I am a seismologist at the USGS Geologic Hazards Science Center, in Golden, Colorado. Much of my research is focused on operational tools that allow the National Earthquake Information Center to rapidly and accurately detect and model the source characteristics of earthquakes. I use these tools to better understand the seismotectonics of significant events.
Education:
2015 - Ph.D. in Geophysics, University of Colorado at Boulder
2008 - B.S. in Physics, Astronomy-Physics, (Minor in Archeology), University of Wisconsin - Madison
Publications:
Please visit my google scholar page for the most up-to-date list of my publications: Click Here
Science and Products
Improving Earthquake Monitoring with Deep Learning
Release Date: MARCH 12, 2021 On January 20, 2021 at 8:32am light shaking interrupted breakfast customers at a local coffee shop south of downtown Los Angeles, California. Everyone paused briefly while they waited to see if it was going to stop… or start shaking harder.
Supporting Data and Models for Characterizing the February 2023 Kahramanmaraş, Türkiye, Earthquake Sequence
This data release pertains to the February 2023 Kahramanmaraş, Türkiye earthquake sequence and complements the following publication:
Goldberg, D.E. et al. (2023) Rapid Characterization of the February 2023 Kahramanmaraş, Türkiye, Earthquake Sequence, The Seismic Record. (xx), 1, doi: 10.1785/0320230009.
Child Items "2023-02-06 Mw7.8 Pazarcık Earthquake Finite Fault Data and Model" and "2023-02-
Waveform Data and Metadata used to National Earthquake Information Center Deep-Learning Models
These data were used to train the Machine Learning models supporting the USGS software release "NEIC Machine Learning Applications Software" (https://doi.org/10.5066/P9ICQPUR), and its companion publication in Seismological Research Letters "Leveraging Deep Learning in Global 24/7 Real-Time Earthquake Monitoring at the National Earthquake Information Center" (https://doi.org/XXXXX). These data are
Spatiotemporal Analysis of the Foreshock-Mainshock-Aftershock Sequence of the 6 July 2017 M5.8 Lincoln, Montana, Earthquake - Data Release
We used matched filter detection and multiple-event relocation techniques to characterize the spatiotemporal evolution of the sequence. Our analysis is from the 14 closest seismic stations to the earthquake sequence, which included seven permanent stations from the Montana Regional Seismic Network, one permanent station from the ANSS backbone network and three temporary seismic stations deployed b
Earthquake Catalogs supporting manuscript "Afterslip Enhanced Aftershock Activity During the 2017 Earthquake Sequence Near Sulphur Peak, Idaho"
This ScienceBase entry contains three seismic catalogs supporting and described by the manuscript - Koper, K. D., Pankow, K. L., Pechmann, J. C., Hale, J. M., Burlacu, R., Yeck, W. L., et al (2018). Afterslip Enhanced Aftershock Activity During the 2017 Earthquake Sequence Near Sulphur Peak, Idaho. Geophysical Research Letters, 45. https://doi.org/10.1029/2018GL078196. These are included in three
Aftershock Catalog for the November 2011 Prague, Oklahoma Earthquake Sequence
The dataset contains the catalog of 5446 events and arrival times resulting from subspace detection processing and relocation in the for the 2011 Prague, Oklahoma, aftershock sequence. Lines beginning with "E" contain event information in the following order: event ID, origin year, origin month, origin day, origin hour, origin minute, origin second, latitude, longitude, depth, and magnitude. Lines
Filter Total Items: 26
Rapid characterization of the February 2023 Kahramanmaraş, Turkey, earthquake sequence
The 6 February 2023 Mw 7.8 Pazarcık and subsequent Mw 7.5 Elbistan earthquakes generated strong ground shaking that resulted in catastrophic human and economic loss across south‐central Türkiye and northwest Syria. The rapid characterization of the earthquakes, including their location, size, fault geometries, and slip kinematics, is critical to estimate the impact of significant seismic events.
