Andrea Llenos
I am a research geophysicist whose research focuses on developing earthquake rate models for seismic hazard forecasts. I use statistical methods to characterize earthquake rate changes in catalogs, investigating the impacts these variations have on short-term earthquake forecasts as well as long-term seismic hazard models.
Professional Experience
Research Geophysicist, US Geological Survey, Geologic Hazards Science Center, Golden, CO. 2020-present
Research Geophysicist (term), US Geological Survey, Earthquake Science Center, Menlo Park/Moffett Field, CA . 2015-2020
Mendenhall Postdoctoral Fellow, US Geological Survey, Earthquake Science Center, Menlo Park, CA. 2011-2015
Postdoctoral Scholar, Stanford University, Stanford, CA. 2010-2011
Graduate Research Assistant, Woods Hole Oceanographic Institution, Woods Hole, MA. 2004-2010
Visiting Researcher, Institute of Statistical Mathematics, Tokyo, Japan. 2008, 2009
Undergraduate Research Assistant, Dept. of Geo. Sci., Brown University, Providence, RI. 2002-2004
NSF-REU Intern, University of Alaska Fairbanks, Geophysical Institute, Fairbanks, AK. 2003
Undergraduate Research Assistant, Planetary Geosci., Brown University, Providence, RI. 2001
Fellowships and Awards
Excellent Reviewer Award for Earth, Planets and Space. 2019
Editors' Citation for Excellence in Refereeing for Geophysical Research Letters. 2016
USGS Mendenhall Postdoctoral Fellowship. 2011-2013
National Defense Science and Engineering Graduate Fellowship. 2005-2008
Hollister Fellowship, Woods Hole Oceanographic Institution. 2004-2005
Outstanding Student Award (in Mechanical Engineering). 2004
Undergraduate Research and Academics Award (in Geological Science). 2004
Education and Certifications
PhD, 2010, Marine Geophysics, MIT/Woods Hole Oceanographic Institution Joint Program in Oceanography
ScB, 2004, Geology-Physics/Mathematics (with honors), Brown University, magna cum laude
ScB, 2004, Engineering (Mechanical), Brown University
Science and Products
Understanding Fluid Injection Induced Seismicity
Fluid injection induced seismicity has been reported since the 1960s. There are currently more than 150,000 injection wells associated with oil and gas production in 34 states in the conterminous US. Pore pressure disturbance caused by injection is generally considered the culprit for injection induced seismicity, but, not all injection causes seismicity. It is not well understood what...
Data Release for the The 2023 Alaska National Seismic Hazard Model
The U.S. National Seismic Hazard Model (NSHM) for the state of Alaska was updated in 2023 as part of the 50-state NSHM update. The new model incorporates more than 15 years of additional science since the release of the previous model in 2007 and has been reviewed by a six-member review panel and a supplementary eight-member team of ground motion model developers. This time-independent...
Data Release for the 2023 U.S. 50-State National Seismic Hazard Model - Overview
This data release contains data sets associated with the 2023 50-State National Seismic Hazard Model Update. The 2023 50-State National Seimsic Hazard Model (NSHM) Update includes an update to the NSHMs for the conterminous U.S (CONUS, last updated in 2018), Alaska (AK, last updated in 2007), and Hawaii (last updated in 2001). Data sets include inputs like seismicity catalogs used as...
Data Release for Latency Testing of Wireless Emergency Alerts intended for the ShakeAlert earthquake early warning system for the West Coast of the United States of America
ShakeAlert, the earthquake early warning (EEW) system for the West Coast of the United States, attempts to provides crucial warnings before strong shaking occurs. However, because the alerts are triggered only when an earthquake is already in progress, and the alert latencies and delivery times are platform dependent, the time between these warnings and the arrival of shaking is variable...
2017 One-Year Seismic Hazard Forecast for the Central and Eastern United States from Induced and Natural Earthquakes
We produced a one-year 2017 seismic hazard forecast for the central and eastern United States from induced and natural earthquakes that replaces the one-year 2016 forecast, and evaluated the 2016 seismic hazard forecast to improve future assessments. The 2016 forecast indicated high seismic hazard (greater than 1% probability of damaging ground shaking in 1 year) in portions of Oklahoma...
