Geology topics

Annemarie S. Baltay

Publications and source records attributed to Annemarie S. Baltay.

At least 55 records · Page 3Linked to original sources

USGS2020

Strain-estimated ground motions associated with recent earthquakes in California

Peak ground velocity (PGV) is a commonly used parameter in earthquake ground‐motion models (GMMs) and hazard analyses, because it is closely related to structural damage and felt ground shaking, and is typically measured on broadband seismometers. Here, we demonstrate that strainmeters, which directly measure in situ strain in the bulk rock, can easily be related to ground velocity by a factor of bulk shear‐wave velocity and, thus, can be used to measure strain‐estimated PGV. We demonstrate the parity of velocity to strain utilizing data from borehole strainmeters deployed along the plate boundaries of the west coast of the United States for nine recent M "> M M 4.4–7.1 earthquakes in California, including the largest two events of the July 2019 Ridgecrest earthquake sequence. PGVs derived from maximum horizontal shear strains fall within the range of seismic‐estimated values recorded at the same distances. We compare the strain‐estimated data with GMMs based on seismic PGVs and find consistency in residual polarity (positive vs. negative; the sign of the difference between observed and modeled data) for certain earthquake–station paths, where some paths indicate an overestimation and others indicate an underestimation of strain‐derived PGVs, as compared with the GMMs. We surmise that this may be indicative of over or underestimation of shear‐wave velocity along those paths, as compared with the average velocity used to derive PGV from strain measurements, or indicative of repeatable site and path effects that are not accounted for in our analyses. This direct comparison of strain with velocity can highlight physical path effects, as well as improve the density and capability of ground‐motion recordings.

California↗

USGS2020

Peak ground velocity spatial variability revealed by dense seismic array in southern California

Understanding and modeling variability of ground motion is essential for building accurate and precise ground motion prediction equations, which can net site‐specific characterization and reduced hazard levels. Here, we explore the spatial variability in peak ground velocity (PGV) at Sage Brush Flats along the San Jacinto Fault in southern California. We use data from a dense array (0.6 x 0.6 km 2 , 1,108 geophones, station spacings 10‐30 m) deployed in 2014 for ~1‐month. These data offer an opportunity to study small scale variability in this region. We examine 38 2≤M L ≤4.2 earthquakes within 200 km of the array. Fault strands and a small basin impact the ground motions, producing PGV variations up to 22% of the mean and a 40% reduction in P and S wave near‐surface velocities. We find along‐fault rupture directivity, source, and path effects can increase PGVs by 167%. Surface PGV measurements exceed the co‐located borehole station (depth 148 m) PGV by factors of 3‐10, confirming the impact on PGV from near surface fault structures, basins, topography, and amplifications from soft sediments. Consistently we find high PGVs within the basin structure. A pair of ~co‐located M L 2.6 events produce repeatable PGV values with similar spatial patterns. The average corner frequencies of these two events are 11‐16 Hz and viable measurements of stress drop can differ by 6.45MPa. Within this small array, the PGV values are variable implying spatial extrapolation of PGV to regions of known faults and basins, even across a small area, should be done with caution.

California↗

USGS2020

Real-time performance of the PLUM earthquake early warning method during the 2019 M6.4 and M7.1 Ridgecrest, California, Earthquakes

We evaluate the timeliness and accuracy of ground‐motion‐based earthquake early warning (EEW) during the July 2019 M 6.4 and 7.1 Ridgecrest earthquakes. In 2018, we began retrospective and internal real‐time testing of the propagation of local undamped motion (PLUM) method for earthquake warning in California, Oregon, and Washington, with the potential that PLUM might one day be included in the ShakeAlert EEW system. A real‐time version of PLUM was running on one of the ShakeAlert EEW system’s development servers at the time of the 2019 Ridgecrest sequence, allowing us to evaluate the timeliness and accuracy of PLUM’s warnings for the M 6.4 and 7.1 mainshocks in real time with the actual data availability and latencies of the operational ShakeAlert EEW system. The latter is especially important because high‐data latencies during the M 7.1 earthquake degraded ShakeAlert’s performance. PLUM proved to be largely immune to these latencies. In this article, we present a retrospective analysis of PLUM performance and explore three potential regional alerting strategies ranging from spatially large regions (counties), to moderate‐size regions (National Weather Service public forecast zones), to high‐spatial specificity (50 km regular geographic grid). PLUM generated initial shaking forecasts for the two mainshocks 5 and 6 s after their respective origin times, and faster than the ShakeAlert system’s first alerts. PLUM was also able to accurately forecast shaking across southern California for all three alerting strategies studied. As would be expected, a cost‐benefit analysis of each approach illustrates trade‐offs between increasing warning time and minimizing the area receiving unneeded alerts. Choosing an optimal alerting strategy requires knowledge of users’ false alarm tolerance and minimum required warning time for taking protective action, as well as the time required to distribute alerts to users.

