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USGS2021

The 6 May 1947 Milwaukee, Wisconsin, earthquake

The State of Wisconsin is not known for earthquake activity. The authoritative public‐facing U.S. Geological Survey Comprehensive Catalog of earthquakes includes only three small (magnitude < 2) earthquakes in the state, all instrumentally recorded. Although other catalogs include more events in Wisconsin, experience has shown that many types of events, such as explosions and cryoseisms, have made their way into earthquake catalogs in this region. In this short report, I summarize available information about an earthquake that was felt in eastern Wisconsin at 15:27 local time on 6 May 1947. As what appears to be the largest historical earthquake in the State of Wisconsin, it is of public interest, its modest size notwithstanding. It appears that no useful instrumental records exist, due in part to a teleseismic event that occurred approximately 3 min later, generating surface waves that were recorded on early long‐period instruments in the region. Instrumental data may exist for this event but have not been found. Comparing the felt area with information from recent earthquakes in the region, I estimate an intensity magnitude of 3.8 for the event, with a subjectively estimated uncertainty range 3.5–4.1. Relatively strong effects, including reports of broken dishes in Milwaukee, and shaking described as short but especially sharp, suggest that the event may have been among the sprinkling of shallow earthquakes now known to occur in the upper Great Lakes region.

Wisconsin↗
USGS2021

SSA task force on diversity, equity, and inclusion: Toward a changing, inclusive future in earthquake science

In the United States, a wide variety of studies show that the geoscience community does not reflect the broader societal makeup (e.g., Velasco and Jaurrieta de Velasco, 2010; Dutt, 2020; Howley, 2020). In fact, only about 10% of all Science, Technology, Engineering, and Mathematics (STEM) Ph.D. degrees are awarded to people of color, although they represent more than a third of the population (Dutt, 2020). These numbers have changed little over the past 40 yr (e.g., Bernard and Cooperdock, 2018; Dutt, 2020). Recent events in the United States have again raised awareness of this discrepancy in many fields; similar divergences may be present throughout the world. This discrepancy represents a tremendous loss of talent and contributes to ongoing bias and racism. As the premier international seismological professional society, Seismological Society of America (SSA) is committed, as stated in its ethics policy, to “freedom and transparency in research and education, which should be conducted in a supportive, inclusive, and respectful environment, free from any discrimination, harassment or bullying.” SSA convened the SSA Diversity, Equity, and Inclusion (DEI) Task Force to identify specific and actionable recommendations that the Society can take to start to address the significant issues surrounding the systematic underrepresentation in seismology and related geosciences by marginalized groups on both short- and long- term time horizons. This report, written by the Task Force, outlines actionable items that SSA can undertake as well as a framework by which progress can be measured to help guide the Society and its members forward as a community to make earthquake science more just, equitable, diverse, and inclusive. We recognize that this document cannot address the multiple individual, cultural, and historical barriers that some members may face (e.g., Núñez et al., 2020), nor can it reflect all possibilities or all recommended practices (e.g., Ali et al., 2021). What this document does represent, however, is the beginning of what we hope to be a significant cultural change in how we conduct earthquake science as an organization, not the end of this process as the Task Force fulfills its charter. As a note, some of the recommendations that the Task Force has outlined here have already been implemented within SSA or are actively being considered. For completeness, we still include them here because this highlights the commitment to change that SSA leadership has embraced.

Seismological Research Letters↗
USGS2021

Modeling seismic network detection thresholds using production picking algorithms

Estimating the detection threshold of a seismic network (the minimum magnitude earthquake that can be reliably located) is a critical part of network design and can drive network maintenance efforts. The ability of a station to detect an earthquake is often estimated by assuming the spectral amplitude for an earthquake of a given size, assuming an attenuation relationship, and comparing the predicted amplitude with the average station background noise level. This approach has significant uncertainty because of unknown regional attenuation and complications in computing small event power spectra, and it fails to account for the specific capabilities of the automatic seismic phase picker used in monitoring. We develop a data‐driven approach to determine network detection thresholds using a multiband phase picking algorithm that is currently in use at the U.S. Geological Survey National Earthquake Information Center. We apply this picking algorithm to cataloged earthquakes to determine an empirical relationship of the observability of earthquakes as a function of magnitude and distance. Using this relationship, we produce maps of detection threshold using station spatial configuration and station noise levels. We show that quiet, well‐sited stations significantly increase the detection capabilities of a network compared with a network composed of many noisy stations. Because our method is data driven, it has two distinct advantages: (1) it is less dependent on theoretical assumptions of source spectra and models of regional attenuation, and (2) it can easily be applied to any seismic network. This tool allows for an objective approach to the management of stations in regional seismic networks.

