David Wilson
David Wilson is the director of the Global Seismographic Network.
Science and Products
Photo Journal: Global Seismographic Network (GSN) Field Engineers Visit the Northernmost Town in the World
In October 2022 GSN field engineers from the Albuquerque Seismic Lab visited the northernmost town in the world, Longyearbyen (Svalbard, Norway) on their way north to GSN station IU-KBS for a station upgrade. GSN station IU-KBS is located in Svalbard, a Norwegian archipelago.
Filter Total Items: 48
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 characteri
Authors
William L. Yeck, Adam T. Ringler, David R. Shelly, Paul S. Earle, Harley M. Benz, David C. Wilson
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 d
Authors
Robert E. Anthony, Nicolas Leroy, Robert Mellors, Adam T. Ringler, Joachim Saul, Martin Vallée, David C. Wilson
Noise constraints on global body‐wave measurement thresholds
Intermediate sized earthquakes (≈M4–6.5) 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 g
Authors
Adam T. Ringler, David C. Wilson, Paul S. Earle, William L. Yeck, David B. Mason, Justin T. Wilgus
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
Authors
Justin T. Wilgus, Adam T. Ringler, Brandon Schmandt, David C. Wilson, Robert E. Anthony
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 Scien
Authors
David C. Wilson, Charles R. Hutt, Lind Gee, Adam T. Ringler, Robert E. Anthony
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
Authors
Adam T. Ringler, Robert E. Anthony, Brian Shiro, Toshiro Tanimoto, David C. Wilson
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
Authors
Robert E. Anthony, Adam T. Ringler, Toshiro Tanimoto, Robin Matoza, Silvio De Angelis, David C. Wilson
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 Seismogr
Authors
Adam T. Ringler, Robert E. Anthony, Rick Aster, T. Taira, Brian Shiro, David C. Wilson, S. H. De Angelis, C. Ebeling, Matthew M. Haney, R. Matoza, H. Ortiz
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 seismomete
Authors
Robert E. Anthony, Josh Watzak, Adam T. Ringler, David C. Wilson
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 prop
Authors
Robin S. Matoza, David Fee, Jelle D. Assink, Alexandra M. Iezzi, David N. Green, Keehoon Kim, Liam Toney, Thomas Lecocq, Siddharth Krishnamoorthy, Jean-Marie Lalande, Kiwamu Nishida, Kent L. Gee, Matthew M. Haney, Hugo D. Ortiz, Quentin Brissaud, Léo Martire, Lucie Rolland, Panagiotis Vergados, Alexandra Nippress, Junghyun Park, Shahar Shani-Kadmiel, Alex Witsil, Stephen Arrowsmith, Corentin Caudron, Shingo Watada, Anna Perttu, Benoit Taisne, Pierrick Mialle, Alexis Le Pichon, Julien Vergoz, Patrick Hupe, Philip S. Blom, Roger M. Waxler, Silvio De Angelis, Jonathan Snively, Adam T. Ringler, Robert E. Anthony, A.D. Jolly, Geoff Kilgour, Gil Averbuch, Maurizio Ripepe, Mie Ichihara, Alejandra Arciniega-Ceballos, Elvira Astafyeva, Lars Ceranna, Sandrine Cevuard, Il-Young Che, Rodrigo de Negri Leiva, Carl W. Ebeling, Läslo G. Evers, Luis E. Franco-Marin, Tom Gabrielson, Katrin Hafner, R. Giles Harrison, Attila Komjathy, Giorgio Lacanna, John J. Lyons, Kenneth A. Macpherson, Emanuele Marchetti, Kathleen McKee, Rob Mellors, Gerardo Mendo-Pérez, T. Dylan Mikesell, Edhah Munaibari, Mayra Oyola-Merced, Iseul Park, Christoph Pilger, Cristina Ramos, Mario Ruiz, Roberto Sabatini, Hans Schwaiger, Dorianne Tailpied, Carrick Talmadge, Jérôme Vidot, Jeremy Webster, David C. Wilson
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
Authors
Nagle Nagle-McNaughton, Adam T. Ringler, Robert E. Anthony, Alexis Casondra Bianca Alejandro, David C. Wilson, Justin Thomas Wilgus
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
Authors
Adam T. Ringler, Robert E. Anthony, P. Thompson Davis, Carl Ebeling, K. Hafner, R. Mellors, S. Schneider, David C. Wilson
Seismic Network Detection Modeling
This DOI points to the code repository for codes used in David C. Wilson, Emily Wolin, William L. Yeck, Robert E. Anthony, Adam T. Ringler; Modeling Seismic Network Detection Thresholds Using Production Picking Algorithms. Seismological Research Letters 2021; 93 1: doi: https://doi.org/10.1785/0220210192
ASL Sensor Test Suite
This program is used to analyze various aspects of seismic sensor data in order to determine information about their configuration, such as gain and orientation.