California↗

USGS2020

Repeatable source, path, and site effects from the 2019 Ridgecrest M7.1 earthquake sequence

We use a large instrumental dataset from the 2019 Ridgecrest earthquake sequence ( Rekoske et al. , 2019 , 2020 ) to examine repeatable source‐, path‐, and site‐specific ground motions. A mixed‐effects analysis is used to partition total residuals relative to the Boore et al. (2014 ; hereafter, BSSA14) ground‐motion model. We calculate the Arias intensity stress drop for the earthquakes and find strong correlation with our event terms, indicating that they are consistent with source processes. We look for physically meaningful trends in the partitioned residuals and test the ability of BSSA14 to capture the behavior we observe in the data. We find that BSSA14 is a good match to the median observations for M > 4 "> M > 4 M>4 ⁠ . However, we find bias for individual events, especially those with small magnitude and hypocentral depth ≥ 7    km "> depth ≥ 7 km depth≥7 km ⁠ , for which peak ground acceleration is underpredicted by a factor of 2.5. Although the site amplification term captures the median site response when all sites are considered together, it does not capture variations at individual stations across a range of site conditions. We find strong basin amplification in the Los Angeles, Ventura, and San Gabriel basins. We find weak amplification in the San Bernardino basin, which is contrary to simulation‐based findings showing a channeling effect from an event with a north–south azimuth. This and an additional set of ground motions from earthquakes southwest of Los Angeles suggest that there is an azimuth‐dependent southern California basin response related to the orientation of regional structures when ground motion from waves traveling south–north are compared with those in the east–west direction. These findings exhibit the power of large, spatially dense ground‐motion datasets and make clear that nonergodic models are a way to reduce bias and uncertainty in ground‐motion estimation for applications like the U.S. Geological Survey National Seismic Hazard Model and the ShakeAlert earthquake early warning System.

California↗

USGS2020

Optimizing earthquake early warning alert distance strategies using the July 2019 Mw6.4 and Mw7.1 Ridgecrest, California, earthquakes

The ShakeAlert earthquake early warning system aims to alert people who experience modified Mercalli intensity (MMI) IV+ shaking during an earthquake using source estimates (magnitude and location) to estimate median‐expected peak ground motions with distance, then using these ground motions to determine median‐expected MMI and thus the extent of MMI IV shaking. Because median ground motions are used, even if magnitude and location are correct, there will be people outside the alert region who experience MMI IV shaking but do not receive an alert (missed alerts). We use 91,000 “Did You Feel It?” survey responses to the July 2019 Mw 6.4 and Mw 7.1 Ridgecrest, California, earthquakes to determine which ground‐motion to intensity conversion equation (GMICE) best fits median MMI with distance. We then explore how incorporating uncertainty from the ground‐motion prediction equation and the GMICE in the alert distance calculation can produce more accurate MMI IV alert regions for a desired alerting strategy (e.g., aiming to alert 95% of people who experience MMI IV+ shaking), assuming accurate source characterization. Without incorporating ground‐motion uncertainties, we find MMI IV alert regions using median‐expected ground motions alert fewer than 20% of the population that experiences MMI IV+ shaking. In contrast, we find >94% of the people who experience MMI IV+ shaking can be included in the MMI IV alert region when two standard deviations of ground‐motion uncertainty are included in the alert distance computation. The optimal alerting strategy depends on the false alert tolerance of the community due to the trade‐off between minimizing missed and false alerts. This is especially the case for situations like the Mw 6.4 earthquake when alerting 95% of the 5 million people who experience MMI IV+ also results in alerting 14 million people who experience shaking below this level and do not need to take protective action.

