Geophysical Journal International · 2008 · 86 citations · 39 references
Natural SciencesEarth SciencesGeophysicsEarthquake EngineeringEarthquake PhysicsSeismologyGeophysical Data ProcessingGeophysical Signal ProcessingModel ResolutionSeismic Data ProcessingSeismic ImagingSeismic TomographyArrival Time PickingAutomated Quality AssessmentHigh-resolution TomographyP-wave Arrival Time AnalysisPhase PickingQuality AssessmentRegional TomographySeismic Event Picking
The resolution and reliability of tomographic velocity models strongly depends on quality and consistency of available traveltime data. Arrival times routinely picked by network analysts on a day-to-day basis often yield a high level of noise due to mispicks and other inconsistencies, particularly in error assessment. Furthermore, tomographic studies at regional scales require merging of phase picks from several networks. Since a common quality assessment is not usually available for phase data provided by different networks, additional inconsistencies are introduced by the merging process. Considerable improvement in the quality of phase data can only be achieved through complete repicking of seismograms. Considering the amount of data necessary for regional high-resolution tomography, algorithms combining accurate picking with an automated error assessment represent the best tool to derive large suitable data sets. In this work, we present procedures for consistent automated and routine picking of P-wave arrival times at local to regional scales including consistent picking error assessment. Quality-attributed automatic picks are derived from the MPX picking system. The application to earthquakes in the greater Alpine region demonstrates the potential of such a repicking approach. The final data set consists of more than 13 000 high-quality first-arrivals and it is used to derive regional 1-D and preliminary 3-D P-wave models of the greater Alpine region. The comparison with a tomographic model based on routine phase data extracted from the ISC Bulletin illustrates effects on tomographic results due to consistency and reliability of our high-quality data set.
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