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Abstract Earthquake doublets—nearby events of similar size striking within a short period—have been a seismological puzzle for 50 years. Is the second event simply an unusually large aftershock, or do doublets arise from a distinct mechanism? If all subduction zones exhibit the same percentage of doublets, that would support the first view. But if some trenches generate many more than others, that would support the second. Here we find that while all doublets undergo Omori-type aftershock decay, the Solomon-Vanuatu subduction zone produces half the world’s doublets, ten times more than the other trench. We argue that this results from abundant near-vertical tear faults in its slab and forearc, with stress transfer more efficient between the subduction interface and adjacent tear faults than along the interface. Tear faults also segment the megathrust interface, hampering propagation of great earthquakes and so confining ruptures, resulting in a low M ≥ 8 quake rate. Thus, while doublets occur along all trenches, their abundance is mediated by tear faults. 

ABSTRACT Dynamic triggering occurs when seismic waves from distant large earthquakes temporarily alter stress conditions along faults, potentially triggering new earthquakes hundreds to thousands of kilometers away from the source. Previous studies have linked triggered seismicity to anthropogenic activities such as geothermal, oil, and gas production. Although these activities are present in Nevada, little work has been conducted to explore dynamically triggered seismicity in Nevada. Here, we analyze a newly published, high-resolution earthquake catalog for Nevada to identify local seismicity dynamically triggered by teleseismic events (Mw≥7) from 2008 to 2023. We identify 94 dynamically triggered earthquakes concentrated in four distinct regions, which qualitatively show a modest positive correlation with geothermal well locations. Triggered seismicity in Nevada is predominantly delayed, with some instantaneously triggered by Rayleigh waves. The prevalence of delayed triggering indicates that pore fluid interactions may play a critical role in controlling dynamic triggering susceptibility in Nevada. Our results demonstrate that dynamic triggering can provide valuable insight to help identify critically stressed regions. 

SUMMARY The Mendocino Triple Junction (MTJ), where the Gorda, North American and Pacific plates meet, is one of the most seismically active regions in California. The tectonic movements along the Mendocino transform fault zone (MTFZ), Gorda slab (GS) and northern San Andreas Fault systems (NSAF) lead to high background seismicity rates but relatively low aftershock productivity. To improve the understanding of earthquake processes in the area, we analyse relations between background seismicity, aftershock productivity and stress parameters. We apply the nearest-neighbour approach to investigate the spatial distributions and properties of background and clustered seismicity, and invert focal mechanisms of events in Voronoi cells for features of the deviatoric stress field. The results indicate that the intensity of background seismicity and aftershock productivity decrease with distance from the MTJ, defined here for simplicity as the hypocentre of the 1992 Mw 7.2 main shock. We also find that the stress regime is the most compressive in the area directly surrounding the MTJ. In the MTFZ and GS, the compressive stress decreases with increasing distance from the MTJ, correlating with the reduced aftershock productivity and background seismicity. In the NSAF, the observed relations between the stress, aftershock productivity and background seismicity are not clear, possibly due to crustal extension related to the slab window and elevated heat flow. Compared to the MTFZ and GS, the NSAF has a higher foreshock proportion, lower aftershock proportion and small-to-medium main shock magnitudes, indicating more swarm-like clusters in this region. The inverted stress regimes in the MTFZ and NSAF are dominated by strike-slip faulting. The GS exhibits mostly strike-slip and normal mechanisms despite the subduction environment, which may reflect slab bending and reactivation of pre-existing normal faults. 

Abstract Moment magnitude Mw is derived from seismic moment and was defined with the intent to be a consistent measure of earthquake size. Here, we demonstrate that reported Mw values depend systematically on the rigidity structure assumed in the moment tensor inversion, which varies between regions and users. We perform regional moment tensor inversions for 70 target earthquakes in the Walker Lane and southern California regions of the western United States, comparing magnitude results across a suite of commonly used 1D velocity models. Inversions performed with slower, lower rigidity velocity models produce lower Mw estimates than inversions performed with faster, higher rigidity velocity models: the epistemic uncertainty from the choice of velocity model averages ±0.08 for the analyzed earthquakes, with larger uncertainties for shallower events. Using magnitudes based on seismic potency (Mp) instead of Mw can reduce this uncertainty by a factor of 2–3. We introduce a potency-based magnitude Mpv that, by correcting for both the rigidity at source depth and characteristic rigidity of the velocity model, produces a robust magnitude scale that is independent of the velocity model. This formulation can be used to generate uniform and consistent regional and global earthquake catalogs necessary for a wide range of applications in earthquake science and engineering. 

Glacier terminus retreat involves complex processes superimposed at the interface between the ice sheet, the ocean, and the subglacial substrate, posing challenges for accurate physical modeling of terminus change. To enhance our understanding of outlet glacier ablation, numerous studies have focused on investigating terminus position changes on a seasonal scale with no clear control on seasonal terminus change that has been identified across all glaciers. Here, we explore the potential of machine learning to analyze glaciological time series data to gain insight into the seasonal changes of outlet glacier termini. Using XGBoost machine learning models, we forecast seasonal changes in terminus positions for 46 outlet glaciers in Greenland. Through the SHapley Additive exPlanations (SHAP) feature importance analysis, we identify the dominant predictors of seasonal terminus position change for each glacier. We find that glacier geometry is important for accurate predictions of the magnitude of terminus seasonality and that environmental variables (mélange, ocean thermal forcing, runoff, and air temperature) are important for determining the onset of seasonal terminus change. Our work highlights the utility of machine learning in understanding and forecasting glacier behavior. 