California↗

USGS2020

When source and path components trade off in ground-motion prediction equations

Current research on ground‐motion models (also known as ground‐motion prediction equations [GMPEs]) and their uncertainties focus on the separate contributions of source, path, and site to both median values and their variability. Implicit here is the assumption that the event term, path term, and site term reflect only properties of the source, path, and site, respectively. Events with larger stress drop generate more high‐frequency energy, and thus more ground motion. Therefore, the correlation of high‐frequency (i.e., peak ground acceleration [PGA] or peak ground velocity [PGV]) event terms in GMPEs with stress drop is taken to be genuine. However, PGA and PGV ground‐motion observations of the 2014 M "> M 6.0 South Napa, California, earthquake clearly violate these assumptions. For this earthquake, high‐frequency ground‐motion residuals of recorded ground motion with respect to Next Generation Attenuation‐West2 Project (NGA‐West2) ground‐motion models show a dependence on distance, biasing the calculation of the event term by incorrectly mapping a regional attenuation effect into it. We examine the trade‐off between source and path effects for the South Napa earthquake and a well‐recorded California subset of the NGA‐West2 data. We fit near‐source (i.e., within 20 or 50 km) event terms and remaining differential geometrical spreading and anelastic attenuation terms in comparison to a simultaneous inversion for the source and path terms. This South Napa instance highlights one situation for which the high‐frequency event term can be interpreted as relative stress drop only when the distance dependence of the ground motions does not bias the residuals.

California↗

USGS2020

Near-field ground motions from the July, 2019 Ridgecrest, California, earthquake sequence

The 2019 Ridgecrest, California, earthquake sequence, including an Mw 6.4 event on 4 July and an Mw 7.1 approximately 34 hr later, was recorded by 15 instruments within 55 km nearest‐fault distance. To characterize and explore near‐field ground motions from the Mw 6.4 foreshock and Mw 7.1 mainshock, we augment these records with available macroseismic information, including conventional intensities and displaced rocks. We conclude that near‐field shaking intensities were generally below modified Mercalli intensity 9, with concentrations of locally high values toward the northern and southern termini of the mainshock rupture. We further show that, relative to near‐field ground motions at hard‐rock sites, instrumental ground motions at alluvial near‐field sites for both the Mw 6.4 foreshock and Mw 7.1 mainshock were depleted in energy at frequencies higher than 2–3 Hz, as expected from ground‐motion models. Both the macroseismic and instrumental observations suggest that sediments in the Indian Wells Valley experienced a pervasively nonlinear response, which helps explain why shaking intensities and damage in the closest population center, Ridgecrest, were relatively modest given its proximity to the earthquakes.

California↗

USGS2020

Developing post-alert messaging for ShakeAlert, the earthquake early warning system for the West Coast of the United States of America

As ShakeAlert, the earthquake early warning system for the West Coast of the U.S., begins its transition to operational public alerting, we explore how post-alert messaging might represent system performance. Planned post-alert messaging can provide timely, crucial information to both emergency managers and ShakeAlert operators as well as calibrate expectations among various publics or public user groups and inform their responses to future alerts. There is a concern among the scientists and emergency managers that false alerts may negatively impact trust in the system, so quickly disseminated post-alert messages are necessary. For a new early warning system, such as ShakeAlert, this is particularly relevant given that the potentially affected population is likely to be unfamiliar with this system. We address this concern in six steps: (1) assessment of ShakeAlert performance to date, (2) characterization of human behavior and response to earthquake alerts, (3) presentation of a decision tree for issuing post-alert messages, (4) design of a critical set of post-alert messaging scenarios, (5) elaboration of these scenarios with message templates for a variety of communication channels, and (6) development of a typology of earthquake alerts. We further explore methods for monitoring and evaluating ShakeAlert post-alert messaging, for continuous improvement to the system.

