Clara E. Yoon

Macroseismic data are a key resource to investigate shaking and damage from preinstrumental and early instrumental eras. However, data are often stored as inconsistently formatted reports describing observed shaking and damage, making manually parsing and interpreting accounts labor-intensive. We introduce a novel workflow using Google’s Gemini 2.5 Pro large language model (LLM) to automate the extraction and structuring of macroseismic observations from summary reports. We apply this workflow to the 22 March 1957 M 5.3 Daly City, California, earthquake as a case study. We used Gemini to extract addresses, originally assigned modified Mercalli intensity values, and descriptions from each report. To address coordinate precision limits, addresses were geocoded via Google’s Geocoding application programming interface. This workflow yielded over 2300 geocoded intensity reports for the Daly City earthquake. We use the geocoded accounts, with the original report intensity assignments, to develop a shaking intensity map that in some respects rivals modern Did You Feel It? Maps. We also extract and present data for the 9 February 1971 ML 6.7 Sylmar, California, earthquake. Our results demonstrate the potential of LLMs for reliably extracting and analyzing large, unstructured macroseismic datasets. LLMs offer a scalable solution for rapidly digitizing macroseismic archives, enabling their broader use to constrain ground-motion models in modern seismic hazard analysis and to improve our understanding of site effects in urban areas. The concepts explored here may also be applied to the handling of other legacy seismological and earth science data.

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 DAS to earthquake monitoring. Here, we develop a machine learning method to distinguish moderate-to-large (defined here as M ≥ 5.4) earthquakes from smaller ones within the first 4 sec of a strain waveform after a P-wave arrival without determining the earthquake 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 results 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. Fiber optic cables plus machine learning could aid earthquake early warning by estimating earthquake size within the first few seconds of shaking.

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.

Analysis of 2 weeks of continuous post‐seismic shaking after the 2019 M7.1 Ridgecrest, CA earthquake sequence using 4 nearby borehole seismometers reveals that continuous ground motions decay as Omori's law in time and follow the Gutenberg‐Richter distribution in logarithmic amplitude. The measured temporal decay in amplitudes agrees with predictions of the rate‐and‐state framework and indicates shaking amplitudes are proportional to the velocity of afterslip. Our ground motion‐based statistical framework provides a basis to forecast shaking intensity in the minutes to hours after a large earthquake.

The Mw7.0 December 5, 2024 Offshore Cape Mendocino earthquake ruptured a km long portion of the east‐west trending Mendocino fault zone (MFZ). In order to clarify the rupture process, we assemble three‐component seismograms from regional seismic stations, horizontal coseismic displacement vectors derived from Global Navigation Satellite System (GNSS) time series, and a Sentinel‐1 ascending interferogram. These data are interpreted with a model of slip distributed on two vertical fault planes representative of the eastern MFZ and spanning the km length of the aftershock zone. Assuming right‐lateral strike slip, we find that the rupture initiates in the oceanic mantle at km depth and proceeds unilaterally updip and toward the east. Early aftershocks locate adjacent to the peak slip areas, tracking the coseismic rupture propagation from oceanic mantle to shallower depth and implying a significant role of static stress transfer in driving aftershocks in an ocean plate environment.

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.

The southernmost portion of the Cascadia subduction zone in northern California produces high rates of moderate and large earthquakes owing to subduction of the Gorda slab and the deformation associated with the Mendocino Triple Junction. Distributed acoustic sensing (DAS) is rapidly advancing as a method for detecting earthquakes and imaging crustal structure. We have begun a long-term DAS monitoring experiment on buried telecom fiber in Arcata, California, to increase the available recordings of moderate-to-large earthquakes as well as image seismogenic structures. We have recorded over a year’s worth of data, including most aftershocks of the 2022 Mw 6.4 Ferndale earthquake, though not the mainshock itself. The dataset includes numerous magnitude 3.5 and larger earthquakes, including the 1 January 2023 Mw 5.4 Rio Dell earthquake. Here we present initial results comparing an earthquake detection algorithm, run in real time on the processing unit of the interrogator system, with both the ShakeAlert® earthquake early warning system and a postprocessed earthquake catalog developed with deep-learning phase-picker algorithms. The rapid onboard processing of the detector demonstrates the potential utility of DAS-based edge computing for earthquake early warning. We also verify the quality of the strain waveforms both in terms of peak amplitudes and waveform similarity using about five months of nodal seismometer data. These instruments were deployed roughly every 300 m along the ∼15-km-long cable and validate large variations in peak strain over short distances that are seen in the DAS data. All data from time windows surrounding both the local and teleseismic earthquakes are publicly available, which will improve our understanding of both the performance of DAS systems in moderate earthquakes and earthquake hazards associated with the Gorda subduction zone.

