Spots of Seismic Danger Extracted by Properties of Low-Frequency Seismic Noise

Transcription

1 Spots of Seismic Danger Extracted by Properties of Low-Frequency Seismic Noise Alexey Lyubushin Institute of Physics of the Earth, Moscow European Geosciences Union General Assembly, Vienna, April 2013, session NH4.1/SM

2 When and Were the prediction of Tohoku EQ was published before the earthquake Lyubushin A.A. Multi-fractal Properties of Low-Frequency Microseismic Noise in Japan, Book of abstracts of 7th General Assembly of the Asian Seismological Commission and Japan Seismological Society, 2008 Fall meeting, Tsukuba, Japan, November 2008, p.92. Lyubushin A.A. Synchronization Trends and Rhythms of Multifractal Parameters of the Field of Low-Frequency Microseisms Izvestiya, Physics of the Solid Earth, 2009, Vol. 45, No. 5, pp Lyubushin A.A. The Statistics of the Time Segments of Low-Frequency Microseisms: Trends and Synchronization Izvestiya, Physics of the Solid Earth, 2010, Vol., No. 6, pp Lyubushin A.A. Synchronization of multi-fractal parameters of regional and global low-frequency microseisms European Geosciences Union General Assembly 2010, Vienna, of May, 2010, Geophysical Research Abstracts, Vol. 12, EGU , 2010, Lyubushin A., Multifractal Parameters of Low-Frequency Microseisms // V. de Rubeis et al. (eds.), Synchronization and Triggering: from Fracture to Earthquake Processes, GeoPlanet: Earth and Planetary Sciences 1, DOI / _15, Springer-Verlag Berlin Heidelberg, 2010, 8p., Chapter 15, pp Lyubushin A.A. Synchronization phenomena of low-frequency microseisms. European Seismological Commission, nd General Assembly, September 06-10, 2010, Montpelier, France. Book of abstracts, p.124, session ES6. Lyubushin A.A. Cluster Analysis of Low-Frequency Microseismic Noise Izvestiya, Physics of the Solid Earth, 2011, Vol. 47, No. 6, pp (submitted April 26, 2010) Publications after the earthquake: 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, 2011, Vol., No. 8, pp Lyubushin, A. (2012) Prognostic properties of low-frequency seismic noise. Natural Science, 4, doi: 10./ns Lyubushin A.A. (2013) Mapping the Properties of Low-Frequency Microseisms for Seismic Hazard Assessment. Izvestiya, Physics of the Solid Earth, 2013, Vol.49, No.1, pp ISSN , DOI: 10.11/S Lyubushin A.A. (2013) Spots of Seismic Danger Extracted by Properties of Low-Frequency Seismic Noise European Geosciences Union General Assembly 2013, Vienna, of April, 2013, Geophysical Research Abstracts, Vol. 15, EGU ,

3 Asian Seismological Commission, Tsukuba, Japan, Nov 2008 The earliest prediction (at the middle of 2008): the magnitude of oncoming catastrophe will be more than 8.3.

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5 The latest prediction: dangerous time for waiting catastrophe begins at the middle of 2010

6 Positions of 78 seismic stations of broadband network F-net in Japan , M = , M =

7 Main sources of lowfrequency microseisms Atmospheric Pressure Variations Oceanic Waves Low-Frequency Microseismic Noise: Slow Earthquakes, Creep 2 min Periods 1000 min

8 Multi-fractal singularity spectrum Measure of the random signal variability at the time interval [ t δ/2, t + δ/2 ] Multi-fractal singularity spectrum F (α) and its parameters: α - support width and α - generalized Hurst exponent. 1.0 F (α) - fractal dimensionality of the set of time moments t for which h(t) = α µ(t,δ ) δ h(t) δ α = α max α min t δ α min α α max α

9 Minimum normalized entropy of squared orthogonal wavelet coefficients distribution Minimum normalized entropy : N En = p log( p ) / log( N) min k = 1 k N En 1, pk = ck / c j, j= 1 c j k - orthogonal wavelet coefficients, minimum is taken by wavelets from Daubechies family.

10 Data transform Initial LHZ-records, t = 1 sec t = 1 min Seismic Noise, t = 1 min Downsampling Detrending Donoho share Log(Variance) Kurtosis Estimates within adjacent daily time intervals, t = 1 day α Linear Predictability Index Spectral Exponent α α min Smoothness Index Normalized Entropy

11 Graphics of seismic noise of the length 1 day with sampling time step 1 minute after removing tidal trends High α Low normalized entropy En Low danger, high variability of stochastic behavior types, a lot of low-frequency spikes because of mutual movements of non-consolidated small blocks of the Earth's crust, energy is not accumulated. Low α High normalized entropy En High danger, the behavior of the seismic noise is much more uniform, small blocks of the Earth's crust are consolidated, the energy could be accumulated. α = 0.249, En = α = 0.821, En = 5 α = 0.154, En = α = 0.757, En = 4 α = 0.207, En = α = 0.809, En = Time, minutes Time, minutes

12 α The sequence of mean maps of multi-fractal singularity spectra support width of lowfrequency seismic noise waveforms for 16 years of observations at broad-band seismic network F-net at Japan Small black star hypocenter of earthquake , M=8.3 Large black star hypocenter of Tohoku megaearthquake , M=