Seismological Research Letters↗
USGS2022

Prospective and retrospective evaluation of the U.S. Geological Survey public aftershock forecast for the 2019-2021 Southwest Puerto Rico Earthquake and aftershocks

The M w "> M w 6.4 Southwest Puerto Rico Earthquake of 7 January 2020 was accompanied by a robust fore‐ and aftershock sequence. The U.S. Geological Survey (USGS) has issued regular aftershock forecasts for more than a year since the mainshock, available on a public webpage. Forecasts were accompanied by interpretive and informational material, published in English and Spanish. Informational products included narrative “scenarios” for how the aftershock sequence could play out, infographics, and a report on the potential duration of the aftershock sequence through the next decade. Forecasts are based on the epidemic‐type aftershock sequence (ETAS) model and generated using the USGS AftershockForecaster software—an interactive graphical user interface built on the OpenSHA platform ( Field et al. , 2003 ). The initial forecast is based on past sequences in similar tectonic environments; subsequent forecasts are tuned to the ongoing sequence via Bayesian model updating. Probabilistic aftershock forecasts for the next day, week, month, and year were publicly released and archived at a daily to monthly tempo, allowing for a truly prospective test of the forecast. Here, we evaluate the forecast over the first year of the recorded aftershocks. The ETAS‐based forecast performed well overall, successfully capturing both the chance of having at least one earthquake of a given magnitude in a forecast interval as well as the non‐Poissonian distribution of the total number of aftershocks within an interval. A retrospective analysis shows that the ETAS model is a substantial improvement over the existing Reasenberg and Jones (1989) forecast model. The exercise also reveals some limitations of the current model, in particular, with respect to nonstationarities in the aftershock magnitude distribution and model parameters throughout the evolving sequence.

Puerto Rico↗
USGS2021

An evaluation of the timing accuracy of global and regional seismic stations and networks

Clock accuracy is a basic parameter of any seismic station and has become increasingly important for seismology as the community seeks to refine structures and dynamic processes of the Earth. In this study, we measure the arrival time differences of moderate repeating earthquakes with magnitude 5.0–5.9 in the time range of 1991–2017 at the same seismic stations by cross‐correlating their highly similar waveforms and thereby identify potential timing errors from the outliers of the measurements. The method has very high precision of about 10 ms and shows great potential to be used for routine inspection of the timing accuracy of historical and future digital seismic data. Here, we report 5131 probable cases of timing errors from 451 global and regional stations available from the Incorporated Research Institutions for Seismology Data Management Center, ranging from several tens of milliseconds to over 10 s. Clock accuracy seems to be a prevailing problem in permanent stations with long‐running histories. Although most of the timing errors have already been tagged with low timing quality, there are quite a few exceptions, which call for greater attention from network operators and the seismological community. In addition, seismic studies, especially those on temporal changes of the Earth’s media from absolute arrival times, should be careful to avoid misinterpreting timing errors as temporal changes, which is indeed a problem in some previous studies of the Earth’s inner core boundary.

