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At least 109 records · Page 6Linked to original sources

USGS2024

Cross-fade sampling: Extremely efficient Bayesian inversion for a variety of geophysical problems

This paper introduces cross-fade sampling, a computationally efficient Markov Chain Monte Carlo simulation method that uses a semi-analytical approach to quickly solve Bayesian inverse problems that do not themselves have an analytical solution. Cross-fading is efficient in two ways. First, it requires fewer samples to obtain the same quality simulation of the target probability density function (PDF). Secondly, it is much faster to evaluate the posterior probability of each sample than conventional sampling methods for simulating Bayesian posterior PDFs. Conventional methods require evaluating the prior probability (which describes your a priori constraints) and data likelihood (which describes the fit between the observations and the predictions of the model) for each sample model. However, cross-fading does not require evaluating the data likelihood, meaning that ‘big data’ can be fit with zero additional computational cost. Further, the cross-fading approach can be used to calculate the marginal likelihood associated with a model design, facilitating model comparison and Bayesian model averaging. Topics covered in this paper include derivation of the cross-fade approach and how it can be used to simulate Bayesian posterior PDFs and compute the marginal likelihood, discussion of the class of problems to which cross-fading can be applied (with examples from earthquake statistics, earthquake ground motion modelling, volcanic eruption forecasting, and finite fault slip modelling), demonstration of efficiency relative to existing sampling methods and discussion of how cross-fading can be used to account for prediction errors (i.e. epistemic errors) as part of the geophysical inverse problem.

Geophysical Journal International↗

USGS2024

Imaging of seismic discontinuities using an adjoint method

For imaging of seismic discontinuities at depth, reverse time migration (RTM) is a powerful method to apply to recordings of seismic events. It is especially powerful when an extensive receiver array, numerous seismic sources, or both, permit adequate reconstruction of incident and scattered wavefields at depth. Reconstructing either the incident or scattered wavefield at depth becomes less accurate when relatively few recordings of seismic events are available. Here we explore an inverse scattering approach to imaging discontinuities based on an adjoint method, employing sensitivity kernels (Frechet derivatives) that represent jumps in material properties across seismic-discontinuity surfaces. When combined with ray-based requirements on scattering geometry, it constitutes a powerful approach to determining the locations and amplitudes of the discontinuities, recovering only those properties that can be resolved by a spatially limited source and/or receiver distribution. This is illustrated by synthetic examples with local sources followed by a field example in a subduction zone setting

Washington↗

USGS2025

A crustal thermal model of the conterminous U.S. constrained by multiple data sets: A Monte-Carlo approach

The thermal structure of the continental crust plays a critical role in understanding its elastic and rheologic properties as well as its dynamic processes. Thermal parameter data sets on continental scales have been used to constrain the crustal thermal structure, including both the direct (e.g. temperature, heat flux and heat conductivity measured at the surface) and indirect (e.g. seismically derived Mohorovičić discontinuity (Moho) temperature, geomagnetically derived Curie depth) observations. In this study, we present a new continental scale crustal heat generation model with additional information from seismologically inferred crustal composition. Together with previous direct and indirect thermal parameter data sets in the conterminous United States, we use the new crustal heat generation model to construct a 3-D crustal temperature model under a newly developed Bayesian framework. Specifically, we first derive profiles of crustal heat generation based on an empirical geochemical relationship at 1683 locations where seismologically derived crustal composition information is available. Then for each of these locations, the average heat generation values in the upper, middle and lower crust are combined with other thermal parameters through a Markov Chain Monte-Carlo inversion for a conductive, vertically smooth temperature profile. The results, posterior distributions of temperature profiles, are used to generate a 3-D crustal thermal model with the uncertainties systematically assessed. The new temperature model overall exhibits similar patterns to that from the U.S. Geological Survey National Crustal Model, but also reduces possible biases and the model's dependence on a single thermal parameter.

conterminous United States↗

USGS2025

Identification of representative earthquakes for probabilistic tsunami hazard analysis (PTHA) using earthquake rupture forecasts and machine learning

