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

Chen, Han; Yang, Hongfeng; Zhu, Gaohua; Xu, Min; Lin, Jian; You, Qinglong

doi:10.1029/2022gl097779

Cited by 20 publications

(12 citation statements)

References 69 publications

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“…For example, expanding to global OTF events would advance our understanding of OTF earthquake mechanics (e.g., Boettcher & Jordan, 2004; Shi et al., 2022). It is also straightforward to use this computationally efficient SEM‐DSM code for modeling teleseismic waves from earthquakes at outer‐rise regions of subduction zones, where the associated hydration processes could have substantial impacts on deep Earth material recycling (Cai et al., 2018; Chen et al., 2022; Emry & Wiens, 2015), and in subducted zones, which could generate serious seismic hazards (Lay et al., 2019; Lay & Rhode, 2019; Wang & Yue, 2022).…”

Section: Discussionmentioning

confidence: 99%

A Reciprocity‐Based Efficient Method for Improved Source Parameter Estimation of Submarine Earthquakes With Hybrid 3‐D Teleseismic Green's Functions

Zang,

Wu,

et al. 2024

JGR Solid Earth

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Accurate source parameters of global submarine earthquakes are essential for understanding earthquake mechanics and tectonic dynamics. Previous studies have demonstrated that teleseismic P coda waveform complexities due to near‐source 3‐D structures are highly sensitive to source parameters of marine earthquakes. Leveraging these sensitivities, we can improve the accuracy of source parameter inversion compared to traditional 1‐D methods. However, modeling these intricate 3‐D effects poses significant computational challenges. To address this issue, we propose a novel reciprocity‐based hybrid method for computing 3‐D teleseismic Green's functions. Based on this method, we develop a grid‐search inversion workflow for determining reliable source parameters of moderate‐sized submarine earthquakes. The method is tested and proven on five Mw5+ earthquakes at the Blanco oceanic transform fault (OTF) with ground truth locations resolved by a local ocean bottom seismometer array, using ambient noise correlation and surface‐wave relocation techniques. Our results show that fitting P coda waveforms through 3‐D Green's functions can effectively improve the source location accuracy, especially for the centroid depth. Our improved centroid depths indicate that all the five Mw5+ earthquakes on the Blanco transform fault ruptured mainly above the depth of 600°C isotherm predicted by the half‐space cooling model. This finding aligns with the hypothesis that the rupture zone of large earthquakes at OTFs is confined by the 600°C isotherm. However, it is noted that the Blanco transform fault serves as a case study. Our 3‐D source inversion method offers a promising tool for systematically investigating global oceanic earthquakes using teleseismic waves.

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Section: Discussionmentioning

confidence: 99%

A Reciprocity‐Based Efficient Method for Improved Source Parameter Estimation of Submarine Earthquakes With Hybrid 3‐D Teleseismic Green's Functions

Zang,

Wu,

et al. 2024

JGR Solid Earth

Self Cite

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“…Similar to template matching, the recent ML-based method often increases the number of events in catalogs by tenfold compared with conventional approaches (Tan et al 2021;Ma and Chen 2022) with a much lower computation cost (Perol et al 2018). By benefiting from the developments in this field, many studies exploring seismicity with high resolution have been published (Liu et al 2020;Park et al 2020;Ross et al 2020;Wang et al 2020a;Baker et al 2021;Li et al 2021;Jiang et al 2022;Gong et al 2022a;Chen et al 2022a). This improvement in catalog quality is expected to improve earthquake forecasts based on seismicity models (Mancini et al 2022).…”

Section: Importance Of Improving Earthquake Cataloging Methods and Co...mentioning

confidence: 99%

Recent advances in earthquake seismology using machine learning

Kubo,

Naoi,

Kano

2024

Earth Planets Space

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Given the recent developments in machine-learning technology, its application has rapidly progressed in various fields of earthquake seismology, achieving great success. Here, we review the recent advances, focusing on catalog development, seismicity analysis, ground-motion prediction, and crustal deformation analysis. First, we explore studies on the development of earthquake catalogs, including their elemental processes such as event detection/classification, arrival time picking, similar waveform searching, focal mechanism analysis, and paleoseismic record analysis. We then introduce studies related to earthquake risk evaluation and seismicity analysis. Additionally, we review studies on ground-motion prediction, which are categorized into four groups depending on whether the output is ground-motion intensity or ground-motion time series and the input is features (individual measurable properties) or time series. We discuss the effect of imbalanced ground-motion data on machine-learning models and the approaches taken to address the problem. Finally, we summarize the analysis of geodetic data related to crustal deformation, focusing on clustering analysis and detection of geodetic signals caused by seismic/aseismic phenomena. Graphical Abstract

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“…3 are from Craig et al ( 2014a ). Microseismicity data are from Hino et al ( 2009 ), Gamage et al ( 2009 ), Obana et al ( 2012 ), (Obana et al 2014 ) and Obana et al ( 2018 ) for Honshu, and Zhu et al ( 2019 ) and (Chen et al 2022 ) for the Marianas (shallow and deeper regions, respecti vel y).…”

Section: A C K N O W L E D G M E N T Smentioning

confidence: 99%

Plate bending earthquakes and the strength distribution of the lithosphere

Sandiford

Craig

2023

Geophysical Journal International

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Summary This study investigates the dynamics and constitutive behaviour of the oceanic lithosphere as it bends and yields during subduction. Two main observational constraints are considered: the maximum bending moment that can be supported by the lithosphere, and the inferred neutral plane depth in bending. We particularly focus on regions of old lithosphere where the ‘apparent’ neutral plane depth is about 30 km. We use subduction modelling approaches to investigate these flexural characteristics. We reassess bending moment estimates from a range of previous studies, and show a significant convergence towards what we call the ‘intermediate’ range of lithosphere strength: weaker than some classical models predict, but stronger than recent inferences at seamounts. We consider the non-uniqueness that arises due to the trade-offs in strength as well background (tectonic) stress state. We outline this problem with several end-member models, which differ in regard to relative strength in the brittle and ductile regimes. We evaluate the consistency of these models in terms of a range of constraints, primarily the seismic expression of the outer rise. We show that a 30 km neutral plane depth implies that net slab pull is not greater than about 2 TN/m. In contrast, models with low brittle strength imply that regions with a 30 km neutral plane depth are under moderate net axial compression. Under these conditions, reverse faulting is predicted beneath the neutral plane at depths > 30 km. We show that moderate variations in background stress have a large impact on the predicted anelastic dissipation. We suggest brittle reverse faulting is a marginal phenomenon which may be inhibited by moderate changes in background stress.

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

Cited by 20 publications

References 69 publications

A Reciprocity‐Based Efficient Method for Improved Source Parameter Estimation of Submarine Earthquakes With Hybrid 3‐D Teleseismic Green's Functions

A Reciprocity‐Based Efficient Method for Improved Source Parameter Estimation of Submarine Earthquakes With Hybrid 3‐D Teleseismic Green's Functions

Recent advances in earthquake seismology using machine learning

Plate bending earthquakes and the strength distribution of the lithosphere

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