Geology topics

Grace Alexandra Parker

Publications and source records attributed to Grace Alexandra Parker.

33 records · Page 2Linked to original sources

USGS2023

High-pass corner frequency selection for implementation in the USGS automated ground motion processing tool

Earthquake ground motion processing for next-generation attenuation (NGA) projects required human inspection to select high-pass corner frequencies ( f cHP ), which is time-intensive and subjective. With growth in the number of recordings per event and interest in enhancing repeatability, we sought to develop automated procedures for f cHP selection. These procedures consider signal-to-noise ratio (SNR) and non-physical features in the displacement time series that indicate high- and/or low-frequency noise effects. The procedures are implemented in a US Geological Survey software package (gmprocess). We extend previous procedures for SNR-based corner frequency selection to also check for low-frequency artifacts in the displacement record using a polynomial fit to improve f cHP selection. We evaluate the performance of the SNR and polynomial fit criteria using recordings from the 2020 M5.1 North Carolina and the 2013 M4.7 Southern Ontario earthquakes. Data processed with the SNR-only criteria can have low f cHP and displacement drift; the displacement check increases f cHP and reduces displacement drift.

Conference Paper↗

USGS2023

Applications of nonergodic site response models to ShakeAlert case studies in the Los Angeles area

In this study, we explore whether the Parker and Baltay (2022) site response models for the Los Angeles (LA) basin region can improve ground‐motion forecasts in the U.S. Geological Survey ShakeAlert earthquake early warning system (hereafter ShakeAlert). We implement the peak ground acceleration and peak ground velocity site response models of Parker and Baltay (2022) in ShakeAlert via the earthquake information to ground‐motion (hereafter eqinfo2GM) module, which predicts ground motions from the estimated earthquake parameters of magnitude, rupture length, and location. The nonergodic site response models for the greater LA area were developed using ground motions from 414 M 3–7.3 earthquakes in southern California. We test nonergodic ground‐motion forecasts for five earthquakes in the LA area: the 1994 M 6.7 Northridge earthquake, the 2008 M 5.4 Chino Hills earthquake, the 2019 M 7.1 Ridgecrest earthquake, the 2020 M 4.5 South El Monte earthquake, and a synthetic M 7.8 earthquake on the southern San Andreas fault from the ShakeOut scenario, which was the basis of a statewide emergency response exercise. From the test results, we find that with the nonergodic site response applied, ShakeAlert not only alerts larger areas but can also result in longer warning times in LA region. In addition, the modified Mercalli intensity (MMI) ground‐motion predictions generated by the ShakeAlert eqinfo2GM module are improved in accuracy when compared with the corresponding ShakeMap ground‐truth MMI when the nonergodic site response model is applied.

California↗

USGS2023

Latency and geofence testing of wireless emergency alerts intended for the ShakeAlert® earthquake early warning system for the West Coast of the United States of America

ShakeAlert, the earthquake early warning (EEW) system for the West Coast of the United States, attempts to provides crucial warnings before strong shaking occurs. However, because the alerts are triggered only when an earthquake is already in progress, and the alert latencies and delivery times are platform dependent, the time between these warnings and the arrival of shaking is variable. The ShakeAlert system uses, among other public alerting platforms like a mobile phone operating system, smartphone apps, and the Federal Emergency Management Agency Integrated Public Alert & Warning System (IPAWS). IPAWS sends Wireless Emergency Alerts (WEAs) informing people via their smartphones and other mobile devices about various events, such as natural hazards, child abductions, or public health information about COVID-19. However, little is known about the IPAWS delivery latencies. Given that people may have only a few seconds of notice after they receive an alert to take a protective action before they feel earthquake shaking, quantifying latencies is critical to understanding whether the IPAWS system is useful for EEW. In this study, we developed new methods to test the IPAWS distribution system's performance, both with devices in a controlled environment and as well as with a 2019 community-based feedback form, in Oakland and San Diego County, California, respectively. The controlled environment test used mobile phones (including smart and non-smart phones) and associated devices to determine alert receipt times; the community research form had participants self-report their receipt times. By triangulating the data between the controlled test environment and the community research, we determined the latency statistics as well as whether the geofence (the geographic area where the alert was intended to be sent) held broadly. We found that the latencies were similar between the two tests despite the large differences in population sizes. WEA messages were received within a median time frame of 6–12 s, and the geofence held with only a few exceptions. We use this latency to assess how the system would have performed in two large earthquakes, the 1989 M6.9 Loma Prieta and 2019 M7.1 Ridgecrest earthquakes, which both occurred near our WEA test locations. Our analysis revealed that had IPAWS been available during those earthquakes, particularly Loma Prieta, it would have provided crucial seconds of notice that damaging shaking was imminent in some locations relatively far from the epicenter. Further, we find affordable non-smart phones can receive WEAs as fast as smartphones. Finally, our new method can be used for latency and geospatial testing going forward for IPAWS and other similar alerting systems.

