scholarly journals A modeling study of the processes of surface salinity seasonal cycle in the Bay of Bengal

2014 ◽  
Vol 119 (6) ◽  
pp. 3926-3947 ◽  
Author(s):  
V. P. Akhil ◽  
Fabien Durand ◽  
Matthieu Lengaigne ◽  
Jérôme Vialard ◽  
M. G. Keerthi ◽  
...  
Keyword(s):  
Bay Of Bengal ◽  
Seasonal Cycle ◽  
Surface Salinity ◽  
Modeling Study

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

2016 ◽  
Vol 121 (12) ◽  
pp. 8471-8495 ◽  
Author(s):  
V. P. Akhil ◽  
M. Lengaigne ◽  
J. Vialard ◽  
F. Durand ◽  
M. G. Keerthi ◽  
...  
Keyword(s):  
Interannual Variability ◽  
Bay Of Bengal ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Modeling Study

Assessment of Aquarius sea surface salinity with Argo in the Bay of Bengal

2019 ◽  
Vol 40 (22) ◽  
pp. 8547-8565 ◽  
Author(s):  
Xinyu Lin ◽  
Yun Qiu ◽  
Jing Cha ◽  
Xiaogang Guo
Keyword(s):  
Bay Of Bengal ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity

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

2020 ◽  
Vol 248 ◽  
pp. 111964 ◽  
Author(s):  
V.P. Akhil ◽  
J. Vialard ◽  
M. Lengaigne ◽  
M.G. Keerthi ◽  
J. Boutin ◽  
...  
Keyword(s):  
Bay Of Bengal ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Salinity Variability

scholarly journals The Seasonal Cycle of Upper-Ocean Mixing at 8°N in the Bay of Bengal

2020 ◽  
Vol 50 (2) ◽  
pp. 323-342 ◽  
Author(s):  
D. A. Cherian ◽  
E. L. Shroyer ◽  
H. W. Wijesekera ◽  
J. N. Moum
Keyword(s):  
Bay Of Bengal ◽  
Seasonal Cycle ◽  
Sea Water ◽  
Turbulent Transport ◽  
Low Frequency ◽  
Salt Flux ◽  
Strong Mixing ◽  
Northeast Monsoon ◽  
Order Of Magnitude ◽  
Episodic Mixing

AbstractWe describe the seasonal cycle of mixing in the top 30–100 m of the Bay of Bengal as observed by moored mixing meters (χpods) deployed along 8°N between 85.5° and 88.5°E in 2014 and 2015. All χpod observations were combined to form seasonal-mean vertical profiles of turbulence diffusivity KT in the top 100 m. The strongest turbulence is observed during the southwest and postmonsoon seasons, that is, between July and November. The northeast monsoon (December–February) is a period of similarly high mean KT but an order of magnitude lower median KT, a sign of energetic episodic mixing events forced by near-inertial shear events. The months of March and April, a period of weak wind forcing and low near-inertial shear amplitude, are characterized by near-molecular values of KT in the thermocline for weeks at a time. Strong mixing events coincide with the passage of surface-forced downward-propagating near-inertial waves and with the presence of enhanced low-frequency shear associated with the Summer Monsoon Current and other mesoscale features between July and October. This seasonal cycle of mixing is consequential. We find that monthly averaged turbulent transport of salt out of the salty Arabian Sea water between August and January is significant relative to local E − P. The magnitude of this salt flux is approximately that required to close model-based salt budgets for the upper Bay of Bengal.

scholarly journals Effects of Tropical Cyclones on Sea Surface Salinity in the Bay of Bengal Based on SMAP and Argo Data

Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 2975
Author(s):  
Huabing Xu ◽  
Rongzhen Yu ◽  
Danling Tang ◽  
Yupeng Liu ◽  
Sufen Wang ◽  
...  
Keyword(s):  
Tropical Cyclones ◽  
Bay Of Bengal ◽  
Vertical Mixing ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Ekman Pumping ◽  
Surface Salinity ◽  
Argo Data ◽  
Before And After ◽  
The Impact

This paper uses the Argo sea surface salinity (SSSArgo) before and after the passage of 25 tropical cyclones (TCs) in the Bay of Bengal from 2015 to 2019 to evaluate the sea surface salinity (SSS) of the Soil Moisture Active Passive (SMAP) remote sensing satellite (SSSSMAP). First, SSSArgo data were used to evaluate the accuracy of the 8-day SMAP SSS data, and the correlations and biases between SSSSMAP and SSSArgo were calculated. The results show good correlations between SSSSMAP and SSSArgo before and after TCs (before: SSSSMAP = 1.09SSSArgo−3.08 (R2 = 0.69); after: SSSSMAP = 1.11SSSArgo−3.61 (R2 = 0.65)). A stronger negative bias (−0.23) and larger root-mean-square error (RMSE, 0.95) between the SSSSMAP and SSSArgo were observed before the passage of 25 TCs, which were compared to the bias (−0.13) and RMSE (0.75) after the passage of 25 TCs. Then, two specific TCs were selected from 25 TCs to analyze the impact of TCs on the SSS. The results show the significant SSS increase up to the maximum 5.92 psu after TC Kyant (2016), which was mainly owing to vertical mixing and strong Ekman pumping caused by TC and high-salinity waters in the deep layer that were transported to the sea surface. The SSSSMAP agreed well with SSSArgo in both coastal and offshore waters before and after TC Roanu (2016) and TC Kyant (2016) in the Bay of Bengal.

