Azimuthal anisotropy from eikonal tomography: example from ambient-noise measurements in the AlpArray network

Abstract

Summary Ambient-noise records from the AlpArray network are used to measure Rayleigh wave phase velocities between more than 150,000 station pairs. From these, azimuthally anisotropic phase-velocity maps are obtained by applying the Eikonal tomography method. Several synthetic tests are shown to study the bias in the Ψ2 anisotropy. There are two main groups of bias, the first one caused by interference between refracted/reflected waves and the appearance of secondary wavefronts that affect the phase travel-time measurements. This bias can be reduced if the amplitude field can be estimated correctly. Another source of error is related to the incomplete reconstruction of the travel-time field that is only sparsely sampled due to the receiver locations. Both types of bias scale with the magnitude of the velocity heterogeneities. Most affected by the spurious Ψ2 anisotropy are areas inside and at the border of low-velocity zones. In the isotropic velocity distribution, most of the bias cancels out if the azimuthal coverage is good. Despite the lack of resolution in many parts of the surveyed area, we identify a number of anisotropic structures that are robust: in the central Alps, we find a layered anisotropic structure, arc-parallel at mid-crustal depths and arc-perpendicular in the lower crust. In contrast, in the eastern Alps, the pattern is more consistently E-W oriented which we relate to the eastward extrusion. The northern Alpine forleand exhibits a preferential anisotropic orientation that is similar to SKS observations in the lowermost crust and uppermost mantle.

Slab Geometry and Upper Mantle Flow Patterns in the Central Mediterranean From 3D Anisotropic P‐Wave Tomography

“…Recent ambient noise tomography by Kästle et al. ( 2022 ) also constrains E‐W fast propagation directions at crustal depths suggesting the SKS splits are not likely the result of crustal fabrics. Using Pn arrivals, Díaz et al.…”

“…Our results (both in terms of SKS splitting and P-wave fast azimuths) are consistent with azimuthal P-wave tomography of Hua et al (2017) who also incorporated local earthquake arrival times. Recent ambient noise tomography by Kästle et al (2022) also constrains E-W fast propagation directions at crustal depths suggesting the SKS splits are not likely the result of crustal fabrics. Using Pn arrivals, Díaz et al (2013) constrain mantle anisotropic velocity structure just below the Moho and find fast P-wave propagation directions that generally parallel SKS splits in the Northern Apennines.…”

Bayesian analysis of azimuthal anisotropy in the Alpine lithosphere from beamforming of ambient noise cross-correlations

“…Meier et al, 2004;Deschamps et al, 2008;Soomro et al, 2015), using relatively few stations in the Swiss Alps. Above 24 s period, they observed a north-south oriented fast direction of anisotropy at odds with the results from XKS measurements and a recent study by Kästle et al (2021). The temporary seismic stations of the AlpArray project (Hetényi et al, 2018), for which station installation began in 2015, complements permanent networks installed in Europe, resulting in an approximately uniform coverage of the greater Alpine region with an inter-station distance of approximately 50 km.…”

“…Combining several virtual sources, and therefore local velocity measurements from several directions, it is possible in any given point to calculate the variation of phase velocity with azimuth. Eikonal tomography has been applied by Lin et al (2009) and Ritzwoller et al (2011) and on the greater Alpine region by Kästle et al (2021).…”

“…Noise correlations in the greater Alpine region have already been the base of several studies of isotropic structure (e.g. Stehly et al, 2008;Lu et al, 2018bLu et al, , 2020Soergel et al, 2020;El-Sharkawy et al, 2020;Alder et al, 2021;Nouibat et al, 2022), and a single study focusing on azimuthal anisotropy (Kästle et al, 2021). At the local scale, azimuthal anisotropy of surface waves from noise correlations with AlpArray data has been studied in the Vienna basin by Schippkus et al (2019).…”