Authors
Dara Elyse Goldberg, Tuncay Taymaz, Nadine G. Reitman, Alexandra Elise Hatem, Seda Yolsal-Çevikbilen, William D. Barnhart, Tahir Serkan Irmak, David J. Wald, Taylan Öcalan, William L. Yeck, Berkan Özkan, Jessica Ann Thompson Jobe, David R. Shelly, Eric M. Thompson, Christopher DuRoss, Paul S. Earle, Richard W. Briggs, Harley M. Benz, Ceyhun Erman, Ali Hasan Doğan, Cemali Altuntaş
Dense geophysical observations reveal a triggered, concurrent multi-fault rupture at the Mendocino Triple Junction
A central question of earthquake science is how far ruptures can jump from one fault to another, because cascading ruptures can increase the shaking of a seismic event. Earthquake science relies on earthquake catalogs and therefore how complex ruptures get documented and cataloged has important implications. Recent investments in geophysical instrumentation allow us to resolve increasingly complex
Authors
William L. Yeck, David R. Shelly, Dara Elyse Goldberg, Kathryn Zerbe Materna, Paul S. Earle
High‐precision characterization of seismicity from the 2022 Hunga Tonga‐Hunga Ha'apai volcanic eruption
The earthquake swarm accompanying the January 2022 Hunga Tonga‐Hunga Ha'apai (HTHH) volcanic eruption includes a large number of posteruptive moderate‐magnitude seismic events and presents a unique opportunity to use remote monitoring methods to characterize and compare seismic activity with other historical caldera‐forming eruptions. We compute improved epicentroid locations, magnitudes, and regi
Authors
Jonas A. Kintner, William L. Yeck, Paul S. Earle, Stephanie Prejean, Jeremy Pesicek
A global catalog of calibrated earthquake locations
We produced a globally distributed catalog of earthquakes and nuclear explosions with calibrated hypocenters, referred to as the Global Catalog of Calibrated Earthquake Locations (GCCEL). This dataset currently contains 18,782 events in 289 clusters with >3.2 million arrival times observed at 19,258 stations. The term “calibrated” refers to the property that the hypocenters are minimally biased by
Authors
Eric A. Bergman, Harley M. Benz, William L. Yeck, Ezgi Karasözen, E. Robert Engdahl, Abdolreza Ghods, Gavin P. Hayes, Paul S. Earle
Beyond the teleseism: Introducing regional seismic and geodetic data into routine USGS finite‐fault modeling
The U.S. Geological Survey (USGS) National Earthquake Information Center (NEIC) routinely produces finite‐fault models following significant earthquakes. These models are spatiotemporal estimates of coseismic slip critical to constraining downstream response products such as ShakeMap ground motion estimates, Prompt Assessment of Global Earthquake for Response loss estimates, and ground failure ass
Authors
Dara Elyse Goldberg, Pablo Koch, Diego Melgar, Sebastian Riquelme, William L. Yeck
Achievements and prospects of global broadband seismographic networks after 30 years of continuous geophysical observations
Global seismographic networks (GSNs) emerged during the late nineteenth and early twentieth centuries, facilitated by seminal international developments in theory, technology, instrumentation, and data exchange. The mid- to late-twentieth century saw the creation of the World-Wide Standardized Seismographic Network (1961) and International Deployment of Accelerometers (1976), which advanced global
Authors
Adam T. Ringler, Robert E. Anthony, R. C. Aster, C. J. Ammon, S. Arrowsmith, Harley M. Benz, C. Ebeling, A. Frassetto, W. Y. Kim, Paula Koelemeijer, H. C. P. Lau, V. Lekic, J. P. Montagner, P. G. Richards, D. P. Schaff, M. Vallee, William L. Yeck
Seismotectonic analysis of the 2019–2020 Puerto Rico sequence: The value of absolute earthquake relocations in improved interpretations of active tectonics
We present a new catalog of calibrated earthquake relocations from the 2019–2020 Puerto Rico earthquake sequence related to the 7 January 2020 Mw 6.4 earthquake that occurred offshore of southwest Puerto Rico at a depth of 15.9 km. Utilizing these relocated earthquakes and associated moment tensor solutions, we can delineate several distinct fault systems that were activated during the sequence an
