Geology topics

S. N. Dybing

Publications and source records attributed to S. N. Dybing.

2 recordsLinked to original sources

USGS2026

ShakeAlert Earthquake Early Warning System performance during the Mw 7.0 offshore Cape Mendocino earthquake

The 5 December 2024 M w 7.0 Offshore Cape Mendocino earthquake was a challenging test of the U.S. West Coast ShakeAlert earthquake early warning system due to its offshore epicenter and limited near‐source station coverage. We analyzed real‐time performance of all components of the ShakeAlert system, including the seismic algorithms (earthquake point‐source integrated code [EPIC] and Finite‐fault rupture Detector [FinDer]), the geodetic algorithm (Geodetic First Approximation of Size and Time–peak ground displacement [GFAST‐PGD]), and network telemetry during the event. EPIC created the first solution for this earthquake 15 s after origin time with an initial magnitude estimate of M 5.6 and location error of 10 km from the Advanced National Seismic System epicenter. An early spurious trigger from station CE.89101 fortuitously maintained location accuracy and, correspondingly, magnitude accuracy. FinDer contributed its first solution at 18 s with a location estimate closer to the seismic network and produced two distinct rupture geometries, leading to minor fluctuations in estimated intensity contours. GFAST‐PGD did not meet alerting thresholds but otherwise performed as expected. Network latencies were <2 s for most stations, supporting the rapid detection of this earthquake by the system. Roughly five million alerts were delivered to cell phone devices in California and Oregon during this event. This was also the first instance of a school district‐wide ShakeAlert‐powered system being activated. Comparisons to recorded seismograms demonstrate that the maximum warning times before potentially damaging shaking (intensity 6+) were in the range of 5–55 s. Although the ShakeAlert system provided accurate solutions and useful alert delivery, this earthquake raised awareness of potential issues within the system, including the need for improved offshore location estimates, a combination of solutions from ShakeAlert servers, and handling of spurious triggers.

California↗

USGS2019

Characteristics and spatial variability of wind noise on near-surface broadband seismometers

By coupling with the ground, wind causes ground motion that appears on seismic records as noise across a wide bandwidth. This wind-generated noise can drown out important features such as small earthquakes and prevent observation of normal modes from large earthquakes. Because the wind field is heterogeneous at local scales due to structures, diurnal heating, and topography, wind-induced seismic noise may be different on seismometers installed just meters apart. We have investigated the spatial variability of wind-induced noise using two weather sensors separated by approximately ~100 m and co-located with one deep borehole and four near-surface broadband seismometers. We found that at longer periods (>5 s), increasing wind speed causes increases in noise on the horizontal components of seismometers. While this has been previously observed, we also measured a γ2-coherence of less than 0.2 between the wind speed, wind direction, and the pressure recorded by our weather stations. We further observed a loss of coherence between the vertical components of our seismometers from 8 s to 20 s period. The amplitude of the drop-in coherence appears to depend on the substrate surrounding the seismometer. Based on two previously-developed theoretical models, we found that the local material surrounding the sensor could be amplifying the wind-generated noise. We also investigated the frequency dependence of wind-induced noise and found that the dominant source of high-frequency seismic noise at some sites could be anthropogenic rather than induced by wind. Additionally, we estimated the linear relationship between the root mean squares (RMS) of wind speed and RMS seismic velocity for all sensors, finding substantial variability between different installments. A more detailed understanding of the complex processes by which wind-induced noise is generated can inform the installation of sensors and the development of methods for mitigation of these effects, thus improving the overall quality of seismic data.

New Mexico↗