Science and Products
Photo Journal: Global Seismographic Network (GSN) Field Engineers Visit the Northernmost Town in the World
In October 2022 GSN field engineers from the Albuquerque Seismic Lab visited the northernmost town in the world, Longyearbyen (Svalbard, Norway) on their way north to GSN station IU-KBS for a station upgrade. GSN station IU-KBS is located in Svalbard, a Norwegian archipelago.
Filter Total Items: 48
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 characteri
Authors
William L. Yeck, Adam T. Ringler, David R. Shelly, Paul S. Earle, Harley M. Benz, David C. Wilson
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 d
Authors
Robert E. Anthony, Nicolas Leroy, Robert Mellors, Adam T. Ringler, Joachim Saul, Martin Vallée, David C. Wilson
Noise constraints on global body‐wave measurement thresholds
Intermediate sized earthquakes (≈M4–6.5) 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 g
Authors
Adam T. Ringler, David C. Wilson, Paul S. Earle, William L. Yeck, David B. Mason, Justin T. Wilgus
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
Authors
Justin T. Wilgus, Adam T. Ringler, Brandon Schmandt, David C. Wilson, Robert E. Anthony
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 Scien
Authors
David C. Wilson, Charles R. Hutt, Lind Gee, Adam T. Ringler, Robert E. Anthony
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
Authors
Adam T. Ringler, Robert E. Anthony, Brian Shiro, Toshiro Tanimoto, David C. Wilson
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
Authors
Robert E. Anthony, Adam T. Ringler, Toshiro Tanimoto, Robin Matoza, Silvio De Angelis, David C. Wilson
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 Seismogr
Authors
Adam T. Ringler, Robert E. Anthony, Rick Aster, T. Taira, Brian Shiro, David C. Wilson, S. H. De Angelis, C. Ebeling, Matthew M. Haney, R. Matoza, H. Ortiz
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 seismomete
Authors
Robert E. Anthony, Josh Watzak, Adam T. Ringler, David C. Wilson
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 prop
Authors
Robin S. Matoza, David Fee, Jelle D. Assink, Alexandra M. Iezzi, David N. Green, Keehoon Kim, Liam Toney, Thomas Lecocq, Siddharth Krishnamoorthy, Jean-Marie Lalande, Kiwamu Nishida, Kent L. Gee, Matthew M. Haney, Hugo D. Ortiz, Quentin Brissaud, Léo Martire, Lucie Rolland, Panagiotis Vergados, Alexandra Nippress, Junghyun Park, Shahar Shani-Kadmiel, Alex Witsil, Stephen Arrowsmith, Corentin Caudron, Shingo Watada, Anna Perttu, Benoit Taisne, Pierrick Mialle, Alexis Le Pichon, Julien Vergoz, Patrick Hupe, Philip S. Blom, Roger M. Waxler, Silvio De Angelis, Jonathan Snively, Adam T. Ringler, Robert E. Anthony, A.D. Jolly, Geoff Kilgour, Gil Averbuch, Maurizio Ripepe, Mie Ichihara, Alejandra Arciniega-Ceballos, Elvira Astafyeva, Lars Ceranna, Sandrine Cevuard, Il-Young Che, Rodrigo de Negri Leiva, Carl W. Ebeling, Läslo G. Evers, Luis E. Franco-Marin, Tom Gabrielson, Katrin Hafner, R. Giles Harrison, Attila Komjathy, Giorgio Lacanna, John J. Lyons, Kenneth A. Macpherson, Emanuele Marchetti, Kathleen McKee, Rob Mellors, Gerardo Mendo-Pérez, T. Dylan Mikesell, Edhah Munaibari, Mayra Oyola-Merced, Iseul Park, Christoph Pilger, Cristina Ramos, Mario Ruiz, Roberto Sabatini, Hans Schwaiger, Dorianne Tailpied, Carrick Talmadge, Jérôme Vidot, Jeremy Webster, David C. Wilson
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
Authors
Nagle Nagle-McNaughton, Adam T. Ringler, Robert E. Anthony, Alexis Casondra Bianca Alejandro, David C. Wilson, Justin Thomas Wilgus
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
Authors
Adam T. Ringler, Robert E. Anthony, P. Thompson Davis, Carl Ebeling, K. Hafner, R. Mellors, S. Schneider, David C. Wilson
Seismic Network Detection Modeling
This DOI points to the code repository for codes used in David C. Wilson, Emily Wolin, William L. Yeck, Robert E. Anthony, Adam T. Ringler; Modeling Seismic Network Detection Thresholds Using Production Picking Algorithms. Seismological Research Letters 2021; 93 1: doi: https://doi.org/10.1785/0220210192
ASL Sensor Test Suite
This program is used to analyze various aspects of seismic sensor data in order to determine information about their configuration, such as gain and orientation.