Authors
C.W. Cromwell, K.P. Furlong, E.A. Bergman, Harley M. Benz, William L. Yeck, M. Herman
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 predic
Authors
David C. Wilson, Emily Wolin, William L. Yeck, Robert E. Anthony, Adam T. Ringler
A big problem for small earthquakes: Benchmarking routine magnitudes and conversion relationships with coda-envelope-derived Mw in southern Kansas and northern Oklahoma
Earthquake magnitudes are widely relied upon measures of earthquake size. Although moment magnitude (MwMw) has become the established standard for moderate and large earthquakes, difficulty in reliably measuring seismic moments for small (generally Mw<4Mw<4) earthquakes has meant that magnitudes for these events remain plagued by a patchwork of inconsistent measurement scales. Because of this,
Authors
David R. Shelly, Kevin Mayeda, Justin Barno, Katherine M. Whidden, Morgan P. Moschetti, Andrea L. Llenos, Justin Rubinstein, William L. Yeck, Paul S. Earle, Rengin Gök, William R. Walter
Seismic monitoring during crises at the NEIC in support of the ANSS
Over the past two decades, the U.S. Geological Survey (USGS) National Earthquake Information Center (NEIC) has overcome many operational challenges. These range from minor disruptions, such as power outages, to significant operational changes, including system reconfiguration to handle unique earthquake sequences and the need to handle distributed work during a pandemic. Our ability to overcome cr
Authors
Paul S. Earle, Harley M. Benz, William L. Yeck, Gavin P. Hayes, Michelle Guy, John Patton, David Kragness, David B. Mason, Brian Shiro, Emily Wolin, John Bellini, Jana Pursley, Robert Lorne Sanders
Leveraging deep learning in global 24/7 real-time earthquake monitoring at the National Earthquake Information Center
Machine‐learning algorithms continue to show promise in their application to seismic processing. The U.S. Geological Survey National Earthquake Information Center (NEIC) is exploring the adoption of these tools to aid in simultaneous local, regional, and global real‐time earthquake monitoring. As a first step, we describe a simple framework to incorporate deep‐learning tools into NEIC operations.
Authors
William L. Yeck, John Patton, Zachary E. Ross, Gavin P. Hayes, Michelle Guy, Nicholas Ambruz, David R. Shelly, Harley M. Benz, Paul S. Earle
National earthquake information center strategic plan, 2019–23
Executive SummaryDamaging earthquakes occur regularly around the world; since the turn of the 20th century, hundreds of earthquakes have caused significant loss of life and (or) millions of dollars or more in economic losses. While most of these did not directly affect the United States and its Territories, by studying worldwide seismicity we can better understand how to mitigate the effects of ea
Authors
Gavin P. Hayes, Paul S. Earle, Harley M. Benz, David J. Wald, William L. Yeck
SYNthetic DEPTH Phase Modeling (SYNDEPTH)
This python code models event depths by comparing high-frequency (~0.5-0.04 Hz) teleseismic body-wave waveforms to synthetics. High-frequency body waves contain depth information, primarily in the form of depth phases. While lower frequencies are used to generate moment tensor solutions, high-frequency body waves allow for more accurate estimates of source depth. A moment tensor solution must exis
neic-machine-learning
NEIC Machine Learning Applications contains various seismic machine learning algorithms developed and used by by the United States Geological Survey, National Earthquake Information Center. These algorithms apply machine learning techniques to seismic processing problems such as seismic phase classification, source-receiver distance classification, and seismic wave arrival time repicking.
neic-glass3
neic-glass3 is an open source and platform independent seismic event detection and association algorithm developed by the United States Geological Survey (USGS) National Earthquake Information Center (NEIC) and Caryl Erin Johnson, PhD, Introspective Systems LLC.
