Pierre Arroucau

TL;DR: This work presents a novel method for joint inversion of receiver functions and surface wave dispersion data, using a transdimensional Bayesian formulation and shows that the Hierarchical Bayes procedure is a powerful tool in this situation, able to evaluate the level of information brought by different data types in the misfit, thus removing the arbitrary choice of weighting factors.

TL;DR: In this paper, a Hierarchical Bayesian inversion (HBIN) is proposed to deal with uncertainties in data noise in seismic tomography, where the level of noise in each data set, as well as the number of model parameters, are treated as unknowns in the inversion.

TL;DR: The SI-Hex project as mentioned in this paper provides a catalogue of seismicity for metropolitan France and the French marine economic zone for the period 1962-2009 by taking into account the contributions of the various seismological networks and observatories from France and its neighbouring countries.

TL;DR: In this paper, the authors extract Rayleigh wave dispersion curves from the continuous records of 104 stations with ∼15 km separation and detect energy at periods as short as 1 s, thanks largely to the close proximity of oceanic microseisms on all sides.

TL;DR: In this article, Rayleigh wave group velocity maps sensitive to crustal structure exhibit low velocity anomalies in the presence of sedimentary basins and recent hot-spot volcanism, and high velocities in regions of out-cropping metamorphic and igneous rocks.