California, Oregon, Washington, Idaho, Nevada, Uta↗

USGS2019

κ0 and broadband site spectra in Southern California from source model-constrained inversion

Ground-motion modeling requires accurate representation of the earthquake source, path, and site. Site amplification is often modeled by VS30, the time-averaged shear-wave velocity of the top 30 meters of the Earth’s surface, though recent studies find that its ability to accurately predict site effects varies. Another measure of the site is κ0, the attenuation of high frequency energy near the site (Anderson & Hough, 1984). We develop a novel application of the Andrews (1986) method to simultaneously invert the spectra of 3,357 earthquakes in Southern California into source and site components. These earthquakes have magnitudes 2.5 to 5.72 and were recorded on 16 stations for a total of 52,297 records. We constrain the inversion with an individual earthquake demonstrating the most Brune-like shape to preserve the site spectra. We then solve for κ0 site amplification at each station in three frequency bands: 1-6 Hz, 6-14 Hz, and 14-35 Hz. The resulting values of κ0 range from 0.017 seconds at ANZA station PFO to 0.059 seconds at ANZA station SND. We compare our results with values of site κ0 from other studies as well as site residuals from GMPEs. We find good agreement between our site κ0 and previous studies in the region. We find that κ0 and high frequency site amplification (14-35 Hz band) correlates well with independent site residuals, making it a good first-order approximation for the effects of site attenuation or amplification on ground motion.

California↗

USGS2019

Event detection performance of the PLUM earthquake early warning algorithm in southern California

We test the Japanese ground‐motion‐based earthquake early warning (EEW) algorithm, propagation of local undamped motion (PLUM), in southern California with application to the U.S. ShakeAlert system. In late 2018, ShakeAlert began limited public alerting in Los Angeles to areas of expected modified Mercalli intensity (⁠IMMI⁠) 4.0+ for magnitude 5.0+ earthquakes. Most EEW systems, including ShakeAlert, use source‐based methods: they estimate the location, magnitude, and origin time of an earthquake from P waves and use a ground‐motion prediction equation to identify regions of expected strong shaking. The PLUM algorithm uses observed ground motions directly to define alert areas and was developed to address deficiencies in the Japan Meteorological Agency source‐based EEW system during the 2011 Mw 9.0 Tohoku earthquake sequence. We assess PLUM using (a) a dataset of 193 magnitude 3.5+ earthquakes that occurred in southern California between 2012 and 2017 and (b) the ShakeAlert testing and certification suite of 49 earthquakes and other seismic signals. The latter suite includes events that challenge the current ShakeAlert algorithms. We provide a first‐order performance assessment using event‐based metrics similar to those used by ShakeAlert. We find that PLUM can be configured to successfully issue alerts using IMMI trigger thresholds that are lower than those implemented in Japan. Using two stations, a trigger threshold of IMMI 4.0 for the first station and a threshold of IMMI 2.5 for the second station PLUM successfully detect 12 of 13 magnitude 5.0+ earthquakes and issue no false alerts. PLUM alert latencies were similar to and in some cases faster than source‐based algorithms, reducing area that receives no warning near the source that generally have the highest ground motions. PLUM is a simple, independent seismic method that may complement existing source‐based algorithms in EEW systems, including the ShakeAlert system, even when alerting to light (⁠IMMI 4.0) or higher ground‐motion levels.

California↗

USGS2019

Ground-motion residuals, path effects, and crustal properties: A pilot study in southern California

To improve models of ground motion estimation and probabilistic seismic hazard analyses, the engineering seismology field is moving toward developing fully nonergodic ground motion models, models specific for individual source‐to‐site paths. Previous work on this topic has examined systematic variations in ground‐motion along particular paths (from either recorded or simulated earthquake data) and has not included physical properties of the path. We present here a framework to include physical path properties, by seeking correlations between ground motion amplitudes along specific paths and crustal properties, specifically seismic velocity and anelastic attenuation, along that path. Using a large data set of small‐magnitude earthquakes recorded in Southern California, we find a correlation between the gradient of seismic S wave velocity and the path term residual, after accounting for an average geometric spreading and anelastic attenuation, indicating that heterogeneity in crustal velocity primarily controls the path‐specific attenuation. Even in aseismic regions, details of path‐specific ground motion prediction equations can be developed from crustal structure and property data.

California↗

USGS2019

Jack Boatwright’s last science

In the months before he passed away, Jack Boatwright asked us to review a manuscript on source properties, specifically stress drop, of earthquakes in northeastern North America (NENA). This manuscript originated in research funded by the U.S. Nuclear Regulatory Commission (NRC), described in his final report to NRC and published as USGS Open-File Report 2018-1073 (Boatwright, 2018). We wish to call attention to Boatwright (2018) for those who may not be aware of what Jack was unable to put into journal publications.

