1. Introduction
The western boundary current (WBC) of the Bay of Bengal (BOB or the bay), also known as the East India Coastal Current (EICC), follows a seasonal reversal (Cutler and Swallow 1984; Shankar et al. 1996; McCreary et al. 1993, 1996; Vinayachandran et al. 1996; Sil and Chakraborty 2011). The EICC is northward during pre–Indian summer monsoon (ISM) and southward during post-ISM (Shetye et al. 1990, 1991; Sil and Chakraborty 2011). The northward EICC is best developed in March–April and dissipates in early May (Potemra et al. 1991; Shetye et al. 1993), whereas the southward EICC peaks in November and decays in early December (Babu et al. 1991; Shetye et al. 1996). Therefore, in pre- and post-ISM, EICC is well directed and continuous along the western boundary of the bay. The basin-scale circulation during pre-ISM (post-ISM) remains anticyclonic (cyclonic) in presence of anticyclonic (cyclonic) gyre in the western BOB (Legeckis 1987; Potemra et al. 1991; Vinayachandran et al. 1996; Shetye et al. 1993; Babu 1992; Somayajulu et al. 2003; Babu et al. 2003). During ISM, EICC does not show any consistent pattern like pre- or post-ISM (Suryanarayana et al. 1992) and a discontinuity exists along the boundary in the presence of several cyclonic and anticyclonic eddies (Das et al. 2019).
The geographic position of the BOB (5°–24°N, 78°–95°E) plays an important role in its dynamics owing to its parabolic and semi-open basin shape (Murty and Flather 1994), availability of huge freshwater from the surrounding rivers (Jana et al. 2015; Behara and Vinayachandran 2016) and seasonal reversal of strong monsoon winds (Suryanarayana et al. 1992). The possible mechanisms of EICC forcing have been examined extensively using different datasets and methods, such as the impact of local winds (Babu et al. 1991; Babu 1992; Shetye et al. 1991; Vinayachandran et al. 1996; Shankar et al. 1996; McCreary et al. 1993, 1996; Mukherjee et al. 2018), Kelvin and Rossby waves (Yu et al. 1991; Shankar et al. 1996; McCreary et al. 1993, 1996; Eigenheer and Quadfasel 2000; Rao et al. 2010), Ekman pumping (Shankar et al. 1996; McCreary et al. 1996), and river water influx (Babu et al. 1991; Babu 1992; Gopalakrishna et al. 2002; Jana et al. 2015, 2018; Behara and Vinayachandran 2016). A few studies have also showed the characteristics (Murty and Henry 1983; Sindhu and Unnikrishnan 2013) and dynamics of tides (Bhagawati et al. 2018) in the BOB, but its impact on circulation and ocean state variability are not well explored. Though several studies are carried to estimate the influence of these factors on the mechanism of seasonally reversing and continuous EICC, the influence on the EICC discontinuity during ISM is not well studied.
The study by Babu et al. (1991) showed that the eddies during the discontinuity (July–August) are generated between two opposing boundary currents, a freshwater-and-wind-stress-driven southward flow and a wind-driven northward flow. The contribution of equatorial remote forcing through the coastal Kelvin and Rossby waves due to monsoon winds also affect sea level (Han and Webster 2002) and seasonal circulation (Yu et al. 1991; McCreary et al. 1993) in the BOB. Eigenheer and Quadfasel (2000) reported that the seasonal upwelling and downwelling baroclinic topographic Rossby waves influence the EICC in northern BOB (north of 14°N), but below 14°N, trapped and free Rossby waves play a major role. During ISM, the boundary current is northward at south and southward at north with strong wind forcing (McCreary et al. 1993; Vinayachandran et al. 1996). Shankar et al. (1996) revealed that the interior Ekman pumping generated baroclinic and barotropic Rossby waves make northward (southward) coastal currents with anticyclonic (cyclonic) local wind stress curl. McCreary et al. (1996) showed that the interior Ekman pumping, remote alongshore winds, and equatorial forcing make the strong northward EICC during pre-ISM, but the strong southward EICC during post-ISM is influenced by the interior Ekman pumping and local alongshore winds. They have also mentioned that the weak northward flows from 10°N during ISM are wind driven. Conversely, Das et al. (2019) showed that the summertime discontinuity is characterized by (i) westward and southwestward moving cyclonic eddies (CEs) and anticyclonic eddies (ACEs) in between two opposing flows along the boundary, northward from 10°N and southward from 21°N, (ii) this northward flow from 10°N is driven by the local winds (June–August) and southern lateral forcing (September), (iii) the southward flow from 21°N is driven by Summer Monsoon Current (June–August) and strong positive wind stress curl (July–September).
