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GFZ VER13 SLCCI precise orbits of altimetry satellites ERS-1, ERS-2, Envisat, TOPEX/Poseidon, Jason-1, and Jason-2 in the ITRF2014 reference frame
ISO19139(INSPIRE)
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Dataset

Rudenko, Sergei
• Schöne, Tilo
• Esselborn, Saskia
• Neumayer, Hans Karl

__Abstract:__The data set provides GFZ VER13 orbits of altimetry satellites: ERS-1 (August 1, 1991 - July 5, 1996),ERS-2 (May 13, 1995 - February 27, 2006),Envisat (April 12, 2002 - April 8, 2012),TOPEX/Poseidon (September 23, 1992 - October 8, 2005),Jason-1 (January 13, 2002 - July 5, 2013) andJason-2 (July 5, 2008 - April 5, 2015) derived at the time spans given at the GFZ German Research Centre for Geosciences (Potsdam, Germany) within the Sea Level phase 2 project of the European Space Agency (ESA) Climate Change Initiative using "Earth Parameter and Orbit System - Orbit Computation (EPOS-OC)" software (Zhu et al., 2004) and the Altimeter Database and processing System (ADS, http://adsc.gfz-potsdam.de/ads/) developed at GFZ. The orbits were computed in the ITRF2014 terrestrial reference frame for all satellites using common, most precise models and standards available and described below. The ERS-1 orbit is computed using satellite laser ranging (SLR) and altimeter crossover data, while the ERS-2 orbit is derived using additionally Precise Range And Range-rate Equipment (PRARE) measurements. The Envisat, TOPEX/Poseidon, Jason-1, and Jason-2 orbits are based on Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) and SLR observations. For Envisat, altimeter crossover data were used additionally at 44 of 764 orbital arcs with gaps in SLR and DORIS data. The orbit files are available in the Extended Standard Product 3 Orbit Format (SP3-c). Files are gzip-compressed. File names are given as sate_YYYYMMDD_SP3C.gz, where "sate" is the abbreviation (ENVI, ERS1, ERS2, JAS1, JAS2, TOPX) of the satellite name, YYYY stands for 4-digit year, MM for month and DD for day of the beginning of the file. More details on these orbits are provided in Rudenko et al. (2018) to which these orbits are supplementary material.

Supplement to: Identification of kinematic boundary conditions triggering removal of material in tectonically erosive margins : insight from scaled physical experiments
ISO19139(INSPIRE)
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DataCite
Dataset

Albert, Francisca

__Abstract:__This data set includes movies and images of sandbox experiments aiming at understainding the process of subduction erosion at active plate margins (Albert, 2013). Four experiments are documented by means of movies showing the evolution of a strong wedge (sand-sugar mix, “Reference experiment.avi”), a weak wedge (sand only, “F1 experiment.avi”) and two successive phases of a wedge that undergoes subduction erosion by subducting topographic highs (first stage without subducting topography= “HL.1 experiment.avi” and second stage with subducting topography = “HL.2 experiment.avi”). Images of preliminary tests and experiments not considered in Albert (2013) are given in “Appendix A2.2.pdf” (small box experiments) and “Appendix A3.3.pdf” (experiments varying friction and slope).

Supplementary information to "Deep low-frequency earthquakes reveal ongoing magmatic recharge beneath Laacher See Volcano (Eifel, Germany)": Moment tensor inversion report
[version 1.0]
ISO19139(INSPIRE)
DIF
DataCite
Dataset

Heimann, Sebastian
• Dahm, Torsten
• Hensch, Martin
• Ritter, Joachim
• Schmidt, Bernd
• (et. al.)

