Journal of Marine Systems 113–114 (2013) 88–93
Contents lists available at SciVerse ScienceDirect
Journal of Marine Systems
journal homepage: www.elsevier.com/locate/jmarsys
Oxygen isotope–salinity relationships of discrete oceanic regions from India to
Antarctica vis-à-vis surface hydrological processes
Manish Tiwari ⁎, Siddhesh S. Nagoji, Thammisetti Kartik, G. Drishya 1, R.K. Parvathy 2, Sivaramakrishnan Rajan
National Centre for Antarctic & Ocean Research, Vasco-Da-Gama, Goa — 403804, India
a r t i c l e
i n f o
Article history:
Received 15 October 2012
Received in revised form 8 January 2013
Accepted 14 January 2013
Available online 26 January 2013
Keywords:
Southern Ocean
Indian Ocean
Seawater
Isotopes
Sea surface salinity
Sea surface temperature
a b s t r a c t
Coupled measurements of the oxygen isotope and salinity of surface waters at every degree latitude along a transect from India to Antarctica during summer 2010 were carried out to gain insight into the surface hydrological
processes active in the Indian and Southern Oceans. It is possible to identify discrete water masses from the Indian and Southern Oceans based on oxygen isotope and salinity. We determine the relationship between oxygen
isotope and sea surface salinity (δ18O–SSS) pertaining to those distinct water masses by combining our data with
those available at the NASA-GISS data center. These relationships are predominantly governed by evaporation/
precipitation except in the Antarctic Zone (beyond Polar Front) where sea ice melting/freezing plays a dominant
role. We obtain more representative, long-term mean values of the slopes and intercepts of the salinity–oxygen
isotope relation that will help to determine paleosalinity from carbonate fossils from sediments more accurately.
The Subtropical and Polar Fronts were identified at 44° S and 54° S, respectively. These new data will also be useful to fill the gap in the existing global gridded δ18O data sets obtained by interpolating the observed values.
© 2013 Elsevier B.V. All rights reserved.
1. Introduction
Polar regions of the world are experiencing rapid climate change,
and the Southern Ocean is no exception (e.g., IPCC, 2007). Consequently, the freshwater budget of the Southern Ocean is significantly affected
(Meredith et al., 2008); this needs to be documented to better understand its consequences. Freshwater variability affects the salinity and
the stable oxygen isotope ratio (δ18O) of surface seawater significantly
(Bigg and Rohling, 2000; Clark and Fritz, 1997). Oxygen isotope–sea
surface salinity (δ18O–SSS) relationship is an important information
for several hydrological processes such as the balance between meteorological input i.e., evaporation/precipitation (E–P) and glacial melt
water, sea ice melting/formation, river run-off, and upwelling or advection and also provides an important tool to delineate different water
masses (Bigg and Rohling, 2000; Meredith et al., 1999; Srivastava et
al., 2007). Furthermore, recent interest in the Southern Ocean regarding
its role in carbon sequestration has led to several paleoclimatic studies
in that region (Mayewski et al., 2009 and references therein). The
δ18O–SSS relationship is widely used in paleoclimatic studies as well
to estimate the salinity variability in the past that is relatable to changing climate, which further strengthens the need to understand the temporal variability of this relationship. In view of this, a few studies have
been carried out in the western Indian Ocean sector of the Southern
⁎ Corresponding author. Tel.: +91 832 2525638; fax: +91 832 2520877.
E-mail address: [email protected] (M. Tiwari).
1
Present Address: Geological Survey of India, DK-6, Sector II, Saltlake, Kolkata – 700091,
India.
2
Present Address: Geological Survey of India, Bandalaguda, Hyderabad - 500 068, India.
