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Keywords:

  • mixed layer salinity;
  • tropical Indian Ocean

Abstract

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data
  5. 3. Analysis and Discussion
  6. 4. Summary
  7. Acknowledgments
  8. References

[1] A subset of the recently published salinity database of the global oceans is utilized to characterize and explain the observed seasonal variability of sea surface salinity of the north Indian Ocean, in greater detail than has been possible previously. The influence of salinity on the seasonal evolution of near-surface mixed layer depth is highlighted. The relative importance of freshwater flux (evaporation minus precipitation) and horizontal advection in accounting the observed seasonal variability of sea surface salinity is evaluated. The influence of massive river outflow in producing the observed sea surface salinity minima in the coastal northwestern Bay of Bengal during August–September is highlighted. The observed interannual variability of sea surface salinity along two major shipping lanes in the tropical Indian Ocean in relation to El Niño is examined. The annual average of sea surface salinity shows contrasting distributions in the Arabian Sea and the Bay of Bengal due to differences in hydrological forcing. The seasonal variability of sea surface salinity is most pronounced in the coastal region of the northern Bay of Bengal, northwestern Arabian Sea, and the southeastern Arabian Sea. The incorporation of salinity effect reduces the thickness of the near-surface mixed layer, and this reduction is most pronounced in the Bay of Bengal, where it builds up from June to July and becomes most prominent by February in the following year, when the freshening effects of hydrological forcing through local rainfall and river discharges are felt the most on the near-surface layers. The salt budget analysis of the mixed layer shows a broad agreement between the patterns of observed and diagnosed seasonal changes caused by freshwater flux and horizontal advection, despite limitations in the accuracy of these estimates. The freshwater input through rainfall and river discharges in the Bay of Bengal far exceeds evaporation, causing surplus freshwater for export. Horizontal advection of salinity is found to be important in the southeastern Arabian Sea during winter and in the western and eastern Arabian Sea during the summer monsoon season and in the Bay of Bengal throughout the year with the exception of premonsoon season. The pronounced dilution observed during the height of the summer monsoon season in the coastal northwestern Bay of Bengal is attributed to peak discharges from major rivers. Historic data along two major shipping lanes in the tropical Indian Ocean have clearly revealed the signature of El Niño in the interannual variability of sea surface salinity.

1. Introduction

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data
  5. 3. Analysis and Discussion
  6. 4. Summary
  7. Acknowledgments
  8. References

[2] In the tropics, the ocean's role in absorbing and transporting heat and freshwater is not thoroughly understood; indeed, in the tropical Indian Ocean (TIO), research on this subject is still at a fairly early stage [Godfrey et al., 1995]. After temperature, salinity is the most important physical property of the seawater that controls its dynamic and thermodynamic behavior. It provides a measure of intensity of the ocean hydrological cycle, which is one of the least understood components of the climate system [Schmitt, 1994; Webster, 1994]. It contributes to the formation of water masses and determines the depth of penetrative convection and thermohaline circulation of the global ocean [Huang, 1993; Pierce et al., 1995]. Salinity plays an important role in controlling near-surface vertical mixing, with relevant vertical scales that are smaller than those of the surface isothermal layer detectable from XBT sampling. This is especially true in areas of excess precipitation, where it can strongly stratify the near-surface region and reduce the response time of SST to surface fluxes. Thus the vertical structure of salinity also contributes to the definition of the near-surface mixed layer depth and its dynamics [Lukas and Lindstrom, 1991; Sprintall and Tomczak, 1992; Murtugudde and Busalacchi, 1998; Han et al., 2001]. The salinity is shown to indirectly influence the evolution of mixed layer temperature in regions of near-surface haline stratification [Moshonkin and Harenduprakash, 1991; Rao and Sanil Kumar, 1991; Rao and Sivakumar, 1999; Howden and Murtugudde, 2001] and salinity jump below near-surface isothermal layer [Miller, 1976; Rao, 1986]. Numerical models with inclusion of salinity effects have shown to reproduce better simulations of the tropical oceanic processes [Cooper, 1988; Murtugudde and Busalacchi, 1998]. The incorporation of upper ocean salinity data into assimilative ocean models provides an additional method of constraining the surface water fluxes [Schmitt, 1994]. Such data are also necessary for improved estimation of the freshwater budget of the oceans. Despite its importance, the total number of historic salinity measurements is smaller by at least two orders of magnitude in the TIO compared to temperature measurements, due to inherent difficulties in measurement practices. Thus, much of our current knowledge on the spatiotemporal variability of the salinity structure of the oceans is based on relatively sparser measurements.