2016 One-Year Seismic Hazard Forecast for the Central and Eastern United States from Induced and Natural Earthquakes
A one-year seismic hazard forecast for the Central and Eastern United States (CEUS), based on induced and natural earthquakes, has been produced by the U.S. Geological Survey. The model assumes that earthquake rates calculated from several different time windows will remain relatively stationary and can be used to forecast earthquake hazard and damage intensity for the year 2016. This...
Filter Total Items: 25
Aftershock forecasting
Aftershocks can compound the impacts of a major earthquake, disrupting recovery efforts and potentially further damaging weakened buildings and infrastructure. Forecasts of the probability of aftershocks can therefore aid decision-making during earthquake response and recovery. Several countries issue authoritative aftershock forecasts. Most aftershock forecasts are based on simple...
Authors
Jeanne L. Hardebeck, Andrea L. Llenos, Andrew J. Michael, Morgan T. Page, Max Schneider, Nicholas van der Elst
Forecasting the long-term spatial distribution of earthquakes for the 2023 US National Seismic Hazard Model using gridded seismicity
Probabilistic seismic hazard analyses such as the U.S. National Seismic Hazard Model (NSHM) typically rely on declustering and spatially smoothing an earthquake catalog to estimate a long‐term time‐independent (background) seismicity rate to forecast future seismicity. In support of the U.S. Geological Survey’s (USGS) 2023 update to the NSHM, we update the methods used to develop this...
Authors
Andrea L. Llenos, Andrew J. Michael, Allison Shumway, Justin Rubinstein, Kirstie Lafon Haynie, Morgan P. Moschetti, Jason M. Altekruse, Kevin R. Milner
The 2023 US 50-State National Seismic Hazard Model: Overview and implications
The US National Seismic Hazard Model (NSHM) was updated in 2023 for all 50 states using new science on seismicity, fault ruptures, ground motions, and probabilistic techniques to produce a standard of practice for public policy and other engineering applications (defined for return periods greater than ∼475 or less than ∼10,000 years). Changes in 2023 time-independent seismic hazard...
Authors
Mark D. Petersen, Allison Shumway, Peter M. Powers, Ned Field, Morgan P. Moschetti, Kishor S. Jaiswal, Kevin R. Milner, Sanaz Rezaeian, Arthur Frankel, Andrea L. Llenos, Andrew J. Michael, Jason M. Altekruse, Sean Kamran Ahdi, Kyle Withers, Charles Mueller, Yuehua Zeng, Robert E. Chase, Leah M. Salditch, Nico Luco, Kenneth S. Rukstales, Julie Herrick, Demi Leafar Girot, Brad T. Aagaard, Adrian Bender, Michael L. Blanpied, Richard W. Briggs, Oliver S. Boyd, Brandon Clayton, Christopher DuRoss, Eileen L. Evans, Peter J. Haeussler, Alexandra Elise Hatem, Kirstie Lafon Haynie, Elizabeth H. Hearn, Kaj M. Johnson, Zachary Alan Kortum, N. Simon Kwong, Andrew James Makdisi, Henry (Ben) Mason, Daniel McNamara, Devin McPhillips, P. Okubo, Morgan T. Page, Frederick Pollitz, Justin Rubinstein, Bruce E. Shaw, Zheng-Kang Shen, Brian Shiro, James Andrew Smith, William J. Stephenson, Eric M. Thompson, Jessica Ann Thompson Jobe, Erin Wirth, Robert C. Witter
The USGS 2023 Conterminous U.S. time‐independent earthquake rupture forecast
We present the 2023 U.S. Geological Survey time‐independent earthquake rupture forecast for the conterminous United States, which gives authoritative estimates of the magnitude, location, and time‐averaged frequency of potentially damaging earthquakes throughout the region. In addition to updating virtually all model components, a major focus has been to provide a better representation...