As probabilistic tsunami hazard analysis (PTHA) focuses more on assessments for localized, populous regions, techniques are needed to identify a subsample of representative earthquake ruptures to make the computational requirements for producing high-resolution hazard maps tractable. Moreover, the greatest epistemic uncertainty in seismic PTHA is related to source characterization, which is often poorly defined and subjective. We address these two salient issues by applying streamlined earthquake rupture forecasts (ERFs), based on combinatorial optimization methods, to an unsupervised machine learning workflow for identifying representative ruptures. ERFs determine the optimal distribution of a millennia-scale sample of earthquakes by inverting the observed slip rate on major faults. We use two previously developed combinatorial optimization ERFs, integer programming and greedy sequential, to produce the optimal location of ruptures with seismic moments sampled from a regional Gutenberg–Richter magnitude–frequency distribution. These ruptures in turn are used to calculate peak nearshore tsunami amplitude, using computationally efficient tsunami Green's functions. An unsupervised machine learning workflow is then used to identify a small subsample of the earthquakes input to ERFs for onshore PTHA analysis. We eliminate epistemic uncertainty related to source distribution under traditional PTHA analysis; in its place, a quantifiable, less subjective and generally smaller uncertainty related to the input to ERFs is included. The Nankai subduction zone is used as a test case, where previous ERFs have been conducted. Results indicate that the locations of representative earthquakes are sensitive to choice of magnitude–area relation and to whether a minimum cumulative stress objective is imposed on the fault. In general, incorporating ERFs into PTHA provide a physically self-consistent method to incorporate fault slip information in determining representative earthquakes for onshore PTHA, eliminating a major source of epistemic uncertainty.

Nankai subduction zone↗

USGS2025

Infrasonic directivity of monopole, dipole, and bipole ground-surface reflected sources

Infrasound (acoustic waves below 20 Hz) can be used to detect, locate and quantify activity in the atmosphere such as volcanic eruptions and anthropogenic explosions. Attempts to quantify volcanic eruption parameters such as exit velocity, plume height and mass flow rate using infrasound data depend strongly on assumptions of the acoustic source type. Infrasonic sources may produce omnidirectional or directional wavefields, while propagation effects, such as interaction with topography, can induce further wavefield directivity that is measured by field instrumentation. Limited sampling of these wavefields can hinder our ability to infer the underlying source, and thus our understanding of the eruption characteristics. Equivalent sources are often used to represent acoustic source mechanisms and resultant wavefields. In this study, we review equivalent acoustic sources as they pertain to infrasonic scale and wavelengths commonly encountered in very local ( ⁠< 5 km range) geophysical field deployments. We highlight the equivalent infrasonic bipole source that can be induced by ground-reflection of an elevated monopole; we are not aware of any prior infrasound studies that use the bipole source concept. We use analytical and numerical methods to explore source directivity of monopole, dipole and bipole ground-reflected sources at infrasonic frequencies as well as the additional directivity complications introduced by interactions with topography. We illustrate that for typical volcano-infrasound wavelengths, increasing height above the ground as well as increasing source frequency leads to increased wavefield directivity. Numerical modelling using a simple omnidirectional monopole source embedded in topography further illustrates that both horizontal and vertical infrasound directionality can be induced by topography at the distance scales appropriate for local volcano infrasound monitoring. Information summarized in this analytical and numerical exploration of infrasound directivity may be used to help guide future volcano-infrasound field deployments intended to estimate source parameters or quantify wavefield directivity. Analytic solutions for simple whole-space or half-space atmospheres provide useful formulations for planning or initially analysing geophysical field-scale experimental data; however, especially at very local distances from the source ( ⁠< 5 km), 3-D simulations are necessary to account for complex topography commonly encountered in volcano-infrasound applications.

