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.

A folder with all inter-station cross-correlations in SAC (Seismic Analysis Code) format can be downloaded at the following link: . Be advised that the size of this folder is 4.3G. Clicking on this link will not automatically start the download. It will take you to a directory where you can select the compressed file EENSANE_cross-correlations.tar.gz for download.

Our data processing flow largely follows the procedure of Bensen et al. (2007) with a few changes. Please see our papers Petrescu et al. (2023) and Borleanu et al. (2023) for more details. The main ambient noise processing steps are:

  1. Continuous ambient noise ground motion data is cut in daily records
  2. Mean and trend removed
  3. Instrument response removed
  4. Broadband filter 0.003-2.4 Hz applied
  5. Seismograms are de-signaled with CWT (Yang et al., 2020)
  6. Data are cut in 2 hour segments and cross-correlated at simultaneous pairs of stations
  7. Cross-correlations are stacked
  8. Inter-station cross-correlograms are de-noised with CWT

Inter-station cross-correlation paths for seismic stations in Eastern Europe

Seismic stations in Eastern Europe operating in 1999 (orange), 2005-2008 (yellow), 2009-2011 (pink) and 2020 (blue)

Cross-correlograms recorded at seismic stations in Eastern Europe as if seismic station MLR in Romania was a virtual impulsive source

From the cross-correlation data, we extracted Rayleigh wave phase velocity dispersion curves using an automatic Bessel-analogue algorithm (Kästle et al., 2016).

A folder with all our dispersion curve data, used for seismic tomography (Petrescu et al., 2023) can be found at the following link: . The folder size is 2.4 Mb.


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.

Borleanu, F., Petrescu, L., Placinta, A.O., Magrini, F., Grecu, B., Radulian, M. and De Siena, L., 2023. Seismic attenuation tomography of Eastern Europe from ambient seismic noise analysis. Geophysical Journal International, p.ggad408.

Kästle, E.D., Soomro, R., Weemstra, C., Boschi, L. and Meier, T., 2016. Two-receiver measurements of phase velocity: cross-validation of ambient-noise and earthquake-based observations. Geophysical Journal International, 207(3), pp.1493-1512.

Petrescu, L., Borleanu, F., Kästle, E., Stephenson, R., Plăcintă, A. and Liashchuk, O.I., 2024. Seismic structure of the Eastern European crust and upper mantle from probabilistic ambient noise tomography. Gondwana Research, 125, pp.390-405.

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.