0924-7963/$ – see front matter © 2013 Elsevier B.V. All rights reserved.
http://dx.doi.org/10.1016/j.jmarsys.2013.01.001
Ocean (e.g., Srivastava et al., 2007), but recent studies in the northern
Indian Ocean have shown that this relationship can change significantly
over the years (e.g., Singh et al., 2010); so it becomes important
to assess this variability over a sufficiently long period (Rohling and
Bigg, 1998). The global gridded data set prepared by LeGrande and
Schmidt (2006) has also raised the issue of the sparseness of observations for certain oceanic regions that include the southern Indian and
the Southern Oceans. They further stress that the δ 18O–SSS relationship
may alter over time scales ranging from seasonal, annual, and interannual. The Indian sector of the Southern Ocean has received much
less attention compared to others. Therefore a systematic and persistent
data collection is required for this sector to reduce the uncertainties.
Here we present new data on the oxygen isotope ratio of surface seawater collected at every degree latitude from a transect starting from Goa,
India (14.04° N, 73.11° E) to the Antarctic coast (66.72° S, 58.83° E).
This study, spanning more than a quarter of the globe, would help identify distinct surface water-masses with separate δ18O–SSS relationship
important for paleosalinity determination and distinct regions dominated by particular surface hydrological processes such as excess of evaporation over precipitation (E–P), sea ice melting/freezing, water mass
advection, continental snowmelt affect and so on. Furthermore, this
new data set would complement and add to the existing global gridded
δ18O data that is obtained by interpolating the observed δ18O values.
2. Materials and methods
Surface water samples were collected at every degree latitude
during the 4 th Indian Expedition to the Southern Ocean in the austral
summer (January–February) of the year 2010 along the track shown
M. Tiwari et al. / Journal of Marine Systems 113–114 (2013) 88–93
in Fig. 1, spanning the Arabian Sea, tropical Indian Ocean, southern
Indian Ocean, and the Southern Ocean. Fig. 1 also depicts the surface
circulation features of the Indian and Southern Oceans (Barker and
Thomas, 2004; Schott and McCreary, 2001), and the position of the
Inter Tropical Convergence Zone (ITCZ) (Webster, 1987). The seawater samples from the surface were collected using a clean bucket,
which was then transferred to 60 ml dry HDPE plastic bottles having
a very low permeability to water vapor (Illig, 2001). These were filled
up to the brim without letting any bubble and capped tightly. Thereafter, another round of Teflon tape was tightly wrapped on the cap to
seal it from the ambient environment to prevent any evaporation that
may alter the isotopic content. Salinity was calculated using its conductivity, measured by a thermosalinograph (Sea-Bird Electronics Inc.;
model name: SBE 45) installed on-board that uses the 1978 Practical
Salinity Scale (PSS-78) equations with a precision of ±0.003 mS/cm.
The resulting precision for salinity is ±0.005. The sea surface temperature (SST) was measured on-board using a bucket thermometer to a
precision of ±0.5 °C. The oxygen isotope values were measured in the
Marine Stable Isotope Lab (MASTIL) at the National Centre for Antarctic
& Ocean Research, Goa, India, using an “Isoprime dual inlet-stable isotope ratio mass spectrometer” using the well established CO2 equilibration method (Epstein and Mayeda, 1953; Gonfiantini, 1981). The water
samples were stored at around 22 °C for about four months before measurement, which was completed within 3 days. The isotopic values are
expressed in terms of delta (δ) notation, which is the relative difference
of isotopic ratios in the sample from an international standard. Thus:
δ18O = {(18O/ 16O)sample /(18O/16O)standard} − 1; where (18O/ 16O)sample
and (18O/ 16O)standard are the ratios of the abundances of the less abundant (heavier, i.e., 18O) to more abundant (lighter, i.e., 16O) isotope in
the sample and standard, respectively. This definition does not include
Fig. 1. Transect from India to Antarctica showing sampling locations at every degree latitude (black circles); frontal structure of Southern Ocean is indicated: STF, SAF, and PF refer
to Subtropical Front, Subantarctic Front, and Polar Front respectively; schematic representation of oceanic currents and ITCZ during the sampling season (boreal winter) is also
shown; current branches indicated are the South Equatorial Current (SEC), South Equatorial Countercurrent (SECC), Northeast and Southeast Madagascar Current (NEMC and
SEMC), East African Coast Current (EACC), Somali Current (SC), West Indian Coast Current
(WICC), East Indian Coast Current (EICC), Northeast Monsoon Current (NMC), South Java
Current (JC),West Wind Drift (WWD), and East Wind Drift (EWD) (Cunningham, 2005;
Schott and McCreary, 2001).
