How soon would the next mega-earthquake occur in Japan?

Author(s)
Alexey Lyubushin

ABSTRACT

The problem of seismic danger estimate in Japan after Tohoku mega-earthquake 11 March of 2011 is considered. The estimates are based on processing low-frequency seismic noise wave-forms from broadband network F-net. A new method of dynamic estimate of seismic danger is used for this problem. The method is based on calculating multi-fractal properties and minimum entropy of squared orthogonal wavelet coefficients for seismic noise. The analysis of the data using notion of “spots of seismic danger” shows that the seismic danger in Japan remains at high level after 2011. 03. 11 within north-east part of Philippine plate—at the region of Nankai Though which traditionally is regarded as the place of strongest earthquakes. It is well known that estimate of time moment of future shock is the most difficult problem in earthquake prediction. In this paper we try to find some peculiarities of the seismic noise data which could extract future danger time interval by analogy with the behavior before Tohoku earthquake. Two possible precursors of this type were found. They are the results of estimates within 1-year moving time window: based on correlation between 2 mean multi-fractal parameters of the noise and based on cluster analysis of annual clouds of 4 mean noise parameters. Both peculiarities of the noise data extract time interval 2013-2014 as the danger.

Cite this paper

Lyubushin, A. (2013) How soon would the next mega-earthquake occur in Japan?.*Natural Science*, **5**, 1-7. doi: 10.4236/ns.2013.58A1001.

Lyubushin, A. (2013) How soon would the next mega-earthquake occur in Japan?.

References

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[5] Kobayashi N. and Nishida, K. (1998) Continuous excita tion of planetary free oscillations by atmospheric distur bances. Nature, 395, 357-360. doi:10.1038/26427

[6] Tanimoto, T. (2005) The oceanic excitation hypothesis for the continuous oscillations of the Earth. Geophysical Journal International, 160, 276-288. doi:10.1111/j.1365-246X.2004.02484.x

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[8] Lyubushin, A.A. (2009) Synchronization trends and rhythms of multifractal parameters of the field of low frequency microseisms. Izvestiya, Physics of the Solid Earth, 45, 381-394. doi:10.1134/S1069351309050024

[9] Lyubushin, A.A. (2010) The statistics of the time seg ments of low-frequency microseisms: Trends and syn chronization. Izvestiya, Physics of the Solid Earth, 46, 544-554. doi:10.1134/S1069351310060091

[10] Lyubushin, A. (2010) Multifractal parameters of low frequency microseisms. In: de Rubeis, V., et al., Eds., Synchronization and Triggering: From Fracture to Earth quake Processes. GeoPlanet: Earth and Planetary Sci ences 1, Springer-Verlag, Berlin Heidelberg, 2010, Chap ter 15, 253-272. doi:10.1007/978-3-642-12300-9_15

[11] Lyubushin, A.A. (2011) Cluster analysis of low-frequency microseismic noise. Izvestiya, Physics of the Solid Earth, 47, 488-495. doi:10.1134/S1069351311040057

[12] Lyubushin, A.A. (2011) Seismic catastrophe in Japan on March 11, 2011: Long-term prediction on the basis of low-frequency microseisms. Izvestiya, Atmospheric and Oceanic Physics, 46, 904-921. doi:10.1134/S0001433811080056

[13] Lyubushin, A. (2012) Prognostic properties of low-fre quency seismic noise. Natural Science, 4, 659-666. doi:10.4236/ns.2012.428087

[14] Lyubushin, A.A. (2013) Mapping the Properties of Low Frequency Microseisms for Seismic Hazard Assessment. Izvestiya, Physics of the Solid Earth, 49, 9-18. doi:10.1134/S1069351313010084

[15] Lyubushin, A.A. (2013) Spots of seismic danger extracted by properties of low-frequency seismic noise. Geophysi cal Research Abstracts, Vol. 15, 2013, 1 Pages.

[16] Feder, J. (1988) Fractals. Plenum Press, New York, London.

[17] Kantelhardt, J.W., Zschiegner, S.A., Konscienly-Bunde, E., Havlin, S., Bunde, A. and Stanley, H.E. (2002) Multi fractal detrended fluctuation analysis of nonstationary time series. Physica A, 316, 87-114. doi:10.1016/S0378-4371(02)01383-3

[18] Mallat, S. (1998) A wavelet tour of signal processing. Academic Press, San Diego, London, Boston, Sydney, Tokyo, Toronto.

[19] Huber, P.J. and Ronchetti, E.M. (2009) Robust statistics, 2nd Edition, John Wiley & Sons, Inc., Hoboken, 354 Pages. doi:10.1002/9780470434697

[20] Duda, R.O., Hart, P.E. and Stork, D.G. (2000) Pattern Classification. Wiley-Interscience Publication, Hoboken, 680 Pages.

