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Shear wave automatic picking and splitting measurements at Ruapehu volcano, New Zealand
Author(s) -
Castellazzi Claire,
Savage Martha K.,
Walsh Ernestynne,
Arnold Richard
Publication year - 2015
Publication title -
journal of geophysical research: solid earth
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.983
H-Index - 232
eISSN - 2169-9356
pISSN - 2169-9313
DOI - 10.1002/2014jb011585
Subject(s) - geology , seismology , shear wave splitting , seismogram , volcano , shear (geology) , arrival time , population , anisotropy , geodesy , physics , optics , petrology , demography , sociology , transport engineering , engineering
Automatic shear wave picking and shear wave splitting measurement tools (Multiple Filter Automatic Splitting Technique ( MFAST )) are combined to build a near‐real time application for monitoring local stress around volcanoes. We use an adapted version of Diehl et al. (2009) on seismograms provided by the New Zealand GeoNet network and having an origin time and location based only on P picks. The best automatic picks are processed by MFAST , which computes the corresponding shear wave fast direction ϕ , and splitting delay time δt , interpreted, respectively, as the principal direction of stress underneath the station and the amount of anisotropy integrated along the wave raypath. We applied our system to 9 years of local earthquakes recorded at seven stations around Ruapehu volcano, New Zealand. Results are compared against MFAST measurements from manual S picks when available and show less than 10° difference for 90% of ϕ measurements and less than 0.05 s difference for 95% of δt measurements. Shear wave splitting from automatic S arrival times are slightly more consistent than those from manual arrival times. At some stations, two populations of delay times occur, which depend upon computed initial polarization. This may be caused in part by cycle skipping, an artifact usually associated with monochromatic signals. However, spatial consistency in the behavior suggests a physical cause as well, such as focal mechanisms varying with earthquake source location or a spatially varying near‐source anisotropic region. The numbers of events in each population group vary over time, possibly related to activity at Ruapehu volcano.