Global Seismographic Network Research Articles

Development and Operation of a Global‐Scale Seismographic Network: The IRIS/USGS GSN

AbstractFrom inception in the late 1980s up to the present, the Global Seismographic Network has produced high quality seismic data that has advanced research into the structure of the Earth's deep interior particularly the large‐scale heterogeneous elastic/anelastic structure of the mantle and core. The network's breadth of coverage enables images of great earthquakes impossible to obtain from regional networks or array data alone. Analysis of the data has provided new insights into non‐traditional seismic sources such as slow earthquakes, glaciers and landslides. Ancillary meteorological and infrasound sensors collocated at the sites support unique studies of volcanic events such as the recent eruption of the Hunga Tonga–Hunga Ha'apai volcano. Near real‐time transmission of the data to hazard warning centers has expanded the network's usefulness as a tool for rapid response to earthquakes, for warning communities effected by tsunamis, and for monitoring compliance with nuclear test ban treaties. The successful construction and operation of the network would not be possible without the outstanding international cooperation of many governmental, academic and private groups who have hosted components of the network.

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.

Inconsistent Citation of the Global Seismographic Network in Scientific Publications

Abstract The highly used Global Seismographic Network (GSN) is a pillar of the seismological research community and contributes to numerous groundbreaking publications. Despite its wide recognition, this survey found that the GSN is not consistently acknowledged in scientific literature and is underrepresented by roughly a factor of 3 in citation searches. Publication tracking is a key metric that factors into operational decisions and funding support for the network; thus, consistent and proper citation of the GSN is important. This study not only serves as a reminder for researchers using GSN observations to cite the network’s digital object identifiers (DOIs) but also promotes a community-wide conversation among researchers, journal editors, network operators, and other stakeholders regarding more standardized policies and review processes to ensure seismic networks are properly and consistently recognized for their contributions to research.

High-resolution mid-mantle imaging with multiple-taper SS-precursor estimates

SUMMARY SS-precursor imaging is used to image sharp interfaces within Earth’s mantle. Current SS-precursor techniques require tightly bandpassed signals (e.g. 0.02–0.05 Hz), limiting both vertical and horizontal resolutions. Higher frequency content would allow for the detection of finer structure in and around the mantle transition zone (MTZ). Here, we present a new SS-precursor deconvolution technique based on multiple-taper correlation (MTC). We show that applying MTC to SS-precursor deconvolution can increase the frequency cut-off up to 0.5 Hz, which potentially sharpens vertical resolution to ∼10 km. Furthermore, the high-pass frequency can be lowered (≪ 0.01 Hz), allowing more long-period energy to be included in the calculation, to better constrain the signal and reduce side lobes. Our method is benchmarked on full-waveform synthetic seismograms computed via AxiSEM3D for the PREM 1-D Earth model. We apply our novel MTC-SS-precursor deconvolution to ∼7000 seismograms recorded at broad-band borehole sensors of the Global Seismographic Network with source–receiver bounce points in the North-Central Pacific Ocean. The MTZ in this region appears to be thin, which agrees with previous results. We do not observe the 520-km discontinuity in our SS-precursor estimates. Additionally, we detect a low-velocity zone above the MTZ to the north of the Hawaiian Islands that has previously been inferred from asymmetry in side lobe amplitudes. Our high-frequency analysis demonstrates this feature to be a sharp interface (≤ 10-km thickness), rather than a thick wave speed gradient.

Seismic source mapping by surface wave time reversal: application to the great 2004 Sumatra earthquake

SUMMARY Different approaches to map seismic rupture in space and time often lead to incoherent results for the same event. Building on earlier work by our team, we ‘time-reverse’ and ‘backpropagate’ seismic surface wave recordings to study the focusing of the time-reversed field at the seismic source. Currently used source-imaging methods relying on seismic recordings neglect the information carried by surface waves, and mostly focus on the P-wave arrival alone. Our new method combines seismic time reversal approach with a surface wave ray-tracing algorithm based on a generalized spherical-harmonic parametrization of surface wave phase velocity, accounting for azimuthal anisotropy. It is applied to surface wave signal filtered within narrow-frequency bands, so that the inherently 3-D problem of simulating surface wave propagation is separated into a suite of 2-D problems, each of relatively limited computational cost. We validate our method through a number of synthetic tests, then apply it to the great 2004 Sumatra–Andaman earthquake, characterized by the extremely large extent of the ruptured fault. Many studies have estimated its rupture characteristics from seismological data (e.g. Lomax, Ni et al., Guilbert et al., Ishii et al., Krüger & Ohrnberger, Jaffe et al.) and geodetic data (e.g. Banerjee et al., Catherine et al., Vigny et al., Hashimoto et al., Bletery et al.). Applying our technique to recordings from only 89 stations of the Global Seismographic Network (GSN) and bandpass filtering the corresponding surface wave signal around 80-to-120, 50-to-110 and 40-to-90 s, we reproduce the findings of earlier studies, including in particular the northward direction of rupture propagation, its approximate spatial extent and duration, and the locations of the areas where most energy appears to be released.

