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SUMMARY We explore the potential of utilizing distributed acoustic sensing (DAS) for back-projection (BP) to image earthquake rupture processes. Synthetic tests indicate that sensor geometry, azimuthal coverage and velocity model are key factors controlling the quality of DAS-based BP images. We show that mitigation strategies and data processing modifications effectively stabilize the BP image in less optimal scenarios, such as asymmetric geometry, narrow azimuthal coverage and poorly constrained velocity structures. We apply our method to the $$M_w7.6$$ 2022 Michoacán earthquake recorded by a DAS array in Mexico City. We also conduct a BP analysis with teleseismic data for a reference. We identify three subevents from the DAS-based BP image, which exhibit a consistent rupture direction with the teleseismic results despite minor differences caused by uncertainties of BP with DAS data. We analyse the sources of the associated uncertainties and propose a transferable analysis scheme to understand the feasibility of BP with known source–receiver geometries preliminarily. Our findings demonstrate that integrating DAS recordings into BP can help with earthquake rupture process imaging for a broad magnitude range at regional distances. It can enhance seismic hazard assessment, especially in regions with limited conventional seismic coverage. 

ABSTRACT Microearthquakes can be dynamically triggered in southern California by remote earthquakes. However, directly connecting dynamic triggering mechanisms with observational data remains challenging. One proposed failure mechanism suggests that both the amplitude and duration of cyclic fatigue caused by the passing seismic wave contribute to triggering occurrence. Here, we measure dynamic strains recorded by borehole strainmeters in the Anza section of the San Jacinto fault zone from 710 earthquakes that occurred over 300 km away between 2008 and 2017 to systematically investigate the role of elevated and sustained strain in controlling dynamic triggering. We design a suite of tests to evaluate whether specific amplitude thresholds and durations of strain can predict dynamic triggering cases. We further test whether the peak dynamic strain (PDS) can predict triggering occurrence in combination with the strain amplitude and duration. Based on these tests, there is no strain amplitude–duration threshold that can distinguish triggering occurrence in Anza. Dynamic triggering is more likely to occur if a remote earthquake causes a PDS above 100 nanostrain, though many cases were triggered at smaller PDSs. The lack of clear correlation between triggering and characteristics of the dynamic strain field suggests that the tested features of the incoming waves do not determine triggering occurrence and local fault conditions and slip processes are more important in controlling dynamic triggering in Anza. 

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. 

Abstract Dynamic earthquake triggering is commonly identified through the temporal correlation between increased seismicity rates and global earthquakes that are possible triggering events. However, correlation does not imply causation. False positives may occur when unrelated seismicity rate changes coincidently occur at around the time of candidate triggers. We investigate the expected false positive rate in Southern California with globalM ≥ 6 earthquakes as candidate triggers. We compute the false positive rate by applying the statistical tests used by DeSalvio and Fan (2023),https://doi.org/10.1029/2023jb026487to synthetic earthquake catalogs with no real dynamic triggering. We find a false positive rate of ∼3.5%–8.5% when realistic earthquake clustering is present, consistent with the 95% confidence typically used in seismology. However, when this false positive rate is applied to the tens of thousands of spatial‐temporal windows in Southern California tested in DeSalvio and Fan (2023),https://doi.org/10.1029/2023jb026487, thousands of false positives are expected. The expected false positive occurrence is large enough to explain the observed apparent triggering following 70% of large global earthquakes (DeSalvio & Fan, 2023,https://doi.org/10.1029/2023jb026487), without requiring any true dynamic triggering. Aside from the known triggering from the nearby El Mayor‐Cucapah, Mexico, earthquake, the spatial and temporal characteristics of the reported triggering are indistinguishable from random false positives. This implies that best practice for dynamic triggering studies that depend on temporal correlation is to estimate the false positive rate and investigate whether the observed apparent triggering is distinguishable from the correlations that may occur by chance. 

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. 

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. 

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 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. 

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.