Albuquerque Seismological Laboratory Research Articles

The Seismic Signature of a High-Energy Density Physics Laboratory and Its Potential for Measuring Time-Dependent Velocity Structure

Abstract The Z Machine at Sandia National Laboratories is a pulsed power facility for high-energy density physics experiments that can shock materials to extreme temperatures and pressures through a focused energy release of up to ∼25 MJ in <100 nanoseconds. It has been in operation for more than two decades and conducts up to ∼100 experiments, or “shots,” per year. Based on a set of 74 known shot times from 2018, we determined that Z Machine shots produce detectable ∼3–17 Hz ground motion 12 km away at the Albuquerque Seismological Laboratory, New Mexico (ANMO), borehole seismograph, with peak signal at ∼7 Hz. The known shot waveforms were used to create a three-component template, leading to the detection of 2339 Z Machine shots since 1998 through single-station cross-correlation. Local seismic magnitude estimates range from local magnitude (ML) −2 to −1.3 and indicate that only a small fraction of the shot energy is transmitted by seismic phases observable at 12 km distance. The most recent major facility renovation, which was intended to decrease mechanical dissipation, is associated with an abrupt decrease in observed seismic amplitudes at ANMO despite stable maximum shot energy. The highly repetitive impulsive sources are well suited to coda-wave interferometry to investigate time-dependent velocity structures. Relative velocity variations (dv/v) show an annual cycle with amplitude of ∼0.2%. Local minima are observed in the late spring, and dv/v increases through the summer monsoon rainfall, possibly reflecting patchy saturation as rainfall infiltrates near the eastern edge of the Albuquerque basin. The cumulative results demonstrate that forensic seismology can provide insight into long-term operation of facilities such as pulsed-power laboratories, and that their recurring signals may be valuable for studies of time-dependent structure.

Local Variations in Broadband Sensor Installations: Orientations, Sensitivities, and Noise Levels

As seismologists continue to place more stringent demands on data quality, accurately described metadata are becoming increasingly important. In order to better constrain the orientation and sensitivities of seismometers deployed in U.S. Geological Survey networks, the Albuquerque Seismological Laboratory (ASL) has recently begun identifying true north with a fiber optic gyroscope (FOG) and has developed methodologies to constrain mid-band, vertical component sensitivity levels to less than 1% in a controlled environment. However, questions remain regarding the accuracy of this new alignment technique as well as if instrument sensitivities and background noise levels are stable when the seismometers are installed in different environmental settings. In this study, we examine the stability and repeatability of these parameters by reinstalling two high-quality broadband seismometers (Streckeisen STS-2.5 and Nanometrics T-360 Global Seismographic Network (GSN) version) at different locations around the ASL and comparing them to each other and a reference STS-6 seismometer that stayed stationary for the duration of the experiment. We find that even in different environmental conditions, the sensitivities of the two broadband seismometers stayed stable to within 0.1% and that orientations attained using the FOG are generally accurate to within a degree. However, one install was off by 5° due to a mistake made by the installation team. These results indicate that while technology and methodologies are now in place to calibrate and orient a seismometer to within 1°, human error both during the installation and while producing the metadata is often a limiting factor. Finally, we find that background noise levels at short periods (0.1–1 s) become noisier when the sensors are emplaced in unconsolidated materials, whereas the noise levels at long periods (30–100 s) are not sensitive to local geological structure on the vertical components.

Seismic Monitoring during Crises at the NEIC in Support of the ANSS

Abstract Over the past two decades, the U.S. Geological Survey (USGS) National Earthquake Information Center (NEIC) has overcome many operational challenges. These range from minor disruptions, such as power outages, to significant operational changes, including system reconfiguration to handle unique earthquake sequences and the need to handle distributed work during a pandemic. Our ability to overcome crises is built on the development and implementation of a continuity of operations plan, well-designed infrastructure, adaptive software systems, experienced staff, and extensive collaboration. The NEIC does not operate in a vacuum but benefits from contributions of United States and international seismic networks. Similarly, the overall resilience of earthquake monitoring in the United States and around the globe benefits from the NEIC’s role as the national center for the Advanced National Seismic System (ANSS). Here, we highlight significant adaptations the NEIC has made in the face of crises. We discuss the COVID-19 pandemic, which represents the most significant operational crisis to impact the NEIC. The NEIC has maintained continuous operations during the ongoing COVID-19 pandemic by shifting from a fully onsite operations center to a distributed hybrid of onsite and telework staffing. We then discuss cases in which the NEIC has supported regional monitoring in the face of significant crises. In 2018, the NEIC assisted the Hawaiian Volcano Observatory with the Kīlauea volcano eruption by responding to large events, implementing contingency monitoring procedures, and calculating moment magnitudes for the low-frequency caldera collapses. Impacts of a crisis extend beyond the immediate response and often require a significant postevent assessment and a rebuilding phase. After the 2017 Hurricane Maria, the NEIC, the USGS National Strong-Motion Program, and the USGS Albuquerque Seismological Laboratory worked with the Puerto Rico Seismic Network and the Puerto Rico Strong-Motion program to assess, plan, and implement upgrades at sites that experienced storm damage.