The seawater characteristics in the bay are highly influenced by freshwater addition through precipitation and river runoff (Shetye et al. 1991; Murty et al. 1993; Behara and Vinayachandran 2016). During ISM, the suppressed coastal upwelling by the Ganges–Brahmaputra River inflow-driven coastal Kelvin waves increases the sea surface temperature (SST) by 0.5°–1°C along the northeast coast of India (Han et al. 2001). Sometimes, the eddies in the bay are confined to the subsurface and are not advected at the surface due to stratification by the freshwater (Babu et al. 1991; Gopalan et al. 2000). The southward EICC is predominantly driven by cross-shore density gradient due to large river input (Babu 1992). The low saline river discharge causes the southward propagation of large plume of warm low saline water from the head bay, above 18°N (Gopalakrishna et al. 2002; Jana et al. 2015, 2018).
Major tidal components estimated for the BOB are M2, S2, N2, K1, and O1 (Murty and Henry 1983; Sindhu and Unnikrishnan 2013). The semidiurnal tides (M2, S2, and N2) amplify nearly twice in the head bay while amplitude of diurnal tides (K1 and O1) reaches maximum (20 and 12 cm, respectively) in the Malacca Strait (Sindhu and Unnikrishnan 2013). Furthermore, tides are considered to be one of the major energy sources for ocean mixing (e.g., Kang and Fringer 2012). Again, the changes in relative sea level and stratification modulate the ocean response to tides (Müller et al. 2011; Müller 2012). Although the influence of tides on currents in BOB is studied by Bhagawati et al. (2018), a thorough analysis is required to estimate the influence of tides on surface currents, mixing, friction, and buoyancy [for instance, in the Yellow Sea by Lee and Beardsley (1999) and in the Yellow and East China Seas by Moon (2005)] associated with the EICC discontinuity.
The bay is very important in the Indian subcontinental weather and climate variability due to its contribution to the South Asian summer monsoon (Nair et al. 2018; Seetha et al. 2020). The complex air–sea interaction here (Bhat et al. 2001; Sanchez-Franks et al. 2018) leads to the genesis of a large number of tropical cyclones (Neumann 1993; Anandh et al. 2018, 2020). In the BOB, the western bay is of great significance because of its nonlinear dynamics due to the significant freshening at the top, Arabian Seawater mass intrusion at the bottom, seasonally reversing EICC, wind-driven strong upwelling/downwelling along the boundary, and various eddy activities. Again, the coastal currents, wind-driven upwelling/downwelling, and various eddy activities highly influence the sea level variability, air–sea exchange, upper-ocean mixing, and the energy distribution in the western BOB (Shenoi et al. 1999; Shankar 2000; Han et al. 2001; Han and Webster 2002; Cheng et al. 2013; Dandapat and Chakraborty 2016; Dandapat et al. 2018; Sanchez-Franks et al. 2018). During ISM, the western BOB exhibits a chaotic pattern in the presence of disorganized currents and numerous cyclonic and anticyclonic eddies (Das et al. 2019). Therefore, a thorough understanding of the dynamics of the BOB is critical to predict its ocean state during ISM (June–September). Furthermore, the influx of freshwater in the bay from the surrounding rivers affects the ocean currents and makes the air–sea interaction more nonlinear in a stratified condition (Jana et al. 2015, 2018; Behara and Vinayachandran 2016; Goswami et al. 2016; Chaudhuri et al. 2019). The influence of tide is also important to assess the currents, mixing, and the changes in surface stratification (Lee and Beardsley 1999; Moon 2005; Bhagawati et al. 2018). Therefore, considering the impact of river freshwater and tide forcing on the BOB simulation, it is necessary to make a comprehensive study on the role of river discharge and tides on the EICC discontinuity.
Previous studies on BOB incorporating river discharge and/or tides were mainly focused on the ocean state and the continuous EICC during pre- or post-ISM. Also, any high-resolution modeling considering both river discharge and tide in the bay, which is necessary to characterize the EICC discontinuity, is not available. Therefore, this study aims at finding the individual and combined influence of river discharge and tidal forcing on the EICC discontinuity in BOB. A recent study by Das et al. (2019) showed the features and physical mechanisms responsible for the summertime EICC discontinuity using high-resolution model simulations. Here, we assess the sensitivity experiments with river discharge, tides, and both [in a similarly configured model as done by Das et al. (2019); see section 2a] to estimate the individual and combined influence of river discharge and tides on EICC discontinuity. The rest of the paper is organized as follows: section 2 includes the description of the model, datasets, and methodology used. In section 3, results and discussions are presented including model validation. The conclusions are given in section 4.
2. Model, data, and methods
a. Model description
The Regional Ocean Modeling System (ROMS) is a hydrostatic, Boussinesq, sigma-coordinate ocean model, which solves the three-dimensional Navier–Stokes equations on a horizontal curvilinear Arakawa-C grid using finite difference approximation. ROMS is used widely to study the ocean state of the BOB (Sil and Chakraborty 2011; Jana et al. 2015, 2018; Dandapat et al. 2018; Bhagawati et al. 2018; Das et al. 2019). We have used ROMS_AGRIF (version 3.1) having a spatial resolution 1/12° × 1/12° and 32 depth levels for the region 4°–24°N, 76°–100°E (Fig. 1a) with the same configuration as was used by Das et al. (2019). The vertical turbulent mixing scheme used in the model is based on the K-profile parameterization (Large et al. 1994). Further details of the model configuration are given in Table S1 in the online supplemental material.
