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At least 145 records · Page 8Linked to original sources

USGS2019

Evaluation of ground‐motion models for U.S. Geological Survey seismic hazard models: 2018 Anchorage, Alaska, Mw 7.1 subduction zone earthquake sequence

Instrumental ground‐motion recordings from the 2018 Anchorage, Alaska ( ⁠ M w "> M w 7.1), earthquake sequence provide an independent data set allowing us to evaluate the predictive power of ground‐motion models (GMMs) for intraslab earthquakes associated with the Alaska subduction zone. In this study, we evaluate 15 candidate GMMs using instrumental ground‐motion observations of peak ground acceleration and 5% damped pseudospectral acceleration (0.02–10 s) to inform logic‐tree weights for the update of the U.S. Geological Survey seismic hazard model for Alaska. GMMs are evaluated using two methods. The first is a total residual visualization approach that compares the probability density function, mean, and standard deviations σ "> σ of the observed and predicted ground motion. The second GMM evaluation method we use is the common total residual probabilistic scoring method (log likelihood [LLH]). The LLH method provides a single score that can be used to weight GMMs in the Alaska seismic hazard model logic trees. To test logic branches in previous seismic hazard models, we evaluate GMM performance as a function of depth and we demonstrate that some GMMs show improved performance for earthquakes with focal depths greater than 50 km. Ten of the initial 15 candidate GMMs fit the observed ground motions and meet established criteria for inclusion in the next update of the Alaska seismic hazard model.

Alaska↗

USGS2020

Revision of Boore (2018) Ground‐motion predictions for Central and Eastern North America: Path and offset adjustments and extension to 200 m/s <= Vs30 <= 3000 m/s

The three sets of ground‐motion predictions (GMPs) of Boore (2018 ; hereafter, B18) are compared with a much larger dataset than was used in deriving the predictions. The B18 GMPs work well for response spectra at periods between ∼ 0.15 "> ∼ 0.15 ∼0.15 and 4.0 s after an adjustment accounting for a path bias at distances beyond 200 km—this was the maximum distance used to derive the stress parameters on which the simulations in B18 are based. An additional offset adjustment is needed in the B18 predictions for short and long periods. The adjustment at short periods may be because the κ 0 "> κ 0 κ0 of 0.006 s stipulated by the Next Generation Attenuation‐East (NGA‐East) project to be used in deriving the GMPs is inconsistent with the observations on rock sites. The explanation for the offset adjustment at long periods is not clear, but it could be a combination of limitations of the point‐source stochastic model for longer period motions, as well as a decreasing number of observations at longer periods available to constrain the simulations on which the predictions are based. The predictions of B18, developed for very‐hard‐rock sites ( ⁠ V S 30 "> V S 30 VS30 of 2000 and 3000    m / s "> 3000 m / s 3000 m/s ⁠ ), have here been extended down to V S 30 "> V S 30 VS30 values as low as 200    m / s "> 200 m / s 200 m/s ⁠ . I find, as have others, that for a given V S 30 "> V S 30 VS30 ⁠ , there is generally less site amplification for central and eastern North America (CENA) than for the active crustal region dataset used for the Boore, Stewart, et al. (2014 ; hereafter, BSSA14) GMP equations. This might have an impact on conclusions of several previous studies of CENA GMPs that used the site amplifications in BSSA14 in comparing data and predictions. An additional finding is that the κ 0 "> κ 0 κ0 implied by recordings on a subset of stations in the Charlevoix region located on rock (data from these stations were not used in the analysis described earlier) is more consistent with a value near 0.014 s than the 0.006 s value used in B18 and the NGA‐East project.

Seismological Research Letters↗

USGS2019

Calibration analysis and noise estimates of WWSSN Station ALQ (Albuquerque, New Mexico)

World‐Wide Standardized Seismograph Network (WWSSN) records contain daily calibration pulses that can be used to retrieve the magnification as well as the response of the instrument for a given day record. We analyze a select number of long‐period vertical (LPZ) records from WWSSN station ALQ (Albuquerque, New Mexico). Although we find that the response of this instrument varies widely throughout time, we show that in most cases, we are able to estimate a pole‐zero response that has a root mean square error of < 10 % "> <10% ⁠ . The variability of responses in historical networks has been reported elsewhere because a large number of adjustments of the galvanometer and seismometer were necessary. Using our derived responses, we estimate noise levels for a number of 1 hr digitized traces. We find that noise levels for the LPZ ALQ records are lower than previously reported, suggesting that these records can resolve smaller amplitude signals than previously suggested. We also find that although care must be taken in the digitization and calibration analysis, we are not limited by noise introduced in the digitization process. Finally, we see that to retrieve the full secondary microseism amplitude, we must use both the LPZ and short‐period components because the LPZ component is limited by system noise at periods less than ∼ 5    s "> ∼5 s ⁠ .

