Interannual variability in the barrier layer and forcing mechanism in the eastern equatorial Indian Ocean and Bay of Bengal

2020 ◽  
Vol 39 (7) ◽  
pp. 19-31
Author(s):  
Tian Ma ◽  
Xuhua Cheng ◽  
Yiquan Qi ◽  
Jiajia Chen
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
Barrier Layer ◽  
Bay Of Bengal ◽  
Equatorial Indian Ocean ◽  
Eastern Equatorial Indian Ocean

Importance of wind variations and intersecting waveguides near Sri Lanka for the intraseasonal sea level variability along the west coast of India

2020 ◽  
Author(s):  
Iyyappan Suresh ◽  
Jerome Vialard ◽  
Matthieu Lengaigne ◽  
Takeshi Izumo ◽  
Muraleedharan Pillathu Moolayil
Keyword(s):  
Sri Lanka ◽  
Indian Ocean ◽  
Sea Level ◽  
Bay Of Bengal ◽  
West Coast ◽  
Equatorial Indian Ocean ◽  
Direct Connection ◽  
Local Wind ◽  
The West ◽  
Eastern Equatorial Indian Ocean

<p>Remote wind forcing plays a strong role in the Northern Indian Ocean, where oceanic anomalies can travel long distances within the coastal waveguide. Previous studies for instance emphasized that remote equatorial forcing is the main driver of the sea level and currents intraseasonal variability along the west coast of India (WCI). Until now, the main pathway for this connection between the equatorial and coastal waveguides was thought to occur in the eastern equatorial Indian Ocean, through coastal Kelvin waves that propagate around the Bay of Bengal rim and then around Sri Lanka to the WCI. Using a linear, continuously stratified ocean model, the present study demonstrates that two other mechanisms in fact dominate. First, the equatorial waveguide also intersects the coastal waveguide at the southern tip of India and Sri Lanka, creating a direct connection between the equator and WCI. Rossby waves reflected from the eastern equatorial Indian Ocean boundary indeed have a sufficiently wide meridional scale to induce a pressure signal at the Sri Lankan coast, which eventually propagates to the WCI as a coastal Kelvin wave. Second, local wind variations in the vicinity of Sri Lanka generate strong intraseasonal signals, which also propagate to the WCI along the same path. Sensitivity experiments indicate that these two new mechanisms (direct equatorial connection and local wind variations near Sri Lanka) dominate the WCI intraseasonal sea level variability, with the “classical” pathway around the Bay of Bengal only coming next. Other contributions (Bay of Bengal forcing, local WCI forcing) are much weaker.</p><p>We further show that the direct connection between the equatorial waveguide and WCI is negligible at seasonal timescale, but not at interannual timescales where it contributes to the occurrence of anoxic events. By providing an improved understanding of the mechanisms that control the WCI thermocline and oxycline variability, our results could have socio-economic implications for regional fisheries and ecosystems.</p>

scholarly journals A model study of the seasonal variability and formation mechanisms of the barrier layer in the eastern equatorial Indian Ocean

2002 ◽  
Vol 107 (C12) ◽  
pp. SRF 18-1-SRF 18-20 ◽  
Author(s):  
Sébastien Masson ◽  
Pascale Delecluse ◽  
Jean-Philippe Boulanger ◽  
Christophe Menkes
Keyword(s):  
Indian Ocean ◽  
Barrier Layer ◽  
Seasonal Variability ◽  
Equatorial Indian Ocean ◽  
Formation Mechanisms ◽  
Model Study ◽  
Eastern Equatorial Indian Ocean

scholarly journals Correlation between subsurface salinity anomalies in the Bay of Bengal and the Indian Ocean Dipole and governing mechanisms

2020 ◽  
Author(s):  
Zheen Zhang ◽  
Thomas Pohlmann ◽  
Xueen Chen
Keyword(s):  
Indian Ocean ◽  
Bay Of Bengal ◽  
Indian Ocean Dipole ◽  
Equatorial Indian Ocean ◽  
Ocean Model ◽  
Subsurface Temperature ◽  
Remote Forcing ◽  
Salinity Variability ◽  
Eastern Equatorial Indian Ocean ◽  
The Indian Ocean