Seismological Research Letters↗

USGS2019

Earthquake stress drop and Arias Intensity

We determine earthquake stress drops directly from the Arias intensity database of NGA-West2. Arias intensity (Arias, 1970) is an engineering measure proportional to the integral of the absolute value of acceleration squared, over the significant duration of the signal. As such, it is closely related to root-mean-square acceleration, and can readily be connected to earthquake stress drop (Hanks and McGuire, 1981). Arias intensity records out to 100 km yield stable stress drops for moderate-to-large magnitude earthquakes, M6.5+; for smaller events ~M4.5 – 6.5, only closer-in records yield stable results. For the 116 events considered, stress drops are about 35% larger for Class 1 mainshocks than for traditional on-fault Class 2 aftershocks, and smaller for those aftershocks close to the main fault plane. Aftershock stress drops show large variability, however, implying that on average they re-rupture weakened patches, but can also rupture intact rock or high-stress asperities. We observe an increase of stress drop with earthquake depth similar to that of other studies but do not find any significant faulting mechanism dependence. The variability of the Arias intensity-based stress drop is lower than that of eGf-based stress drops from Baltay et al. (2010, 2011), and nearly on par with variability seen in ground-motion prediction equations. The Arias intensity stress drop is a novel and promising method to estimate stress drop without the need for path and site corrections, and yields further insight into the connection between source physics and ground-motion.

Journal of Geophysical Research B: Solid Earth↗

USGS2019

The limits of earthquake early warning accuracy and best alerting strategy

We explore how accurate earthquake early warning (EEW) can be, given our limited ability to forecast expected shaking even if the earthquake source is known. Because of the strong variability of ground motion metrics, such as peak ground acceleration (PGA) and peak ground velocity (PGV), we find that correct alerts (i.e., alerts that accurately predict the observed ground motion above a predetermined damage threshold) are not expected to be the most common EEW outcome even when the earthquake magnitude and location are accurately determined. Infrequently, ground motion variability results in a user receiving a false alert because the ground motion turned out to be significantly smaller than the damage threshold. More commonly, users will experience missed alerts when the system does not issue an alert but the user experiences potentially damaging shaking. Despite these inherit limitations, EEW can significantly mitigate earthquake losses for false-alert-arm-tolerant users who choose to receive alerts for expected ground motions much smaller than the level that could cause damage. Although this results in many false alerts for earthquakes that do not produce damaging ground shaking, it minimizes the number of missed alerts and produces overall optimal performance.

California↗

USGS2018

Ground motions from the 7 and 19 September, 2017 Tehuantepec and Puebla-Morelos, Mexico, earthquakes

The 2017 M "> M 8.2 Tehuantepec and M "> M 7.1 Puebla‐Morelos earthquakes were deep inslab normal‐faulting events that caused significant damage to several central‐to‐southern regions of Mexico. Inslab earthquakes are an important component of seismicity and seismic hazard in Mexico. Ground‐motion prediction equations (GMPEs) are an integral part of seismic hazard assessment as well as risk and rapid‐response products. This work examines the observed ground motions from these two events in comparison to the predicted median ground motions from four GMPEs. The residuals between the observed and modeled ground motions allow us to study regional differences in shaking, the effects of each earthquake, and basin effects in Mexico City, Puebla, and Oaxaca. We find that the ground motions from these two earthquakes are generally well modeled by the GMPEs. However, the Tehuantepec event shows larger than expected ground motions at greater distances and longer periods, which suggests a waveguide effect from the subduction zone geometry. Finally, Mexico City and the cities of Puebla and Oaxaca exhibit very large ground motions, indicative of well‐known site and basin effects that are much stronger than the basin terms included in some of the GMPEs. Simple and rapid ground‐motion parameter estimates that include site effects are key for hazard and real‐time risk assessments in regions such as Mexico, where the vast majority of the population lives in areas where the aforementioned effects are relevant. However, GMPEs based on site correction terms dependent on topographic slope proxies underestimate, at least in the three cities tackled in this work, the observed amplification. Therefore, there is a need to improve models of seismic amplification in basins that could be included in GMPEs.