From July to October 2022, a noneruptive volcanic earthquake swarm occurred within ∼15 km of Ta‘ū Island, located in eastern American Samoa. Felt reports from residents were the only available information about the swarm when it started, as American Samoa lacked a seismic monitoring network. We developed a consistent single-station catalog for the entire swarm, using seismic data from the nearest station IU.AFI, ∼250 km away. We applied the EQTransformer deep-learning model (Mousavi et al., 2020), automatically picking Pn and Sn arrivals on IU.AFI continuous data. We retained only events with Sn–Pn times of 22.5–25 s, consistent with the expected locations based on felt reports, then detected smaller swarm events with subsequent template-matching. This single-station catalog characterized the swarm’s onset and escalation to peak activity before a multiagency field response team installed a local seismic network in mid-August 2022. This permanent seismic network captured the swarm’s decline. EQTransformer identified short S–P times on the first two locally deployed seismometers, both Raspberry Shake sensors, to constrain the swarm’s distance from Ta‘ū Island. Modern seismological processing methods, combined with basic observations such as felt reports, can quickly contribute useful information during an earthquake response in a poorly monitored region.

On 5 April 2024, 10:23 a.m. local time, a moment magnitude 4.8 earthquake struck Tewksbury Township, New Jersey, about 65 km west of New York City. Millions of people from Virginia to Maine and beyond felt the ground shaking, resulting in the largest number (>180,000) of U.S. Geological Survey (USGS) “Did You Feel It?” reports of any earthquake. A team deployed by the Geotechnical Extreme Events Reconnaissance Association and the National Institute of Standards and Technology documented structural and nonstructural damage, including substantial damage to a historic masonry building in Lebanon, New Jersey. The USGS National Earthquake Information Center reported a focal depth of about 5 km, consistent with a lack of signal in Interferometric Synthetic Aperture Radar data. The focal mechanism solution is strike slip with a substantial thrust component. Neither mechanism’s nodal plane is parallel to the primary northeast trend of geologic discontinuities and mapped faults in the region, including the Ramapo fault. However, many of the relocated aftershocks, for which locations were augmented by temporary seismic deployments, form a cluster that parallels the general northeast trend of the faults. The aftershocks lie near the Tewksbury fault, north of the Ramapo fault.

The 17 January 1994 Northridge, California, earthquake was a watershed event with far-reaching societal and scientific impacts. The earthquake, which occurred in the early days of both broadband seismic networks and the Internet, spurred advances in seismic monitoring, real-time systems, and development of data products. Motivated by the 30th anniversary of the earthquake, we present a brief retrospective of the earthquake and its impact, and reconsider both ground motions and the aftershock distribution using modern tools and the best-available data. With improvements in instrumentation and analysis methodology, recent earthquakes continue to reveal the increasing complexity of ground motions, fault systems, and earthquake ruptures. Even in the absence of data from state-of-the-art instrumentation, a retrospective consideration of ground-motion data from the Northridge earthquake reveals complexities beyond what could be characterized (and modeled) 30 yr ago. Aftershock relocations for both the 1971 Sylmar and 1994 Northridge earthquakes also reveal an updated view of fault complexity. Our study does provide a cautionary tale regarding legacy data sets and research results that are not easily accessible, which can result in discrepancies between catalog data and products from the best available science. We also briefly describe outreach products produced as a part of the anniversary commemoration.