We are working on providing the scientific community with freely available virtual earthquake data. Each seismic station in Eastern Europe is turned into a virtual seismic source, via cross correlation and stacking of ambient seismic noise at pairs of seismic receivers.
Our data processing flow largely follows the procedure of Bensen et al. (2007) with a few changes:
- Continuous ambient noise ground motion data is cut in daily records
- Mean and trend removed
- Instrument response removed
- Broadband filter 0.003-2.4 Hz applied
- Seismograms are de-signaled with CWT (Yang et al., 2020)
- Data are cut in 2 hour segments and cross-correlated at simultaneous pairs of stations
- Cross-correlations are stacked
- Inter-station cross-correlograms are de-noised with CWT
- Cross-correlate cross-correlograms at pairs of asynchronous seismic stations to obtain virtual seismic records at station that were not operating at the same time (the SRI method, Curtis et al., 2012)
Bensen, G.D., Ritzwoller, M.H., Barmin, M.P., Levshin, A.L., Lin, F., Moschetti, M.P., Shapiro, N.M. and Yang, Y., 2007. Processing seismic ambient noise data to obtain reliable broad-band surface wave dispersion measurements. Geophysical Journal International, 169(3), pp.1239-1260.
Curtis, A., Y. Behr, E. Entwistle, E. Galetti, J. Townend, and S. Bannister (2012), The benefit of hindsight in observational science: Retrospective seismological observations, EarthPlanet.Sci.Lett., 345-348, 212–220, doi:10.1016/j.epsl.2012.06.008.
Yang, Y., Liu, C. and Langston, C.A., 2020. Processing seismic ambient noise data with the continuous wavelet transform to obtain reliable empirical Green’s functions. Geophysical Journal International, 222(2), pp.1224-1235.