Geophysical Journal International↗

USGS2025

Divide and conquer: Separating the two probabilities in seismic phase picking

There are two fundamental probabilities in the seismic phase picking process – the probability of the existence of a seismic phase (detection probability) and the probability of correctly identifying the phase arrival time (timing probability). The nearly ubiquitous approach in developing deep learning phase picking models is to use a kernel, such as a truncated Gaussian, to mask the labeled phase arrival time, and train a segmentation model. Once a model is trained, the times of the peaks in the output are taken as phase arrival times (picks) and the height of the peaks are taken as “probability” of the picks. Here, we show that this “probability” represents neither the detection nor the timing probabilty because this approach forces the output to follow the shape of the kernel. We introduce an approach using two models to estimate these two distinct probabilities. We use a binary classifier with a calibrated confidence to address the detection probability and a multi-class classifier to obtain a probability mass function to address the timing probability. This new approach makes the deep learning-based phase picking process more interpretable and gives us options to logically control seismic monitoring workflows.

Geophysical Journal International↗

USGS2025

Refinements to the attenuated propagation of local earthquake shaking (APPLES) ground-motion-based earthquake early warning algorithm

We refined the Attenuated ProPagation of Local Earthquake Shaking (APPLES) ground-motion-based earthquake early warning (EEW) approach, and directly compare APPLES performance with that of the source-characterization-based U.S. ShakeAlert EEW system for a suite of historical earthquakes in the U.S. West Coast and Japan. APPLES is an extension of the Propagation of Local Undamped Motion (PLUM) algorithm in which observed shaking intensity at seismic stations is used to forward-predict intensity distributions to surrounding areas using an attenuation model derived from an intensity prediction equation. We test new configuration options within APPLES, such as using the second highest estimated ground motion rather than the maximum, to better match median ground-motion observations and reduce alerts for small magnitude earthquakes, both of which are key alerting priorities within ShakeAlert. We evaluate these configurations alongside ShakeAlert by comparing the ground-motion estimation accuracy and available warning times relative to station observations and ShakeMap distributions. Our preferred APPLES configuration produces accurate ground-motion estimates and corresponds better with median observations compared to ShakeAlert’s estimates. This preferred configuration substantially reduces alert issuance for M < 5.0 earthquakes compared to the previous APPLES configuration, and alert-release criteria can further restrict alerts to primarily M ≥ 5.5 earthquakes without requiring magnitude estimation. Prioritizing matching median-observed ground motions may reduce APPLES warning times compared to configurations that were tuned to avoid missed alerts (such as those that use the maximum estimated ground motions), which can lead to shorter warning times compared to ShakeAlert for the same alert threshold. However, station-based warning time assessments demonstrate that APPLES can outperform ShakeAlert for high target thresholds. APPLES is a simple, independent EEW approach that may improve the robustness of EEW for the West Coast of the U.S.

California, Oregon, Washington↗

USGS2026

Subsurface structure across the Tacoma Basin, Washington State, using trans-dimensional Bayesian inversion of fundamental mode spatial autocorrelation data

Spatial autocorrelation (SPAC), the azimuthal average of the normalized cross-correlation between equidistant station pairs deployed in a 2-D array, is widely used to image the subsurface structure. However, the rigorous estimate of subsurface structure and its uncertainties as a function of depth using SPAC data is challenging due to the nonlinear relation between the SPAC data and Earth structure as well as the trade-off between depth and velocity. Additionally, data noise is strongly correlated due to data processing (e.g. filtering, stacking from multiple time segments and azimuthal averaging). Most studies do not account for the correlated noise and fix the ratio of compressional-wave velocity ( V P ) to shear-wave velocity ( V s ) (i.e. V P / V s ratio) and the number of layers, both of which are typically unknown. To address these challenges, we develop a hierarchical trans-dimensional Bayesian inversion of fundamental mode of SPAC data that properly accounts for the correlated data noise, samples the V P / V s ratio and relaxes the number of layers (i.e. model parametrization) to be unknown in the inversion. We further examine the limitation of using only fundamental modes in the inversion. Our synthetic experiments show that the inversion recovers an incorrect model unless we sample the correlated noise and V P / V s ratio in the inversion. The inversion is then applied to SPAC data acquired at 19 sites across the Tacoma basin in Washington State to characterize the V s and the time-averaged V s over 30-m depth ( V s 30 ). Our results show that the V s 30 varies from ∼200 to 800 m s −1 . The V s 30 within the basin is higher in the middle and lower on the east and west sides. We find that these V s 30 values vary with geologic unit. The uncertainties for V s 30 are within 20 m s −1 in average except for the most eastern site TB28. Additionally, the uncertainties are greater for deeper depths beneath most of the sites as the sensitivity decreases as a function of depth. The Vs structure as a function of depth is also complex beneath some sites, possibly because the SPAC curves are affected by higher order Rayleigh modes that are not considered in the inversion. To better constrain the deeper V s structure, V s 30 and/or other average measures of V s over depth, additional constraints from complementary data, such as ellipticity or geologic data are needed. Moreover, our synthetic experiments show that higher order modes can have significant effect in the inversion results, particularly when there is a low-velocity layer.

