Observation of Inner Core Shear Waves with AlpArray
Abstract
Although the solidity of Earths inner core is evidenced by seismic data, its shear properties are poorly understood till this day due to the lack of direct observations of inner core seismic shear waves (PKJKP/SKJKP). One of the reasons why observation of shear waves in the inner core remains challenging is that the inefficient conversion from P- to S-waves at the inner core boundary results in small energy and thus low amplitudes on seismograms. Previous studies have claimed to detect these shear phases in different seismic datasets (e.g., Okal and Cansi Y, 1998, Deuss et al., 2000, Wookey and Helffrich, 2008), however, the observability seems to be highly dependent not only on distance, but also on the location of the source and receiver on the globe. Tkalcic and Pham (2018) found the shear phase in global correlation stacks, but these might be dominated by single, efficient paths. We use an approach that combines the array method of slant stacking and polarization filtering to enhance linearly polarized signals with the expected slowness and incident angle. We apply this method on the short-period data of the AlpArray Seismic Network, a large-scale seismic network in Europe that consists of over 600 broadband stations with a mean station spacing of 30-40km, from earthquakes in 110-135 degree distance to avoid overlapping of phases. An arrival consistent with PKJKP in reference travel time and polarization can be found in deep events from the Solomon Islands. We present an overview of PKJKP candidate paths and examine potential links to previous observations of inner core attenuation and anisotropy. We show below an example 3-component polarization-filtered spectrogram and polarization of BFO, a German station located in Black Forest. The is filtered mainly for P-waves based on different polarization attributes: ellipticity, azimuth, and inclination. We are currently working on adding more stations to the processing.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2021
- Bibcode:
- 2021AGUFMDI35D0065L