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.

The global seismographic network reveals atmospherically coupled normal modes excited by the 2022 Hunga Tonga eruption

SUMMARY The eruption of the submarine Hunga Tonga-Hunga Haʻapai (Hunga Tonga) volcano on 15 January 2022, was one of the largest volcanic explosions recorded by modern geophysical instrumentation. The eruption was notable for the broad range of atmospheric wave phenomena it generated and for their unusual coupling with the oceans and solid Earth. The event was recorded worldwide across the Global Seismographic Network (GSN) by seismometers, microbarographs and infrasound sensors. The broad-band instrumentation in the GSN allows us to make high fidelity observations of spheroidal solid Earth normal modes from this event at frequencies near 3.7 and 4.4 mHz. Similar normal mode excitations were reported following the 1991 Pinatubo (Volcanic Explosivity Index of 6) eruption and were predicted, by theory, to arise from the excitation of mesosphere-scale acoustic modes of the atmosphere coupling with the solid Earth. Here, we compare observations for the Hunga Tonga and Pinatubo eruptions and find that both strongly excited the solid Earth normal mode 0S29 (3.72 mHz). However, the mean modal amplitude was roughly 11 times larger for the 2022 Hunga Tonga eruption. Estimates of attenuation (Q) for 0S29 across the GSN from temporal modal decay give Q = 332 ± 101, which is higher than estimates of Q for this mode using earthquake data (Q = 186.9 ± 5). Two microbarographs located at regional distances (<1000 km) to the volcano provide direct observations of the fundamental acoustic mode of the atmosphere. These pressure oscillations, first observed approximately 40 min after the onset of the eruption, are in phase with the seismic Rayleigh wave excitation and are recorded only by microbarographs in proximity (<1500 km) to the eruption. We infer that excitation of fundamental atmospheric modes occurs within a limited area close to the site of the eruption, where they excite select solid Earth fundamental spheroidal modes of similar frequencies that are globally recorded and have a higher apparent Q due to the extended duration of atmospheric oscillations.

Data Quality Analysis of China Permanent Seismic Network by Repeating Earthquakes

Abstract Highly similar waveforms recorded from repeating earthquakes can be utilized to evaluate the data quality of a seismic station. We used a hypothesis testing method to establish a data quality detection model based on repeating earthquakes. The model effectiveness was verified by using waveforms of a pair of repeating earthquakes, which occurred in northeastern Japan on 20 March 2021 (Mw=7.0) and 1 May 2021 (Mw=6.9), from 109 stations in the Global Seismographic Network. A total of 842 permanent broadband stations in mainland China were evaluated using this model. Eighteen anomalies were found mainly attributed to calibration, instrument noise, mass recentering, and regional long-period interference. We found that most of the stations function well. Moreover, utilizing repeating earthquakes to analyze the waveform quality can circumvent the need for extensive forward calculations, as well as greatly reduce the influence of source parameter uncertainties and structural complexity on the seismogram. Additionally, the need for detection in other datasets in different regional networks has broadened the scope of these applications.

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.

2000 Uglegorsk earthquake

The paper presents the results of waveform inversion of the Mw 6.8 August 4 (5), 2000 Uglegorsk earthquake (Sakhalin Island, Russia). The detailed rupture process of the 2000 Uglegorsk earthquake was simulated using the waveform inversion method. The average parameters were calculated for both nodal planes. Waveform inversion was carried out on the basis of Global Seismographic Network (GSN) data. Only P-waves from BHZ channels of all stations from the GSN were used. The simulated source parameters included a double-couple source, the scalar seismic moment, the source time function, and the slip directions. The performed studies made it possible to investigate the features of the rupture development and the amplitude of displacements along the east and west-dipping nodal planes of the August 4 (5), 2000 Uglegorsk earthquake. The obtained P-slip model for the 2000 Uglegorsk earthquake source area is in good agreement with the surface manifestations of the rupture according to the field geology data and the results of geodetic inversion.

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.