Washington↗

USGS2026

Surface-wave relocation and characterization of the 2024–2025 dyking episode along the Fentale–Dofen segment of the Ethiopian rift

From late-December 2024 to mid-March 2025, a 50-km-long dyke intrusion triggered over 300 earthquakes (magnitude 4 to 5.9) between Fentale and Dofen volcanoes along the Northern Main Ethiopian Rift. Dyke intrusions periodically occur along the Fentale–Dofen magmatic segment and are an expression of ongoing rift extension. Preliminary analyses using interferometric synthetic aperture radar revealed extensive ground deformation (up to 60 cm), which closely matched the temporal and spatial evolution of surface manifestations and earthquake locations from global catalogues. While global catalogues are critical for real-time monitoring, the precision of locations in remote and or sparsely instrumented regions can be low. In this investigation, we present surface-wave relocation results of the dyking episode that began near Fentale volcano in December 2024. We estimate relative locations using differential traveltimes measured from regional-to-teleseismic distance surface-wave observations of earthquakes reported by the U.S. Geological Survey. Relative relocations reduce the initial region of diffuse seismicity to a 50-km-long narrow band bounding the strike of surface manifestations and the zone of maximum surface deformation. We demonstrate the precision of surface-wave relocations over incremental time periods, capturing the progression of dyking from seismic onset through seismic migration and caldera subsidence. Results showcase the utility of surface-wave relocations in the characterization of dyking episodes and provide complementary insights into the current understanding of the Fentale–Dofen volcanic plumbing system.

Geophysical Journal International↗

USGS2013

Size distribution of Parkfield’s microearthquakes reflects changes in surface creep rate

The nucleation area of the series of M6 events in Parkfield has been shown to be characterized by low b-values throughout the seismic cycle. Since low b -values represent high differential stresses, the asperity structure seems to be always stably stressed and even unaffected by the latest main shock in 2004. However, because fault loading rates and applied shear stress vary with time, some degree of temporal variability of the b -value within stable blocks is to be expected. We discuss in this study adequate techniques and uncertainty treatment for a detailed analysis of the temporal evolution of b -values. We show that the derived signal for the Parkfield asperity correlates with changes in surface creep, suggesting a sensitive time resolution of the b-value stress meter, and confirming near-critical loading conditions within the Parkfield asperity.

Geophysical Journal International↗

USGS2013

Ambient seismic noise interferometry in Hawai'i reveals long-range observability of volcanic tremor

The use of seismic noise interferometry to retrieve Green's functions and the analysis of volcanic tremor are both useful in studying volcano dynamics. Whereas seismic noise interferometry allows long-range extraction of interpretable signals from a relatively weak noise wavefield, the characterization of volcanic tremor often requires a dense seismic array close to the source. We here show that standard processing of seismic noise interferometry yields volcanic tremor signals observable over large distances exceeding 50 km. Our study comprises 2.5 yr of data from the U.S. Geological Survey Hawaiian Volcano Observatory short period seismic network. Examining more than 700 station pairs, we find anomalous and temporally coherent signals that obscure the Green's functions. The time windows and frequency bands of these anomalous signals correspond well with the characteristics of previously studied volcanic tremor sources at Pu'u 'Ō'ō and Halema'uma'u craters. We use the derived noise cross-correlation functions to perform a grid-search for source location, confirming that these signals are surface waves originating from the known tremor sources. A grid-search with only distant stations verifies that useful tremor signals can indeed be recovered far from the source. Our results suggest that the specific data processing in seismic noise interferometry—typically used for Green's function retrieval—can aid in the study of both the wavefield and source location of volcanic tremor over large distances. In view of using the derived Green's functions to image heterogeneity and study temporal velocity changes at volcanic regions, however, our results illustrate how care should be taken when contamination by tremor may be present.

