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Projectied longterm trend of the Southeast Indian subantarctic mode water under climate change scenarios
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Zishan Qiu1, 2, 3, 4, Tengfei Xu1, 2, 3, 4, *, Zexun Wei1, 2, 3, 4, Xunwei Nie1, 2, 3, 4
Haiyang Xuebao | 2021, 43(11) : 1 - 21
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Haiyang Xuebao | 2021, 43(11): 1-21
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Projectied longterm trend of the Southeast Indian subantarctic mode water under climate change scenarios
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Zishan Qiu1, 2, 3, 4, Tengfei Xu1, 2, 3, 4, *, Zexun Wei1, 2, 3, 4, Xunwei Nie1, 2, 3, 4
Affiliations
  • 1Frist Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China
  • 2Key Laboratory of Marine Science and Numerical Modeling, Ministry of Natural Resources, Qingdao 266001, China
  • 3Shandong Key Laboratory of Marine Science and Numerical Modeling, Qingdao 266061, China
  • 4Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266237, China
Published: 2021-11-25 doi: 10.12284/hyxb2021127
Outline
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Based on the outputs of eight earth system models involved in the Coupled Model Intercomparison Project Phase 6 (CMIP6), this study assessed the simulation skill of the Southeast Indian subantarctic mode water (SEISAMW) of these models by comparing with observations. Moreover, this study investigated the projected long-term trends in subduction rate, volume and properties of the SEISAMW under medium and high greenhouse gas emission scenarios (i.e., SSP245, SSP585). The results show that the CMIP6 models generally have produced artificially greater mixed layer depth and smaller upper layer potential density in comparison with those of the Argo observation. Consequently, the simulated SEISAMW in the CMIP6 models are generally with larger subduction rate and smaller potential density. Meanwhile, the subduction regions of the SEISAMWs show significant differences among the analyzed CMIP6 models, which are attribute to lateral induction in the mixed layer. Furthermore, in the historical, SSP245 and SSP585 outputs, the SEISAMWs show consistent decreasing trends in subduction rate and volume, increasing trend in temperature, and decreasing trends in salinity and potential density. The long-term trends of the SEISAMWs are largest under SSP585 scenario, followed by the SSP245 scenario and historical simulation. The projected trends of SEISAMW can be explained by the following mechanism: the temperature and freshwater flux in the southeastern Indian Ocean upper layer tend to increase under enhanced radioactive forcing, resulting in shoaling in mixed layer and flattening of the mixed layer gradient. As a result, the trends of SEISAMWs in subduction rate, volume and water properties show larger values in accordance with stronger radioactive forcing.

CMIP6  /  Southeast Indian Ocean  /  subantarctic mode water  /  subduction rate  /  climate change  /  scenario experiments
Zishan Qiu, Tengfei Xu, Zexun Wei, Xunwei Nie. Projectied longterm trend of the Southeast Indian subantarctic mode water under climate change scenarios[J]. Haiyang Xuebao, 2021 , 43 (11) : 1 -21 . DOI: 10.12284/hyxb2021127
Year 2021 volume 43 Issue 11
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Article Info
doi: 10.12284/hyxb2021127
  • Receive Date:2020-12-04
  • Online Date:2026-02-26
  • Published:2021-11-25
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History
  • Received:2020-12-04
  • Revised:2021-01-26
Funding
Affiliations
    1Frist Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China
    2Key Laboratory of Marine Science and Numerical Modeling, Ministry of Natural Resources, Qingdao 266001, China
    3Shandong Key Laboratory of Marine Science and Numerical Modeling, Qingdao 266061, China
    4Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266237, China
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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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