(a) The Bay of Bengal bathymetry (shaded) from ETOPO2 (m). The river-mouth locations considered in the simulations are marked with red open circles. The black-outlined rectangle represents the study region (4°–24°N, 76°–100°E), where the dotted and solid line denote the open and closed lateral boundaries, respectively. The transects L1 (from 19°N, 86°E to 18.2°N, 87.38°E) and L2 (from 11°N, 80°E to 11°N, 82°E), perpendicular to the boundary, are taken to examine the influence on the currents. (b) Amount of river discharge (m3 s−1) for the seven rivers (Ganges, Brahmaputra, Irrawaddy, Godavari, Krishna, Mahanadi, and Subarnarekha) included in Exp2 and Exp4 (Dai and Trenberth 2002). (c) Spatial amplitude (m) from TPX07 for the 10 tidal components (M2, S2, N2, K2, K1, O1, P1, Q1, Mf, and Mm) included in Exp3 and Exp4.
Citation: Journal of Physical Oceanography 50, 12; 10.1175/JPO-D-20-0133.1
b. Datasets
In the model simulations, the ETOPO2 gridded bathymetry data provided by the National Geophysical Data Center (NGDC 2006) are used (see Table S1). The surface forcings are taken from the monthly climatology (1° × 1° spatial resolution) of the Comprehensive Ocean and Atmosphere Datasets (COADS05), which includes surface wind stresses, heat fluxes, and heat flux sensitivity to SST (Worley et al. 2005). The lateral boundary conditions are set from the World Ocean Atlas 2009 (WOA09; 1° × 1° spatial with 24 vertical levels) temperature and salinity (Locarnini et al. 2010; Antonov et al. 2010). The point source river input is taken from Global River Flow and Continental Discharge monthly climatology data (Dai and Trenberth 2002). The sea level data for tidal influence are from TPXO7_atlas of Oregon State University Tidal Data Inversion (Egbert and Erofeeva 2002), where the complex amplitudes of Earth-relative sea surface elevation for eight primary (M2, S2, N2, K2, K1, O1, P1, and Q1), two long-period (Mf, Mm), and three nonlinear (M4, MS4, and MN4) harmonic constituents are provided on a ¼° global grid.
For model validations, the simulated surface currents and eddy kinetic energy (EKE) are compared with ⅓° spatial and 5-day temporal resolution OSCAR surface current spanning from 1992 to 2015 (Bonjean and Lagerloef 2002). The sea surface height anomaly (SSHA) is compared with the AVISO TOPEX/Poseidon, ERS, and Jason-1 (AVISO hereinafter) combined weekly ⅓° spatial SSHA from October 1992 to August 2013 (Pascual et al. 2006). The surface EKE derived from AVISO SSHA is also used in comparison. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) ¼° monthly climatology (1998–2006) of SST (Senan et al. 2001) is used to compare simulated SST. The model sea surface salinity (SSS) is compared with 1° spatial Aquarius/SAC-D (Aquarius hereinafter) weekly SSS that spans from 25 August 2011 to 7 June 2015 (Melnichenko et al. 2016). The Simple Ocean Data Assimilation (SODA3.3.1) monthly mean ocean salinity and temperature data in ½° × ½° Mercator horizontal grid forced by MERRA-2 for the period from 1980 to 2015 (Carton et al. 2018) are considered to compare simulated salinity and temperature at the subsurface. The tide gauge measurements at Visakhapatnam (17.68°N, 83.28°E; location is shown in Fig. 1a) for June 2018 is taken from the Indian National Centre for Ocean Information Services (INCOIS) to validate the tide inclusion in the model.
