Deep Outer-Rise Faults in the Southern Mariana Subduction Zone Indicated by a Machine-Learning-Based High-Resolution Earthquake Catalog
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.
NI Journal Papers
National Natural Science Foundation of China;National Natural Science Foundation of China;National Natural Science Foundation of China;Chinese Academy of Sciences[QYZDY-SSW-DQC005];Chinese Academy of Sciences[Y4SL021001];
|WOS Research Area|
|WOS Accession No|
|EI Accession Number|
Machine learning ; Oceanography ; Plates (structural components) ; Seismographs ; Tomography
|ESI Classification Code|
Structural Members and Shapes:408.2 ; Oceanography, General:471.1 ; Seismology:484 ; Earthquake Measurements and Analysis:484.1 ; Artificial Intelligence:723.4 ; Imaging Techniques:746 ; Special Purpose Instruments:943.3
|ESI Research Field|
Cited Times [WOS]:4
|Document Type||Journal Article|
|Department||Department of Ocean Science and Engineering|
1.Earth System Science Programme,Faculty of Science,The Chinese University of Hong Kong,Hong Kong
2.Shenzhen Research Institute,The Chinese University of Hong Kong,Shenzhen,China
3.CAS Key Laboratory of Marine Geology and Environment,Center for Ocean Mega-Science,Institute of Oceanology,Chinese Academy of Sciences,Qingdao,China
4.Laboratory for Marine Geology,Qingdao National Laboratory for Marine Science and Technology,Qingdao,China
5.Key Laboratory of Marginal Sea Geology,Chinese Academy of Sciences,South China Sea Institute of Oceanology,Guangzhou,China
6.Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou),Guangzhou,China
7.Department of Ocean Science and Engineering,Southern University of Science and Technology,Shenzhen,China
8.Department of Geology and Geophysics,Woods Hole Oceanographic Institution,Falmouth,United States
9.Key Laboratory of Petroleum Resources Research,Institute of Geology and Geophysics,Chinese Academy of Sciences,Beijing,China
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).
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).
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).
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