Global Seismographic Network Stations Research Articles

Global Seismic Networks Operated by the U.S. Geological Survey

Abstract The U.S. Geological Survey (USGS) Global Seismographic Network (GSN) Program operates two thirds of the GSN, a network of state-of-the-art, digital seismological and geophysical sensors with digital telecommunications. This network serves as a multiuse scientific facility and a valuable resource for research, education, and monitoring. The other one third of the GSN is funded by the National Science Foundation (NSF), and the operations of this component are overseen by EarthScope. This collaboration between the USGS, EarthScope, and NSF has allowed for the development and operations of the GSN to be a truly multiuse network that provides near real-time open access data, facilitating fundamental discoveries by the Earth science community, supporting the earthquake hazards mission of the USGS, benefitting tsunami monitoring by the National Oceanic and Atmospheric Administration, and contributing to nuclear test monitoring and treaty verification. In this article, we describe the installation and evolution of the seismic networks operated by the USGS that ultimately led to the USGS portion of the GSN (100 stations under network codes IU, IC, and CU) as they are today and envision technological advances and opportunities to further improve the utility of the network in the future. This article focuses on the USGS-operated component of the GSN; a companion article on the GSN stations funded by the NSF and operated by the Cecil and Ida Green Institute of Geophysics and Planetary Physics, Scripps Institution of Oceanography, University of California at San Diego by Davis et al. (2023) appears in this volume.

Earth’s Upper Crust Seismically Excited by Infrasound from the 2022 Hunga Tonga–Hunga Ha’apai Eruption, Tonga

AbstractRecords of pressure variations on seismographs were historically considered unwanted noise; however, increased deployments of collocated seismic and acoustic instrumentation have driven recent efforts to use this effect induced by both wind and anthropogenic explosions to invert for near-surface Earth structure. These studies have been limited to shallow structure because the pressure signals have relatively short wavelengths (<∼300 m). However, the 2022 eruption of Hunga Tonga–Hunga Ha’apai (also called “Hunga”) volcano in Tonga generated rare, globally observed, high-amplitude infrasound signals with acoustic wavelengths of tens of kilometers. In this study, we examine the acoustic-to-seismic coupling generated by the Hunga eruption across 82 Global Seismographic Network (GSN) stations and show that ground motion amplitudes are related to upper (0 to ∼5 km) crust material properties. We find high (>0.8) correlations between pressure and vertical component ground motion at 83% of the stations, but only 30% of stations show this on the radial component, likely due to complex tilt effects. We use average elastic properties in the upper 5.2 km from the CRUST1.0 model to estimate vertical seismic/acoustic coupling coefficients (SV/A) across the GSN network and compare these to recorded observations. We exclude many island stations from these comparisons because the 1° resolution of the CRUST1.0 model places a water layer below these stations. Our simple modeling can predict observed SV/A within a factor of 2 for 94% of the 51 non-island GSN stations with high correlations between pressure and ground motion. These results indicate that analysis of acoustic-to-seismic coupling from the eruption could be used to place additional constraints on crustal structure models at stations with collocated seismic and pressure sensors. Ultimately, this could improve tomographic imaging models, which rely on methods that are sensitive to local structure.

Improved Resolution across the Global Seismographic Network: A New Era in Low-Frequency Seismology

Abstract The Global Seismographic Network (GSN)—a global network of ≈150 very broadband stations—is used by researchers to study the free oscillations of the Earth (≈0.3–10 mHz) following large earthquakes. Normal-mode observations can provide information about the radial density and anisotropic velocity structure of the Earth (including near the core–mantle boundary), but only when signal-to-noise ratios at very low frequencies are sufficiently high. Most normal-mode observations in the past three decades have been made using Streckeisen STS-1 vault seismometers. However, these sensors are no longer being manufactured or serviced. Candidate replacement sensors, the Streckeisen STS-6 and the Nanometrics T-360GSN, have been recently installed in boreholes, postholes, and vaults at several GSN stations and GSN testbeds. In this study, we examine normal-mode spectra following three Mw 8 earthquakes in 2021 and from one Mw 8.2 earthquake in 2014 to evaluate the change in GSN low-frequency performance on the vertical component. From this analysis, we conclude that the number of GSN stations capable of resolving normal modes following Mw 8 earthquakes has nearly doubled since 2014. The improved observational capabilities will help better understand the radial velocity and density estimates of the Earth.

