77 documents found in 490ms
# 1
Frick, Daniel A. • Schuessler, Jan A. • Sommer, Michael • von Blanckenburg, Friedhelm
Abstract: Silicon is a beneficial element for many plants, and is deposited in plant tissue as amorphous bio-opal (phytoliths). The biochemical processes of uptake and precipitation induce isotope fractionation: the mass-dependent shift in the relative abundances of the stable isotopes of silicon. At the bulk scale, the silicon isotope composition reported as δ30Si span from -2 to +6 ‰. To further constrain these variations, at the scale of individual phytolith fragments we applied in situ femtosecond laser ablation multicollector inductively coupled plasma mass spectrometry (fsLA-MC-ICP-MS) to a set of 7 natural phytolith samples. Two phytoliths samples (Norway spruce Picea abies and European beech Fagus sylvatica L.) were extracted from the organic-rich topsoil horizon (O) of two studies sites in Germany (Beerenbusch, close to village Rheinsberg and Wildmooswald, in the southern Black Forest). The other five phytolith samples (bushgrass Calamagrostis epigejos, common reed Phragmites australis, common horsetail Equisetum arvense, annual and perennial rough horsetail Equisetum hyemale) were separated from plant materials. The individual phytolith fragments were analysed by fsLA-MC-ICP-MS and Si isotope results are reported in the δ-notation (delta) as permil deviation relative to NIST SRM610, which is isotopically indistinguishable from the reference material NBS28 (quartz NIST SRM8546 alias NBS28, δ29Si ≡ 0 and δ30Si ≡ 0). Raw data processing and background corrections were made according to the protocol described in Schuessler and von Blanckenburg (2014) that also involves application of several data rejection/acceptance criteria. Of these, the most important ones are that A) only 30/28Si and 29/28Si ratios are used for the calculation which deviate less than 3 standard deviation from the mean and B) only results which follow the mass-depended terrestrial fractionation line in a three-isotope-plot of δ29Si vs. δ30Si within analytical uncertainties and C) have a mass bias drift between the two bracketing standards of less than 0.30 ‰ in 30/28Si are accepted and reported in this study. Detailed description of the sample origin, preparation steps, and the measurement protocol can be found in Frick, D. A.; Schuessler, J. A.; Sommer, M.; von Blanckenburg, F. (2018): Laser ablation in situ silicon stable isotope analysis of phytoliths. Geostandards and Geoanalytical Research. https://doi.org/10.1111/ggr.12243. With this supplement we aim to provide a comprehensive dataset for in situ stable silicon isotope composition of individual phytolith fragments.
# 2
Radosavljevic, Boris
Abstract: This publication contains tools for statistical evaluation and exploration of data published by Radosavljevic et al. (2016). These data contain bulk geochemistry data (total organic carbon, nitrogen, stable carbon isotope) and granulometry of nearshore samples in the vicinity of Herschel Island, Yukon, Canadian Beaufort Sea. In addition, the functions of the script herein provide a means for summaries and comparison with terrestrial (Couture, 2010; Tanski et al., 2017; Obu et al., 2016) and marine (a subset of Naidu et al., 2000) data. The tools are contained in a script written for the R software environment for statistical computing and graphics. The script (sediments_geochemistry_plots_and_summaries.r) is richly documented and explains the functionality. Each data file also contains a description of the data in a comma separated file (csv).The functions of the script are:myinteract() - interactive modemysum() - provides numerical summaries for WBP and TB, a box plot and runs a Two-sided Mann-Whitney-Wilcoxon testmyloc() - provides numerical summaries and comparisons among the current study, marine, and terrestrial samples, a box plot and runs a Two-sided Mann-Whitney-Wilcoxon testmyseds() - provides numerical summaries and comparisons of grain size data among the current studymycums() - plots cumulative frequency curves of grain size distributions by transectThe package contains (included in the zip folder):sediments_geochemistry_plots_and_summaries.r - script filegeochemistry_data_including_other_studies.csv - contains data by Radosavljevic et al. (2016) and other studies in the regionVolFrequenciesCoordsTransects.csv - contains volumetric grain size frequenciesgranulometry_stats.csv - contains summary statistics of grain size dataTransectSampleIndex.csv - provides an index of transectsTransectMap.png - an overview map of sample transects
# 3
Fuchs, Sven • Förster, Hans-Jürgen • Braune, Kathleen • Förster, Andrea
Abstract: This data set compiles the raw data that were used to calculate the bulk thermal conductivity (λb) of low-porosity igneous rocks from modal mineralogy, porosity, and nature of saturation fluid. It compliments a paper by Fuchs et al. (2018) to which it represents supplementary material. The paper reports the result of seeking out the mixing model(s) providing the best match between measured (λb.meas) and calculated bulk thermal conductivity (λb.calc) for low-porous igneous rocks. The study encompassed 45 samples representing various geological provinces in eight countries. Our suite of samples covers the entire range from ultramafic (gabbro/diorite) to silicic rocks (granite), straddling the range 36–76 wt.% SiO2 (corresponding quartz range: 0–45 vol.%), and includes both such of alkaline, peralkaline, metaluminous, and peraluminous affinity. Assessment of the quality of fit involved all frequently applied mixing models that consider quantitative data on modal mineralogy. Our evaluation clearly demonstrates that λb of low-porous igneous rocks, irrespective of being ultramafic or felsic, could be indirectly calculated from their mineral content with an acceptable error by employing the harmonic mean model. We show that the use of the harmonic-mean (HM) model for both rock matrix and porosity provided a good match between λb.meas and λb.calc of < 10% deviation (2σ), with relative and absolute errors amounting to 1.4 ± 9.7% and 4.4 ± 4.9% respectively. The results of our study constitute a big step forward to a robust conclusion on the overall applicability of the HM model for inferring λb of low-porous, mafic to silicic magmatic and metamorphic rocks with an acceptable magnitude of error. The data included in this data publication are the tables and plots described in Fuchs et al. (2018). They are provided in Excel (.xlsx) and .csv Formats and are further described in the data description file. The diagrams are only included in the Excel version.
