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Jeffrey J. McGuire

Publications and source records attributed to Jeffrey J. McGuire.

7 recordsLinked to original sources

USGS2026

Rapid earthquake magnitude classification via P-wave strains from borehole strainmeters and Distributed Acoustic Sensing

Distributed Acoustic Sensing (DAS) offers a promising approach for earthquake early warning (EEW) in settings where seismic networks are costly to maintain. By repurposing fiber-optic cables as dense strainmeter arrays, DAS enables real-time earthquake detection wherever those fibers are accessible. However, poor azimuthal coverage and challenges in estimating magnitude from strain measurements remain key hurdles in applying for earthquake monitoring. Here, we develop a machine learning method to distinguish large (M≥5.4) earthquakes from smaller ones within the first 4 seconds of a strain waveform after a P-wave arrival without determining location. Using ensemble decision tree models trained on borehole strainmeter data (3.5≤M≤7.1) and tested on onshore DAS waveforms (including the 2024 M7 Offshore Cape Mendocino earthquake), we find that low-frequency (0.2–0.5 Hz) continuous wavelet transform coefficients are the strongest predictors of magnitude, in addition to strain amplitude. Both DAS and borehole strainmeters effectively capture long-period strain signals, making these findings valuable for EEW systems. Our method shows high precision compared to the real-time EEW system, ShakeAlert®, supporting the position that DAS is a viable technology for earthquake monitoring and magnitude classification.

California↗

USGS2026

Predictable seismic cycles result from structural rupture barriers on oceanic transform faults

Earthquakes of magnitude ( M ) >5.5 on oceanic transform faults (OTFs) repeatedly rupture the same locked patches, sometimes quasiperiodically. These patches are separated by “barriers” that halt earthquake propagation and slip mostly aseismically. However, the physical processes governing this systematic behavior remain unclear. We analyzed two barriers along the Gofar transform fault that have arrested ~15 M 6 earthquakes over the past three decades. Ocean bottom seismometer data indicate that the barriers hosted intense microseismicity before the mainshocks and comprise multistrand faults and transtensional stepovers with 100- to 400-m lateral offset. These characteristics contradict earthquake rupture termination models invoking velocity-strengthening friction or large geometric steps and instead point to damage-enhanced porosity and dilatancy-strengthening mechanisms. By isolating rupture segments, the barriers regulate the quasiperiodic recurrence of OTF earthquakes.

Science↗

USGS2026

ShakeAlert Earthquake Early Warning System performance during the Mw 7.0 offshore Cape Mendocino earthquake

The 5 December 2024 M w 7.0 Offshore Cape Mendocino earthquake was a challenging test of the U.S. West Coast ShakeAlert earthquake early warning system due to its offshore epicenter and limited near‐source station coverage. We analyzed real‐time performance of all components of the ShakeAlert system, including the seismic algorithms (earthquake point‐source integrated code [EPIC] and Finite‐fault rupture Detector [FinDer]), the geodetic algorithm (Geodetic First Approximation of Size and Time–peak ground displacement [GFAST‐PGD]), and network telemetry during the event. EPIC created the first solution for this earthquake 15 s after origin time with an initial magnitude estimate of M 5.6 and location error of 10 km from the Advanced National Seismic System epicenter. An early spurious trigger from station CE.89101 fortuitously maintained location accuracy and, correspondingly, magnitude accuracy. FinDer contributed its first solution at 18 s with a location estimate closer to the seismic network and produced two distinct rupture geometries, leading to minor fluctuations in estimated intensity contours. GFAST‐PGD did not meet alerting thresholds but otherwise performed as expected. Network latencies were <2 s for most stations, supporting the rapid detection of this earthquake by the system. Roughly five million alerts were delivered to cell phone devices in California and Oregon during this event. This was also the first instance of a school district‐wide ShakeAlert‐powered system being activated. Comparisons to recorded seismograms demonstrate that the maximum warning times before potentially damaging shaking (intensity 6+) were in the range of 5–55 s. Although the ShakeAlert system provided accurate solutions and useful alert delivery, this earthquake raised awareness of potential issues within the system, including the need for improved offshore location estimates, a combination of solutions from ShakeAlert servers, and handling of spurious triggers.