Discussion of: “A geological map of the Scotia Sea area constrained by bathymetry, geological data, geophysical data and seismic tomography models from the deep mantle”, by A. Beniest and W.P. Schellart (https://doi.org/10.1016/j.earscirevv.2020.103391)

Global geophysical networks provide powerful databases to infer globally coherent signals, and array processing techniques are useful for inferring them. In this study, we comprehensively analyze seven spherical harmonic-based array processing techniques: spherical harmonic stacking (SHS) as well as its gridded form (SHS_GT) and grid-interval weighted forms (SHS_GK1, SHS_GK2); matrix SHS (MSHS); multi-station experiment (MSE); and optimal sequence estimation (OSE). We first use more specific synthetic tests to evaluate the pros and cons of these techniques, and estimate bias in solutions caused by the station distributions. These methods are applied to four global observation networks, the Global Geodynamics Project (GGP) Network, the Global Seismographic Network (GSN), the Global Geomagnetic (GGM) Network and the Global GNSS Network. For the first time, we restored a much cleaner sequence for one singlet of the 0S2 mode based on the GGP network, and restored similar result for one singlet of the 3S1 mode based on the GSN network. We further isolate different Ylm-related tidal signals from the GGM network for the first time. Moreover, based on global GNSS observations, we estimate the Love number h21 = 0.6243(±7e−4) − 0.01(±6e−3)i at the Chandler Wobble (CW) frequency with OSE/MSHS (The accuracy of the estimate is an order of magnitude higher than the previous results), and further obtain the corresponding lower-mantle anelasticity (fr(ω) = −29.5 ± 0.9, fi(ω) = 12.0 ± 7.2). Our findings confirm that OSE and MSHS methods can more accurately obtain the complex amplitude of any Ylm-related signal, which is not possible with other methods (and we do obtain more precise results than previous studies upon using them); besides, we also confirm that OSE and MSHS methods can greatly reduce the interference of other signals to the target signals. Hence, we believe the results obtained from the OSE/MSHS will helpful for obtaining reasonable geophysical explanations.

Array processing techniques for analyzing global geophysical observation networks: Comprehensive analysis and typical applications

Global geophysical networks provide powerful databases to infer globally coherent signals, and array processing techniques are useful for inferring them. In this study, we comprehensively analyze seven spherical harmonic-based array processing techniques: spherical harmonic stacking (SHS) as well as its gridded form (SHS_GT) and grid-interval weighted forms (SHS_GK1, SHS_GK2); matrix SHS (MSHS); multi-station experiment (MSE); and optimal sequence estimation (OSE). We first use more specific synthetic tests to evaluate the pros and cons of these techniques, and estimate bias in solutions caused by the station distributions. These methods are applied to four global observation networks, the Global Geodynamics Project (GGP) Network, the Global Seismographic Network (GSN), the Global Geomagnetic (GGM) Network and the Global GNSS Network. For the first time, we restored a much cleaner sequence for one singlet of the 0S2 mode based on the GGP network, and restored similar result for one singlet of the 3S1 mode based on the GSN network. We further isolate different Ylm-related tidal signals from the GGM network for the first time. Moreover, based on global GNSS observations, we estimate the Love number h21 = 0.6243(±7e−4) − 0.01(±6e−3)i at the Chandler Wobble (CW) frequency with OSE/MSHS (The accuracy of the estimate is an order of magnitude higher than the previous results), and further obtain the corresponding lower-mantle anelasticity (fr(ω) = −29.5 ± 0.9, fi(ω) = 12.0 ± 7.2). Our findings confirm that OSE and MSHS methods can more accurately obtain the complex amplitude of any Ylm-related signal, which is not possible with other methods (and we do obtain more precise results than previous studies upon using them); besides, we also confirm that OSE and MSHS methods can greatly reduce the interference of other signals to the target signals. Hence, we believe the results obtained from the OSE/MSHS will helpful for obtaining reasonable geophysical explanations.

Synthetic Modeling of Ambient Seismic Noise Tomography Data

Ambient seismic noise tomography is one of the most widely used methods in seismological studies today, especially after a comprehensive Earth noise model was published and noise analysis was performed on the IRIS Global Seismographic Network. Furthermore, the Power Spectral Density technique was introduced to identify background seismic noise in the United States. Many studies have been carried out using the ambient seismic noise tomography method which can be broadly grouped into several groups based on the objectives and research targets, such as to determine the structure of the earth’s crust and the upper mantle, to know the thickness of the sedimentary basins, to know the tectonic settings and geological structures, to know volcanic systems and geothermal systems, knowing near-surface geological features and as a monitoring effort the Ambient Noise Tomography method carried out by repeated measurements or time lapse. In this study, we investigate the characteristics of the ambient noise seismic tomography method, both its advantages and limitations of the method by utilizing synthetic data modeling using a simple geological model. Synthetic data is generated based on 1D dispersion curve forward modelling and the forward modeling of surface waves travel time for each period, which is then convoluted with the wavelets of each periods, then doing reverse correlation using a reference signal to produce synthetic recording data. We found that the estimate target depth and vertical resolution depend on the recorded data periods and the synthetic data modeling can be used as a basis in determining the acquisition design.

