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This dataset provides rheometric data of three viscous materials used for centrifuge experiments at the Tectonic Modelling Laboratory of CNR-IGG at the Earth Sciences Department of the University of Florence (Italy). The first material, PP45, is a mixture of a silicone (Polydimethylsiloxane or PDMS SGM36) and plasticine (Giotto Pongo). The PDMS is produced by Dow Corning and its characteristics are described by e.g. Rudolf et al. 2016a,b). Giotto Pongo is produced by FILA (Italy). Both components are mixed following a weight ratio of 100:45, and the final mixture has a density of 1520 kg m3. The second material, SCA705 is a mixture of Dow Corning 3179 putty, mixed with fine corundum sand and oleic acid with a weight ratio of 100:70:05 and a resulting density of 1660 kg m3. The final material, SCA7020 consists of the same components as SCA705, but with a slightly higher oleic acid content reflected in the weight ratio of 100:70:20. The mixture’s density is 1620 kg m3. The material samples have been analyzed in the Helmholtz Laboratory for Tectonic Modelling (HelTec) at GFZ German Research Centre for Geosciences in Potsdam using an Anton Paar Physica MCR 301 rheometer in a plate-plate configuration at room temperature (20˚C). Rotational (controlled shear rate) tests with shear rates varying from 10-4 to 1 s-1 were performed. Additional temperature tests were run with shear rates between 10-2 to 10-1 s-1 for a temperature range between 15 and 30˚C. According to our rheometric analysis, the materials all exhibit shear thinning behavior, with high power law exponents (n-number) for strain rates below 10-2s-1, while power law exponents are lower above that threshold.For PP45, the respective n-numbers are 4.8 and 2.6, for SCA705 6.7 and 1.5, and for SCA7020 9.1 and 2.0. The temperature tests show decreasing viscosities with increasing temperatures with rates of -3.8, -1.4 and -1.9% per ˚K for PP45, SCA705 and SCA7020, respectively. An application of the materials tested can be found in Zwaan et al. (2020).
TEAM, the Transformer Earthquake Alerting Model is a deep learning model for real time estimation of peak ground acceleration (TEAM), earthquake magnitude and earthquake location (TEAM-LM). This software package contains the joint implementation of both TEAM and the derivative TEAM-ML, as well as the scripts for training and evaluating these models. In addition, it contains scripts to download an early warning datasets for Japan and implementations of baseline approaches for the estimation of earthquake magnitude and peak ground acceleration. TEAM is implemented in Python. TEAM and TEAM-ML have a variety of configuration parameters that are documented in the README. These configurations need to be provided in JSON format. In addition, multiple example configuration files are provided in the subdirectories pga_configs and magloc_configs. Please note that this implementation is intended for research purpose only. Production use is discouraged.
This Python package is a collaborative effort by the gravity Metrology group at the German Federal Agency for Carthography and Geoesy (BKG) and the Hydrology section at GFZ Helmholtz Centre for Geosciences. It comprises functionalities and features around the respectively new instrument type of a Quantum Gravimeter (here AQG). New (standardized) instrument data format additional to new measurement and processing concepts lead to the first collection of scripts and now complete python package for a fully-featured analysis of AQG data. This encompasses live-monitoring while the instrument is actually measuring (with enhanced functionality than what is provided by the manufacturer), data processing, visualizations as well as archiving data, fulfilling the idea of reproducible data within FAIR principles. Many of these functionalities and concepts also apply to other gravimeter types. It is thus planned to include also access and processing of data for these other devices (starting in the near future with CG-6 relative gravimeters). This package is actively maintained and developed. If you are interested in contributing, please do not hesitate to contact us. Please find instructions for its installation and usage in the documentation or git repository, linked in the left panel. gravitools is listed in the python standard repository database "PyPi". Some highlight features, available in the first official stable release are: • Read and process raw data of the Exail Absolute Quantum Gravimeter (AQG) • Apply standardized or customized AQG data processing and outlier detection • Read and write processed datasets with metadata to .nc-files in NETCDF4-format • Handle Earth orientation parameters (EOP) from iers.org for polar motion correction • Visualize data with matplotlib • CLI for standard processing of AQG raw data to .nc-file • Dashboard for real-time processing and visualization during measurements (on AQG laptop) • Dashboard includes a proposed standard template for a measurement protocol • Standardized, easy-to-read and modify config files for processing options and reproducible data handling • Generation of PDF reports from individual measurements
This publication contains software that can be used to pre-process data from the Globe at Night citizen science project, and then run an analysis to determine the rate of change in sky brightness. The software requires input data, which can be obtained directly from Globe at Night. The data used for our publication "Citizen scientists report global rapid reductions in the visibility of stars from 2011 to 2022" is published here, and can be used as input to the software. The process requires access to the World Atlas of Artificial Night Sky Brightness, which is also available from GFZ Data Services.
This software package contains code for performing agglomerative hierarchical clustering on river long profiles extracted from topographic data. The software requires initial topographic analysis to extract river profiles based on the Edinburgh Land Surface Topographic Tools package. Detailed documentation and tutorials for installation and running the code can be found at https://lsdtopotools.github.io/LSDTT_documentation/. The package written in Python and based on the scipy cluster package. The development version of the code can be found on GitHub (https://github.com/UP-RS-ESP/river-clusters) along with full instructions on how to install and run the code.