Hawai'i↗

USGS2013

Quantifying potential earthquake and tsunami hazard in the Lesser Antilles subduction zone of the Caribbean region

In this study, we quantify the seismic and tsunami hazard in the Lesser Antilles subduction zone, focusing on the plate interface offshore of Guadeloupe. We compare potential strain accumulated via GPS-derived plate motions to strain release due to earthquakes that have occurred over the past 110 yr, and compute the resulting moment deficit. Our results suggest that enough strain is currently stored in the seismogenic zone of the Lesser Antilles subduction arc in the region of Guadeloupe to cause a large and damaging earthquake of magnitude M w ∼ 8.2 ± 0.4. We model several scenario earthquakes over this magnitude range, using a variety of earthquake magnitudes and rupture areas, and utilizing the USGS ShakeMap and PAGER software packages. Strong ground shaking during the earthquake will likely cause loss of life and damage estimated to be in the range of several tens to several hundreds of fatalities and hundreds of millions to potentially billions of U.S. dollars of damage. In addition, such an event could produce a significant tsunami. Modelled tsunamis resulting from these scenario earthquakes predict meter-scale wave amplitudes even for events at the lower end of our magnitude range (M 7.8), and heights of over 3 m in several locations with our favoured scenario (M 8.0, partially locked interface from 15–45 km depth). In all scenarios, only short lead-times (on the order of tens of minutes) would be possible in the Caribbean before the arrival of damaging waves.

Lesser Antilles↗

USGS2014

Seismological analyses of the 2010 March 11, Pichilemu, Chile Mw 7.0 and Mw 6.9 coastal intraplate earthquakes

On 2010 March 11, a sequence of large, shallow continental crust earthquakes shook central Chile. Two normal faulting events with magnitudes around M w 7.0 and M w 6.9 occurred just 15 min apart, located near the town of Pichilemu. These kinds of large intraplate, inland crustal earthquakes are rare above the Chilean subduction zone, and it is important to better understand their relationship with the 2010 February 27, M w 8.8, Maule earthquake, which ruptured the adjacent megathrust plate boundary. We present a broad seismological analysis of these earthquakes by using both teleseismic and regional data. We compute seismic moment tensors for both events via a W-phase inversion, and test sensitivities to various inversion parameters in order to assess the stability of the solutions. The first event, at 14 hr 39 min GMT, is well constrained, displaying a fault plane with strike of N145°E, and a preferred dip angle of 55°SW, consistent with the trend of aftershock locations and other published results. Teleseismic finite-fault inversions for this event show a large slip zone along the southern part of the fault, correlating well with the reported spatial density of aftershocks. The second earthquake (14 hr 55 min GMT) appears to have ruptured a fault branching southward from the previous ruptured fault, within the hanging wall of the first event. Modelling seismograms at regional to teleseismic distances (Δ > 10°) is quite challenging because the observed seismic wave fields of both events overlap, increasing apparent complexity for the second earthquake. We perform both point- and extended-source inversions at regional and teleseismic distances, assessing model sensitivities resulting from variations in fault orientation, dimension, and hypocentre location. Results show that the focal mechanism for the second event features a steeper dip angle and a strike rotated slightly clockwise with respect to the previous event. This kind of geological fault configuration, with secondary rupture in the hanging wall of a large normal fault, is commonly observed in extensional geological regimes. We propose that both earthquakes form part of a typical normal fault diverging splay, where the secondary fault connects to the main fault at depth. To ascertain more information on the spatial and temporal details of slip for both events, we gathered near-fault seismological and geodetic data. Through forward modelling of near-fault synthetic seismograms we build a kinematic k −2 earthquake source model with spatially distributed slip on the fault that, to first-order, explains both coseismic static displacement GPS vectors and short-period seismometer observations at the closest sites. As expected, the results for the first event agree with the focal mechanism derived from teleseismic modelling, with a magnitude M w 6.97. Similarly, near-fault modelling for the second event suggests rupture along a normal fault, M w 6.90, characterized by a steeper dip angle (dip = 74°) and a strike clockwise rotated (strike = 155°) with respect to the previous event.