Six Decades of Seismology at South Pole, Antarctica: Current Limitations and Future Opportunities to Facilitate New Geophysical Observations

Abstract Seismograms from the South Pole have been important for seismological observations for over six decades by providing (until 2007) the only continuous seismic records from the interior of the Antarctic continent. The South Pole, Antarctica station has undergone many updates over the years, including conversion to a digital recording station as part of the Global Seismographic Network (GSN) in 1991 and being relocated to multiple deep (>250 m) boreholes 8 km away from the station in 2003 (and renamed to Quiet South Pole, Antarctica [QSPA]). Notably, QSPA is the second most used GSN station by the National Earthquake Information Center to pick phases used to rapidly detect and locate earthquakes globally, and has been used for a variety of glaciological and oceanography studies. In addition, it is the only seismic station on the Earth where low-frequency (<5 mHz), normal-mode oscillations of the planet excited by large earthquakes can be recorded without influence from Earth’s rotation, and most of the direct effects of the solid Earth tide vanish. However, the current sensors are largely 1980s vintage, and, while able to make some lower-frequency observations from earthquakes, the borehole sensors appear unable to resolve ambient ground motions at frequencies lower than 25 mHz due to instrument noise and contamination from magnetic field variations. Recently developed borehole sensors offer the potential to extend background noise observations to below 3 mHz, which would substantially improve the fidelity and scientific value of seismic observations at South Pole. Through collaboration with the IceCube Neutrino Observatory, the opportunity exists to emplace a modern very broadband seismometer near the base (>2 km depth) of the Antarctic ice cap, which could lead to unprecedented seismic observations at long periods and facilitate a broad spectrum of Earth science studies.

Mantle Transition Zone Receiver Functions for Bermuda: Automation, Quality Control, and Interpretation

AbstractThe origin of the Bermuda rise remains ambiguous, despite, or perhaps because of, the existence of sometimes incongruous seismic wave‐speed and discontinuity models in the sub‐Bermudian mantle. Hence, whether Bermuda is the surface manifestation of a mantle plume remains in question. Using the largest data set of seismic records from Bermuda to date, we estimate radial receiver functions at the Global Seismographic Network station BBSR in multiple frequency bands, using iterative time‐domain deconvolution. Motivated by synthetic experiments using axisymmetric spectral‐element forward waveform modeling, we devise a quality metric for our receiver functions to aid in the automation and reproduction of mantle transition zone discontinuity studies. We interpret the complex signals we observe by considering the mineralogical controls on mantle transition zone discontinuity structure, and conclude that our results are likely to be indicative of a thicker than average mantle transition zone. Our result is incompatible with the canonical model of a whole mantle plume in an olivine dominated mantle; however, considerations of phase transitions in the garnet system would allow us to reconcile our observations with the possible presence of a through‐going hot thermal anomaly beneath Bermuda.

Upper-mantle discontinuities beneath Australia from transdimensional Bayesian inversions using multimode surface waves and receiver functions

SUMMARYRadially anisotropic S-wave structures under the permanent seismic stations in Australia are reconstructed using multimode surface waves (SWs) and receiver functions (RFs) in a framework of the Bayesian inference. We have developed a fully nonlinear method of joint inversions incorporating P-RFs and multimode Rayleigh and Love waves, based on the transdimensional Hierarchical Bayesian formulation. The method allows us to estimate a probabilistic Earth model taking account of the complexity and uncertainty of Earth structure, by treating the model parameters and data errors as unknowns. The Parallel Tempering algorithm is employed for the effective parameter search based on the reversible-jump Markov Chain Monte Carlo method. The use of higher modes enables us to enhance the sensitivity to the depth below the continental asthenosphere. Synthetic experiments indicate the importance of higher mode SWs for the better recovery of radial anisotropy in the whole depth range of the upper mantle. The method is applied to five Global Seismographic Network stations in Australia. While the S-wave models in eastern Australia show shallow lithosphere–asthenosphere boundary (LAB) above 100 km depth, those in central and Western Australia exhibit both mid-lithosphere discontinuities (MLDs) and LAB. Also, seismic velocity jumps equivalent to the Lehmann discontinuity (L-D) are found in all seismic stations. The L-D under the Australian continents is found at around 200–300 km depth, depending on locations. Radial anisotropy in the depth range between LAB and L-D tends to show faster SH anomalies, which may indicate the effects of horizontal shear underneath the fast-moving Australian plate.