Towards understanding relationships between atmospheric pressure variations and long-period horizontal seismic data: a case study

SUMMARYVariations in atmospheric pressure have long been known to introduce noise in long-period (>10 s) seismic records. This noise can overwhelm signals of interest such as normal modes and surface waves. Generally, this noise is most pronounced on the horizontal components where it arises due to tilting of the seismometer in response to changes in atmospheric pressure. Several studies have suggested methodologies for correcting unwanted pressure-induced noise using collocated microbarograph records. However, how applicable these corrections are to varying geologic settings and installation types (e.g. vault versus post-hole) is unclear. Using coefficients obtained by solving for the residuals of these corrections, we can empirically determine the sensitivity of instruments in a specific location to the influences of pressure. To better understand how long-period, pressure-induced noise changes with time and emplacement, we examine horizontal seismic records along with barometric pressure at five different Global Seismographic Network stations, all with multiple broadband seismometers. We also analyse three Streckeisen STS-2 broadband seismometers, which are collocated with a microbarograph, at the Albuquerque Seismological Laboratory. We observe periods of high magnitude-squared-coherence (γ2-coherence; γ2 > 0.8) between the seismic and pressure signals which fluctuate through time, frequency, and even between seismic instruments in the same vault. These observations suggest that these tilt-generated signals are highly sensitive to very local (<10 m) site effects. However, we find that in cases where instruments are not located at a large depth (<100 m), the pressure-induced noise is polarized in a nearly constant direction that is consistent with local topographic features or the geometry of the vault. We also find that borehole instruments at a large depth (>100 m) appear to be unaffected by pressure-loading mechanisms outlined by Sorrells (1971) but possibly by Newtonian attraction. Correlating the induced-noise polarization direction with times of high coherence, we work to identify sensors that are ultimately limited by pressure-induced horizontal noise as well as period bands that can benefit from pressure corrections. We find that while the situation is complex, each sensor appears to have its own unique response to pressure. Our findings suggest that we can determine empirical relationships between pressure and induced tilt on a case by case basis.

Installation and Performance of the Albuquerque Seismological Laboratory Small-Aperture Posthole Array

AbstractThe Global Seismographic Network (GSN) has been used extensively by seismologists to characterize large earthquakes and image deep earth structure. Although the network’s original design goals have been met, the seismological community has suggested that the incorporation of small-aperture seismic arrays at select sites may improve performance of the network and enable new observations. As a pilot study for this concept, we have created a 500 m aperture, nine-element broadband seismic array around the GSN station ANMO (Albuquerque, New Mexico) at the U.S. Geological Survey Albuquerque Seismological Laboratory (ASL). The array was formed by supplementing the secondary borehole seismometer (90 m depth) at ANMO with eight additional 2.6 m posthole sites. Each station’s seismometer was oriented using a fiber optic gyroscope to within 2.0° of north. Data quality, particularly on the vertical components, is excellent with median power levels closely tracking the secondary sensor at ANMO at frequencies lower than 1 Hz. Horizontal component data are more variable at low frequencies (<0.02 Hz), with the type of installation and local geography appearing to strongly influence the amount of tilt-induced noise. Throughout the article, we pose several fundamental questions related to the variability and precision of seismic wavefield measurements that we seek to address with data from this array. In addition, we calculate the array response and show a few examples of using the array to obtain back azimuths of a local event and a continuous narrowband noise source. The apparent velocity of the event across the array is then used to infer the local P-wave velocity at the ASL. Near-real-time data collected from the array along with collocated meteorological, magnetic, and infrasound data are freely available in near-real time from the Incorporated Research Institutions for Seismology Data Management Center.