New Mexico↗

USGS2019

The sedimentary record of the 2018 Anchorage Earthquake in Eklutna Lake, Alaska: Calibrating the lacustrine seismograph

The 30 November 2018 M w "> M M w "> w 7.1 Anchorage earthquake caused modified Mercalli intensities of V¼ to V½ at Eklutna Lake (south central Alaska). A few hours after the earthquake, a “dirt streak” was observed on the lake surface, followed by a peak in sediment turbidity values ( ⁠ ∼ 80 "> ∼ 80 times normal) at a drinking water facility, which receives water from the lake through a pipe. These observations hint toward turbidity currents triggered by the earthquake in Eklutna Lake. Here, we study 32 short sediment cores retrieved from across Eklutna Lake and observe a millimeter‐to‐centimeter scale turbidite that can be confidently attributed to the 2018 earthquake in all coring locations. X‐ray computed tomography, grain‐size, and color‐spectral analyses of the turbidite show that it shares physical characteristics with the turbidite generated by the 1964 M w "> M w 9.2 Great Alaska earthquake, while it is considerably different from turbidites caused by historical floods. The 2018 turbidite reaches its largest thickness in the inflow‐proximal basin, but when compared to the 1964 turbidite and thereby canceling out local site effects, it is relatively thick in the inflow‐distal sub‐basin. The latter was exposed to stronger shaking during the 2018 earthquake, and this relative thickness trend may therefore be attributed to shaking intensity and gives an indication of the location of the earthquake epicenter relative to the basin axis. Furthermore, in contrast to the 1964 turbidite, which was sourced from both deltas and hemipelagic slopes, the 2018 turbidite was sourced from deltas only, as evidenced by its distribution. These results confirm that while it is generally accepted that shaking intensities of ≥ VI "> ≥ VI are needed to trigger turbidity currents from hemipelagic slopes, intensities as low as V¼ can be sufficient to trigger turbidity currents from deltaic slopes. Our results show that proglacial lakes can sensitively record differences in shaking intensity and that investigating deposits from recent earthquakes is crucial to calibrate the lacustrine seismograph.

Alaska↗

USGS2020

Using a dense seismic array to determine structure and site effects of the Two Towers earthflow in northern California

We deployed a network of 68 three-component geophones on the slow moving Two Towers earthflow in northern California. We compute horizontal-to-vertical spectral ratios (HVSRs) from the ambient seismic field. The HVSRs have two prominent peaks, one near 1.23 Hz and another between 4 and 8 Hz at most stations. The 1.23 Hz resonance is a property of the background noise field and may be due to a velocity contrast at a few hundred meters depth. We interpret the higher frequency peaks as being related to slide deposits and invert the spectral ratios for shallow velocity structure using in situ thickness measurements as a priori constraints on the inversion. The thickness of the shallowest, low-velocity layer is systematically larger than landslide thicknesses inferred from inclinometer data acquired since 2013. Given constraints from field observations and boreholes, the inversion may reflect the thickness of deposits of an older slide that is larger in spatial extent and depth than the currently active slide. Because the HVSR peaks measured at Two Towers are caused by shallow slide deposits and represent frequencies that will experience amplification during earthquakes, the depth of the actively sliding mass may be less relevant for assessing potential slide volume and associated hazard than the thicknesses determined by our inversions. More generally, our results underscore the utility of combining both geotechnical measurements and subsurface imaging for landslide characterization and hazard assessment.

