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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| Format: | Article |
| Language: | English |
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Wiley
2022-06-01
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| Series: | Geophysical Research Letters |
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| 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. |
| format | Article |
| id | doaj-art-636a766e169947f49f6a006beaa350d7 |
| institution | Kabale University |
| issn | 0094-8276 1944-8007 |
| language | English |
| publishDate | 2022-06-01 |
| publisher | Wiley |
| record_format | Article |
| 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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