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      Towards forecasting volcanic eruptions using seismic noise

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          High-Resolution Surface-Wave Tomography from Ambient Seismic Noise

          Cross-correlation of 1 month of ambient seismic noise recorded at USArray stations in California yields hundreds of short-period surface-wave group-speed measurements on interstation paths. We used these measurements to construct tomographic images of the principal geological units of California, with low-speed anomalies corresponding to the main sedimentary basins and high-speed anomalies corresponding to the igneous cores of the major mountain ranges. This method can improve the resolution and fidelity of crustal images obtained from surface-wave analyses.
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            Long-period volcano seismicity: its source and use in eruption forecasting

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              Long-range correlations in the diffuse seismic coda.

              The late seismic coda may contain coherent information about the elastic response of Earth. We computed the correlations of the seismic codas of 101 distant earthquakes recorded at stations that were tens of kilometers apart. By stacking cross-correlation functions of codas, we found a low-frequency coherent part in the diffuse field. The extracted pulses have the polarization characteristics and group velocities expected for Rayleigh and Love waves. The set of cross-correlations has the symmetries of the surface-wave part of the Green tensor. This seismological example shows that diffuse waves produced by distant sources are sufficient to retrieve direct waves between two perfectly located points of observation. Because it relies on general properties of diffuse waves, this result has potential applications in other fields.
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                Author and article information

                Journal
                Nature Geoscience
                Nature Geosci
                Springer Science and Business Media LLC
                1752-0894
                1752-0908
                February 2008
                January 20 2008
                February 2008
                : 1
                : 2
                : 126-130
                Article
                10.1038/ngeo104
                de4622bb-efce-4e34-9b18-f87a8bc7e2b9
                © 2008

                http://www.springer.com/tdm

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