Geology topics

David C. Wilson

Publications and source records attributed to David C. Wilson.

At least 19 recordsLinked to original sources

USGS2026

Albuquerque Seismological Laboratory strategic vision

This circular presents a strategic outlook for the U.S. Geological Survey (USGS) Albuquerque Seismological Laboratory (ASL) for the next 10 years (2026–36). The ASL is a USGS field office in the Geological Hazards Science Center that operates portions of the Advanced National Seismic System and the Global Seismographic Network and focuses on fundamental research for instrumentation testing and data quality. The strategic outlook is categorized into two types of tasks: “Foundational Tasks” and “Aspirational Tasks.” Foundational Tasks are those that maintain the laboratory’s basic operations and services, including regional and global seismic monitoring, improving data quality, and providing instrument testing and support. A suite of Aspirational Tasks is also articulated; these can be considered priority targets of ASL that could improve ASL’s seismic monitoring capabilities and mission. Such tasks include improvements to remote stations, testing capabilities of nonseismic geophysical instruments, detection threshold monitoring, rapid aftershock deployments, and expanding seismic monitoring networks. This report was written with input from the USGS Geological Hazards Science Center, the USGS Earthquake Hazards Program (EHP), and colleagues with an interest in the work done by the ASL. Although the details of these tasks may change, this document can provide guidance on the overarching tasks at the ASL from 2026 to 2036 and an overview of the various components of the ASL and how they fit into the EHP and the Global Seismographic Network Program.

Circular↗

USGS2025

U.S. Geological Survey geomagnetic variometer data: Capitalizing on seismic infrastructure

The U.S. Geological Survey’s Geomagnetism Program is collaborating with the Earthquake Hazards Program and Global Seismographic Network Program to densify magnetic field observations. This collaboration focuses on the installation of magnetometers, or magnetic variometers, at existing seismic stations. Along with improving the density of space weather observations for hazard monitoring, these data can be used to correct colocated magnetic field induced noise in seismic data. Such corrections are especially useful during time periods of large magnetic storms where the magnetic field‐induced instrument noise can be of similar amplitude to earthquake ground‐motion records.

contiguous United States↗

USGS2025

Revisiting seismological discoveries of the inner core

Seismology has been used as a tool for understanding the current physical properties of the interior of the Earth and its dynamic evolution with remarkable success over the last century. Much of this progress is due to the ever‐expanding set of high‐quality quantitative observations of teleseismic waveforms recorded at seismographic stations worldwide. In this work, we revisit historical seismological studies that helped first identify a core distinct in physical properties from the overlying mantle, followed by the detection of an inner core that was eventually verified to be solid based on normal‐mode eigenperiods. Along with a brief overview of past studies of the Earth’s inner core, we examine the reproducibility of these results and discuss how historical data compare against modern observations. After accounting for past normal‐mode misidentifications, we confirm that introducing a solid inner core is required to afford significant improvements in fits to both radial modes and core‐sensitive spheroidal overtones. Strong shear dissipation in the inner core of the radial reference Earth model, REM1D ( ⁠⁠ Q u = 89.54 ), fits the reference datasets of both normal‐mode eigenperiods and quality factors accounting for physical dispersion. Because a liquid region would only have bulk dissipation, a narrow range of low Q u values that are preferred by the reference datasets affords additional evidence of a solid inner core. In addition, we find that there is little systematic bias in the timing accuracy of historical data, although large variances exist. Investigations into the temperature, composition, and evolution of the inner core, as well as the reproducibility of past studies, can benefit from the reconciliation of historical and modern seismological datasets.

Seismological Research Letters↗

USGS2024

Perspectives on transportable array Alaska background noise levels

Background seismic noise fundamentally sets a lower bound on our ability to record signals arising from earthquakes. The background noise spectrum at a station is a combination of cultural noise, ocean-generated microseism noise, intrinsic instrument self-noise, and the sensitivity of the instrument to nonseismic noise sources. The USArray-Transportable Array Alaska deployed 195 stations across Alaska and parts of Canada (Yukon, British Columbia, and Northwest Territories). These stations were all installed using similar techniques and made use of instruments with similar self-noise levels. As such, this network provides an opportunity to look at how geographic location influences seismic background. Using these broadband stations, we report background noise levels from 0.2 to 75 s period in six discrete bands. By constructing “noise maps,” we depict both spatial and temporal changes in the background noise field. Using these maps, combined with targeted analysis, we infer sources and contributing factors to noise levels in these different period bands. These include cultural noise, the formation of sea ice, seasonal changes in permafrost and wave activity in the Gulf of Alaska, and magnetic field variability. We use this study as an opportunity to review several previous studies examining seismic noise in Arctic regions.