Pichilemu↗

USGS2014

Post-earthquake relaxation using a spectral element method: 2.5-D case

The computation of quasi-static deformation for axisymmetric viscoelastic structures on a gravitating spherical earth is addressed using the spectral element method (SEM). A 2-D spectral element domain is defined with respect to spherical coordinates of radius and angular distance from a pole of symmetry, and 3-D viscoelastic structure is assumed to be azimuthally symmetric with respect to this pole. A point dislocation source that is periodic in azimuth is implemented with a truncated sequence of azimuthal order numbers. Viscoelasticity is limited to linear rheologies and is implemented with the correspondence principle in the Laplace transform domain. This leads to a series of decoupled 2-D problems which are solved with the SEM. Inverse Laplace transform of the independent 2-D solutions leads to the time-domain solution of the 3-D equations of quasi-static equilibrium imposed on a 2-D structure. The numerical procedure is verified through comparison with analytic solutions for finite faults embedded in a laterally homogeneous viscoelastic structure. This methodology is applicable to situations where the predominant structure varies in one horizontal direction, such as a structural contrast across (or parallel to) a long strike-slip fault.

Geophysical Journal International↗

USGS2014

CyberShake-derived ground-motion prediction models for the Los Angeles region with application to earthquake early warning

Real-time applications such as earthquake early warning (EEW) typically use empirical ground-motion prediction equations (GMPEs) along with event magnitude and source-to-site distances to estimate expected shaking levels. In this simplified approach, effects due to finite-fault geometry, directivity and site and basin response are often generalized, which may lead to a significant under- or overestimation of shaking from large earthquakes ( M > 6.5) in some locations. For enhanced site-specific ground-motion predictions considering 3-D wave-propagation effects, we develop support vector regression (SVR) models from the SCEC CyberShake low-frequency (<0.5 Hz) and broad-band (0–10 Hz) data sets. CyberShake encompasses 3-D wave-propagation simulations of >415 000 finite-fault rupture scenarios (6.5 ≤ M ≤ 8.5) for southern California defined in UCERF 2.0. We use CyberShake to demonstrate the application of synthetic waveform data to EEW as a ‘proof of concept’, being aware that these simulations are not yet fully validated and might not appropriately sample the range of rupture uncertainty. Our regression models predict the maximum and the temporal evolution of instrumental intensity (MMI) at 71 selected test sites using only the hypocentre, magnitude and rupture ratio, which characterizes uni- and bilateral rupture propagation. Our regression approach is completely data-driven (where here the CyberShake simulations are considered data) and does not enforce pre-defined functional forms or dependencies among input parameters. The models were established from a subset (∼20 per cent) of CyberShake simulations, but can explain MMI values of all >400 k rupture scenarios with a standard deviation of about 0.4 intensity units. We apply our models to determine threshold magnitudes (and warning times) for various active faults in southern California that earthquakes need to exceed to cause at least ‘moderate’, ‘strong’ or ‘very strong’ shaking in the Los Angeles (LA) basin. These thresholds are used to construct a simple and robust EEW algorithm: to declare a warning, the algorithm only needs to locate the earthquake and to verify that the corresponding magnitude threshold is exceeded. The models predict that a relatively moderate M 6.5–7 earthquake along the Palos Verdes, Newport-Inglewood/Rose Canyon, Elsinore or San Jacinto faults with a rupture propagating towards LA could cause ‘very strong’ to ‘severe’ shaking in the LA basin; however, warning times for these events could exceed 30 s.

