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Interannual variability of winter water in the Indian Ocean Sector of the Southern Ocean and its causes during 2011−2020
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Lingqiao Cheng1, 2, 3, Junjie Meng1, Deng Li1, Yujiro Kitade4, Chunling Zhang1, 2, Juncheng Zuo1, 2
Haiyang Xuebao | 2023, 45(8) : 11 - 23
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Haiyang Xuebao | 2023, 45(8): 11-23
Article
Interannual variability of winter water in the Indian Ocean Sector of the Southern Ocean and its causes during 2011−2020
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Lingqiao Cheng1, 2, 3, Junjie Meng1, Deng Li1, Yujiro Kitade4, Chunling Zhang1, 2, Juncheng Zuo1, 2
Affiliations
  • 1College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China
  • 2Key Laboratory of Marine Ecological Monitoring and Restoration Technologies, Ministry of Natural Resources, Shanghai 201306, China
  • 3Center for Polar Research, Shanghai Ocean University, Shanghai 201306, China
  • 4Department of Ocean Sciences, Tokyo University of Marine Science and Technology, Tokyo 108-8477, Japan
Published: 2023-08-31 doi: 10.12284/hyxb2023100
Outline
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Multiple studies have confirmed the long-term property modification of water columns from the bottom to the sea surface at the Southern Ocean and pointed out that it is closely related to the changes of large-scale external forcing. However, the higher frequency interannual variability of the water masses and its causes are still poorly understood, including the winter water (WW), which is the most vulnerable to external forcing near the sea surface. Based on repeated hydrographic observations along 110°E in Januaries 2011 to 2020 and meteorological reanalysis datasets, this study estimated interannual variability of the WW layer in the seasonal ice zone (SIZ) and its possible causes over ten years. Results show that WW properties have significant temporal and spatial variability in this region. A significant positive correlation between the WW core temperature anomaly and the previous-year Antarctic Oscillation (AAO) index anomaly (R = 0.69) and a negative correlation between the AAO index and the turning latitude of the local zonal wind component (R = −0.61), indicate that a larger (smaller) AAO index corresponds to a southward (northward) shift of the divergence zone, and the increase (decrease) of the WW core temperature in the SIZ. A negative correspondence between the local net precipitation anomaly and the WW core salinity anomaly indicates the negative net precipitation anomaly (less freshwater transport to the ocean) after 2016 contributes to an increase in the WW core salinity anomaly. Meanwhile, the local eddy kinetic energy anomaly is negatively correlated with the WW thickness anomaly (R = −0.70), which supports the idea that the enhancement (decrease) in the intensity of persistent cyclonic eddies in this region may strengthen (weaken) the upward pumping to shoal the depth of the circumpolar deep water, and further affect the WW thickness. This study contributes to an in-depth understanding of the specific response of water columns in the Southern Ocean to the high-frequency variability of external forcing.

the Indian Ocean Sector of the Southern Ocean  /  winter water  /  interannual variability  /  external forcing
Lingqiao Cheng, Junjie Meng, Deng Li, Yujiro Kitade, Chunling Zhang, Juncheng Zuo. Interannual variability of winter water in the Indian Ocean Sector of the Southern Ocean and its causes during 2011−2020[J]. Haiyang Xuebao, 2023 , 45 (8) : 11 -23 . DOI: 10.12284/hyxb2023100
Year 2023 volume 45 Issue 8
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Article Info
doi: 10.12284/hyxb2023100
  • Receive Date:2022-11-09
  • Online Date:2025-12-28
  • Published:2023-08-31
Article Data
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History
  • Received:2022-11-09
  • Revised:2023-03-31
Funding
Affiliations
    1College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China
    2Key Laboratory of Marine Ecological Monitoring and Restoration Technologies, Ministry of Natural Resources, Shanghai 201306, China
    3Center for Polar Research, Shanghai Ocean University, Shanghai 201306, China
    4Department of Ocean Sciences, Tokyo University of Marine Science and Technology, Tokyo 108-8477, Japan
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表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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