South-East Asia hosts the largest and most complicated subduction system of our planet, associated with extensive volcanism and seismicity. Obtaining high-resolution seismic images of South-East Asia can provide important constraints on the lateral variations of physical parameters such as density, composition, temperature, and viscosity of this dynamic patchwork. In turn, this has relevant implications on our ability to forecast its geodynamic evolution by numerical modeling. In this study, we join all the publicly-available seismic data distributed across the Malay Peninsula, Sumatra, Java, Sulawesi, South Borneo, and North Australia (amounting of 468 broad-band seismic receivers) with the continuous seismograms from 70 receivers recently installed in North Borneo, resulting in an unprecedented seismic coverage of the region.
We first use such data to extract Rayleigh and Love phase velocities based on both seismic ambient noise and teleseismic earthquakes. Overall, we retrieve 14,036 Rayleigh- and 12,005 Love-wave dispersion curves, covering surface-wave periods between 3 and 150 s and sensitive to both the shallow crust and the upper mantle. We then invert the dispersion curves for phase-velocity maps at different periods, using a linearized-inversion algorithm based on the ray theory with a roughness damping constraint. In doing so, we adopt an adaptive parameterization, allowing for a finer resolution of the resulting maps in the areas characterized by a relatively high density of measurements. At relatively short periods (<20 s), the phase-velocity maps are characterized by strong lateral heterogeneities. We find, for example, relatively low velocities in correspondence of the Central- and South-Sumatra Basin, ascribed to thick sedimentary layers, and higher velocities in the (adjacent) Barisan Mountains. Low velocities also characterize a large region approximately centered onto the Merapi volcano (Central Java), the Mentawai islands (in correspondence of the Mentawai Fault System), the Sahul Shelf (including the East Timor island), and the marine region between east Borneo and Sulawesi. Relatively high velocities are found below the Banda Sea. The amplitude of such lateral variations quickly decreases at larger periods and, among the most pronounced features, we observe relatively low velocities in the north-east of Borneo (as opposed to its south-western part), and high velocities in the Celebes Sea (north of the North-Sulawesi Trench).
At the time of writing, we are planning to translate the phase-velocity maps thus retrieved into shear-wave velocity (Vs) as a function of depth. Specifically, we plan to extract one Rayleigh- and one Love-wave phase-velocity profile for each grid cell constituting our phase-velocity maps, and (non-linearly) jointly invert them for Vs using the neighbourhood algorithm. The resulting 3-D tomographic model will thus be interpreted in light of the existing literature on the study area, involving (but not limited to) geodynamic and geologic models, geophysical, geochemical, and geodetic observations.

How to cite: Magrini, F., De Siena, L., Pilia, S., Rawlinson, N., and Kaus, B.: Surface-wave tomography of the South-East Asia by joint inversion of Rayleigh and Love phase velocities from seismic ambient noise and teleseismic earthquakes, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2459, https://doi.org/10.5194/egusphere-egu22-2459, 2022.

Given that subduction is an important driver of plate tectonics on Earth, it is notable that the effects of subduction termination are often complex and poorly understood. Northern Borneo is a prime example of a post-subduction environment, where two subduction zones have terminated within the last 20 Ma. The region however has seen very few seismic studies likely due to the low levels of seismicity in the region compared to the rest of Southeast Asia and due to the challenging deployment environment. The goal of the northern Borneo Orogeny Seismic Survey (nBOSS) network, which operated between 2018 and 2020 and consisted of 47 broadband instruments, was to provide constraints and answer first order questions about the structure of the lithosphere and asthenosphere in this post-subduction setting. Waveform data from this network were supplemented with data recorded by 33 permanent instruments operated by the Malaysian meteorological authority, METMalaysia. In this study we produce the first model of the crustal shear wave velocity structure under northern Borneo using surface wave ambient noise tomography to try and better understand the effects of subduction termination on the crust and to better understand the present day structure of the crust in this region which has not been imaged in this way before. We use a trans-dimensional tomography to produce variable resolution 2D Rayleigh wave phase velocity maps in the period range 2-30 seconds sampled every 2 seconds. Then to produce the final 3D shear wave velocity model a series of 1D inversions were used in combination with a neural network that is trained to find a generalised solution to the 1D inverse problem for this data set. This helps to prevent artefacts forming in the final model as a result of there being no lateral correlations in the 1D inversions by providing the more region specific trained neural network to perform the bulk of the 1D inversions. The result is a model that shows a detailed 3D shear wave velocity structure of the crust that matches expected velocity anomalies from known geological features. This includes the large sedimentary basins in the region, which are revealed as large slow velocity anomalies. Our new model agrees with results from other methods used to study this region, including receiver functions and surface wave tomography.

