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Deep Outer-Rise Faults in the Southern Mariana Subduction Zone Indicated by a Machine-Learning-Based High-Resolution Earthquake Catalog

文献类型：期刊论文

作者Chen, Han9; Yang, Hongfeng8,9; Zhu, Gaohua6,7,9; Xu, Min4,5; Lin, Jian1,3,5; You, Qingyu2
刊名GEOPHYSICAL RESEARCH LETTERS
出版日期2022-06-28
卷号49期号:12页码:12
ISSN号0094-8276
关键词outer-rise fault Mariana Subduction Zone EQTransformer ocean bottom seismometer
DOI10.1029/2022GL097779
通讯作者Yang, Hongfeng(hyang@cuhk.edu.hk)
英文摘要Outer-rise faults are predominantly concentrated near ocean trenches due to subducted plate bending. These faults play crucial roles in the hydration of subducted plates and the consequent subducting processes. However, it has not yet been possible to develop high-resolution structures of outer-rise faults due to the lack of near-field observations. In this study we deployed an ocean bottom seismometer (OBS) network near the Challenger Deep in the Southernmost Mariana Trench, between December 2016 and June 2017, covering both the overriding and subducting plates. We applied a machine-learning phase detector (EQTransformer) to the OBS data and found more than 1,975 earthquakes. An identified outer-rise event cluster revealed an outer-rise fault penetrating to depths of 50 km, which was inferred as a normal fault based on the extensional depth from tomographic images in the region, shedding new lights on water input at the southmost Mariana subduction zone.
资助项目National Natural Science Foundation of China[91858207] ; National Natural Science Foundation of China[92158205] ; National Natural Science Foundation of China[41890813] ; Hong Kong Research Grant Council[14304820] ; CORE ; Chinese Academy of Sciences[Y4SL021001] ; Chinese Academy of Sciences[QYZDY-SSW-DQC005] ; Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Faculty of Science at CUHK[GML2019ZD0205]
WOS研究方向Geology
语种英语
出版者AMER GEOPHYSICAL UNION
WOS记录号WOS:000813617100001
源URL[http://ir.qdio.ac.cn/handle/337002/179655]  
专题海洋研究所_海洋地质与环境重点实验室
通讯作者Yang, Hongfeng
作者单位1.Woods Hole Oceanog Inst, Dept Geol & Geophys, Falmouth, MA USA
2.Chinese Acad Sci, Inst Geol & Geophys, Key Lab Petr Resources Res, Beijing, Peoples R China
3.Southern Univ Sci & Technol, Dept Ocean Sci & Engn, Shenzhen, Peoples R China
4.Southern Marine Sci & Engn Guangdong Lab Guangzho, Guangzhou, Peoples R China
5.Chinese Acad Sci, South China Sea Inst Oceanol, Key Lab Marginal Sea Geol, Guangzhou, Peoples R China
6.Qingdao Natl Lab Marine Sci & Technol, Lab Marine Geol, Qingdao, Peoples R China
7.Chinese Acad Sci, Inst Oceanol, Ctr Ocean Mega Sci, CAS Key Lab Marine Geol & Environm, Qingdao, Peoples R China
8.Chinese Univ Hong Kong, Shenzhen Res Inst, Shenzhen, Peoples R China
9.Chinese Univ Hong Kong, Earth Syst Sci Programme, Fac Sci, Hong Kong, Peoples R China
推荐引用方式
GB/T 7714		 Chen, Han,Yang, Hongfeng,Zhu, Gaohua,et al. Deep Outer-Rise Faults in the Southern Mariana Subduction Zone Indicated by a Machine-Learning-Based High-Resolution Earthquake Catalog[J]. GEOPHYSICAL RESEARCH LETTERS,2022,49(12):12.
APA Chen, Han,Yang, Hongfeng,Zhu, Gaohua,Xu, Min,Lin, Jian,&You, Qingyu.(2022).Deep Outer-Rise Faults in the Southern Mariana Subduction Zone Indicated by a Machine-Learning-Based High-Resolution Earthquake Catalog.GEOPHYSICAL RESEARCH LETTERS,49(12),12.
MLA Chen, Han,et al."Deep Outer-Rise Faults in the Southern Mariana Subduction Zone Indicated by a Machine-Learning-Based High-Resolution Earthquake Catalog".GEOPHYSICAL RESEARCH LETTERS 49.12(2022):12.

入库方式： OAI收割

来源：海洋研究所

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