# 4
Ritter, Patricia
Abstract: This dataset comprises profiles of Hall ionospheric current densities derived from scalar magnetic field data measured from the CHAMP satellite during six magnetic storms. The Hall currents are intense electric currents that flow horizontally above the earth’s surface in the polar region and perpendicular to the geomagnetic field. They peak at approximately ± 80° of geomagnetic latitude. Together with the field-aligned currents they form part of the ionospheric current system. During enhanced geomagnetic activity the Hall current peak locations are shifted equatorward. The CHAllenging Minisatellite Payload (CHAMP) spacecraft circled the Earth during the years 2000 – 2010 on a near-polar orbit (inclination 87.3°), each orbit taking 93 minutes at an altitude of initially 455 km. Within 4 months CHAMP covered all local times. The data records used for determining the Hall currents are scalar magnetic field measurements obtained with the Overhauser magnetometer on the satellite boom, with a sample frequency of 1 Hz and a resolution of 0.1 nT. In order to isolate the magnetic effects of ionospheric currents in the satellite observations, the contributions from all other sources were removed from the scalar field readings. The main, crustal and external magnetic fields were subtracted using the POMME 6 model (Maus et al, 2010, http://www.geomag.us/models/pomme6.html). The Hall current densities were obtained by fitting a line current model to the observed magnetic field residuals. The model consists of a series of 160 horizontal infinite current lines centered at the orbit position closest to the geographic pole, at an altitude of 110 km and separated by 1° in latitude. The magnetic field of the line currents are related to the current strength according to the Biot–Savart law. Assuming a static current, the strength of each current line is derived from an inversion of the observed field residuals applying a least squares fitting approach. This method of Hall current estimation from scalar magnetometer records measured at satellites was proposed initially by Olsen (1996). The reliability of the approach was demonstrated and validated in a statistical study where Hall current density estimates from CHAMP were directly compared with independent determinations from ground observations of the IMAGE magnetometer array (Ritter et al., 2004).
# 5
Soares, Gabriel B. • Matzka, Jürgen • Pinheiro, Katia
Abstract: This dataset comprises preliminary minute means of the XYZ (X=geographic north, Y=geographic east, Z=downward) magnetic field components measured at the geomagnetic observatory Tatuoca (IAGA code TTB) for the period June 1st, 2008 to December 31st, 2017. TTB is located in northern Brazil and operates under the administration of Observatório Nacional (ON) since 1957. Since 2015 it is operated in cooperation between ON and GFZ. Since the early years of the 2000 decade, the magnetic equator is close to the observatory TTB. The variations from June 1st 2008 until November 19th, 2015 were recorded by a LEMI-417M fluxgate magnetometer (sampling rate during most of this period was 1 sec, but occasionally 0.25 or 6 sec). From November 20th, 2015 onwards, a DTU FGE fluxgate magnetometer (1 sec sampling) provided the variations. From late October 2016, the total field F was measured with a Gemsys overhauser absolute scalar magnetometer with 1 sec sampling. This is a processed and calibrated dataset. Inconsistencies like spikes and data jumps were corrected. The maximum admitted noise level in this dataset is 1 nT peak to peak in the underlying 1 sec data. Periods of recurrent noise exceeding this criterion were systematically deleted from the records. For data calibration, the baseline was constructed by means of absolute measurements of the geomagnetic field and applied to the variation data. The data files are provided in the IAGA-2002 format (https://www.ngdc.noaa.gov/IAGA/vdat/IAGA2002/iaga2002format.html) as daily files for 1-minute means. Following the IAGA2002-format, the filename consists of the IAGA-code, the year (YYYY), the month (MM), the day (DD), the letter p for preliminary, the letters min for 1-minute data, and the file extension min again for 1-minute data. The first 16 lines in each file are a IAGA2002-typical header, then comes, blank separated, the date (YYYY-MM-DD), time (hh:mm:ss.sss in UTC), day of year (DOY), the X component (XXXXX.XX in nT), the Y-component (YYYYY.YY in nT), the Z-component (ZZZZZ.ZZ in nT) and F (FFFFF.FF in nT). Please note that a dataset based on the data provided here will be submitted to the World Data Centre for Geomagnetism (WDC Edinburgh) at a later stage and might undergo further modifications. Geomagnetic observatories in general are described in e.g. Jankowski and Sucksdorff (1996), Matzka et al. (2010). GFZ observatories and observatory cooperations are described in Matzka (2016). The Geomagnetic Observatory Tatuoca (TTB) is described in Moschhauser et al. (2017).