A Collection of Historic Seismic Instrumentation Photographs at the Albuquerque Seismological Laboratory

A Collection of Historic Seismic Instrumentation Photographs at the Albuquerque Seismological Laboratory

Repeatability of Testing a Small Broadband Sensor in the Albuquerque Seismological Laboratory Underground Vault

Abstract 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°. Electronic Supplement: Table of dates of the trials used as well as Q – Q plots for the statistics collected from the sensor tests.

Characterizing Local Variability in Long‐Period Horizontal Tilt Noise

ABSTRACT 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 ( γ 2 ‐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).

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.

Upgrade of the New China Digital Seismograph Network

Online Material: Figures of waveform comparison, 10th percentile noise levels, and sensor coherence. In 1980, the State Seismological Bureau (SSB) of the People’s Republic of China, the U.S. Geological Survey (USGS), and the U.S. National Science Foundation (NSF) signed the Earthquake Studies Protocol to initiate research programs for the benefit of the earthquake hazards reduction programs in both countries (Russ and Johnson, 1985). Because high‐quality seismic data are essential to earthquake studies, one of the first elements of this protocol was the establishment of the China Digital Seismograph Network (CDSN; Fig. 1 and ![Graphic][1] Table S1, available in the electronic supplement to this article.). Figure 1. Map of China and surrounding area showing the location of China Digital Seismograph Network (CDSN) and New China Digital Seismograph Network (NCDSN) stations. Black squares mark the locations of upgraded NCDSN stations; an open triangle indicates the location of station LZH (Lanzhou, Gansu Province, China), one of the original CDSN stations that was not made part of the Global Seismographic Network (GSN). Stations BJI (Baijiatuan, Beijing, China) and BJT (Baijiatuan, Beijing, China) are coincident on this scale. Open squares mark the location of neighboring GSN stations. The CDSN was designed as a national facility, building on existing Chinese observatories where possible. Implemented by the SSB Institute of Geophysics (IG) and USGS Albuquerque Seismological Laboratory (ASL), the first phase of the network was installed in 1985–1986 and consisted of nine stations (BJI, Baijiatuan; ENH, Enshi; HIA, Hailar; KMI, Kunming; LZH, Lanzhou; MDJ, Mudanjiang; QIZ, Qiongzhong; SSE, Sheshan; and WMQ, Urumqi) with network code CD. Under the terms of the original CDSN agreement, the SSB provided the equipment for five data acquisition systems, and the USGS supplied four (Institute of Geophysics et al. , 1987). The USGS systems were installed at Baijiatuan, Kunming, Lanzhou, and Mudanjiang; the SSB systems were installed … [1]: /embed/inline-graphic-1.gif

Self‐Noise Models of Five Commercial Strong‐Motion Accelerometers

Research Article| May 20, 2015 Self‐Noise Models of Five Commercial Strong‐Motion Accelerometers A. T. Ringler; A. T. Ringler aU.S. Geological Survey, Albuquerque Seismological Laboratory, P.O. Box 82010, Albuquerque, New Mexico 87198 U.S.A.aringler@usgs.gov Search for other works by this author on: GSW Google Scholar J. R. Evans; J. R. Evans bU.S. Geological Survey, 400 Natural Bridges Drive, Santa Cruz, California 95060 U.S.A. Search for other works by this author on: GSW Google Scholar C. R. Hutt C. R. Hutt aU.S. Geological Survey, Albuquerque Seismological Laboratory, P.O. Box 82010, Albuquerque, New Mexico 87198 U.S.A.aringler@usgs.gov Search for other works by this author on: GSW Google Scholar Author and Article Information A. T. Ringler aU.S. Geological Survey, Albuquerque Seismological Laboratory, P.O. Box 82010, Albuquerque, New Mexico 87198 U.S.A.aringler@usgs.gov J. R. Evans bU.S. Geological Survey, 400 Natural Bridges Drive, Santa Cruz, California 95060 U.S.A. C. R. Hutt aU.S. Geological Survey, Albuquerque Seismological Laboratory, P.O. Box 82010, Albuquerque, New Mexico 87198 U.S.A.aringler@usgs.gov Publisher: Seismological Society of America First Online: 14 Jul 2017 Online ISSN: 1938-2057 Print ISSN: 0895-0695 © 2015 by the Seismological Society of America Seismological Research Letters (2015) 86 (4): 1143–1147. https://doi.org/10.1785/0220150027 Article history First Online: 14 Jul 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation A. T. Ringler, J. R. Evans, C. R. Hutt; Self‐Noise Models of Five Commercial Strong‐Motion Accelerometers. Seismological Research Letters 2015;; 86 (4): 1143–1147. doi: https://doi.org/10.1785/0220150027 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietySeismological Research Letters Search Advanced Search Strong‐motion accelerometers provide onscale seismic recordings during moderate‐to‐large ground motions (e.g., up to tens of m/s2 peak). Such instruments have played a fundamental role in improving our understanding of earthquake source physics (Bock et al., 2011), earthquake engineering (Youd et al., 2004), and regional seismology (Zollo et al., 2010). Although strong‐motion accelerometers tend to have higher noise levels than high‐quality broadband velocity seismometers, their higher clip‐levels provide linear recordings at near‐field sites even for the largest of events where a collocated broadband sensor would no longer be able to provide... You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

