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At least 73 records · Page 4Linked to original sources
USGS2022

Fast rupture of the 2009 Mw 6.9 Canal de Ballenas earthquake in the Gulf of California dynamically triggers seismicity in California

In the Gulf of California, Mexico, the relative motion across the North America-Pacific boundary is accommodated by a series of marine transform faults and spreading centers. About 40 M>6 earthquakes have occurred in the region since 1960. On 3 August 2009, an Mw 6.9 earthquake occurred near Canal de Ballenas in the region. The earthquake was a strike-slip event with a shallow hypocenter that is likely close to the seafloor. In contrast to an adjacent M7 earthquake, this earthquake triggered a ground-motion-based earthquake early warning algorithm being tested in southern California (∼600 km away). This observation suggests that the abnormally large ground motions and dynamic strains observed for this earthquake relate to its rupture properties. To investigate this possibility, we image the rupture process and resolve the slip distribution of the event using a P-wave back-projection approach and a teleseismic, finite-fault inversion method. Results from these two independent analyses indicate a relatively simple, unilateral rupture propagation directed along-strike in the northward direction. However, the average rupture speed is estimated around 4 km/s, suggesting a possible supershear rupture. The supershear speed is also supported by a Rayleigh wave Mach cone analysis, although uncertainties in local velocity structure preclude a definitive conclusion. The Canal de Ballenas earthquake dynamically triggered seismicity at multiple sites in California, with triggering response characteristics varying from location-to-location. For instance, some of the triggered earthquakes in California occurred up to 24 hours later, suggesting that nonlinear triggering mechanisms likely have modulated their occurrence.

Baja California↗
USGS2022

Connection between the cross correlation and the Green’s function: Strain and rotation of surface waves

Recent developments of distributed acoustic sensing (DAS) techniques and rotational seismometers enable us to record strain and rotational seismograms. This prompts us to adapt the methods used for traditional translational seismograms to strain and rotational seismograms. Recently, we extended the formulation of the spatial autocorrelation (SPAC) method to strain, rotation and tilt records. According to seismic interferometry for translation seismograms, cross correlations have clear connections to Green's functions under the isotropy and equipartition of noise wavefields. In this study, we clarify similar connections for strain and rotation seismograms. Because we extend the formulation in the frequency domain, we actually study the connection between the cross-spectral matrix of strain and rotation at two receivers and the Green's tensor. First, we provide a proof under a general framework by simply extending the proof for translation to that for strain and rotation. The proof shows the following results: (1) The cross-spectral matrix of (i, j)-component strains at two receivers is found to be proportional to the strain Green's tensor at one receiver for the sum of (i, j)- and (j, i)-components of the moment tensor source at the other receiver. (2) The cross-spectral matrix of (i, j)-component rotations at two receivers is found to be proportional to the rotation Green's tensor at one receiver for the difference of (i, j)- and (j, i)-components of the moment tensor source at the other receiver. Necessary assumptions for the proof are the isotropy and equipartition of the wavefield. We then check this proof with specific calculations for surface waves observed on the free surface. The proof is confirmed for the isotropic incidence of random-phase surface waves with a specific ratio between Rayleigh and Love wave energies. Seismic interferometry for strain and rotation was already studied. However, the connection of cross correlations to the Green's function for strain and rotation seismograms is discovered by this study for the first time. A specific proof for body waves that is assured by the general proof will be our next study.

Geophysical Journal International↗
USGS2022

Characteristics, relationships and precision of direct acoustic-to-seismic coupling measurements from local explosions