[3] The evolution of salinity is governed by several processes such as evaporation, precipitation, river runoff, formation and melting of sea ice, and internal ocean dynamics such as circulation and mixing of water masses. However, the relative importance of these processes is not known accurately as most of these processes are not directly measured but are only indirectly estimated, with yet unknown errors. With the available data sets, several authors have investigated the observed seasonal and interannual variability of freshwater forcing and salinity of the tropical Atlantic [Taylor and Stephens, 1980; Schmitt et al., 1989; Levitus, 1989; Yoo and Carton, 1990; Dessier and Donguy, 1994; Reverdin et al., 1994; Montogomery and Schmitt, 1994; Reverdin, 1995] and of the tropical Pacific [Piola and Gordon, 1984; Delcroix and Henin, 1991; Donguy, 1994; Tomczak, 1995; You, 1995; Delcroix et al., 1996]. Levitus [1982, 1986] used all the available salinity measurements to generate global ocean salinity climatology, and found a pronounced annual cycle in the tropics in association with the location of the Intertropical Convergence Zone (ITCZ). In the recent past several interesting results emerged from TOGA COARE. Cronin and McPhaden [1998] have found that excess surface fresh water flux (P-E) was balanced primarily by vertical mixing and zonal advection. Feng et al. [1998] have reported that advection terms are important in the salt balance of the mixed layer and meridional advection dominates over zonal and vertical advection acting to increase salinity in the surface layer. Delcroix and Picaut [1998] have found that the zonal displacements of the eastern edge of the western equatorial Pacific fresh pool {sea surface salinity (SSS) < 35‰} during 1974–1989 marked by a salinity front and closely related to the eastern edge of the warm pool, were dominated by interannual variation that are highly correlated with the Southern Oscillation Index (SOI). Henin et al. [1998] have reported strong SSS variability at seasonal and interannual timescales that is attributed to the successive passages of a zonal salinity front trapped in the equatorial band (5°N–5°S) and migrating in phase with the SOI.

[4] Studies on salinity variability in the TIO are few, and no study is reported in the literature on the dynamics of SSS and its interannual variability due to extreme scarcity of measurements. Although few studies on the variability of rainfall over the TIO are reported in the literature [Rao et al., 1989, Martin et al., 1993; Rameshkumar and Prasad, 1997] no study examining the relationship between the freshwater flux and SSS in the TIO is reported. Most of the studies on salinity were based on measurements made during special observational campaigns. Rochford [1964] described the observed salinity maximum in the upper 1000m of the North Indian Ocean (NIO). Wyrtki [1971] presented distributions of bimonthly SSS and yearly subsurface salinity for the Indian Ocean. Sastry and D'Souza [1972] described the observed salinity structure of the Arabian Sea (AS) during the summer monsoon season. Toole and Raymer [1985] and Fu [1986] estimated the freshwater budget of the Indian Ocean. Using the historic data, Hastenrath and Grieschar [1989] presented distributions of 6-monthly averages of salinity at the surface, 100m and 300m depths for the TIO. Sprintall and Tomczak [1992] found that monsoon rainfall and river runoff contribute significantly to the freshwater flux, producing salt stratification in the surface layers of the eastern equatorial Indian Ocean. Using Levitus [1982] salinity climatology, Shenoi et al. [1993] identified four extrema, three maxima and one minimum in the salinity distribution of the AS. Shetye [1993] has examined the movement and implications of the Ganges-Bramhaputra runoff on the SST of the northern BB. Considering bimonthly distributions, Donguy and Meyers [1996] found seasonal variability of SSS over the western Indian Ocean to be larger and extensive, while it is smaller and localised in the eastern Indian Ocean due to local rainfall and river runoff. Using a subset of Levitus et al. [1994] climatology, Conkright et al. [1994] produced an atlas describing the annual and seasonal (three month averages) evolution of salinity field at selected depths in the TIO. Hareeshkumar and Mathew [1997] have studied the seasonal variability of the near-surface salinity distribution in the AS. Prasannakumar and Prasad [1999] have studied the formation and spreading of Arabian Sea High Salinity Water Mass. Shankar [2000] reported that large inflow of fresh water into the seas around India forces large changes in salinity, and hence, in coastal sea level. Han et al. [2001] has studied the influence of salinity on dynamics, thermodynamics and mixed layer physics of the TIO in a 4.5 layer nonlinear model. Han and McCreary [2001] have simulated the SSS of the TIO with a 4.5 layer model with active thermodynamics and mixed layer physics invoking various forcing mechanisms. Using a reduced gravity primitive equation ocean model, Howden and Murtugudde [2001] have studied the influence of river inputs on the SST of the BB. As the evolution of SSS is fully three-dimensional, an ocean GCM with good mixed layer physics can only resolve the relative importance of different mechanisms that produce the observed seasonal variability of SSS in the NIO. However, none of these studies have attempted to address the influence of salinity in the evolution of the mixed layer depth, and to estimate the salt budget of the mixed layer of the NIO utilizing the observed database. Recently Conkright et al. [1998] updated Levitus [1982] and Levitus et al. [1994] climatologies to provide a comprehensive description on the physical and chemical properties of the global ocean. The availability of enriched SSS database of Conkright et al. [1998] has provided a unique opportunity for a refined description of the annual cycle of the SSS, and to address the above mentioned issues for the NIO. Utilizing climatologies of several relevant parameters, Rao and Sivakumar [2000] have attempted to explain the observed seasonal variability of sea surface temperature (SST) of the TIO but no such study was reported in the literature for SSS of the NIO. In this context there is a place for a purely observational study such as the present one. In this study, subsets of the new global ocean salinity and temperature climatologies, and monthly climatologies of near-surface flow, evaporation, precipitation, river discharges into the Bay of Bengal (BB) are utilized to (1) describe the observed seasonal variability of SSS in the NIO, (2) highlight the importance of salinity in the seasonal evolution of the near-surface mixed layer depth of the NIO, (3) assess the relative importance of freshwater flux and advection on the salt budget of the near-surface mixed layer of the NIO, (4) examine the influence of river discharges on the variability of SSS in the BB (5) describe the observed interannual variability of SSS along two major shipping lanes in the TIO.

