Advertisement

Izvestiya, Atmospheric and Oceanic Physics

, Volume 47, Issue 8, pp 904–921 | Cite as

Seismic catastrophe in Japan on March 11, 2011: Long-term prediction on the basis of low-frequency microseisms

  • A. A. LyubushinEmail author
Article

Abstract

This paper presents a software technique for analyzing the multidimensional time series of microseismic oscillations on the basis of over 14 years of continuous observations, from early 1997 to February 2011, at F-net (Japan) broadband seismic stations. An analysis of the multifractal parameters of low-frequency microseismic noise allowed us to hypothesize, in as early as 2008, that Japanese Islands were approaching a large seismic catastrophe, the signature of which was a statistically significant decrease in the support width of the multifractal singularity spectrum. Subsequently, as new data became available and after some new statistics of microseismic noise (such as a logarithm of noise variance and an index of linear predictability) were included in joint analysis, we obtained some new results, indicating the facts that the parameters of the microseismic background had been increasingly synchronized (the synchronization process was estimated to start in mid-2002) and that the seismic danger had permanently grown. A cluster analysis of background parameters led us to conclude that in mid-2010 the islands of Japan entered a critically dangerous developmental phase of seismic process. The prediction of the catastrophe, first in terms of approximate magnitude (mid-2008) and then in terms of approximate time (mid-2010), was documented in advance in a series of papers and in proceedings at international conferences.