Acoustic energy originating from explosions, sonic booms, bolides and thunderclaps have been recorded on seismometers since the 1950s. Direct pressure loading from the passing acoustic wave has been modelled and consistently observed to produce ground deformations of the near surface that have retrograde elliptical particle motions. In the past decade, increased deployments of colocated seismometers and infrasound sensors have driven efforts to use the transfer function between direct acoustic-to-seismic coupling to infer near-surface material properties including seismic velocity structure and elastic moduli. In this study, we use a small aperture (≈600 m) array of broadband seismometers installed in different manners and depths in both granite and sedimentary overburden to understand the fundamental nature and repeatability of seismic excitation from 1 to 15 Hz using horizontally propagating acoustic waves generated by 97 local (2–10 km) explosions. In agreement with modelling, we find that the ground motions induced by acoustic-to-seismic coupling attenuate rapidly with depth. We confirm the modelled relation between acoustic and ground motion amplitudes, but show that within one acoustic wavelength, the uncertainty in the transfer coefficient between seismic and acoustic energy at a given seismic station increases linearly with separation distance between the seismic and acoustic sensor. We attribute this observation to the rapid decorrelation of the infrasonic wavefield across small spatial scales and recommend colocating seismic and infrasound sensors for use in studies seeking to invert for near-surface material properties. Additionally, contrary to acoustic-to-seismic coupling theory and prior observations, we find that seismometers emplaced in granite do not record retrograde elliptical particle motions in response to direct pressure loading. We rule out seismometer tilt effects as a likely source of this observations and suggest that existing models of acoustic-to-seismic excitation may be too simplistic for seismometers placed in high rigidity materials.

Geophysical Journal International↗
USGS2022

Infrasound single-channel noise reduction: application to detection and localization of explosive volcanism in Alaska using backprojection and array processing

Infrasound sensors are deployed in a variety of spatial configurations and scales for geophysical monitoring, including networks of single sensors and networks of multisensor infrasound arrays. Infrasound signal detection strategies exploiting these data commonly make use of intersensor correlation and coherence (array processing, multichannel correlation); network-based tracking of signal features (e.g. reverse time migration); or a combination of these such as backazimuth cross-bearings for multiple arrays. Single-sensor trace-based denoising techniques offer significant potential to improve all of these various infrasound data processing strategies, but have not previously been investigated in detail. Single-sensor denoising represents a pre-processing step that could reduce the effects of ambient infrasound and wind noise in infrasound signal association and location workflows. We systematically investigate the utility of a range of single-sensor denoising methods for infrasound data processing, including noise gating, non-negative matrix factorization, and data-adaptive Wiener filtering. For the data testbed, we use the relatively dense regional infrasound network in Alaska, which records a high rate of volcanic eruptions with signals varying in power, duration, and waveform and spectral character. We primarily use data from the 2016–2017 Bogoslof volcanic eruption, which included multiple explosions, and synthetics. The Bogoslof volcanic sequence provides an opportunity to investigate regional infrasound detection, association, and location for a set of real sources with varying source spectra subject to anisotropic atmospheric propagation and varying noise levels (both incoherent wind noise and coherent ambient infrasound, primarily microbaroms). We illustrate the advantages and disadvantages of the different denoising methods in categories such as event detection, waveform distortion, the need for manual data labelling, and computational cost. For all approaches, denoising generally performs better for signals with higher signal-to-noise ratios and with less spectral and temporal overlap between signals and noise. Microbaroms are the most globally pervasive and repetitive coherent ambient infrasound noise source, with such noise often referred to as clutter or interference. We find that denoising offers significant potential for microbarom clutter reduction. Single-channel denoising of microbaroms prior to standard array processing enhances both the quantity and bandwidth of detectable volcanic events. We find that reduction of incoherent wind noise is more challenging using the denoising methods we investigate; thus, station hardware (wind noise reduction systems) and site selection remain critical and cannot be replaced by currently available digital denoising methodologies. Overall, we find that adding single-channel denoising as a component in the processing workflow can benefit a variety of infrasound signal detection, association, and location schemes. The denoising methods can also isolate the noise itself, with utility in statistically characterizing ambient infrasound noise.

Alaska↗
USGS2022

P- and S-wave velocity estimation by ensemble Kalman inversion of dispersion data for strong motion stations in California

