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David C. Wilson

Publications and source records attributed to David C. Wilson.

At least 55 records · Page 3Linked to original sources
USGS2018

Sensor suite: The Albuquerque Seismological Laboratory Instrumentation Testing Suite

To standardize parameters used in seismometer testing and calibration and to make these algorithms accessible to the seismological community, we have developed a new seismometer testing software package called Albuquerque Seismological Laboratory (ASL) Sensor Test Suite. This software is written in Java and makes use of Seismological Exchange for Earthquake Data (SEED) format. Our goal is not to be all‐inclusive but instead to focus on a few of the instrumentation tests we view as critical when verifying a sensor’s performance. The tests include self‐noise, relative azimuth, relative gain, and estimation of the poles and zeros. For the self‐noise and the relative azimuth, we also include three‐component versions of these tests to allow for the case of sensors with potentially different orientations (e.g., boreholes). The software has been made available on GitHub with the hope that it will be useful for other seismologists who need to quickly verify various sensor parameters without having to write their own versions of the algorithms. Furthermore, by using a common platform and processing algorithms, it becomes possible to compare results among different tests with similar processing methods being used for both.

Seismological Research Letters↗
USGS2018

The widespread influence of Great Lakes microseisms across the United States revealed by the 2014 polar vortex

During the winter of 2014, a weak polar vortex brought record cold temperatures to the north‐central (“Midwest”) United States, and the Great Lakes reached the highest extent of ice coverage (92.5%) since 1979. This event shut down the generation of seismic signals caused by wind‐driven wave action within the lakes (termed “lake microseisms”), giving an unprecedented opportunity to isolate and characterize these novel signals through comparison with nonfrozen time periods. Using seismic records at 72 broadband stations, we observe Great Lakes microseism signals at distances >300 km from the lakes. In contrast to conventional oceanic microseisms, there is no clear relationship between the frequency content of the seismic signals (observed from ~0.5–5‐s period) and the dominant swell period or resonance periods of the lakes based on their bathymetric profiles. Thus, the exact generation mechanism is not readily explained by conventional microseism theory and warrants further investigation.

Geophysical Research Letters↗
USGS2018

Laboratory tests of three Z‐Land Fairfield Nodal 5‐Hz, three‐component sensors

We conduct a number of laboratory tests at the Albuquerque Seismological Laboratory to verify the self‐noise and fidelity in which 3 three‐component Fairfield Nodal Z‐Land, Generation 2, 5‐Hz sensors are able to record seismic signals. In addition to the incoherent self‐noise of the sensors, we estimate the sensitivity of the units in digital volts/m/s, the damping, and the free period. These three parameters allow us to completely characterize the response of the instruments. We find that the responses of all components match a mean‐derived response to within 5% of amplitude and 0.03 radians in phase. This close agreement suggests that for most applications a nominal response is suitable. We also checked the timing of the units as compared to a Quanterra Q330HR and found good agreement up to 200samples/s . Finally, we compared the results of our noise tests on these sensors to a couple of nodal sensors recently deployed at the Community Wavefield Demonstration Experiment in north‐central Oklahoma and found that local site noise and not the sensor self‐noise is a fundamental limiter in the resolution of these deployed sensors at frequencies above ∼0.1Hz .

Seismological Research Letters↗
USGS2018

Seismic sensors record a hurricane’s roar

The instruments installed at Global Seismographic Network (GSN) stations were designed to record Earth’s vibrations, but they sometimes pick up sound waves from unexpected sources. For example, newly installed infrasound sensors at a station on Puerto Rico recorded the passage of Hurricane Maria on 20 September 2017.

Eos, Earth and Space Science News↗
USGS2017

Effects of thermal variability on broadband seismometers: Controlled experiments, observations, and implications

Isolating seismic instruments from temperature fluctuations is routine practice within the seismological community. However, the necessary degree of thermal stability required in broadband installations to avoid generating noise or compromising the fidelity in the seismic records is largely unknown and likely application dependent. To quantify the temperature sensitivity of seismometers over a broad range of frequencies, we artificially induced local temperature changes on three different models of seismometers to measure the effect of thermal variations on seismometer output. We found that diurnal temperature changes above 0.002°C root mean square (rms) showed significant changes in velocity and acceleration output in comparison to thermally stable reference measurements. We also found that sensor incoherent self‐noise increased with temperature variation; these increases in noise can be modeled as 1 / f "> 1 / f noise (pink noise), and are unlikely to be easily corrected for. These experimental results are compared with the data from Incorporated Research Institutions for Seismology (IRIS) U.S. Geological Survey (USGS) Global Seismographic Network (GSN) station TUC (Tucson, Arizona). This station is well instrumented with temperature sensors and has three different broadband seismometers, each of which uses a different method of thermal isolation. We show that the water bricks and borehole installations give ample temperature attenuation to thermally isolate seismometers from diurnal thermal variability that would compromise seismic data. We find that seismometer installations that provide thermal stability below 0.002°C rms could help to improve long‐period vertical seismic data across the GSN by decreasing temperature‐driven 1 / f "> 1 / f noise.