Keywords

synchronization microseismic background multifractals earthquake precursors 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Berger, J., Davis, P., and Ekstrom, G., Ambient Earth Noise: A Survey of the Global Seismographic Network, J. Geophys. Res., 2004, vol. 109, p. B11307.CrossRefGoogle Scholar
  2. Box, G.E.R. and Jenkins, G.M., Time Series Analysis. Forecasting and Control, San Francisco, Cambridge, London, Amsterdam: Holden-Day, 1970; Moscow: Mir, 1974.Google Scholar
  3. Cox, D.R. and Hinkleu, D.V., Theoretisal Statistics, London: Chapman and Hall, 1974; Moscow: Mir, 1978.Google Scholar
  4. Currenti, G., del Negro, C., Lapenna, V., and Telesca, L., Multifractality in Local Geomagnetic Field at Etna Volcano, Sicily (Southern Italy), Natural Hazards Earth Syst. Sci., 2005, vol. 5, pp. 555–559.CrossRefGoogle Scholar
  5. Duda, R.O. and Hart, P.E., Pattern Classification and Scene Analysis, New York: Wiley, 1973; Moscow: Mir, 1976.Google Scholar
  6. Ekstrom, G., Time Domain Analysis of Earth’s Long-Period Background Seismic Radiation, J. Geophys. Res., 2001, vol. 106, no. B11, pp. 26483–26493.CrossRefGoogle Scholar
  7. Feder, J., Fractals, New York: Plenum Press, 1988; Moscow: Mir, 1989.Google Scholar
  8. Friedrich, A., Krüger, F., and Klinge, K., Ocean-Generated Microseismic Noise Located ol. with the Gräfenberg Array, J. Seismol., 1998, vol. 2, no. 1, pp. 47–64.CrossRefGoogle Scholar
  9. Gilmore, R., Catastrophe Theory for Scientists and Engineers, New York: Wiley, 1981; Moscow: Mir, 1984.Google Scholar
  10. Hardle, W., Applied Nonparametric Regression, Cambridge: Univ. Press, 1989; Moscow: Mir, 1993.Google Scholar
  11. Hotelling, H., Relations between Two Sets of Variates, Biometrika, 1936, vol. 28, pp. 321–377.Google Scholar
  12. Huber, P.J., Robust Statistics, New York: Wiley, 1981; Moscow: Mir, 1984.CrossRefGoogle Scholar
  13. Ida, Y., Hayakawa, M., Adalev, A., and Gotoh, K., Multifractal Analysis for the ULF Geomagnetic Data during the 1993 Guam Earthquake, Nonlin. Proc. Geophys., 2005, vol. 12, pp. 157–162.CrossRefGoogle Scholar
  14. Kantelhardt, J.W., Zschiegner, S.A., Konscienly-Bunde, E., Havlin, S., Bunde, A., and Stanley, H.E., Multifractal Detrended Fluctuation Analysis of Nonstationary Time Series, Phys. A, 2002, vol. 316, pp. 87–114.CrossRefGoogle Scholar
  15. Kashyap, R.L. and Rao, A.R., Dynamic Stochastic Models from Empirical Data, New York: Acad. Press, 1976; Moscow, Nauka, 1983.Google Scholar
  16. Kobayashi, N. and Nishida, K., Continuous Excitation of Planetary Free Oscillations by Atmospheric Disturbances, Nature, 1998, vol. 395, pp. 357–360.CrossRefGoogle Scholar
  17. 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.Google Scholar
  18. Lyubushin, A.A. and Sobolev, G.A., Multifractal Measures of Synchronization of Microseismic Oscillations in a Minute Range of Periods, Izv. Phys. Solid Earth, 2006, vol. 42, no. 9, pp. 734–744.CrossRefGoogle Scholar
  19. Lyubushin, A.A., Analiz dannykh system geofizicheskogo i ekologicheskogo monitoringa (Data Analysis of Geophysical and Ecological Monitoring Systems), Moscow: Nauka, 2007.Google Scholar
  20. Lyubushin, A.A., Mean Multifractal Properties of Low-Frequency Microseismic Noise, in Proc. 31st General Assembly of the European Seismological Commission ESC-2008, Hersonissos, Crete, Sept. 7–12, 2008a, pp. 255–270.Google Scholar
  21. Lyubushin, A.A., Microseismic Noise in Minute Period Range: Properties and Possible Prognostic Features, Izv. Phys. Solid Earth, 2008c, vol. 44, no. 4, pp. 275–290.CrossRefGoogle Scholar
  22. Lyubushin, A.A., Multifractal Properties of Low-Frequency Microseismic Noise in Japan, 1997–2008, in Proc. 7th General Assembly of the Asian Seismological Commission and Japan Seismological Society. Fall Meeting, Tsukuba, Nov. 24–27, 2008b, p. 92.Google Scholar
  23. Lyubushin, A.A., Synchronization Trends and Rhythms of Multifractal Parameters of the Field of Low-Frequency Microseisms, Izv. Phys. Solid Earth, 2009, vol. 45, no. 5, pp. 381–394.CrossRefGoogle Scholar
