Other language confidence: 0.9180931474544567
A seismic network was installed in the Helsinki capital area of Finland to monitor the response to a 6 km deep geothermal stimulation experiment in 2018. The Institute of Seismology, University of Helsinki (ISUH), installed these 100 geophones in addition to five surface broadband sensors and a 13-site borehole network deployed by the operating company. The stations operated for 106 days between 7 May and 20 August 2018 (day 127 to 232). The data set consists of raw CUBE-recorder data and converted MSEED data.
This dataset provides mechanical test data for quartz sand (“MAM1ST-300”, Sibelco, Mol, Belgium), gypsum powder (plaster; “Goldband”, Knauf), kaolin clay powder, garnet sand, and mixtures of quartz sand and gypsum powder, used at the Analogue Laboratory of the Department of Geography at the Vrije Universiteit Brussel, Brussels, Belgium, for simulating brittle rocks in the upper crust (Poppe et al., 2019). The measured properties are density ρ, tensile strength T0, shear strength σ, obtained by density measurements, ring-shear tests (RST; at Helmholtz Centre Potsdam GFZ, Germany), direct shear tests, traction tests (at University of Maine, Le Mans, France) and extension tests. The obtained tensile strengths and shear strengths reconstruct two-dimensional failure envelopes for each material. By fitting linear Coulomb and non-linear combined Griffith failure criteria to the characterised failure envelopes (Jaeger et al., 2007), the internal friction coefficient µC, Coulomb cohesion CC and Griffith cohesion CG are obtained. The influence of the material emplacement technique has been investigated in Poppe et al. (2021) to which this data set is supplementary, by repeat characterisation of the above physical parameters under three emplacement conditions, i.e. sieving, pouring (non-dried state) and compaction after pouring (oven-dried state). We find that densities of the materials and mixtures range from ~1600 kg.m³ (sieved) and ~1700 kg.m³ (compacted) for pure quartz sand to ~600 kg.m³ (poured) to ~900 kg.m³ (compacted) for pure plaster. Tensile strengths range from ~166 Pa (sand) to ~425 Pa (plaster). Velocity ring-shear tests on a 90 wt% quartz sand – 10 wt% plaster mixture show a minor shear rate-weakening of <2% per ten-fold increase in shear velocity. The materials show a behavior ranging from Mohr-Coulomb behavior for the materials with coarser grain size (sands) to combined Griffith-Mohr-Coulomb behavior for the powder materials (plaster, kaolin), with the sand-plaster mixtures occupying a spectrum between both end-members. Peak friction coefficients range from ~0.5 (sand) to ~0.6 (plaster) with a maximum of ~0.9 (80:20 wt% sand:plaster), peak Coulomb cohesions range from 13 Pa (sand) to 248 Pa (plaster), peak Griffith cohesions range from ~10 Pa (sand) to ~425 Pa (plaster).
In order to understand the difference between high temperature drop across the mantle's basal thermal boundary layer and much lower plume excess temperatures we evaluated computations with ASPECT. Some of them are published in the Ph.D. thesis of Poulami Roy, some others in previous work. Hence here we only include those models that are not published elsewhere. We also provide the routine to extract maximum and average plume temperatures versus depth. Our results show reduced excess temperatures, if plumes are more sheet-like, similar to 2-D models, or temperature at their source depth is less than at the CMB, for example if they are sourced on top of thermochemical piles. Excess temperatures are further reduced when averaged over the plume conduit or melting region. We provide here the prm files and required input files for the Aspect 2-D cases shown in Figures 2 and 3, which are the only cases that are neither included in Steinberger et al. (2023) nor in the Ph.D. thesis of Poulami Roy (2024). Figure 2 is computed with matteo_4.prm; in this case, the initial temperature is in initial_temp_ascii_2, prescribed (zero) surface velocitites are in vel-top-zero Figure 3 is computed with matteo_14.prm; in this case, the initial temperature is in in initial_temp_ascii_4b. In both