c. Methods
Four climatological simulations with the configuration specified in Table S1 in the online supplemental material are analyzed to examine the individual and combined effect of river and tide forcings on the EICC discontinuity. The first experiment (Exp1) is the control run with climatological lateral and surface boundary conditions that was used earlier by Das et al. (2019) to study the features and mechanism of EICC discontinuity. The other three sensitivity experiments have the same lateral and surface boundary conditions to ensure similar equatorial remote and atmospheric forcing as that of Exp1, but with additional river input (Exp2), tidal forcing (Exp3), and both (Exp4). Based on the high amount of discharge in the bay, seven rivers, Ganges, Brahmaputra, Irrawaddy, Godavari, Krishna, Mahanadi, and Subarnarekha (Figs. 1a,b), are included as point source input (Jana et al. 2015) in Exp2 and Exp4. Ten tidal components (semidiurnal, diurnal, and long period), M2, S2, N2, K2, K1, O1, P1, Q1, Mf, and Mm, with high amplitude (Fig. 1c) in the region are included for tide forcing in Exp3 and Exp4 (Sindhu and Unnikrishnan 2013; Bhagawati et al. 2018). All simulations are run for 10 years and the average of the last 3 years from all experiments are analyzed except for eddy detection and tracking and horizontal diffusivity coefficient, where only the final year (tenth) model output is used. Note that details of eddy detection and tracking during the eighth, ninth, and tenth years from each experiment (Exp1–4) are included in the online supplemental material (Figs. S4–S15) for reference. Though there are differences in the eddy statistics among the final and the previous two years in each experiment, the differences in the pattern of eddy characteristics among four experiments during any particular year (eighth or ninth or tenth) are reasonably consistent (Figs. S4–S15). Therefore, the statistical inferences in the eddy properties during the final year (for the ISM period) from all experiments are presented here.
The study compares the results of Exp1 with the other three sensitivity experiments, Exp2, Exp3, and Exp4, to estimate the influence of river discharge, tidal forcing, and both, respectively. The features of EICC discontinuity during ISM include disorganized currents, various CEs and ACEs with energy perturbations in between two opposing flows along the boundary and the upper-ocean instability (Das et al. 2019). Therefore, in result and discussions (section 3), we present the model validations followed by the role of individual and combined effect of river discharge and tide forcing on the features of EICC discontinuity.
3. Results and discussions
a. Model validation
The results from Exp1 are compared for overall ocean conditions, while the simulation of river discharge and tide forcings are validated from Exp2 and Exp3, respectively. The surface current and SSHA from Exp1 show a very good agreement with OSCAR currents and AVISO SSHA (see Fig. S1 in the online supplemental material) as shown previously by Das et al. (2019). The surface EKE field comparison with OSCAR and AVISO (⅓°) shows similar pattern as that of Exp1 (1/12°) and also confirms the availability of high EKE along the western boundary (Figs. S2a–c in the online supplemental material) in which ISM period has substantial contribution (Fig. S2d). Note that, the high-resolution numerical modeling overestimates the surface current fields compared to the coarse-resolution observations, which, in turn, overestimates the surface EKE as seen in Exp1 (Fig. S2a). The annual average SSS from Exp2 are compared with Aquarius and SODA datasets (Figs. 2a,b), whereas SST is compared with TMI data (Fig. 2c). The SSS difference between Exp2 and Aquarius (SODA) shows a good agreement with pattern correlation 0.99 (0.96) and root-mean-square error (RMSE) 0.42 (0.37) over the bay. The approximation in the amount of river discharge inclusion leads to the overestimation of SSS (up to 2 psu) in the model near the coastal head bay where the maximum freshwater is received. The SST difference between Exp2 and TMI shows pattern correlation 0.99 and RMSE 0.39 with a warm bias in the northern bay up to 1°C. The average depth–longitude salinity and temperature along 15°N from Exp2 (Figs. 2d,e, respectively) and SODA (Figs. 2f,g, respectively) also show very similar patterns. The sea level anomaly from Exp3 is compared with the INCOIS tide gauge measurements at Visakhapatnam (17.683°N, 83.283°E) for the month of June 2018 (Fig. 2h). The simulated SSHA shows a good correlation (coefficient = 0.81) with the tide gauge data, in terms of both tidal cycle and amplitude. Furthermore, note that the inclusion of river discharge improves temperature and salinity simulation, whereas tide reduces SST overestimation and makes overestimation of SSS [due to vertical tidal mixing as also mentioned by Moon (2005); see section 3b(4) and Figs. S16 and S17 in the online supplemental material].
Annual average SSS difference (psu) (a) between Exp2 and SODA and (b) between Exp2 and Aquarius. (c) Annual average SST difference (°C) between Exp2 and TMI. Positive value indicates overestimation of the simulations. Vertical sections of (left) salinity and (right) temperature along 15°N are shown from (d),(e) Exp2 and (f),(g) SODA. (h) The sea level anomaly from Exp3 (blue) and tide gauge (red) at Visakhapatnam during June 2018.
Citation: Journal of Physical Oceanography 50, 12; 10.1175/JPO-D-20-0133.1
b. Role of river discharge and tide on EICC discontinuity
1) Surface and subsurface currents
Monthly averaged current speed at surface and vertically integrated across depths, are shown in Fig. 3 from all experiments. All simulations follow the same temporal evolution except the difference in magnitude, depending on the physical processes associated to the additional forcings. At the surface (Fig. 3a), Exp2 (with river discharge) shows high current velocity with a maximum in July (13 cm s−1), while the same in Exp3 (with tide) and Exp4 (with river discharge and tide) are even smaller than that of Exp1 (control run). Conversely, vertically integrated current magnitude shows a higher value in Exp3 and Exp4 compared to Exp1 and Exp2 (Fig. 3b). Therefore, the results indicate that the river discharge increases current velocity at the surface, while the tide forcing does the same at the subsurface. The physical processes and implications of these effects are explained later in this section and also in section 3b(4).