Authors
Ned Field, Kevin R. Milner, Alexandra Elise Hatem, Peter M. Powers, Frederick Pollitz, Andrea L. Llenos, Yuehua Zeng, Kaj M. Johnson, Bruce E. Shaw, Devin McPhillips, Jessica Ann Thompson Jobe, Allison Shumway, Andrew J. Michael, Zheng-Kang Shen, Eileen L. Evans, Elizabeth H. Hearn, Charles Mueller, Arthur Frankel, Mark D. Petersen, Christopher DuRoss, Richard W. Briggs, Morgan T. Page, Justin Rubinstein, Julie Herrick
Latency and geofence testing of wireless emergency alerts intended for the ShakeAlert® earthquake early warning system for the West Coast of the United States of America
ShakeAlert, the earthquake early warning (EEW) system for the West Coast of the United States, attempts to provides crucial warnings before strong shaking occurs. However, because the alerts are triggered only when an earthquake is already in progress, and the alert latencies and delivery times are platform dependent, the time between these warnings and the arrival of shaking is variable...
Authors
Sara McBride, Danielle Sumy, Andrea L. Llenos, Grace Alexandra Parker, Jeffrey McGuire, Jessie Kate Saunders, Men-Andrin Meier, Pascal Schuback, Douglas D. Given, Robert Michael deGroot
An efficient, analytic solution using order statistics for probabilistic seismic‐hazard assessment without the Poisson assumption
Standard approaches to probabilistic seismic‐hazard assessment (PSHA) assume that earthquakes are random, independent events that follow a Poisson distribution of occurrences in a given time period (Cornell, 1968). To overcome the limitations of the Poisson assumption, such as ignoring earthquake clustering, we introduce an analytic method for PSHA that uses order statistics to allow for...
Authors
Andrew J. Michael, Andrea L. Llenos
Modeling the occurrence of M ∼ 5 caldera collapse-related earthquakes in Kīlauea volcano, Hawai'i
During the 2018 Kīlauea eruption and caldera collapse, M ∼ 5 caldera collapse earthquakes occurred almost daily from mid-May until the beginning of August. While caldera collapses happen infrequently, the collapse-related seismicity damaged nearby structures, and so these events should be included in a complete seismic hazard assessment. Here, we present an approach to forecast the...
Authors
Andrea L. Llenos, Andrew J. Michael
2021 U.S. National Seismic Hazard Model for the State of Hawaii
The 2021 U.S. National Seismic Hazard Model (NSHM) for the State of Hawaii updates the two-decades-old former model by incorporating new data and modeling techniques to improve the underlying ground shaking forecasts of tectonic-fault, tectonic-flexure, volcanic, and caldera collapse earthquakes. Two earthquake ground shaking hazard models (public policy and research) are produced that...
Authors
Mark D. Petersen, Allison Shumway, Peter M. Powers, Morgan P. Moschetti, Andrea L. Llenos, Andrew J. Michael, Charles Mueller, Arthur Frankel, Sanaz Rezaeian, Kenneth S. Rukstales, Daniel E. McNamara, P. Okubo, Yuehua Zeng, Kishor S. Jaiswal, Sean Kamran Ahdi, Jason M. Altekruse, Brian Shiro
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
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
Regionally Optimized Background Earthquake Rates from ETAS (ROBERE) for probabilistic seismic hazard assessment
We use an epidemic‐type aftershock sequence (ETAS) based approach to develop a regionally optimized background earthquake rates from ETAS (ROBERE) method for probabilistic seismic hazard assessment. ROBERE fits parameters to the full seismicity catalog for a region with maximum‐likelihood estimation, including uncertainty. It then averages the earthquake rates over a suite of catalogs...
Authors
Andrea L. Llenos, Andrew J. Michael
#EarthquakeAdvisory: Exploring discourse between government officials, news media and social media during the Bombay Beach 2016 Swarm
Communicating probabilities of natural hazards to varied audiences is a notoriously difficult task. Many of these challenges were encountered during the 2016 Bombay Beach, California, swarm of ~100 2≤M≤4.3 earthquakes, which began on 26 September 2016 and lasted for several days. The swarm’s proximity to the southern end of the San Andreas fault caused concern that a larger earthquake...
Authors
Sara McBride, Andrea L. Llenos, Morgan T. Page, Nicholas van der Elst
Ensembles of ETAS models provide optimal operational earthquake forecasting during swarms: Insights from the 2015 San Ramon, California swarm
Earthquake swarms, typically modeled as time-varying changes in background seismicity that are driven by external processes such as fluid flow or aseismic creep, present challenges for operational earthquake forecasting. While the time decay of aftershock sequences can be estimated with the modified Omori law, it is difficult to forecast the temporal behavior of seismicity rates during a...