Bulletin of the Seismological Society of America↗
USGS2017

Improvements in absolute seismometer sensitivity calibration using local earth gravity measurements

The ability to determine both absolute and relative seismic amplitudes is fundamentally limited by the accuracy and precision with which scientists are able to calibrate seismometer sensitivities and characterize their response. Currently, across the Global Seismic Network (GSN), errors in midband sensitivity exceed 3% at the 95% confidence interval and are the least‐constrained response parameter in seismic recording systems. We explore a new methodology utilizing precise absolute Earth gravity measurements to determine the midband sensitivity of seismic instruments. We first determine the absolute sensitivity of Kinemetrics EpiSensor accelerometers to 0.06% at the 99% confidence interval by inverting them in a known gravity field at the Albuquerque Seismological Laboratory (ASL). After the accelerometer is calibrated, we install it in its normal configuration next to broadband seismometers and subject the sensors to identical ground motions to perform relative calibrations of the broadband sensors. Using this technique, we are able to determine the absolute midband sensitivity of the vertical components of Nanometrics Trillium Compact seismometers to within 0.11% and Streckeisen STS‐2 seismometers to within 0.14% at the 99% confidence interval. The technique enables absolute calibrations from first principles that are traceable to National Institute of Standards and Technology (NIST) measurements while providing nearly an order of magnitude more precision than step‐table calibrations.

Bulletin of the Seismological Society of America↗
USGS2017

Detection and characterization of pulses in broadband seismometers

Pulsing - caused either by mechanical or electrical glitches, or by microtilt local to a seismometer - can significantly compromise the long‐period noise performance of broadband seismometers. High‐fidelity long‐period recordings are needed for accurate calculation of quantities such as moment tensors, fault‐slip models, and normal‐mode measurements. Such pulses have long been recognized in accelerometers, and methods have been developed to correct these acceleration steps, but considerable work remains to be done in order to detect and correct similar pulses in broadband seismic data. We present a method for detecting and characterizing the pulses using data from a range of broadband sensor types installed in the Global Seismographic Network. The technique relies on accurate instrument response removal and employs a moving‐window approach looking for acceleration baseline shifts. We find that pulses are present at varying levels in all sensor types studied. Pulse‐detection results compared with average daily station noise values are consistent with predicted noise levels of acceleration steps. This indicates that we can calculate maximum pulse amplitude allowed per time window that would be acceptable without compromising long‐period data analysis.

Bulletin of the Seismological Society of America↗
USGS2017

Repeatability of testing a small broadband sensor in the Albuquerque Seismological Laboratory Underground Vault

Variability in seismic instrumentation performance plays a fundamental role in our ability to carry out experiments in observational seismology. Many such experiments rely on the assumed performance of various seismic sensors as well as on methods to isolate the sensors from nonseismic noise sources. We look at the repeatability of estimating the self‐noise, midband sensitivity, and the relative orientation by comparing three collocated Nanometrics Trillium Compact sensors. To estimate the repeatability, we conduct a total of 15 trials in which one sensor is repeatedly reinstalled, alongside two undisturbed sensors. We find that we are able to estimate the midband sensitivity with an error of no greater than 0.04% with a 99th percentile confidence, assuming a standard normal distribution. We also find that we are able to estimate mean sensor self‐noise to within ±5.6 dB with a 99th percentile confidence in the 30–100‐s‐period band. Finally, we find our relative orientation errors have a mean difference in orientation of 0.0171° from the reference, but our trials have a standard deviation of 0.78°.

Bulletin of the Seismological Society of America↗
USGS2017

Characterizing local variability in long‐period horizontal tilt noise

Horizontal seismic data are dominated by atmospherically induced tilt noise at long periods (i.e., 30 s and greater). Tilt noise limits our ability to use horizontal data for sensitive seismological studies such as observing free earth modes. To better understand the local spatial variability of long‐period horizontal noise, we observe horizontal noise during quiet time periods in the Albuquerque Seismological Laboratory (ASL) underground vault using four small‐aperture array configurations. Each array comprises eight Streckeisen STS‐2 broadband seismometers. We analyze the spectral content of the data using power spectral density and magnitude‐squared coherence (γ2‐coherence). Our results show a high degree of spatial variability and frequency dependence in the long‐period horizontal wavefield. The variable nature of long‐period horizontal noise in the ASL vault suggests that it might be highly local in nature and not easily characterized by simple physical models when overall noise levels are low, making it difficult to identify locations in the vault with lower horizontal noise. This variability could be limiting our ability to apply coherence analysis for estimating horizontal sensor self‐noise and could also complicate various indirect methods for removing long‐period horizontal noise (e.g., collocated rotational sensor or microbarograph).

