EK
Emanuel D. Kästle
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Phase velocities derived from ambient-noise (AN) cross-correlation are compared with phase velocities calculated from earthquake data via the two-station method (EQ). The EQ approach involves crosscorrelating recordings of teleseismic earthquakes whose epicenters are approximately on the station-station great circle. The AN and EQ methods can be combined effectively to cover a broad period range from about 4 to 250 s. The comparison is conducted for both Rayleigh and Love waves using over 1000 station pairs in central Europe. The analysis shows that at periods between 20 and 40s, AN-based phase velocities are systematically slower by about 1.5% compared to the EQ measurements. We revise the theory, explaining possible biases from the stationary-phase approximation and from using horizontal components of the noise wavefield. A series of numerical tests of the AN method is conducted, which allow us to evaluate the effects of the variable distance between station array and noise sources, of the illumination pattern, and of horizontal anisotropy and attenuation. We finally determine phase-velocity maps based on AN vs. EQ data; we find that discrepancies between such maps are far weaker than the mapped anomalies, and too small to result in significantly different geological interpretation of the mapped structure.
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Phase velocities derived from ambient-noise (AN) cross-correlation are compared with phase velocities calculated from earthquake data via the two-station method (EQ). The EQ approach involves crosscorrelating recordings of teleseismic earthquakes whose epicenters are approximately on the station-station great circle. The AN and EQ methods can be combined effectively to cover a broad period range from about 4 to 250 s. The comparison is conducted for both Rayleigh and Love waves using over 1000 station pairs in central Europe. The analysis shows that at periods between 20 and 40s, AN-based phase velocities are systematically slower by about 1.5% compared to the EQ measurements. We revise the theory, explaining possible biases from the stationary-phase approximation and from using horizontal components of the noise wavefield. A series of numerical tests of the AN method is conducted, which allow us to evaluate the effects of the variable distance between station array and noise sources, of the illumination pattern, and of horizontal anisotropy and attenuation. We finally determine phase-velocity maps based on AN vs. EQ data; we find that discrepancies between such maps are far weaker than the mapped anomalies, and too small to result in significantly different geological interpretation of the mapped structure.
Phase velocities derived from ambient-noise cross-correlation are compared with phase velocities calculated from cross-correlations of waveform recordings of teleseismic earthquakes whose epicentres are approximately on the station–station great circle. The comparison is conducted both for Rayleigh and Love waves using over 1000 station pairs in central Europe. We describe in detail our signal-processing method which allows for automated processing of large amounts of data. Ambient-noise data are collected in the 5–80 s period range, whereas teleseismic data are available between about 8 and 250 s, resulting in a broad common period range between 8 and 80 s. At intermediate periods around 30 s and for shorter interstation distances, phase velocities measured from ambient noise are on average between 0.5 per cent and 1.5 per cent lower than those observed via the earthquake-based method. This discrepancy is small compared to typical phase-velocity heterogeneities (10 per cent peak-to-peak or more) observed in this period range.We nevertheless conduct a suite of synthetic tests to evaluate whether known biases in ambient-noise cross-correlation measurements could account for this discrepancy; we specifically evaluate the effects of heterogeneities in source distribution, of azimuthal anisotropy in surface-wave velocity and of the presence of near-field, rather than far-field only, sources of seismic noise. We find that these effects can be quite important comparing individual station pairs. The systematic discrepancy is presumably due to a combination of factors, related to differences in sensitivity of earthquake versus noise data to lateral heterogeneity. The data sets from both methods are used to create some preliminary tomographic maps that are characterized by velocity heterogeneities of similar amplitude and pattern, confirming the overall agreement between the two measurement methods.
...
Phase velocities derived from ambient-noise cross-correlation are compared with phase velocities calculated from cross-correlations of waveform recordings of teleseismic earthquakes whose epicentres are approximately on the station–station great circle. The comparison is conducted both for Rayleigh and Love waves using over 1000 station pairs in central Europe. We describe in detail our signal-processing method which allows for automated processing of large amounts of data. Ambient-noise data are collected in the 5–80 s period range, whereas teleseismic data are available between about 8 and 250 s, resulting in a broad common period range between 8 and 80 s. At intermediate periods around 30 s and for shorter interstation distances, phase velocities measured from ambient noise are on average between 0.5 per cent and 1.5 per cent lower than those observed via the earthquake-based method. This discrepancy is small compared to typical phase-velocity heterogeneities (10 per cent peak-to-peak or more) observed in this period range.We nevertheless conduct a suite of synthetic tests to evaluate whether known biases in ambient-noise cross-correlation measurements could account for this discrepancy; we specifically evaluate the effects of heterogeneities in source distribution, of azimuthal anisotropy in surface-wave velocity and of the presence of near-field, rather than far-field only, sources of seismic noise. We find that these effects can be quite important comparing individual station pairs. The systematic discrepancy is presumably due to a combination of factors, related to differences in sensitivity of earthquake versus noise data to lateral heterogeneity. The data sets from both methods are used to create some preliminary tomographic maps that are characterized by velocity heterogeneities of similar amplitude and pattern, confirming the overall agreement between the two measurement methods.