Journal of Geophysical Research: Solid Earth最新文献

Providing spatio-temporal constraints on what influences the rheology of deeply subducted continental crust during subduction–exhumation remains elusive but crucial for understanding the exhumation dynamics of ultrahigh pressure (UHP) terranes. Here, we report results of a systematic study of microstructures, crystallographic preferred orientations (CPOs) and seismic properties of four UHP–HP eclogites formed along a common P–T path from Yangkou Bay, Sulu belt, China. The eclogites have different bulk compositions and record heterogeneous strain patterns. Peak metamorphic conditions (800°C–900°C and >5.5 GPa) were retrieved from early F1 isoclinal fold hinges. Subsequent overprinting by F2 tight folds occurred during the transition to quartz-eclogite facies. Localized shear zones exhibit amphibolite-facies retrogression, indicative of enhanced fluid activity. Omphacite exhibits crystal plasticity, while garnet displays a brittle–plastic transition during exhumation. A change from S- to L-type CPO in omphacite was controlled by folding geometry during subduction–exhumation. Strain localization controlled intergranular fluid connectivity and redistribution, correlating with increasing strain from F1 folds to localized shear zones. This process led to progressive dynamic recrystallization, and changes in deformation mechanisms and seismic properties. Dynamic recrystallization resulted in significant grain refinement, thereby triggering diffusion creep assisted grain boundary sliding in the presence of fluid. Seismic anisotropy is linked to the omphacite fabric and the presence of phengite, with modal phengite as the primary determinant in UHP–HP eclogites. Fluid migration controlled by strain localization led to heterogeneous weakening of eclogite, which enabled exhumation of tectonic slices of UHP crustal rocks from mantle depths.

The cause of unrest at large quaternary silicic calderas, specifically whether the source is magmatic or hydrothermal, has critical implications for the potential eruptive hazard and is debated, even at well-studied systems. Recent advances in Interferometric Synthetic Aperture Radar (InSAR), driven by the Sentinel-1 mission, allow us to examine the spatial and temporal patterns of deformation in unprecedented detail. Here, we apply spatial Independent Component Analysis (sICA) to separate the contribution of magmatic and hydrothermal processes to deformation based on their distinct spatial and temporal characteristics. We use Corbetti Caldera, Ethiopia as an example. The hydrothermal system here is known to be laterally bound by a major rift-perpendicular structure, which means deformation associated with the hydrothermal system has a distinctly different spatial pattern to that of the underlying magmatic source. The sICA is able to separate two spatially distinct deformation signals associated with (a) the shallow magmatic system with constant uplift at a rate of $��\sim �$5.1 cm/yr in the satellite line-of-sight and (b) a laterally bound hydrothermal system that includes a strong seasonal signal with a magnitude of 0.65 cm. Although a magmatic source modeled using a Mogi point source fits the original data well, a two-source inversion improves the model quality. As debates regarding the source of unrest at silicic systems continue, we demonstrated the potential of new data sets and machine learning techniques to isolate contributions of magmatic and non-magmatic processed to surface deformation when they have distinct spatial and temporal patterns, which can have important implications for interpretation and consequently hazard forecasts.

Little is known about the local plumbing systems that fuel Yellowstone's famous hot springs, geysers and mud pots. A multi-method, multi-scale geophysical investigation was carried out in the Obsidian Pool Thermal Area (OPTA) to: (a) delineate the lateral extent of the hydrothermal area and associated surface features; (b) estimate the dimensions of the upflow zone and identify its main controlling structures; (c) assess fluids circulation pathways from depth to surface. Ground and airborne geophysical data were acquired to connect local and regional scales, from shallow to large depths. Maps of surface electrical resistivity show a strong correlation with hydrothermal features. At intermediate depths, electrical resistivity permits delineating the upper limit of the upflow zone, while Poisson's ratio highlights differences in subsurface fluid content. Combining these results with surface observations and topographic information, we speculate that differential mixing of hydrothermal and fresh water could explain the wide diversity of features observed at OPTA. Low electrical resistivity observed at large depths also suggest that a vast upflow zone, controlled by rhyolite flows and conjugate faults, underlies the OPTA. We speculate that hydrothermal fluids rise along fractures and reach the surface in topographic lows to form hydrothermal features. Our results show that synoptic, multi-scale geophysical measurements provide a roadmap for understanding where and how geologic heterogeneity, topography, fluid-gas separation, and the mixing of thermal and meteoric waters conspire to produce the wide variety of Yellowstone's renowned hydrothermal features.