California↗

USGS2019

USGS near-real-time products-and their use-for the 2018 Anchorage earthquake

In the minutes to hours after a major earthquake, such as the recent 2018 M w "> M w 7.1 Anchorage event, the U.S. Geological Survey (USGS) produces a suite of interconnected earthquake products that provides diverse information ranging from basic earthquake source parameters to loss estimates. The 2018 Anchorage earthquake is the first major domestic earthquake to occur since several new USGS products have been developed, thus providing an opportunity to discuss the newly expanded USGS earthquake product suite, its timeliness, performance, and reception. Overall, the products were relatively timely, accurate, well received, and widely used, including by the media, who used information and visualizations from many products to frame their early reporting. One downside of the codependence of multiple products is that reasonable updates to upstream products (e.g., magnitude and source characterization) can result in significant changes to downstream products; this was the case for the Anchorage earthquake. However, the coverage of strong‐motion stations and felt reports was so dense that the ShakeMap and downstream products were relatively insensitive to changes in magnitude or fault‐plane orientation once the ground‐motion data were available. Shaking and loss indicators initially fluctuated in the first hour or two after the earthquake, but they stabilized quickly. To understand how the products are being used and how effectively they are being communicated, we analyze the media coverage of USGS earthquake products. Most references to USGS products occurred within the first 48 hr after the event. The lack of coverage after 48 hr could indicate that longer‐term products addressing what actions the USGS is taking or what early reconnaissance has revealed might be useful for those people wanting additional information about the earthquake.

Alaska↗

USGS2020

How processing methodologies can distort and bias power spectral density estimates of seismic background noise

Power spectral density (PSD) estimates are widely used in seismological studies to characterize background noise conditions, assess instrument performance, and study quasi‐stationary signals that are difficult to observe in the time domain. However, these studies often utilize different processing techniques, each of which can inherently bias the resulting PSD estimates. The level of smoothing, the size of the data window, and the method used for actually estimating the spectral content can all have strong influences on PSD estimates and background noise statistics. We show that although smoothing reduces the variance of the PSD estimate, the corresponding decrease in frequency resolution can eliminate or distort features of interest. For instance, popular software packages such as Incorporated Research Institutions for Seismology Modular Utility for STAatistical kNowledge Gathering (MUSTANG) and earlier versions of Portable Array Seismic Studies of the Continental Lithosphere Quick Look eXtended (PQLX), which were designed for data quality control and are effective in that regard, are less suitable for scientific studies that require accurate resolution of spectral peaks, even for peaks as broad as the primary ( ⁠ ∼ 14    s "> ∼ 14 s period) and secondary ( ⁠ ∼ 7    s "> ∼ 7 s period) microseisms. We also demonstrate how the 1 and 3 hr data windows used in MUSTANG and PQLX can be strongly influenced by energy generated from moderate‐size ( ⁠ M > ∼ 4.8 "> M > ∼ 4.8 ⁠ ) teleseismic earthquakes. The ubiquity of these events is likely skewing median ambient‐noise estimates by as much as 5 dB upward, for periods of 10–50 s at high‐quality broadband stations. Finally, we illustrate that many of the discrepancies between global low‐noise models are attributable to processing methodologies rather than fundamental differences in the underlying seismic data.

Seismological Research Letters↗

USGS2020

A brief introduction to seismic instrumentation: Where does my data come from?

Modern seismology has been able to take advantage of several technological advances. These include feedback loops in the seismometer, specialized digitizers with absolute timing, and compression formats for storing data. While all of these advances have helped to improve the field, they can also leave newcomers a bit confused. Our goal here is to give a brief overview of how recordings of seismic ground motion originate. We discuss the chain of events that are required to obtain digital data plus how these steps can be reversed to recover units of ground motion such as acceleration, velocity, or displacement. Finally, we show a few examples of data that has become compromised because of various non-ground motion signals. We hope to give a quick practical introduction to allow the reader to become familiar with the various jargon used in observational seismology.

Seismological Research Letters↗

USGS2020

Goals and development of the Alaska Volcano Observatory Seismic Network and application to forecasting and detecting volcanic eruptions

The Alaska Volcano Observatory (AVO) seismic network has been in operation since 1988 and during this time has grown from 29 to 217 seismic stations providing real-time monitoring of 32 active volcanoes in Alaska, as well as useful data for regional earthquake monitoring. Since 1988, AVO has detected 59 volcanic eruptions at Aleutian arc volcanoes, and 31 of these have been captured by local seismic instrumentation. As part of this monitoring effort, AVO has cataloged more than 120,000 earthquake hypocenters and magnitudes associated with volcanic processes throughout the arc. This high rate of volcanic activity provides an excellent opportunity to study seismicity associated with magmatic and eruptive processes and develop and refine analytical techniques to track volcanic seismicity and warn of hazardous eruptions. The network is currently undergoing an extensive upgrade, replacing aging short-period analog seismometers with digital broadband instruments. These are expected to improve AVO’s seismic capability and further facilitate other geophysical instrumentation such as continuous Global Positioning System receivers, infrasound sensors, and web cams.