How to cite: Fone, J., Pilia, S., Rawlinson, N., and Hou, S.: Ambient noise tomography of post-subduction setting in northern Borneo enhanced with machine learning, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7668, https://doi.org/10.5194/egusphere-egu22-7668, 2022.

How to cite: Karkowska, K., Wilde-Piórko, M., Dykowski, P., Sękowski, M., and Polkowski, M.: Exploring the Earth's mantle structure based on joint gravimetric and seismometric group-velocity dispersion curves of Rayleigh waves, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6235, https://doi.org/10.5194/egusphere-egu22-6235, 2022.

How to cite: Agius, M., Magrini, F., Diaferia, G., Kastle, E., Cammarano, F., Faccenna, C., Funiciello, F., and van der Meijde, M.: Shear-velocity structure and dynamics beneath the Central Mediterranean inferred from seismic surface waves , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4870, https://doi.org/10.5194/egusphere-egu22-4870, 2022.

Ultra-slow spreading ridges are characterized by huge volcanic complexes which are separated by up to 150 km long amagmatic segments. The mechanisms controlling the ultra-slow spreading ridges are not yet fully understood. With the aim to better understand the spreading mechanisms and the flow of the magma beneath the volcanic complexes an ocean-bottom array has been installed along a segment of the ultra-slow spreading Knipovich Ridge in the Greenland sea. The array consists of 23 LOBSTER-type ocean bottom seismometers (OBS) from the DEPAS pool and 5 LOBSTERs from the Institute of Geophysics of the Polish Academy of Sciences. We aim to constrain the crustal and mantle structure beneath the segment of the Knipovich Ridge by using receiver functions calculated from teleseismic events.

Seismic data, recorded on the ocean bottom, are highly contaminated by different noise sources, which are dominating at frequencies below 1 Hz. During the experiment the DEPAS-LOBSTERs were equipped with a MCS recorder and a Güralp CMG-40T seismometer (changed now to 6D6 recorder and Trillium Compact seismometer). This characteristic design introduces electronic noise at selected stations at frequencies below 0.2 Hz. Recently head-buoy-strumming has been identified as additional noise source at frequencies above 0.5 Hz during tidal currents. Hence, most teleseismic signals are masked by the high noise level, especially on the horizontal components. However, a good signal to noise ratio on both, the vertical and horizontal components is crucial for seismological analysis, especially the receiver function method. Applying the HPS noise reduction algorithm on OBS data, as shown by Zali et al (submitted in 2021), allows to separate percussive or transient signals, such as the teleseismic earthquake from more harmonic and monochromatic signals, such as most of the noise generated at the ocean bottom.

The results of the HPS noise reduction algorithm processing of selected KNIPAS station data show a significantly reduced noise level below 1 Hz on all seismogram components, especially on the horizontals. Here, the signal-to-noise ratio increased by up to 3.2-3.7 (average by 1.4-1.6). The increased signal-to-noise ratio on the noise reduced data allows for more reliable receiver function results and their interpretation. Here, we show the reduced noise level on the OBS data and compare the receiver function results calculated from original data with the results from noise-reduced data.

How to cite: Rein, T., Zali, Z., Krüger, F., and Schlindwein, V.: Receiver Function analysis of noise reduced OBS data recorded at the ultra-slow spreading Knipovich Ridge, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3755, https://doi.org/10.5194/egusphere-egu22-3755, 2022.

