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Geophysical Journal International
Article . 2024 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Caltech Authors
Article . 2025
License: CC BY
Data sources: Caltech Authors
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Spatiotemporal forecast of extreme events in a chaotic model of slow slip events

Authors: Hojjat Kaveh; Jean Philippe Avouac; Andrew M Stuart;

Spatiotemporal forecast of extreme events in a chaotic model of slow slip events

Abstract

SUMMARY Seismic and aseismic slip events result from episodic slips on faults and are often chaotic due to stress heterogeneity. Their predictability in nature is a widely open question. In this study, we forecast extreme events in a numerical model. The model, which consists of a single fault governed by rate-and-state friction, produces realistic sequences of slow events with a wide range of magnitudes and interevent times. The complex dynamics of this system arise from partial ruptures. As the system self-organizes, the state of the system is confined to a chaotic attractor of a relatively small dimension. We identify the instability regions within this attractor where large events initiate. These regions correspond to the particular stress distributions that are favourable for near complete ruptures of the fault. We show that large events can be forecasted in time and space based on the determination of these instability regions in a low-dimensional space and the knowledge of the current slip rate on the fault.

Country
United States
Related Organizations
Keywords

Self-organization, Seismic cycle, Earthquake interaction, forecasting, and prediction–Numerical modelling

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Top 10%
Average
Average
Green
gold