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Nonlinear Processes in Geophysics An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/npg-2019-19
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-2019-19
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 15 Jul 2019

Submitted as: research article | 15 Jul 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Nonlinear Processes in Geophysics (NPG).

Magnitude correlations in a self-similar aftershock rates model of seismicity

Andres F. Zambrano Moreno1 and Jörn Davidsen1,2 Andres F. Zambrano Moreno and Jörn Davidsen
  • 1Department of Physics and Astronomy, University of Calgary, 2500 University Drive NW Calgary, Alberta T2N 1N4, Canada
  • 2Hotchkiss Brain Institute, University of Calgary, 3330 Hospital Dr NW, Calgary, Alberta T2N 4N1, Canada

Abstract. Crucial to the development of earthquake forecasting schemes is the manifestation of spatiotemporal correlations between earthquakes as highlighted, for example, by the notion of aftershocks. Here, we present an analysis of the statistical relation between subsequent magnitudes for a recently proposed self-similar aftershock rates model of seismicity, whose main distinguishing feature is that of interdependence between trigger and triggered events in terms of a time-varying frequency magnitude distribution. By means of a particular statistical measure, we study the level of magnitude correlations under specific types of time conditioning, explain their provenance within the model framework and show that the type of null model chosen in the analysis plays a pivotal role in the type and strength of observed correlations. Specifically, we show that while the variations in the magnitude distribution can give rise to large trivial correlations between subsequent magnitudes, the non-trivial magnitude correlations are rather minimal. Simulations mimicking Southern California show that these non-trivial correlations cannot be observed at the 3σ-level at the current level of completeness. We conclude that only the time variations in the frequency-magnitude distribution might lead to significant improvements in earthquake forecasting.

Andres F. Zambrano Moreno and Jörn Davidsen
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Status: open (until 09 Sep 2019)
Status: open (until 09 Sep 2019)
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Andres F. Zambrano Moreno and Jörn Davidsen
Data sets

SSAR magnitude correlation code, catalog, and plot data A. F. Zambrano Moreno https://doi.org/10.5683/SP2/PGYQEV

Model code and software

SSAR magnitude correlation code, catalog, and plot data A. F. Zambrano Moreno https://doi.org/10.5683/SP2/PGYQEV

Andres F. Zambrano Moreno and Jörn Davidsen
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Latest update: 19 Aug 2019
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Short summary
We study a model containing the characteristic of self-similarity (invariance under scale) which allows for scaling between lab experiments and geographical scale seismicity. Particular to this model is the dependency of the earthquake rates on the magnitude difference between events that are causally connected. We present results of a statistical analysis of magnitude correlations for the model along with its implications for the ongoing efforts in earthquake forecasting.
We study a model containing the characteristic of self-similarity (invariance under scale) which...
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