Abstract
A method is proposed for describing low-frequency microseismic noise from the network of broadband seismic stations in a large seismically active region of the Japan Islands. The median values of daily estimates from each station for seven parameters (three characteristics of the multifractal singularity spectra of the waveforms, their spectral exponents and the smoothness indices, the logarithmic variance and the linear predictability index) are used for the description. These parameters are determined for consecutive daily time intervals from the beginning of January 1997 through the end of February 2010. Since these parameters are taken as the median values of the estimates from each station, they are, actually, the integral statistics of the microseismic field. The present paper is the continuation of two previous works [Lyubushin, 2009; 2010], where the effects of synchronization in the low-frequency microseismic field on a large time scale were analyzed on the data from the F-net stations. In the present work, the number of different “behavior modes” of the microseismic field are sought as the number of clusters in the optimal partition of the cloud of 7-dimensional vector parameters, estimated within a moving time window with a width of 2 years. A new characteristic of the geophysical field is introduced, namely, the notion of the cluster exponent, which is the power exponent in the dependence of the value of the compactness function of a cloud of vector parameters on the number of clusters in the optimal partition of this cloud. Previously, a relatively rapid increase was revealed in the level of synchronization of the microseismic field, which started in the middle of 2002 and lasted for approximately one year. The level of synchronization remains high up to now. During the past 4 years (taking into account the width (2 years) of the time window within which the estimates were made), the cluster exponent exhibits a long trend which is similar to the shorter trend before the Hokkaido event (M = 8.3) that occurred on September 25, 2003. These facts, together with the pattern of variations in the coefficient of correlation between two multifractal parameters of the field, suggest a hypothesis of the enhancement of the seismic hazard in the region of the Islands of Japan from the second half of 2010.
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References
Aivazyan, S.A., Bukhshtaber, V.M., Enyukov, I.S., and Meshalkin, L.D., Prikladnaya statistika. Klassifikatsiya i snizhenie razmernosti (Applied Statistics: Classification and Dimension Reduction), Moscow: Finansy i Statistika, 1989.
Box, G.E.R. and Jenkins, G.M., Time Series Analysis: Fore-casting and Control, San Francisco, CA: Holden-Day, 1970.
Duda, R.O. and Hart, R.E., Pattern Classification and Scene Analysis, New York: Wiley, 1973.
Ekstrom, G., Time Domain Analysis of Earth’s Long-Period Background Seismic Radiation, J. Geophys. Res., 2001, vol. 106, no. B11, pp. 26 483–26 493.
Feder, J., Fractals, New York: Plenum, 1988.
Friedrich, A., Kruger, F., and Klinge, K., Ocean-Generated Microseismic Noise Located with the Gräfenberg Array, J. Seismol., 1998, vol. 2, no. 1, pp. 47–64.
Kantelhardt, J.W., Zschiegner, S.A., Konscienly-Bunde, E., et al., Multifractal Detrended Fluctuation Analysis of Nonstationary Time Series, Phys. A (Amsterdam, Neth.), 2002, vol. 316, pp. 87–114.
Kashyap, R.L. and Rao, A.R., Dynamic Stochastic Models from Empirical Data, New York: Academic Press, 1976.
Kobayashi, N. and Nishida, K., Continuous Excitation of Planetary Free Oscillations by Atmospheric Disturbances, Nature, 1998, vol. 395, pp. 357–360.
Kurrle, D. and Widmer-Schnidrig, R., Spatiotemporal Features of the Earth’s Background Oscillations Observed in Central Europe, Geophys. Rev. Lett., 2006, vol. 33, p. L24304.
Lyubushin, A.A. and Sobolev, G.A., Multifractal Measures of Synchronization of Microseismic Oscillations in a Minute Range of Periods, Fiz. Zemli, 2006, no. 9, pp. 18–28 [Izv. Phys. Earth (Engl. Transl.), 2006, vol. 42, no. 9, pp. 734–744].
Lyubushin, A.A., Analiz dannykh sistem geofizicheskogo i ekologicheskogo monitoringa (Geophysical and Ecological Monitoring Data Analysis), Moscow: Nauka, 2007.
