Prognostic properties of low-frequency seismic noise

ABSTRACT

The prognostic properties of four low-frequency seismic noise statistics are discussed: multi- fractal singularity spectrum support width, wavelet-based smoothness index of seismic noise waveforms, minimum normalized entropy of squared orthogonal wavelet coefficients and index of linear predictability. The proposed methods are illustrated by data analysis from broad-band seismic network F-net in Japan for more than 15 years of observation: since the beginning of 1997 up to 15 of May 2012. The previous analysis of multi-fractal properties of low-frequency seismic noise allowed a hypothesis about approaching Japan Islands to a future seismic catastrophe to be formulated at the middle of 2008. The base for such a hypothesis was statistically significant decreasing of multi-fractal singularity spectrum support width mean value. The peculiarities of correlation coefficient estimate within 1 year time window between median values of singularity spectra support width and generalized Hurst exponent allowed to make a decision that starting from July of 2010 Japan come to the state of waiting strong earthquake. This prediction of Tohoku mega-earthquake, initially with estimate of lower magnitude as 8.3 only (at the middle of 2008) and further on with estimate of the time beginning of waiting earthquake (from the middle of 2010) was published in advance in a number of scientific articles and abstracts on international conferences. It is shown that other 3 statistics (except singularity spectrum support width) could extract seismically danger domains as well. The analysis of seismic noise data after Tohoku mega-earthquake indicates increasing of probability of the 2nd strong earthquake within the region where the north part of Philippine sea plate is approaching island Honshu (Nankai Trough).

The prognostic properties of four low-frequency seismic noise statistics are discussed: multi- fractal singularity spectrum support width, wavelet-based smoothness index of seismic noise waveforms, minimum normalized entropy of squared orthogonal wavelet coefficients and index of linear predictability. The proposed methods are illustrated by data analysis from broad-band seismic network F-net in Japan for more than 15 years of observation: since the beginning of 1997 up to 15 of May 2012. The previous analysis of multi-fractal properties of low-frequency seismic noise allowed a hypothesis about approaching Japan Islands to a future seismic catastrophe to be formulated at the middle of 2008. The base for such a hypothesis was statistically significant decreasing of multi-fractal singularity spectrum support width mean value. The peculiarities of correlation coefficient estimate within 1 year time window between median values of singularity spectra support width and generalized Hurst exponent allowed to make a decision that starting from July of 2010 Japan come to the state of waiting strong earthquake. This prediction of Tohoku mega-earthquake, initially with estimate of lower magnitude as 8.3 only (at the middle of 2008) and further on with estimate of the time beginning of waiting earthquake (from the middle of 2010) was published in advance in a number of scientific articles and abstracts on international conferences. It is shown that other 3 statistics (except singularity spectrum support width) could extract seismically danger domains as well. The analysis of seismic noise data after Tohoku mega-earthquake indicates increasing of probability of the 2nd strong earthquake within the region where the north part of Philippine sea plate is approaching island Honshu (Nankai Trough).

Cite this paper

Lyubushin, A. (2012) Prognostic properties of low-frequency seismic noise.*Natural Science*, **4**, 659-666. doi: 10.4236/ns.2012.428087.

Lyubushin, A. (2012) Prognostic properties of low-frequency seismic noise.

References

[1] Kobayashi, N. and Nishida, K. (1998) Continuous excitation of planetary free oscillations by atmospheric disturbances. Nature, 395, 357-360. doi:10.1038/26427

[2] Tanimoto, T. (2001) Continuous free oscillations: Atmosphere-solid Earth coupling. Earth and Planetary Sciences, 29, 563-584. doi:10.1146/annurev.earth.29.1.563

[3] 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

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

[5] Lyubushin, A.A. (2008) Multifractal properties of low-frequency microseismic noise in Japan, 1997-2008. Book of Abstracts of 7th General Assembly of the Asian Seismological Commission and Japan Seismological Society, 2008 Fall Meeting, Tsukuba, 24-27 November 2008, 92.

[6] 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

[7] Lyubushin, A.A. (2010) Synchronization of multifractal parameters of regional and global low-frequency microseisms. European Geosciences Union General Assembly, Vienna, 2-7 May 2010, 696.

[8] Lyubushin, A.A. (2010) Synchronization phenomena of low-frequency microseisms. European Seismological Commission: 32nd General Assembly, 6-10 September 2010, Montpelier, 124.

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

[10] Lyubushin, A.A. (2010) Multifractal parameters of low-frequency microseisms. In: V. de Rubeis et al., Eds., Synchronization and triggering: From fracture to earthquake processes, Springer-Verlag, Berlin Heidelberg

[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.A. (2011) Prediction of Tohoku seismic catastrophe by microseismic noise multi-fractal properties. Abstract S53A-2273 Presented at 2011 Fall Meeting, American Geophysical Union, San Francisco, 5-9 December 2011.