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.

Efforts to Recover and Digitize Analog Seismograms from Harvard-Adam Dziewo ski Observatory

The Harvard‐Adam Dziewonski observatory is one of the oldest seismic stations academically established in the United States, and it is owned and maintained by Harvard University (Leet, 1934). It is currently one of the Global Seismic Network stations operated by the U.S. Geological Survey (USGS)’s Albuquerque Seismological Laboratory (network code IU) and is also used as a testing facility for new instruments by Quanterra, Inc. The digital data from the Harvard seismic station since 1988 are readily available to the scientific community through the Incorporated Research Institutions for Seismology Data Management Center and are widely used for various research purposes. The data from this station are known to be of high quality, partly because the instruments are housed in a vault that is about 4.5 m below ground, ensuring reduced surface noise and a stable environment (e.g., nearly constant temperature and humidity). In this manuscript, we focus on the analog data that have been collected at this station prior to 1988. The vision of operating a high‐quality seismic station is attributed to a Harvard professor, J. B. Woodworth, who began seismic instrumentation in 1908 (Leet, 1934). Initially, two Bosch–Omori 100 kg horizontal pendulum seismographs were installed in the basement of the Harvard Museum of Natural History building in Cambridge, Massachusetts, and the two instruments operated until 1928. Ground‐motion monitoring continued at this location with two Milne–Shaw horizontal pendulum seismographs until April 1933. Only a handful of seismograms appears to have survived from this time period. In 1933, under the direction of L. Don Leet, a new seismic observatory (Fig. 1), one that is used today, was constructed at the Oak Ridge Observatory, also known as Harvard Astronomical Observatory, at Harvard, Massachusetts (note that this is about 40 km northwest of Cambridge, Massachusetts, where Harvard University is located). Instruments began recording ground motion at …

Seismic Station Installation Orientation Errors at ANSS and IRIS/USGS Stations

Many seismological studies depend on the published orientations of sensitive axes of seismic instruments relative to north (e.g., Li et al. , 2011). For example, studies of the anisotropic structure of the Earth’s mantle through SKS‐splitting measurements (Long et al. , 2009), constraints on core–mantle electromagnetic coupling from torsional normal‐mode measurements (Dumberry and Mound, 2008), and models of three‐dimensional (3D) velocity variations from surface waves (Ekstrom et al. , 1997) rely on accurate sensor orientation. Unfortunately, numerous results indicate that this critical parameter is often subject to significant error (Laske, 1995; Laske and Masters, 1996; Yoshizawa et al. , 1999; Schulte‐Pelkum et al. , 2001; Larson and Ekstrom, 2002). For the Advanced National Seismic System (ANSS; ANSS Technical Integration Committee, 2002), the Global Seismographic Network (GSN; Butler et al. , 2004), and many other networks, sensor orientation is typically determined by a field engineer during installation. Successful emplacement of a seismic instrument requires identifying true north, transferring a reference line, and measuring the orientation of the instrument relative to the reference line. Such an exercise is simple in theory, but there are many complications in practice. There are four commonly used methods for determining true north at the ANSS and GSN stations operated by the USGS Albuquerque Seismological Laboratory (ASL), including gyroscopic, astronomical, Global Positioning System (GPS), and magnetic field techniques. A particular method is selected based on site conditions (above ground, below ground, availability of astronomical observations, and so on) and in the case of gyroscopic methods, export restrictions. Once a north line has been determined, it must be translated to the sensor location. For installations in mines or deep vaults, this step can include tracking angles through the one or more turns in the access tunnel leading to the vault (e.g., GSN station WCI in Wyandotte Cave, Indiana). Finally, …