2. Data

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data
  5. 3. Analysis and Discussion
  6. 4. Summary
  7. Acknowledgments
  8. References

[5] The monthly mean climatologies of all the relevant surface marine meteorological, near-surface oceanographic and hydrological parameters available in the literature used in this study are near-surface salinity [Conkright et al., 1998; Donguy and Meyers, 1996], near-surface temperature [Conkright et al., 1998], evaporation [Rao et al., 1989, 1991], rainfall [Legates and Willmott, 1990], near-surface circulation [Cutler and Swallow, 1984], and river discharges [United Nations Educational, Scientific, and Cultural Organization (UNESCO), 1969, 1971a, 1971b; Dumenil et al., 1993].

[6] Conkright et al. [1998] assembled, quality controlled and composited all the historical station (exclusive of the post-TOGA Ship of Opportunity thermosalinograph network) and CTD data available with NODC (National Oceanographic Data Center, Washington DC) as of 1998. This database has a greater coverage in space and time than ever before, as a result of NODAR (NODC Oceanographic Data Archaeology and Rescue) and GODAR (Global Oceanographic Data Archaeology and Rescue) Projects, and receipt of other special data sets. Additional salinity data that were used by Conkright et al. [1998] significantly improved the spatiotemporal distribution of observations to describe the salient features of the annual cycle with greater confidence limits. Accordingly the database for the NIO is richer in density than the earlier compilations of Wyrtki [1971], Robinson et al. [1979], Levitus [1982], Hastenrath and Greischar [1989], and Levitus et al. [1994]. The merged database was objectively analyzed and the gridded fields at standard depths were generated on a 1° resolution for all twelve calendar months. A subset of these objectively analyzed fields of SSS for all the twelve calendar months, on a 1° grid is used in this study. The temperature data set of Conkright et al. [1998] is used in the estimation of near-surface mixed layer depth. The monthly climatologies of rainfall [Legates and Willmott, 1990] and evaporation estimated with COADS surface marine meteorological data [Woodruff et al., 1987; Rao et al., 1989, 1991] following Large and Pond [1982], are utilized for the estimation of freshwater flux (i.e., evaporation minus precipitation) into the ocean. The evaporation estimates for both light and strong wind conditions, common in the NIO probably need some revision as the presently available bulk aerodynamic formulations are not adequately calibrated for extreme wind conditions. The monthly rainfall climatology might also need major improvement as the errors are not known due to lack of adequate direct measurements at sea for calibration. The ship drift vectors compiled by Cutler and Swallow [1984] are used for the estimation of horizontal advection of salinity. The observed river discharges from major rivers are used to highlight their influence on the variability of the SSS in the BB. The measurements of SSS are utilized to map and describe the observed interannual variability during 1982–1994 along two major shipping lanes in the TIO.