89
the multiplication by 10 3 as ‘δ’ value is a dimensionless quantity but is
multiplied by such extraneous factors and expressed in per mil (‰)
units for the sake of readability and ease of comprehension (Coplen,
2011). The isotopic values are reported with respect to the international
standard V-SMOW (Vienna-Standard Mean Ocean Water). The reproducibility of the δ18O measurement is better than ±0.1‰ (1σ standard
deviation) as determined by repeated measurements (n= 25) of the lab
standard, which is seawater from 52° 02′ S and 57° 32′ E with δ18O
value of −0.18± 0.05 with respect to V-SMOW.
The δ 18O–SSS relationship has been obtained by ‘linear regression’
using the ‘least squares’ method (Topping, 1962). The confidence
limits of the correlation coefficient values presented here have been
determined using ‘Student's t-test’. The uncertainties on the slope
(m) and intercept (c) have been calculated according to Topping
(1962) as follows: when y = m x + c, ‘n’ is the number of data points,
and the ‘residual’ i.e., d = m x + c − yobserved; then error on the slope is
σm = ({n/n − 2}{Σd 2 / (nΣx 2) − (Σx) 2}) 1/2 while that on the intercept
is σc = σm(Σx 2/n) 1/2. Here ‘y’ is the δ 18O value while ‘x’ is the sea surface salinity.
3. Results and discussion
3.1. Oxygen isotope, salinity, and SST vs. latitude
Fig. 2 shows the salinity, temperature (SST), and δ18O value of surface seawater vs. latitude (also see Supplementary Table 1) southwards
from Goa (from ~14° N). The first sampling point, which is very near the
coast, shows considerably less salinity (35) than the subsequent locations (salinity ~36), farther away from the coast, as near the Goa
coast, several small streams, namely Mandovi, Zuari, Terekhol, Chapora,
Baga, and Sal debouch into the sea. Subsequently from 6° N to 2° N,
there is a narrow zone of declining salinity (by 2 units; from 36 to 34)
while δ18O value decreases by 0.4‰ (from 0.8‰ to 0.4‰). This coupled
decline in δ18O values and salinity indicates freshening of the seawater
due to the Northeast monsoon induced precipitation and oceanic currents. Although the core of the ITCZ during Northeast monsoon lies farther south, yet precipitation of 40 mm/month is recorded in this region
(http://iri.ldeo.columbia.edu), which reduces salinity/δ18O (Dansgaard,
1964; IAEA/WMO, 2006). Additionally, the Northeast monsoon current
brings lower salinity/δ 18O waters of the Bay of Bengal (Fig. 1; Antonov
Fig. 2. δ18O (filled squares), sea surface salinity (filled circles) and SST (filled triangles)
variability across the sampling transect; shaded area represents the samples influenced
by the ITCZ while dashed and dotted lines show the deciphered positions of the Subtropical Front and Polar Front respectively.
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M. Tiwari et al. / Journal of Marine Systems 113–114 (2013) 88–93
et al., 2010; Singh et al., 2010), which feeds the North Equatorial current
found in these latitudes (Schott and McCreary, 2001). Thus, the effects
of both the Northeast monsoon precipitation as well as the oceanic currents generated by the Northeast monsoon winds are recorded. Both
the salinity and δ18O values at the equator increase indicating reduced
precipitation. In the southern tropics (till 20° S), a broad zone where
the SST stays around 29 °C while both the salinity and δ18O values decline from 36 to 34, and 1‰ to 0.4‰, respectively, is observed. This decline in salinity and δ18O values reflects the influx of freshwater via
Northeast monsoon precipitation as the boreal winter ITCZ is situated
over the southern tropical region during the sampling period (January)
(Webster, 1987). From 24° S to 43° S, the SST gradually declines from
27.5 °C to 16 °C meanwhile the salinity and δ 18O value stay more or
less uniform, centered at ~35.5 and 0.6‰ respectively. This signifies
that the Subtropical Zone, during the study period, is marked by increased E–P. At ~44° S, a strong and simultaneous change in all the
three parameters viz. temperature, salinity and δ18O value is observed
(shown by the dashed line in Fig. 2) that marks the Subtropical Front.
