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Testing the correlations between anomalies of statistical indexes of the geoelectric system and earthquakes

Author

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  • Hong-Jia Chen

    (National Central University
    ETH Zürich)

  • Chien-Chih Chen

    (National Central University)

Abstract

Geoelectric precursors are considered to be predictors of earthquakes, but this issue is still under debate. The objective of this research is to statistically test the relationship between the geoelectric system and earthquakes. We observed that anomalies of skewness and kurtosis of geoelectric fields may precede large earthquakes. Next, we developed an alarm model of time of increased probability to quantitatively determine their relationship. Performing binary classification and C1–F1 analysis on both statistical anomalies and earthquake occurrences, the alarm model implies that the statistical correlation between the geoelectric system and earthquakes exists with high confidence. We explained the results by critical transition, which refers to the state of a system becoming slower as it recovers from small perturbations when the system approaches critical points. Hence, generic symptoms, such as autocorrelation, variance, skewness, and kurtosis, can vary appreciably. Early warning signals for critical transitions of the geoelectric system might correspond to impending large earthquakes, in agreement with independent suggestions by other authors that appeared very recently. Consequently, we suggest that the critical transition will take place in the crustal system. Furthermore, we establish a standard procedure to examine the relationship between potential precursor indexes and earthquakes.

Suggested Citation

  • Hong-Jia Chen & Chien-Chih Chen, 2016. "Testing the correlations between anomalies of statistical indexes of the geoelectric system and earthquakes," 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. 84(2), pages 877-895, November.
    • Handle: RePEc:spr:nathaz:v:84:y:2016:i:2:d:10.1007_s11069-016-2460-4
    DOI: 10.1007/s11069-016-2460-4
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    References listed on IDEAS

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    1. Vasilis Dakos & Stephen R Carpenter & William A Brock & Aaron M Ellison & Vishwesha Guttal & Anthony R Ives & Sonia Kéfi & Valerie Livina & David A Seekell & Egbert H van Nes & Marten Scheffer, 2012. "Methods for Detecting Early Warnings of Critical Transitions in Time Series Illustrated Using Simulated Ecological Data," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-20, July.
    2. Telesca, Luciano & Lovallo, Michele & Ramirez-Rojas, Alejandro & Angulo-Brown, Fernando, 2009. "A nonlinear strategy to reveal seismic precursory signatures in earthquake-related self-potential signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(10), pages 2036-2040.
    3. Marten Scheffer & Jordi Bascompte & William A. Brock & Victor Brovkin & Stephen R. Carpenter & Vasilis Dakos & Hermann Held & Egbert H. van Nes & Max Rietkerk & George Sugihara, 2009. "Early-warning signals for critical transitions," Nature, Nature, vol. 461(7260), pages 53-59, September.
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