A Generic Model of Global Earthquake Rupture Characteristics Revealed by Machine Learning

Rupture processes of global large earthquakes have been observed to exhibit great variability, whereas recent studies suggest that the average rupture behavior could be unexpectedly simple. To what extent do large earthquakes share common rupture characteristics? Here, we use a machine learning algo...

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Bibliographic Details
Published in:Geophysical research letters 2022-04, Vol.49 (8), p.n/a
Main Author: Li, Zefeng
Format: Article
Language:English
Subjects:
Algorithms
Earthquake magnitude
Earthquake prediction
earthquake process
Earthquakes
Learning algorithms
Learning behaviour
Machine learning
Modelling
Origins
Rupture
Rupturing
Seismic activity
Similarity
source time function
Time functions
Variability
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Summary:Rupture processes of global large earthquakes have been observed to exhibit great variability, whereas recent studies suggest that the average rupture behavior could be unexpectedly simple. To what extent do large earthquakes share common rupture characteristics? Here, we use a machine learning algorithm to derive a generic model of global earthquake source time functions. The model indicates that simple and homogeneous ruptures are pervasive whereas complex and irregular ruptures are relatively rare. Despite the standard long‐tail and near‐symmetric moment release processes, the model reveals two special rupture types: runaway earthquakes with weak growing phases and relatively abrupt termination, and complex earthquakes with all faulting mechanisms but mostly shallow origins (
ISSN:0094-8276
1944-8007
DOI:10.1029/2021GL096464