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Both large and small earthquakes rupture in complex ways. However, microearthquakes are often simplified as point sources and their rupture properties are challenging to resolve. We leverage seismic wavefields recorded by a dense array in Oklahoma to image microearthquake rupture processes. We construct machine-learning enabled catalogs and identify four spatially disconnected seismic clusters. These clusters likely delineate near-vertical strike-slip faults. We develop a new approach to use the maximum absolute SH-wave amplitude distributions (S-wave wavefields) to compare microearthquake rupture processes. We focus on one cluster with earthquakes located beneath the dense array and have a local magnitude range of -1.3 to 2.3. The S-wave wavefields of single earthquakes are generally coherent but differ slightly between the low-frequency (<12 Hz) and high-frequency (>12 Hz) bands. The S-wave wavefields are coherent between different earthquakes at low frequencies with average correlation coefficients greater than 0.95. However, the wavefield coherence decreases with increasing frequency for different earthquakes. This reduced coherence is likely due to the rupture differences among individual earthquakes. Our results suggest that earthquake slip of the microearthquakes dominates the radiated S-wave wavefields at higher frequencies. Our method suggests a new direction in resolving small earthquake source attributes using dense seismic arrays without assuming a rupture model. 

Abstract The 2019 Mw 7.1 Ridgecrest earthquake was the largest event in California over the past 20 years. The earthquake was preceded by a sequence of foreshocks. However, the physical processes leading to the mainshock remain unclear. Here, we image the ratios of compressional (P)‐ to shear (S)‐wave velocity (V_p/V_s) in the fault zones and examine the spatial and temporal evolution of near‐source material properties during the Ridgecrest earthquake sequence. We find that theV_p/V_sratios are spatially homogeneous in the rupture zones, indicating a lack of fault‐zone material difference along strike. We identify an anomalously lowV_p/V_sratio fault patch near the mainshock hypocenter before its occurrence, which returned to the background value after the earthquake. This lowV_p/V_sratio suggests fluid overpressure, which may have facilitated the nucleation of the 2019 Ridgecrest mainshock. 

The January 1st, 2024, moment magnitude (Mw) 7.5 Noto Peninsula earthquake ruptured in complex ways, challenging timely analysis of the tsunami generation. We present rapid and accurate tsunami models informed by a 6-subevent centroid moment tensor (CMT) model that we obtain by inverting teleseismic and strong motion data and validation against geodetic observations. We identify two distinct bilateral rupture episodes, including six subevents and a re-nucleation episode at its hypocenter 20 seconds after its initiation, likely aided by fault weakening. We construct a complex uplift model that aligns with known fault system geometries and is critical in modeling the observed tsunami. Our tsunami simulation can explain wave amplitude, timing, and polarity of the leading wave, which are crucial for tsunami early warning. Analyzing a 2000 multi-CMT solution ensemble and comparing to alternative rapid source models, we highlight the importance of incorporating complex source effects for realistic tsunami simulations. 

Abstract Deep earthquakes at depths below 500 km are under prohibitive pressure and temperature conditions for brittle failure. Individual events show diverse rupture behaviors and a coherent mechanism to explain their rupture nucleation, propagation, and characteristics has yet to be established. We systematically resolve the rupture processes of 40 large deep earthquakes from 1990 to 2023 and compare the rupture details to their local metastable olivine wedge (MOW) structures informed from thermo‐mechanical simulations in seven subduction zones. Our results suggest that these events likely initiate from metastable olivine transformations within the cold slab core and rupture beyond the MOW due to sustained weakening from molten rock at the rupture tip. Over half of the earthquakes likely rupture beyond the MOW boundary and are controlled by both mechanisms. Rupturing outside the MOW boundary leads to greater moment release, increased geometric complexity, and a reduction in rupture length, causing greater stress drops. 

SUMMARY Surface waves are critical in detecting and locating seismic sources that do not produce much high-frequency radiation. For such sources, typical approaches using body waves for detecting and locating earthquakes are less effective. Slow earthquakes and exotic seismic sources often have this seismic radiation characteristic, and array analyses of surface waves recorded on global and regional seismic networks have proven effective in recognizing such sources. Most approaches have relied on Rayleigh waves, whereas Love waves have rarely been used. Here we develop a new approach using multiscale arrays to detect and locate seismic sources with both Love and Rayleigh surface waves. The method first forms three-station subarrays and then uses three-component records of the stations to independently estimate three sets of surface wave propagation directions and centroid arrival times. The subarray estimates are then assembled to locate seismic sources and their origin times. We find that using multiple, disconnected global networks improves location accuracy and that using both types of surface waves can enhance detection sensitivity and robustness. 