Lyubushin, A.A., Microseismic Noise in the Low Frequency Range (Periods of 1–300 min): Properties and Possible Prognostic Features, Fiz. Zemli, 2008, no. 4, pp. 17–34 [Izv. Phys. Earth (Engl. Transl.), 2008, vol. 44, no. 4, pp. 275–290].
Lyubushin, A.A., Synchronization Trends and Rhythms of Multifractal Parameters of the Field of Low-Frequency Microseisms, Fiz. Zemli, 2009, no. 5, pp. 15–28 [Izv. Phys. Earth (Engl. Transl.), 2009, vol. 45, no. 5, pp. 381–394].
Lyubushin, A.A., The Statistics of the Time Segments of Low-Frequency Microseisms: Trends and Synchronization, Fiz. Zemli, 2010, no. 6, pp. 86–96 [Izv. Phys. Earth (Engl. Transl.), 2010, vol. 46, no. 6, pp. 544–554].
Mallat, S.A., A Wavelet Tour of Signal Processing, San Diego: Academic Press, 1998.
Pavlov, A.N., Sosnovtseva, O.V., and Mosekilde, E., Scaling Features of Multimode Motions in Coupled Chaotic Oscillations, Chaos, Solitons Fractals, 2003, vol. 16, pp. 801–810.
Rhie, J. and Romanowicz, B., Excitation of Earth’s Continuous Free Oscillations by Atmosphere-Ocean-Seafloor Coupling, Nature, 2004, vol. 431, pp. 552–556.
Sobolev, G.A. and Lyubushin, A.A., Microseismic Impulses as Earthquake Precursors, Fiz. Zemli, 2006, no. 9, pp. 5–17 [Izv. Phys. Earth (Engl. Transl.), 2006, vol. 42, no. 9, pp. 721–733].
Sobolev, G.A., Lyubushin, A.A., and Zakrzhevskaya, N.A., Asymmetrical Pulses, the Periodicity and Synchronization of Low Frequency Microseisms, Vulkanol. Seismol., 2008, no. 2, pp. 135–152 [J. Volcanol. Seismol. (Engl. Transl.), 2008, vol. 2, no. 2, pp. 118–134].
Sobolev, G.A., Lyubushin, A.A., and Zakrzhevskaya, N.A., Synchronization of Microseismic Variations within a Minute Range of Periods, Fiz. Zemli, 2005, no. 8, pp. 3–27 [Izv. Phys. Earth (Engl. Transl.), 2005, vol. 41, no. 8, pp. 599–621].
Stehly, L., Campillo, M., and Shapiro, N.M., A Study of the Seismic Noise from Its Long-Range Correlation Properties, J. Geophys. Res., 2006, vol. 111, p. B10306.
Tanimoto, T. and Um, J., Cause of Continuous Oscillations of the Earth, J. Geophys. Res., 1999, vol. 104, no. B12, p. 28 723–28 739.
Tanimoto, T., Continuous Free Oscillations: Atmosphere-Solid Earth Coupling, Annu. Rev. Earth Planet. Sci, 2001, vol. 29, pp. 563–584.
Tanimoto, T., The Oceanic Excitation Hypothesis for the Continuous Oscillations of the Earth, Geophys. J. Int., 2005, vol. 160, p. 276–288.
Tanimoto, T., Um, J., Nishida, K., and Kobayashi, N., Earth’s Continuous Oscillations Observed on Seismically Quiet Days, Geophys. Rev. Lett., 1998, vol. 25, pp. 1553–1556.
Vogel, M.A. and Wong, A.K.C., PFS Clustering Method, IEEE Trans. Pattern Analysis. Mach. Intell., 1979, vol. PAMI-1, no. 3, pp. 237–245.
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Original Russian Text © A.A. Lyubushin, 2011, published in Fizika Zemli, 2011, No. 6, pp. 26–34.
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Lyubushin, A.A. Cluster analysis of low-frequency microseismic noise. Izv., Phys. Solid Earth 47, 488–495 (2011). https://doi.org/10.1134/S1069351311040057
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DOI: https://doi.org/10.1134/S1069351311040057