This study uses an ensemble Kalman method for near-surface seismic site characterization of 154 network earthquake monitoring stations in California to improve the resolution of S -wave velocity ( V S ) and P -wave velocity ( V P ) profiles—up to the resolution depth—coupled with better quantification of uncertainties compared to previous site characterization studies at this network. These stations were part of the Yong et al . site characterization project, with selected stations based on future recordings of ground motions that are expected to exceed 10 per cent peak ground acceleration in 50 yr. To estimate V S and V P from experimental dispersion data, Yong et al . investigated these stations using linearized (local search and iteration) routines, and Yong et al . later studied a subset of these stations using nonlinear (global search and optimization) routines. In both studies, the selection of model parameters—that is, discretization of the V S and V P profiles with only five fixed thickness layers—was mainly based on trial and error. In contrast, this paper uses an approximate Bayesian method to assimilate experimental dispersion data and sequentially update an ensemble of particle estimates that span the V S and V P parameter spaces. Doing so, we systematically determine the most probable profiles conditioned on the experimental dispersion data, the introduced noise levels, and a priori knowledge in the form of physical constraints. We consider two configurations to discretize the soil depth from the surface to half of the maximum discernible wavelength obtained from the experimental dispersion data, namely refined and coarse models, and two initial models for each configuration to study solution multiplicity. Our results suggest that using the refined model for the top surface layers improves the resolution of near-surface site characteristics and the model’s success rate in capturing dispersion data at high frequencies. All models result in similar V S but distinct V P profiles, with increasing uncertainty at deeper layers, suggesting that the fundamental mode of Rayleigh wave dispersion data is not adequate to constrain the P -wave velocity profile and the S -wave velocity close to the resolution depth.

California↗
USGS2022

What to expect when you are expecting earthquake early warning

We present a strategy for earthquake early warning (EEW) alerting that focuses on providing users with a target level of performance for their shaking level of interest (for example, ensuring that users receive warnings for at least 95 per cent of the occurrences of that shaking level). We explore the factors that can affect the accuracy of EEW shaking forecasts including site conditions (which can make shaking more or less varied), the share of earthquake hazard that comes from outlier events, and even the metric of shaking being forecast (with modified Mercalli intensity being the most uncertain quantity to forecast). To provide different locations with the same level of EEW performance, the alert issuance criteria will need to change based on these factors. Finally, we present a hierarchy of information approach with which to communicate EEW system design and performance to the public and other stakeholders, including how frequently alerts will be issued and how accurate those alerts will be.

Geophysical Journal International↗
USGS2022

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

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 0 S 29 (3.72 mHz). However, the mean modal amplitude was roughly 11 times larger for the 2022 Hunga Tonga eruption. Estimates of attenuation ( Q ) for 0 S 29 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.

Geophysical Journal International↗
USGS2022

Impact of sedimentary basins on Green’s functions for static slip inversion

Earthquakes often occur in regions with complex material structure, such as sedimentary basins or mantle wedges. However, the majority of co-seismic modelling studies assume a simplified, often homogeneous elastic structure in order to expedite the process of model construction and speed up calculations. These co-seismic forward models are used to produce Green’s functions for finite-fault inversions, so any assumptions made in the forward model may introduce bias into estimated slip models. In this study, we use a synthetic model of a sedimentary basin to investigate the impact of 3-D elastic structure on forward models of co-seismic surface deformation. We find that 3-D elastic structure can cause changes in the shape of surface deformation patterns. The magnitude of this effect appears to be primarily controlled by the magnitude of contrast in material properties, rather than the sharpness of contrast, the fault orientation, the location of the fault, or the slip orientation. As examples of real-world cases, we explore the impact of 3-D elastic structure with a model of the Taipei basin in Taiwan and a simulated earthquake on the Sanchaio fault, and with a 3-D geologic model of the San Francisco Bay Area and a slip model of the 1984 Morgan Hill earthquake on the Calaveras fault. Once again, we find that the presence of the basin leads to differences in the shape and amplitude of the surface deformation pattern, but we observe that the primary differences are in the magnitude of surface deformation and can be accounted for with a layered elastic structure. Our results imply that the use of homogeneous Green’s functions may lead to bias in inferred slip models in regions with sedimentary basins, so, at a minimum, a layered velocity structure should be used.

Geophysical Journal International↗
USGS2022

Structural properties of the Southern San Andreas fault zone in northern Coachella Valley from magnetotelluric imaging

