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SUMMARY The recent developments in array-based surface-wave tomography have made it possible to directly measure apparent phase velocities through wave front tracking. While directionally dependent measurements have been used to infer intrinsic $$2\psi $$ azimuthal anisotropy (with a 180° periodicity), a few studies have also demonstrated strong but spurious $$1\psi $$ azimuthal anisotropy (360° periodicity) near major structure boundaries particularly for long period surface waves. In such observations, Rayleigh waves propagating in the direction perpendicular to the boundary from the slow to the fast side persistently show a higher apparent velocity compared to waves propagating in the opposite direction. In this study, we conduct numerical and theoretical investigations to explore the effect of scattering on the apparent Rayleigh-wave phase velocity measurement. Using 2-D spectral-element numerical wavefield simulations, we first reproduce the observation that waves propagating in opposite directions show different apparent phase velocities when passing through a major velocity contrast. Based on mode coupling theory and the locked mode approximation, we then investigate the effect of the scattered fundamental-mode Rayleigh wave and body waves interfering with the incident Rayleigh wave separately. We show that scattered fundamental-mode Rayleigh waves, while dominating the scattered wavefield, mostly cause short wavelength apparent phase velocity variations that could only be studied if the station spacing is less than about one tenth of the surface wave wavelength. Scattered body waves, on the other hand, cause longer wavelength velocity variations that correspond to the existing real data observations. Because of the sensitivity of the $$1\psi $$ apparent anisotropy to velocity contrasts, incorporating such measurements in surface wave tomography could improve the resolution and sharpen the structural boundaries of the inverted model. 

Abstract Understanding the generation of damaging, high‐frequency ground motions during earthquakes is essential both for fundamental science and for effective hazard preparation. Various theories exist regarding the origin of high‐frequency ground motions, including the standard paradigm linked to slip heterogeneity on the rupture plane, and alternative perspectives associated with fault complexity. To assess these competing hypotheses, we measure ground motion amplitudes in different frequency bands for 3 ≤ M ≤ 5.8 earthquakes in Southern California and compare them to empirical ground motion models. We utilize a Bayesian inference technique called the Integrated Nested Laplace Approximation (INLA) to identify earthquake source regions that produce higher or lower ground motions than expected. Our analysis reveals a strong correlation between fault complexity measurements and the high‐frequency ground motion event terms identified by INLA. These findings suggest that earthquakes on complex faults (or fault networks) lead to stronger‐than‐expected ground motions at high frequencies. 

Abstract Imaging of Earth’s interior has led to a large number of successful discoveries of plausible structures and associated geophysical processes. However, due to the limitations of geophysical data, Earth imaging has many trade-offs between the underlying features, and most approaches apply smoothing to reduce the effect of such trade-offs. Unfortunately, this smoothing often results in blurry images that are not clear enough either to infer the geologic processes of interest or to make quantitative inferences about the various geologic properties. Here, we first summarize some of the basic issues that make Earth imaging so difficult and explain how Earth imagers must choose between more open-ended discovery-oriented goals and more specific, scientific-inference-oriented goals. We discuss how the choice of the optimal imaging framework depends crucially on the desired goal, and particularly on whether plausible discovery or inference is the desired outcome. We argue that as Earth imaging has become more mature, sufficiently many plausible structures have been imaged that it is becoming more crucial for Earth imaging to serve the inference goal and would benefit from an inference-oriented imaging framework, despite the additional challenges in posing imaging problems in this manner. Examples of inference-oriented imaging frameworks are provided and contrasted with discovery-oriented frameworks. We discuss how the success of the various frameworks depends critically on the data quality and suggest that a careful balance must be struck between the ambition of the imager and the reality of the data. If Earth imaging is to move beyond presenting qualitatively plausible structures, it should move toward making quantitative estimates of the underlying geologic processes inferred through a self-consistent framework. 

Abstract Numerical modeling of ice sheet motion and hence projections of global sea level rise require information about the evolving subglacial environment, which unfortunately remains largely unknown due to its difficulty of access. Here we advance such subglacial observations by reporting multi‐year observations of seismic tremor likely associated with glacier sliding at Helheim Glacier. This association is confirmed by correlation analysis between tremor power and multiple environmental forcings on different timescales. Variations of the observed tremor power indicate that different factors affect glacial sliding on different timescales. Effective pressure may control glacial sliding on long (seasonal/annual) timescales, while tidal forcing modulates the sliding rate and tremor power on short (hourly/daily) timescales. Polarization results suggest that the tremor source comes from an upstream subglacial ridge. This observation provides insights on how different factors should be included in ice sheet modeling and how their timescales of variability play an essential role. 