Abstract. Lead-lag correlations between the subsurface temperature/salinity anomalies in the Bay of Bengal (BoB) and the Indian Ocean Dipole (IOD) are revealed in model results, ocean synthesis, and observations. Mechanisms for such correlations are further investigated using the Hamburg Shelf Ocean Model (HAMSOM), mainly on the salinity variability. It is found that the subsurface salinity anomaly of the BoB positively correlates to the IOD with a lag of three months on average, while the subsurface temperature anomaly negatively correlates. The model results suggest the remote forcing from the equatorial Indian Ocean dominates the interannual subsurface salinity variability in the BoB. The coastal Kelvin waves carry signals of positive (negative) salinity anomalies from the eastern equatorial Indian Ocean and propagate counterclockwise along the coasts of the BoB during positive (negative) IOD events. Subsequently westward Rossby waves propagate these signals to the basin at a relatively slow speed, which causes a considerable delay of the subsurface salinity anomalies in the correlation. By analyzing the salinity budget of the BoB, it is found that the diffusion dominates the salinity changes near the surface, while the advection dominates the subsurface; the vertical advection of salinity contributes positively to this correlation, while the horizontal advection contributes negatively. These results suggest that the IOD plays a crucial role in the interannual subsurface salinity variability in the BoB.

scholarly journals Correlation between subsurface salinity anomalies in the Bay of Bengal and the Indian Ocean Dipole and governing mechanisms

Ocean Science ◽  
2021 ◽  
Vol 17 (1) ◽  
pp. 393-409
Author(s):  
Zheen Zhang ◽  
Thomas Pohlmann ◽  
Xueen Chen
Keyword(s):  
Indian Ocean ◽  
Bay Of Bengal ◽  
Indian Ocean Dipole ◽  
Equatorial Indian Ocean ◽  
Ocean Model ◽  
Subsurface Temperature ◽  
Remote Forcing ◽  
Salinity Variability ◽  
Eastern Equatorial Indian Ocean ◽  
The Indian Ocean

Abstract. Lead–lag correlations between the subsurface temperature and salinity anomalies in the Bay of Bengal (BoB) and the Indian Ocean Dipole (IOD) are revealed in model results, ocean synthesis, and observations. Mechanisms for such correlations are further investigated using the Hamburg Shelf Ocean Model (HAMSOM), mainly relating to the salinity variability. It is found that the subsurface salinity anomaly of the BoB positively correlates to the IOD, with a lag of 3 months on average, while the subsurface temperature anomaly correlates negatively. The model results suggest the remote forcing from the equatorial Indian Ocean dominates the interannual subsurface salinity variability in the BoB. The coastal Kelvin waves carry signals of positive (negative) salinity anomalies from the eastern equatorial Indian Ocean and propagate counterclockwise along the coasts of the BoB during positive (negative) IOD events. Subsequently, westward Rossby waves propagate these signals to the basin at a relatively slow speed, which causes a considerable delay of the subsurface salinity anomalies in the correlation. By analyzing the salinity budget of the BoB, it is found that diffusion dominates the salinity changes near the surface, while advection dominates the subsurface; the vertical advection of salinity contributes positively to this correlation, while the horizontal advection contributes negatively. These results suggest that the IOD plays a crucial role in the interannual subsurface salinity variability in the BoB.

Photosynthetic physiologies of phytoplankton in the eastern equatorial Indian Ocean during the spring inter-monsoon

2019 ◽  
Vol 38 (6) ◽  
pp. 83-91 ◽  
Author(s):  
Chao Yuan ◽  
Zongjun Xu ◽  
Xuelei Zhang ◽  
Qinsheng Wei ◽  
Huiwu Wang ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Equatorial Indian Ocean ◽  
Eastern Equatorial Indian Ocean

scholarly journals Intraseasonal meridional current variability in the eastern equatorial Indian Ocean

2008 ◽  
Vol 113 (C7) ◽  
Author(s):  
Tomomichi Ogata ◽  
Hideharu Sasaki ◽  
V. S. N. Murty ◽  
M. S. S. Sarma ◽  
Yukio Masumoto
Keyword(s):  
Indian Ocean ◽  
Equatorial Indian Ocean ◽  
Eastern Equatorial Indian Ocean

Seasonal and Interannual Variability in the Barrier Layer of the Bay of Bengal

2018 ◽  
Vol 123 (2) ◽  
pp. 1001-1015 ◽  
Author(s):  
Anshu Kumari ◽  
S. Prasanna Kumar ◽  
Arun Chakraborty
Keyword(s):  
Interannual Variability ◽  
Barrier Layer ◽  
Bay Of Bengal ◽  
Seasonal And Interannual Variability
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