Journal of Seismology

, Volume 13, Issue 1, pp 73–87 | Cite as

Seasonal variations of cross correlations of seismic noise in Israel

Original article


The long-period microseismic noise was recently found to carry deterministic information about the crust and upper mantle structure in the cross-section between the two station sites in terms of the surface wave Green function, which is theoretically proportional to the noise cross-correlation function (NCF) for the long-term observations at the pair of the BB stations. We performed daily-long cross correlations for the period of 2–3 years between the 7 BB stations, distributed in the Eastern Mediterranean, and stacked them for every month of a year. A preprocessing of the broadband waveforms included whitening of the direct and inverse DFT of the waveforms to avoid influence of earthquakes recordings and to equalize energy of different types of microseisms. As the result, we have found that the NCFs obtained exhibit clear seasonal variations within period band 2–20 s persistent from year to year. For the best description of these variations, we applied seasonal diagrams, which presented the distribution of the NCF maximal amplitudes in three narrow frequency bands, with respect to the month of a year. The diagrams helped in determining that these variations can be split into four types. The different types of the seasonal NCF variations are assumed to be attributed to the four certain remote deep ocean regions, which are responsible for the increased microseismic activity due to the specific interaction between the ocean waves and the bottom during ocean storms.


Cross-correlation function Microseismic noise Broadband recordings Sources of microseismic noise 


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  1. Bensen GD, Ritzwoller MH, Barmin MP, Levshin AL, Lin F, Moschetti MP, et al (2007) Processing seismic ambient noise data to obtain reliable broad-band surface wave dispersion measurements. Geophys J Int 169:1239–1260. doi:10.1111/j.1365-246X.2007.03374.x CrossRefGoogle Scholar
  2. Lin FC, Ritzwoller MH, Shapiro NM (2006) Is ambient noise tomography across ocean basins possible? Geophys Res Let 33:L14304CrossRefGoogle Scholar
  3. Gutenberg B (1951) Observation and theory of microseisms. In: Malone TF (ed) Compendium of meteorology. Am Meteorol Soc, Providence, pp 1303–1311Google Scholar
  4. Kedar S, Longuet-Higgins M, Webb F, Graham N, Clayton R, Jones C (2008) The origin of deep ocean microseisms in the North Atlantic Ocean. Proc R Soc A 2091:777–893, March. doi:10.1098/rspa.2007.0277 CrossRefGoogle Scholar
  5. Levshin AL, Barmin MP, Yang X, Ritzwoller MH, Randall GE (2007) Toward a Rayleigh wave attenuation model for Central Asia and surrounding regions. In: Proceedings of the 29th monitoring research review of ground-based nuclear explosion monitoring technologies, p 10. Denver, CO, 25–27 September 2007Google Scholar
  6. Longuet-Higgins M (1950) A theory of the origin of microseisms. Philos Trans R Soc Lond 243:137–171Google Scholar
  7. Paul A, Campillo M, Margerin L, Larose E, Derode A (2005) Empirical synthesis of time-asymmetrical Green functions from the correlation of coda waves. J Geophys Res 110:B08302.1–B08302.13. doi:10.1029/2004JB003521 CrossRefGoogle Scholar
  8. Peterson J (1993) Observations and modeling of seismic background noise. U.S. Geol. Surv. Open File Rep. 93–322Google Scholar
  9. Rhie J, Romanowicz B (2006) A study of the relation between ocean storms and the Earth’s hum. Geochem Geophys Geosyst 7:Q10004. doi:10.1029/2006GC001274 CrossRefGoogle Scholar
  10. Sabra KG, Gerstoft P, Roux P, Kuperman WA, Fehler MC (2005a) Extracting time-domain Green’s function estimates from ambient seismic noise. Geophys Res Lett 32:L03310. doi:10.1029/2004GL021862 CrossRefGoogle Scholar
  11. Sabra KG, Gerstoft P, Roux P, Kuperman WA, Fehler MC (2005b) Surface wave tomography from microseisms in Southern California. Geophys Res Lett 32:L14311. doi:1029/2005GL023155 CrossRefGoogle Scholar
  12. Shapiro NM, Campillo M (2004) Emergence of broadband Rayleigh waves from correlations of the ambient seismic noise. Geophys Res Lett 31:L07614. doi:10.1029/2004GL019491, p 23CrossRefGoogle Scholar
  13. Shapiro NM, Campillo M, Stehly L, Ritzwoller MH (2005) High resolution surface wave tomography from ambient seismic noise. Science 307:1615–1618. doi:10.1126/science.1108339 CrossRefGoogle Scholar
  14. Snieder R (2004) Extracting the Green’s function from the correlation of coda waves: a derivation based on stationary phase. Phys Rev E Stat Nonlin Soft Matter Phys 69:046610. doi:10.1103/PhysRevE.69.046610 Google Scholar
  15. Stehly L, Campillo M, Shapiro NM (2006) A study of the seismic noise from its long-range correlation properties. J Geophys Res 111:B10306, p 12CrossRefGoogle Scholar
  16. Wapenaar CPA (2004) Retrieving the elastodynamic Green’s function of an arbitrary inhomegeneous medium by cross correlation. Phys Rev Lett 93:254301. doi:10.1103/PhysRevLett.93.254301 CrossRefGoogle Scholar
  17. Weaver RL (2005) Information from seismic noise. Science 307:5715. doi:10.1126/science.1109834, 1568–1569CrossRefGoogle Scholar
  18. Yang Y, Ritzwoller M (2008) Characteristics of ambient seismic noise as a source for surface wave tomography. Geochem Geophys Geosyst 9:Q02008. doi:10.1029/2007GC001814 CrossRefGoogle Scholar
  19. Yang Y, Ritzwoller M, Levshin A, Shapiro N (2007) Ambient noise Rayleigh wave tomography across Europe. Geophys J Int 168:259–274. doi:10.1111/j.1365-246X.2006.03203.x CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  1. 1.University of Western OntarioLondonCanada
  2. 2.Geophysical Institute of IsraelLodIsrael

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