New Mexico↗
USGS2016

Noise reduction in long‐period seismograms by way of array summing

Long‐period (>100 s period) seismic data can often be dominated by instrumental noise as well as local site noise. When multiple collocated sensors are installed at a single site, it is possible to improve the overall station noise levels by applying stacking methods to their traces. We look at the noise reduction in long‐period seismic data by applying the time–frequency phase‐weighted stacking method of Schimmel and Gallart (2007) as well as the phase‐weighted stacking (PWS) method of Schimmel and Paulssen (1997) to four collocated broadband sensors installed in the quiet Albuquerque Seismological Laboratory underground vault. We show that such stacking methods can improve vertical noise levels by as much as 10 dB over the mean background noise levels at 400 s period, suggesting that greater improvements could be achieved with an array involving multiple sensors. We also apply this method to reduce local incoherent noise on horizontal seismic records of the 2 March 2016 M w 7.8 Sumatra earthquake, where the incoherent noise levels at very long periods are similar in amplitude to the earthquake signal. To maximize the coherency, we apply the PWS method to horizontal data where relative azimuths between collocated sensors are estimated and compared with a simpler linear stack with no azimuthal rotation. Such methods could help reduce noise levels at various seismic stations where multiple high‐quality sensors have been deployed. Such small arrays may also provide a solution to improving long‐period noise levels at Global Seismographic Network stations.

Bulletin of the Seismological Society of America↗
USGS2015

Potential improvements in horizontal very broadband seismic data in the IRIS/USGS component of the Global Seismic Network

The Streckeisen STS‐1 has been the primary vault‐type seismometer used in the over‐150‐station Global Seismographic Network (GSN). This sensor has long been known for its outstanding vertical, very long‐period (e.g., >100  s period), and low‐noise performance, although the horizontal long‐period noise performance is less well known. The STS‐1 is a limited, important resource, because it is no longer made or supported by the original manufacturer. We investigate the incoherent noise of horizontal‐component sensors, where coherent signals among sensors have been removed, giving an upper bound on the self‐noise of both the STS‐1 and STS‐2 horizontal components. Our findings suggest that a well‐installed STS‐2 could potentially produce data with similar or better incoherent noise levels to that of a horizontal‐component STS‐1. Along with our experimental investigation, we compare background noise levels for a calendar year at Incorporated Research Institutions for Seismology/U.S. Geological Survey network stations, which comprise approximately two‐thirds of the GSN, with collocated STS‐1 and STS‐2 seismometers. The use of an STS‐2‐class of sensor (flat to velocity to 120 s period) to acquire low‐frequency data in surface‐vault installations would allow network operators to focus more attention on improving vertical data. In order to deal with the difference in instrument response shapes between the two instruments, we detail two different time‐domain filters that would allow users to convert broadband STS‐2 data into very broadband data with a response similar to that of an STS‐1 (flat to velocity to 360 s period). We conclude that the complexity of the current primary horizontal vault sensors in the GSN may not be necessary until we are better able to isolate surface horizontal sensors from various noise sources.

Seismological Research Letters↗
USGS2015

The data quality analyzer: a quality control program for seismic data

The U.S. Geological Survey's Albuquerque Seismological Laboratory (ASL) has several initiatives underway to enhance and track the quality of data produced from ASL seismic stations and to improve communication about data problems to the user community. The Data Quality Analyzer (DQA) is one such development and is designed to characterize seismic station data quality in a quantitative and automated manner. The DQA consists of a metric calculator, a PostgreSQL database, and a Web interface: The metric calculator, SEEDscan, is a Java application that reads and processes miniSEED data and generates metrics based on a configuration file. SEEDscan compares hashes of metadata and data to detect changes in either and performs subsequent recalculations as needed. This ensures that the metric values are up to date and accurate. SEEDscan can be run as a scheduled task or on demand. The PostgreSQL database acts as a central hub where metric values and limited station descriptions are stored at the channel level with one-day granularity. The Web interface dynamically loads station data from the database and allows the user to make requests for time periods of interest, review specific networks and stations, plot metrics as a function of time, and adjust the contribution of various metrics to the overall quality grade of the station. The quantification of data quality is based on the evaluation of various metrics (e.g., timing quality, daily noise levels relative to long-term noise models, and comparisons between broadband data and event synthetics). Users may select which metrics contribute to the assessment and those metrics are aggregated into a “grade” for each station. The DQA is being actively used for station diagnostics and evaluation based on the completed metrics (availability, gap count, timing quality, deviation from a global noise model, deviation from a station noise model, coherence between co-located sensors, and comparison between broadband data and synthetics for earthquakes) on stations in the Global Seismographic Network and Advanced National Seismic System.