Bulletin of the Seismological Society of America↗

USGS2018

Revised technical implementation plan for the ShakeAlert system—An earthquake early warning system for the West Coast of the United States

The U.S. Geological Survey (USGS), along with partner organizations, has developed an earthquake early warning (EEW) system called ShakeAlert for the highest risk areas of the United States: namely, California, Oregon, and Washington. The purpose of the system is to reduce the impact of earthquakes and save lives and property by providing alerts to institutional users and the public. Using networks of ground-motion sensors and sophisticated computer algorithms, ShakeAlert can detect an earthquake seconds after it begins, calculate its location and magnitude, and estimate the resulting intensity of shaking. Alerts can then be sent to people and systems that may experience damaging shaking, allowing them to take appropriate protective actions. Depending on the user’s distance from the earthquake, alerts may be delivered before, during, or after the arrival of strong shaking. ShakeAlert is built on the foundation of the sensor networks and data processing infrastructure of the USGS-led Advanced National Seismic System. However, these networks were not originally designed for EEW; old equipment needs to be updated and new stations must be added to construct EEW-capable networks. The ShakeAlert data-processing infrastructure includes redundant servers that are geographically distributed at monitoring centers in Seattle, Washington, as well as Menlo Park, Berkeley, and Pasadena in California. Three data-processing layers collect raw ground-motion data from field stations (data layer), analyze these data to estimate the area and intensity of the resulting shaking (production layer), and publish alert products as appropriate for end users (alert layer). The alert layer can support thousands of institutional users and alert redistributors, but the USGS does not have the mission, infrastructure, or expertise to perform public notifications and is therefore recruiting technology enablers from the private sector. Additionally, ShakeAlert will coordinate with both public and private partners to accomplish consistent and ongoing public communication, education, and outreach. The estimated cost of completing the ShakeAlert infrastructure and sensor networks is \$39.4 million and has an estimated annual operation and maintenance cost of \$28.6 million per year. Building a highly reliable data telemetry infrastructure would cost another \$20.5 million and operating this telemetry system would add \$49.8 million per year; however, these costs could be reduced if project partners provide bandwidth on existing systems.

Open-File Report↗

USGS2018

Using tectonic tremor to constrain seismic‐wave attenuation in Cascadia

Tectonic tremor can be used to constrain seismic‐wave attenuation for use in ground‐motion prediction equations (GMPEs) in regions where moderately sized earthquakes occur infrequently. Here we quantify seismic‐wave attenuation by inverting tremor ground motion amplitudes in different frequency bands of interest, to determine frequency dependence of and spatial variations in seismic‐wave attenuation in Cascadia. Due to the density of tremor data, we are able to resolve along‐strike variations in the attenuation parameter. We find that tectonic tremor exhibits the frequency dependence expected for attenuation, as determined from GMPEs developed from moderate‐to‐large magnitude earthquakes. This implies that attenuation along these paths is independent of the source mechanism. This study demonstrates that tectonic tremor can be used to provide insight into the physical factors responsible for attenuation, and to refine estimates of attenuation for ground‐motion prediction, thus having important implications for hazard assessment and engineering seismology.

Geophysical Research Letters↗

USGS2018

Research to improve ShakeAlert earthquake early warning products and their utility