Explosive eruptions triggered by rockfalls at Kīlauea volcano, Hawai‘i

Research Article| February 01, 2013 Explosive eruptions triggered by rockfalls at Kīlauea volcano, Hawai‘i Tim R. Orr; Tim R. Orr 1U.S. Geological Survey, Hawaiian Volcano Observatory, Hawai‘i National Park, Hawaii 96718, USA Search for other works by this author on: GSW Google Scholar Weston A. Thelen; Weston A. Thelen 1U.S. Geological Survey, Hawaiian Volcano Observatory, Hawai‘i National Park, Hawaii 96718, USA Search for other works by this author on: GSW Google Scholar Matthew R. Patrick; Matthew R. Patrick 1U.S. Geological Survey, Hawaiian Volcano Observatory, Hawai‘i National Park, Hawaii 96718, USA Search for other works by this author on: GSW Google Scholar Donald A. Swanson; Donald A. Swanson 1U.S. Geological Survey, Hawaiian Volcano Observatory, Hawai‘i National Park, Hawaii 96718, USA Search for other works by this author on: GSW Google Scholar David C. Wilson David C. Wilson 2U.S. Geological Survey, Albuquerque Seismological Laboratory, Albuquerque, New Mexico 87198, USA Search for other works by this author on: GSW Google Scholar Author and Article Information Tim R. Orr 1U.S. Geological Survey, Hawaiian Volcano Observatory, Hawai‘i National Park, Hawaii 96718, USA Weston A. Thelen 1U.S. Geological Survey, Hawaiian Volcano Observatory, Hawai‘i National Park, Hawaii 96718, USA Matthew R. Patrick 1U.S. Geological Survey, Hawaiian Volcano Observatory, Hawai‘i National Park, Hawaii 96718, USA Donald A. Swanson 1U.S. Geological Survey, Hawaiian Volcano Observatory, Hawai‘i National Park, Hawaii 96718, USA David C. Wilson 2U.S. Geological Survey, Albuquerque Seismological Laboratory, Albuquerque, New Mexico 87198, USA Publisher: Geological Society of America Received: 25 Apr 2012 Revision Received: 09 Aug 2012 Accepted: 29 Aug 2012 First Online: 09 Mar 2017 Online ISSN: 1943-2682 Print ISSN: 0091-7613 © 2013 Geological Society of America Geology (2013) 41 (2): 207–210. https://doi.org/10.1130/G33564.1 Article history Received: 25 Apr 2012 Revision Received: 09 Aug 2012 Accepted: 29 Aug 2012 First Online: 09 Mar 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Tim R. Orr, Weston A. Thelen, Matthew R. Patrick, Donald A. Swanson, David C. Wilson; Explosive eruptions triggered by rockfalls at Kīlauea volcano, Hawai‘i. Geology 2013;; 41 (2): 207–210. doi: https://doi.org/10.1130/G33564.1 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyGeology Search Advanced Search Abstract 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. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

Data Quality of Seismic Records from the Tohoku, Japan, Earthquake as Recorded across the Albuquerque Seismological Laboratory Networks

Online material : Additional network summary figures. Great earthquakes recorded across modern digital seismographic networks, such as the recent Tohoku, Japan, earthquake on 11 March 2011 ( Mw = 9.0 ), provide unique datasets that ultimately lead to a better understanding of the Earth’s structure ( e.g. , Pesicek et al. 2008) and earthquake sources ( e.g. , Ammon et al. 2011). For network operators, such events provide the opportunity to look at the performance across their entire network using a single event, as the ground motion records from the event will be well above every station’s noise floor. Methods for in situ identification of possible instrumentation problems have been the focus of a number of recent studies (Davis et al. 2005; Ekstrom et al. 2006; Davis and Berger 2007; Ekstrom and Busby 2008; Ringler et al. 2010). One common thread to these studies is that they all rely on a large number of observations or focus on specific frequencies to identify possible instrumentation problems. In contrast, great earthquakes such as Tohoku provide the opportunity for station operators to verify instrument sensitivities as well as to identify other possible station problems ( e.g. , excessive noise at the station, clipped records, or low-gain instrument problems) from a single event, allowing station operators to identify current instrumentation problems without having to use a large number of historical events. This approach also allows station operators to see potential changes in data quality as a result of recent station maintenance visits ( e.g. , modernization of current station digitizers to Quanterra Q330HRs; Anderson et al. 2011), along with other improvements to data quality such as changes in calibration practices (Ringler et al. , 2012). Recent accessibility to high-quality full-waveform synthetic seismograms derived from 3D Earth models (Tromp et al. 2010), along with well-constrained …

