Seismic noise analysis and Green functions Sample Clauses

Seismic noise analysis and Green functions. The main objectives of the Workpackage are (1) the computation of Green functions among the broad-band ISNet stations, from noise cross-correlation; (2) the S wave velocity model for the Irpinia area, to be compared to P wave tomographic models derived from the inversion of first arrivals; (3) the extension of the method up to higher frequencies (0.5 to 1 Hz), with the investigation of the stability and robustness of the solutions. The appraisal of the Green function from cross-correlation of ambient noise is a well consolidated technique at global and regional scales, where coherent sources are associated with the low frequency motion of the oceans. In such cases, low frequency signals (between 0.01 and 0.1 Hz) are cross-correlated and stacked over a period of several months. In this WP, we started to apply the technique to the local scale of ISNet, the characteristic size of which is about 100 km with an inter-station distance of 10-20 km. There are several problems in downscaling the methodology at smaller wavelengths. First, the arrival time of low frequency contributions (below 0.1 Hz) is so close to the origin, that they cannot be recognized from the cross-correlation. Hence, it is necessary to move to higher frequencies (above 0.1Hz), where the coherency of the noise may be lost between the stations. We also apply the one bit normalization to the data, to cancel out the phases which not clearly appear with the same shape and frequency content at both stations. In such a case, we need to sum up a large amount of signal to allow the Green function to get raised from the noise. We processed 4 months of data from the broad-band xxxxxxxx XXX0, XXX0, XXX0 and TEO3, starting from July 15, 2008 to November 13, 2008. Single station data have been subdivided in windows of 6 hour length, such a time representing a good compromise between the amount of RAM required by the computation and the accuracy of the cross-correlation. Data have been filtered and whitened in the frequency band 0.1-1 Hz; then they have been one-bit normalized in order to suppress any information about the amplitude and preserve only their phase content. For each couple of stations, data have been time-aligned and common windows selected for the computation of the cross-correlation. Final traces have been stacked with the constrain that the signal to noise ratio is larger than 3, where the signal corresponds to the maximum of the amplitude in a time window compatible with the surface wave ...
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