California↗

USGS2025

3D Converted wave reverse time migration imaging

We describe a newly developed method for recovering high-resolution images of seismic discontinuities, such as subducting slabs, in 3D. Our method makes use of converted S → P or P → S waves observed by dense arrays of seismometers to infer the locations and relative strengths of seismic discontinuities at depth in a target region. Observed direct and converted waves are backpropagated to their times of origin. The time-reversed wavefield is then separated into its constituent P and S components via the Helmholtz decomposition, and those separated wavefields are used to compute imaging functions that characterize the locations and relative strengths of seismic discontinuities. Imaging functions may be designed to use either S → P or P → S waves, so that users can target those arrivals expected to be most dominant in a given dataset. We have previously demonstrated the efficacy of our method in two dimensions, and we now present a 3D implementation of our technique which addresses the significant computational challenges posed by the size of volumetric wavefield data in three dimensions. Through a series of synthetic examples, we demonstrate that our method is capable of recovering the fine scale structure of a subducting slab given realistic station coverage and earthquake sources. We investigate optimal seismic station geometries for our technique and explore image interpretability in regions with poor data coverage. We find that linear station geometries yield more optimal, interpretable imaging functions than collections of small arrays can. We also show that our method can successfully recover bothS → P or P → S images when realistic shear earthquake sources are used, and we explore the additional computational challenges presented by the high frequency content of S waves. Our results demonstrate the potential for our technique to recover high-resolution information about subducting slabs in real-world regions, given that relatively sparse seismic arrays with only approximately 100 stations are capable of recovering interpretable imaging functions from just a few realistic earthquake sources for multiple discontinuities at significant depth in an area of approximately 400~sq~km.

Seismica↗

USGS2025

Fiber-optic sensing for earthquake hazards research, monitoring and early warning

The use of fiber‐optic sensing systems in seismology has exploded in the past decade. Despite an ever‐growing library of ground‐breaking studies, questions remain about the potential of fiber‐optic sensing technologies as tools for advancing if not revolutionizing earthquake‐hazards‐related research, monitoring, and early warning systems. A working group convened to explore these topics; we comprehensively examined the application of fiber optics in various aspects of earthquake hazards, encompassing earthquake source processes, crustal imaging, data archiving, and technological challenges. There is great potential for fiber‐optic systems to advance earthquake monitoring and understanding, but to fully unlock their capabilities requires continued progress in key areas of research and development, including instrument testing and validation, increased dynamic range for applications focused on larger earthquakes, and continued improvement in subsurface and source imaging methods. A key current stumbling block results from the lack of clear data archiving requirements, and we propose an initial strategy that balances data volume requirements with preserving key data for a broad range of future studies. In addition, we demonstrate the potential for fiber‐optic sensing to impact monitoring efforts by documenting the data completeness in a number of long‐term experiments. Finally, we outline the features of a instrument testing facility that would enable progress toward reliable and standardized distributed acoustic sensing data. Overcoming these current obstacles would facilitate progress in fiber‐optic sensing and unlock its potential application to a broad range of earthquake hazard problems.

California, Oregon, Washington↗

USGS2025

Earthquake magnitude and source parameter estimation with a distributed acoustic sensing dataset in the Gorda subduction zone

Distributed acoustic sensing (DAS) systems offer a cost‐effective way to create large‐scale strainmeter arrays for seismological applications using fiber‐optic cables. DAS‐based strain measurements are known to be influenced by various factors, bringing into question their general reliability for accurate earthquake characterization. A 15‐km‐long DAS deployment in northern California was operational within 3 days of the 2022 M w 6.4 Ferndale earthquake and ran continuously throughout the aftershock sequence. We utilize these aftershock data to validate DAS‐based strain measurements in two ways. We first test the accuracy of DAS‐based magnitude estimates from peak dynamic strains by comparing them with magnitude and attenuation scaling relations derived independently from traditional borehole strainmeter (BSM) data. We demonstrate that DAS‐based magnitudes are comparable to BSM‐based magnitudes when corrections for variations in site response along the fiber‐optic cable are properly made. Magnitude errors are spatially correlated, potentially because of factors such as finite‐fault effects (e.g., stress drop) or more complex, unmodeled path attenuation or because of wave propagation effects in heterogeneous media. We then apply more advanced source characterization methodology to the DAS data using a time‐domain empirical Green’s function (EGF) deconvolution approach to measure details of the moment rate history. The EGF approach using DAS data depends on careful treatment of distorting factors such as anthropogenic sources of noise and optical phase wrapping but successfully isolates source spectra for moderate‐magnitude earthquakes: source spectral ratios obtained from DAS data, broadband seismometer data, and BSM data in the same region show consistent results, revealing differences in directivity and spectral shape among earthquakes. Although further research is needed to refine source‐time‐function estimation techniques for DAS data, particularly for larger magnitude events, these case studies demonstrate the clear potential of DAS for earthquake source characterization.

California↗

USGS2025

Fiber-imaged supershear dynamics in the 2024 Mw 7 Mendocino Fault earthquake

Fault structure and rupture physics are deeply intertwined, and observations of this coupling are critical for understanding earthquake behavior. Rupture propagation is observable at fine scales using dense seismic networks. Fiber-optic sensing allows for long-term deployments of ultradense arrays that enable high-resolution measurements of infrequent, large earthquakes. We recorded the 2024 moment magnitude ( M w ) 7 Mendocino Fault earthquake with a nearby fiber-optic array and imaged its behavior with seismic beamforming. The rupture propagated to the east at subshear velocity; stagnated near the Mendocino Triple Junction, a zone of structural complexity; and subsequently transitioned to supershear velocity. The correlation between source physics and structure shows how lithospheric heterogeneity affects first-order characteristics of earthquake ruptures. Our results also demonstrate the potential for fiber-optic sensing to improve real-time estimation of key parameters for early warning.

California↗