Designs and test results for three new rotational sensors

We discuss the designs and testing of three rotational seismometer prototypes developed at the Institute of Geophysics, Academy of Sciences (Prague, Czech Republic). Two of these designs consist of a liquid-filled toroidal tube with the liquid as the proof mass and providing damping; we tested the piezoelectric and pressure transduction versions of this torus. The third design is a wheel-shaped solid metal inertial sensor with capacitive sensing and magnetic damping. Our results from testing in Prague and at the Albuquerque Seismological Laboratory of the US Geological Survey of transfer function and cross-axis sensitivities are good enough to justify the refinement and subsequent testing of advanced prototypes. These refinements and new testing are well along.

Challenges Ahead for the Global Seismographic Network

Twenty-five years ago, a new global digital seismic network was identified by the National Academies' Committee on Science, Engineering, and Public Policy as one of five research areas in which significant dividends could be expected as a result of incremental federal investment. That recommendation, through coordinated planning and support by scientists, mission agencies, and international partners, spawned the development of the Global Seismographic Network (GSN). The GSN is a joint program of the National Science Foundation (NSF) and the U.S. Geological Survey (USGS). The NSF program is implemented by the Incorporated Research Institutions for Seismology (IRIS) and the University of California at San Diego (UCSD); the USGS program is implemented by the Albuquerque Seismological Laboratory. Network completion is a beginning, not an end, and there is a need for continual rejuvenation of such a network, both to improve operational capabilities and to open new avenues for scientific exploration. The GSN has now far exceeded initial plans and expectations, both in terms of its operational scope and performance and the scientific applications of the data it produces. Originally envisioned as a 100-station network to gather data mainly for research applications, the network has evolved into a real-time Earth-observing system also supporting earthquake alerts, tsunami warning, nuclear treaty verification, and other uses. Several recent publications have documented the GSN's remarkable successes. Butler et al. (2004) emphasized that the GSN had exceeded its original technical design goal of 128 globally distributed stations—last year the core network plus affiliates reached 150 stations, strategically scattered across continents and islands from the Arctic to the South Pole. One in four of these stations has evolved into a cooperative “geophysical observatory,” which may include a range of sensor types (gravimeters, GPS receivers, magnetometers, microbarographs, etc.) in addition to the broadband and very-broadband seismometers that are capable of …

Calibration of the Global Seismographic Network Using Tides

The Incorporated Research Institutions for Seismology/United States Geological Survey (IRIS/USGS) Global Seismographic Network (GSN) is now a fully operational scientific facility routinely used to investigate earth structure and seismicity throughout the world (Butler et al. 2004). Data recorded at GSN stations are rapidly transmitted to international agencies charged with hazard assessment and response as well as to individual scientists eager to study in detail the properties of the most recent earthquake. All who use these recordings depend upon the accuracy of the GSN's metadata provided to them through the IRIS Data Management System (http://www.iris.edu). The IRIS DMS in turn distributes response information supplied by the GSN network operators, the University of California San Diego's Project IDA (International Deployment of Accelerometers) and the USGS's Albuquerque Seismological Laboratory (ASL). To maximize the scientific return from these data and to ensure that accurate measurements may be made at the various monitoring centers that use GSN data in their analyses, both network operators subject the equipment at each GSN station to a series of stringent tests before field deployment. These tests include careful calibration of the data acquisition system. A goal of the GSN is to publish instrument responses accurate to 1%. In principle, the Earth's' tides provide an independent check of the laboratory-determined instrument response. The bulk properties of the Earth are well-enough known to compute the solid earth's response to tides to a high degree of accuracy. However, until the advent of improved ocean tidal models based upon analysis of TOPEX/Poseidon orbit cycles, the effects of ocean loading were too poorly known to be used for this purpose. Using the current generation of tidal models that effectively incorporate ocean loading as well as the solid earth tide, one may now compute a tidal series accurate to 1% in many regions. In this …