Seasonal Evolution of Sea Surface Salinity in the Northwestern Indian Ocean: Argo Data Study

2021 ◽  
Author(s):  
Sartaj Khan ◽  
Shengchun Piao ◽  
Yang Song ◽  
Shazia Khan ◽  
Bingchen Xu ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Argo Data ◽  
Seasonal Evolution

Assessing Sea Surface Salinity Derived by Aquarius in the Indian Ocean

2014 ◽  
Vol 11 (4) ◽  
pp. 719-722 ◽  
Author(s):  
Smitha Ratheesh ◽  
Rashmi Sharma ◽  
Rajesh Sikhakolli ◽  
Raj Kumar ◽  
Sujit Basu
Keyword(s):  
Indian Ocean ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
The Indian Ocean

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.

Meridional Distribution of Surface CO2 along 67°E of the Indian Ocean

2020 ◽  
Author(s):  
Dong-Jin Kang ◽  
Sang-Hwa Choi ◽  
Daeyeon Kim ◽  
Gyeong-Mok Lee
Keyword(s):  
Indian Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Seawater ◽  
Surface Salinity ◽  
The North ◽  
The Indian Ocean ◽  
North And South

<p>Surface seawater carbon dioxide was observed from 3 °S to 27 °S along 67 °E of the Indian Ocean in April 2018 and 2019. Partial pressure of CO<sub>2</sub>(pCO<sub>2</sub>) in the surface seawater and the atmosphere were observed every two minutes using an underway CO2 measurement system (General Oceanics Model 8050) installed on R/V Isabu. Surface water temperature and salinity were measured as well. The pCO<sub>2</sub> was measured using Li-7000 NDIR. Standard gases were measured every 8 hours in five classes with concentrations of 0 µatm, 202 µatm, 350 µatm, 447 µatm, and 359.87 µatm. The fCO<sub>2</sub> of atmosphere remained nearly constant at 387 ± 2 µatm, but the surface seawater fCO<sub>2</sub> peaked at about 3 °S and tended to decrease toward the north and south. The distribution of fCO<sub>2</sub> in surface seawater according to latitude tends to be very similar to that of sea surface temperature. In order to investigate the factors that control the distribution of fCO<sub>2</sub> in surface seawater, we analyzed the sea surface temperature, sea surface salinity, and other factors. The effects of salinity are insignificant, and the surface fCO<sub>2</sub> distribution is mainly controlled by sea surface temperature and other factors that can be represented mainly by biological activity and mixing.</p>

Indian Ocean Rossby waves detected in HYCOM sea surface salinity

2008 ◽  
Vol 35 (3) ◽  
Author(s):  
David M. Heffner ◽  
Bulusu Subrahmanyam ◽  
Jay F. Shriver
Keyword(s):  
Indian Ocean ◽  
Rossby Waves ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity

A sea surface salinity dipole mode in the tropical Indian Ocean

2016 ◽  
Vol 47 (7-8) ◽  
pp. 2573-2585 ◽  
Author(s):  
Yuhong Zhang ◽  
Yan Du ◽  
Tangdong Qu
Keyword(s):  
Indian Ocean ◽  
Tropical Indian Ocean ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Dipole Mode ◽  
Surface Salinity

scholarly journals Salinity changes in the Agulhas leakage area recorded by stable hydrogen isotopes of C<sub>37</sub> alkenones during Termination I and II

2014 ◽  
Vol 10 (1) ◽  
pp. 251-260 ◽  
Author(s):  
S. Kasper ◽  
M. T. J. van der Meer ◽  
A. Mets ◽  
R. Zahn ◽  
J. S. Sinninghe Damsté ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Saline Water ◽  
Planktonic Foraminifera ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Agulhas Current ◽  
Salinity Changes ◽  
Leakage Area ◽  
The Indian Ocean