Seismological Research Letters↗
USGS2022

Ground failure triggered by the 7 January 2020 M6.4 Puerto Rico earthquake

The 7 January 2020 M 6.4 Puerto Rico earthquake, the mainshock of an extended earthquake sequence, triggered significant ground failure. In this study, we detail the ground failure that occurred based largely on a postearthquake field reconnaissance campaign that we conducted. We documented more than 300 landslides, mainly rock falls that were concentrated in areas where peak ground acceleration (PGA) exceeded 30% g ; sparse smaller landslides occurred in highly susceptible areas more than 50 km from the epicenter and at PGA values <10% g . Though some of the largest mass movements were in natural slopes, rock falls in road cuts had more impact because they caused widespread transportation disruption. Some structures also were damaged by landslides, but no landslide‐related fatalities were reported. Liquefaction and related lateral spreading were severe in some areas, causing damage to residential and commercial structures and a power plant. Most of the liquefaction occurred in coastal areas where shaking exceeded 50% g , though some of the most damaging instances were in Ponce, where shaking estimates were as low as 20% g . In this article, we summarize the most notable ground failures and detail the overall patterns that we observed. The observations and compiled inventory datasets presented here are valuable because no island‐wide hazard maps for earthquake‐triggered landslides or liquefaction have been developed for Puerto Rico, and postevent inventories are vital for such an effort. In general, the datasets presented here contribute to a global understanding of coseismic ground‐failure hazard by presenting detailed observations for a relatively moderate ground‐failure event with well‐constrained shaking estimates; current models and expectations are biased by the tendency to collect detailed datasets mainly for exceptional events.

Puerto Rico↗
USGS2021

Seismotectonic analysis of the 2019–2020 Puerto Rico sequence: The value of absolute earthquake relocations in improved interpretations of active tectonics

We present a new catalog of calibrated earthquake relocations from the 2019–2020 Puerto Rico earthquake sequence related to the 7 January 2020 M w 6.4 earthquake that occurred offshore of southwest Puerto Rico at a depth of 15.9 km. Utilizing these relocated earthquakes and associated moment tensor solutions, we can delineate several distinct fault systems that were activated during the sequence and show that the M w 6.4 mainshock may have resulted from positive changes in Coulomb stress from earlier events. Seismicity and mechanisms define (1) a west–southwest (∼260°) zone of seismicity comprised of largely sinistral strike‐slip and oblique‐slip earthquakes that mostly occurs later in the sequence and to the west of the mainshock, (2) an area of extensional faulting that includes the mainshock and occurs largely within the mainshock’s rupture area, and (3) an north–northeast (∼30°)‐striking zone of seismicity, consisting primarily of dextral strike‐slip events that occurs before and following the mainshock and generally above (shallower than) the normal‐faulting events. These linear features intersect within the M w 6.4 mainshock’s fault plane in southwest Puerto Rico. In addition, we show that earthquake relocations for M 4+ normal‐faulting events, when traced along their fault planes, daylight along east–west‐trending bathymetric features offshore of southwest Puerto Rico. Correlation of these normal‐faulting events with bathymetric features suggests an active fault system that may be a contributor to previously uncharacterized seismic hazards in southwest Puerto Rico.

Puerto Rico↗
USGS2022

Toppling of a Trona Pinnacles Spire following the M5.5 RidgecrestaAftershock of June 2020

The 2019 M w 7.1 Ridgecrest California earthquake rupture passed within 4 km of the Trona Pinnacles, a large group of tufa rock pillars. Reconnaissance following the Ridgecrest mainshock documented fresh damage to several of the Pinnacles. Repeated aerial photogrammetric surveys also documented damage during subsequent aftershocks. Here, we describe the photogrammetric data with emphasis on a specific rock spire that toppled during an M w 5.5 aftershock. We calculate the volumes of the intact spire and of its subsequent debris. To explore the utility of the pinnacles as fragile geologic features for constraining past earthquake shaking intensity, we calculate the quasi static, horizontal acceleration required to break the spire at its base. We also examine the response of this feature to observed shaking using a dynamic model of the spire. In this case, we find that the quasi‐static estimate provides a conservative maximum constraint on fragility. The dynamic model of the spire suggests that shaking during the M w 7.1 mainshock likely generated tensile stresses in excess of the spire’s bulk strength, thereby making it vulnerable to collapse in subsequent aftershocks.