Monthly averaged current speed from Exp1 (black), Exp2 (blue), Exp3 (red), and Exp4 (green) (a) at the surface and (b) vertically integrated across depth. The purple-outlined box highlights the ISM months (June–September). (c) Average surface currents from all experiments during ISM. The enhanced southward EICC reversal in Exp2 and northward EICC in Exp3 are highlighted in red. The anticyclonic eddy in the pathways of EICC reversal in Exp3 and Exp4 is highlighted in blue.
Citation: Journal of Physical Oceanography 50, 12; 10.1175/JPO-D-20-0133.1
During ISM, the surface current from all experiments show the opposing boundary current flows (Fig. 3c); northward from north of Sri Lanka (10°N) and southward from the head bay (21°N) as mentioned by Babu (1992), McCreary et al. (1993), and Das et al. (2019). In addition, Fig. 3c also reveals that the river forcing simulation (Exp2) enhances southward EICC reversal, while the tide forcing strengthens the northward flow in both Exp3 and Exp4. In contrary, the southward flow in tide forcing simulations (Exp3 and Exp4) and the northward flow in standalone river forcing simulation (Exp2) are weakened. During ISM, the huge amount of low saline river freshwater makes the upper ocean relatively stable and stratified, but creates a very strong horizontal density gradient [see section 3b(4)]. Since the head bay receives maximum river discharge, the southern bay waters remain high saline relative to the northern bay water and hence results southward density gradient flow. This flow enhances the southward EICC reversal during ISM and also the surface current field in the river discharge simulation. The strengthening of northward flow in tidal forcing simulations is due to a strong cyclonic eddy (similar direction) that is much clearer at the subsurface (Fig. 4; Exp3–4, 100–500 m). On the other hand, the southward EICC reversal in the tide forcing model is disturbed by an anticyclonic eddy in its pathway that can be seen in Figs. 3c and 4 (Exp3–4, highlighted in blue), Figs. 8c and 8d (ISM), and Figs. S6 and S7e in the online supplemental material. The Arabian Seawater intrusion through Summer Monsoon Current (SMC) is consistent in all experiment with high magnitude in Exp2 (Fig. 3c). The horizontal current at 100-m depth during ISM (Fig. 4, first row) shows the same pattern of forcing along the boundary as that of surface, but the currents at southern boundary are westward with high magnitude in Exp3 and Exp4. Further, with increasing depth (200, 300, and 500 m), the eddy-driven disorganized flow pattern along the boundary also increases in Exp3 (Fig. 4, highlighted in red). Here, in combined-forcing Exp4, discontinuity is weaker than that of Exp3, but stronger than that of Exp2 due to the combined effect of river discharge and tidal forcings.
Current vectors during ISM in western BOB at (top) 100-, (top middle) 200-, (bottom middle) 300-, and (bottom) 500-m depth from (left) Exp1, (left center) Exp2, (right center) Exp3, and (right) Exp4. At 100-m depth, the southward EICC reversal in Exp2 and northward EICC in Exp3 are highlighted in red, and the anticyclonic eddy in the pathways of EICC reversal in Exp3 and Exp4 is highlighted in blue. At 200-, 300-, and 500-m depth, the enhanced disorganized currents are highlighted in red in tide forcing model (Exp3).
Citation: Journal of Physical Oceanography 50, 12; 10.1175/JPO-D-20-0133.1
The vertical section of velocity along the transects L1 and L2 (as shown in Fig. 1a) during July from all the experiments are shown in Fig. 5. At L1, southward reversal of EICC becomes stronger (up to ~5–10 cm) and wider (>200 km) in Exp2 driven by the strong southward salinity gradient flow (purple outlined box in Fig. 5b). Again, it is weaker (up to ~2–7 cm), narrow (~75-km width and 150-m depth) and limited within the continental slope in tide and combined-forcing simulations (Figs. 5c,d). In Exp3–4, the southward flow is disturbed by a strong northward flow (between 40 and 130 km from coast). At L2, the northward EICC in Exp1 is away from the continental slope (Fig. 5e). This northward flow is much stronger (up to ~7–20 cm; red dotted box in Fig. 5g) and deep (>300 m) in Exp3 than Exp2 (up to ~2–7 cm; Fig. 5f) influenced by a cyclonic eddy. In Exp4, the northward flow is weaker in presence of an opposing flow at top (Fig. 5h).
Vertical section of velocity (10−3 m s−1) along the transects (left) L1 and (right) L2 (shown in Fig. 1a) during July from (a),(e) Exp1; (b),(f) Exp2; (c),(g) Exp3; and (d),(h) Exp4. Positive value indicates northward flow, and vice versa. The purple-outlined box in (b) indicates the strong and wide southward boundary current reversal at transect L1 in Exp2. The red-outlined box in (g) indicates the very strong and deep northward boundary current at transect L2 in Exp3.