Abstract. At the southern tip of Africa, the Agulhas Current reflects back into the Indian Ocean causing so-called "Agulhas rings" to spin off and release relatively warm and saline water into the South Atlantic Ocean. Previous reconstructions of the dynamics of the Agulhas Current, based on paleo-sea surface temperature and sea surface salinity proxies, inferred that Agulhas leakage from the Indian Ocean to the South Atlantic was reduced during glacial stages as a consequence of shifted wind fields and a northwards migration of the subtropical front. Subsequently, this might have led to a buildup of warm saline water in the southern Indian Ocean. To investigate this latter hypothesis, we reconstructed sea surface salinity changes using alkenone δD, and paleo-sea surface temperature using TEXH86 and UK'37, from two sediment cores (MD02-2594, MD96-2080) located in the Agulhas leakage area during Termination I and II. Both UK'37 and TEXH86 temperature reconstructions indicate an abrupt warming during the glacial terminations, while a shift to more negative δDalkenone values of approximately 14‰ during glacial Termination I and II is also observed. Approximately half of the isotopic shift can be attributed to the change in global ice volume, while the residual isotopic shift is attributed to changes in salinity, suggesting relatively high salinities at the core sites during glacials, with subsequent freshening during glacial terminations. Approximate estimations suggest that δDalkenone represents a salinity change of ca. 1.7–1.9 during Termination I and Termination II. These estimations are in good agreement with the proposed changes in salinity derived from previously reported combined planktonic Foraminifera δ18O values and Mg/Ca-based temperature reconstructions. Our results confirm that the δD of alkenones is a potentially suitable tool to reconstruct salinity changes independent of planktonic Foraminifera δ18O.

scholarly journals Multiple Time Scale Variability of the Sea Surface Salinity Dipole Mode in the Tropical Indian Ocean

2017 ◽  
Vol 31 (1) ◽  
pp. 283-296 ◽  
Author(s):  
Yuhong Zhang ◽  
Yan Du ◽  
Ming Feng
Keyword(s):  
Indian Ocean ◽  
Western Australia ◽  
Time Scale ◽  
Tropical Indian Ocean ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Multiple Time ◽  
Multiple Time Scale ◽  
Surface Salinity ◽  
Ocean Advection

Abstract In this study, multiple time scale variability of the salinity dipole mode in the tropical Indian Ocean (S-IOD) is revealed based on the 57-yr Ocean Reanalysis System 4 (ORAS4) sea surface salinity (SSS) reanalysis product and associated observations. On the interannual time scale, S-IOD is highly correlated with strong Indian Ocean dipole (IOD) and ENSO variability, with ocean advection forced by wind anomalies along the equator and precipitation anomalies in the southeastern tropical Indian Ocean (IO) dominating the SSS variations in the northern and southern poles of the S-IOD, respectively. S-IOD variability is also associated with the decadal modulation of the Indo-Pacific Walker circulation, with a stronger signature at its southern pole. Decadal variations of the equatorial IO winds and precipitations in the central IO force zonal ocean advection anomalies that contribute to the SSS variability in the northern pole of S-IOD on the decadal time scale. Meanwhile, oceanic dynamics dominates the SSS variability in the southern pole of S-IOD off Western Australia. Anomalous ocean advection transports the fresher water from low latitudes to the region off Western Australia, with additional contributions from the Indonesian Throughflow. Furthermore, the southern pole of S-IOD is associated with the thermocline variability originated from the tropical northwestern Pacific through the waveguide in the Indonesian Seas, forced by decadal Pacific climate variability. A deepening (shoaling) thermocline strengthens (weakens) the southward advection of surface freshwater into the southern pole of S-IOD and contributes to the high (low) SSS signatures off Western Australia.

Indian Ocean sea surface salinity variations in a coupled model

2009 ◽  
Vol 33 (2-3) ◽  
pp. 245-263 ◽  
Author(s):  
P. N. Vinayachandran ◽  
Ravi S. Nanjundiah
Keyword(s):  
Indian Ocean ◽  
Coupled Model ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
Salinity Variations
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