This data publication contains airborne wind and eddy covariance data files, that were recorded with the ASK-16, a motorized glider owned by the FU Berlin, Germany. These data files include a large range of meteorological variables (wind speed, direction, temperature, humidity, etc.), positioning information, but also information on atmospheric chemistry (mainly methane concentration, carbon dioxide concentration, water vapor concentration) and turbulent matter (CH4 and CO2) and energy fluxes (latent heat flux) is available. Measurements were recorded between 2017 and 2022 to: (1) obtain three-dimensional wind vectors in within the atmospheric boundary layer (2) calibrate of wind measurements (3) record turbulent energy and matter fluxes A lot of these data files have been used in the publication “The ASK-16 Motorized Glider: An Airborne Eddy Covariance Platform to measure Turbulence, Energy and Matter Fluxes (to be published in atmospheric measurement techniques)” by Wiekenkamp et al., 2024a. This publication also provides a lot of additional details on the measurement system, the data handling and processing.
The datasets contain low resolution image data [1] that can be used to approximately remove natural light from the monthly composite nighttime images produced by the Earth Observation Group (EOG) using the Visible Infrared Imaging Radiometer Suite (VIIRS) Day-Night Band (DNB) [2]. Natural light includes airglow and reflected light from stars, as well as polar light at high latitudes.The low-resolution images can be expanded and then subtracted from the EOG monthly composites, using python scripts included in this data publication [1]. More details are provided in the data description and in Coesfeld et al. (2020).The background correction is based on the VIIRS-DNB monthly composites data from April 2012 to December 2019 without stray light correction produced by the EOG, and the associated file containing the number of cloud-free observations (Earth Observation Group, 2015). Locations away from human settlements and artificial lights were selected using the Global Human Settlement Layer (GHSL) population density map from 2015 [3] and the VIIRS-DNB 2015 vcm-orm annual composite by the EOG (Earth Observation Group, 2015).The python script we used in Coesfeld et al. (2020) to select locations on an equally spaced grid over the global DNB extent (from 75N to 65S) is included. The six images of the EOG composite are processed separately. This code identifies locations on a 72x28 grid (2016 locations total). In order to optimize the location of the specified grid points, the Global Human Settlement Layer (GHSL) population density and VIIRS-DNB annual composite of 2015 are consulted.
The aim of this software is to assess the influence of water well production rates to the measured water level data dependent on the reservoir properties. Daily abstraction rates can be used for this production rate well test analysis. For the analysis, a modified deconvolution algorithm is implemented in the code. The algorithm derives the reservoir response function by solving a least square problem with the unique feature of imposing only implicit constraints on the solution space.
This data set provides two series of experiments from ring-shear tests (RST) on glass beads that are in use at the Helmholtz Laboratory for Tectonic Modelling (HelTec) at the GFZ German Research Centre for Geosciences in Potsdam. The main experimental series contains shear experiments to analyse the slip behaviour of the granular material under analogue experiment conditions. Additionally, a series of slide-hold-slide (SHS) tests was used to determine the rate and state friction properties. A basic characterisation and average friction coefficients of the glass beads are found in Pohlenz et al. (2020). The glass beads show a slip behaviour that is depending on loading rate, normal stress and apparatus stiffness which were varied systematically for this study. The apparatus was modified with springs resulting in 4 different stiffnesses. For each stiffness a set of 4 experiments with different normal stresses (5, 10, 15 and 20 kPa) were performed. During each experiment loading rate was decreased from 0.02 to 0.0008 mm/s resulting in 9 subsets of constant velocity for each experiment. We observe a large variety of slip modes that ranges from pure stick-slip to steady state creep. The main characteristics of these slip modes are the slip velocity and the ratio of slip event duration compared to no slip phases. We find that high loading rates promote stable slip, while low loading rates lead to stick-slip cycles. Lowering the normal stress leads to a larger amount of creep which changes the overall shape of a stick-slip curve and extends the time between slip events. Changing stiffness leads to an overall change in slip behaviour switching from simple stick-slip to more complex patterns of slip modes including oscillations and bimodal slip events with large and small events. The SHS tests were done at maximum stiffness and higher loading rates (>0.05 mm/s) but at the same normal stress intervals as the main series. Using various techniques, we estimate the rate-and-state constitutive parameters. The peak stress after a certain amount of holding increases with a healing rate of b=0.0057±0.0005. From the increase in peak stress compared to the loading rate in slide-hold-slide tests we compute a direct effect a=-0.0076±0.0005 which leads to (a-b)=-0.0130±0.0006. Using a specific subset of the SHS tests, which have an equal ratio of hold time to reloading rate, we estimate (a-b)=-0.0087±0.0029. Both approaches show that the material is velocity weakening with a reduction in friction of 1.30 to 0.87 % per e-fold increase in loading rate. Additionally, the critical slip distance Dc is estimated to be in the range of 200 µm. With these parameters the theoretical critical stiffness kc is estimated and applied to the slip modes found in the main series. We find that the changes in slip mode are in good agreement with the estimated critical stiffness and thus confirm the findings from the SHS tests.
We present SCOTER, an open-source Python programming package that is designed to relocate multiple seismic events by using direct P- and S-wave station correction terms. The package implements static and shrinking-box source-specific station terms techniques extended to regional and teleseimic distances and adopted for probabilistic, non-linear, global-search location for large-scale multiple-event location. This program provides robust relocation results for seismic event sequences over a wide range of spatial and temporal scales by applying empirical corrections for the biasing effects of 3-D velocity structure. Written in the Python programming language, SCOTER is run as a stand-alone command-line tool (requiring no knowledge of Python) and also provides a set of sub-commands to develop required input files (e.g. phase files, travel-time grid files, configuration) and export relocation results (such as hypocenter parameters, travel-time residuals) in different formats -- routine but non-trivial tasks that can consume much user time. This package can be used for relocating data sets in local, regional, and teleseimic scales.
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