This algorithm converts a time series of seismic phase arrival times, back azimuth estimates from array beams, and cross-correlated de
Science and Products
- Science
Improving Earthquake Monitoring with Deep Learning
Release Date: MARCH 12, 2021 On January 20, 2021 at 8:32am light shaking interrupted breakfast customers at a local coffee shop south of downtown Los Angeles, California. Everyone paused briefly while they waited to see if it was going to stop… or start shaking harder. - Data
Supporting Data and Models for Characterizing the February 2023 Kahramanmaraş, Türkiye, Earthquake Sequence
This data release pertains to the February 2023 Kahramanmaraş, Türkiye earthquake sequence and complements the following publication: Goldberg, D.E. et al. (2023) Rapid Characterization of the February 2023 Kahramanmaraş, Türkiye, Earthquake Sequence, The Seismic Record. (xx), 1, doi: 10.1785/0320230009. Child Items "2023-02-06 Mw7.8 Pazarcık Earthquake Finite Fault Data and Model" and "2023-02-Waveform Data and Metadata used to National Earthquake Information Center Deep-Learning Models
These data were used to train the Machine Learning models supporting the USGS software release "NEIC Machine Learning Applications Software" (https://doi.org/10.5066/P9ICQPUR), and its companion publication in Seismological Research Letters "Leveraging Deep Learning in Global 24/7 Real-Time Earthquake Monitoring at the National Earthquake Information Center" (https://doi.org/XXXXX). These data areSpatiotemporal Analysis of the Foreshock-Mainshock-Aftershock Sequence of the 6 July 2017 M5.8 Lincoln, Montana, Earthquake - Data Release
We used matched filter detection and multiple-event relocation techniques to characterize the spatiotemporal evolution of the sequence. Our analysis is from the 14 closest seismic stations to the earthquake sequence, which included seven permanent stations from the Montana Regional Seismic Network, one permanent station from the ANSS backbone network and three temporary seismic stations deployed bEarthquake Catalogs supporting manuscript "Afterslip Enhanced Aftershock Activity During the 2017 Earthquake Sequence Near Sulphur Peak, Idaho"
This ScienceBase entry contains three seismic catalogs supporting and described by the manuscript - Koper, K. D., Pankow, K. L., Pechmann, J. C., Hale, J. M., Burlacu, R., Yeck, W. L., et al (2018). Afterslip Enhanced Aftershock Activity During the 2017 Earthquake Sequence Near Sulphur Peak, Idaho. Geophysical Research Letters, 45. https://doi.org/10.1029/2018GL078196. These are included in threeAftershock Catalog for the November 2011 Prague, Oklahoma Earthquake Sequence
The dataset contains the catalog of 5446 events and arrival times resulting from subspace detection processing and relocation in the for the 2011 Prague, Oklahoma, aftershock sequence. Lines beginning with "E" contain event information in the following order: event ID, origin year, origin month, origin day, origin hour, origin minute, origin second, latitude, longitude, depth, and magnitude. Lines - Publications
Filter Total Items: 26
Rapid characterization of the February 2023 Kahramanmaraş, Turkey, earthquake sequence
The 6 February 2023 Mw 7.8 Pazarcık and subsequent Mw 7.5 Elbistan earthquakes generated strong ground shaking that resulted in catastrophic human and economic loss across south‐central Türkiye and northwest Syria. The rapid characterization of the earthquakes, including their location, size, fault geometries, and slip kinematics, is critical to estimate the impact of significant seismic events.AuthorsDara Elyse Goldberg, Tuncay Taymaz, Nadine G. Reitman, Alexandra Elise Hatem, Seda Yolsal-Çevikbilen, William D. Barnhart, Tahir Serkan Irmak, David J. Wald, Taylan Öcalan, William L. Yeck, Berkan Özkan, Jessica Ann Thompson Jobe, David R. Shelly, Eric M. Thompson, Christopher DuRoss, Paul S. Earle, Richard W. Briggs, Harley M. Benz, Ceyhun Erman, Ali Hasan Doğan, Cemali AltuntaşDense geophysical observations reveal a triggered, concurrent multi-fault rupture at the Mendocino Triple Junction
