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Earthquake magnitude with DAS: a transferable data-based scaling relation
  • +9
  • Jiuxun Yin,
  • Weiqiang Zhu,
  • Jiaxuan Li,
  • Ettore Biondi,
  • Yaolin Miao,
  • Zack Jack Spica,
  • Loïc Viens,
  • Masanao Shinohara,
  • Satoshi Ide,
  • Kimihiro Mochizuki,
  • Allen LeRoy Husker,
  • Zhongwen Zhan
Jiuxun Yin
California Institute of Technology

Corresponding Author:[email protected]

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Weiqiang Zhu
California Institute of technology
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Jiaxuan Li
California Institute of Technology
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Ettore Biondi
California Institute of technology
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Yaolin Miao
University of Michigan
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Zack Jack Spica
University of Michigan
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Loïc Viens
Los Alamos National Laboratory
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Masanao Shinohara
University of Tokyo
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Satoshi Ide
University of Tokyo
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Kimihiro Mochizuki
University of Tokyo
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Allen LeRoy Husker
California Institute of Technology
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Zhongwen Zhan
California Institute of Technology
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Abstract

Distributed Acoustic Sensing (DAS) is a promising technique to improve the rapid detection and characterization of earthquakes. Due to some instrumental limitations, current DAS studies primarily focus on the phase information but less on the amplitude information. In this study, we compile earthquake data from two DAS arrays in California, USA, and one submarine array in Sanriku, Japan. We develop a data-driven method to obtain the first scaling relation between DAS amplitude and earthquake magnitude. Our results reveal that the DAS amplitude in different regions follows a similar scaling relation. The scaling relation can provide a rapid magnitude estimation and effectively avoid uncertainties caused by the conversion to ground motions. We finally show that the scaling relation is transferable from one to another new region. The scaling relation highlights the great potential of DAS in earthquake source characterization and early warning.
08 Feb 2023Submitted to ESS Open Archive
09 Feb 2023Published in ESS Open Archive