scholarly journals Response of the Salinity-Stratified Bay of Bengal to Cyclone Phailin

2019 ◽  
Vol 49 (5) ◽  
pp. 1121-1140 ◽  
Author(s):  
Dipanjan Chaudhuri ◽  
Debasis Sengupta ◽  
Eric D’Asaro ◽  
R. Venkatesan ◽  
M. Ravichandran
Keyword(s):  
Barrier Layer ◽  
Bay Of Bengal ◽  
Sea Surface ◽  
Density Stratification ◽  
Upper Ocean ◽  
Dimensional Model ◽  
Cyclone Track ◽  
Surface Salinity ◽  
Near Surface ◽  
One Dimensional

AbstractCyclone Phailin, which developed over the Bay of Bengal in October 2013, was one of the strongest tropical cyclones to make landfall in India. We study the response of the salinity-stratified north Bay of Bengal to Cyclone Phailin with the help of hourly observations from three open-ocean moorings 200 km from the cyclone track, a mooring close to the cyclone track, daily sea surface salinity (SSS) from Aquarius, and a one-dimensional model. Before the arrival of Phailin, moored observations showed a shallow layer of low-salinity water lying above a deep, warm “barrier” layer. As the winds strengthened, upper-ocean mixing due to enhanced vertical shear of storm-generated currents led to a rapid increase of near-surface salinity. Sea surface temperature (SST) cooled very little, however, because the prestorm subsurface ocean was warm. Aquarius SSS increased by 1.5–3 psu over an area of nearly one million square kilometers in the north Bay of Bengal. A one-dimensional model, with initial conditions and surface forcing based on moored observations, shows that cyclone winds rapidly eroded the shallow, salinity-dominated density stratification and mixed the upper ocean to 40–50-m depth, consistent with observations. Model sensitivity experiments indicate that changes in ocean mixed layer temperature in response to Cyclone Phailin are small. A nearly isothermal, salinity-stratified barrier layer in the prestorm upper ocean has two effects. First, near-surface density stratification reduces the depth of vertical mixing. Second, mixing is confined to the nearly isothermal layer, resulting in little or no SST cooling.

Observed year-to-year sea surface salinity variability in the Bay of Bengal during the 2009–2014 period

2014 ◽  
Vol 65 (2) ◽  
pp. 173-186 ◽  
Author(s):  
Akurathi Venkata Sai Chaitanya ◽  
Fabien Durand ◽  
Simi Mathew ◽  
Vissa Venkata Gopalakrishna ◽  
Fabrice Papa ◽  
...  
Keyword(s):  
Bay Of Bengal ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Salinity Variability

scholarly journals On the Possible Mechanisms for Saltening of the Bay of Bengal

2019 ◽  
Vol 69 (1) ◽  
pp. 93-103
Author(s):  
Anoopa Prasad C ◽  
P.V. Hareesh Kumar
Keyword(s):  
Bay Of Bengal ◽  
Arabian Sea ◽  
Coastal Upwelling ◽  
Salt Water ◽  
Dominant Role ◽  
Salinity Gradient ◽  
Ekman Transport ◽  
Surface Salinity ◽  
Near Shore ◽  
Lateral Advection

The Bay of Bengal (BoB) is a low saline basin owing to large influx of freshwater from precipitation and river runoff. To maintain the salt balance of the BoB, the incessant lowering of salinity is to be balanced by the inflow of saltier water into the basin. In the present work, various processes that contribute to the saltening of the BoB, viz. coastal upwelling, eddies and their interaction, lateral advection from Arabian Sea and tropical cyclones are discussed. In the near-shore regions, the coastal upwelling due to wind induced Ekman transport plays a dominant role in increasing the surface salinity. On the other hand, in the open ocean, the divergence induced by eddies and their mutual interaction contributes significantly to the salt water pumping. In the southern BoB, the advection from the Arabian Sea increases the salinity. The formation of cyclones in the BoB also leads to an increase in the surface salinity. However, the magnitude of saltening of the Bay due to these processes varies from north to south. The uplift of saltier water from subsurface levels increases the salinity in the surface layers thereby creating a salinity gradient and a salinity front.

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