# 6
Rosenau, Matthias • Horenko, Illia • Corbi, Fabio • Rudolf, Michael • Kornhuber, Ralf • (et. al.)
Abstract: This data set provides data from subduction zone earthquake experiments and analysis described in Rosenau et al. (2019). In the experiments analogue seismotectonic scale models of subduction zones characterized by two seismogenic asperities are used to study the interaction of asperities over multiple seismic cycles by means of static (Coulomb failure) stress transfer. Various asperity geometries (lateral/along-strike of the subduction zone distance and vertical/across-strike of the subduction zone offset) are tested on their effect on recurrence pattern of simulated great (M8+) earthquakes. The results demonstrate the role of stress coupling in the synchronization of asperities leading to multi-asperity M9+ events in nature. The data set contains time series of experimental surface velocities from which analogue earthquakes are detected and classified into synchronized events and solo events. The latter are subcategorized into main events and aftershocks and into normal and thrust events. An analogue earthquake catalogue lists all categorized events of the 12 experiments used for statistical analysis. Moreover, results from elastic dislocation modelling aimed ate quantifying the stress coupling between the asperities for the various geometries are summarized. Basic statistics of classified events (e.g. percentage of categorized events, coefficient of variation in size and recurrence time etc.) are documented. Matlab scripts are provided to visualize the data as in the paper.
# 7
Blanke, Aglaja • Kwiatek, Grzegorz • Martínez-Garzón, Patricia • Bohnhoff, Marco
Abstract: This data set is supplementary to the BSSA research article of Blanke et al. (2019), in which the local S-wave coda quality factor at The Geysers geothermal field, California, is investigated. Over 700 induced microseismic events recorded between June 2009 and March 2015 at 31 short-period stations of the Berkeley-Geysers Seismic Network were used to estimate the frequency-dependent coda quality factor (Q_C) using the method of Phillips (1985). A sensitivity analysis was performed to different input parameters (magnitude range, lapse time, moving window width, total coda length and seismic sensor component) to gain a better overview on how these parameters influence Q_C estimates. Tested parameters mainly show a low impact on the outcome whereas applied quality criteria like signal-to-noise ratio and allowed uncertainties of Q_C estimates were found to be the most sensitive factors. Frequency-dependent mean-Q_C curves were calculated from seismograms of induced earthquakes for each station located at The Geysers using the tested favored input parameters. The final results were tested in the context of spatio-temporal behavior of Q_C in the reservoir considering distance-, azimuth and geothermal production rate variations. A distance and azimuthal dependence was found which is related to the reservoir anisotropy, lithological-, and structural features. By contrast, variations in geothermal production rates do not influence the estimates. In addition, the final results were compared with previous estimated frequency-independent intrinsic direct S-wave quality factors (Q_D) of Kwiatek et al. (2015). A match of Q_D was observed with Q_C estimates obtained at 7 Hz center-frequency, suggesting that Q_D might not be of an intrinsic but of scattering origin at The Geysers. Additionally, Q_C estimates feature lower spreading of values and thus a higher stability. The Geysers geothermal field is located approximately 110 km northwest of San Francisco, California in the Mayacamas Mountains. It is the largest steam-dominated geothermal reservoir operating since the 1960s. The local seismicity is clearly related to the water injections and steam production with magnitudes up to ~5 occurring down to 5 km depth, reaching the high temperature zone (up to 360°C). The whole study area is underlain by a felsite (granitic intrusion) that shows an elevation towards the southeast and subsides towards northwest. A fracture network induces anisotropy into the otherwise isotropic rocks featuring different orientations. Moreover, shear-wave splitting and high attenuating seismic signals are observed and motivate to analyze the frequency-dependent coda quality factor. Two data sets were analyzed: one distinct cluster located in the northwest (NW) close to injection wells Prati-9 and Prati-29, and the other one southeast (SE) of The Geysers, California, USA, close to station TCH (38° 50′ 08.2″ N, 122° 49′ 33.7″ W and 38° 46′ 59.5″ N, 122° 44′ 13.2″ W, respectively). The frequency-dependent coda quality factor is