Computers & Geosciences↗
USGS2015

Efforts to monitor and characterize the recent increasing seismicity in central Oklahoma

The sharp increase in seismicity over a broad region of central Oklahoma has raised concerns regarding the source of the activity and its potential hazard to local communities and energy-industry infrastructure. Efforts to monitor and characterize the earthquake sequences in central Oklahoma are reviewed. Since early 2010, numerous organizations have deployed temporary portable seismic stations in central Oklahoma to record the evolving seismicity. A multiple-event relocation method is applied to produce a catalog of central Oklahoma earthquakes from late 2009 into early 2015. Regional moment tensor (RMT) source parameters were determined for the largest and best-recorded earthquakes. Combining RMT results with relocated seismicity enabled determination of the length, depth, and style of faulting occurring on reactivated subsurface fault systems. It was found that the majority of earthquakes occur on near-vertical, optimally oriented (northeast-southwest and northwest-southeast) strike-slip faults in the shallow crystalline basement. In 2014, 17 earthquakes occurred with magnitudes of 4 or larger. It is suggested that these recently reactivated fault systems pose the greatest potential hazard to the region.

Oklahoma↗
USGS2014

Uncertainty estimates in broadband seismometer sensitivities using microseisms

The midband sensitivity of a seismic instrument is one of the fundamental parameters used in published station metadata. Any errors in this value can compromise amplitude estimates in otherwise high-quality data. To estimate an upper bound in the uncertainty of the midband sensitivity for modern broadband instruments, we compare daily microseism (4- to 8-s period) amplitude ratios between the vertical components of colocated broadband sensors across the IRIS/USGS (network code IU) seismic network. We find that the mean of the 145,972 daily ratios used between 2002 and 2013 is 0.9895 with a standard deviation of 0.0231. This suggests that the ratio between instruments shows a small bias and considerable scatter. We also find that these ratios follow a standard normal distribution ( R 2  = 0.95442), which suggests that the midband sensitivity of an instrument has an error of no greater than ±6 % with a 99 % confidence interval. This gives an upper bound on the precision to which we know the sensitivity of a fielded instrument.

Journal of Seismology↗
USGS2013

Obtaining changes in calibration-coil to seismometer output constants using sine waves

The midband sensitivity of a broadband seismometer is one of the most commonly used parameters from station metadata. Thus, it is critical for station operators to robustly estimate this quantity with a high degree of accuracy. We develop an in situ method for estimating changes in sensitivity using sine‐wave calibrations, assuming the calibration coil and its drive are stable over time and temperature. This approach has been used in the past for passive instruments (e.g., geophones) but has not been applied, to our knowledge, to derive sensitivities of modern force‐feedback broadband seismometers. We are able to detect changes in sensitivity to well within 1%, and our method is capable of detecting these sensitivity changes using any frequency of sine calibration within the passband of the instrument.

Bulletin of the Seismological Society of America↗
USGS2012

Explosive eruptions triggered by rockfalls at Kīlauea volcano, Hawaii

Ongoing eruptive activity at Kīlauea volcano’s (Hawai‘i) summit has been controlled in part by the evolution of its vent from a 35-m-diameter opening into a collapse crater 150 m across. Geologic observations, in particular from a network of webcams, have provided an unprecedented look at collapse crater development, lava lake dynamics, and shallow outgassing processes. These observations show unequivocally that the hundreds of transient outgassing bursts and weak explosive eruptions that have punctuated the vent’s otherwise nearly steady-state behavior, and that are associated with composite seismic events, were triggered by rockfalls from the vent walls onto the top of the lava column. While the process by which rockfalls drive the explosive bursts is not fully understood, we believe that it is initiated by the generation of a rebound splash, or Worthington jet, which then undergoes fragmentation. The external triggering of low-energy outgassing events by rockfalls represents a new class of small transient explosive eruptions.

Hawai'i↗
USGS2011

New episodes of volcanism at Kilauea Volcano, Hawaii

Mid‐2007 was a time of intense activity at Kilauea Volcano, Hawaii (see Figure 1). In June, the long‐lived Pu'u 'Ō'ō—Kupaianaha eruption, a dual‐vent system along the east rift zone (ERZ) that has been erupting since 1983 [Heliker et al., 2003], paused due to the outbreak of a new vent farther up the rift (see Figure 2). The Pu'u 'Ō'ō vent collapsed following that activity, and the resulting reorganization of the magma plumbing system led to the formation of a second new eruptive vent 2 kilometers downrift of Pu'u 'Ō'ō. These events were well documented by geological, geophysical, and geochemical monitoring. This article summarizes results from these monitoring efforts and interprets the changes that have occurred at Kilauea since June 2007.

Hawaii↗