cases, radial_visc_simple.txt is the radial viscosity structure corresponding to adiabatic temperatures, and the file temp-viscosity-prefactor.txt specifies the lateral viscosity variations due to temperature variations. We also provide the Routine post_processing_matteo_10km.py for extracting plume temperatures versus depth, written by Matteo Jopke. Furthermore, we provide csv files for all time steps listed in Tables B1 and B2 and shown in Figures 5-7 of the paper. These data have been used to compute plume temperatures and anomalous mass fluxes, in order to address the question posed in the title of the paper. Files are grouped according to model runs into tar files with the same name. The tables are also provided in the Appendix of this data description. The model files are grouped in .tar files according to the model types: single_plume.tar, 2_10.tar; 2.5_2_10.tar; no_slap.tar)
In Finger et al. (2022), we created consistent three-dimensional models in terms of temperature, density and composition of the upper mantle of the cratonic part of the African continent by combining seismic [Celli et al., 2020] and gravity [Förste et al., 2014] data with mineral physics constraints in an iterative integrated inversion approach [Kaban et al., 2014; Tesauro et al., 2014]. Further, we calculated a new model of depth to the Moho to correct the gravity field for crustal effects and calculate the residual topography, and provide an update for the average crystalline crust density from Litho1.0 [Pasyanos et al., 2014]. To calculate depth to the Moho, data from the GSC [Global Seismic Catalog, Mooney, 2015 with updates up to 2019] were combined with those published by Globig et al. [2016]. Here, we share data used from the GSC, final models of the upper mantle and crust that are discussed in the article, as well as the test cases set up in the uncertainty assessment. The upper mantle models are given in six layers centered at 50, 100, 150, 200, 250 and 300 km. In addition, density variations determined for the crust are given in an additional layer at 15 km depth. All fields range from -40.5°N to 40.5°N and -20.5°E to 55.5°E with a 1° by 1° lateral resolution. The data is provided in binary format as three netCDF4 files, containing the final results discussed in the paper ("Results_AF"), and the two uncertainty assessment cases for an upwards/downwards shifted Moho ("Results_AF_Moho_up" / "Results_AF_Moho_down"), respectively. In addition, data extracted from "Results_AF" to create the six profiles shown in the main article, and measurements of depth to Moho from the GSC are provided as ASCII formatted .dat files.
The Collisional Orogeny in the Scandinavian Caledonides (COSC) drilling project focuses on understanding orogenic processes in western Scandinavia (Lorenz et al., 2015). The project presents an opportunity to study how heat transport affects brittle and ductile deformation in the lithosphere. Here, we present results of measurements with an optical scanning instrument (Thermal Conductivity Scanner; TCS) on about 100 core samples retrieved from the borehole COSC-1. Details about the measurement procedures are given in the following sections. For a list of core sample IDs that are assigned with International Generic Sample Numbers (IGSN, see Conze et al., 2017), please see the associated data description file. The sample IDs give the identifier of the borehole (5054_1_a) and then core# and section# (e.g., 5054_1_A_7_1_WR_4-24, where core# is 7 and section# is 1). Further information (e.g., elevation, depth, sample photos, etc.) about each sample can be found on the GFZ Data Services repository. Individual sample pages can be accessed directly using the IGSN, for example: https://igsn.org/ICDP5054EX71601 (or via the links in the Related Works section of this DOI landing page). The TCS measurements were made at the Fraunhofer Institute, Bochum, formerly known as the International Geothermal Centre, Bochum, on a Lippmann Geophysical Instruments TCSCAN, hardware version 2 (https://www.l-gm.de/en/en_tcs.html). The procedure used for the measurements is described in the user manual, which can be found at https://www.tcscan.de.
