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Abstract Body‐to‐surface wave scattering, originated from strong lateral heterogeneity, has been observed and modeled for decades. Compared to body waves, scattered surface waves propagate along the Earth's surface with less energy loss and, thus, can be observed over a wider distance range. In this study, we utilize surface waves converted from teleseismicSHorSdiffwave incidence to map strong lateral heterogeneities across the entire contiguous United States. We apply array‐based phase coherence analysis to broadband waveforms recorded by the USArray Transportable Array and other permanent/temporary networks to detect coherent signals that are associated with body‐to‐surface wave scattering. We then locate the source of the scattering by back‐propagating the beamformed energy using both straight‐ray and curved‐ray approximations. Our results show that the distribution of scatterers correlates well with known geological features across the contiguous United States. Topographic/bathymetric relief along the continental slope off the Pacific Border is the major source of scattering in the western United States. On the other hand, sedimentary basins, especially their margins, are the dominant scatterers in the central United States. Moho offsets, such as the one around the periphery of the Colorado Plateau, are also a strong contributor to scattering, but isolating their effect from that of other near‐surface structures without any additional constraints can be complicated. Finally, we demonstrate the possibility of using scattered surface waves to constrain subsurface velocity structures, as complementary to conventional earthquake‐ or ambient noise‐based surface wave tomography. 

Abstract The 2010M_W7.2 El Mayor‐Cucapah earthquake ruptured a zone of ~120 km in length in northern Baja California. The geographic distribution of this earthquake sequence was well constrained by waveform relocation. The depth distribution, however, was poorly determined as it is near the edge of, or outside, the Southern California Seismic Network. Here we use two complementary methods to constrain the focal depths of moderate‐sized events (M≥ 4.0) in this sequence. We first determine the absolute earthquake depth by modeling the regional depth phases at high frequencies (~1 Hz). We mainly focus onPnand its depth phasespPnandsPn, which arrive early at regional distance and are less contaminated by crustal multiples. To facilitate depth phase identification and to improve signal‐to‐noise ratio, we take advantage of the dense Southern California Seismic Network and use array analysis to align and stackPnwaveforms. For events without clear depth phases, we further determine their relative depths with respect to those with known depths using differential travel times of thePn, directP, and directSphases recorded for event pairs. Focal depths of 93 out of 122M≥ 4.0 events are tightly constrained with absolute uncertainty of about 1 km. Aftershocks are clustered in the depth range of 3–10 km, suggesting a relatively shallow seismogenic zone, consistent with high surface heat flow in this region. Most aftershocks are located outside or near the lower terminus of coseismic high‐slip patches of the main shock, which may be governed by residual strains, local stress concentration, or postseismic slip. 

Abstract Distributed acoustic sensing (DAS) is a recently developed technique that has demonstrated its utility in the oil and gas industry. Here we demonstrate the potential of DAS in teleseismic studies using the Goldstone OpticaL Fiber Seismic experiment in Goldstone, California. By analyzing teleseismic waveforms from the 10 January 2018 M7.5 Honduras earthquake recorded on ~5,000 DAS channels and the nearby broadband station GSC, we first compute receiver functions for DAS channels using the vertical‐component GSC velocity as an approximation for the incident source wavelet. The MohoP‐to‐sconversions are clearly visible on DAS receiver functions. We then derive meter‐scale arrival time measurements along the entire 20‐km‐long array. We are also able to measure path‐averaged Rayleigh wave group velocity and local Rayleigh wave phase velocity. The latter, however, has large uncertainties. Our study suggests that DAS will likely play an important role in many fields of passive seismology in the near future.