Delineating fault structures through microseismicity is crucial for earthquake hazard assessment, yet constructing high-resolution catalogs over extended periods remains challenging. This study introduces AI-PAL, a novel deep learning-driven workflow that employs a Self-Attention RNN (SAR) model trained with detections from PAL, an established rule-based algorithm (Zhou, Yue, et al., 2021, https://doi.org/10.1785/0220210111), for generalized earthquake detection. PAL utilizes short-term-average over long-term-average algorithm for event detection, ensuring consistent performance across different datasets. AI-PAL leverages these rule-based picks as training labels, enabling self-supervised learning of the SAR model across arbitrary regions, thereby enhancing PAL's detection capabilities. We applied SAR-PAL to two distinct regions that are featured by recent large earthquakes: (a) the preseismic period of the Ridgecrest-Coso region (2008–2019), and (b) the pre-to-postseismic period of the East Anatolian Fault Zone (EAFZ, 2020–2023/04). Our results demonstrate that SAR-PAL offers slightly higher detection completeness than the quake template matching matched filter catalog, while boosts over 100 times faster processing and a superior temporal stability, avoiding detection gaps during background periods. Compared to PhaseNet and GaMMA, two widely recognized phase picker and associator, SAR-PAL proved more scalable, achieving ∼2.5 times more event detections in the EAFZ case, along with a ∼7 times higher phase association rate. We further experimented training PhaseNet and SAR with PAL detections and routine catalogs, and found that no other combinations matched the detection performance of SAR-PAL. The enhanced catalogs built by SAR-PAL reveals geometrical complexities of the Ridgecrest faults and the Erkenek-Pütürge segment of EAFZ, offering insights into their contrasting roles during the large earthquake.

Broadband seismometers are sensitive to tilt as a consequence of their design. We used broadband data from Erebus volcano on Ross Island, Antarctica, and Augustine volcano in Lower Cook Inlet, Alaska, to make tilt measurements associated with individual volcanic explosions and investigate the near-terminal magmatic system configuration of each volcano. At Erebus volcano we found no evidence of tilt associated with the classic Strombolian eruptions from the lava lake. Tilt has been observed preceding Strombolian eruptions at volcanoes. The lack of tilt at Erebus is evidence that its conduit system lacks sufficient viscous plugging or mechanical restrictions to generate slug-transport or explosion-related forces large enough to produce measurable tilt. At Augustine volcano we measured tilt changes associated with 13 events during the explosive phase of its 2006 eruption. We used the tilt changes to invert for a dual deformation source model of a depressurizing open conduit above a depressurizing prolate spheroid. This deflation source geometry is in agreement with an existing magmatic system model developed from petrologic, seismic, and Global Positioning System data. This further supports this model while highlighting the capabilities of seismometer ground tilt measurements as independent model constraints.

Distributed Acoustic Sensing (DAS) is an emerging technology that converts optical fibers into dense arrays of strainmeters, significantly enhancing our understanding of earthquake physics and Earth's structure. While most past DAS studies have focused primarily on seismic wave phase information, accurate measurements of true ground motion amplitudes are crucial for comprehensive future analyses. However, amplitudes in DAS recordings, especially for pre-existing telecommunication cables with uncertain fiber-ground coupling, have not been fully quantified. By calibrating three DAS arrays with co-located seismometers, we systematically evaluate DAS amplitudes. Our results indicate that the average DAS amplitude of earthquake signals closely matches that of co-located seismometer data across frequencies from 0.01 to 10 Hz. The noise floor of DAS is comparable to that of strong-motion stations but higher than that of broadband stations. The saturation amplitude of DAS is adjustable by modifying the pulse repetition rate and gauge length. We also demonstrate how our findings enhance the understanding of fiber-optic seismology and its implications for natural hazard mitigation and Earth structure imaging and monitoring. Specifically, our results suggest that with proper settings, DAS can detect P-waves from an M6+ earthquake occurring 10 km from the cable without saturation, indicating its viability for earthquake early warning. Through quantitative comparison and analysis, we also find that local ambient traffic noise levels strongly affect the quality of seismic interferometry measurement, which is a powerful tool for near-surface imaging and monitoring. Our methodology and findings are valuable for future DAS experiments that require precise seismic amplitude measurements.