A central question of earthquake science is how far ruptures can jump from one fault to another, because cascading ruptures can increase the shaking of a seismic event. Earthquake science relies on earthquake catalogs and therefore how complex ruptures get documented and cataloged has important implications. Recent investments in geophysical instrumentation allow us to resolve increasingly complexAuthorsWilliam L. Yeck, David R. Shelly, Dara Elyse Goldberg, Kathryn Zerbe Materna, Paul S. EarleHigh‐precision characterization of seismicity from the 2022 Hunga Tonga‐Hunga Ha'apai volcanic eruption
The earthquake swarm accompanying the January 2022 Hunga Tonga‐Hunga Ha'apai (HTHH) volcanic eruption includes a large number of posteruptive moderate‐magnitude seismic events and presents a unique opportunity to use remote monitoring methods to characterize and compare seismic activity with other historical caldera‐forming eruptions. We compute improved epicentroid locations, magnitudes, and regiAuthorsJonas A. Kintner, William L. Yeck, Paul S. Earle, Stephanie Prejean, Jeremy PesicekA global catalog of calibrated earthquake locations
We produced a globally distributed catalog of earthquakes and nuclear explosions with calibrated hypocenters, referred to as the Global Catalog of Calibrated Earthquake Locations (GCCEL). This dataset currently contains 18,782 events in 289 clusters with >3.2 million arrival times observed at 19,258 stations. The term “calibrated” refers to the property that the hypocenters are minimally biased byAuthorsEric A. Bergman, Harley M. Benz, William L. Yeck, Ezgi Karasözen, E. Robert Engdahl, Abdolreza Ghods, Gavin P. Hayes, Paul S. EarleBeyond the teleseism: Introducing regional seismic and geodetic data into routine USGS finite‐fault modeling
The U.S. Geological Survey (USGS) National Earthquake Information Center (NEIC) routinely produces finite‐fault models following significant earthquakes. These models are spatiotemporal estimates of coseismic slip critical to constraining downstream response products such as ShakeMap ground motion estimates, Prompt Assessment of Global Earthquake for Response loss estimates, and ground failure assAuthorsDara Elyse Goldberg, Pablo Koch, Diego Melgar, Sebastian Riquelme, William L. YeckAchievements and prospects of global broadband seismographic networks after 30 years of continuous geophysical observations
Global seismographic networks (GSNs) emerged during the late nineteenth and early twentieth centuries, facilitated by seminal international developments in theory, technology, instrumentation, and data exchange. The mid- to late-twentieth century saw the creation of the World-Wide Standardized Seismographic Network (1961) and International Deployment of Accelerometers (1976), which advanced globalAuthorsAdam T. Ringler, Robert E. Anthony, R. C. Aster, C. J. Ammon, S. Arrowsmith, Harley M. Benz, C. Ebeling, A. Frassetto, W. Y. Kim, Paula Koelemeijer, H. C. P. Lau, V. Lekic, J. P. Montagner, P. G. Richards, D. P. Schaff, M. Vallee, William L. YeckSeismotectonic analysis of the 2019–2020 Puerto Rico sequence: The value of absolute earthquake relocations in improved interpretations of active tectonics
We present a new catalog of calibrated earthquake relocations from the 2019–2020 Puerto Rico earthquake sequence related to the 7 January 2020 Mw 6.4 earthquake that occurred offshore of southwest Puerto Rico at a depth of 15.9 km. Utilizing these relocated earthquakes and associated moment tensor solutions, we can delineate several distinct fault systems that were activated during the sequence anAuthorsC.W. Cromwell, K.P. Furlong, E.A. Bergman, Harley M. Benz, William L. Yeck, M. HermanModeling 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 predicAuthorsDavid C. Wilson, Emily Wolin, William L. Yeck, Robert E. Anthony, Adam T. RinglerA big problem for small earthquakes: Benchmarking routine magnitudes and conversion relationships with coda-envelope-derived Mw in southern Kansas and northern Oklahoma