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.

Monitoring the Processes of Interseismic Accumulation and Coseismic Release of Stresses in the Medium Nearby Earthquake Sources Based on the Analysis of Tidal Response of the Earth’s Surface

Abstract—The Global Seismographic Network (GSN) incorporating more than 150 seismic stations all over the world allows recording not only high-frequency seismic signals but also the response of the medium to semidiurnal and diurnal tidal impact. The correlation method for the analysis of GSN data developed by us makes it possible to detect variations in the amplitudes of tidal response associated with elastic moduli of the medium with an accuracy of 0.5%. The processes of stress accumulation and fracturing in the zone of a tectonic fault can significantly affect elastic properties of the medium which, in turn, may cause changes in tidal response of the medium in the vicinity of the earthquake’s source. In this work, a linear dependence is detected between the change in the amplitude of tidal response at GSN stations and the magnitude of the coseismic stress change in the medium in the vicinity of the station estimated from GPS data. The developed method for the analysis of tidal tilts can be used for studying the processes of accumulation and redistribution of tectonic stresses before the strong earthquakes in seismically active regions.

Determining the Orientation of Ocean-Bottom Seismometers on the Seafloor and Correcting for Polarity Flipping via Polarization Analysis and Waveform Modeling

Abstract The erroneous flipping of polarity in seismic records of ocean-bottom seismometers (OBSs) could go unnoticed and undiagnosed because it is coupled with unknown horizontal orientation of OBS instruments on the seafloor. In this study, we present detailed approaches to first identify potential errors in the flipping polarity of individual OBS instruments, and then determine the correct orientation of OBS instruments on the seafloor. We first conduct a series of tests by artificially flipping the polarity of seismic records of the Global Seismographic Network stations to determine the effects on orientation estimates, utilizing polarization characteristics of teleseismic P and Rayleigh waves, respectively. The tests demonstrate that erroneous polarity reversal in seismic recording could cause false estimates and reverse radial (R) and tangential (T) components. We determine the sensor orientations through comparing the observed waveforms to the synthetic waveforms, which could solve the ambiguity of R and T directions caused by potential erroneous polarity reversal of OBS data. We then apply the approaches to an OBS data set collected in the southern Mariana subduction zone to obtain the correct orientation for 9 out of 12 OBS instruments.

Seismic Sensors Record a Hurricane’s Roar

Newly installed infrasound sensors at a Global Seismographic Network station on Puerto Rico recorded the sounds of Hurricane Maria passing overhead.

Southern Alaska Lithosphere and Mantle Observation Network (SALMON): A Seismic Experiment Covering the Active Arc by Road, Boat, Plane, and Helicopter

ABSTRACT The Southern Alaska Lithosphere and Mantle Observation Network (SALMON) is a deployment of 28 broadband, direct‐burial posthole seismometers in the Cook Inlet region of the southern Alaska subduction zone. Here we describe the objectives of the project, the deployment strategy, and station design. We analyze time‐dependent and frequency‐dependent seismic noise for the first year of data at 18 SALMON stations, 11 of which are inside Cook Inlet basin and 7 of which are outside the basin. We compare noise at the SALMON stations with four previous collocated seismic stations, two Transportable Array stations, and one Global Seismographic Network station. The type of site, notably surface bedrock versus sedimentary basin, has the strongest impact on seismic noise levels across all periods and especially on horizontal components at long periods (>20 s). Seismic noise and earthquakes recorded by SALMON stations reveal amplification of seismic waves in Cook Inlet basin. Aftershocks of an M w 7.1 intraslab earthquake augment a catalog of local earthquakes to be used for source inversions and seismic imaging of the complex seismic structure in the Cook Inlet region.

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.

