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Foreshock sequences and short-term earthquake predictability on East Pacific Rise transform faults

Author

Listed:
  • Jeffrey J. McGuire

    (Woods Hole Oceanographic Institution)

  • Margaret S. Boettcher

    (MIT-Woods Hole Oceanographic Institution Joint Program)

  • Thomas H. Jordan

    (University of Southern California)

Abstract

East Pacific Rise transform faults are characterized by high slip rates (more than ten centimetres a year), predominately aseismic slip and maximum earthquake magnitudes of about 6.5. Using recordings from a hydroacoustic array deployed by the National Oceanic and Atmospheric Administration, we show here that East Pacific Rise transform faults also have a low number of aftershocks and high foreshock rates compared to continental strike-slip faults. The high ratio of foreshocks to aftershocks implies that such transform-fault seismicity cannot be explained by seismic triggering models in which there is no fundamental distinction between foreshocks, mainshocks and aftershocks. The foreshock sequences on East Pacific Rise transform faults can be used to predict (retrospectively) earthquakes of magnitude 5.4 or greater, in narrow spatial and temporal windows and with a high probability gain. The predictability of such transform earthquakes is consistent with a model in which slow slip transients trigger earthquakes, enrich their low-frequency radiation and accommodate much of the aseismic plate motion.

Suggested Citation

  • Jeffrey J. McGuire & Margaret S. Boettcher & Thomas H. Jordan, 2005. "Foreshock sequences and short-term earthquake predictability on East Pacific Rise transform faults," Nature, Nature, vol. 434(7032), pages 457-461, March.
    • Handle: RePEc:nat:nature:v:434:y:2005:i:7032:d:10.1038_nature03377
    DOI: 10.1038/nature03377
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    Cited by:

    1. Kádár, Viktória & Danku, Zsuzsa & Pál, Gergő & Kun, Ferenc, 2022. "Approach to failure through record breaking avalanches in a heterogeneous stress field," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
    2. K. M. Asim & F. Martínez-Álvarez & A. Basit & T. Iqbal, 2017. "Earthquake magnitude prediction in Hindukush region using machine learning techniques," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 85(1), pages 471-486, January.

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