW properties and energetics. For the central Atlantic TIWs, the maximum of the SST contribution to the density anomaly lags the SSS one by approximately one month. Argo vertical profiles indicate that temperature and salinity both significantly contribute to TIW‐related density anomalies. In May–June, salinity contributes to 50% of the perturbation potential energy in the top 60 m, and between 30% and 45% from July to September. While variations in SST appear to be related to dynamic processes, the interannual variability of SSS is also influenced by precipitations. However, the two leading modes of variability in the region (Atlantic Meridional and Zonal modes) do not well explain at 1°N these interannual variations.

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.

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.

Satellite Observed Salinity Distributions at High Latitudes in the Northern Hemisphere: A Comparison of Four Products.

Global surface ocean salinity measurements have been available since the launch of SMOS in 2009 and coverage was further enhanced with the launch of Aquarius in 2011. In the polar regions where spatial and temporal changes in sea surface salinity (SSS) are deemed important, the data has not been as robustly validated because of the paucity of in situ measurements. This study presents a comparison of four SSS products in the ice-free Arctic region, three using Aquarius data and one using SMOS data. The accuracy of each product is assessed through comparative analysis with ship and other in situ measurements. Results indicate RMS errors ranging between 0.33 and 0.89 psu. Overall, the four products show generally good consistency in spatial distribution with the Atlantic side being more saline than the Pacific side. A good agreement between the ship and satellite measurements were also observed in the low salinity regions in the Arctic Ocean, where SSS in situ measurements are usually sparse, at the end of summer melt seasons. Some discrepancies including biases of about 1 psu between the products in spatial and temporal distribution are observed. These are due in part to differences in retrieval techniques, geophysical filtering, and sea ice and land masks. The monthly SSS retrievals in the Arctic from 2011 to 2015 showed variations (within ~1 psu) consistent with effects of sea ice seasonal cycles. This study indicates that spaceborne observations capture the seasonality and interannual variability of SSS in the Arctic with reasonably good accuracy.

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.

Assessment of interannual sea surface salinity variability and its effects on the barrier layer in the equatorial Pacific using BNU-ESM

As salinity stratification is necessary to form the barrier layer (BL), the quantification of its role in BL interannual variability is crucial. This study assessed salinity variability and its effect on the BL in the equatorial Pacific using outputs from Beijing Normal University Earth System Model (BNU-ESM) simulations. A comparison between observations and the BNU-ESM simulations demonstrated that BNU-ESM has good capability in reproducing most of the interannual features observed in nature. Despite some discrepancies in both magnitude and location of the interannual variability centers, the displacements of sea surface salinity (SSS), barrier layer thickness (BLT), and SST simulated by BNU-ESM in the equatorial Pacific are realistic. During El Nino, for example, the modeled interannual anomalies of BLT, mixed layer depth, and isothermal layer depth, exhibit good correspondence with observations, including the development and decay of El Nino in the central Pacific, whereas the intensity of the interannual variabilities is weaker relative to observations. Due to the bias in salinity simulations, the SSS front extends farther west along the equator, whereas BLT variability is weaker in the central Pacific than in observations. Further, the BNU-ESM simulations were examined to assess the relative effects of salinity and temperature variability on BLT. Consistent with previous observation-based analyses, the interannual salinity variability can make a significant contribution to BLT relative to temperature in the western-central equatorial Pacific.

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.

A new technique for the estimation of sea surface salinity in the tropical Indian Ocean from OLR

Algorithms are developed for the estimation of sea surface salinity (SSS) in the tropical Indian Ocean from the space‐borne satellite measurements of outgoing longwave radiation (OLR). The algorithms are based on the interrelationships between OLR, the effective oceanic layer (EOL), climatological SSS (World Ocean Atlas 1998 (WOA98)), and freshwater flux (P‐E). Coupling between the atmospheric convection (OLR) and the geopotential thickness of the oceanic near‐surface stratified layer (EOL) forms the main relationship for the estimation of SSS, followed by the relationships between EOL and WOA98 SSS and between OLR and P‐E. The SSS has been estimated using 16 years (1979–1994) of OLR data and the algorithms for the tropical Indian Ocean. The estimated SSS at 2.5° × 2.5° grid on monthly scale is nearer to the WOA98 SSS with lower differences within ±0.5–0.8 away from the coastal region. The estimated SSS also agrees reasonably with the observed SSS along the trans‐Indian zonal sections occupied during World Ocean Circulation Experiment (WOCE) and also other sections. The SSS differences bring out clearly the impact of the strong 1997–1998 El Niño on the rainfall in the southeastern Indian Ocean and the eastern equatorial region. On the basis of the results, the seasonal and interannual variability of SSS in the tropical Indian Ocean are discussed. Through a physical model, phase lags between P‐E and SSS and between OLR and P‐E are estimated and their incorporation into the algorithms is suggested for improvement in the estimation of SSS. This SSS information is useful to the studies on coupled models, El Niño‐Southern Oscillation forecast models, and Ocean Global Circulation Models or regional scale circulation models.

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.

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.