The maximum achievable resolution of a tomographic model varies spatially and depends on the data sampling and errors in the data. The significant and continual measurement-error decreases in seismology and data-redundancy increases have reduced the impact of random errors on tomographic models. Systematic errors, however, are resistant to data redundancy and their effect on the model is difficult to predict; often this results in models dominated by noise if the target resolution is too high. Here, we develop a method for finding the optimal resolving length at every point, implementing it for surface-wave tomography. As in the Backus-Gilbert method, every solution at a point results from an entire-system inversion, and the model error is reduced by increasing the model-parameter averaging. The key advantage of our method consists in its direct, empirical evaluation of the posterior model error at a point.

We first measure interstation phase velocities at simultaneously recording station pairs and compute phase-velocity maps at densely, logarithmically spaced periods. Numerous versions of the maps with varying smoothness are then computed, ranging from very rough to very smooth. Phase-velocity curves extracted from the maps at every point can be inverted for shear-velocity (V_S) profiles. As we show, errors in these phase-velocity curves increase nearly monotonically with the map roughness. We evaluate the error by isolating the roughness of the phase-velocity curve that cannot be explained by any Earth structure and determine the optimal resolving length at a point such that the error of the local phase-velocity curve is below a threshold.

A 3-D V_S model is then computed by the inversion of the composite phase-velocity maps with an optimal resolution at every point. Importantly, the optimal resolving length does not scale with the density of the data coverage: some of the best-sampled locations display relatively low lateral resolution, due to systematic errors in the data.

We apply this method to image the lithosphere and underlying mantle beneath Ireland and Britain. Our very large data produces a total of 11238 inter-station dispersion curves, spanning a very broad total period range (4–500 s), yielding unprecedented data coverage of the area and providing state-of-the-art regional resolution from the crust to the deep asthenosphere. Our tomography reveals pronounced, previously unknown variations in the lithospheric thickness beneath Ireland and Britain, with implications for their Caledonian assembly and for the mechanisms of the British Tertiary Igneous Province magmatism.

How to cite: Bonadio, R., Lebedev, S., Meier, T., Arroucau, P., Schaeffer, A. J., Licciardi, A., Agius, M. R., Horan, C., Collins, L., O'Really, B. M., Readman, P. W., and Working Group, I. A.: Optimal resolution tomography with error tracking and the structure of the crust and upper mantle beneath Ireland and Britain, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4477, https://doi.org/10.5194/egusphere-egu22-4477, 2022.

The North Anatolian Fault (NAF) is a right-lateral, strike-slip fault in the northern part of the Anatolian peninsula. It is estimated to have a length of up to 1500 km, extending westwards between the Karliova Triple Junction, where it nucleates, to the Aegean Sea. In the west and close to the Sea of Marmara, the NAF splays into northern (NNAF) and southern (SNAF) strands. The splay of the western part of the NAF separates the area into three primary terranes: the Istanbul Zone (north of the northern strand), the Armutlu-Almacik Block (between the two strands of the fault) and the Sakarya Zone (south of the southern strand).

There have been a series of high-magnitude earthquakes along the NAF since the 1930s, migrating from east to west. In order to investigate the western part of the North Anatolian Fault Zone (NAFZ), which is the most seismically active at the moment, the Dense Array for North Anatolia (DANA) temporary seismic network was deployed for 18 months between 2012 and 2013. A set of local earthquakes, recorded by DANA, were utilised to study the 2D scattering and coda attenuation structure in the western NAFZ, between 1 and 18 Hz. P-wave arrival times were manually picked and the events were re-located using the Non-Linear Location software. Peak-delay travel times were calculated as a measure of forward scattering, and the exponential decay of the coda wave envelopes was used to invert for the absorption structure using multiple scattering sensitivity kernels.

The obtained models are 2D averages of the first 10-15 km of the crust, where the majority of the seismic activity is located and they have been compared to recent geophysical studies in the same area. The scattering structure, between 1 and 6 Hz, highlights the three main tectonic units in the area. The absorption structure is generally more heterogeneous than the scattering structure, with the overall absorption decreasing as the frequency increases. The lithological variations and heterogeneity between and within the three terranes of the area, arising from the complex tectonic history of the region, are believed to be the main reasons for the scattering and absorption observations made. The high absorption zones observed along the two branches of the fault, and especially the southern branch, is a very important finding, as the signature of the southern branch in geophysical studies is often unclear.