The dataset contains the seismic weight drop data acquired in Private Reserve Santa Gracia, Chile. The data acquisition was conducted as a part of the EarthShape project in the subproject of Geophysical Imaging of the Deep EarthShape (GIDES). The seismic line was setup to cut across an existing borehole location with core and geophysical logging data available (Krone et al., 2021; Weckmann et al., 2020). The data was acquired to image the deep weathering zone identified by the borehole data across the seismic profile. Included in the datasets are the raw data of the CUBE data logger, SEG-Y data of the recorded shots, and the shot and receiver geometry data. A vital aspect of comprehending the interplay between geological and biological processes lies in the imaging of the critical zone, located deep beneath the surface, where the transition from unaltered bedrock to fragmented regolith occurs. It had been hypothesized that the depth of such weathering zone is dependent on the climate condition of the area. A more humid climate with higher precipitation will result in a deeper weathering front. As a part of the EarthShape project (SPP-1803 ‘EarthShape: Earth Surface Shaping by Biota’), specifically the Geophysical Imaging of the Deep EarthShape (GIDES - Grant No. KR 2073/5-1), we aim to image the weathering zone using the geophysical approach. Using the seismic method, we can differentiate different weathered layers based on the seismic velocity while also providing a 2D subsurface image of the critical zone. We conducted a seismic weight drop experiment in the Private Reserve Santa Gracia, Chile, to observe the depth of the weathering zone in a semi-arid climate and compare the resulting model with existing borehole data (Krone et al., 2021; Weckmann et al., 2020). The acquired data can then be used for multiple seismic imaging techniques, including body wave tomography and multichannel analysis of surface waves.
SEG-Y data of small-scale high-resolution controlled-source seismic experiment to investigate the mesoscopic fault structure of the Wadi Arava fault, Dead Sea Transform. The Dead Sea Transform (DST) is a major shear zone running for more than 1000km from the Red Sea in the South to the Zagros mountain chain in the North. It accommodates the lateral movement of the Sinai microplate and the Arabian shield; the total displacement along this shear zone is >100km. As part of the DESERT 2000 research project, several geophysical studies on a wide range of scales aimed to reveal the structure and evolution of the DST (Weber et al., 2009, 2010, and references therein). In October/November 2010 we conducted a high-resolution seismic experiment in the central part of the Arava/Araba segment of the shear zone. The analysis of the data (reflection seismics, tomography) revealed the shallow structure of the Wadi Arava fault (main strand of the DST) down to a depth of ~1km. The main findings are published in Maercklin (2004) and Haberland et al. (2007).
This dataset contains supplementary data concerning the SELASOMA project (GIPP-Project: Madagaskar; ID: 201204; FDSN-network code: ZE): (1) For stations with Cube data loggers, the raw data files are included. (2) For stations with EDL data loggers the log and auxiliary files are included. The main purpose of this dataset is to archive raw information on the timing quality, and to allow future use of alternative Cube-to-miniseed converters. Do not use this dataset if you are interested in continuous or event-based waveform data. Instead, refer to related dataset containing continuous waveforms. The dataset contains 1) log files for the stations with EDL data loggers (organized in sub-directories according to time range and station code); 2) separated MSEED-formatted data affected by some problems (organized in sub-directories according to time range and station code) and 3) raw CUBE-formatted data (organized in sub-directories according to time range and station name).
Bedload transport is a key process in fluvial morphodynamics and hydraulic engineering, but is notoriously difficult to measure. The recent advent of stream-side seismic monitoring techniques provides an alternative to in-stream monitoring techniques, which are often costly, staff-intensive, and cannot be deployed during large floods. Seismic monitoring is a surrogate method requiring several steps to convert seismic data into bedload data. State-of-the-art approaches of conversion exploit physical models predicting the seismic signal generated by bedload transport. Here, we did an active seismic survey (2017-11) and used seismic data from a flood event (2016-02-22) on the Nahal Ehstemoa to constrain a seismic bedload model. We conducted the active seismic survey to determine the local seismic ground properties, i.e., the Green’s function. We also used water depth and bedload grain size distribution to constrain the seismic bedload model and were able to compare the bedload flux obtained from the seismic data using the model with high-quality independent bedload measurements from slot samplers on the site. The complementary non-seismic data is published in a separate data publication (Lagarde et al., 2020).
| Organisation | Count |
|---|---|
| Weitere | 4 |
| Wissenschaft | 74 |
| Type | Count |
|---|---|
| unbekannt | 78 |
| License | Count |
|---|---|
| Geschlossen | 2 |
| Offen | 73 |
| Unbekannt | 3 |
| Language | Count |
|---|---|
| Englisch | 78 |
| Resource type | Count |
|---|---|
| Keine | 78 |
| Topic | Count |
|---|---|
| Boden | 54 |
| Lebewesen und Lebensräume | 41 |
| Luft | 21 |
| Mensch und Umwelt | 72 |
| Wasser | 20 |
| Weitere | 78 |