California↗

USGS2023

Panel review of Ground Motion Characterization Model in 2023 NSHM

The 2023 National Seismic Hazard Model (NSHM; Petersen et al., 2023) has two major components – a seismic source characterization (SSC) model and a ground motion characterization (GMC) model. The US Geological Survey (USGS) established separate panels to review and provide input on these two models. Both panels are advisory, meaning that they provide input on technical issues for consideration by the USGS NSHM team, but they do not have decision making authority. Here, we report on the activities and recommendations of the Ground Motion Characterization Panel, made up of the authors of this review. Final modeling decisions are presented in separate USGS documents, including Petersen et al., (2023) and Moschetti et al., (2023). Where modeling decisions depart from our recommendations, the rationale is explained in those publications.

Report↗

USGS2022

Comparisons of the NGA-Subduction ground motion models

In this article, ground-motion models (GMMs) for subduction earthquakes recently developed as part of the Next Generation Attenuation-Subduction (NGA-Sub) project are compared. The four models presented in this comparison study are documented in their respective articles submitted along with this article. Each of these four models is based on the analysis of the large NGA-Sub database. Three of the four current models are developed for a global version as well as separate regionalized models. The fourth model was developed based on earthquakes only from Japan, and as such is applicable only for Japan. As part of this comparison study, a general discussion on the parameterization of the four models and the regionalization of the three models is provided. The specific strengths and or weaknesses or the technical decisions and justifications of any one model are not part of this comparison. A selected suite of deterministic attenuation curves and spectra are presented for the models along with a selected suite of currently used subduction models. A limited number of comparisons are presented in this article with a larger number of comparisons and the digital values provided in the electronic attachment. In addition to these scenario calculation comparisons, the results from a standard probabilistic seismic hazard analysis (PSHA) for two sites located in the Pacific Northwest Region in the state of Washington are presented. These calculations highlight the potential impact of using the new GMMs. Based on the comparisons presented here, a general understanding of these new GMMs can be obtained with the expectation that the implementation of a specific seismic hazard study should incorporate similar and additional comparisons and sensitivity studies pertinent to the site of interest.

Earthquake Spectra↗

USGS2022

The potential of using fiber optic distributed acoustic sensing (DAS) in earthquake early warning applications

As the seismological community embraces fiber optic distributed acoustic sensing (DAS), DAS arrays are becoming a logical, scalable option to obtain strain and ground‐motion data for which the installation of seismometers is not easy or cheap, such as in dense offshore arrays. The potential of strain data in earthquake early warning (EEW) applications has been recently demonstrated using records from borehole strainmeters (BSMs). However, current BSM networks are sparse, installing more BSMs is expensive and often impractical, and BSMs have the same limitations in offshore environments as other traditional seismic instruments. Here, we aim to provide a road map about how DAS data could be used in existing EEW applications, using the ShakeAlert EEW System for the West Coast of the United States as an example. We review the data requirements for EEW systems, examine ways in which strain‐derived ground‐motion data can be incorporated into such systems without significant modifications, and determine what is still needed for full utilization of DAS data in these applications. Importantly, EEW algorithms require ground‐motion amplitude information for rapid earthquake source characterization; thus, accurate strain amplitude observations, not only phase information, are necessary for deriving these ground‐motion metrics from DAS data. To obtain high‐quality ground‐motion observations, EEW‐compatible DAS arrays need to be multicomponent, well coupled, and low noise. We suggest ways to achieve such data requirements using existing DAS technology and discuss areas in which further research is needed to optimize DAS array performance for EEW.