3. Analysis and Discussion

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data
  5. 3. Analysis and Discussion
  6. 4. Summary
  7. Acknowledgments
  8. References

3.1. Annual Average and Variance of SSS

[7] The distributions of the historic SSS stations, annual average and variance of SSS are shown in Figure 1. The SSS data are relatively denser in the western TIO and in the coastal regions. The distribution of annual average SSS shows a very distinct pattern in the TIO with primary maxima in the northern AS, secondary maxima in the southern TIO and minima in the northern BB. From the head BB, the SSS progressively increases toward northern AS. Although located in the same latitude band, both the AS and BB exhibit very contrasting SSS distributions due to large differences in local hydrological forcing. In the equatorial region, the AS high saline waters flow eastward. South of the equator, a tongue of low saline waters, with an east-west gradient driven by Indo-Pacific throughflow is present. South of this low saline east-west tongue, another zonal band of moderately high saline waters (>35.5‰) with strong meridional gradient is noticed. In the equatorial region the meridional gradient is weaker than the zonal gradient. In the off-equatorial region the zonal gradient is much weaker than the meridional gradient. The annual variance of SSS is more pronounced in the NIO compared to that of in the southern TIO due to strong seasonality in the local hydrological forcing and reversal of near-surface circulation driven by the seasonal monsoons. Pronounced variance with onshore maxima occurs in the northern and coastal regions of the BB, off the Arabia coast and off southwest India where horizontal gradients are also marked.

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Figure 1. Maps showing data density, annual average, and annual variance of SSS for the tropical Indian Ocean.

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3.2. Annual Cycle of SSS

[8] As the annual variance of SSS is pronounced only in the NIO, the analysis in this study is limited to NIO. The multiyear averaged monthly mean SSS distributions (Figure 2a) show several features of interest and the contrast between the distributions of the AS and the BB is quite obvious even on monthly resolution. The SSS in much of the AS is in excess of 35‰ during the entire year primarily due to excessive evaporation over precipitation. In the AS, the clockwise (anticlockwise) gyral circulation during summer monsoon (winter) season determines the north-south oscillation of 36‰ salinity contour. In the southeastern AS relatively low saline waters advected from the BB appear during January–April resulting in a gradient normal to the west coast of India. Advection of these low saline waters from the BB and north equatorial Indian Ocean into the southeastern AS is very well simulated in a fine resolution model of Semtner and Chervin [1992]. During the summer monsoon the high saline AS waters show their pathways into the southern BB. Schott et al. [1994] have documented on the Southwest Monsoon Current south of Sri Lanka from direct current measurements. Vinayachandran et al. [1999] have studied the intrusion of Southwest Monsoon Current into the BB from the circulation derived from historic ship drifts, dynamic topography, and TOPEX sea surface height anomalies and in a OGCM solution. Advection of low salinity waters by Somalia Current into the western AS during summer monsoon is also clearly seen [Swallow et al., 1983]. The SSS in the BB shows rich structure with onshore minima in particular during summer and postsummer monsoon months. During these seasons very intense horizontal gradients in SSS occur in the northwestern and northeastern BB. In a nonlinear 4.5 layer model with active thermodynamics and mixed layer physics, Han et al. [2001] have shown that the BB river runoff has improved the simulated SSS fields within the BB and along the west coast of India.

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Figure 2a. Annual cycle of SSS for the north Indian Ocean.

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[9] The SSS fields are subjected to Fourier analysis [Jenkins and Watts, 1968] to resolve the relative importance of different harmonics of the observed annual cycle. Most of the variance is explained by the first two harmonics (CPY = 1, 2) over much of the basin. The distribution of amplitude of the annual harmonic (CPY = 1) shows coherent spatial patterns (Figure 2b). The most prominent signals with onshore maxima are noticed in the northwestern and northeastern BB and in the southeastern AS. In the AS, where pronounced seasonal reversal occurs in the flow patterns [Schott, 1983], the SSS maxima shows a clear southeastward propagation from off Arabia and Somalia coasts during March to September. In the southeastern AS, the SSS maxima propagates from off southwest India to the interior from July–August to October. In the northwestern BB an offshore propagation of SSS maxima during March–April to September is noticed. Although large amplitude semiannual harmonic (CPY = 2) is seen in the northwestern and northeastern BB, it is not supported by large variance.

