A new approach to construct 3-D crustal shear-wave velocity models: method description and application to the Central Alps

Abstract

We develop a new inversion approach to construct a 3-D structural and shear-wave velocity model of the crust based on teleseismic P-to-S converted waves. The proposed approach does not require local earthquakes such as body wave tomography, nor a large aperture seismic network such as ambient noise tomography, but a three-component station network with spacing similar to the expected crustal thickness. The main features of the new method are: (1) a novel model parametrization with 3-D mesh nodes that are fixed in the horizontal directions but can flexibly vary vertically; (2) the implementation of both sharp velocity changes across discontinuities and smooth gradients; (3) an accurate ray propagator that respects Snell’s law in 3-D at any interface geometry. Model parameters are inverted using a stochastic method composed of simulated annealing followed by a pattern search algorithm. The first application is carried out over the Central Alps, where long-standing permanent and the temporary AlpArray Seismic Network stations provide an ideal coverage. For this study we invert 4 independent parameters, which are the Moho discontinuity depth, the Conrad discontinuity depth, the P-velocity change at the Conrad and the average Vp/Vs of the crust. The 3-D inversion results clearly image the roots of the Alpine orogen, including the Ivrea Geophysical Body. The lower crust's thickness appears fairly constant. Average crustal Vp/Vs ratios are relatively higher beneath the orogen, and a low-Vp/Vs area in the northern foreland seems to correlate with lower crustal earthquakes, which can be related to mechanical differences in rock properties, probably inherited. Our results are in agreement with those found by 3-D ambient noise tomography, though our method inherently performs better at localizing discontinuities. Future developments of this technique can incorporate joint inversions, as well as more efficient parameter space exploration.

Lithospheric Structure of the Circum‐Pannonian Region Imaged by S‐To‐P Receiver Functions

“…The first quality control (QC1) was performed in the time window −200 before and +200 s after the predicted S‐wave arrival (with IASP91 global velocity model) on the filtered ZNE components (Figure 3). This QC step is a complex signal‐to‐noise ratio investigation (Colavitti et al., 2022; Hetényi et al., 2018b; Kalmár et al., 2021) adapted to S waves. We defined 3 different independent criteria, calculating the various ratios of the signals: For each event, only traces with a root mean square (rmsall) between 0.5 and 3 times the median of all traces of each component for that event were kept; The maximum amplitude of the S peak (maxpk) was required to be 7 times more than the rms of the background (rmsbg); The absolute magnitude of the S peak amplitude (lgthS) within maxpk was required to be 4 times larger than the maximum amplitude of the pre‐S wave window (maxbg); …”

“…The location of the stations is shown in Figure 1. (Colavitti et al, 2022;Hetényi et al, 2018b;Kalmár et al, 2021) adapted to S waves. We defined 3 different independent criteria, calculating the various ratios of the signals:…”

A Cascadia Slab Model From Receiver Functions

“…At lower frequencies (≤1 Hz), the receiver function method can be used to image sharp velocity changes such as the Moho or the Conrad interface, low‐velocity zones, and mantle transition zone discontinuities. It has previously been employed to identify discontinuities in complex 3‐D geological structures worldwide for example, in the Himalayan belt (e.g., Caldwell et al., 2013; Singer et al., 2017; Subedi et al., 2018; Xu et al., 2021), the Alps (e.g., Colavitti et al., 2022; Liu et al., 2022; Michailos et al., 2023), the Andes (e.g., Bar et al., 2019; Rodriguez & Russo, 2019; Yuan et al., 2000), and Japan (e.g., Chen et al., 2005; Li et al., 2000; Niu et al., 2005).…”

Moho depths beneath the European Alps: a homogeneously processed map and receiver functions database

“…The crustal structure in the broader Alps region has been investigated with active-source experiments (e.g., Roure et al, 1990;Blundell et al, 1992;Pfiffner et al, 1997), local earthquake tomography (e.g., Diehl et al, 2009), receiver function studies (e.g., Kummerow et al, 2004;Lombardi et al, 2008;Zhao et al, 2015;Colavitti and Hetényi, 2022), a combination of published controlled source seismic (CSS) and receiver function measurements (e.g., Waldhauser et al, 1998;Di Stefano et al, 2011;Spada et al, 2013), and ambient noise studies (e.g., Molinari et al, 2020;Nouibat et al, 2022). Global crustal models give estimates of the Moho depths in the vicinity of the European Alps, however, their results are generally of low resolution (e.g.…”

“…Previous studies based on AASN (e.g., Lu et al, 2020;Paffrath et al, 2021;Bianchi et al, 2021;Monna et al, 2022;Colavitti and Hetényi, 2022;Nouibat et al, 2022) or AlpArray supplementary data (e.g., EASI, SWATH-D; Hetényi et al, 2018b;Molinari et al, 2020;Kind et al, 2021;Sadeghi-Bagherabadi et al, 2021;Jozi Najafabadi et al, 2022) have produced high resolution local images of the crustal structure beneath the European Alps. However, these studies have been limited in their geographic scope which left unresolved regions.…”