2015
DOI: 10.1002/2015gc006176
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Italian and Alpine three‐dimensional crustal structure imaged by ambient‐noise surface‐wave dispersion

Abstract: International audienceWe derive the 3-D crustal structure (S wave velocity) underneath Italy and the Alpine region, expanding and exploiting the database of ambient noise Rayleigh-wave phase- and group-velocity of Verbeke et al. (2012). We first complement the database of Verbeke et al. (2012) with a dense set of new ambient-noise-based phase-velocity observations. We next conduct a suite of linear least squares inversion of both phase- and group-velocity data, resulting in 2-D maps of Rayleigh-wave phase and … Show more

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Cited by 59 publications
(70 citation statements)
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“…A comparison between observed and inverted data for all the 50 stations are given in the supporting information ( Figure S1). Inversion results at these stations are also given in the supporting information ( Figure S2), together with the corresponding model from Molinari et al (2015) as a comparison.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…A comparison between observed and inverted data for all the 50 stations are given in the supporting information ( Figure S1). Inversion results at these stations are also given in the supporting information ( Figure S2), together with the corresponding model from Molinari et al (2015) as a comparison.…”
Section: Resultsmentioning
confidence: 99%
“…The CROP project (Finetti, 2005) shed light on intracrustal features through deep seismic reflection. While these studies have mainly characterized the crust in terms of compressional-wave velocities, Verbeke et al (2012), Molinari et al (2015), and Kästle et al (2018) used ambient noise to obtain the shear velocity distribution at depth. Despite the abundance of data, interpretation is made difficult by uneven coverage, varying resolution, and sensitivity of each method.…”
Section: Introductionmentioning
confidence: 99%
“…Our synthetic seismic velocities are compared with those from two seismological models covering the area of interest. These are the EPcrust model (Molinari & Morelli, ) and the one from Molinari, Verbeke, et al (), MB from now on. The first is derived from the combination (i.e., weighted average; see reference for more details) of previous models covering the European continent.…”
Section: Methodsmentioning
confidence: 99%
“…Stipčević et al, 2011, Belinić et al, 2018, ambient noise tomography (e.g. Molinari et al, 2015), SKS-splitting (e.g. Salimbeni at el.…”
Section: Scientific Aimsmentioning
confidence: 99%