Subsections

Tomography of the Alpine Region from Observations of Seismic Ambient Noise

L. Stehly, B. Fry, M. Campillo, N.M Shapiro, J. Guilbert, L. Boschi and D.Giardini

Introduction

We use correlations of the ambient seismic noise to study the crust in western Europe (Shapiro et al, 2005). Cross correlation of one year of noise recorded at 150 3-component broadband stations yields more than 3000 Rayleigh and Love wave group velocity measurements. These measurements are used to construct Rayleigh and Love group velocity maps of the Alpine region and surrounding area in the 5-80s period band. Finally, we invert the resulting Rayleigh wave group velocity maps to determine the Moho depth.

Method

We used one year of continuous records from October 2004 to October 2005 from 150 3-component broadband European stations. Our aim is to focus on the Alps, where we have a particularly high density of stations All the records are processed day by day. First the data are decimated to 1 Hz and corrected for the instrumental response. North and East horizontal components are rotated to get radial and transverse components with respect to the inter-station azimuth. The records are then band-pass filtered and their spectrum whitened between 5 and 150 s. We correlated signals recorded on the components that correspond to Rayleigh and Love waves (ZZ, ZR, RZ, RR, and TT). Correlations of one-day records are stacked.

Group velocities maps

Rayleigh and Love wave dispersion curves are evaluated from the emerging Green's function using frequency-time analysis (Levshing et al, 1989, Ritzwoller and Levshin, 1998) for the 11,000 inter-station paths. For each path, we get eight evaluations of the Rayleigh-wave dispersion curves by considering four components of the correlation tensor (ZZ, RR, RZ and ZR) and both the positive and the negative part of the NCF. Similarly, we get two estimates of the Love-wave dispersion curves from positive and negative parts of TT correlations.

We reject waveforms 1) with S/N (ratio between Rayleigh wave's amplitude and noise variance after it) lower than seven; 2) with group velocities measured on the positive and negative correlation time differing by more than 5 percents, and 3) with paths shorter than two wavelengths at the selected period for the group velocity map. This results in about 3,500 paths over the initial 11,000 inter-station paths at 16 s. We then apply a tomographic inversion following (Barmin et al, 2001) to this data set to obtain group velocity maps on 100$\times$100 = 10,000 cells of 25$\times$25 km across Europe (Fig. 2.34). Several geological features can be seen on those maps. At 16s, low velocity anomalies are associated with sedimentary basins, such as the Po basin (Northern Italy), the North Sea basin and the Pannonian basin (Slovakia and Hungary). Both Rayleigh and Love waves exhibit smaller values below the molassic sediments (Southern Germany and Austria) than in the surrounding area.

Figure 2.34: Rayeigh group velocity maps at 16s (left) and 35s (right).
\begin{figure}\centering\epsfig{file=map_ray16s-RSB7-SYM5-3587paths.eps, width=5.2cm} \epsfig{file=map_ray35s-RSB7-SYM5-3255paths.eps, width=5.2cm} \end{figure}

Moho map of the alpine region

At each cell of our model, we extracted Rayleigh wave dispersion curves from our group velocities map, and inverted them using a Monte Carlo algorithm in order to determine the depth of the Moho in the Western Alps (Switzerland, Austria, southern Germany). Our results clearly show thickening of the crust below the Alps (Fig2.35). Our map of Moho depth shares striking similarities with the compilation of (Waldhauser et al, 1998) in the region where we have a high density of paths. This comparison confirms that seismic noise can be efficiently used to obtain high resolution Love and Rayleigh wave group velocity maps at periods up to 80s and 3D images of the crust and the upper mantle. This method provides spatially continuous seismic velocity distributions on large areas. The resolution of the obtained model depends mostly on the density of stations and is not limited by the uneven distribution of earthquakes. At period less than 10s, the resolution length is not isotropic as the noise is strongly directional.

Figure 2.35: 3D view of the Moho depth.
\begin{figure}\centering\epsfig{file=Moho3D2.eps, width=6.2cm} \end{figure}

References

M. P Barmin, M. H. Ritzwoller, and A. L. Levshin, A fast and reliable method for surface wave tomography, Pure and Applied Geophysics, 158:1351-1375, 2001.

A.L Levshin, T. B. Yanocskaya, A. V. Lander, B. G. Bukchin, M. P. Barmin, L. I. Ratnikova, and E. N. Its, Seismic surface waves in a laterally inhomogeneous Earth,
Kluwer Academic Publishers, 1989.

M. Ritzwoller and A. L. Levshin, Eurasian surface wave tomography: group velocities, Journal of Geophysical Research, 103(4839-4878):4839, 1998.

N. M. Shapiro, M. Campillo, L. Stehly, and M. H. Ritzwoller, High-resolution surface wave tomography from ambient seismic noise, Science, 307:1615-1618, march 2005.

F. Waldhauser, E. Kissling, J. Ansorge, and St. Mueller, Three-dimensional interface modelling with two-dimensional seismic data: the Alpine crust mantle boundary, Geophysical Journal International, 135:264-278, 1998.

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