Seismological Research Letters↗

USGS2019

Highlights of a cursory study of behavior of three instrumented buildings during the Mw7.1 Anchorage, Alaska, earthquake of November 30, 2018

This is a cursory study of the recorded responses of three buildings instrumented by the U.S. Geological Survey (USGS) in Anchorage, Alaska, during the M w "> M w Mw 7.1 earthquake of 30 November 2018. The earthquake caused the strongest shaking in Anchorage since the well‐known 1964 M w "> M w Mw 9.2 Great Alaska earthquake. Since the 1964 event, several structures (buildings and bridges) in Anchorage have been instrumented by the USGS, and their responses have been recorded during multiple events. For each of the three buildings (the 14‐story Frontier Building, the 20‐story Atwood Building, and the 22‐story Hilton Hotel) studied herein, essential dynamic characteristics and significant behavioral aspects such as beating and torsional motions are identified. Recorded peak accelerations and displacements are provided, and average drift ratios are computed using the peak displacements at the roof levels with respect to the ground level. These average drift ratios imply that the motions are at levels expected not to cause damage to the buildings. Visualization videos of both the 14‐story Frontier and the 20‐story Atwood Buildings have been developed to display overall shaking of the buildings during the earthquake.

Alaska↗

USGS2020

Earthquake early warning ShakeAlert 2.0: Public rollout

The ShakeAlert Earthquake Early Warning System is designed to automatically identify and characterize the initiation and rupture evolution of large earthquakes, estimate the intensity of ground shaking that will result, and deliver alerts to people and systems that may experience shaking, prior to the occurrence of shaking at their location. It is configured to issue alerts to locations within the West Coast of the U.S. In 2018, ShakeAlert 2.0 went live in a regional public test in the first phase of a general public rollout. The ShakeAlert system is now providing alerts to over sixty institutional partners in the three states of the Western U.S. where most of the nation’s earthquake risk is concentrated: California, Oregon, and Washington. The ShakeAlert 2.0 product for public alerting is a message containing a polygon enclosing a region predicted to experience Modified Mercalli Intensity ≥ IV for an earthquake of M5.0 or larger, corresponding to moderate-to-strong ground shaking. A polygon format alert is the easiest description for selective re-broadcasting mechanisms (e.g. cell towers) and is a requirement for some mass notification systems such as the Federal Emergency Management Agency’s Integrated Public Alert and Warning System. ShakeAlert 2.0 is tested using historic waveform data consisting of 60 M3.5+ and 25 M5.0+ earthquakes, in addition to other anomalous waveforms. For the historic event test, the average M5+ false alert rate/missed event rate for ShakeAlert 2.0 is 8%/16%, and the M3.5+ false alert rate/missed event rate is 10%/36.7%. Real-time performance metrics are also presented to assess how the system behaves in regions that are well-instrumented, sparsely instrumented, and offshore.

British Columbia, California, Oregon, Washinton↗

USGS2020

The community code verification exercise for simulating sequences of earthquakes and aseismic slip (SEAS)

Numerical simulations of sequences of earthquakes and aseismic slip (SEAS) have made great progress over past decades to address important questions in earthquake physics. However, significant challenges in SEAS modeling remain in resolving multiscale interactions between earthquake nucleation, dynamic rupture, and aseismic slip, and understanding physical factors controlling observables such as seismicity and ground deformation. The increasing complexity of SEAS modeling calls for extensive efforts to verify codes and advance these simulations with rigor, reproducibility, and broadened impact. In 2018, we initiated a community code-verification exercise for SEAS simulations, supported by the Southern California Earthquake Center. Here, we report the findings from our first two benchmark problems (BP1 and BP2), designed to verify different computational methods in solving a mathematically well-defined, basic faulting problem. We consider a 2D antiplane problem, with a 1D planar vertical strike-slip fault obeying rate-and-state friction, embedded in a 2D homogeneous, linear elastic halfspace. Sequences of quasi-dynamic earthquakes with periodic occurrences (BP1) or bimodal sizes (BP2) and their interactions with aseismic slip are simulated. The comparison of results from 11 groups using different numerical methods show excellent agreements in long-term and coseismic fault behavior. In BP1, we found that truncated domain boundaries influence interseismic stressing, earthquake recurrence, and coseismic rupture, and that model agreement is only achieved with sufficiently large domain sizes. In BP2, we found that complexity of fault behavior depends on how well physical length scales related to spontaneous nucleation and rupture propagation are resolved. Poor numerical resolution can result in artificial complexity, impacting simulation results that are of potential interest for characterizing seismic hazard such as earthquake size distributions, moment release, and recurrence times. These results inform the development of more advanced SEAS models, contributing to our further understanding of earthquake system dynamics.