[14] Ivanov, P.Ch., Amaral, L.A.N., Goldberger, A.L., Havlin, S., Rosenblum, M.B., Struzik, Z. and Stanley, H.E. (1999) Multifractality in healthy heartbeat dynamics. Nature, 399, 461-465. doi:10.1038/20924

[15] Pavlov, A.N. and Anishchenko, V.S. (2007) Multifractal analysis of complex signals. Physics-Uspekhi, 50, 819-834. doi:10.1070/PU2007v050n08ABEH006116

[16] Humeaua, A., Chapeau-Blondeau, F., Rousseau, D., Rousseau, P., Trzepizur, W. and Abraham, P. (2008) Multifractality, sample entropy, and wavelet analyses for age-related changes in the peripheral cardiovascular system: Preliminary results. Medical Physics, 35, 717-727. doi:10.1118/1.2831909

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

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

[19] Mallat, S. (1998) A wavelet tour of signal processing. Academic Press, San Diego.

[20] Box, G.E.P. and Jenkins, G.M. (1970) Time series analysis: Forecasting and control. Holden-Day. San Francisco.

[21] Kashyap, R.L. and Rao, A.R. (1976) Dynamic stochastic models from empirical data. Academic Press, New York.

[22] Hirata, T., Satoh, T. and Ito, K. (1987) Fractal structure of spatial distribution of microfacturing in rock. Geophysical Journal of the Royal Astronomical Society, 90, 369-377. doi:10.1111/j.1365-246X.1987.tb00732.x

[23] Turcotte, D.L. (1997) Fractals and chaos in geology and geophysics. 2nd Edition, Cambridge University Press, New York. doi:10.1017/CBO9781139174695

[1] Kobayashi, N. and Nishida, K. (1998) Continuous excitation of planetary free oscillations by atmospheric disturbances. Nature, 395, 357-360. doi:10.1038/26427

[2] Tanimoto, T. (2001) Continuous free oscillations: Atmosphere-solid Earth coupling. Earth and Planetary Sciences, 29, 563-584. doi:10.1146/annurev.earth.29.1.563

[3] 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

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

[5] Lyubushin, A.A. (2008) Multifractal properties of low-frequency microseismic noise in Japan, 1997-2008. Book of Abstracts of 7th General Assembly of the Asian Seismological Commission and Japan Seismological Society, 2008 Fall Meeting, Tsukuba, 24-27 November 2008, 92.

[6] 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

[7] Lyubushin, A.A. (2010) Synchronization of multifractal parameters of regional and global low-frequency microseisms. European Geosciences Union General Assembly, Vienna, 2-7 May 2010, 696.

[8] Lyubushin, A.A. (2010) Synchronization phenomena of low-frequency microseisms. European Seismological Commission: 32nd General Assembly, 6-10 September 2010, Montpelier, 124.

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

[10] Lyubushin, A.A. (2010) Multifractal parameters of low-frequency microseisms. In: V. de Rubeis et al., Eds., Synchronization and triggering: From fracture to earthquake processes, Springer-Verlag, Berlin Heidelberg

[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.A. (2011) Prediction of Tohoku seismic catastrophe by microseismic noise multi-fractal properties. Abstract S53A-2273 Presented at 2011 Fall Meeting, American Geophysical Union, San Francisco, 5-9 December 2011.

[14] Ivanov, P.Ch., Amaral, L.A.N., Goldberger, A.L., Havlin, S., Rosenblum, M.B., Struzik, Z. and Stanley, H.E. (1999) Multifractality in healthy heartbeat dynamics. Nature, 399, 461-465. doi:10.1038/20924

[15] Pavlov, A.N. and Anishchenko, V.S. (2007) Multifractal analysis of complex signals. Physics-Uspekhi, 50, 819-834. doi:10.1070/PU2007v050n08ABEH006116

[16] Humeaua, A., Chapeau-Blondeau, F., Rousseau, D., Rousseau, P., Trzepizur, W. and Abraham, P. (2008) Multifractality, sample entropy, and wavelet analyses for age-related changes in the peripheral cardiovascular system: Preliminary results. Medical Physics, 35, 717-727. doi:10.1118/1.2831909

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

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

[19] Mallat, S. (1998) A wavelet tour of signal processing. Academic Press, San Diego.

[20] Box, G.E.P. and Jenkins, G.M. (1970) Time series analysis: Forecasting and control. Holden-Day. San Francisco.

[21] Kashyap, R.L. and Rao, A.R. (1976) Dynamic stochastic models from empirical data. Academic Press, New York.

[22] Hirata, T., Satoh, T. and Ito, K. (1987) Fractal structure of spatial distribution of microfacturing in rock. Geophysical Journal of the Royal Astronomical Society, 90, 369-377. doi:10.1111/j.1365-246X.1987.tb00732.x

[23] Turcotte, D.L. (1997) Fractals and chaos in geology and geophysics. 2nd Edition, Cambridge University Press, New York. doi:10.1017/CBO9781139174695