The Southern San Andreas fault (SSAF) poses one of the largest seismic risks in California. Yet, there is much ambiguity regarding its deeper structural properties around Coachella Valley, in large part due to the relative paucity of everyday seismicity. Here, we image a multistranded section of the SSAF using a non-seismic method, namely magnetotelluric (MT) soundings, to help inform depth-dependent fault zone geometry, fluid content and porosity. The acquired MT data and resultant inversion models highlight a conductive column encompassing the SSAF zone that includes a 2–3 km wide vertical to steeply northeast dipping conductor down to ∼4 km depth (maximum of ∼1 Ω·m at 2 km depth) and another prominent conductor in the ductile crust (∼1 Ω·m at 12 km depth and slightly southwest of the surface SSAF). We estimate porosities of 18–44 per cent for the conductive uppermost 500 m, a 10–15 per cent porosity at 2 km depth and that small amounts (0.1–3 per cent) of interconnected hypersaline fluids produce the deeper conductor. Located northeast of this conductive region is mostly resistive crust indicating dry crystalline rock that extends down to ∼20 km in places. Most of the local seismicity is associated with this resistive region. Located farther northeast still is a conductive region at >13 km depth and separate from the one to the southwest. The imaged anomalies permit two interpretations. The SSAF zone is vertical to steeply northeast dipping in the upper crust and (1) is near vertical at greater depth creating mostly an impermeable barrier for northeast fluid migration or (2) continues to dip northeast but is relatively dry and resistive up to ∼13 km depth where it manifests as a secondary deep ductile crustal conductor. Taken together with existing knowledge, the first interpretation is more likely but more MT investigations are required.

California↗
USGS2023

Quantification of geodetic strain rate uncertainties and implications for seismic hazard estimates

Geodetic velocity data provide first-order constraints on crustal surface strain rates, which in turn are linked to seismic hazard. Estimating the 2-D surface strain tensor everywhere requires knowledge of the surface velocity field everywhere, while geodetic data such as Global Navigation Satellite System (GNSS) only have spatially scattered measurements on the surface of the Earth. To use these data to estimate strain rates, some type of interpolation is required. In this study, we review methodologies for strain rate estimation and compare a suite of methods, including a new implementation based on the geostatistical method of kriging, to compare variation between methods with uncertainty based on one method. We estimate the velocity field and calculate strain rates in southern California using a GNSS velocity field and five different interpolation methods to understand the sources of variability in inferred strain rates. Uncertainty related to data noise and station spacing (aleatoric uncertainty) is minimal where station spacing is dense and maximum far from observations. Differences between methods, related to epistemic uncertainty, are usually highest in areas of high strain rate due to differences in how gradients in the velocity field are handled by different interpolation methods. Parameter choices, unsurprisingly, have a strong influence on strain rate field, and we propose the traditional L -curve approach as one method for quantifying the inherent trade-off between fit to the data and models that are reflective of tectonic strain rates. Doing so, we find total variability between five representative strain rate models to be roughly 40 per cent, a much lower value than roughly 100 per cent that was found in previous studies (Hearn et al .). Using multiple methods to tune parameters and calculate strain rates provides a better understanding of the range of acceptable models for a given velocity field. Finally, we present an open-source Python package (Materna et al .) for calculating strain rates, Strain_2D, which allows for the same data and model grid to be used in multiple strain rate methods, can be extended with other methods from the community, and provides an interface for comparing strain rate models, calculating statistics and estimating strain rate uncertainty for a given GNSS data set.

Geophysical Journal International↗
USGS2023

Converted-wave reverse time migration imaging in subduction zone settings

We use a newly developed 2-D elastic reverse time migration (RTM) imaging algorithm based on the Helmholtz decomposition to test approaches for imaging the descending slab in subduction zone regions using local earthquake sources. Our elastic RTM method is designed to reconstruct incident and scattered wavefields at depth, isolate constituent P- and S- wave components via Helmholtz decomposition, and evaluate normalized imaging functions that leverage dominant P and S signals. This method allows us to target particular converted-wave scattering geometries, for example incident S to scattered P , which may be expected to have dominant signals in any given data set. The method is intended to be applied to dense seismic array observations that adequately capture both incident and converted wavefields. We draw a direct connection between our imaging functions and the first-order contrasts in shear wave material properties across seismic discontinuities. Through tests on synthetic data using either S → P or P → S conversions, we find that our technique can successfully recover the structure of a subducting slab using data from a dense wide-angle array of surface stations. We also calculate images with a small-aperture array to test the impact of array geometry on image resolution and interpretability. Our results show that our imaging technique is capable of imaging multiple seismic discontinuities at depth, even with a small number of earthquakes, but that limitations arise when a small aperture array is considered. In this case, the presence of artefacts makes it more difficult to determine the location of seismic discontinuities.