How to cite: Sketsiou, P., Cornwell, D., and De Siena, L.: Scattering and Absorption Imaging of the North Anatolian Fault Zone, northern Turkey, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2686, https://doi.org/10.5194/egusphere-egu22-2686, 2022.

Seismic full-waveform inversion (FWI) produces high resolution images of the subsurface by exploiting information in full seismic waveforms, and has been applied at global, regional and industrial spatial scales. FWI is traditionally solved by using optimization, in which one seeks a best model by minimizing the misfit between observed waveforms and model predicted waveforms. Due to the nonlinearity of the physical relationship between model parameters and waveforms, a good starting model is often required to produce a reasonable model. In addition, the optimization methods cannot produce accurate uncertainty estimates, which are required to better interpret the results.

To estimate uncertainties more accurately, nonlinear Bayesian methods have been deployed to solve the FWI problem. Monte Carlo sampling is one such algorithm but it is computationally expensive, and all Markov chain Monte Carlo-based methods are difficult to parallelise fully. Variational inference provides an efficient, fully parallelisable alternative methodology. This is a class of methods that optimize an approximation to a probability distribution describing post-inversion parameter uncertainties. Both Monte Carlo and variational full waveform inversion (VFWI) have been applied previously to solve 2D FWI problems, but neither of them have been applied to 3D FWI. In this study we apply the VFWI method to a 3D FWI problem. Specifically we use Stein variational gradient descent (SVGD) method to solve the 3D Bayesian FWI problem and to obtain an optimised set of samples of the full posterior probability distribution. The aim of this study is to explore performance of the method in 3D, to assess the computational requirements and to provide useful information for practitioners. Our results demonstrate that the 3D VFWI is practical, at least for small problems, and can be applied to image the subsurface in reality.

How to cite: Zhang, X., Zhou, M., Lomas, A., Zheng, Y., and Curtis, A.: 3D Variational Full-Waveform Inversion, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8319, https://doi.org/10.5194/egusphere-egu22-8319, 2022.

How to cite: Lanteri, A., Gebraad, L., Zunino, A., and Fichtner, A.: Hamiltonian Monte Carlo Inversion of Surface Wave Dispersion to Evaluate their Potential to Constrain the Density Distribution in the Earth., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6399, https://doi.org/10.5194/egusphere-egu22-6399, 2022.

Multi-parameter teleseismic full-waveform inversion (FWI) can provide key insights on the composition and thermal state of the lithosphere. In the isotropic version of such inversions, one classically inverts for a set of independent model parameters,  for example (density, Vp, Vs). In this study, we demonstrate that by introducing model covariance matrices with non-diagonal terms to FWI, i.e. accounting for the existing correlations between density, Vp, and Vs, has a dramatic impact on the quality of the reconstructed models. We perform synthetic tests using with a simple subduction model. The teleseismic and regional wavefields are computed with our FK-SEM hybrid method. We invert vertical and radial component P waveforms from four teleseismic events coming from different epicentral distances and azimuths. We use a hierarchical iterative l-BFGS inversion, starting at long period (T > 10 s) to obtain a long wavelength model, and then progressively decreasing the spatial smoothing and cut-off period to 5 s and then 2.5 s. We also demonstrate that a complete non-diagonal model covariance matrix allows us to make the inversion results consistent, i.e. independent of the model parameterization. The inversions which account for the correlations between model parameters provide better models especially for density and Vs, less numerical artifacts, and are characterized by a faster convergence rate compared to inversions performed by assuming that model parameters are independent.

How to cite: Kan, L.-Y., Chevrot, S., and Monteiller, V.: A consistent full waveform inversion scheme for imaging heterogeneous isotropic elastic media, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7767, https://doi.org/10.5194/egusphere-egu22-7767, 2022.