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Figure 2b. Distribution of amplitude, percent variance, and phase of the annual (CPY = 1) and semiannual (CPY = 2) harmonics of SSS for the north Indian Ocean.

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3.3. Influence of Near-Surface Salinity on Mixed Layer Depth

[10] Descriptions on the seasonal variability of the mixed layer depth derived only from temperature profiles are available for the TIO [Wyrtki, 1971; Robinson et al., 1979; Rao et al., 1989, 1991; Rao and Sivakumar, 1996]. However, the upper ocean is usually not equally well mixed both in temperature and salinity. The variation in salinity, supposedly produced by either horizontal advection of low saline waters and by freshwater flux at the surface, reduces the surface buoyancy flux. This reduction limits surface mixing to a shallow halocline, creating a barrier layer between the bottom of the mixed layer and the top of the thermocline [Lukas and Lindstrom, 1991]. Clearly, the mixed layer has to be defined relative to both temperature and salinity. The fresh water at the surface, in conjunction with the saline layer below, increases the stability of the column, effectively decreasing the turbulent mixing length. With less mixing, the temperature of the fresh surface layer can increase. In the literature, the near-surface mixed layer depth (MLD) is defined in several ways [Lukas and Lindstrom, 1991; Kara et al., 2000]. A net change in the physical property as temperature, salinity and density from the surface value, or the depth of occurrence of a critical gradient in the physical property was considered in several studies to define the mixed layer depth [Wyrtki, 1964; Bathen, 1972; Levitus, 1982]. The influence of near-surface halocline in the definition of the mixed layer of the global oceans was examined by Sprintall and Tomczak [1992]. Their study has compared two techniques of determining the mixed layer depth, one (MLDt) based on a 0.5°C change from SST and the other (MLDts) on a variable σt criterion. The latter method involves calculating the coefficient of expansion with surface values of temperature and salinity to determine σt difference required to obtain a temperature difference equal to 0.5°C. The difference in depths (MLDt−MLDts) produced by the two criteria is attributed to salinity stratification. In this study, the mixed layer depth is estimated employing both the methods. The MLDts is calculated by interpolating the deepest depth at which,

  • equation image

where σt(z=0) is the surface σt value, ΔT the desired temperature criterion (1°C, following Wyrtki [1971]) and dσt/dt is the coefficient of thermal expansion evaluated with the surface values of temperature and salinity.

[11] The difference fields between MLDt and MLDts are contoured (Figure 3) to highlight the influence of near-surface salinity effects on the seasonal evolution of MLD. The basin scale monthly distributions show a great deal of spatial structure and seasonal variability. The incorporation of salinity effects reduces the thickness of the mixed layer. In the BB, these differences build up from June to July, and attain maximum during the following February, when the freshening effects of hydrological forcing through local rainfall and river discharges are felt the most on the near-surface waters. These differences begin to weaken from February and attain minima during May, i.e., before the commencement of the summer monsoon season. In the AS, the difference fields are relatively less marked due to weaker hydrological forcing. However, the entry of low saline waters as East India Coastal Current and as North Equatorial Current into the southeastern AS during November to March [Cutler and Swallow, 1984], produces a maxima off southwest India during January–February, which propagates offshore during the following two months under the influence of a mode 2 Rossby wave shown in numerical simulations [Jensen, 1991; Perigaud and Delecluse, 1992; McCreary et al., 1993; Bruce et al., 1998]. Another maxima occurs in the southcentral AS during the height of the summer monsoon season where the deepening of the near-surface isothermal layer is greatest due to Ekman pumping effects [Bauer et al., 1991]. The maxima in the eastern equatorial region during monsoon transitions is attributed to eastward propagating downward Kelvin waves [Han et al., 1999] associated with Wyrtki Jets [Wyrtki, 1973].

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Figure 3. Monthly differences between mixed layer depth with and without salinity effects for the north Indian Ocean (areas of differences are shaded with increasing intensity).