Citation: Journal of Physical Oceanography 50, 12; 10.1175/JPO-D-20-0133.1
2) Eddy kinetic energy
Here, u and υ are the zonal and meridional components of the horizontal currents, respectively. The
The monthly averaged EKE shows high contribution from river discharge (Exp2) to increase the energy at the surface (Fig. 6a) as it increases the surface current field, but when the depth increases, the tide forcing (Exp3) plays significant role in increasing the EKE (Figs. 6b–d) due to strong vertical mixing [discussed in section 3b(4)]. Since Exp4 has combined forcing, river discharge increases the EKE compared to Exp1 and Exp3 at surface, while tidal mixing increases the EKE at subsurface compared to Exp1 and Exp2. The temporal EKE distribution shows that the river discharge and tide forcing impart relatively high energy across all depths during ISM (Fig. 6, purple-outlined box). Further, the spatial EKE map during ISM from all experiments show that the spatial distribution of EKE is confined to the western boundary (Fig. 7) with high values at west and southwest as also found by Chen et al. (2012) and Jia et al. (2011). At surface, Exp2 shows relatively high spatial EKE along the boundary (Fig. 7b) as seen in the monthly averaged time series in Fig. 6a. As depth increases, EKE along the boundary becomes higher in Exp3 (Figs. 7g,k,o, highlighted in blue). Similar to the time series pattern (Figs. 6b–d), EKE along the boundary is higher in Exp4 relative to Exp2 but smaller relative to that in Exp3 at 100-, 200-, and 500-m depth (Figs. 7h,l,p). The eddy available potential energy (EAPE), which is the energy of fluctuations in density around a time mean and available for conversion (Luecke et al. 2017) is calculated and provided in the online supplemental material (Fig. S3). It is seen that the river discharge model shows high EAPE at the upper ocean that in turn increases the EKE. Moreover, EAPE increases with depth in tide forcing model as seen for EKE along the boundary.
Monthly average EKE in log10 scale (cm2 s−2) at (a) the surface and (b) 100-, (c) 200-, and (d) 500-m depth from Exp1 (black), Exp2 (blue), Exp3 (red), and Exp4 (green). The purple-outlined box demarcates the ISM months (June–September).
Citation: Journal of Physical Oceanography 50, 12; 10.1175/JPO-D-20-0133.1
Seasonal EKE distribution in western BOB during ISM in log10 scale (cm2 s−2) at (a)–(d) the surface and (e)–(h)100-, (i)–(l) 200-, and (m)–(p) 500-m depth from (left) Exp1, (left center) Exp2, (right center) Exp3, and (right) Exp4. Ocean blue closed contours highlight the fact that EKE is relatively higher at the surface in Exp2 but that with depth EKE increases in Exp3.
Citation: Journal of Physical Oceanography 50, 12; 10.1175/JPO-D-20-0133.1
3) Eddy characteristics
During ISM, various CEs and ACEs are generated in the western BOB (Babu et al. 1991; Sil and Chakraborty 2011; Dandapat and Chakraborty 2016) and the EICC discontinuity is characterized by westward and southwestward movement of those eddies (Das et al. 2019). Further, Chen et al. (2012) suggested that the western BOB is the most critical region for interaction between eddy and the mean flow. Therefore, to analyze the impact on discontinuity, it is indeed important to investigate the influence on the eddy activities during ISM (such as eddy lifetime, area, amplitude, energy, and propagation speed). Here, to detect and track these eddies, a hybrid method is used based on the geometric criteria that finds the closed SSH loops (Chelton et al. 2011) followed by the Okubo–Weiss parameter (Okubo 1970; Weiss 1991) that finds the flow areas dominated by vorticity (Isern-Fontanet et al. 2006; Chelton et al. 2007). A detailed description of the eddy tracking method used in this study can be found in Das et al. (2019). Since we focus on the western BOB, the area 76°–94°E and 4°–24°N (Fig. 8) is considered for the eddy detection and tracking. We have considered the eddies that sustained more than 15 days. To exclude gyres, eddies having radius more than 300 km are excluded and the minimum radius is set to 30 km. In eddy tracking, each eddy is counted only once by following the Lagrangian approach (Penven et al. 2005), even if it has a longer lifetime. Previously Das et al. (2019) compared the eddy characteristics from Exp1 with the eddy analysis over BOB from AVISO SSHA done by Dandapat and Chakraborty (2016) and showed a good agreement. Therefore, here the eddies are detected and tracked throughout the final year (Fig. 8, top row) of all the experiments and their characteristics during ISM are highlighted (Fig. 8, bottom row and Table S2 in the online supplemental material). Note that separate eddy tracks from the last three years of each experiment are given additionally in the online supplemental material (Figs. S4–S15).