Book chapter↗

USGS2024

Uncertainty and spatial correlation in station measurements for mb magnitude estimation

The body‐wave magnitude (⁠⁠) is a long‐standing network‐averaged, amplitude‐based magnitude used to estimate the magnitude of seismic sources from teleseismic observations. The U.S. Geological Survey National Earthquake Information Center (NEIC) relies on in its global real‐time earthquake monitoring mission. Although waveform modeling‐based moment magnitudes are the modern standard to characterize earthquake size, is important because (1) in many cases, waveform modeling is not possible (e.g., low signal‐to‐noise events), (2) is applicable over a broad range of magnitudes, ∼M 4–7, and (3) there is a many decades‐long history of estimating magnitudes. We use the NEIC Preliminary Determination of Epicenters earthquake catalog to investigate the uncertainty in NEIC station measurements. We show that measurements are spatially correlated, which can bias event ⁠, and we describe an empirical relation between this spatial correlation and station‐to‐station distance. We further describe an approach to mitigate bias from the spatial correlation. Accounting for the spatial covariance of observations can change the event from −0.15 to 0.07 units (10th to 90th percentile) for smaller events (⁠⁠). These smaller events have the largest standard deviations ranging from 0.05 to 0.15 units (10th to 90th percentile).

The Seismic Record↗

USGS2024

Preface to focus section on new frontiers and advances in global seismology

Over the last century, many of the fundamental advances in our understanding of the solid Earth have been underpinned by seismic observations recorded on long‐running networks of globally distributed seismic instruments (e.g., Agnew et al. , 1976; Romanowicz et al. , 1984; Hanka and Kind, 1994; Peterson and Hutt, 2014; Ringler et al. , 2022a). During this time, seismic data quality and the speed of dissemination have improved substantially from early analog paper records to digital, very broadband data transmitted in near‐real time (Steim, 2015) and rapidly archived in online data repositories with...

Seismological Research Letters↗

USGS2024

Noise constraints on global body‐wave measurement thresholds

Intermediate sized earthquakes (≈ M 4–6.5) are often measured using the teleseismic body‐wave magnitude ( ⁠𝑚b⁠ ). 𝑚b measurements are especially critical at the lower end of this range when teleseismic waveform modeling techniques (i.e., moment tensor analysis) are difficult. The U.S. Geological Survey National Earthquake Information Center (NEIC) determines the location and magnitude of all M 5 and greater earthquakes worldwide within 20 min of the rupture time, and therefore accurate 𝑚b magnitude estimates are essential to fulfill its mission. To better understand how network geometry and noise levels affect the global response capabilities, we developed a method to spatially estimate the minimum measurable 𝑚b⁠ . To do this, we compare expected 𝑚b amplitudes at every station to the station’s background noise level. We find that using NEIC’s current network geometry and these idealized thresholds, NEIC can potentially estimate 𝑚b magnitudes down to M 4.5 globally. Low‐latitude regions in the Southern Hemisphere present the biggest opportunity to improve monitoring capabilities. However, logistically they also present the biggest hurdles for network operators. Finally, to test the resiliency of the network we removed the 20 most important stations and found the 𝑚b threshold remains 𝑚b 4.5. However, the region where only 𝑚b 4.5 and greater can be estimated increases and is again restricted to the Southern Hemisphere.