Earthquake early warning (EEW) is the rapid detection of an earthquake and issuance of an alert or notification to people and vulnerable systems likely to experience potentially damaging ground shaking. The level of ground shaking that is considered damaging is defined by the specific application; for example, manufacturing equipment may experience damage at a lower intensity ground shaking than would cause damage to a building. Along the West Coast of the United States, the warning times for ground shaking could range as high as tens of seconds for moderate levels of ground shaking, or potentially longer, if a lower ground-shaking threshold is used to issue alerts. However, it is not always possible to provide advance warning of ground shaking, particularly for locations close to an earthquake that are most likely to experience very strong ground shaking. EEW alerts may be useful to individuals who can use a few seconds to move to a safe zone and to electromechanical systems that can take automatic actions to reduce damage and injuries. An EEW system, ShakeAlert, has been under development in the United States since 2006. Federal and State governments, as well as the private sector, are now investing in the ShakeAlert prototype system that will, when completed, become an operational public system for the West Coast of the United States. While the current prototype is delivering alerts to test users, improvements to the accuracy, timeliness, and utility of the alerts are needed. For this reason, it is essential that the ShakeAlert system be continuously improved through targeted research, involving not only the current ShakeAlert partner organizations, but also the broader scientific, engineering, and emergencyresponse communities. To this end, this report describes the opportunities for improvement that can be addressed through research and development over the next 5 years. Our recommendations are organized into four areas: (1) understand EEW capabilities and user needs, (2) make alerts as fast and accurate as possible, (3) ensure reliability when it counts, and (4) explore the use of new instrumentation. The first challenge is to understand EEW capabilities and user needs. EEW must deliver actionable information to people and to automated systems to mitigate short- and longterm impacts of damaging ground shaking, so development of EEW must be motivated by the needs of users. Within this challenge, we must study the technical capabilities and limitations of EEW in general, and the ShakeAlert system specifically. This includes development of performance metrics that assess the timeliness and accuracy of alerts to understand the value and utility of the ShakeAlert EEW product(s) for various user groups, including different industry sectors, emergency-management agencies, and the public. Research is needed to define the alerting choices that maximize the utility of the system for users and to determine what the available communication pathways are for providing timely alert information. Additionally, we engage users to assess how alerts will be used by different sectors to mitigate losses and to inform EEW product design. Further, social-science research is needed to develop alert messaging, including what relevant prior and follow-up information are required, to ensure effective use of alerts. The second challenge is to make alerts as fast and as accurate as possible. The timeliness and accuracy of an EEW alert is important because it will set in motion a series of actions and downstream products. An EEW alert will trigger notification across emergency-alert systems and across multiple communication channels to populations in impacted regions. The EEW alert region may grow as the earthquake fault-rupture length increases, and the EEW system’s characterization of it, evolves. We must continue research into new or improved seismic and geodetic waveform-processing methods necessary to rapidly characterize the expected ground shaking and associated uncertainties. It is important to thoroughly evaluate whether new methods improve alerts through more accurate ground-motion estimates and (or) reduced latencies (that is, longer warning times). New methods could include tracking the extent of a large rupture in real time (known as finite-fault algorithms) and ground-motionbased EEW algorithms. Additionally, ground motion predictions could be optimized for each earthquake as the earthquake fault rupture progresses by using, for example, event terms to shift ground-motion curves for more (or less) energetic ruptures. The third challenge is to ensure reliability when it counts. This challenge requires us to explore approaches that assess the expected performance of ShakeAlert across the range of earthquake magnitudes, locations, and depths that may occur within the alerting region. Large, damaging earthquakes and their associated aftershock sequences matter most for hazard and for EEW, but these large-earthquake sequences occur infrequently. We expect ShakeAlert to respond robustly to these large-earthquake sequences despite potentially long periods of relative seismic quiescence in the intervening years, and in spite of inevitable communication challenges that arise during and after a large earthquake. We must develop methods to utilize the broadest available datasets to test EEW performance, including ground-motion data recorded in other parts of the world. The observational period for large, damaging earthquakes in any particular region has been short in comparison to estimated large-earthquake recurrence times. Ground-motion records for very large, damaging western United States events and major aftershock sequences do not yet exist, nor do data exist for all potential sources of noise and spurious signals that ShakeAlert must be “tuned” to reject. In addition, robust synthetic data could provide the flexibility to test a wider range of earthquake magnitude, tectonic-setting, and noise scenarios than are covered by existing observational data. Synthetic ground-motion data must be thoroughly vetted against records of smaller magnitude earthquakes to ensure that they accurately capture both the onset and the amplitude of the ground shaking. The final challenge is to explore the use of new instrumentation. The development of EEW around the world to date has focused on the use of high-quality, scientific-grade seismic and geodetic instrumentation. The use of additional types of instrumentation or information may also improve EEW products by filling gaps in sensor coverage in countries that already have dense seismic networks or enable EEW in countries without such networks. We must keep up with these developments and continuously assess their value in supplementing existing EEW systems, such as ShakeAlert, or enabling EEW where such systems do not exist. Such developments include low-cost instrumentation with microelectromechanical system (MEMS) sensors and global positioning system (GPS)/global navigation satellite system (GNSS) antennas embedded in low-cost consumer electronics, sea-floor seismometers, geodetic instrumentation deployed along the Cascadia and Alaska megathrust margins of western North America, and borehole strainmeters that are already deployed across the region.

Open-File Report↗