The Earth’s crust hosts most of the geo-resources of societal interests (e.g. minerals, geothermal energy etc.). Integrative approaches combining geophysical and petrological observations to study the mantle assuming thermodynamic equilibrium are relatively common nowadays. However, in contrast to the mantle, where thermodynamic equilibrium is prevalent, vast portions of the crust are thermodynamically metastable. This is because equilibration processes are essentially temperature activated and the temperature in the crust is usually too low to trigger them. Consequently, the mineralogical assemblage of crustal rocks is mostly decoupled from the in situ pressure and temperature conditions, reflecting instead the conditions present at the moment of rock formation. Here we present a new methodology for integrated geophysical-petrological multi-data modelling of the crust. Our primary constraining data are fundamental mode Rayleigh wave surface wave dispersion curves determined by interstation cross-correlation measurements and teleseisms, as well as surface elevation (isostasy) and heat flow. Additional prior information is provided by P-wave velocities coming from controlled source and body wave tomography data. The inversion is framed within an integrated geophysical-petrological setting where mantle seismic velocities and densities are computed thermodynamically as a function of the in situ temperature and compositional conditions. In this work we develop a new parameterization of the crust where we first invert following global statistical correlations between Vp, Vs and crustal densities for different lithologies in a two-layered model. In a second step we compute the rock physical properties for different metamorphic facies and water contents using computational petrology to derive a plausible and consistent lithological model. In order to optimize the inversion procedure, we perform a sensitivity  analysis assessing the resolution of the different data sets. The new methodology is applied to the Iberian Peninsula and adjacent margins where we jointly invert for both the crustal and lithospheric mantle structure.

How to cite: Clemente-Gómez, C., Fullea, J., and Arnaiz-Rodríguez, M. S.: A new Integrated lithological model of the Iberian crust, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10232, https://doi.org/10.5194/egusphere-egu22-10232, 2022.

Characterising the physical state of the Earth's interior with high resolution requires the joint inversion of complementary geophysical datasets. LitMod3D_4inv is a method/software that allows regional and continental scale joint inversions within a probabilistic framework for the 3D thermochemical structure of the lithosphere and upper mantle. The software can simultaneously invert gravity anomalies, geoid height, gravity gradients, Love and Rayleigh surface-wave dispersion curves, receiver functions, body-wave travel times, surface heat flow, absolute elevation and magnetotelluric data, or any combination of them. The result is a collection of Earth models (a probabilistic distribution) with exceptional explicative power and robust estimates for uncertainties.

We use equations of state and Gibbs free energy minimisation routines to produce self-consistent sets of the seismic velocities, densities, and other properties from the actual parameters (unknowns) of the inversion – mantle chemical compositions, thermal profiles, and properties of the crustal layers (thickness, reference densities, Vp/Vs). The code relies on highly-optimised solvers for gravity, seismic, and magnetotelluric forward problems and multi-level hybrid parallel architecture to make use of multiple interacting markov chains. The modular structure of the code allows for extending the set of solvers to include new observables or to implement new Markov chain Monte Carlo algorithms.

In this presentation we will discuss recent developments in the LitMod3D_4inv suite and illustrate their performance with real examples in eastern Canada, in southern and central Africa, and north eastern Australia.

How to cite: Fomin, I., Afonso, J., and Manassero, C.: LitMod3D_4inv: Multi-observable and multi-scale geophysical inversions for the physical state of the Earth., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1567, https://doi.org/10.5194/egusphere-egu22-1567, 2022.