SST declines from 16 °C to 12.5 °C, salinity falls from 35.5 to 34.3
while the δ 18O values decrease from 0.5‰ to 0‰. Across the Subantarctic Front, SST falls rapidly and reaches a value near 2.5 °C at 54° S, where
a sudden decline in salinity to 32.4 is also observed, which marks the
Polar Front (shown by the dotted line in Fig. 2). These low salinity
values could be caused by ‘Polar Lows’ associated with frequent storms
and precipitation (Cunningham, 2005). The δ18O values are also low,
centered at −0.25‰. In the Antarctic Zone, the SST values decline further reaching a minimum of 0 °C. The salinity values stay uniform except at the southernmost location (66.7° S) while the δ18O values rise
slightly by 0.15‰ and thereafter show a decline towards the Antarctic
coast. Sea ice is enriched in the heavier oxygen isotope by about 2.6 to
2.9‰ (Beck and Münnich, 1988; Melling and Moore, 1995) while its salinity can be as low as 7 (Meredith et al., 2008). Mid-February was the
period of the sample collection from beyond the Polar Front when sea
ice reaches a minimum (Deacon, 1984). The extensive sea ice melting
would result in a decline in salinity and a slight increase in δ18O values.
We also observe lower salinity and slight increase in δ18O values in the
Antarctic Zone (between the Polar Front and Antarctica) as compared to
region prior to Polar Front (50° S to 54° S) indicating the dominance of
sea ice melting process. The southernmost point of this study at 66.73° S
appears to be affected by the continental snow/glacial melt water having very low salinity/δ18O values due to its proximity to Antarctica. Continental ice is made up of evaporated water (and subsequent meteoric
precipitation) that is highly depleted in the heavier isotope of oxygen
(δ 18O values of ice can be as low as −20‰; Potter and Paren, 1985),
so when it melts, it reduces the salinity as well as the δ 18O values of
the ambient seawater (Archambeau et al., 1998). This input of freshwater can be either in the form of surface runoff or melt water from ice
shelf directly in contact with seawater, which is seen in the case of the
southernmost point.
1985; Östlund et al., 1987; Singh et al., 2010; Srivastava et al., 2007) including data from the large programs such as SWINDEX and CDOHC
(Schmidt et al., 1999) to the present study. The data points selected are
from depths of up to 100 m and in between 40° E to 80° E except for latitude 14° N to 7° N where the data represent the eastern Arabian Sea. This
provides us an opportunity to determine the δ18O–SSS slope for some of
the least studied regions of the world's oceans. Additionally, we have improved on the earlier studies that club together huge areas (e.g., whole of
the Indian Ocean or Southern Ocean) by identifying distinct regions in
the Indian Ocean and Southern Ocean (Clusters 1 to 5 in Fig. 3). This
should yield a relationship that is more representative of the area
under consideration (Fig. 4c to g pertaining to Clusters 1 to 5 of Fig. 3).
The x, y and z axis in Fig. 3 represent salinity, δ18O values and latitude respectively. Cluster-1 pertaining to tropical samples (14° N to 7° N) from
the northern hemisphere has higher δ18O values coupled with higher salinity. The 2nd distinct cluster shows samples from the northern equatorial and southern tropical Indian Ocean (7° N to 17° S) representing a
large spatial extent. Cluster-3 depicts samples from the subtropical
region of the southern hemisphere (24° S to 44° S) where we note higher
salinities and δ18O values. A clear distinction is evident as we cross 44° S
and moves into the Southern Ocean (Clusters 4 and 5). Such a distinction
was also visible in SST, δ18O values and salinity plots (Fig. 2; shown by
dashed line). In the Southern Ocean, unambiguous distinction is visible
between the Subantarctic/Polar Frontal Zone (Cluster-4; 44° S to 54° S)
and the Antarctic Zone (Cluster-5; 54° S to 68° S) with progressively
lower oxygen isotope and salinity values as we move southwards due
to the effect of sea ice and glacial melt water.
