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  • 1
    Publication Date: 2016-06-17
    Description: We present a new technique for deriving detailed information on seismic velocities of the subsurface material from continuous ambient noise recorded by spatially dense seismic arrays. This method uses iterative double beamforming between various subarrays to extract surface wave contributions from the ambient-noise data in complex environments with unfavourable noise-source distributions. The iterative double beamforming extraction makes it possible to retrieve large amounts of Rayleigh wave traveltime information in a wide frequency band. The method is applied to data recorded by a highly dense Nodal array with 1108 vertical geophones, centred on the damage zone of the Clark branch of the San Jacinto Fault Zone south of Anza, California. The array covers a region of ~650 x 700 m 2 , with instrument spacing of 10–30 m, and continuous recording at 500 samples s –1 over 30 d in 2014. Using this iterative double beamforming on subarrays of 25 sensors and cross-correlations between all of the station pairs, we separate surface waves from body waves that are abundant in the raw cross-correlation data. Focusing solely on surface waves, maps of traveltimes are obtained at different frequencies with unprecedented accuracy at each point of a 15-m-spacing grid. Group velocity inversions at 2–4 Hz reveal depth and lateral variations in the structural properties within and around the San Jacinto Fault Zone in the study area. This method can be used over wider frequency ranges and can be combined with other imaging techniques, such as eikonal tomography, to provide unprecedented detailed structural images of the subsurface material.
    Keywords: Seismology
    Print ISSN: 0956-540X
    Electronic ISSN: 1365-246X
    Topics: Geosciences
    Published by Oxford University Press on behalf of The Deutsche Geophysikalische Gesellschaft (DGG) and the Royal Astronomical Society (RAS).
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  • 2
    Publication Date: 2015-04-17
    Description: High-melt areas of glaciers and ice sheets foster a rich spectrum of ambient seismicity. These signals not only shed light on source mechanisms (e.g. englacial fracturing, water flow, iceberg detachment, basal motion) but also carry information about seismic wave propagation within glacier ice. Here, we present two approaches to measure and potentially monitor phase velocities of high-frequency seismic waves (≥1 Hz) using naturally occurring glacier seismicity. These two approaches were developed for data recorded by on-ice seasonal seismic networks on the Greenland Ice Sheet and a Swiss Alpine glacier. The Greenland data set consists of continuous seismograms, dominated by long-term tremor-like signals of englacial water flow, whereas the Alpine data were collected in triggered mode producing 1–2 s long records that include fracture events within the ice (‘icequakes’). We use a matched-field processing technique to retrieve frequency-dependent phase velocity measurements for the Greenland data. In principle, this phase dispersion relationship can be inverted for ice sheet thickness and bed properties. For these Greenland data, inversion of the dispersion curve yields a bedrock depth of 541 m, which may be too small by as much as 35 per cent. We suggest that the discrepancy is due to lateral changes in ice sheet depth and bed properties beneath the network, which may cause unaccounted mixing of surface wave modes in the dispersion curve. The Swiss Alpine icequake records, on the other hand, allow for reconstruction of the impulse response between two seismometers. The direct and scattered wave fields from the vast numbers of icequake records (tens of thousands per month) can be used to measure small changes in englacial velocities and thus monitor structural changes within the ice.
    Keywords: Seismology
    Print ISSN: 0956-540X
    Electronic ISSN: 1365-246X
    Topics: Geosciences
    Published by Oxford University Press on behalf of The Deutsche Geophysikalische Gesellschaft (DGG) and the Royal Astronomical Society (RAS).
    Location Call Number Expected Availability
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