ABSTRACT We present initial findings from the ongoing Community Stress Drop Validation Study to compare spectral stress-drop estimates for earthquakes in the 2019 Ridgecrest, California, sequence. This study uses a unified dataset to independently estimate earthquake source parameters through various methods. Stress drop, which denotes the change in average shear stress along a fault during earthquake rupture, is a critical parameter in earthquake science, impacting ground motion, rupture simulation, and source physics. Spectral stress drop is commonly derived by fitting the amplitude-spectrum shape, but estimates can vary substantially across studies for individual earthquakes. Sponsored jointly by the U.S. Geological Survey and the Statewide (previously, Southern) California Earthquake Center our community study aims to elucidate sources of variability and uncertainty in earthquake spectral stress-drop estimates through quantitative comparison of submitted results from independent analyses. The dataset includes nearly 13,000 earthquakes ranging from M 1 to 7 during a two-week period of the 2019 Ridgecrest sequence, recorded within a 1° radius. In this article, we report on 56 unique submissions received from 20 different groups, detailing spectral corner frequencies (or source durations), moment magnitudes, and estimated spectral stress drops. Methods employed encompass spectral ratio analysis, spectral decomposition and inversion, finite-fault modeling, ground-motion-based approaches, and combined methods. Initial analysis reveals significant scatter across submitted spectral stress drops spanning over six orders of magnitude. However, we can identify between-method trends and offsets within the data to mitigate this variability. Averaging submissions for a prioritized subset of 56 events shows reduced variability of spectral stress drop, indicating overall consistency in recovered spectral stress-drop values. 

Large earthquakes rupture faults over hundreds of kilometers withinminutes. Finite-fault models elucidate these processes and provideobservational constraints for understanding earthquake physics. However,finite-fault inversions are subject to non-uniqueness and substantialuncertainties. The diverse range of published models for thewell-recorded 2011 M_w 9.0 Tohoku-Oki earthquake aptly illustrates thisissue, and details of its rupture process remain under debate. Here, wecomprehensively compare 32 finite-fault models of the Tohoku-Okiearthquake and analyze the sensitivity of three commonly-usedobservational data types (geodetic, seismic, and tsunami) to the slipfeatures identified. We first project all models to a realisticmegathrust geometry and a 1-km subfault size. At this scale, we observepoor correlation among the models, irrespective of the data type.However, model agreement improves significantly when subfault sizes areincreased, implying that their differences primarily stem fromsmall-scale features. We then forward-compute geodetic and teleseismicsynthetics and compare them with observations. We find that seismicobservations are sensitive to rupture propagation, such as thepeak-slip-rise time. However, neither teleseismic nor geodeticobservations are sensitive to spatial slip features smaller than 64 km.In distinction, the synthesized seafloor deformation of all modelsexhibits poor correlation, indicating sensitivity to small-scale slipfeatures. Our findings suggest that fine-scale slip features cannot beunambiguously resolved by remote or sparse observations, such as thethree data types tested in this study. However, better resolution maybecome achievable from uniformly gridded dense offshore instrumentation. 

Abstract Oceanic detachment fault systems are characteristic of slow‐spreading mid‐ocean ridges, where reduced magma supply leads to increased extension by faulting and exhumation of oceanic core complexes (OCCs). OCCs have complicated structure reflecting the interplay between magmatic, hydrothermal, and tectonic processes. We use microearthquake data from a 9‐month ocean bottom seismometer deployment to image deformation structures in the Rainbow massif on the Mid‐Atlantic Ridge. Using a machine‐learning enabled workflow to obtain an earthquake catalog containing 68,000 events, we find seismicity occurred in distinct clusters that correlate with previously imaged velocity anomalies and dipping subsurface reflections. Our results are consistent with a dipping alteration front within the massif overlying late‐stage intrusions and suggest a transpressional fault accommodates a non‐transform offset north of the massif. Our results demonstrate OCCs continue to deform in a complex way after a detachment fault has been abandoned due to combined effects of tectonic stresses, magmatism, and alteration. 

Abstract We identify 51 near-contemporaneous earthquake pairs along a 100 km segment of California’s San Andreas fault south of San Juan Bautista between 1981 and 2021 that are separated by 5–50 s in time and 5–50 km in space. The event pairs are found throughout the time period and generally involve events smaller than magnitude 2. For 42 of these pairs (82%), the later earthquake is northwest of the earlier event—an asymmetry that is hard to explain with standard earthquake triggering models and suggests an underlying physical connection between the events. We explore possible origins for these observations but are unable to identify a definitive explanation. 

Abstract Large earthquakes rupture faults over hundreds of kilometers within minutes. Finite‐fault models image these processes and provide observational constraints for understanding earthquake physics. However, finite‐fault inversions are subject to non‐uniqueness and uncertainties. The diverse range of published models for the well‐recorded 2011 9.0 Tohoku‐Oki earthquake illustrates this challenge, and its rupture process remains under debate. Here, we comprehensively compare 32 published finite‐fault models of the Tohoku‐Oki earthquake. We aim to identify the most coherent slip features of the Tohoku‐Oki earthquake from these slip models and develop a new method for quantitatively analyzing their variations. We find that the models correlate poorly at 1‐km subfault size, irrespective of the data type. In contrast, model agreement improves significantly with increasing subfault sizes, consistently showing that the largest slip occurs up‐dip of the hypocenter near the trench. We use the set of models to test the sensitivity of available teleseismic, regional seismic, and geodetic observations. For the large Tohoku‐Oki earthquake, we find that the analyzed finite‐fault models are less sensitive to slip features smaller than 64 km. When we use the models to compute synthetic seafloor deformation, we observe strong variations in the synthetics, suggesting their sensitivity to small‐scale slip features. Our newly developed approach offers a quantitative framework to identify common features in distinct finite‐fault slip models and to analyze their robustness using regional and global geophysical observations for megathrust earthquakes. Our results indicate that dense offshore instrumentation is critical for resolving the rupture complexities of megathrust earthquakes.