Bulletin of the Seismological Society of America↗

USGS2024

Background seismic noise levels among the Caribbean network and the role of station proximity to coastline

The amplitude and frequency content of background seismic noise is highly variable with geographic location. Understanding the characteristics and behavior of background seismic noise as a function of location can inform approaches to improve network performance and in turn increase earthquake detection capabilities. Here, we calculate power spectral density estimates in one‐hour windows for over 15 yr of vertical‐component data from the nine‐station Caribbean network (CU) and look at background noise within the 0.05–300 s period range. We describe the most visually apparent features observed at the CU stations. One of the most prominent features occurs in the 0.75–3 s band for which power levels are systematically elevated and decay as a function of proximity to the coastline. Further examination of this band on 1679 contiguous USArray Transportable Array stations reveals the same relationship. Such a relationship with coastal distance is not observed in the 4–8 s range more typical of globally observed secondary microseisms. A simple surface‐wave amplitude decay model fits the observed decay well with geometric spreading as the most important factor for stations near the coast (<∼50 km). The model indicates that power levels are strongly influenced by proximity to coastline at 0.75–3 s. This may be because power from nearshore wave action at 0.75–3 s overwhelms more distant and spatially distributed secondary microseism generation. Application of this basic model indicates that a power reduction of ∼25 dB can be achieved by simply installing the seismometer 25 km away from the coastline. This finding may help to inform future site locations and array design thereby improving network performance and data quality, and subsequently earthquake detection capabilities.

Seismological Research Letters↗

USGS2023

Global seismic networks operated by the U.S. Geological Survey

The U.S. Geological Survey (USGS) Global Seismographic Network (GSN) Program operates two thirds of the GSN, a network of state‐of‐the‐art, digital seismological and geophysical sensors with digital telecommunications. This network serves as a multiuse scientific facility and a valuable resource for research, education, and monitoring. The other one third of the GSN is funded by the National Science Foundation (NSF), and the operations of this component are overseen by EarthScope. This collaboration between the USGS, EarthScope, and NSF has allowed for the development and operations of the GSN to be a truly multiuse network that provides near real‐time open access data, facilitating fundamental discoveries by the Earth science community, supporting the earthquake hazards mission of the USGS, benefitting tsunami monitoring by the National Oceanic and Atmospheric Administration, and contributing to nuclear test monitoring and treaty verification. In this article, we describe the installation and evolution of the seismic networks operated by the USGS that ultimately led to the USGS portion of the GSN (100 stations under network codes IU, IC, and CU) as they are today and envision technological advances and opportunities to further improve the utility of the network in the future. This article focuses on the USGS‐operated component of the GSN; a companion article on the GSN stations funded by the NSF and operated by the Cecil and Ida Green Institute of Geophysics and Planetary Physics, Scripps Institution of Oceanography, University of California at San Diego by Davis et al. (2023) appears in this volume.

Seismological Research Letters↗

USGS2023

Comment on “A new decade in seismoacoustics (2010–2022)” by Fransiska Dannemann Dugick, Clinton Koch, Elizabeth Berg, Stephen Arrowsmith, and Sarah Albert

An increase in seismic stations also having microbarographs has led to increased interest in the field of seismoacoustics. A review of the recent advances in this field can be found in Dannemann Dugick et al. (2023) . The goal of this note is to draw the attention of the readers of Dannemann Dugick et al. (2023) to several additional interactions between the solid Earth and atmosphere that have not been classically considered in the field of seismoacoustics. The 15 January 2022 Hunga Tonga–Hunga Ha‘api eruption produced acoustic gravity waves that were recorded globally. For example, the Lamb wave from this eruption produced early‐arriving and long‐lasting tsunami waves. This eruption also provided globally recorded coupling of atmospheric modes with solid Earth modes, providing another example of the complex interactions that can occur at the boundary between the atmosphere and the solid Earth. Even in the absence of large atmospheric signals, collocated pressure sensors at seismic stations can be a useful tool for estimating the local substructure, such at V S 30 ⁠ , the average shear velocity of the upper 30 m. Finally, at low frequencies, it is possible to use pressure records to correct out atmospheric disturbances recorded on seismometers. We briefly review the aforementioned, nontraditional seismoacoustic topics that we feel are important to consider as part of the full suite of interactions occurring between the solid Earth and atmosphere.