California↗
USGS2022

Ready for real time: Performance of Global Navigation Satellite System in 2019 Mw 7.1 Ridgecrest, California, rapid response products

Global Navigation Satellite Systems (GNSSs) have undergone notable advancement in the last few decades, leading to the availability of a dataset with capabilities well beyond its original intended purpose. The proliferation of high‐rate (1 Hz or greater) GNSS receivers in areas of seismological interest now allows for routine consideration of dynamic earthquake ground motions, with centimeter‐level displacement accuracy via precise point positioning methods. Real‐time (RT) GNSS observations, from stations that are both telemetered and processed to displacement with minimal latency, have lower accuracy compared to post‐processed (PP) GNSS displacements due to imprecise knowledge of atmospheric conditions, satellite clocks, and satellite orbits in RT. Whether the quality of RT high‐rate GNSS is sufficient for use in rapid response products remains to be thoroughly examined. Here, we highlight RT GNSS displacement time series processed during the 2019 M w "> M w Mw 7.1 Ridgecrest, California, earthquake in the context of common rapid‐response products, magnitude estimation, and kinematic fault‐slip models. We discuss how these data can be used to supplement RT seismic data for rapid characterization of significant earthquakes. We find that kinematic fault‐slip models using RT GNSS data retain the general spatiotemporal characteristics of those with PP data, with subtle differences in size and amplitude of modeled slip asperities. We demonstrate the effect of these rapid seismic source models using RT GNSS data on the U.S. Geological Survey product ShakeMap—a downstream ground‐motion prediction algorithm informed by the rupture dimensions estimated in the slip model. Discrepancies in the ShakeMap estimate are minor, within ±12% change, with the most severe variation at the fault edges. Our analysis suggests that, when used in conjunction with available seismic data sources, RT GNSS is sufficient and valuable for rapid earthquake characterization.

California↗
USGS2022

Classifying Worldwide Standardized Seismograph Network records using a simple convolution neural network

The U.S. Geological Survey (USGS) maintains an archive of 189,180 digitized scans of analog seismic records from the World‐Wide Standardized Seismograph Network (WWSSN). Although these scans have been made public, the archive is too large to manually review, and few researchers have utilized large numbers of these records. To facilitate further research using this historical dataset, we develop a simple convolutional neural network (CNN) that rapidly (∼4.75 s/film chip) classifies scanned film chip images (called “chips,” because they are individually cut segments of 70 mm film) into four categories of “interestingness” to earthquake seismologists based on the presence of earthquakes and other seismic signals in the record: “no interest,” “little interest,” “interest,” and “high interest.” The CNN, dubbed “Seismic Analog Record Network” (SARNet), can identify four types of seismic traces (“no events,” “minor events,” “major events,” and “errors”) in 200 × 200 pixel subcrops with an accuracy of 92% using a confidence threshold of 85%. SARNet then converts 100 random subcrops from each film chip into the overall classification of interestingness. In this task, SARNet performed as well as expert human classifiers in determining the film chip’s overall interest grade. Applying SARNet to 34,000 film chips in the WWSSN archive found that 21% of the images were of “high interest” and had an “indeterminate” rate of only 4%. Thus, the need for the manual review of images was reduced by 79%. Sorting of film chips derived from SARNet will expedite further exploration of the archive of digitized analog seismic records stored at the USGS.

Seismological Research Letters↗
USGS2022

Working with dynamic earthquake rupture models: A practical guide

Dynamic rupture models are physics‐based simulations that couple fracture mechanics to wave propagation and are used to explain specific earthquake observations or to generate a suite of predictions to understand the influence of frictional, geometrical, stress, and material parameters. These simulations can model single earthquakes or multiple earthquake cycles. The objective of this article is to provide a self‐contained and practical guide for students starting in the field of earthquake dynamics. Senior researchers who are interested in learning the first‐order constraints and general approaches to dynamic rupture problems will also benefit. We believe this guide is timely given the recent growth of computational resources and the range of sophisticated modeling software that are now available. We start with a succinct discussion of the essential physics of earthquake rupture propagation and walk the reader through the main concepts in dynamic rupture model design. We briefly touch on fully dynamic earthquake cycle models but leave the details of this topic for other publications. We also highlight examples throughout that demonstrate the use of dynamic rupture models to investigate various aspects of the faulting process.

