Geology topics

Justin T. Wilgus

Publications and source records attributed to Justin T. Wilgus.

3 recordsLinked to original sources

USGS2024

Noise constraints on global body‐wave measurement thresholds

Intermediate sized earthquakes (≈ M 4–6.5) 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 greater earthquakes worldwide within 20 min of the rupture time, and therefore accurate 𝑚b magnitude estimates are essential to fulfill its mission. To better understand how network geometry and noise levels affect the global response capabilities, we developed a method to spatially estimate the minimum measurable 𝑚b⁠ . To do this, we compare expected 𝑚b amplitudes at every station to the station’s background noise level. We find that using NEIC’s current network geometry and these idealized thresholds, NEIC can potentially estimate 𝑚b magnitudes down to M 4.5 globally. Low‐latitude regions in the Southern Hemisphere present the biggest opportunity to improve monitoring capabilities. However, logistically they also present the biggest hurdles for network operators. Finally, to test the resiliency of the network we removed the 20 most important stations and found the 𝑚b threshold remains 𝑚b 4.5. However, the region where only 𝑚b 4.5 and greater can be estimated increases and is again restricted to the Southern Hemisphere.

Bulletin of the Seismological Society of America↗

USGS2024

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 15 yr of vertical‐component data from the nine‐station Caribbean network (CU) and look at background noise within the 0.05–300 s period range. We describe the most visually apparent features observed at the CU stations. One of the most prominent features occurs in the 0.75–3 s band for which power levels are systematically elevated and decay as a function of proximity to the coastline. Further examination of this band on 1679 contiguous USArray Transportable Array stations reveals the same relationship. Such a relationship with coastal distance is not observed in the 4–8 s range more typical of globally observed secondary microseisms. A simple surface‐wave amplitude decay model fits the observed decay well with geometric spreading as the most important factor for stations near the coast (<∼50 km). The model indicates that power levels are strongly influenced by proximity to coastline at 0.75–3 s. This may be because power from nearshore wave action at 0.75–3 s overwhelms more distant and spatially distributed secondary microseism generation. Application of this basic model indicates that a power reduction of ∼25 dB can be achieved by simply installing the seismometer 25 km away from the coastline. This finding may help to inform future site locations and array design thereby improving network performance and data quality, and subsequently earthquake detection capabilities.

Seismological Research Letters↗

USGS2017

The morphology of transverse aeolian ridges on Mars

A preliminary survey of publicly released high resolution digital terrain models (DTMs) produced by the High Resolution Imaging Science Experiment (HiRISE) camera on Mars Reconnaissance Orbiter identified transverse aeolian ridges (TARs) in 154 DTMs in latitudes from 50°S to 40°N. Consistent with previous surveys, the TARs identified in HiRISE DTMs are found at all elevations, irrespective of the regional thermal inertia of the surface. Ten DTMs were selected for measuring the characteristics of the TARs, including maximum height, mean height, mean spacing (wavelength), and the slope of the surface where they are located. We confined our measurements to features that were taller than 1 m and spaced more than 10 m apart. We found a surprisingly wide variability of TAR sizes within each local region (typically 5 km by 25 km), with up to a factor of 7 difference in TAR wavelengths in a single DTM. The TAR wavelengths do not appear to be correlated to latitude or elevation, but the largest TARs in our small survey were found at lower elevations. The tallest TARs we measured were on the flat floor of Moni crater, within Kaiser crater in the southern highlands. These TARs are up to 14 m tall, with a typical wavelength of 120 m. TAR heights are weakly correlated with their wavelengths. The height-to-wavelength ratios for most TARs are far less than 1/2π (the maximum predicted for antidunes), however in two cases the ratio is close to 1/2π, and in one case (in the bend of a channel) the ratio exceeds 1/2π. TAR wavelengths are uncorrelated with surface slope, both on local and regional scales. TAR heights are weakly anti-correlated with local slope. These results help constrain models of TAR formation, particularly a new hypothesis (Geissler, 2014) that suggests that TARs were formed from micron-sized dust that was transported in suspension. The lack of correlation between TAR wavelength and surface slope seems to rule out formation by gravity-driven dust flows such as avalanches or density currents, and suggests that the TARs were instead produced by the Martian winds.

Aeolian Research↗