Seismological Research Letters↗

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

Caltech/USGS Southern California Seismic Network (SCSN) and Southern California Earthquake Data Center (SCEDC): Data availability for the 2019 Ridgecrest sequence

The 2019 M6.4 and M7.1 Ridgecrest earthquake sequence occurred in the eastern California shear zone (ECSZ). The mainshock ruptured the Little Lake fault zone and aftershocks extended from the Garlock fault in the south, to the southern end of the 1872 M7.5 Owens Valley earthquake rupture in the north. We present data from the Southern California Seismic Network (SCSN) and partner seismic networks recorded by the SCSN in the region. These time series data and related products such as the SCSN earthquake picks and catalogs, available from the Southern California Earthquake Data Center (SCEDC), provide the most comprehensive seismic datasets for the 2019 Ridgecrest earthquake sequence.

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↗

USGS2020

Operational earthquake forecasting during the 2019 Ridgecrest, California, earthquake sequence with the UCERF3-ETAS model

The first Uniform California Earthquake Rupture Forecast, Version 3–epidemic‐type aftershock sequence (UCERF3‐ETAS) aftershock simulations were running on a high‐performance computing cluster within 33 min of the 4 July 2019 M 6.4 Searles Valley earthquake. UCERF3‐ETAS, an extension of the third Uniform California Earthquake Rupture Forecast (UCERF3), is the first comprehensive, fault‐based, epidemic‐type aftershock sequence (ETAS) model. It produces ensembles of synthetic aftershock sequences both on and off explicitly modeled UCERF3 faults to answer a key question repeatedly asked during the Ridgecrest sequence: What are the chances that the earthquake that just occurred will turn out to be the foreshock of an even bigger event?

California↗

USGS2020

The U.S. Geological Survey’s Rapid Seismic Array Deployment for the 2019 Ridgecrest Earthquake Sequence

Rapid seismic deployments following large earthquakes capture ephemeral near‐field recordings of aftershocks and ambient noise that can provide valuable data for seismological studies. The U.S. Geological Survey installed 19 temporary seismic stations following the 4 July 2019 M w 6.4 and 6 July 2019 (UTC) M w 7.1 earthquakes near the city of Ridgecrest, California. The stations record the aftershock sequence beginning two days after the mainshock and are expected to remain in the field through approximately January 2020. The deployment augments the permanent seismic network in the area to improve azimuthal coverage and provide additional near‐field observations. This article summarizes the motivation and goals of the deployment; details of station installation, instrumentation, and configurations; and initial data quality and observations from the network. We expect these data to be useful for a range of studies including detailing near‐field variability in strong ground motions, determining stress drops and rupture directivity of small events, imaging the fault zone, documenting the evolution of crustal properties within and outside of the fault zone, and others.

California↗

USGS2020

A high-resolution seismic catalog for the initial 2019 Ridgecrest Earthquake sequence: Foreshocks, aftershocks, and faulting complexity

I use template matching and precise relative relocation techniques to develop a high-resolution earthquake catalog for the initial portion of the 2019 Ridgecrest earthquake sequence, from July 4-16, encompassing the foreshock sequence and the first 10+ days of aftershocks following the M w 7.1 mainshock. Using 13,525 routinely cataloged events as waveform templates, I detect and precisely locate a total of 34,091 events. Precisely located earthquakes reveal numerous cross-cutting fault structures with dominantly perpendicular SW- and NW-strikes. Foreshocks of the M w 6.4 event appear to align on a NW-striking fault. Aftershocks of the M w 6.4 event suggest that it further ruptured this NW-striking fault, as well as the SW-striking fault where surface rupture was observed. Finally, aftershocks of the M w 7.1 show a highly complex distribution, illuminating a primary NW-striking fault zone consistent with surface rupture, but also numerous cross-cutting SW-striking faults. Aftershock relocations suggest that the M w 7.1 event ruptured adjacent to the previous NW-striking rupture of the M w 6.4, perhaps activating a subparallel structure southwest of the earlier rupture. Both the NW and SE rupture termini of the M w 7.1 rupture exhibited multiple-fault branching, with particularly high rates of aftershocks and multiple fault orientations in the dilatational quadrant NE of the NW rupture terminus.

California↗