High-resolution surface wave tomography of the European crust and uppermost mantle from ambient seismic noise

International audienceTaking advantage of the large number of seismic stations installed in Europe, in particular in the greater Alpine region with the AlpArray experiment, we derive a new high-resolution 3-D shear wave velocity model of the European crust and uppermost mantle from ambient-noise tomography. The correlation of up to 4 yr of continuous vertical-component seismic recordings from 1293 broad-band stations (10 • W-35 • E, 30 • N-75 • N) provides Rayleigh wave group velocity dispersion data in the period band 5-150 s at more than 0.8 million virtual source-receiver pairs. 2-D Rayleigh wave group velocity maps are estimated using adaptive parametrization to accommodate the strong heterogeneity of path coverage. A probabilistic 3-D shear wave velocity model, including probability densities for the depth of layer boundaries and S-wave velocity values, is obtained by nonlinear Bayesian inversion. A weighted average of the probabilistic model is then used as starting model for the linear inversion step, providing the final V s model. The resulting S-wave velocity model and Moho depth are validated by comparison with previous geophysical studies. Although surface wave tomography is weakly sensitive to layer boundaries, vertical cross-sections through our V s model and the associated probability of the presence of interfaces display striking similarities with reference controlled-source seismology (CSS) and receiver function sections across the Alpine belt. Our model even provides new structural information such as an ∼8 km Moho jump along the CSS ECORS-CROP profile that was not imaged by the reflection data due to poor penetration across a heterogeneous upper crust. Our probabilistic and final shear wave velocity models have the potential to become new reference models of the European crust, both for crustal structure probing and geophysical studies including waveform modelling or full-waveform inversion