Geophysical Journal International↗
USGS2023

Multiphysics modelling in PyLith: Poroelasticity

PyLith, a community, open-source code for modelling quasi-static and dynamic crustal deformation with an emphasis on earthquake faulting, has recently been updated with a flexible multiphysics implementation. We demonstrate the versatility of the multiphysics implementation by extending the code to model fully coupled continuum poromechanics. We verify the newly incorporated physics using standard benchmarks for a porous medium saturated with a slightly compressible fluid. The benchmarks include the 1-D consolidation problem as outlined by Terzaghi, Mandel’s problem for the 2-D case, and Cryer’s problem for the 3-D case. All three benchmarks have been added to the PyLith continuous integration test suite. We compare the closed form analytical solution for each benchmark against solutions generated by our updated code, and lastly, demonstrate that the poroelastic material formulation may be used alongside the existing fault implementation in PyLith.

Geophysical Journal International↗
USGS2024

Constraints from GPS measurements on plate coupling within the Makran subduction zone and tsunami scenarios in the western Indian Ocean

Plate-coupling estimates and previous seismicity indicate that portions of the Makran megathrust of southern Pakistan and Iran are partially coupled and have the potential to produce future magnitude 7+ earthquakes. However, the GPS observations needed to constrain coupling models are sparse and lead to an incomplete understanding of regional earthquake and tsunami hazard. In this study, we assess GPS velocities for plate coupling of the Makran subduction zone with specific attention to model resolution and the accretionary prism rheology. We use finite element model-derived Green's functions to invert for the interseismic slip deficit under both elastic and viscoelastic Earth assumptions. We use the model resolution matrix to characterize plate-coupling scenarios that are consistent with the limited spatial resolution afforded by GPS observations. We then forward model the corresponding tsunami responses at major coastal cities within the western Indian Ocean basin. Our plate-coupling results show potential segmentation of the megathrust with varying coupling from west to east, but do not rule out a scenario where the entire length of the megathrust could rupture in a single earthquake. The full subduction zone rupture scenarios suggest that the Makran may be able to produce earthquakes up to M w 9.2. The corresponding tsunami model from the largest earthquake event ( M w 9.2) estimates maximum wave heights reaching 2–5 m at major port cities in the northern Arabian Sea region. Cities on the west coast of India are less affected (1–2 m). Coastlines bounding eastern Africa, and the Strait of Hormuz, are the least affected (<1 m).

Geophysical Journal International↗
USGS2024

Density structure of Kilauea volcano: Implications for magma storage and transport

A Bayesian linear regression to determine the bias in the Nafe–Drake relationship between compressional velocity and density provides an improved model for the density structure of Kīlauea volcano, Hawaiʻi. In previous work, we combined the results of seismic tomography with the Nafe–Drake relationship between compressional velocity and density to explain the large values of gravity disturbances overlying the summits and rift zones of the island's volcanoes. These results were used to determine mechanisms for gravitational instability of the island flanks. Here, we use laboratory measurements of the relationship of velocity and density for a wide range of Hawaiʻi island rocks as a prior in a Bayesian regression, with seismic tomography, to refine the 3-D density structure for Kīlauea volcano. This refined structure shows dense bodies (3220 kg m −3 ) between 5 and 8 km below sea level that underly regions of magma storage, found from geodetic and geophysical studies, beneath the summit and East Rift Zone of Kīlauea volcano. Above these bodies, density isosurfaces surround and cradle sources of pressure change determined from geodetic models, both at the summit and along the East Rift Zone. Continued subsidence of the summit following the 2018 eruption is aligned with a bowl-shaped density structure, formed primarily by density isosurfaces between 2800 and 2900 kg m −3 at 4–6 km depth. These surfaces underly the ∼3 km depth at which dyke injection initiates, are largely aseismic, and from their density values are inferred to contain high concentrations of olivine. Taken together, these density structures are consistent with an olivine-rich mush with variable porosity that increases in density with depth and provides a mechanism to form olivine cumulates both at the summit and along the rift zones. This structural framework for Kīlauea volcano is consistent with melt and mush transport occurring over a large range of depths to accommodate the growth and spreading of the volcano.

Hawaii↗
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↗