2019
DOI: 10.1093/gji/ggz081
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Arrival angles of teleseismic fundamental mode Rayleigh waves across the AlpArray

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Cited by 13 publications
(26 citation statements)
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“…In Figure 3, arrival angle deviations are plotted as the difference between measured arrival angle and geometrical great circle for eight periods between 50 and 120 s, inside the magenta-bordered region surrounding the AlpArray. The same measurements have been presented in Figures 11 (M7.4) and S6 (M7.2) of Kolínský and Bokelmann (2019). Key observations are, on the one hand, the similarity of the patterns for the two earthquakes and, on the other hand, a lateral shift of the stripes by around 170 km.…”
Section: Observationsupporting
confidence: 63%
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“…In Figure 3, arrival angle deviations are plotted as the difference between measured arrival angle and geometrical great circle for eight periods between 50 and 120 s, inside the magenta-bordered region surrounding the AlpArray. The same measurements have been presented in Figures 11 (M7.4) and S6 (M7.2) of Kolínský and Bokelmann (2019). Key observations are, on the one hand, the similarity of the patterns for the two earthquakes and, on the other hand, a lateral shift of the stripes by around 170 km.…”
Section: Observationsupporting
confidence: 63%
“…They have similar magnitudes (7.2 and 7.4) and distances (around 12,000 km, differing by 54 km), and the epicenters are separated by 330 km (Figure 1). These two events were chosen from the 20 earthquakes investigated by Kolínský and Bokelmann (2019), since the stripe-like patterns are clear over a broad period range and the arrival angle deviations are of high amplitude. The similarity of both events and the similarity of the observed patterns suggest that the arrival angle deviations are caused by the same structural anomaly.…”
Section: Data and Measurementmentioning
confidence: 99%
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“…Smearing and weakening of the imaged anomalies are not only caused by the large wavelengths but also by the reduction in data coverage at long periods in the dataset (Kästle et al 2018). Complexities in the propagation path of surface waves can also affect the uncertainty in the deeper part of the model where it is largely constrained by earthquake data (Kolínskỳ et al 2019). Given that we use a pre-AlpArray (Hetényi et al 2018a) dataset, there is a considerable variability in station coverage which can additionally cause lateral variations in anomaly strength.…”
Section: Surface-wave Tomographymentioning
confidence: 99%