Earthquake magnitudes are widely relied upon measures of earthquake size. Although moment magnitude (MwMw) has become the established standard for moderate and large earthquakes, difficulty in reliably measuring seismic moments for small (generally Mw<4Mw<4) earthquakes has meant that magnitudes for these events remain plagued by a patchwork of inconsistent measurement scales. Because of this,AuthorsDavid R. Shelly, Kevin Mayeda, Justin Barno, Katherine M. Whidden, Morgan P. Moschetti, Andrea L. Llenos, Justin Rubinstein, William L. Yeck, Paul S. Earle, Rengin Gök, William R. WalterSeismic monitoring during crises at the NEIC in support of the ANSS
Over the past two decades, the U.S. Geological Survey (USGS) National Earthquake Information Center (NEIC) has overcome many operational challenges. These range from minor disruptions, such as power outages, to significant operational changes, including system reconfiguration to handle unique earthquake sequences and the need to handle distributed work during a pandemic. Our ability to overcome cr
AuthorsPaul S. Earle, Harley M. Benz, William L. Yeck, Gavin P. Hayes, Michelle Guy, John Patton, David Kragness, David B. Mason, Brian Shiro, Emily Wolin, John Bellini, Jana Pursley, Robert Lorne SandersLeveraging deep learning in global 24/7 real-time earthquake monitoring at the National Earthquake Information Center
Machine‐learning algorithms continue to show promise in their application to seismic processing. The U.S. Geological Survey National Earthquake Information Center (NEIC) is exploring the adoption of these tools to aid in simultaneous local, regional, and global real‐time earthquake monitoring. As a first step, we describe a simple framework to incorporate deep‐learning tools into NEIC operations.AuthorsWilliam L. Yeck, John Patton, Zachary E. Ross, Gavin P. Hayes, Michelle Guy, Nicholas Ambruz, David R. Shelly, Harley M. Benz, Paul S. EarleNational earthquake information center strategic plan, 2019–23
Executive SummaryDamaging earthquakes occur regularly around the world; since the turn of the 20th century, hundreds of earthquakes have caused significant loss of life and (or) millions of dollars or more in economic losses. While most of these did not directly affect the United States and its Territories, by studying worldwide seismicity we can better understand how to mitigate the effects of eaAuthorsGavin P. Hayes, Paul S. Earle, Harley M. Benz, David J. Wald, William L. Yeck - Software
SYNthetic DEPTH Phase Modeling (SYNDEPTH)
This python code models event depths by comparing high-frequency (~0.5-0.04 Hz) teleseismic body-wave waveforms to synthetics. High-frequency body waves contain depth information, primarily in the form of depth phases. While lower frequencies are used to generate moment tensor solutions, high-frequency body waves allow for more accurate estimates of source depth. A moment tensor solution must exisneic-machine-learning
NEIC Machine Learning Applications contains various seismic machine learning algorithms developed and used by by the United States Geological Survey, National Earthquake Information Center. These algorithms apply machine learning techniques to seismic processing problems such as seismic phase classification, source-receiver distance classification, and seismic wave arrival time repicking.neic-glass3
neic-glass3 is an open source and platform independent seismic event detection and association algorithm developed by the United States Geological Survey (USGS) National Earthquake Information Center (NEIC) and Caryl Erin Johnson, PhD, Introspective Systems LLC. This algorithm converts a time series of seismic phase arrival times, back azimuth estimates from array beams, and cross-correlated de