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Found 39 results.

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Subsurface Vp and Vs model of crust and upper mantle under the Alps

The model contains the 3D structure of Vp and Vs in the crust and the mantle under the European Alps, as published in Kästle et al. (2025). It is the result of a direct inversion of surface-wave data, from ambient noise and earthquake records, and of teleseismic P and S wave data. A Bayesian tomography approach is used where we implement a reversible jump Markov chain Monte Carlo method to constrain the free parameters. This gives not only the mean Vp and Vs values, but also their uncertainties, as well as a distribution (histograms) of the sampled velocity parameters at each point of the model.

REHEATFUNQ: A Python package for the inference of regional aggregate heat flow distributions and heat flow anomalies

The REHEATFUNQ Python package helps to work with the (residual) scatter of surface heat flow even in small regions. REHEATFUNQ uses a stochastic model for regional aggregate heat flow distributions (RAHFD), that is, the collected set of heat flow measurements within a region marginalized to the heat flow dimension. The stochastic model is used in a Bayesian analysis that (1) yields a posterior estimate of the RAHFD which captures the range of heat flow within the analysis region, and (2) quantifies the magnitude of a surface heat flow anomaly within the region, for instance through the generating frictional power. The stochastic model underlying REHEATFUNQ views heat flow data, uniformly sampled across the region of interest, as a random variable. A gamma distribution is used as a model for this random variable and information from the global data set of Lucazeau (2019) is introduced by means of a conjugate prior (Miller, 1980). The detailed science behind the model is described in Ziebarth et al. (202X). The analysis by Ziebarth et al. (202X) can be reproduced through the Jupyter notebooks contained in the subdirectory “jupyter/REHEATFUNQ/”. The location specified in the map below covers the region to which REHEAFUNQ is applied in this analysis. REHEATFUNQ is a Python package that uses a compiled Cython/C++ backend. Compiling REHEATFUNQ requires the Meson build system and a number of scientific libraries and Python packages (and their dependencies) that are listed in the documentation. A Docker image “reheatfunq” is provided as an alternative means of installation. The Docker image comes in two flavors, specified in “Dockerfile” and “Dockerfile-stable”. The former is based on the current “python:slim” image and downloads further dependencies through the Debian package manager, leading to a short image generation time. The latter bootstraps the REHEATFUNQ dependencies from source, aiming to create a reproducible model. To do so, “Dockerfile-stable” depends on the sources contained in “vendor-1.3.3.tar.xz”. If you plan to build the stable image, download both “REHEATFUNQ-1.3.3.tar.gz” and “vendor-1.3.3.tar.xz”, and see the README contained in the latter. Later versions of the “REHEATFUNQ” archive are compatible with the latest “vendor” archive. A quickstart introduction and the API documentation can be found in the linked documentation.

3D geodynamic data-driven model of the Southern Central Andes

In the southern Central Andes (~32°S), subduction of the Nazca oceanic plate beneath the South American continental plate becomes horizontal. The growth of the Altiplano-Puna Plateau is covalently related to the southward migration of the flat subduction, but the role of subduction geometry and the plate strength on current and long-term deformation of the Andes remains poorly explored. This study takes a data-driven approach of integrating the previous structural and thermal model of the lithosphere of the southern central Andes into a 3D geodynamic model to explore the different parameters contributing to the localization of deformation. We simulate visco-plastic deformation using the geodynamic code ASPECT. The repository includes parameter files and input files for the reference model (S1) and the following alternative simulations: a series of models with variation in friction at the subduction interface (S2a-d), a series of models with variation in sedimentary strength (S3a-d), a series that studies the effect of topography (S4), and a series that studies the effect of plate velocities. In addition, a readme file gives all the instructions to run them.