  24. Lyubushin, A., Multifractal Parameters of Low-Frequency Microseisms, in Synchronization and Triggering: from Fracture to Earthquake Processes, GeoPlanet: Earth and Planetary Sciences, Berlin: Springer, 2010b, chapter 15, pp. 253–272. doi: 10.1007/978-3-642-12300-9-15CrossRefGoogle Scholar
  25. Lyubushin, A.A., Synchronization of Multifractal Parameters of Regional and Global Low-Frequency Microseisms, European Geosciences Union General Assembly 2010, Vienna, May 2–7, 2010a; Geophys. Res. Abstr., 2010a, vol. 12, abstr. EGU2010-696.Google Scholar
  26. Lyubushin, A.A., Synchronization Phenomena of Low-Frequency Microseisms, Proc. 32nd European Seismological Commission General Assembly, Montpelier, Sept. 6–10, 2010b, p. 124.Google Scholar
  27. Lyubushin, A.A., The Statistics of the Time Segments of Low-Frequency Microseisms: Trends and Synchronization, Izv. Phys. Solid Earth, 2010d, vol. 46, no. 6, pp. 544–554.CrossRefGoogle Scholar
  28. Lyubushin, A.A., Cluster Analysis of the Properties of Low-Frequency Microseismic Noise, Izv. Phys. Solid Earth, 2011, vol. 47, no. 6.Google Scholar
  29. Mallat, S.A., A Wavelet Tour of Signal Processing, San Diego Academic Press, 1998; Moscow: Mir, 2005.Google Scholar
  30. Mandelbrot, B.B., The Fractal Geometry of Nature, New York: Freeman, 1982; Moscow: Inst. Komp’yut. Issled., 2002.Google Scholar
  31. Pavlov, A.N., Sosnovtseva, O.V., and Mosekilde, E., Scaling Features of Multimode Motions in Coupled Chaotic Oscillators, Chaos, Solitons, Fractals, 2003, vol. 16, pp. 801–810.CrossRefGoogle Scholar
  32. Ramírez-Rojas, A., Muñoz-Diosdado, A., Pavía-Miller, C.G., and Angulo-Brown, F., Spectral and Multifractal Study of Electroseismic Time Series Associated to the M w = 6.5 Earthquake of 24 Oct. 1993 in Mexico, Natural Hazards Earth Syst. Sci., 2004, vol. 4, pp. 703–709.CrossRefGoogle Scholar
  33. Rao, C.R., Linear Statistical Inference and Its Applications, New York: John Wiley and Sons, 1965; Moscow: Nauka, 1968.Google Scholar
  34. Rhie, J. and Romanowicz, B., Excitation of Earth’s Continuous Free Oscillations by Atmosphere-Ocean-Seafloor Coupling, Nature, 2004, vol. 431, pp. 552–554.CrossRefGoogle Scholar
  35. Rhie, J. and Romanowicz, B., A Study of the Relation between Ocean Storms and the Earth’s Hum-G3: Geochemistry, Geophysics, Geosystems, Electron. J. Earth Sci., 2006, vol. 7, no. 10, Available from: http://www.agu.org/journals/gc/
  36. 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.CrossRefGoogle Scholar
  37. 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.CrossRefGoogle Scholar
  38. Tanimoto, T. and Um, J., Cause of Continuous Oscillations of the Earth, J. Geophys. Res., 1999, vol. 104, no. 28, pp. 723–739.Google Scholar
  39. Tanimoto, T., Continuous Free Oscillations: Atmosphere-Solid Earth Coupling, Ann. Rev. Earth Planet. Sci., 2001, vol. 29, pp. 563–584.CrossRefGoogle Scholar
  40. Tanimoto, T., The Oceanic Excitation Hypothesis for the Continuous Oscillations of the Earth, Geophys. J. Int., 2005, vol. 160, pp. 276–288.CrossRefGoogle Scholar
  41. Taqqu, M.S., Self-Similar Processes, in Encyclopedia of Statistical Sciences, New York: John Wiley and Sons, 1988, vol. 8, pp. 352–357.Google Scholar
  42. Telesca, L., Colangelo, G., and Lapenna, V., Multifractal Variability in Geoelectrical Signals and Correlations with Seismicity: a Study Case in Southern Italy, Natural Hazards Earth Syst. Sci., 2005, vol. 5, pp. 673–677.CrossRefGoogle Scholar
  43. Vogel, M.A. and Wong, A.K.C., PFS Clustering Method, IEEE Trans. Pattern Anal. Mach. Intell., 1978, vol. PAMI1-5, pp. 237–245.Google Scholar
  44. Ziganshin, A.R. and Pavlov, A.N., Scaling Properties of Multimode Dynamics in Coupled Chaotic Oscillators, Proc. 2nd Int. Conf. “Physics and Control”, St. Petersburg, Aug. 24–26, 2005, pp. 180–183.Google Scholar

Copyright information

© Pleiades Publishing, Ltd. 2011

Authors and Affiliations

  1. 1.Schmidt Institute of Physics of the EarthRussian Academy of SciencesMoscowRussia

Personalised recommendations