Seismological Research Letters↗
USGS2022

Beyond the teleseism: Introducing regional seismic and geodetic data into routine USGS finite‐fault modeling

The U.S. Geological Survey (USGS) National Earthquake Information Center (NEIC) routinely produces finite‐fault models following significant earthquakes. These models are spatiotemporal estimates of coseismic slip critical to constraining downstream response products such as ShakeMap ground motion estimates, Prompt Assessment of Global Earthquake for Response loss estimates, and ground failure assessments. Because large earthquakes can involve slip over tens to hundreds of kilometers, point‐source approximations are insufficient, and it is vital to rapidly assess the amount, timing, and location of slip along the fault. Initially, the USGS finite‐fault products were computed in the first several hours after a significant earthquake, using teleseismic body wave and surface wave observations. With only teleseismic waveforms, it is generally possible to obtain a reliable model for earthquakes of magnitude 7 and larger. Here, we detail newly implemented updates to NEIC’s modeling capabilities, specifically to allow joint modeling of local‐to‐regional strong‐motion accelerometer, Global Navigation Satellite System (GNSS), and Interferometric Synthetic Aperture Radar (InSAR) observations in addition to teleseismic waveforms. We present joint inversion results for the 2015 M w ">

Seismological Research Letters↗
USGS2022

Testing the ShakeAlert earthquake early warning system using synthesized earthquake sequences

We test the behavior of the United States (US) West Coast ShakeAlert earthquake early warning (EEW) system during temporally close earthquake pairs to understand current performance and limitations. We consider performance metrics based on source parameter and ground‐motion forecast accuracy, as well as on alerting timeliness. We generate ground‐motion times series for synthesized earthquake sequences from real data by combining the signals from pairs of well‐recorded earthquakes (⁠4.4≤M≤7.1⁠) using time shifts ranging from −60 to +180 s. We examine fore‐ and aftershock sequences, near‐simultaneous events in different source regions, and simulated out‐of‐network and offshore earthquakes. We find that the operational ShakeAlert algorithms Earthquake Point‐source Integrated Code (EPIC) and Finite‐Fault Rupture Detector (FinDer) and the Propagation of Local Undamped Motion (PLUM) method perform largely as expected: EPIC provides the best source location estimates and is often fastest but can underestimate magnitudes or, in extreme cases, miss large earthquakes; FinDer provides real‐time line‐source models and unsaturated magnitude estimates for large earthquakes but currently cannot process concurrent events and may mislocate offshore earthquakes; PLUM identifies pockets of strong ground motion, but can overestimate alert areas. Implications for system performance are: (1) spatially and temporally close events are difficult to identify separately; (2) challenging scenarios with foreshocks that are close in space and time can lead to missed alerts for large earthquakes; and (3) in these situations the algorithms can often estimate ground motion better than source parameters. To improve EEW, our work suggests revisiting the current algorithm weighting in ShakeAlert, to continue developments that focus on using ground‐motion data to aggregate alerts from multiple algorithms, and to investigate methods to optimally leverage algorithm ground‐motion estimates. For testing and certification of EEW performance in ShakeAlert and other EEW systems where applicable, we also suggest that 25 of our 73 scenarios become part of the baseline data set.

California↗
USGS2022

Using machine learning techniques with incomplete polarity datasets to improve earthquake focal mechanism determination

Earthquake focal mechanisms are traditionally produced using P ‐wave first‐motion polarities and commonly require well‐recorded seismicity. A recent approach that is less dependent on high signal‐to‐noise exploits similar waveforms to produce relative polarity measurements between earthquake pairs. Utilizing these relative polarity measurements, it is possible to produce composite focal mechanisms for clusters within microseismic sequences using regional networks. However, missing or low‐confidence polarity measurements still limit our ability to calculate high‐quality composite focal mechanisms. Here, we replaced unreliable polarity measurements with estimates using iterative random forests, an unsupervised ensemble machine learning method. Using the imputed (“replaced”) polarity data, we then categorically clustered the events into families. As a case study, we applied this modified composite mechanism workflow to a multistation template matched catalog of an earthquake swarm that occurred during 2020 near the Maacama fault in northern California. We found that our modified methodology produced higher‐quality earthquake families and improved composite focal mechanisms, with fault‐plane uncertainties <35° for 94% of the families compared with 34% of families using the previous methodology.

