An official website of the United States government
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.
more »
« less
Likely P‐to‐S Conversion at the Core‐Mantle Boundary Extracted From Array Processing of Noise Records
Abstract Seismic noise has been widely used to image Earth's structure in the past decades as a powerful supplement to earthquake signals. Although the seismic noise field contains both surface‐wave and body‐wave components, most previous studies have focused on surface waves due to their large amplitudes. Here, we use array analyses to identify body‐wave noise traveling asPKPwaves. We find that by cross‐correlating the array‐stacked horizontal‐ and vertical‐component data in the time windows containing thePKPnoise signals, we extract a phase likely representingPKS‐PKP, the differential phase betweenPKSandPKP. This phase can potentially be used for shear‐wave‐splitting analysis. Our results also suggest that the sources of body‐wave noise are extremely heterogeneous in both space and time, which should be accounted for in future studies using body‐wave noise to image Earth structure.
more »
« less
- PAR ID:
- 10381070
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Geophysical Research Letters
- Volume:
- 49
- Issue:
- 7
- ISSN:
- 0094-8276
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Seismic energy arriving before the compressional (P) wave passing through the core (PKP), called PKP precursors, have been detected for decades, but the origin of those arrivals is ambiguous. The largest amplitude arrivals are linked to scattering at small‐scale lowermost mantle structure, but because these arrivals traverse both source and receiver sides of the mantle, it is unknown which side of the path the energy is scattered from. To address this ambiguity, we apply a new seismic array method to analyze PKP waveforms from 58 earthquakes recorded in North America that allows localization of the origin of the PKP precursors at the core‐mantle boundary (CMB). We compare these measurements with high frequency 2.5‐D synthetic predictions showing that the PKP precursors are most likely associated with ultra‐low velocity zone structures beneath the western Pacific and North America. The most feasible scenario to generate ULVZs in both locations is through melting of mid‐ocean ridge basalt in subducted oceanic crust.more » « less
-
Abstract Seismicity of several intraplate seismic zones in the North American midcontinent is believed to be related to reactivation of ancient faults in Precambrian continental rifts by the contemporary stress field. Existence of such a rift system beneath the Wabash Valley Seismic Zone (WVSZ) is not clear. Here we obtained a crustal structural image along a 300‐km‐long profile across WVSZ using a dense linear seismic array. We first calculated teleseismic receiver functions of stations and applied the Common‐Conversion‐Point stacking method to image crustal interfaces and the Moho. We then used ambient noise cross correlation to obtain phase and group velocities of Rayleigh and Love waves. Finally, we jointly inverted the receiver function and surface wave dispersion data to determine shear wave velocity structure along the profile. The results show a thick (50‐ to 60‐km) crust with a typical Proterozoic crustal layering: a 1‐ to 2‐km thick Phanerozoic sedimentary layer, an upper crust ∼15 km thick, and a 30‐ to 40‐km‐thick lower crust. The unprecedented high‐resolution image also reveals a 50‐km‐wide high‐velocity body above an uplifted Moho and several velocity anomalies in the upper and middle crust beneath the La Salle Deformation Belt. We interpreted them as features produced by magmatic intrusions in a failed, immature continental rift during the end of Precambrian. Current seismicity in WVSZ is likely due to reactivation of ancient faults of the rift system by a combination of stress fields from the far‐field plate motion and prominent crustal and upper mantle heterogeneities in the region.more » « less
-
Abstract Seismic deployments in the Alaska subduction zone provide dense sampling of the seismic wavefield that constrains thermal structure and subduction geometry. We measurePandSattenuation from pairwise amplitude and phase spectral ratios for teleseismic body waves at 206 stations from regional and short‐term arrays. Parallel teleseismic travel‐time measurements provide information on seismic velocities at the same scale. These data show consistently low attenuation over the forearc of subduction systems and high attenuation over the arc and backarc, similar to local‐earthquake attenuation studies but at 10× lower frequencies. The pattern is seen both across the area of normal Pacific subduction in Cook Inlet, and across the Wrangell Volcanic Field where subduction has been debated. These observations confirm subduction‐dominated thermal regime beneath the latter. Travel times show evidence for subducting lithosphere much deeper than seismicity, while attenuation measurements appear mostly reflective of mantle temperature less than 150 km deep, depths where the mantle is closest to its solidus and where subduction‐related melting may take place. Travel times show strong delays over thick sedimentary basins. Attenuation signals show no evidence of absorption by basins, although some basins show signals anomalously rich in high‐frequency energy, with consequent negative apparent attenuation. Outside of basins, these data are consistent with mantle attenuation in the upper 220 km that is quantitatively similar to observations from surface waves and local‐earthquake body waves. Differences betweenPandSattenuation suggest primarily shear‐modulus relaxation. Overall the attenuation measurements show consistent, coherent subduction‐related structure, complementary to travel times.more » « less
-
null (Ed.)SUMMARY Horizontal slowness vector measurements using array techniques have been used to analyse many Earth phenomena from lower mantle heterogeneity to meteorological event location. While providing observations essential for studying much of the Earth, slowness vector analysis is limited by the necessary and subjective visual inspection of observations. Furthermore, it is challenging to determine the uncertainties caused by limitations of array processing such as array geometry, local structure, noise and their effect on slowness vector measurements. To address these issues, we present a method to automatically identify seismic arrivals and measure their slowness vector properties with uncertainty bounds. We do this by bootstrap sampling waveforms, therefore also creating random sub arrays, then use linear beamforming to measure the coherent power at a range of slowness vectors. For each bootstrap sample, we take the top N peaks from each power distribution as the slowness vectors of possible arrivals. The slowness vectors of all bootstrap samples are gathered and the clustering algorithm DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is used to identify arrivals as clusters of slowness vectors. The mean of slowness vectors in each cluster gives the slowness vector measurement for that arrival and the distribution of slowness vectors in each cluster gives the uncertainty estimate. We tuned the parameters of DBSCAN using a data set of 2489 SKS and SKKS observations at a range of frequency bands from 0.1 to 1 Hz. We then present examples at higher frequencies (0.5–2.0 Hz) than the tuning data set, identifying PKP precursors, and lower frequency by identifying multipathing in surface waves (0.04–0.06 Hz). While we use a linear beamforming process, this method can be implemented with any beamforming process such as cross correlation beamforming or phase weighted stacking. This method allows for much larger data sets to be analysed without visual inspection of data. Phenomena such as multipathing, reflections or scattering can be identified automatically in body or surface waves and their properties analysed with uncertainties.more » « less