Attenuation of free spheroidal oscillations of the Earth after the M = 9 Earthquake in Sumatra and the super-deep Earthquake in the Sea of Okhotsk: I. the Admissible Q-factor range for the fundamental mode and overtones of the free spheroidal oscillations

The problem of reconstructing the depth distribution of density and the depth and frequency dependences of the mechanical Q-factor in the Earth’s mantle from the entire set of the present-day seismic and astrometric data on the travel times and periods of seismic waves and the amplitudes and phases of forced nutations is considered. The solution of the problem is refined by including the new data about the attenuation of the free oscillations of the Earth excited by the Sumatra earthquake (M = 9) and super-deep earthquake in the Sea of Okhotsk. The actual accuracy of the Q-factor is studied in the first part of the paper. To this end, we analyze (1) the convergence of the Q-factor estimated from the time series of different length shifted along the time axis and (2) the convergence of the results based on the different data. Since the accuracy of identifying all the periods and attenuation factors for the free oscillations from the Sumatra earthquake is significantly higher than for the earthquake with M = 9 in Japan, the data are only compared for the Sumatra and Okhotsk events. The signal-to-noise ratio (SNR) is analyzed based on the records from different Global Seismographic Network (GSN) stations including the station in Obninsk, the Kurchatov station in Kazakhstan, and the main ERM and MAJO stations in Japan. It is found that the highest SNR was observed in Obninsk. The inverse problem of reconstructing the density and Q-factor is solved for the frequency dependent real parts of the shear moduli with allowance for the most accurate data about the attenuation factors for the fundamental spheroidal modes of the free oscillations of the Earth.

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

Seismic interferometry with antipodal station pairs

In this study, we analyze continuous data from all Global Seismographic Network stations between year 2000 and 2009 and demonstrate that several body wave phases (e.g., PP, PcPPKP, SKSP, and PPS) propagating between nearly antipodal station pairs can be clearly observed without array stacking using the noise/coda cross‐correlation method. Based on temporal correlations with global seismicity, we show that the observed body waves are clearly earthquake related. Moreover, based on single‐earthquake analysis, we show that the earthquake coda energy observed between ~10,000 and 30,000 s after a large earthquake contributes the majority of the signal. We refine our method based on these observations and show that the signal can be significantly improved by selecting only earthquake coda times. With our improved processing, the PKIKP phase, which does not benefit from the focusing effect near the antipode, can now also clearly be observed for long‐distance station pairs.

A Statistical Low Noise Model of the Earth

An accurate modeling of background seismic noise is important to modern seismology in several respects, such as the identification of the best sites for permanent seismic stations, which see noise as a major nuisance; the definition of baselines for automatic detection of station malfunctioning; the definition of the instrumental requirements necessary to correctly record the lowest noises on Earth; and the burgeoning field of passive seismology, which uses noise as a source to explore the interior of the Earth. While a number of scientists have recently approached the study of defining the Earth seismic noise curve using statistics with various degrees of sophistication, the original empirical Peterson’s model (1993) is still a very popular reference. Called the new low noise model (NLNM), it is based simply on the envelope of the lowest noises recorded on the vertical component at 75 stations from eight networks. For each station, a maximum of 9.48 days of recording was considered after removing earthquakes and other transients. No statistical analysis was performed to assess the noise distribution and, as the author states and is evident in his Figure 2, due to the scarce availability of spectra from quiet sites at frequencies above 2.5 Hz, it cannot be considered reliable above this frequency. The NLNM has been followed by several noise models; the first one, proposed in 2004 by Berger et al. , was based on the analysis of hourly spectra from 118 Global Seismograph Network (GSN) stations in a one-year period (mid 2001–mid 2002) in order to capture the seasonal variability and provide results for both the horizontal and vertical components. In this analysis data were not scrutinized for transients and earthquakes search and removal. As a final low noise model, the envelope of the first percentile of the empirical distribution for each frequency …