Seismological Research Letters↗
USGS2022

An interactive viewer to improve operational aftershock forecasts

The U.S. Geological Survey (USGS) issues forecasts for aftershocks about 20 minutes after most earthquakes above M 5 in the United States and its territories, and updates these forecasts 75 times during the first year. Most of the forecasts are issued automatically, but some forecasts require manual intervention to maintain accuracy. It is important to identify the sequences whose forecasts will benefit from a modified approach so the USGS can provide accurate information to the public. The oaftools R package ( Paris and Michael, 2022 ) includes functions that analyze and plot earthquake sequences and their forecasts to identify which sequences require such intervention. The package includes the Operational Aftershock Forecast (OAF) Viewer, which incorporates the functions into an interactive web environment that can be used to explore aftershock sequences. The OAF Viewer starts with a global map and table of mainshocks. After a mainshock has been selected, the map and a new table show its aftershocks and the OAF Viewer generates five analytical plots: (1) magnitude–time, which is used to look for patterns in the data; (2) cumulative number, to see how the productivity of the sequence compares to a Reasenberg and Jones (1989) aftershock model over time; (3) magnitude–frequency, to compare the ratio of large to small magnitudes and extrapolate to higher magnitudes with sparse data and lower magnitudes with incomplete data; (4) forecast success, to compare the forecasts with observations for a sequence; and (5) parameter–time, which examines the temporal evolution of the forecast model parameters. The user can interact with the functions provided by the oaftools package through the OAF Viewer or by incorporating the functions into their own analysis methods. The OAF Viewer will help seismologists understand complexities in the data, communicate with the public and emergency managers, and improve the OAF system by maintaining operational awareness.

Seismological Research Letters↗
USGS2022

Revised earthquake recurrence intervals in California, USA: New paleoseismic sites and application of event likelihoods

Recurrence intervals for ground rupturing earthquakes are critical data for assessing seismic hazard. Recurrence intervals are presented here for 38 paleoseismic sites in California. Eleven of these include new or updated data; the remainder use data previously included in the Unified California Earthquake Rupture Forecast Version 3 (UCERF3). The methods and results are consistent with UCERF3. In addition, revised recurrence intervals are presented at every site. The revised recurrence intervals incorporate uncertainty in the interpretation of paleoseismic evidence, which is expressed as event likelihood. Event likelihood is the probability that the evidence has been correctly interpreted as a unique earthquake. Event likelihoods are estimated here for 85 inferred past earthquakes at eight paleoseismic sites in California, using a single, consistent methodology. The average event likelihood is 0.85. The revised recurrence intervals are 16% longer, on average, than conventional estimates, and their confidence intervals are disproportionately wider. These recurrence intervals are suitable for inclusion in a “grand inversion” rupture forecast, and they may be important for addressing a systematic misfit in the UCERF3 grand inversion. The revised recurrence intervals may also be important for assessing the unusually long earthquake hiatus in California. Other applications may not need to consider event likelihoods because the effects are small relative to typical uncertainties.

California↗
USGS2022

Viscoelastic fault-based model of crustal deformation for the 2023 update to the U.S. National Seismic Hazard Model

The 2023 update to the National Seismic Hazard (NSHM) model is informed by several deformation models that furnish geodetically estimated fault slip rates. Here I describe a fault‐based model that permits estimation of long‐term slip rates on discrete faults and the distribution of off‐fault moment release. It is based on quantification of the earthquake cycle on a viscoelastic model of the seismogenic upper crust and ductile lower crust and mantle. I apply it to a large dataset of horizontal and vertical Global Positioning System (GPS) interseismic velocities in the western United States, resulting in long‐term slip rates on more than 1000 active faults defined for the NSHM. A reasonable fit to the GPS dataset is achieved with a set of slip rates designed to lie strictly within a priori geologic slip rate bounds. Time‐dependent effects implemented via a “ghost transient” have a profound effect on slip rate estimation and tend to raise calculated slip rates along the northern and southern San Andreas fault by up to several mm/yr.

Seismological Research Letters↗