Bulletin of the Seismological Society of America↗

USGS2022

Empirical map-based nonergodic models of site response in the greater Los Angeles area

We develop empirical estimates of site response at seismic stations in the Los Angeles area using recorded ground motions from 414 M 3–7.3 earthquakes in southern California. The data are from a combination of the Next Generation Attenuation‐West2 project, the 2019 Ridgecrest earthquakes, and about 10,000 newly processed records. We estimate site response using an iterative mixed‐effects residuals partitioning approach, accounting for azimuthal variations in anelastic attenuation and potential bias due to spatial clusters of colocated earthquakes. This process yields site response for peak ground acceleration, peak ground velocity, and pseudospectral acceleration relative to a 760 m/s shear‐wave velocity ( ⁠ V S "> V V S "> s ) reference condition. We employ regression kriging to generate a spatially continuous site response model, using the linear site and basin terms from Boore et al. (2014) as the background model, which depend on V S "> V V S "> s V S "> 30 ⁠ and depth to the 1 km/s V S "> V V S "> s isosurface. This is different from past approaches to nonergodic models, in which spatially varying coefficients are regressed. We validate the model using stations in the Community Seismic Network (CSN) that are in the middle of our model spatial domain but were not considered in model development, finding strong agreement between the interpolated model and CSN data for long periods. Our model could be implemented in regional seismic hazard analyses, which would lead to improvements especially at long return periods. Our site response model also has potential to improve both ground‐motion accuracy and warning times for the U.S. Geological Survey ShakeAlert earthquake early warning (EEW) system. For a point‐source EEW simulation of the 1994 M 6.7 Northridge earthquake, our model produces ground motions more consistent with the ground‐truth ShakeMap and would alert areas with high population density such as downtown Los Angeles at lower estimated magnitudes (i.e., sooner) than an ergodic model for a modified Mercalli intensity 4.5 alerting threshold.

California↗

USGS2022

Earthquake early warning for estimating floor shaking levels of tall buildings

This article investigates methods to improve earthquake early warning (EEW) predictions of shaking levels for residents of tall buildings. In the current U.S. Geological Survey ShakeAlert EEW system, regions far from an epicenter will not receive alerts due to low predicted ground‐shaking intensities. However, residents of tall buildings in those areas may still experience significant shaking due to the acceleration amplification caused by tall buildings’ dynamic behavior, as recently experienced by residents of the 52‐story building in downtown Los Angeles (DTLA) during the 2019 M 7.1 Ridgecrest earthquake. Using more than 400 recorded response data acquired from 77 instrumented buildings in California, here we compare the Federal Emergency Management Agency (FEMA) P‐58 and American Society of Civil Engineers (ASCE) 7‐16 simplified equations for peak floor acceleration (PFA), finding that the ASCE estimation is close to the median of data recorded in large and long‐distance events, whereas the current FEMA estimation is not suitable. In the second part of this article, four instrumented tall buildings in DTLA are extensively studied, and the performance of the simplified and response spectrum (RS) methods giving both an estimation of the free‐field horizontal peak ground acceleration (PGA) and pseudospectral acceleration is evaluated. The results show that the RS method is as accurate as the response history analysis as long as the ground‐motion RS is accurate, whereas the ASCE 7‐16 prediction is conservative. However, when ground‐motion RS or PGA is estimated for DTLA using a ground‐motion model (GMM), the performance of the RS method significantly degrades due to underestimation by the GMM at long periods. The results of this study imply that a nonergodic GMM, which may give more accurate prediction in Los Angeles, could improve the results for PFA when the building’s behavior is dominated by a few long‐period fundamental modes, as is the case for the 52‐story building in DTLA.