1D reference Earth models are widely used by the geoscience community and include global, regional and tectonic-type reference models. Seismic 1D profiles are used routinely as reference in imaging studies. Multi-parameter models can also include density, composition, attenuation, lithospheric thickness and other parameters, of interest in a broad range of studies. The recent growth in the number of seismic stations worldwide has yielded a dramatic increase in the global sampling of the Earth with seismic data and presents an opportunity for an improvement in the global and tectonic-type reference models. Concurrent developments in computational petrology have provided methods to constrain self-consistent multi-parameter Earth models with seismic and other data. Here, we use a large global dataset of Love and Rayleigh fundamental mode, phase-velocity measurements, performed with multimode waveform inversion using all available broadband data since the 1990s, and compute phase-velocity maps at densely spaced periods in a broad, 17-310 s period range. We then invert the phase velocity curves averaged globally and across 8 tectonic environments (4 continental: Archean cratons, stable platforms, recently active continents, and active rift zones; and 4 oceanic: old, intermediate and young oceans, and backarc regions) for 1D reference models of the upper mantle. For each tectonic type, a multi-parameter 1D model is computed in a petrological inversion, where the lithospheric thickness and temperature at the bottom of the lithosphere and in the underlying mantle are the inversion parameters, and steady-state conductive lithospheric geotherms are assumed. Lithospheric and asthenospheric compositions are taken from geochemical databases, and seismic velocities, densities and Q are computed from composition, temperature and pressure using computational petrology and thermodynamic databases. The models quantify the age dependence of the lithospheric thickness and temperature in continents and oceans. Radial anisotropy is also determined and shows notable variations with depth and with tectonic environments. For most tectonic types, the smooth, accurate observed phase velocity curves can be fit by the 1D models with a misfit under 0.1-0.2% of the phase velocity value. Additionally, we compute models with minimal complexity of seismic velocity structure, also fitting the data but without a sub-lithospheric low-velocity zone as in the thermal multi-parameter models. These purely seismic models, similar in appearance to ak135, do not correspond to realistic geotherms but provide useful reference for seismic imaging studies in different environments.

How to cite: Civiero, C., Lebedev, S., Xu, Y., Bonadio, R., and Fullea, J.: Seismic and multi-parameter 1D reference models of the upper mantle, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4784, https://doi.org/10.5194/egusphere-egu22-4784, 2022.

Seismic reflection images derived by ambient-noise seismic interferometry (SI) can show subsurface structures without active sources. To image and interpret the upper mantle structures and tectonic boundaries beneath the southern part of Korean Peninsula, we applied SI method to seismic ambient noise data recorded at 119 seismic stations on the Korean Peninsula in 2014 (from the seismic network of the Korean Meteorological Administration). The factor that makes interpretation difficult is the steeply dipping events in reflection images. Most of these events of apparent steeply dips show as true reflection events from steep geologic boundaries. Therefore, we need to attenuate these events to interpret true reflection events. These events overlap many times. Also, the value of the slope has several values close to half of the Rayleigh waves or P waves. To attenuate these events with these complex features, we used machine learning techniques. We attenuated our steeply dipping events by applying the Extraction of diffractions method. As the steeply dipping events are attenuated, horizontal events were strengthened, and noises were attenuated. We can more clearly identify the reflection events of the Moho discontinuity and the lithosphere/asthenosphere (LAB) boundary near the two-way reflection times of 7-11 s and 17-22 s respectively.

How to cite: Song, Y., Byun, J., Kim, S., Choi, Y., and Bae, S.: Machine learning-based attenuation of steeply dipping events of seismic reflection image beneath the Korean Peninsula, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9636, https://doi.org/10.5194/egusphere-egu22-9636, 2022.

Knowledge about the electrical conductivity structure of the Earth's interior is a key to understanding its thermo-chemical state and evaluate the impact of space weather events. USMTArray is a high quality data set of magnetotelluric measurements that addresses both of these problems. Covering ~70% of the contiguous United States on a quasi-regular 70 km spaced grid, this unique publicly available data led to the development of several regional 3D electrical conductivity models. However, an inversion of the entire data set demands novel multi-scale imaging approaches that can handle and take advantage of a large range of spatial scales contained in the data. We present a 3D electrical conductivity model of the contiguous United States derived from the inversion of ~1100 USArray magnetotelluric stations. The use of state-of-the-art modeling techniques based on high-order finite-element methods allows us to take into account complex coastline and reconstruct Earth’s conductivity across many scales. The retrieved electrical conductivity variations are in overall agreement with well-known continental structures such as the active tectonic processes within the western United States (e.g., Yellowstone hotspot, Basin and Range extension, and subduction of the Juan de Fuca slab) as well as the presence of deep roots (~250 km) beneath cratons.

How to cite: Munch, F. and Grayver, A.: Three-dimensional electrical conductivity structure of the contiguous US from USArray MT data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-376, https://doi.org/10.5194/egusphere-egu22-376, 2022.