Bulletin of the Seismological Society of America↗

USGS2022

Earth’s upper crust seismically excited by infrasound from the 2022 Hunga Tonga–Hunga Ha’apai eruption, Tonga

Records of pressure variations on seismographs were historically considered unwanted noise; however, increased deployments of collocated seismic and acoustic instrumentation have driven recent efforts to use this effect induced by both wind and anthropogenic explosions to invert for near‐surface Earth structure. These studies have been limited to shallow structure because the pressure signals have relatively short wavelengths (<∼300 m). However, the 2022 eruption of Hunga Tonga–Hunga Ha’apai (also called “Hunga”) volcano in Tonga generated rare, globally observed, high‐amplitude infrasound signals with acoustic wavelengths of tens of kilometers. In this study, we examine the acoustic‐to‐seismic coupling generated by the Hunga eruption across 82 Global Seismographic Network (GSN) stations and show that ground motion amplitudes are related to upper (0 to ∼5 km) crust material properties. We find high (>0.8) correlations between pressure and vertical component ground motion at 83% of the stations, but only 30% of stations show this on the radial component, likely due to complex tilt effects. We use average elastic properties in the upper 5.2 km from the CRUST1.0 model to estimate vertical seismic/acoustic coupling coefficients ( ⁠ S V / A ">

Seismological Research Letters↗

USGS2022

The global seismographic network reveals atmospherically coupled normal modes excited by the 2022 Hunga Tonga eruption

The eruption of the submarine Hunga Tonga-Hunga Haʻapai (Hunga Tonga) volcano on 15 January 2022, was one of the largest volcanic explosions recorded by modern geophysical instrumentation. The eruption was notable for the broad range of atmospheric wave phenomena it generated and for their unusual coupling with the oceans and solid Earth. The event was recorded worldwide across the Global Seismographic Network (GSN) by seismometers, microbarographs and infrasound sensors. The broad-band instrumentation in the GSN allows us to make high fidelity observations of spheroidal solid Earth normal modes from this event at frequencies near 3.7 and 4.4 mHz. Similar normal mode excitations were reported following the 1991 Pinatubo (Volcanic Explosivity Index of 6) eruption and were predicted, by theory, to arise from the excitation of mesosphere-scale acoustic modes of the atmosphere coupling with the solid Earth. Here, we compare observations for the Hunga Tonga and Pinatubo eruptions and find that both strongly excited the solid Earth normal mode 0 S 29 (3.72 mHz). However, the mean modal amplitude was roughly 11 times larger for the 2022 Hunga Tonga eruption. Estimates of attenuation ( Q ) for 0 S 29 across the GSN from temporal modal decay give Q = 332 ± 101, which is higher than estimates of Q for this mode using earthquake data ( Q = 186.9 ± 5). Two microbarographs located at regional distances (<1000 km) to the volcano provide direct observations of the fundamental acoustic mode of the atmosphere. These pressure oscillations, first observed approximately 40 min after the onset of the eruption, are in phase with the seismic Rayleigh wave excitation and are recorded only by microbarographs in proximity (<1500 km) to the eruption. We infer that excitation of fundamental atmospheric modes occurs within a limited area close to the site of the eruption, where they excite select solid Earth fundamental spheroidal modes of similar frequencies that are globally recorded and have a higher apparent Q due to the extended duration of atmospheric oscillations.

Geophysical Journal International↗

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

Characteristics, relationships and precision of direct acoustic-to-seismic coupling measurements from local explosions

Acoustic energy originating from explosions, sonic booms, bolides and thunderclaps have been recorded on seismometers since the 1950s. Direct pressure loading from the passing acoustic wave has been modelled and consistently observed to produce ground deformations of the near surface that have retrograde elliptical particle motions. In the past decade, increased deployments of colocated seismometers and infrasound sensors have driven efforts to use the transfer function between direct acoustic-to-seismic coupling to infer near-surface material properties including seismic velocity structure and elastic moduli. In this study, we use a small aperture (≈600 m) array of broadband seismometers installed in different manners and depths in both granite and sedimentary overburden to understand the fundamental nature and repeatability of seismic excitation from 1 to 15 Hz using horizontally propagating acoustic waves generated by 97 local (2–10 km) explosions. In agreement with modelling, we find that the ground motions induced by acoustic-to-seismic coupling attenuate rapidly with depth. We confirm the modelled relation between acoustic and ground motion amplitudes, but show that within one acoustic wavelength, the uncertainty in the transfer coefficient between seismic and acoustic energy at a given seismic station increases linearly with separation distance between the seismic and acoustic sensor. We attribute this observation to the rapid decorrelation of the infrasonic wavefield across small spatial scales and recommend colocating seismic and infrasound sensors for use in studies seeking to invert for near-surface material properties. Additionally, contrary to acoustic-to-seismic coupling theory and prior observations, we find that seismometers emplaced in granite do not record retrograde elliptical particle motions in response to direct pressure loading. We rule out seismometer tilt effects as a likely source of this observations and suggest that existing models of acoustic-to-seismic excitation may be too simplistic for seismometers placed in high rigidity materials.