A Statistical Low Noise Model of the Earth

An accurate modeling of background seismic noise is important to modern seismology in several respects, such as the identification of the best sites for permanent seismic stations, which see noise as a major nuisance; the definition of baselines for automatic detection of station malfunctioning; the definition of the instrumental requirements necessary to correctly record the lowest noises on Earth; and the burgeoning field of passive seismology, which uses noise as a source to explore the interior of the Earth. While a number of scientists have recently approached the study of defining the Earth seismic noise curve using statistics with various degrees of sophistication, the original empirical Peterson’s model (1993) is still a very popular reference. Called the new low noise model (NLNM), it is based simply on the envelope of the lowest noises recorded on the vertical component at 75 stations from eight networks. For each station, a maximum of 9.48 days of recording was considered after removing earthquakes and other transients. No statistical analysis was performed to assess the noise distribution and, as the author states and is evident in his Figure 2, due to the scarce availability of spectra from quiet sites at frequencies above 2.5 Hz, it cannot be considered reliable above this frequency. The NLNM has been followed by several noise models; the first one, proposed in 2004 by Berger et al. , was based on the analysis of hourly spectra from 118 Global Seismograph Network (GSN) stations in a one-year period (mid 2001–mid 2002) in order to capture the seasonal variability and provide results for both the horizontal and vertical components. In this analysis data were not scrutinized for transients and earthquakes search and removal. As a final low noise model, the envelope of the first percentile of the empirical distribution for each frequency …

Some Possible Causes of and Corrections for STS-1 Response Changes in the Global Seismographic Network

The Global Seismographic Network (GSN) (Figure 1) plays a key role in providing seismic data for global earthquake monitoring ( e.g. , Benz et al. 2005), earthquake science ( e.g. , Tsai et al. 2005), and studies of Earth structure ( e.g. , Dalton et al. 2008). One of the key GSN design goals is to “provide high fidelity digital recordings of all teleseismic ground motions (adequate to resolve at or near ambient noise up to the largest teleseismic signals over the bandwidth from free oscillations (10-4 Hz) to teleseismic body waves (up to approximately 15 Hz))” (GSN ad hoc Design Goals Subcommittee 2002). To help meet this goal, Streckeisen STS-1 seismometers were deployed at 80 GSN stations. Some of the GSN sensors have been deployed for more than 25 years. Several recent studies (Davis et al. 2005; Ekstrom et al. 2006; Davis and Berger 2007) have examined the question of overall calibration of the GSN. Ekstrom et al. (2006) indicated that a number of sites showed anomalous responses and suggested a gradual decay in the sensitivity. We have investigated the anomalous responses at several GSN sites. At least some of the problems observed by Ekstrom et al. (2006) may be attributed to humid air leaking into the feedback electronics of the STS-1 seismometers, which produces lower than normal sensitivities near the long-period corner of the instrument (360 seconds period). It appears that even though the feedback electronics boxes are designed to be sealed, water vapor can penetrate their interior after they have been exposed to highly humid seismometer vault air for extended periods. Highly humid air was also found to be present inside some STS-1 bell-jars (especially horizontal instruments) after loss of vacuum, resulting in corrosion and leakage between electrical conductors in connectors. This also resulted in a lowered …

Self-Noise Models of Seismic Instruments

Based on coherence analysis methods we develop a method for computing low self-noise models of seismic sensors. We calculate self-noise models for 11 different production seismometers. This collection contains the majority of sensors currently in use at Global Seismographic Network Stations. By developing these noise models, with a standard estimation method, we are able to make absolute comparisons between different models of seismic sensors. This also provides a method of identifying quality variations between two or more of the same model sensor. Studying Earth's free oscillations requires a large amount of seismic data with a high signal-to-noise ratio at long periods (Laske 2004). Recent tomographic studies using ambient seismic noise (Shapiro et al. 2005) also require the self-noise of seismic instruments to be below that of the Earth's ambient background noise, because as they use Earth noise as the seismic signal. It is also important when making temporary sensor deployments that the instrument's noise levels are below that of the signals being used in the study (Wilson et al. 2002). In order to verify that seismic instruments meet the above demands and other user requirements it is important from a testing standpoint, that one be able to measure the self-noise of seismic sensors and develop baselines for different models of seismic instruments. The different methods used to estimate self-noise of seismic sensors have made it difficult to do side-by-side comparisons of their performance (Hutt et al. 2009). This lack of a self-noise estimate standard makes it difficult to assess when a sensor's self-noise is above the manufacturers' specifications, indicating a possible problem with the sensor or noisy site conditions. In sensor development it is important to be able to compare a prototype sensor's self-noise to that of known self-noise levels of a reference sensor. On top of these complications some …