Kyle Withers is a Mendenhall Post-Doc in the Earthquake Hazards Program.
Science and Products
Automated detection of clipping in broadband earthquake records
Because the amount of available ground‐motion data has increased over the last decades, the need for automated processing algorithms has also increased. One difficulty with automated processing is to screen clipped records. Clipping occurs when the ground‐motion amplitude exceeds the dynamic range of the linear response of the instrument. Clipped records in which the amplitude exceeds the dynamic
Spectral damping scaling factors for horizontal components of ground motions from subduction earthquakes using NGA-Subduction data
This article develops global models of damping scaling factors (DSFs) for subduction zone earthquakes that are functions of the damping ratio, spectral period, earthquake magnitude, and distance. The Next Generation Attenuation for subduction earthquakes (NGA-Sub) project has developed the largest uniformly processed database of recorded ground motions to date from seven subduction regions: Alaska
A machine learning approach to developing ground motion models from simulated ground motions
We use a machine learning approach to build a ground motion model (GMM) from a synthetic database of ground motions extracted from the Southern California CyberShake study. An artificial neural network is used to find the optimal weights that best fit the target data (without overfitting), with input parameters chosen to match that of state-of-the-art GMMs. We validate our synthetic-based GMM with
Combining dynamic rupture simulations with ground motion data to characterize seismic hazard from Mw 3-5.8 earthquakes in Oklahoma and Kansas
Many seismically active areas suffer from a lack of near‐source ground‐motion recordings, making ground‐motion prediction difficult at distances within ∼40 km∼40 km from an earthquake. We aim to aid the development of near‐source ground‐motion prediction equations (GMPEs) by generating synthetic ground‐motion data via simulation. Building on previous work using point‐source moment tensor sources
A suite of exercises for verifying dynamic earthquake rupture codes
We describe a set of benchmark exercises that are designed to test if computer codes that simulate dynamic earthquake rupture are working as intended. These types of computer codes are often used to understand how earthquakes operate, and they produce simulation results that include earthquake size, amounts of fault slip, and the patterns of ground shaking and crustal deformation. The benchmark ex
Integrate urban‐scale seismic hazard analyses with the U.S. National Seismic Hazard Model
For more than 20 yrs, damage patterns and instrumental recordings have highlighted the influence of the local 3D geologic structure on earthquake ground motions (e.g., MM 6.7 Northridge, California, Gao et al., 1996; MM 6.9 Kobe, Japan, Kawase, 1996; MM 6.8 Nisqually, Washington, Frankel, Carver, and Williams, 2002). Although this and other local‐scale features are critical to improving seismic ha
Science and Products
- Publications
Automated detection of clipping in broadband earthquake records
Because the amount of available ground‐motion data has increased over the last decades, the need for automated processing algorithms has also increased. One difficulty with automated processing is to screen clipped records. Clipping occurs when the ground‐motion amplitude exceeds the dynamic range of the linear response of the instrument. Clipped records in which the amplitude exceeds the dynamicSpectral damping scaling factors for horizontal components of ground motions from subduction earthquakes using NGA-Subduction data
This article develops global models of damping scaling factors (DSFs) for subduction zone earthquakes that are functions of the damping ratio, spectral period, earthquake magnitude, and distance. The Next Generation Attenuation for subduction earthquakes (NGA-Sub) project has developed the largest uniformly processed database of recorded ground motions to date from seven subduction regions: AlaskaA machine learning approach to developing ground motion models from simulated ground motions
We use a machine learning approach to build a ground motion model (GMM) from a synthetic database of ground motions extracted from the Southern California CyberShake study. An artificial neural network is used to find the optimal weights that best fit the target data (without overfitting), with input parameters chosen to match that of state-of-the-art GMMs. We validate our synthetic-based GMM withCombining dynamic rupture simulations with ground motion data to characterize seismic hazard from Mw 3-5.8 earthquakes in Oklahoma and Kansas
Many seismically active areas suffer from a lack of near‐source ground‐motion recordings, making ground‐motion prediction difficult at distances within ∼40 km∼40 km from an earthquake. We aim to aid the development of near‐source ground‐motion prediction equations (GMPEs) by generating synthetic ground‐motion data via simulation. Building on previous work using point‐source moment tensor sourcesA suite of exercises for verifying dynamic earthquake rupture codes
We describe a set of benchmark exercises that are designed to test if computer codes that simulate dynamic earthquake rupture are working as intended. These types of computer codes are often used to understand how earthquakes operate, and they produce simulation results that include earthquake size, amounts of fault slip, and the patterns of ground shaking and crustal deformation. The benchmark exIntegrate urban‐scale seismic hazard analyses with the U.S. National Seismic Hazard Model
For more than 20 yrs, damage patterns and instrumental recordings have highlighted the influence of the local 3D geologic structure on earthquake ground motions (e.g., MM 6.7 Northridge, California, Gao et al., 1996; MM 6.9 Kobe, Japan, Kawase, 1996; MM 6.8 Nisqually, Washington, Frankel, Carver, and Williams, 2002). Although this and other local‐scale features are critical to improving seismic ha