Abstract Accurate precipitation monitoring is crucial for understanding climate change and rainfall-driven hazards at a local scale. However, the current suite of monitoring approaches, including weather radar and rain gauges, have different insufficiencies such as low spatial and temporal resolution and difficulty in accurately detecting potentially destructive precipitation events such as hailstorms. In this study, we develop an array-based method to monitor rainfall with seismic nodal stations, offering both high spatial and temporal resolution. We analyze seismic records from 1825 densely spaced, high-frequency seismometers in Oklahoma, and identify signals from nine precipitation events that occurred during the one-month station deployment in 2016. After removing anthropogenic noise and Earth structure response, the obtained precipitation spatial pattern mimics the one from a nearby operational weather radar, while offering higher spatial (~ 300 m) and temporal (< 10 s) resolution. We further show the potential of this approach to monitor hail with joint analysis of seismic intensity and independent precipitation rate measurements, and advocate for coordinated seismological-meteorological field campaign design. 

SUMMARY Seismic tomography is a cornerstone of geophysics and has led to a number of important discoveries about the interior of the Earth. However, seismic tomography remains plagued by the large number of unknown parameters in most tomographic applications. This leads to the inverse problem being underdetermined and requiring significant non-geologically motivated smoothing in order to achieve unique answers. Although this solution is acceptable when using tomography as an explorative tool in discovery mode, it presents a significant problem to use of tomography in distinguishing between acceptable geological models or in estimating geologically relevant parameters since typically none of the geological models considered are fit by the tomographic results, even when uncertainties are accounted for. To address this challenge, when seismic tomography is to be used for geological model selection or parameter estimation purposes, we advocate that the tomography can be explicitly parametrized in terms of the geological models being tested instead of using more mathematically convenient formulations like voxels, splines or spherical harmonics. Our proposition has a number of technical difficulties associated with it, with some of the most important ones being the move from a linear to a non-linear inverse problem, the need to choose a geological parametrization that fits each specific problem and is commensurate with the expected data quality and structure, and the need to use a supporting framework to identify which model is preferred by the tomographic data. In this contribution, we introduce geological parametrization of tomography with a few simple synthetic examples applied to imaging sedimentary basins and subduction zones, and one real-world example of inferring basin and crustal properties across the continental United States. We explain the challenges in moving towards more realistic examples, and discuss the main technical difficulties and how they may be overcome. Although it may take a number of years for the scientific program suggested here to reach maturity, it is necessary to take steps in this direction if seismic tomography is to develop from a tool for discovering plausible structures to one in which distinct scientific inferences can be made regarding the presence or absence of structures and their physical characteristics. 

Abstract Earthquake source spectra provide unique insights into the earthquake rupture process. Motivated by previous research suggesting that complex fault geometries enhance high‐frequency seismic radiation, we study the influence of fault network geometry on earthquake source spectra using multiple independent observations. At regional scales, we examine correlations of stress drop measurements with surface fault trace misalignment in Southern California, Japan, and Central Italy. At a global scale, we examine correlations of moment‐rate function complexity of large earthquakes with focal mechanism variability, a proxy for local fault complexity. Despite significant scatter in the observations, we find overall consistent positive correlations. The concept that elastic interactions of discrete fault structures during the earthquake rupture process generates high‐frequency ground motions offers a coherent framework for interpreting our observations. These findings suggest that variations in fault complexity explain why some earthquakes produce stronger high‐frequency ground motions than others. 

ABSTRACT Seismic tomography is the most abundant source of information about the internal structure of the Earth at scales ranging from a few meters to thousands of kilometers. It constrains the properties of active volcanoes, earthquake fault zones, deep reservoirs and storage sites, glaciers and ice sheets, or the entire globe. It contributes to outstanding societal problems related to natural hazards, resource exploration, underground storage, and many more. The recent advances in seismic tomography are being translated to nondestructive testing, medical ultrasound, and helioseismology. Nearly 50 yr after its first successful applications, this article offers a snapshot of modern seismic tomography. Focused on major challenges and particularly promising research directions, it is intended to guide both Earth science professionals and early-career scientists. The individual contributions by the coauthors provide diverse perspectives on topics that may at first seem disconnected but are closely tied together by a few coherent threads: multiparameter inversion for properties related to dynamic processes, data quality, and geographic coverage, uncertainty quantification that is useful for geologic interpretation, new formulations of tomographic inverse problems that address concrete geologic questions more directly, and the presentation and quantitative comparison of tomographic models. It remains to be seen which of these problems will be considered solved, solved to some extent, or practically unsolvable over the next decade.