California↗

USGS2022

Spatially continuous models of aleatory variability in seismic site response for southern California

We develop an empirical, spatially continuous model for the single-station within-event ( ϕ SS ) component of earthquake ground motion variability in the Los Angeles area. ϕ SS represents event-to-event variability in site response or remaining variability due to path effects not captured by ground motion models. Site-specific values of ϕ SS at permanent seismic network stations were estimated during our previous work [1]. Here we first fit a model to ϕ SS conditioned on the time-averaged shear wave velocity in the upper 30 m (V S30 ). We observe that stations on soft soil have larger average variability in site response than those on rock, especially at short periods. We use regression kriging to spatially interpolate ϕ SS to an even grid spacing, using the V S30 -scaling as the background model [2]. This improves on previous work that used ordinary kriging for interpolation [1]. We find that ϕ SS ranges from about 0.1 to 0.4 natural log units in our study area, representing variations in site response at single locations of a factor of 1.1 up to a factor of 1.5. There is both greater variability and more coherency in the variability for short-period site response than for long periods. We recommend using these ϕ SS models with the site response models of [1] for applications where quantification of variability is needed, such as probabilistic seismic hazard analyses.

California↗

USGS2022

Performance of NGA-East GMMs and site amplification models relative to CENA ground motions

We investigate bias in ground motions predicted for Central and Eastern North America (CENA) using ground motion models (GMMs) combined with site amplification models developed in the NGA-East project. Bias is anticipated because of de-coupled procedures used in the development of the GMMs and site amplification models. The NGA-East GMMs were mainly calibrated by adjusting CENA data to a reference site condition using a site amplification model appropriate for active tectonic regions. Hence, these GMMs are likely biased relative to the CENA reference site condition (3000 m/sec shear wave velocity). Moreover, the NGA-East site amplification model recommended for hazard applications contains a simulation-based term for amplification between the reference condition and time-averaged shear wave velocity V S30 =760 m/sec, which is uncertain and has not been calibrated against data from sites with that reference condition. Using the NGA-East dataset, we apply mixed-effects residual analysis and identify that period-dependent bias in 5% damped response spectral acceleration is present across a wide frequency range, but is strongest (i.e., overestimating by a factor of 2) at short oscillator periods <0.2 sec. Ongoing work to remedy this bias consists of expanding the NGA-East dataset with more recent recordings and enhanced metadata, particularly regarding site conditions.

Conference Paper↗

USGS2021

NGA-Subduction research program

This article summarizes the Next Generation Attenuation (NGA) Subduction (NGA-Sub) project, a major research program to develop a database and ground motion models (GMMs) for subduction regions. A comprehensive database of subduction earthquakes recorded worldwide was developed. The database includes a total of 214,020 individual records from 1,880 subduction events, which is by far the largest database of all the NGA programs. As part of the NGA-Sub program, four GMMs were developed. Three of them are global subduction GMMs with adjustment factors for up to seven worldwide regions: Alaska, Cascadia, Central America and Mexico, Japan, New Zealand, South America, and Taiwan. The fourth GMM is a new Japan-specific model. The GMMs provide median predictions, and the associated aleatory variability, of RotD50 horizontal components of peak ground acceleration, peak ground velocity, and 5%-damped pseudo-spectral acceleration (PSA) at oscillator periods ranging from 0.01 to 10 s. Three GMMs also quantified “within-model” epistemic uncertainty of the median prediction, which is important in regions with sparse ground motion data, such as Cascadia. In addition, a damping scaling model was developed to scale the predicted 5%-damped PSA of horizontal components to other damping ratios ranging from 0.5% to 30%. The NGA-Sub flatfile, which was used for the development of the NGA-Sub GMMs, and the NGA-Sub GMMs coded on various software platforms, have been posted for public use.