Eddy (cyclonic in blue and anticyclonic in red) tracking during (top) the whole year and (bottom) ISM from (a) Exp1, (b) Exp2, (c) Exp3, and (d) Exp4. The eddy genesis points are marked with magenta and black for cyclonic and anticyclonic eddies, respectively. The panels composing (a) (Exp1) are regenerated from Das et al. (2019). The green-dashed contours depict the spreading in the eddy-activity area.
Citation: Journal of Physical Oceanography 50, 12; 10.1175/JPO-D-20-0133.1
A total of 77 (45 CEs and 32 ACEs), 83 (46 CEs and 37 ACEs), 61 (32 CEs and 29 ACEs), and 71 (32 CEs and 39 ACEs) eddies are found in Exp1, Exp2, Exp3, and Exp4, respectively. The number of eddies indicate an increase in Exp2 but a decrease in Exp3 and Exp4. Of the total number of eddies, a total of 32 (19 CEs and 13 ACEs), 30 (18 CEs and 12 ACEs), 27 (14 CEs and 13 ACEs), and 31 (17 CEs and 14 ACEs) eddies remain present in Exp1, Exp2, Exp3, and Exp4, respectively, during ISM (Table S2 in the online supplemental material). The 95% confidence intervals of the mean eddy properties in Table S2 show that the estimated eddy parameters are statistically significant and robust. The surface eddy tracking shows that the eddy activities are distributed all over the western BOB in the river forcing experiments (Exp2 and Exp4), whereas in Exp3, the activities are mainly restricted to the western boundary of the bay (Fig. 8 and Figs. S4–S7 in the online supplemental material). Further, river discharge helps the ACEs (CEs) to move southwestward (both southwestward and northwestward) in Exp2 and Exp3. In case of tide forcing simulation (Exp3), genesis and propagations (mostly southwestward) of both ACEs and CEs remain confined to the western boundary of the bay intensifying the discontinuity. The eddy statistics shows (Table S2) that the average eddy properties are enhanced by the horizontal density gradient flow in the highly stratified, relatively less friction ocean surface of Exp2 due to addition of river discharge [horizontal diffusivity coefficient, section 3b(4)]. Meanwhile, the eddy properties are reduced by tide forcing as tide suppresses the surface current field through strong vertical mixing [turbulent buoyancy, section 3b(4)]. In Exp4, a river-discharge-driven stratified surface layer enhances the eddy properties compared to Exp3, but the presence of tide forcing weakens the eddy properties compared to Exp2.
4) Diffusion, mixing, and instability
(a) Horizontal diffusivity coefficient at the surface, and (b) vertically integrated turbulent buoyancy flux (N m s−1) in the upper 300 m from all experiments, over the western BOB (76°–90°E).
Citation: Journal of Physical Oceanography 50, 12; 10.1175/JPO-D-20-0133.1
Difference of the square of Brunt–Väisälä frequency (BVF) of Exp1 from Exp2 (blue), Exp3 (red), and Exp4 (green) during (a) June, (b) July, (c) August, and (d) September.
Citation: Journal of Physical Oceanography 50, 12; 10.1175/JPO-D-20-0133.1
The model results suggest that the addition of river discharge in Exp2 increases the horizontal diffusivity due to strong salinity gradient (Fig. 9a), but the vertical turbulent buoyancy flux remains very small (Fig. 9b). In Exp3, tidal mixing increases the vertical turbulent buoyancy (downward) that peaks during ISM. Due to high tidal mixing, Exp4 shows low horizontal diffusivity but high turbulent buoyancy (upward due to presence of river discharge). The differences of the square of BVF between the experiments Exp2, Exp3, Exp4, and Exp1 for ISM months are shown in Figs. 10a–d. The river-water-induced upper-ocean stratification makes the upper ocean more stable in Exp2, and the maximum difference is noted at 25 m in September (1.8 × 104 S−1; Fig. 10d). Due to high vertical mixing in Exp3, the upper layer remains unstable that peaks at around 60 m during June–July (0.8 × 104 S−1; Figs. 10a,b). In Exp4, the upper layers (~50 m) are stable due to river water, but addition of tide forcing reduces the stability afterward and the instability increases rapidly below 30 m. From Eq. (4), it is evident that the square of BVF N2 changes due to the change in density [ρ = ρ(T, S, z)] with depth z. Now in Exp1–4, the ρ changes predominantly because of salinity S depending on the presence of river discharge (Figs. S16 and S18 in the online supplemental material). Therefore, during discontinuity, river influx plays a key role in increasing static stability in the upper ocean, which can be seen in Exp2 and Exp4, but the vertical mixing by tide forcing does the opposite (Müller 2012). Below 50-m depth, combined forcing reduces stability (Exp4) due to tide, but the individual river forcing (Exp2) continues to increase the stability. Tidal forcing reduces the stability in the upper layers up to 80–90 m and then slowly the instability reduces. The density gradient flow over the stratified and relatively less–friction upper ocean in the river forcing model enhances the surface ocean features. Again, the strong lower-layer friction caused by the high buoyancy in the tide model suppress the surface current field. The vertical salinity section (Fig. S16) and the variations of MLD in the western BOB (Fig. S17 in the online supplemental material) also confirm as the implications of such river and tide effect. The penetration of low saline freshwater is deeper in Exp2 and further vertical mixing in Exp4 makes the penetration even deeper. Again, the month July shows the maximum isohaline layer depth as compared with March and November because of the maximum buoyancy during ISM. Upper-layer stratification caused by the low-saline, lighter river water makes the MLD shallower in Exp2 (Fig. S17b); meanwhile, the tidal vertical mixing due to high buoyancy leads to much deeper MLD in Exp3 (Fig. S17c). In Exp4, presence of both freshwater and vertical mixing makes the MLD deeper than in Exp2, but shallower than that in Exp3 (Fig. S17d).