13 Maps of singularity spectra support width of low-frequency seismic noise waveforms for 4 adjacent time of the length 0.5 years during Seasonal periodicity of seismic danger is obvious: autumn-winter period is more dangerous than spring-summer , 183 days , 183 days , 183 days , 183 days Regions of relatively low values of singularity spectrum support width extract seismically danger domains

14 Maps of multi-fractal singularity spectra support width α. Low α values ( blue and violet regions ) indicate synchronization and danger α α α From the beginning of 1997 up to 25 of Sept 2003: the area of future seismic catastrophe is characterized by relatively low α and it is not split into North and South parts. From 26 of Sept 2003 up to 10 of March 2011: the area of future seismic catastrophe is characterized by relatively low α and the previous area of low α values is split into North and South parts. From 14 of March 2011 up to 15 June 2013: the North part of the relatively low α values before was realized as the area of Great Japan Earthquake 11 of March 2011, M=9.0, whereas the South part is still characterized by low α values The region of Nankai Though near Tokyo is the place of the next Japan mega-earthquake which could occur at

15 En The sequence of mean maps of minimum normalized entropy of squared orthogonal wavelet coefficients of low-frequency seismic noise waveforms for 16 years of observations at broad-band seismic network F-net at Japan. Small black star hypocenter of earthquake , M=8.3 Large black star hypocenter of Tohoku megaearthquake , M=

16 Maps of minimum normalized entropy of low-frequency seismic noise waveforms for 4 adjacent time of the length 0.5 years during Seasonal periodicity of seismic danger is obvious: autumn-winter period is more dangerous than spring-summer , 183 days , 183 days , 183 days , 183 days Regions of relatively high normalized entropy extract seismically danger domains

17 Maps of low-frequency seismic noise wavelet-based normalized entropy, i.e. normalized entropy of the noise waveforms squared wavelet coefficients for the best orthogonal wavelet which is found for each station within each daily time window from the minimum of entropy En En En From the beginning of 1997 up to 25 of Sept 2003: the area of future seismic catastrophe is characterized by relatively high values of normalized entropy and it is not split into North and South parts From 26 of Sept 2003 up to 10 of March 2011: the area of future seismic catastrophe is characterized by relatively high values of normalized entropy and the previous area of high entropy values is split into North and South parts From 14 of March 2011 up to 15 June 2013: the North part of the relatively high values of normalized entropy before was realized as the area of Great Japan Earthquake 11 of March 2011, M=9.0, whereas the South part is still characterized by high entropy values. The region of Nankai Though near Tokyo is the place of the next Japan mega-earthquake which could occur at

18 0.8 Time Prediction: Squared correlation between mean values of multi-fractal parameters α and α of microseisms from all F-net stations estimated within 1 year moving time window. Strong earthquake is nevertheless only a foreshock , M = , M = Blue arrows were plotted at the April of The 2-nd arrow indicates the middle of 2010 as the lower estimate of catastrophe time moment Right-hand end of moving time window of the length 1 year A new sharp minimum of correlation between multi-fractal parameters α and α is observed. Starting from the sharp minimum of correlation 2 years dangerous time interval is estimated.

19 Averaged maps of annual correlation coefficient between multi-fractal singularity spectrum support width α and generalized Hurst exponent α* Before Tohoku EQ the region of future event was extracted by relatively high values of correlation coefficient What is observed for time period 14 March June 2013

20 Clustering of seismic noise daily median parameters for prediction of seismic event time moment

21 2.0 Pseudo-F-statistics Number of clusters from maximum of PFS = Pseudo-F-statistics Number of clusters from maximum of PFS = Probe number of clusters 0.4 Probe number of clusters

22 Cases of 1 or 2 clusters are distinguished by the existence of break point of the dependence σ 0 (q) at q= σ 0 (q) for 1 cluster δ lg(σ 0 (q)) 10 1 σ 0 (q) for 2 clusters δ lg(σ 0 (q)) - deflection from red line q q 0.01 q - number of clusters q - number of clusters

23 α α June α min En Median values of 4 daily parameters of seismic noise from Japan broadband seismic network F-net: α, α *, α min - multifractal singularity spectra parameters; En - minimum normalized entropy of squared wavelet-coeffcients Green lines - running average within 57 days moving time window Clusterization of 3 first principal components of medians of 4 daily seismic noise parameters within moving windows of the length 5 days with mutual shift 3 days. Preliminary normalization & winsorization ±4σ within each window. Number of clusters providing maximum of pseudo-f-statistics M= Difference between means of pseudo-f-statistics for big (21-) and small (2-20) numbers of probe clusters Right-hand end of 5 days moving time window with mutual shift 3 days

24 Conclusions. During preparing huge seismic catastrophe geological medium become more simple and homogenous. This manifests in the following properties of lowfrequency microseisms noise waveforms: 1) Multi-fractal singularity spectrum support width α decreases, i.e. the noise structure become more simple, less multi-fractal. 2) Minimum value of normalized entropy of squared orthogonal wavelet coefficients increases. 3) According to the results of seismic noise processing from Japan broadband network F-net the region of Nankai Trough could be the place of the next mega-earthquake with dangerous time interval