GEOMODELATOR - A python library to generate simple structured 2d+ and 3d cell-based VTK models/files

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3D-SCS: Three-dimensional lithospheric-scale structural and density model of the South China Sea

We present a comprehensive 3D lithospheric-scale model of the South China Sea region (SCS), which reveals the structural configuration of the area. This model delineates seven distinct geological units: (1) seawater, (2) sedimentary cover, (3) continental crystalline crust, (4) oceanic crust, (5) upper lithospheric mantle, (6) lower lithospheric mantle, and (7) sub-lithospheric mantle. The model covers an area of 960 km × 1260 km and reach down to a depth of 250 km. It is provided as uniformly spaced grids with 10 km intervals for each unit. The geometries and density distributions within the crust have been compiled and interpolated from a variety of datasets, predominantly seismic data (see section 6). To eliminate boundary effects, the model boundaries have been extended by more than 500 km in all horizontal directions, incorporating additional constraining data from the extended region. Additionally, we provide gridded gravity field data, a density voxel cube for the sub-lithospheric mantle, and relevant tomography data. Notably, the density of the lower lithospheric mantle was derived from 3D gravity inversion modeling.

InVent4Cast: Bayesian Inversion of Stress Field and Physics-based Eruptive Vent Forecast at Calderas

BayStress4 is a package of MatLab routine, designed to constrain the state of stress of a volcanic system by means of posterior Probability Density Functions (PDFs) of the stress tensor components. To do so, it employs the model of three-dimensional (3D) dyke pathways developed by Mantiloni et al., 2023 (SAM: Simplified Analytical Model of dyke Pathways in Three Dimensions) to match the known locations of past eruptive vents to the known or assumed volume in the subsurface ("Dyke nucleation zone" or "D") where their parent dykes nucleated from. This is achieved by a) using SAM to backtrack dyke pathways from the vents down through the crust for a given stress model; b) quantifying the intersection between such pathways and D through a misfit function; c) using this procedure to run a Markov Chain Monte Carlo (MCMC) algorithm to sample the stress parameters' space. The posterior information provided by the stress inversions can then be used to produce forward simulations of dyke pathways with SAM and forecast the surface distribution of future eruptive vents across the volcanic system. This repository contains InVent4Cast, a package of MatLab routines designed to constrain the state of stress of a volcanic system by means of posterior Probability Density Functions (PDFs) of the stress tensor components. To do so, it employs the model of three-dimensional (3D) dyke pathways developed by Mantiloni et al., 2023a (SAM: Simplified Analytical Model of dyke Pathways in Three Dimensions) to match the known locations of past eruptive vents to the known or assumed volume in the subsurface ("Dyke nucleation zone" or "D") where their parent dykes nucleated from. This is achieved by a) using SAM to backtrack dyke pathways from the vents down through the crust for a given stress model; b) quantifying the intersection between such pathways and D through a misfit function; c) using this procedure to run a Markov Chain Monte Carlo (MCMC) algorithm to sample the stress parameters' space. The posterior information provided by the stress inversions can then be used to produce forward simulations of dyke pathways with SAM and forecast the surface distribution of future eruptive vents across the volcanic system. The repository also collects data, figures and results of the application of InVent4Cast to some of the synthetic scenarios of dyke pathways in calderas presented by Mantiloni et al., 2023a. These results were detailed and discussed by Mantiloni et al., 2024a, to which the reader is referred for further information. The synthetic scenarios include numerical models of crustal stress state, focusing on gravitational loading/unloading due to topography and tectonic processes as the dominant stress sources. These stress sources are accounted for by a set of stress parameters. Results include posterior probability density functions (PDFs) of such stress parameters after applying the stress inversion to the scenarios, as well as probability maps of eruptive vent opening across the synthetic volcanic areas. Synthetic scenarios, stress inversions and vent forecasts were produced between May 2022 and November 2023.