4. Conclusions
The study investigates the individual and combined influence of river discharge and tide forcing on EICC discontinuity using four climatological ROMS simulations. The analysis shows that the density-gradient-driven horizontal advection caused by the river discharge strengthens the southward reversal of the boundary current during ISM. Further, the northward boundary current from north of Sri Lanka becomes stronger in tide forcing and the impact is driven by a cyclonic eddy across depth. In river forcing simulation, the density-driven horizontal flow in stratified and less-friction upper-ocean increases the surface currents associated with the discontinuity, and further helps to enhance and spread the surface eddy activities over the whole western BOB. River discharge increases the horizontal diffusivity due to high salinity gradient, but the small vertical turbulence makes the upper ocean comparatively more stable and a shallower MLD. On the other hand, high subsurface friction and strong vertical mixing (turbulent buoyancy) in tide forcing reduces the surface current velocity and EKE. Further, as depth increases, the gradually relaxing subsurface friction favors to increase the kinetic energy due to strong turbulent buoyancy. As tidal vertical mixing suppresses the surface current field, the discontinuity associated surface eddies also reduce their average property, but the tidal oscillation restricts the eddy activities near and along the boundary. The high vertical turbulent buoyancy in tide forcing makes the MLD deeper and the upper ocean relatively unstable. The combined forcing also suppresses the surface features and intensifies the discontinuity at subsurface due to tide, but river water makes the upper ocean relatively stable, and thus, the buoyancy thrust becomes upward. Therefore, during ISM, the river discharge enhances the southward EICC reversal with eddy activities over the entire western BOB in a stable upper-ocean condition. The tidal forcing strengthens the northward EICC with restricted eddy activities and accumulation of high kinetic energy along the western boundary in a relatively unstable upper ocean. And the combined forcing mostly shows the control of river influx at surface with suppressed upper-ocean conditions due to tide, which again intensifies the discontinuity at subsurface.
Acknowledgments
We sincerely thank the editor and two anonymous reviewers for their valuable comments and suggestions, which have helped us to improve the quality of the paper. This work is partly funded by the University Grants Commission, Government of India. The first author Das is grateful to Dr. Sumit Dandapat, IITM, for his valuable suggestions and discussions. Author Chakraborty appreciates the support from the Ministry of Earth Sciences, Ministry of Human Resource and Development, Department of Science and Technology, Government of India. Author Kuttippurath appreciates the financial support received from IIT Kharagpur through the SRIC/CMI and the IME/INCOIS/O-MASCOT Project. There is no conflict of interest that can influence the outcomes of the study. The figures are generated using MATLAB.
Data availability statement
The simulated datasets are available to the corresponding author. The ETOPO2 data are obtained from http://www.ngdc.noaa.gov/mgg/global/etopo2.html. The COADS05 dataset is taken from http://icoads.noaa.gov/. The WOA09 dataset is available by request from http://www.nodc.noaa.gov/OC5/WOA09/pr_woa09.html. The Global River Flow and Continental Discharge can be found at http://www.cgd.ucar.edu/cas/catalog/surface/dai-runoff/index.html. The AVISO TOPEX Poseidon, ERS, and Jason-1 combined altimeter products were produced by the CLS Space Oceanography Division as part of the Environment and Climate EU ENACT project (EVK2-CT2001-00117) and with support from CNES and were obtained from https://www.aviso.altimetry.fr/en/data.html. The OSCAR data are downloaded from https://podaac.jpl.nasa.gov/dataset/OSCAR_L4_OC_third-deg. The Aquarius/SAC-D data are taken from https://podaac.jpl.nasa.gov/aquarius. The SODA3.3.1 is obtained from http://www.atmos.umd.edu/~ocean/. The TMI SST is taken from http://www.remss.com/missions/tmi. Tide gauge data at Visakhapatnam are provided by INCOIS (https://incois.gov.in/).
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