Earthquake Spectra↗

USGS2021

Ergodic site response model for subduction zone regions

We present an ergodic site response model with regional adjustments for use with subduction zone ground-motion models. The model predicts site amplification of peak ground acceleration, peak ground velocity, and 5% damped pseudo-spectral accelerations of the orientation-independent horizonal component for oscillator periods from 0.01 to 10 s. The model depends on the time-averaged shear-wave velocity in the upper 30 m ( V S 30 ), basin depth, and region and is independent of subduction earthquake type. It has three components: a linear site-amplification term in the form of V S 30 -scaling, a nonlinear term that depends on V S 30 and shaking intensity parameterized by peak ground acceleration at the reference-rock velocity condition of 760 m/s, and a basin sediment-depth term for Japan and Cascadia conditioned on the depth to the 2.5 km/s shear-wave velocity isosurface ( Z 2.5 ). A global V S 30 -scaling model is provided along with regional adjustments for Japan, Taiwan, South America, Alaska, and Cascadia. The nonlinear model is global, with a functional form that has often been used to fit nonlinear responses inferred from simulations, but here we calibrate it empirically. Relative to a prior model for shallow earthquakes in active tectonic regions, our subduction zone global V S 30 -scaling is comparable at short periods (<1.0 s) but weaker at long periods, while the nonlinear site response is generally less pronounced but extends to lower levels of shaking. Basin depth models are conditioned on the difference of the actual Z 2.5 and a V S 30 -conditioned mean Z 2.5 . Sites with positive differential depths have increased long-period site responses and decreased short-period responses, with the opposite occurring for negative differential depths.

Earthquake Spectra↗

USGS2021

NGA-subduction global ground motion models with regional adjustment factors

We develop semi-empirical ground motion models (GMMs) for peak ground acceleration, peak ground velocity, and 5%-damped pseudo-spectral accelerations for periods from 0.01 to 10 s, for the median orientation-independent horizontal component of subduction earthquake ground motion. The GMMs are applicable to interface and intraslab subduction earthquakes in Japan, Taiwan, Mexico, Central America, South America, Alaska, the Aleutian Islands, and Cascadia. The GMMs are developed using a combination of data inspection, data regression with respect to physics-informed functions, ground-motion simulations, and geometrical constraints for certain model components. The GMMs capture observed differences in source and path effects for interface and intraslab events, conditioned on moment magnitude, rupture distance, and hypocentral depth. Site effect and aleatory variability models are shared between event types. Regionalized GMM components include the model constant (that controls ground motion amplitude), anelastic attenuation, magnitude-scaling break point, linear site response, and sediment depth terms. We develop models for the aleatory between-event variability ( τ ) "> ( τ ) , within-event variability ( ϕ ) "> ( ϕ ) , single-station within-event variability ( ϕ SS ) "> ( ϕ SS ) , and site-to-site variability ( ϕ S 2 S ) "> ( ϕ S 2 S ) . Ergodic analyses should use the median GMM and aleatory variability computed using the between-event and within-event variability models. An analysis incorporating non-ergodic site response should use the median GMM at the reference shear-wave velocity condition, a site-specific site response model, and aleatory variability computed using the between-event and single-station within-event variability models. Epistemic uncertainty in the median model is represented by standard deviations on the regional model constants, which facilitates scaled-backbone representations of model uncertainty in hazard analyses.

Earthquake Spectra↗

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

The 2019 Ridgecrest, California, earthquake sequence ground motions: Processed records and derived intensity metrics

Following the 2019 Ridgecrest, California, earthquake sequence, we compiled ground‐motion records from multiple data centers and processed these records using newly developed ground‐motion processing software that performs quality assurance checks, performs standard time series processing steps, and computes a wide range of ground‐motion metrics. In addition, we compute station and waveform metrics such as the time‐averaged shear‐wave velocity to 30 m depth ( ⁠ V S 30 "> V S 30 ⁠ ), finite‐rupture distances, and spectral accelerations. This data set includes 22,708 records from 133 events from 4 July 2019 (UTC) to 18 October 2019 with a magnitude range from 3.6 to 7.1. We expect that the rapid collection and dissemination of this information will facilitate detailed studies of these ground motions. In this article, we describe the data selection, processing steps, and how to access the data.

California↗