Shallow elasticity structure from colocated pressure and seismic stations in the Piñon Flat Observatory and estimation of Vs30

Abstract

SUMMARY An algorithm developed in Tanimoto & Wang for deriving shallow elasticity structure from colocated pressure and seismic instruments is applied to data at nine stations in the Piñon Flat Observatory (PFO) in Southern California. Depth resolution kernels indicate that this approach can recover near-surface shear-modulus structure in the upper 50–100 m of the Earth. Our estimate for Vs30 at the closest station (BPH01) agrees with an independent result by Yong et al. which was based on an active source survey with a geophone array. Vs30 derived from the borehole S-wave speed model by Fletcher et al. also agrees with estimates at nearby locations, considering the size of uncertainties. Derived structures are much smoother than their models, however. This is because our method analyses slow quasi-static deformation of the solid Earth in the frequency range 0.005–0.05 Hz that inherently limits depth resolution. Lack of detailed variations in structures does not seem to be the problem for estimating Vs30 as Vs30 is an averaged quantity from the upper 30 m of the Earth. Also our estimates are not affected by different choices of frequency range in the inversion. However, our method may have some difficulty at stiff, hard-rock sites because ground deformation caused by surface pressure can become small and the key observables in our method, the ratios between seismic amplitude and surface pressure change, become difficult to measure accurately.

Estimation of Vs30 at the EarthScope Transportable Array Stations by Inversion of Low‐Frequency Seismic Noise

“…Information shown in the box plot is consistent with visual patterns seen in Figure 7. Besides these large‐scale analyses of our results, we validated results from the inversion by comparing our estimates of Vs30 with measured Vs30 in the Southern California (Tanimoto & Wang, 2020).…”

“…On the other hand, because we aim to estimate Vs30, which is an averaged quantity for the upper 30 m, the inversion method still provides reasonable estimates. Comparison with on‐site measured Vs30 in Tanimoto and Wang (2020) supports such a claim. Second, even with the upper frequency limit of 0.05 Hz, we cannot resolve the uppermost layer shallower than 5–10 m. In Figure 14, the minimum median peak depths of shear‐modulus kernels are still deeper than 10 m. This suggests we typically lack sensitivity for structures shallower than 10 m. Uppermost velocity profiles of 355A and I05D (Figure 3) show faster Vs at 0–10 m than Vs at 10–20 m due to the lack of resolution in uppermost 10 m. The uppermost velocities are essentially aligned with half‐space parameters at the highest frequency in the starting models and are not affected by the iterative process due to the lack of sensitivity.…”

“…In order to estimate Vs30 for a layered structure beneath a station, we developed an inversion approach by inverting data between 0.01 and 0.05 Hz (hereafter referred to as “the inversion method”; Tanimoto & Wang, 2019). Near‐surface elastic structures estimated from the inversion method have been corroborated by comparing with measured Vs30 (Yong et al., 2013) at collocated stations within the Piñon Flat Observatory (Tanimoto & Wang, 2020).…”

“…Different distributions of Vs30 on different categories of surficial materials also agree with the general understanding between seismic velocity and sediment types. Although there are no available measured velocity profiles to compare with the TA stations, we previously validated our single‐station approach by comparing with measured velocity profile in the Piñon Flat Observatory (Tanimoto & Wang, 2020). We support the more straightforward half‐space approach because it correlates well with Vs30 found in the layered structure.…”

Achievements and Prospects of Global Broadband Seismographic Networks After 30 Years of Continuous Geophysical Observations

“…The secondary broadband sensors have many applications including providing lower‐noise high‐frequency (>20 Hz) data, which is used by the CTBTO (Bell, 2018), enabling quality control of the station by comparing seismograms with the primary sensor (Ringler, Hagerty, et al., 2015), and providing a redundant recording in the event of primary sensor failure. As will be discussed in detail in Section 10, simultaneous recordings of local environmental conditions such as pressure and magnetic field variations can be used to both reduce unwanted signals recorded on seismic instruments (e.g., Beauduin et al., 1996; Ringler et al., 2020) and to provide information about the elastic properties of the material in which the seismometer is emplaced (Tanimoto & Wang, 2020). The most recent equipment update to the GSN has been the incorporation of Streckeisen STS‐6 and Nanometrics T‐360 seismometers (Figure 7).…”