California↗

USGS2014

Bayesian historical earthquake relocation: an example from the 1909 Taipei earthquake

Locating earthquakes from the beginning of the modern instrumental period is complicated by the fact that there are few good-quality seismograms and what traveltimes do exist may be corrupted by both large phase-pick errors and clock errors. Here, we outline a Bayesian approach to simultaneous inference of not only the hypocentre location but also the clock errors at each station and the origin time of the earthquake. This methodology improves the solution for the source location and also provides an uncertainty analysis on all of the parameters included in the inversion. As an example, we applied this Bayesian approach to the well-studied 1909 M w 7 Taipei earthquake. While our epicentre location and origin time for the 1909 Taipei earthquake are consistent with earlier studies, our focal depth is significantly shallower suggesting a higher seismic hazard to the populous Taipei metropolitan area than previously supposed.

Taipei↗

USGS2014

Investigation of the high-frequency attenuation parameter, κ (kappa), from aftershocks of the 2010 M w 8.8 Maule, Chile earthquake

The Bío Bío region of Chile experienced a vigorous aftershock sequence following the 2010 February 27 M w 8.8 Maule earthquake. The immediate aftershock sequence was captured by two temporary seismic deployments: the Quake Catcher Network Rapid Aftershock Mobilization Program (QCN RAMP) and the Incorporated Research Institutions for Seismology CHile Aftershock Mobilization Program (IRIS CHAMP). Here, we use moderate to large aftershocks ( M L ≥ 4.0) occurring between 2010 March 1 and June 30 recorded by QCN RAMP and IRIS CHAMP stations to determine the spectral decay parameter, kappa ( κ ). First, we compare waveforms and κ estimates from the lower-resolution QCN stations to the IRIS CHAMP stations to ensure the QCN data are of sufficient quality. We find that QCN stations provide reasonable estimates of κ in comparison to traditional seismic sensors and provide valuable additional observations of local ground motion variation. Using data from both deployments, we investigate the variation in κ for the region to determine if κ is influenced primarily by local geological structure, path attenuation, or source properties (e.g. magnitude, mechanism and depth). Estimates of κ for the Bío Bío region range from 0.0022 to 0.0704 s with a mean of 0.0295 s and are in good agreement with κ values previously reported for similar tectonic environments. κ correlates with epicentral distance and, to a lesser degree, with source magnitude. We find little to no correlation between the site kappa, κ 0 , and mapped geology, although we were only able to compare the data to a low-resolution map of surficial geology. These results support an increasing number of studies that suggest κ observations can be attributed to a combination of source, path and site properties; additionally, measured κ are often highly scattered making it difficult to separate the contribution from each of these factors. Thus, our results suggest that contributions from the site, path and source should be carefully considered when interpreting κ values.

Bío Bío Region↗

USGS2015

Point spread functions for earthquake source imaging: An interpretation based on seismic interferometry

Recently, various methods have been proposed and applied for earthquake source imaging, and theoretical relationships among the methods have been studied. In this study, we make a follow-up theoretical study to better understand the meanings of earthquake source imaging. For imaging problems, the point spread function (PSF) is used to describe the degree of blurring and degradation in an obtained image of a target object as a response of an imaging system. In this study, we formulate PSFs for earthquake source imaging. By calculating the PSFs, we find that waveform source inversion methods remove the effect of the PSF and are free from artifacts. However, the other source imaging methods are affected by the PSF and suffer from the effect of blurring and degradation due to the restricted distribution of receivers. Consequently, careful treatment of the effect is necessary when using the source imaging methods other than waveform inversions. Moreover, the PSF for source imaging is found to have a link with seismic interferometry with the help of the source-receiver reciprocity of Green’s functions. In particular, the PSF can be related to Green’s function for cases in which receivers are distributed so as to completely surround the sources. Furthermore, the PSF acts as a low-pass filter. Given these considerations, the PSF is quite useful for understanding the physical meaning of earthquake source imaging.

Geophysical Journal International↗