Authors
Andrea L. Llenos, Andrew J. Michael
Non-USGS Publications**
Segall, P., A. L. Llenos, S.-H. Yun, A. M. Bradley, and E. M. Syracuse (2013), Time-dependent dike propagation from joint inversion of seismicity and deformation data, J. Geophys. Res. Solid Earth, 118, doi: 10.1002/2013JB010251.
Llenos, A. L., and J. J. McGuire (2011), Detecting aseismic strain transients from seismicity data, J. Geophys. Res., 116, B06305, doi: 10.1029/2010JB007537.
Llenos, A. L., J. J. McGuire, and Y. Ogata (2009), Modeling seismic swarms triggered by aseismic transients, Earth Planet. Sci. Lett., 281, 59-69, doi:10.1016/j.epsl.2009.02.011.
Llenos, A. L., and J. J. McGuire (2007), Influence of fore-arc structure on the extent of great subduction zone earthquakes, J. Geophys. Res., 112, B09301, doi: 10.1029/2007JB004944.
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.
Science and Products
Understanding Fluid Injection Induced Seismicity
Fluid injection induced seismicity has been reported since the 1960s. There are currently more than 150,000 injection wells associated with oil and gas production in 34 states in the conterminous US. Pore pressure disturbance caused by injection is generally considered the culprit for injection induced seismicity, but, not all injection causes seismicity. It is not well understood what...
Data Release for the The 2023 Alaska National Seismic Hazard Model
The U.S. National Seismic Hazard Model (NSHM) for the state of Alaska was updated in 2023 as part of the 50-state NSHM update. The new model incorporates more than 15 years of additional science since the release of the previous model in 2007 and has been reviewed by a six-member review panel and a supplementary eight-member team of ground motion model developers. This time-independent...
Data Release for the 2023 U.S. 50-State National Seismic Hazard Model - Overview
This data release contains data sets associated with the 2023 50-State National Seismic Hazard Model Update. The 2023 50-State National Seimsic Hazard Model (NSHM) Update includes an update to the NSHMs for the conterminous U.S (CONUS, last updated in 2018), Alaska (AK, last updated in 2007), and Hawaii (last updated in 2001). Data sets include inputs like seismicity catalogs used as...
Data Release for Latency Testing of Wireless Emergency Alerts intended for the ShakeAlert earthquake early warning system for the West Coast of the United States of America
ShakeAlert, the earthquake early warning (EEW) system for the West Coast of the United States, attempts to provides crucial warnings before strong shaking occurs. However, because the alerts are triggered only when an earthquake is already in progress, and the alert latencies and delivery times are platform dependent, the time between these warnings and the arrival of shaking is variable...
2017 One-Year Seismic Hazard Forecast for the Central and Eastern United States from Induced and Natural Earthquakes
We produced a one-year 2017 seismic hazard forecast for the central and eastern United States from induced and natural earthquakes that replaces the one-year 2016 forecast, and evaluated the 2016 seismic hazard forecast to improve future assessments. The 2016 forecast indicated high seismic hazard (greater than 1% probability of damaging ground shaking in 1 year) in portions of Oklahoma...
2016 One-Year Seismic Hazard Forecast for the Central and Eastern United States from Induced and Natural Earthquakes
A one-year seismic hazard forecast for the Central and Eastern United States (CEUS), based on induced and natural earthquakes, has been produced by the U.S. Geological Survey. The model assumes that earthquake rates calculated from several different time windows will remain relatively stationary and can be used to forecast earthquake hazard and damage intensity for the year 2016. This...
Filter Total Items: 25
Aftershock forecasting
Aftershocks can compound the impacts of a major earthquake, disrupting recovery efforts and potentially further damaging weakened buildings and infrastructure. Forecasts of the probability of aftershocks can therefore aid decision-making during earthquake response and recovery. Several countries issue authoritative aftershock forecasts. Most aftershock forecasts are based on simple...
Authors
Jeanne L. Hardebeck, Andrea L. Llenos, Andrew J. Michael, Morgan T. Page, Max Schneider, Nicholas van der Elst
Forecasting the long-term spatial distribution of earthquakes for the 2023 US National Seismic Hazard Model using gridded seismicity
Probabilistic seismic hazard analyses such as the U.S. National Seismic Hazard Model (NSHM) typically rely on declustering and spatially smoothing an earthquake catalog to estimate a long‐term time‐independent (background) seismicity rate to forecast future seismicity. In support of the U.S. Geological Survey’s (USGS) 2023 update to the NSHM, we update the methods used to develop this...