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3.4. Salt Budget of the Near-Surface Mixed Layer

[12] The mixed layer salinity storage rate over an annual cycle is primarily governed by freshwater flux (residual of evaporation, precipitation, and river discharges), horizontal advection and entrainment across the mixed layer base. The contribution of horizontal mixing could also be important in regions where horizontal gradient in flow and salinity are strong. Following Sui et al. [1991] and Delcroix and Henin [1991], the time averaged salt conservation equation for the mixed layer may be written as

  • equation image

where

S

vertically averaged mixed layer salinity (‰)

t

time unit (month)

E

evaporation (m/month)

P

rainfall (m/month)

h

mixed layer depth, MLDts(m)

u

zonal component of flow inferred from ship drift vectors (m/month)

v

meridional component of flow inferred from ship drift vectors (m/month)

wh

vertical advection below mixed layer inferred from 20°C isotherm topography; (m/month)

H

Heaviside step function {= 0 if (wh + dh/dt) < 0), = 1 if (wh + dh/dt) > 0}

Sh

salinity just below the mixed layer base (‰).

[13] All the four terms of the equation (2) are estimated for each month and their respective distributions for four representative seasons i.e., winter (December–February), presummer monsoon (March–May), summer monsoon (June–August), and postsummer monsoon (September–November) seasons are shown in Figures 4a, 4b, 4c, and 4d. Here the mixed layer (MLDts) salinity estimated from the database of Conkright et al. [1998] is considered equivalent to SSS. The SSS variability due to entrainment is not shown separately due its small magnitude. The diagnosed change in SSS is the sum of respective contributions from fresh water flux, horizontal advection and entrainment. Positive (negative) values imply increase (decrease) in SSS during the season. Coherent patterns of SSS changes are clearly seen from these distributions. Despite constraints in both accuracy and adequacy of measurements or estimates, the relative importance of these processes in the space-time domain has clearly emerged. However, a word of caution would be in order while interpreting the diagnosed and observed SSS variability in the eastern BB where measurements are relatively sparse.

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Figure 4a. Distribution of seasonal diagnosed and observed changes (‰/3 months) of the mixed layer salinity with respective contributions from freshwater flux and horizontal advection during winter (December–February) for the north Indian Ocean.

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Figure 4b. Same as Figure 4a but for premonsoon (March–May).

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Figure 4c. Same as Figure 4a but for summer monsoon (June–August).

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Figure 4d. Same as Figure 4a but for postmonsoon (September–November).

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[14] During winter the SSS change due to fresh water flux is relatively smaller than that of due to horizontal advection (Figure 4a). The cold and dry continental northeasterly winds cause excessive evaporation over rainfall over the AS and northern BB. This excess is pronounced over the head BB causing an increase in SSS. In the region between the BB (south of 8°N) and the equator the rainfall exceeds evaporation causing a decrease in SSS around Sri Lanka and off Sumatra coast. Relatively low saline waters are brought into the southeastern AS both by East India Coastal Current and North Equatorial Current producing significant dilution there. Large reduction in SSS is also seen over the northeastern BB due to offshore advection of low saline waters diluted by river outflow during the postmonsoon season. An increase in SSS in the western BB is attributed to clockwise gyral advection of relatively high saline waters from south. Thus the near-surface circulation dominates the evolution of SSS field in the NIO during winter. However, the reasons for pronounced disagreement between diagnosed and observed SSS change in the eastern BB are not clear. As mentioned earlier insufficient data could be a possible candidate in such cases. During presummer monsoon season, in general the SSS changes are least both in the AS and BB (Figure 4b). Freshwater flux produces reduction in SSS in the northeastern BB. In the northwestern BB the observed increase in SSS is accounted by both freshwater flux and advection where the qualitative agreement between diagnosed and observed variability in SSS is good. The disagreement is most conspicuous off southwest India and south of Sri Lanka.

[15] During the summer monsoon season, freshwater flux causes significant dilution in the eastern AS and northern BB with onshore maxima (due to orography effects and river discharges) (Figure 4c). The advective contribution with smaller space scales is more pronounced in the eastern and western AS, and in the BB, where strong seasonal circulation and horizontal gradients in SSS occur. The effect of clockwise gyral circulation is clearly seen in the AS, with a decrease (increase) in SSS in the western (eastern) region. The SSS increased off southeast of Sri Lanka with a northeastward extension attributed to Southwest Monsoon Current. In general, the agreement in the patterns of diagnosed and observed seasonal changes in the SSS are the most striking in the southeastern AS and northwestern and central BB although their corresponding magnitudes differ. During the postmonsoon season the fresh water input is most pronounced in the northeastern and northwestern BB, southwest of Sri Lanka and off the west coast of India (Figure 4d). Horizontal advection also contributes to significant reduction in SSS in these areas with the exception of north central BB. The agreement between diagnosed and observed seasonal changes in SSS is reasonably good in the northeastern BB and southwest of Sri Lanka. The most conspicuous discrepancy, however, occurs in the northwestern BB. Intense freshening at the surface has occurred in the western BB with onshore maxima, where river outflows are advected offshore.