Experimental data on Long-term Isostatic Relaxation of Large Terrestrial Impact Structures: Structural Characteristics Inferred from Scaled Analogue Experiments at the UHH-Tec Modelling Lab of the Universität Hamburg

This data set includes the results of digital image correlation of 21 analogue experiments on isostatic relaxation of the crater floors performed at UHH-Tec Modelling Laboratory of the Universität Ham-burg. The structural evolution of model upper crust was systematically analysed for various initial depths and diameters of crater floors, gleaned from numerical models for average continental crust. The experiments show that crater floor uplift is accomplished by long-wavelength subsidence of the crater periphery and may operate on time scales of thousands of years in nature. Detailed descriptions of the experiments and monitoring techniques can be found in Eisermann and Riller (2023) to which this data set is supplementary. The data presented here consist of movies and images displaying cumulative displacements of deforming analogue model surfaces.

Seismic data, seismic crustal velocity and anisotropy models for Sri Lanka

The data present the intermediate to final results when we introduce a two-step fully Bayesian approach with coupled uncertainty propagation for estimating crustal isotropic and radial anisotropy models using Rayleigh and Love dispersion data along with receiver functions in Sri Lanka. In the first step, 2D surface wave tomography is used to generate period-wise ambient noise phase velocity maps for Rayleigh and Love waves along with their associated uncertainties. Here we provide the inter-station dispersion data (folder: 2024-003_1_Ke-et-al_interstation_surface_ dispersion_curves; ASCII) for the 2D surface wave tomography process, along with the results of the tomography, including the velocity maps (folder: 2024-003_Ke-et-al_2_velocity_map; ASCII). In addition, the results (folder: 2024-003_3_Ke-et-al_2Dmcmc_inversion_results) are available in MAT format, along with a MATLAB script to allow users to extract the data independently. In a second step, local surface wave dispersion and model errors are derived from the velocity maps. The surface wave dispersion receiver functions are jointly inverted to obtain the isotropic mean shear wave and radial anisotropy profiles as a function of depth at each station site. The input data (folder: 2024-003_Ke-et-al_4_inv_data; ASCII) of surface dispersion and receiver function for the inversion are presented here, as well as the final result model from the inversion (folder: 2024-003_Ke-et-al_5_model; ASCII and .dat formats).

3D structural geological model of the Mallik Anticline, Canadian Arctic

The Mallik Anticline is a geologic structure in the Mackenzie Delta in the Canadian Arctic. Tectonics throughout the Cenozoic, with compressional phases in the early Eocene to the late Miocene, formed this large, domed structure that is today an important source of hydrocarbons. Gas hydrates occur in the clastic sedimentary rocks of the Oligocene to Pleistocene Kugmallite, Mackenzie Bay, and Iperk sequences, which were essentially formed by deltaic processes. The presence of hydrocarbon gases within the permafrost zone in the Canadian Arctic has led to extensive exploration and production activities in the region since the mid-1960s, and the investigations by geologists and geophysicists have already been published in numerous scientific articles to date. The associated report (Chabab and Kempka, 2023) describes the implementation of the first field-scale 3D static geologic model of the Mallik site, which was created using data from well logs and 2D seismic reflection profiles. The dataset presented here provides elevation depths and thickness data of the three distinct sequence boundaries Kugmallit-Richards, Mackenzie Bay-Kugmallit and Iperk-Mackenzie Bay as well as fault data from the Mallik site.

3D-NEA: Three-dimensional lithospheric-scale structural model of the North East Atlantic

The Northeast Atlantic (NEA) region has long been a subject of interest due to its complex geological history, particularly regarding the interaction between the Iceland plume and the lithospheric plates. In this data publication, we present a comprehensive three-dimensional structural and density model of the NEA crust and uppermost mantle, consolidating and integrating a wide range of previously fragmented data sets. Our model highlights the influence of the Iceland plume on the region's geological evolution, shedding light on the mechanisms that facilitated the continental breakup between Europe and Laurentia during the earliest Eocene period. The whole workflow and methods are described in Gomez Dacal et al. (2023) and its Supplementary Information.

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