The oxygen isotope–salinity (δ18O–SSS) relationship observed in the
present study in the case of the whole of the Indian Ocean (Fig. 4a) shows
a positive relationship (slope of 0.15±0.05; n=52) i.e. both δ18O values
and salinity covary implying the role of evaporation/precipitation in this
region. In the region south of 44° S (Southern Ocean), we observe a slope
of 0.03±0.06 (n=24) and a correlation of determination (r2)=0.03,
which is not only nonexistent but is also not significant at the 99% or
95% level (p= 0.01 or 0.05) determined using Student's t-test. In
Fig. 4b, we add data from the previous studies to the present study
(shown by differently colored and shaped symbols) and again divide
them in the Indian and Southern Oceans similar to Fig. 4a. We note
that the slope becomes steeper both for the Indian Ocean (m= 0.39±
3.2. Long-term oxygen isotope–salinity relationship of discrete
water-masses: implications to paleoclimatic interpretations
δ18O–SSS slope is widely used in paleoclimatology/paleoceanography
to delineate the effect of salinity from the oxygen isotopic composition of
carbonate shells of marine microfossils such as foraminifera. Singh et al.
(2010) have shown that the δ18O–SSS relationship in a fresh water
dominated area, such as the Bay of Bengal, is variable on different time
scales. Presently, the slopes (m) of this relationship being used are mostly based on measurement of samples collected during a single cruise
representing a specific season (e.g., Duplessy, 1970; Duplessy et al.,
1981; Srivastava et al., 2007). In contrast, this study attempts to obtain
a long-term value for the δ18O–SSS relationship by adding data stored
at NASA-GISS (Schmidt et al., 1999) from previous isolated studies carried over past few decades (Craig and Gordon, 1965; Delaygue et al.,
2001; Duplessy, 1970; Duplessy et al., 1981; Frew et al., 1995; Kallel,
Fig. 3. Three dimensional plot depicting δ18O vs. salinity vs. latitude that helps to identify water masses from specific regions with discrete characteristics (see text for more
details); gray lines indicate the respective latitude.
M. Tiwari et al. / Journal of Marine Systems 113–114 (2013) 88–93
91
Fig. 4. The relationship between oxygen isotope and salinity in specific regions of the Indian Ocean and Southern Ocean obtained using the linear regression by the least square
method (details in the text).
0.04) and the Southern Ocean (m= 0.24 ± 0.04) but the errors are quite
large, especially in the case of the Indian Ocean, which may be due to
the large spatial area covered. This stresses the need of dividing such
large areas into discrete regions, which we do here onwards based on
the clusters identified in Fig. 3. Fig. 4c shows the δ18O–SSS relationship
from the northern tropical Indian Ocean (14° N to 7° N; Cluster-1 in
Fig. 3) with δ18O–SSS slope of 0.41 ± 0.24; r2 = 0.12; n =26; significant
at p = 0.95. In this case, the low value of r2 may result because the samples are from regions affected by processes causing widely fluctuating
salinities and δ 18O values. For example samples near the Indian coast
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M. Tiwari et al. / Journal of Marine Systems 113–114 (2013) 88–93
will be affected by surface runoff and lower salinity waters from the
NMC while those away from it will be affected by the E–P balance. In
the equatorial Indian Ocean and southern tropical Indian Ocean (7° N
to 17° S; 40° E to 80° E), the δ18O–SSS slope changes to 0.08 ± 0.05;
r2 = 0.04; n = 87; significant at p = 0.95 as determined using Student's
t-test (Fig. 4d). The weak correlation may result because of wide spatial
and temporal scales covered in this case. Interestingly, in the Fig. 4d,
comparison of the results of the present study (red colored closed circles) with those of previous studies yields a much steeper slope. Addition of freshwater increases the slope and decreases the intercept
(Delaygue et al., 2001; Singh et al., 2010). During the sample collection
period (January) the ITCZ was over the southern tropical Indian Ocean