[16] Among all the four seasons, the best agreement between diagnosed and observed changes is seen during the summer monsoon season due to large amplitude signals. Although differences in magnitudes are present, the patterns of the signals in the AS and BB are best captured confirming the importance of horizontal redistribution of salinity in the NIO during this season.

3.5. Influence of River Discharges on the SSS in the BB

[17] The freshwater discharges from rivers are well known for their dilution effects on the near-surface salinity distribution in the coastal seas. However, the relative importance of rainfall and river discharges in freshening the near-surface layers of the BB is not clarified in the literature. The available climatologies of rainfall [Legates and Willmott, 1990], river discharges [UNESCO, 1969; Dumenil et al., 1993] and evaporation [Rao et al., 1989, 1991] are used to examine the annual cycles of evaporation (E), precipitation (P) and river runoff (R) for the entire BB (north of 8°N) (Figure 5). All the three elements show very well defined seasonal variability. The E shows a bimodal distribution with maxima during summer monsoon and winter seasons. On the other hand, both P and R show unimodal distributions with peaks during July and August respectively. The residual of P + R − ∣E∣ is positive almost throughout the year, reaching maximum during the height of the summer monsoon season. The corresponding area averaged (north of 8°N) annual cycle of SSS is seen as a mirror image of the annual cycle of the freshwater budget. The estimated annual evaporation and rainfall, and observed river discharges for the BB are 119, 224 and 52 cm/year, respectively. This implies that nearly 20% of the total freshwater input to BB comes from river discharges. These estimates also indicate that over a year, the BB receives a surplus of 157 cm/year, which needs to be redistributed through horizontal circulation and intense vertical mixing during transient disturbed weather associated with monsoon depressions and cyclonic storms.

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Figure 5. Annual cycle of evaporation (E), rainfall (P), river discharges (R) from all the major rivers flowing into the BB, P + R − ∣E∣, SSS for the entire BB (north of 8°N), and the annual cycle of discharge from major rivers and SSS of the coastal northwestern BB (shaded boxes in the map).

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[18] The observed discharge data for five major rivers along the east coast of India, namely, Bramhaputra, Ganges, Mahanadi, Godavari, and Krishna are examined to seek a relationship with the SSS of the coastal northwestern BB (shaded boxes). All these rivers show a pronounced annual cycle with peak discharges during the height of the summer monsoon season (Figure 5). The freshening effects of these river discharges are very well reflected in the observed annual cycle of SSS of the coastal northwestern BB. The total discharge of all the five rivers is highest during August while the SSS of the coastal northwestern BB is lowest during August–September.

3.6. Interannual Variability of SSS During 1982–1994

[19] Although considerable literature exists on the observed interannual variability of SST of the TIO [Fieux and Stommel, 1976; Brown and Evans, 1981; Cadet and Dhiel, 1984; Rao and Goswamy, 1988; Rao et al., 1996], no study has reported observed interannual variability of SSS due to scarcity of measurements. An examination of the historic SSS data assembled by Donguy and Meyers [1996] for the TIO revealed that only two shipping lanes (La Reunion to Gulf of Aden-a meridional transect representing the western TIO and Gulf of Aden to Singapore-a near-zonal transect representing NIO) could be considered to resolve the observed interannual variability in the SSS. The evolution of SSS along these two shipping lanes during 1982–1994 is shown as Hovmuller diagrams (Figure 6). A careful examination of these diagrams clearly reveals that the annual cycle of SSS shows year-to-year variability both in amplitude and phase. For instance, in the near-zonal section, the SSS did not reach 36.5‰ (boxes 5–11) only during 1982, 1983, and 1987, the years of pronounced El Niño. The southeastern BB also shows considerable variability with the occurrence of waters <34‰ only during 1982–1983, 1986–1987, and 1991–1992 the years of pronounced El Niño. In the meridional section, the northward penetration of waters <35.5‰ is seen only during 1982–1983, 1987–1989, and 1991–1993 the years of pronounced El Niño. This reported interannual variability cannot be explained due to lack of accurate and adequate measurements on freshwater flux and near-surface circulation on interannual timescale.

