Empirical Spectral Characteristics of the Medium near Strong-Motion Seismic Stations of Kamchatka

Abstract

—Spectral characteristics of the medium around 23 digital strong-motion seismic stations of Kamchatka region have been studied from local earthquake data relative to a reference bedrock station (Petropavlovsk, PET). Spectra are determined by multiband filtering. In each band peak velocity amplitudes, levels of Fourier S-spectra and mean-square coda amplitudes were compared. Average Fourier spectra were obtained from S-wave energy using Parseval’s equation. The difference in hypocentral distances for pairs of stations was compensated by empirical S-wave attenuation functions. Records of more than 300 events were processed, with M = 5–6 and hypocentral distances mainly 100–600 km. The spectral ratios estimated by the three methods show behavior diversity. Some non-rock stations show expected spectral characteristics at high frequencies. The conditions at other stations can be considered similar to those at PET. Some stations show amplifications of up to 10 times in the 20–30 Hz frequency range. In general, the obtained spectral characteristics within 3–5 Hz are consistent with the expected trends corresponding to known local geology around strong-motion stations.

Scaling of two corner frequencies of source spectra for earthquakes of the Bering fault

“…By 2011, several stations of Kamchatka seismic network was upgraded with CMG-5TD accelerometers [Chebrov et al, 2013], including Bering (BKI) set up in 2008, Krutoberegovo (KBG), Ust-Kamchatsk (UK1), Tumrok (TUMD), Gupanovo (GPN) and Shipunskii (SPN) stations (Table 2), closest to the Bering fault ( Figure 1). During 2010-2018, when most of the stations have been operated, within 54-56 ∘ N and 162.5-169.5 ∘ E, about 500 earthquakes with > 4.0 have been recorded.…”

“…Spectra calculation. Spectra were calculated using a specialized interactive program written in Matlab, the description of which can be found in [Skorkina and Gusev, 2017]. In brief, the program performs visualizing of seismic traces, selecting time windows for signal and noise, implying instrument corrections, estimating of signalto-noise ratio, calculating Fast Fourier Transform, smooth spectra over bands of 2/3 octave wide, and visualizing of spectra.…”

“…To reduce the observed spectra to the conditions of homogenous media and recover source spectra, we need to evaluate the contributions of such factors as near-surface attenuation and inelastic loss in the media. The function was assumed to have the form, following the technique implied earlier to earthquakes of the Avacha Gulf and described in [Skorkina and Gusev, 2017]: (1) where 0 = 1 Hz, 0 = 30 km, 0 = 156, = −0.08; and kappa equals to 0.01 for rock stations (including pyroclastic one) and 0.03 for medium soils, respectively. To pick three corner frequencies at the source spectrum (corrected for propagation effects), the interactive mode was used ( Figure 3 and Figure 4).…”

“…Regularly observed magnitude discrepancies in the region, with discrepancies up to 1.2 magnitude units (Table 1), might be considered as an indicator of complex spectra shape [Duda, 1978], when, for example, the low-frequency part of a spectrum ( , 0.2-0.5 Hz) scales differently than mediumfrequency part ( ,. Previously, study on determination of corner frequencies for source spectra of Kamchatka earthquakes revealed that a three-corner frequencies shape is preferred for approximation of source spectra of thrust earthquakes from the Avacha Gulf with = 3-6 [Skorkina and. The earth- quakes from transform faults near the Bering Island were not considered earlier and are of interest in this paper.…”

“…Focal mechanisms gradually changes from thrusts of subduction zones to transform faults near Komandorsky Islands (Bering and Medny Islands), at the boundary of the Pacific and Bering plates. The existence of Bering plate was disputable, however, nowadays the fact is usually accepted [Mackey et al, 1997;Cross and Freymueller, 2008]. The tectonic deformation is distributed in the region between a few sub parallel [Abubakirov et al, 2018] and, additionally, about one third of events (when it is possible) are evaluated via the coda magnitude scale, which characterizes the signal in the frequency range of 0.2-0.5 Hz (Figure 2).…”