that appears to play a major role in controlling the slope via precipitation. This observation further strengthens the case of using a temporally
averaged slope value instead of relying on a single study during a specific season. In the subtropical region of the southern Indian Ocean (24° S
to 44° S; Cluster-3; Fig. 4e), we observe a δ18O–SSS slope of 0.44 ±0.03;
r2 = 0.69; n = 115; significant at p = 0.99. We find a steep slope and
a strong correlation of high significance indicating a dominance of
evaporation/precipitation in controlling the surface δ18O–SSS relation
in this region. In the Subantarctic/Polar Frontal Zone (Cluster-4; 44° S
to 54° S; Fig. 4f), the δ18O–SSS relationship is δ18O = (0.51± 0.06)
SSS-(17.45 ±2.18); r2 =0.44; n = 111; significant at p = 0.99. The
slope is steep here with a significant coefficient indicating dominance
of evaporation/precipitation. This is a cyclonic region characterized by
strong winds and therefore experiences high evaporation/precipitation,
which was also observed by Srivastava et al., 2007. The data from the
Antarctic Zone (Cluster-5; 54° S to 68° S; Fig. 4g) exhibits a δ18O–SSS
slope of 0.11± 0.05; r 2 = 0.09; n = 51; significant at p = 0.95, which implies an increasingly dominant role played by sea ice melting/freezing.
The low slope reflects the fact that sea ice melting/freezing alters the salinity [salinity of sea ice is low (around 7; Meredith et al., 2008) as
brines are expelled during sea-ice formation increasing the seawater
salinity] but has very little effect on the δ18O because of small isotope
fractionation between seawater and ice (Beck and Münnich, 1988;
Melling and Moore, 1995). In the southern subtropical Indian Ocean,
the Subantarctic/Polar Frontal Zone, and the Antarctic Zone, the data
of the present study is similar to the data of the earlier studies. A few
data points from earlier studies and from the present study (in the
case of Antarctic Zone) do exhibit wider spread of salinity, which imply
the existence of varying meteorological conditions during different periods of sample collection reiterating the need for accounting the temporal variability. The δ18O–SSS slope values of distinct water masses
incorporating long-term variability presented in the Fig. 4 of this study
are more representative of their respective regions and would therefore
help in the more accurate paleosalinity determination.
4. Conclusion
This new data set elucidates the spatially and temporally varying relationship between δ18O and sea surface salinity from one of the least
studied regions of the world viz. Indian sector of the Southern Ocean
and the adjoining Indian Ocean. This relationship, in the region north
of the 54° S, appears to be governed predominantly by evaporation/
precipitation (represented as Clusters 1, 2, 3 and 4 in this study). In contrast, in the Antarctic Zone (Cluster 5), sea ice melting/freezing plays a
dominant role governing the δ18O–SSS relationship. The fact that the
δ18O–SSS slope in the Antarctic Region (beyond Polar Front) is much
lower than the region prior to the Polar Front attests to the dominance
of sea ice melting beyond it. Based on coupled measurement of isotopes
and salinity, we observed the presence of Subtropical Front and Polar
front at 44° S and 54° S latitude respectively. The effect of continental
ice melt is observed only at the southernmost location at 66.73° S latitude. Importantly, this study presents specific region-wise, long-term
values for δ18O–SSS slope that will help to more accurately determine
the salinity contribution to oxygen isotopes of carbonates.
Supplementary data to this article can be found online at http://
dx.doi.org/10.1016/j.jmarsys.2013.01.001.
Acknowledgment
This is NCAOR contribution no. NCAOR Contribution no. 01/2013.
We thank ISRO-GBP for support. We take this opportunity to thank
the Chief Scientist and colleagues on-board and crew of the ORV
Sagar Nidhi for help during sample collection. We are also grateful
to the two anonymous reviewers for providing constructive criticism.
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