Abstract Earthquake focal mechanisms provide crucial information about subsurface fault geometry and stress orientations. Focal mechanisms are typically inferred through analysis of seismic radiation patterns, for example, using P-wave first-motion polarities, potentially in combination with S/P amplitude ratios, to identify nodal planes. The motivation for this procedure is well-founded, as P- and S-wave radiation patterns depend fundamentally on the fault orientation. However, in practice, S/P amplitude ratio measurements can be strongly influenced by factors that are unrelated to the source mechanism. In this study, I characterize several underappreciated issues with S/P amplitude ratio data that are relevant to focal mechanism inversion. The analysis combines synthetic tests with new waveform measurements from ∼64,000 ML≥1.0 earthquakes in Nevada and California. Key findings include that (1) the statistical distribution of S/P amplitude ratio data differs markedly in shape and width from the theoretical expectation, (2) S/P amplitude ratios decay systematically with source-station distance beyond ∼60 km or so, (3) this distance effect is more severe for smaller earthquakes than for larger ones, and (4) modifying the frequency band in which amplitudes are measured can shift the observed amplitude ratio distribution but does not significantly mitigate issues (1)–(3). Taken together, these findings indicate that S/P amplitude ratio measurements are influenced by differential path attenuation and signal-to-noise effects that are not accounted for with existing workflows. Using independent moment tensor solutions, I systematically test various strategies to incorporate S/P amplitude ratios into focal mechanism solutions. The best-performing strategies transform S/P amplitude data to better match the theoretical expectation. Overall, S/P amplitude ratio data appear helpful in improving a typical mechanism solution, but even with the best-performing strategies considered here, the inclusion of S/P amplitude ratio data is expected to hinder rather than improve the solution for a subset of events. 

Abstract The Rock Valley fault zone in southern Nevada has a notable history of seismic activity and is the site of a future direct comparison experiment of explosion and earthquake sources. This study aims to gain insight into regional tectonic processes by leveraging recent advances in seismic monitoring capabilities to elucidate the local stress regime. A crucial step in this investigation is the accurate determination of P-wave first-motion polarities, which play a vital role in resolving earthquake focal mechanisms of small earthquakes. We deploy a deep learning-based method for automatic determination of first-motion polarities to vastly expand the polarity dataset beyond what has been reviewed by human analysts. By the integrating P-wave polarities with new measurements of S/P amplitude ratios, we obtain robust focal mechanism estimates for 1306 earthquakes with a local magnitude of 1 and above occurring between 2010 and 2023 in southern Nevada. We then use the focal mechanism catalog to examine the regional stress orientation, confirming an overall trans-tensional stress regime with smaller scale complexities illuminated by individual earthquake sequences. These findings demonstrate how detailed analyses of small earthquakes can provide fundamental information for understanding earthquake processes in the region and inform future experiments at the Nevada National Security Site. 

The size, frequency, and geographic scope of severe wildfires are expanding across the globe, including in the Western United States. Recently burned steeplands have an increased likelihood of debris flows, which pose hazards to downstream communities. The conditions for postfire debris‐flow initiation are commonly expressed as rainfall intensity‐duration thresholds, which can be estimated given sufficient observational history. However, the spread of wildfire across diverse climates poses a challenge for accurate threshold prediction in areas with limited observations. Studies of mass‐movement processes in unburned areas indicate that thresholds vary with local climate, such that higher rainfall rates are required for initiation in climates characterized by frequent intense rainfall. Here, we use three independent methods to test whether initiation of postfire runoff‐generated debris flows across the Western United States varies similarly with climate. Through the compilation of observed thresholds at various fires, analysis of the spatial density of observed debris flows, and quantification of feature importance at different spatial scales, we show that postfire debris‐flow initiation thresholds vary systematically with short‐duration rainfall‐intensity climatology. The predictive power of climatological data sets that are readily available before a fire occurs offers a much‐needed tool for hazard management in regions that are facing increased wildfire activity, have sparse observational history, and/or have limited resources for field‐based hazard assessment. Furthermore, if the observed variation in thresholds reflects long‐term adjustment of the landscape to local climate, rapid shifts in rainfall intensity related to climate change will likely induce spatially variable shifts in postfire debris‐flow likelihood. 

Abstract On 9 December 2024, at 3:08 p.m. local time, the Mw 5.7 Parker Butte earthquake occurred about 24 km north-northeast of Yerington, Nevada. From 1 December 2024 to 10 May 2025, we cataloged 1301 earthquakes, including seven events ML>3.5. We use high-precision earthquake relocation, Interferometric Synthetic Aperture Radar (InSAR) data, Global Positioning System (GPS) data, and strong-motion data to explore the tectonic context and spatiotemporal evolution of this sequence. The high-precision relocations of the sequence reveal a main cluster of earthquakes that form a planar feature which can be fit with a plane striking N62°E and dipping 85° SE. Events that are not in the main cluster are primarily 5–10 km to the southeast and are more scattered, but some smaller linear clusters can be identified. We used InSAR and GPS data to model fault geometry and slip. From this analysis, we found that the ground deformation can be fit with a single fault 12 km long × 8 km wide with a strike of N61.5°E ± 1.0°, dipping 73° ± 1.5° southeast and slip up to ∼50 cm, concentrated between depths of 2.5 and 7 km, consistent with an Mw 5.7 rupture. However, a better fit is found by adding a second fault plane. The second fault strikes N24.5°W and was detected as a displacement discontinuity in descending InSAR scenes, correlating to minor surface fracturing observed in the field, but had low aftershock activity. The GPS observations of interseismic deformation before the event show similar directions of principal strain accumulation and strain release in the mainshock moment tensor. Ground-motion measurements from the mainshock strong-motion data are generally in agreement with existing active crustal ground-motion models for the western United States. The sequence provided a valuable dataset for examining faulting rupture patterns in the Walker Lane Shear Zone.