Geophysical Journal International↗

USGS2022

Improved resolution across the Global Seismographic Network: A new era in low-frequency seismology

The Global Seismographic Network (GSN)—a global network of ≈150 very broadband stations—is used by researchers to study the free oscillations of the Earth (≈0.3–10 mHz) following large earthquakes. Normal‐mode observations can provide information about the radial density and anisotropic velocity structure of the Earth (including near the core–mantle boundary), but only when signal‐to‐noise ratios at very low frequencies are sufficiently high. Most normal‐mode observations in the past three decades have been made using Streckeisen STS‐1 vault seismometers. However, these sensors are no longer being manufactured or serviced. Candidate replacement sensors, the Streckeisen STS‐6 and the Nanometrics T‐360GSN, have been recently installed in boreholes, postholes, and vaults at several GSN stations and GSN testbeds. In this study, we examine normal‐mode spectra following three M w "> M w 8 earthquakes in 2021 and from one M w "> M w 8.2 earthquake in 2014 to evaluate the change in GSN low‐frequency performance on the vertical component. From this analysis, we conclude that the number of GSN stations capable of resolving normal modes following M w "> M w 8 earthquakes has nearly doubled since 2014. The improved observational capabilities will help better understand the radial velocity and density estimates of the Earth.

The Seismic Record↗

USGS2022

Seismic background noise levels across the continental United States from USArray Transportable Array: The influence of geology and geography

Since 2004, the most complete estimate of background noise levels across the continental U.S. was attained using 61 broadband seismic stations to calculate power spectral density (PSD) probability density functions. To improve seismic noise estimates across the U.S., we examine vertical component seismic data from the EarthScope USArray Transportable Array seismic network that rolled across the U.S. and southeastern Canada between 2004 and 2015 and form a large (10 TB) PSD database from 1679 stations that contains no smoothing or binning of the spectral estimates. Including station outages, our database has a mean of 98.9% data completeness, and we present maps showing the spatial and temporal variability of seismic noise in six bands of interest between 0.2- and 75-s period. At 0.2 s period, seismic noise across the eastern U.S. is predominantly anthropogenically generated and may be subsequently amplified more than 20 decibels in the sandy and water-saturated sediments of the southeastern U.S. Coastal Plain and Mississippi Embayment. In these sediments, 1 s noise shows similar amplification and is generated through a variety of mechanisms including cultural activity throughout Kentucky and the southeastern Appalachian Mountains, lake waves around the Great Lakes, and ocean waves throughout New England, the Pacific Northwest, and Florida. Both 0.2 and 1 s noise levels are the lowest in the Intermountain West portion of the U.S. We attribute this to a combination of installations on crystalline rocks and reduced population density. Finally, we find that sensors emplaced in sandy, water-saturated sediments observe median, diurnal variations in vertical component power at 18 to 75 s period, which we infer arise through local deformation driven by pressure variations. Ultimately, our results underscore that for shallow (<5 m depth) sensor installation, bedrock provides superior broadband noise performance compared to unconsolidated sediments.

Bulletin of the Seismological Society of America↗

USGS2022

Atmospheric waves and global seismoacoustic observations of the January 2022 Hunga eruption, Tonga

The 15 January 2022 climactic eruption of Hunga volcano, Tonga, produced an explosion in the atmosphere of a size that has not been documented in the modern geophysical record. The event generated a broad range of atmospheric waves observed globally by various ground-based and spaceborne instrumentation networks. Most prominent was the surface-guided Lamb wave (≲0.01 hertz), which we observed propagating for four (plus three antipodal) passages around Earth over 6 days. As measured by the Lamb wave amplitudes, the climactic Hunga explosion was comparable in size to that of the 1883 Krakatau eruption. The Hunga eruption produced remarkable globally detected infrasound (0.01 to 20 hertz), long-range (~10,000 kilometers) audible sound, and ionospheric perturbations. Seismometers worldwide recorded pure seismic and air-to-ground coupled waves. Air-to-sea coupling likely contributed to fast-arriving tsunamis. Here, we highlight exceptional observations of the atmospheric waves.

Hunga volcano↗

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↗