[21] Vogel, M.A. and Wong, A.K.C. (1979) PFS Clustering method. IEEE Transactions on Pattern Analysis and Ma chine Intelligence, 1, 237-245. doi:10.1109/TPAMI.1979.4766919

[1] Rikitake, T. (1999) Probability of a great earthquake to recur in the Tokai district, Japan: Reevaluation based on newly-developed paleoseismology, plate tectonics, tsu nami study, micro-seismicity and geodetic measurements. Earth, Planets and Space, 51, 147-157.

[2] Mogi, K. (2004) Two grave issues concerning the ex pected Tokai Earthquake. Earth, Planets and Space, 56, li-lxvi.

[3] Simons, M., Minson, S.E., Sladen, A., Ortega, F., Jiang, J., Owen, S.E., Meng, L., Ampuero, J.-P., Wei, S., Chu, R., Helmberger, D.V., Kanamori, H., Hetland, E., Moore, A.W. and Webb, F.H. (2011) The 2011 magnitude 9.0 Tohoku-Oki earthquake: Mosaicking the megathrust from seconds to centuries. Science, 332, 911. doi:10.1126/science.332.6032.911

[4] Kagan Y.Y. and Jackson D.D. (2013) Tohoku earthquake: A Surprise? Bulletin of the Seismological Society of America, 103, 1181-1194. doi:10.1785/0120120110

[5] Kobayashi N. and Nishida, K. (1998) Continuous excita tion of planetary free oscillations by atmospheric distur bances. Nature, 395, 357-360. doi:10.1038/26427

[6] Tanimoto, T. (2005) The oceanic excitation hypothesis for the continuous oscillations of the Earth. Geophysical Journal International, 160, 276-288. doi:10.1111/j.1365-246X.2004.02484.x

[7] Rhie, J. and Romanowicz, B. (2004) Excitation of Earth’s continuous free oscillations by atmosphere-ocean-sea floor coupling. Nature, 431, 552-554. doi:10.1038/nature02942

[8] Lyubushin, A.A. (2009) Synchronization trends and rhythms of multifractal parameters of the field of low frequency microseisms. Izvestiya, Physics of the Solid Earth, 45, 381-394. doi:10.1134/S1069351309050024

[9] Lyubushin, A.A. (2010) The statistics of the time seg ments of low-frequency microseisms: Trends and syn chronization. Izvestiya, Physics of the Solid Earth, 46, 544-554. doi:10.1134/S1069351310060091

[10] Lyubushin, A. (2010) Multifractal parameters of low frequency microseisms. In: de Rubeis, V., et al., Eds., Synchronization and Triggering: From Fracture to Earth quake Processes. GeoPlanet: Earth and Planetary Sci ences 1, Springer-Verlag, Berlin Heidelberg, 2010, Chap ter 15, 253-272. doi:10.1007/978-3-642-12300-9_15

[11] Lyubushin, A.A. (2011) Cluster analysis of low-frequency microseismic noise. Izvestiya, Physics of the Solid Earth, 47, 488-495. doi:10.1134/S1069351311040057

[12] Lyubushin, A.A. (2011) Seismic catastrophe in Japan on March 11, 2011: Long-term prediction on the basis of low-frequency microseisms. Izvestiya, Atmospheric and Oceanic Physics, 46, 904-921. doi:10.1134/S0001433811080056

[13] Lyubushin, A. (2012) Prognostic properties of low-fre quency seismic noise. Natural Science, 4, 659-666. doi:10.4236/ns.2012.428087

[14] Lyubushin, A.A. (2013) Mapping the Properties of Low Frequency Microseisms for Seismic Hazard Assessment. Izvestiya, Physics of the Solid Earth, 49, 9-18. doi:10.1134/S1069351313010084

[15] Lyubushin, A.A. (2013) Spots of seismic danger extracted by properties of low-frequency seismic noise. Geophysi cal Research Abstracts, Vol. 15, 2013, 1 Pages.

[16] Feder, J. (1988) Fractals. Plenum Press, New York, London.

[17] Kantelhardt, J.W., Zschiegner, S.A., Konscienly-Bunde, E., Havlin, S., Bunde, A. and Stanley, H.E. (2002) Multi fractal detrended fluctuation analysis of nonstationary time series. Physica A, 316, 87-114. doi:10.1016/S0378-4371(02)01383-3

[18] Mallat, S. (1998) A wavelet tour of signal processing. Academic Press, San Diego, London, Boston, Sydney, Tokyo, Toronto.

[19] Huber, P.J. and Ronchetti, E.M. (2009) Robust statistics, 2nd Edition, John Wiley & Sons, Inc., Hoboken, 354 Pages. doi:10.1002/9780470434697

[20] Duda, R.O., Hart, P.E. and Stork, D.G. (2000) Pattern Classification. Wiley-Interscience Publication, Hoboken, 680 Pages.

[21] Vogel, M.A. and Wong, A.K.C. (1979) PFS Clustering method. IEEE Transactions on Pattern Analysis and Ma chine Intelligence, 1, 237-245. doi:10.1109/TPAMI.1979.4766919