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Figure 6. Interannual variability of SSS along two shipping lanes in the tropical Indian Ocean (La Reunion to Gulf of Aden and Gulf of Aden to Singapore) during 1982–1994 (regions of higher salinity are shaded with increasing intensity).

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4. Summary

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data
  5. 3. Analysis and Discussion
  6. 4. Summary
  7. Acknowledgments
  8. References

[20] The annual average SSS shows primary maxima in the northern AS, secondary maxima in the southern TIO and minima in the northern BB. The annual variance of SSS is more pronounced in the NIO with onshore maxima occurring in the northern and coastal regions of the BB, off Arabia coast and off southwest India. In the southeastern AS, the SSS maxima propagate from off southwest India to the interior from July–August to October. In the northwestern BB an offshore propagation of SSS maxima during March–April to September is noticed. The incorporation of salinity effect reduces the thickness of the mixed layer. In the BB, these differences build up from June to July and attain maximum during the following February, when the freshening effects of hydrological forcing through local rainfall and river discharges are felt the most on the near-surface waters. These differences begin to weaken from February and attain minima during May, i.e., before the commencement of the summer monsoon season. Despite constraints in both accuracy and adequacy of measurements or estimates, the relative importance of fresh water flux, horizontal advection and entrainment on the salt budget of the mixed layer has clearly emerged in the space-time domain. During winter, the horizontal advection overwhelms local fresh water flux in producing large variability in SSS. During presummer monsoon season, the variability due to fresh water flux and horizontal advection is relatively low in comparison with that of during winter. During the summer monsoon season, freshwater input causes significant dilution in the northern BB and eastern AS with onshore maxima (due to orography effects and river discharges). The advective contribution with smaller space scales is more pronounced in the eastern and western AS, and the BB. During the postmonsoon season the fresh water input is most pronounced in northeastern and northwestern BB and southwest of Sri Lanka. Horizontal advection also contributes to significant reduction in SSS in these regions. Among all the four seasons, the best agreement between diagnosed and observed changes is seen during the summer monsoon season due to large amplitude signals. In the BB north of 8°N the residual of P + R − ∣E∣ is positive almost throughout the year, reaching maximum during the height of the summer monsoon season when the SSS is minimum. Historic SSS data along two major shipping lanes clearly show interannual variability both in amplitude and phase associated with El Niño. For instance, in the near-zonal section, the SSS did not reach 36.5‰ (boxes 5–11) only during 1982, 1983, and 1987, the years of pronounced El Niño. The southeastern BB also shows considerable variability with the occurrence of waters <34‰ only during 1982–1983, 1986–1987, and 1991–1992 the years of pronounced El Niño. This study on the salt budget of the mixed layer has clearly revealed how the ocean circulation is crucial in the redistribution of the fresh water flux within the ocean and how these fluxes effect the ocean circulation by changing the mixed layer depth. However, our current understanding on SSS variability would significantly improve when adequate high quality measurements on salinity, evaporation, precipitation, river runoff and near-surface flow by instrumented buoys, floats, satellites and river outflow gauges become routinely available.

Acknowledgments

  1. Top of page
  2. Abstract
  3. 1. Introduction
  4. 2. Data
  5. 3. Analysis and Discussion
  6. 4. Summary
  7. Acknowledgments
  8. References

[21] Highest appreciation is placed on record for the excellent compilation of historic data sets by several individuals; near-surface salinity and temperature by Dr. Conkright and his coworkers and Drs. Douguy and Meyers, marine meteorological elements by Dr. Woodruff and his coworkers, rainfall by Drs. Legates and Willmott, ship drift vectors by Mr. Cutler and Dr. Swallow, and river discharges by Dr. Wolfgang and his coworkers, used in this study. The encouragement and the facilities provided by the Director, NPOL are gratefully acknowledged. The comments from two anonymous reviewers and Dr.L.M.Rothstein are very helpful in the revision of the manuscript.

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  3. 1. Introduction
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  5. 3. Analysis and Discussion
  6. 4. Summary
  7. Acknowledgments
  8. References
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