Authors
Andrea L. Llenos, Andrew J. Michael, Allison Shumway, Justin Rubinstein, Kirstie Lafon Haynie, Morgan P. Moschetti, Jason M. Altekruse, Kevin R. Milner
The 2023 US 50-State National Seismic Hazard Model: Overview and implications
The US National Seismic Hazard Model (NSHM) was updated in 2023 for all 50 states using new science on seismicity, fault ruptures, ground motions, and probabilistic techniques to produce a standard of practice for public policy and other engineering applications (defined for return periods greater than ∼475 or less than ∼10,000 years). Changes in 2023 time-independent seismic hazard...
Authors
Mark D. Petersen, Allison Shumway, Peter M. Powers, Ned Field, Morgan P. Moschetti, Kishor S. Jaiswal, Kevin R. Milner, Sanaz Rezaeian, Arthur Frankel, Andrea L. Llenos, Andrew J. Michael, Jason M. Altekruse, Sean Kamran Ahdi, Kyle Withers, Charles Mueller, Yuehua Zeng, Robert E. Chase, Leah M. Salditch, Nico Luco, Kenneth S. Rukstales, Julie Herrick, Demi Leafar Girot, Brad T. Aagaard, Adrian Bender, Michael L. Blanpied, Richard W. Briggs, Oliver S. Boyd, Brandon Clayton, Christopher DuRoss, Eileen L. Evans, Peter J. Haeussler, Alexandra Elise Hatem, Kirstie Lafon Haynie, Elizabeth H. Hearn, Kaj M. Johnson, Zachary Alan Kortum, N. Simon Kwong, Andrew James Makdisi, Henry (Ben) Mason, Daniel McNamara, Devin McPhillips, P. Okubo, Morgan T. Page, Frederick Pollitz, Justin Rubinstein, Bruce E. Shaw, Zheng-Kang Shen, Brian Shiro, James Andrew Smith, William J. Stephenson, Eric M. Thompson, Jessica Ann Thompson Jobe, Erin Wirth, Robert C. Witter
The USGS 2023 Conterminous U.S. time‐independent earthquake rupture forecast
We present the 2023 U.S. Geological Survey time‐independent earthquake rupture forecast for the conterminous United States, which gives authoritative estimates of the magnitude, location, and time‐averaged frequency of potentially damaging earthquakes throughout the region. In addition to updating virtually all model components, a major focus has been to provide a better representation...
Authors
Ned Field, Kevin R. Milner, Alexandra Elise Hatem, Peter M. Powers, Frederick Pollitz, Andrea L. Llenos, Yuehua Zeng, Kaj M. Johnson, Bruce E. Shaw, Devin McPhillips, Jessica Ann Thompson Jobe, Allison Shumway, Andrew J. Michael, Zheng-Kang Shen, Eileen L. Evans, Elizabeth H. Hearn, Charles Mueller, Arthur Frankel, Mark D. Petersen, Christopher DuRoss, Richard W. Briggs, Morgan T. Page, Justin Rubinstein, Julie Herrick
Latency and geofence testing of wireless emergency alerts intended for the ShakeAlert® earthquake early warning system for the West Coast of the United States of America
ShakeAlert, the earthquake early warning (EEW) system for the West Coast of the United States, attempts to provides crucial warnings before strong shaking occurs. However, because the alerts are triggered only when an earthquake is already in progress, and the alert latencies and delivery times are platform dependent, the time between these warnings and the arrival of shaking is variable...
Authors
Sara McBride, Danielle Sumy, Andrea L. Llenos, Grace Alexandra Parker, Jeffrey McGuire, Jessie Kate Saunders, Men-Andrin Meier, Pascal Schuback, Douglas D. Given, Robert Michael deGroot
An efficient, analytic solution using order statistics for probabilistic seismic‐hazard assessment without the Poisson assumption
Standard approaches to probabilistic seismic‐hazard assessment (PSHA) assume that earthquakes are random, independent events that follow a Poisson distribution of occurrences in a given time period (Cornell, 1968). To overcome the limitations of the Poisson assumption, such as ignoring earthquake clustering, we introduce an analytic method for PSHA that uses order statistics to allow for...
