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

Abstract 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 o...

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Main Authors: Han Chen, Hongfeng Yang, Gaohua Zhu, Min Xu, Jian Lin, Qingyu You
Format: Article
Language:English
Published: Wiley 2022-06-01
Series:Geophysical Research Letters
Subjects:
Online Access:https://doi.org/10.1029/2022GL097779
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author Han Chen
Hongfeng Yang
Gaohua Zhu
Min Xu
Jian Lin
Qingyu You
author_facet Han Chen
Hongfeng Yang
Gaohua Zhu
Min Xu
Jian Lin
Qingyu You
author_sort Han Chen
collection DOAJ
description Abstract 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.
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institution Kabale University
issn 0094-8276
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language English
publishDate 2022-06-01
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series Geophysical Research Letters
spelling doaj-art-636a766e169947f49f6a006beaa350d72025-01-22T14:38:16ZengWileyGeophysical Research Letters0094-82761944-80072022-06-014912n/an/a10.1029/2022GL097779Deep Outer‐Rise Faults in the Southern Mariana Subduction Zone Indicated by a Machine‐Learning‐Based High‐Resolution Earthquake CatalogHan Chen0Hongfeng Yang1Gaohua Zhu2Min Xu3Jian Lin4Qingyu You5Earth System Science Programme Faculty of Science The Chinese University of Hong Kong Hong Kong ChinaEarth System Science Programme Faculty of Science The Chinese University of Hong Kong Hong Kong ChinaEarth System Science Programme Faculty of Science The Chinese University of Hong Kong Hong Kong ChinaKey Laboratory of Marginal Sea Geology Chinese Academy of Sciences South China Sea Institute of Oceanology Guangzhou ChinaKey Laboratory of Marginal Sea Geology Chinese Academy of Sciences South China Sea Institute of Oceanology Guangzhou ChinaKey Laboratory of Petroleum Resources Research Institute of Geology and Geophysics Chinese Academy of Sciences Beijing ChinaAbstract 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.https://doi.org/10.1029/2022GL097779outer‐rise faultMariana Subduction ZoneEQTransformerocean bottom seismometer
spellingShingle Han Chen
Hongfeng Yang
Gaohua Zhu
Min Xu
Jian Lin
Qingyu You
Deep Outer‐Rise Faults in the Southern Mariana Subduction Zone Indicated by a Machine‐Learning‐Based High‐Resolution Earthquake Catalog
Geophysical Research Letters
outer‐rise fault
Mariana Subduction Zone
EQTransformer
ocean bottom seismometer
title Deep Outer‐Rise Faults in the Southern Mariana Subduction Zone Indicated by a Machine‐Learning‐Based High‐Resolution Earthquake Catalog
title_full Deep Outer‐Rise Faults in the Southern Mariana Subduction Zone Indicated by a Machine‐Learning‐Based High‐Resolution Earthquake Catalog
title_fullStr Deep Outer‐Rise Faults in the Southern Mariana Subduction Zone Indicated by a Machine‐Learning‐Based High‐Resolution Earthquake Catalog
title_full_unstemmed Deep Outer‐Rise Faults in the Southern Mariana Subduction Zone Indicated by a Machine‐Learning‐Based High‐Resolution Earthquake Catalog
title_short Deep Outer‐Rise Faults in the Southern Mariana Subduction Zone Indicated by a Machine‐Learning‐Based High‐Resolution Earthquake Catalog
title_sort deep outer rise faults in the southern mariana subduction zone indicated by a machine learning based high resolution earthquake catalog
topic outer‐rise fault
Mariana Subduction Zone
EQTransformer
ocean bottom seismometer
url https://doi.org/10.1029/2022GL097779
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AT gaohuazhu deepouterrisefaultsinthesouthernmarianasubductionzoneindicatedbyamachinelearningbasedhighresolutionearthquakecatalog
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AT jianlin deepouterrisefaultsinthesouthernmarianasubductionzoneindicatedbyamachinelearningbasedhighresolutionearthquakecatalog
AT qingyuyou deepouterrisefaultsinthesouthernmarianasubductionzoneindicatedbyamachinelearningbasedhighresolutionearthquakecatalog