High-resolution Rayleigh-wave velocity maps of central Europe from a dense ambient-noise data set

Details High-resolution Rayleigh-wave velocity maps of central Europe from a dense ambient-noise data set High-resolution Rayleigh-wave velocity maps of central Europe from a dense ambient-noise data set

Mar 2012

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2012geoji.188.1173v&link_type=abstract

Geophysical Journal International, Volume 188, Issue 3, pp. 1173-1187.

Mathematics

Logic

Surface Waves And Free Oscillations, Seismic Tomography, Crustal Structure, Europe

Scientific paper

We present a new database of surface wave group and phase-velocity dispersion curves derived from seismic ambient noise, cross-correlating continuous seismic recordings from the Swiss Network, the German Regional Seismological Network (GRSN), the Italian national broad-band network operated by the Istituto Nazionale di Geosica e Vulcanologia (INGV). To increase the aperture of the station array, additional measurements from the Mediterranean Very Broad-band Seismographic Network (MedNet), the Austrian Central Institute for Meteorology and Geodynamics (ZAMG), the French, Bulgarian, Hungarian, Romanian and Greek stations obtained through Orfeus are also included. The ambient noise, we are using to assemble our database, was recorded at the above-mentioned stations between 2006 January and 2006 December. Correlating continuous signal recorded at pairs of stations, allows to extract coherent surface wave signal travelling between the two stations. Usually the ambient-noise cross-correlation technique allows to have informations at periods of 30 s or shorter. By expanding the database of noise correlations, we seek to increase the resolution of the central Europe crustal model.
We invert the resulting data sets of group and phase velocities associated with 8-35 s Rayleigh waves, to determine 2-D group and phase-velocity maps of the European region. Inversions are conducted by means of a 2-D linearized tomographic inversion algorithm. The generally good agreement of our models with previous studies and good correlation of well-resolved velocity anomalies with geological features, such as sedimentary basins, crustal roots and mountain ranges, documents the effectiveness of our approach.

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