Authors
Andrew J. Michael, Andrea L. Llenos
Modeling the occurrence of M ∼ 5 caldera collapse-related earthquakes in Kīlauea volcano, Hawai'i
During the 2018 Kīlauea eruption and caldera collapse, M ∼ 5 caldera collapse earthquakes occurred almost daily from mid-May until the beginning of August. While caldera collapses happen infrequently, the collapse-related seismicity damaged nearby structures, and so these events should be included in a complete seismic hazard assessment. Here, we present an approach to forecast the...
Authors
Andrea L. Llenos, Andrew J. Michael
2021 U.S. National Seismic Hazard Model for the State of Hawaii
The 2021 U.S. National Seismic Hazard Model (NSHM) for the State of Hawaii updates the two-decades-old former model by incorporating new data and modeling techniques to improve the underlying ground shaking forecasts of tectonic-fault, tectonic-flexure, volcanic, and caldera collapse earthquakes. Two earthquake ground shaking hazard models (public policy and research) are produced that...
Authors
Mark D. Petersen, Allison Shumway, Peter M. Powers, Morgan P. Moschetti, Andrea L. Llenos, Andrew J. Michael, Charles Mueller, Arthur Frankel, Sanaz Rezaeian, Kenneth S. Rukstales, Daniel E. McNamara, P. Okubo, Yuehua Zeng, Kishor S. Jaiswal, Sean Kamran Ahdi, Jason M. Altekruse, Brian Shiro
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
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
Regionally Optimized Background Earthquake Rates from ETAS (ROBERE) for probabilistic seismic hazard assessment
We use an epidemic‐type aftershock sequence (ETAS) based approach to develop a regionally optimized background earthquake rates from ETAS (ROBERE) method for probabilistic seismic hazard assessment. ROBERE fits parameters to the full seismicity catalog for a region with maximum‐likelihood estimation, including uncertainty. It then averages the earthquake rates over a suite of catalogs...
Authors
Andrea L. Llenos, Andrew J. Michael
#EarthquakeAdvisory: Exploring discourse between government officials, news media and social media during the Bombay Beach 2016 Swarm
Communicating probabilities of natural hazards to varied audiences is a notoriously difficult task. Many of these challenges were encountered during the 2016 Bombay Beach, California, swarm of ~100 2≤M≤4.3 earthquakes, which began on 26 September 2016 and lasted for several days. The swarm’s proximity to the southern end of the San Andreas fault caused concern that a larger earthquake...
Authors
Sara McBride, Andrea L. Llenos, Morgan T. Page, Nicholas van der Elst
Ensembles of ETAS models provide optimal operational earthquake forecasting during swarms: Insights from the 2015 San Ramon, California swarm
Earthquake swarms, typically modeled as time-varying changes in background seismicity that are driven by external processes such as fluid flow or aseismic creep, present challenges for operational earthquake forecasting. While the time decay of aftershock sequences can be estimated with the modified Omori law, it is difficult to forecast the temporal behavior of seismicity rates during a...
Authors
Andrea L. Llenos, Andrew J. Michael
Non-USGS Publications**
Segall, P., A. L. Llenos, S.-H. Yun, A. M. Bradley, and E. M. Syracuse (2013), Time-dependent dike propagation from joint inversion of seismicity and deformation data, J. Geophys. Res. Solid Earth, 118, doi: 10.1002/2013JB010251.
Llenos, A. L., and J. J. McGuire (2011), Detecting aseismic strain transients from seismicity data, J. Geophys. Res., 116, B06305, doi: 10.1029/2010JB007537.
Llenos, A. L., J. J. McGuire, and Y. Ogata (2009), Modeling seismic swarms triggered by aseismic transients, Earth Planet. Sci. Lett., 281, 59-69, doi:10.1016/j.epsl.2009.02.011.
Llenos, A. L., and J. J. McGuire (2007), Influence of fore-arc structure on the extent of great subduction zone earthquakes, J. Geophys. Res., 112, B09301, doi: 10.1029/2007JB004944.
**Disclaimer: The views expressed in Non-USGS publications are those of the author and do not represent the views of the USGS, Department of the Interior, or the U.S. Government.