Moho Complexity in Southern California Revealed by Local PmP and Teleseismic Ps Waves

Abstract

The Moho discontinuity represents a petrological boundary separating the Earth's silicic crust from the ultramafic mantle. It is the strongest seismic discontinuity within the Earth's outermost cold shell and even within the whole solid Earth except for the core-mantle boundary. The P-wave velocity contrast across the Moho in continental region can reach ∼20% in the IASP91 model (Kennett & Engdahl, 1991) or ∼15% in the CM95 model (Christensen & Mooney, 1995;Rabbel et al., 2013). Thus, seismic waves derived from the Moho discontinuity, which follow the first arrivals, usually dominate the early portion of a seismogram and serve as an important toolkit to decipher crustal structures (Grad & Tiira, 2009).Both active source surveys and passive seismic studies use Moho-related phases to constrain crustal structures. Active source surveys exploit local Moho-reflected waves PmP and Moho-refracted waves Pn (with frequency typically centered at ∼10 Hz) to investigate the Moho topography and crustal volumetric structure (Grad & Tiira, 2009;Mooney, 2010;Wright et al., 2013). Passive seismic studies sometimes use local Moho-reflected waves PmP or teleseismic Moho-converted waves Ps to image the crustal structure (Figure 1). Local PmP waves

Elongated Magma Plumbing System Beneath the Coso Volcanic Field, California, Constrained by Seismic Reflection Tomography

“…(e) Additionally, we reduce the P wave SNR cutoff to 3 to allow more seismograms to be considered, and additional PmP waves that have similar traveling paths as those selected in previous steps are sought out on newly involved seismograms. More details about PmP data selection as well as validation can be found in a separate paper (Li et al., 2022). Finally, we have manually picked 8,636 high‐quality PmP arrivals from 4,482 local events at 51 seismic stations, in which, more than half are from the 2019 Ridgecrest earthquake sequence (the yellow dots in Figure 1).…”

“…However, PmP arrivals are usually very emergent and hard to pick on individual seismograms (Richards‐Dinger & Shearer, 1997), which hinders its wide usage in seismic tomography. In this study, we apply a newly developed PmP picking workflow (Li et al., 2022), and take advantage of the intensive seismicity (especially the 2019 Ridgecrest earthquake sequence), to pick a large amount of robust PmP arrivals in and around the Coso region (referred as the Coso‐Ridgecrest area). Using high‐quality first P and PmP arrivals simultaneously, we are able to build a high‐resolution P‐wave velocity model for the entire crust, which sheds light on the evolution and dynamics of the magma plumbing system beneath the CVF, especially in the deep crust.…”

Deep Neural Networks for Creating Reliable PmP Database With a Case Study in Southern California

“…In other regions like the Ventura Basin and the Coso volcanic field, we observe some small‐scale Moho undulations, which is related to the complicated local crust structure (Wilson et al., 2003; Yan & Clayton, 2007). In the western Peninsular Ranges, the Moho depth estimated by sparse PmP data is much shallower compared to the CMM‐1.0, which may be related to the oversimplified one‐layer crust model assumed here or/and a gradual transition from the crust to the upper mantle there (Li et al., 2022).…”

“…For the PmP database spanning from January 2000 to December 2018 built by the two-stage PmP-picking workflow (Li et al, 2022), we observe that travel times of the PmP waves increase linearly with respect to epicentral distance, amplitudes of the PmP waves are mostly larger than the P waves and particle motions of most PmP waves polarize in a similar way as the P waves. Here, we apply the trained PmPNet to the same 19-year long vertical-component seismic data to automatically identify the waveforms which could contain high-quality PmP waves.…”

“…We have developed a two‐stage workflow of identifying and picking PmP waves in a semiautomatic way (Li et al., 2022). Briefly speaking, the two‐stage workflow includes two parts: At the first stage, high‐quality PmP waves are automatically picked on selected seismograms.…”