Shear localization within the fault core, as evidenced by grain comminution in fault gouge, plays a crucial role in the initiation of frictional instabilities. To upscale the physics of shear localization and understand the influence of grain size, it is essential to identify the governing physical parameters and micro-mechanisms. In this study, we conducted double-direct shear experiments on quartz fault gouges with varying initial grain sizes (coarse, small, and bi-disperse mixtures) under constant normal stress and shearing velocity, while continuously monitoring Acoustic Emissions (AE). Microstructural analyses were performed on the deformed samples to complement the mechanical and AE data. Our results reveal that, while the initial grain size and distribution do not substantially alter the steady-state friction coefficient, they significantly influence the early stages of frictional evolution leading to a steady state, which is reflected in a different rate and amplitude of AEs. Specifically, coarse grains and bi-disperse mixtures exhibit strain-hardening behavior before reaching steady-state friction, whereas fine grains show strain-weakening behavior. Microstructural observations further indicate that bi-disperse mixtures retard the localization of deformation with increasing fault displacement. The AE data shows a strong dependence on both the average grain size and the evolving state of the gouge layer. Notably, there is a direct correlation between b-value evolution and the average grain size within the gouge. These findings suggest that variations in the characteristics of AE are indicative of distinct micro-mechanisms active during different stages of shear localization, which cannot be fully captured by mechanical data and microstructural analysis alone.

The entire editorial board of the Journal of Geophysical Research-Solid Earth would like to sincerely thank all our colleagues who reviewed manuscripts for us in 2024. The hours they spent reading in order to provide insightful comments on manuscripts not only help improve the quality of these manuscripts but also ensure the scientific rigor of our reviewing process and eventually, of the research published in the field of Solid Earth Geophysics by our journal. With the advent of open science and AGU's data policy, the reviewing process now also encompasses checking the accessibility and availability of data and developed software. This is a key objective of AGU's FAIR (Findable, Accessible, Interoperable and Reusable) (FAIR) policy, for which many reviewers have provided suggestions that helped to improve the data presentation and availability, and which also fed the editorial board's reflection on the matter. Of course, we particularly appreciate timely reviews, particularly in light of the growing demands imposed by the increase of manuscripts submitted to Journal of Geophysical Research-Solid Earth. We received 1,999 submissions in 2024, and 1,628 reviewers contributed to their evaluation by providing 2,534 reviews in total. We are deeply thankful for all of their contributions.

With the advancement of dense seismic arrays, array-processing methods for ambient noise data have become highly effective in extracting high-quality broadband surface wave dispersion curves from ambient noise. Recent advancements in array data processing methods have enabled the extraction of multimode dispersion curves, offering improved constraints on deep Earth structures. However, these array-based methods often produce regionalized dispersion curves, and conventional phase velocity maps constructed by interpolating these dispersion curves typically have limited resolution, and display smooth images of phase velocities. In this study, we develop an array tomography method aimed at improving the resolution of ambient noise tomography by utilizing dispersion curves extracted through array-based data processing. To demonstrate the effectiveness of our method in enhancing tomography resolution, we construct fundamental-mode 2-D Rayleigh wave phase velocity maps by applying our approach to regionalized dispersion curves obtained from array-based methods in the western United States. By comparing our tomographic results with those from conventional array-based methods, we show that our method can produce more accurate and higher-resolution phase velocity maps. Additionally, our approach is versatile and can be applied to construct high-resolution 1-D and 2-D velocity structures using regionalized phase velocities obtained from various other array-based data processing methods.