A Review of Timing Accuracy across the Global Seismographic Network

AbstractThe accuracy of timing across a seismic network is important for locating earthquakes as well as studies that use phase-arrival information (e.g., tomography). The Global Seismographic Network (GSN) was designed with the goal of having reported timing be better than 10 ms. In this work, we provide a brief overview of how timing is kept across the GSN and discuss how clock-quality metrics are embedded in Standard for Exchange of Earthquake Data records. Specifically, blockette 1001 contains the timing-quality field, which can be used to identify time periods when poor clock quality could compromise timing accuracy. To verify the timing across the GSN, we compare cross-correlation lags between collocated sensors from 1 January 2000 to 1 January 2020. We find that the mean error is less than 10 ms, with much of the difference likely coming from the method or uncertainty in the phase response of the instruments. This indicates that timing across the GSN is potentially better than 10 ms. We conclude that unless clock quality is compromised (as indicated in blockette 1001), GSN data’s timing accuracy should be suitable for most current seismological applications that require 10 ms accuracy. To assist users, the GSN network operators have implemented a “gsn_timing” metric available via the Incorporated Research Institutions for Seismology Data Management Center that helps users identify data with substandard timing accuracy (the 10 ms design goal of the GSN).

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.

Rayleigh-Wave Amplitude Uncertainty across the Global Seismographic Network and Potential Implications for Global Tomography

ABSTRACT The Global Seismographic Network (GSN) is a multiuse, globally distributed seismic network used by seismologists, to both characterize earthquakes and study the Earth’s interior. Most stations in the network have two collocated broadband seismometers, which enable network operators to identify potential metadata and sensor issues. In this study, we investigate the accuracy with which surface waves can be measured across the GSN, by comparing waveforms of vertical-component Rayleigh waves from Mw 6 and larger events between collocated sensor pairs. We calculate both the amplitude deviation and correlation coefficient between waveforms at sensor pairs. In total, we make measurements on over 670,000 event–station pairs from events that occurred from 1 January 2010 to 1 January 2020. We find that the average sensor-pair amplitude deviation, and, therefore, GSN calibration level, is, approximately, 4% in the 25–250 s period band. Although, we find little difference in sensor-pair amplitude deviations as a function of period across the entire network, the amount of useable data decreases rapidly as a function of increasing period. For instance, we determined that just over 12% of records at 250 s period provided useable recordings (e.g., sensor-pair amplitude deviations of less than 20% and sensor-pair correlation greater than 0.95). We then use these amplitude-estimate deviations to identify how data coverage and quality could be limiting our ability to invert for whole Earth 3D attenuation models. We find an increase in the variance of our attenuation models with increasing period. For example, our degree 12 attenuation inversion at 250 s period shows 32% more variance than our degree 12 attenuation model at 25 s. This indicates that discrepancies of deep-mantle tomography between studies could be the result of these large uncertainties. Because these high uncertainties arise from limited, high-quality observations of long-period (>100 s) surface waves, improving data quality at remote GSN sites could greatly improve ray-path coverage, and facilitate more accurate and higher resolution models of deep Earth structure.

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.

The influences of large earthquake signals on the recovery of surface waves from ambient noise cross-correlation functions*

Ambient noise tomography (ANT) has been widely used to image crust and upmost mantle structures. ANT assumes that sources of ambient noise are diffuse and evenly distributed in space and the energy of different modes is equipartitioned. At present, the sources of the primary and the secondary microseisms are well studied, but there are only a few on the studies of long-period ambient noise sources. In this study, we study the effects of large earthquake signals on the recovery of surface waves from seismic ambient noise data recorded by seismic stations from the US permanent networks and Global Seismographic Network (GSN). Our results show that large earthquake signals play an important role on the recovery of long-period surface waves from ambient noise cross-correlation functions. Our results are consistent with previous studies that suggest the contribution of earthquake signals to the recovery of surface waves from cross-correlations of ambient noise is dominant at periods larger than 20–40 s.

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.