estimated from the seismic S-wave coda by applying the moving window method and regression analysis of Phillips (1985). Different input parameters including moving widow width, lapse time and total coda length are used to obtain Q_C estimates and associated uncertainties. Within a sensitivity analysis we investigated the influence of these parameters and also of magnitude ranges and seismic sensor components on Q_C estimates. The coda analysis was performed for each event at each sensor component of each station. The seismograms were filtered in predefined octave-width frequency bands with center-frequencies ranging from 1-69 Hz. The moving window method was applied starting in the early coda (after the S-onset) for each frequency band measuring the decay of Power Spectral Density spectra. The decay of coda amplitudes was fitted with a regression line and Q_C estimates were calculated from its decay slope for each frequency band. In a final step a mean-Q_C curve was calculated for each available station within the study area resulting in different curves dependent on event location sites in the northwest and southeast. Data Description The data contain final mean-Q_C estimates of the NW and SE Geysers, coda Q estimates at 7 Hz center-frequency calculated by using the NW cluster, and initial direct Q estimates of Kwiatek et al. (2015) using the same data of the NW cluster. Table S1 shows final mean coda quality factor estimates obtained from the NW cluster at injection wells Prati-9 and Prati-29. The column headers show stations (station), center-frequencies of octave-width frequency bands in Hertz (f[Hz]), mean coda Q estimates (meanQc) and related standard deviations (std), all obtained by coda analysis. Table S2 shows the final mean coda quality factor estimates obtained from additional selected 100 events in the SE Geysers. Column headers correspond to those in Table S1. Table S3 shows coda Q estimates related to 7 Hz center-frequency. The column headers show stations (station), center-frequency of octave-width frequency bands in Hertz (f[Hz]), coda Q estimates at 7 Hz center-frequency (Q_C) and related standard deviations (std2sigma; 95% confidence level), all obtained by coda analysis. Table S4 shows selected direct S-wave quality factors of Kwiatek et al. (2015) obtained by spectral fitting. The column headers show stations (station) and direct S-wave Q estimates (Q_D). The four tables are provided in tab separated txt format. Tables S3 and S4 are used for a comparative study and displayed in Figure 12 of the BSSA article mentioned above.
# 8
Pick, Leonie • Korte, Monika
Abstract: The HMC (Hourly Magnetospheric Currents) index measures the activity of large-scale magnetospheric currents on Earth's surface from 1900 to 2015. It resolves the absolute intensity of low-frequency variations, especially at periods relevant to the solar cycle, more robustly than existing geomagnetic indices. HMC is based on hourly means of vector magnetic field measurements from 34 mid latitude geomagnetic observatories obtained from WDC Edinburgh (http://www.wdc.bgs.ac.uk/catalog/master.html). This data has been manually revised to correct for spikes, jumps and drifts. A detailed description of the derivation method is given in Pick et al., 2018 to which these data are supplementary material. This directory contains the HMC index (hmc1900phor.hor) and the modified observatory data that it is based on (data.zip). The index and the observatory data files are formatted in compliance with the IAGA-2002 ASCII exchange format (https://www.ngdc.noaa.gov/IAGA/vdat/IAGA2002/iaga2002format.html). Individual file names are composed of:[IAGA code of observatory] + [first active year during 1900-2015] + [p(provisional)] + [hor(hourly)] + [_mod(modified)].hor Also included is information on how the data modifications (list in modifications.pdf) were applied (readme.txt).
# 9
GEOFON Data Centre
Abstract: P-phase arrival times automatically created by the SeisComP3 (https://www.seiscomp3.org/) software at the GFZ scanning all stations available in real-time at GEOFON Data Centre and listed in the contributors list. Data have been used in the publication by Steed et al 2018 to test the new CsLoc method, sent in relatime to EMSC using the HMB application (Heinloo, 2016, http://doi.org/10.5880/GFZ.2.4.2016.001). The data sets includes P-phases from 2016 and 2017. The data are presented in two csv tables (part I and part II) that are included in the folder 2018-002_Geofon_csloc_test_phases.zip.
# 10
Nooshiri, Nima • Heimann, Sebastian • Tilmann, Frederik • Dahm, Torsten • Saul, Joachim
Abstract: 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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