__Abstract:__The interactive web page contains supplementary information for a publication by Hensch et al. 2019: "Deep low-frequency earthquakes reveal ongoing magmatic recharge beneath Laacher See Volcano (Eifel, Germany)". Details on the analysis of three tectonic and nine deep low-frequency earthquakes are given, including parameter results, error estimates, and figures. The analysis has been performed using the Grond software package (Heimann et. al 2018). The open source software for seismic source parameter optimization (Grond, Heimann et al., 2018) implements a bootstrap-based method to retrieve solution sub-spaces, parameter trade-offs and uncertainties of earthquake source parameters. Synthetic and observed P and S phase waveforms are restituted to displacement and filtered between 0.5 and 5 Hz in variable frequency ranges, depending on the signal-to-noise ratio (SNR) and the character of the signals. Station amplification factors and transfer functions have been evaluated before the restitution using an empirical calibration method (see Dahm et al., 2018). From waveforms, different types of body wave attributes were calculated, as amplitude spectra, envelopes, and amplitude spectral ratios. The Green's functions (GF) were calculated with the orthonormal propagator method (QSEIS, Wang, 1999; see https://github.com/pyrocko/fomosto-qseis/), for a 1 km grid spacing in a volume of 150 km source-receiver distances and 1 - 50 km source depths. The sampling rate was 40 Hz and the GF include near field terms. All GF are stored in a Pyrocko GF store (Pyrocko toolbox, see Heimann et al., 2017). We use a nearest neighbor interpolation in between the grid points of the pre-computed GF. Restituted observed and synthetic ground displacement time series are filtered and windowed between [-2 s; +3 s] from the expected phase arrival, given the tested candidate source model at each forward modeling step in the optimization. Additional to full waveforms, amplitude spectra, envelopes and spectral ratios between P-SV and SH-SV waves are compared. For spectral ratios, a water level approach was implemented to avoid bias from high noise. All components of the mixed inversion received a proper linear weighting with factors between 0.5 and 3, which was selected after running tests with some master events. Weighting and frequency range were defined different for earthquakes with magnitudes above or below ML 2. P and S phase arrivals have been picked to ensure correct selection of time windows during the centroid inversion, and station blacklists were considered event-wise, depending on the SNR. The plots show for every event the data fits and different types of solution plots. The naming of pages is self-explanatory, but more information can be found in the Grond documentation (https://pyrocko.org/grond/). In order to evaluate the ensembles of solutions for interpretation, we extended the standard statistical analysis of Grond to consider a cluster analysis of source mechanism distributions before statistical analysis. This is introduced because the best ensemble solutions of many of the DLF events show higher variability and groups of different mechanisms. A simple mean or median does not always represent the families of best performing solutions. We therefore declustered the ensemble of best solutions using the method of Cesca et al. (2013), applying the Kagan angle norm, and performed the statistical analysis for each individual cluster.

Dobslaw, Henryk
• Dill, Robert
• Dahle, Christoph

__Abstract:__Spherical harmonic coefficients that represent anomalous contributions of the non-tidal dynamic ocean to ocean bottom pressure during the specified timespan. The anomalous signals are relative to the mean field from 2003-2014.

Dobslaw, Henryk
• Dill, Robert
• Dahle, Christoph

__Abstract:__Spherical harmonic coefficients that represent the sum of the ATM (or GAA) and OCN (or GAB) coefficients during the specified timespan. These coefficients represent anomalous contributions of the non-tidal dynamic ocean to ocean bottom pressure, the non-tidal atmospheric surface pressure over the continents, the static contribution of atmospheric pressure to ocean bottom pressure, and the upper-air density anomalies above both the continents and the oceans. The anomalous signals are relative to the mean field from 2003-2014.

Dobslaw, Henryk
• Dill, Robert
• Dahle, Christoph

__Abstract:__Spherical harmonic coefficients that are zero over the continents, and provide the anomalous simulated ocean bottom pressure that includes non-tidal air and water contributions elsewhere during the specified timespan. These coefficients differ from GLO (or GAC) coefficients over the ocean domain by disregarding upper air density anomalies. The anomalous signals are relative to the mean field from 2003-2014.

Dobslaw, Henryk
• Dill, Robert
• Dahle, Christoph

__Abstract:__Spherical harmonic coefficients that represent anomalous contributions of the non-tidal atmosphere to the Earth's mean gravity field during the specified timespan. This includes the contribution of atmospheric surface pressure over the continents, the static contribution of atmospheric pressure to ocean bottom pressure elsewhere, and the contribution of upper-air density anomalies above both the continents and the oceans. The anomalous signals are relative to the mean field from 2003-2014.

Dahle, Christoph
• Flechtner, Frank
• Murböck, Michael
• Michalak, Grzegorz
• Neumayer, Hans
• (et. al.)

__Abstract:__Spherical harmonic coefficients representing an estimate of Earth's mean gravity field during the specified timespan derived from GRACE mission measurements. These coefficients represent the full magnitude of land hydrology, ice, and solid Earth processes. Further, they represent atmospheric and oceanic processes not captured in the accompanying GAC product.

Ring-shear test data of quartz sand G23 used for analogue experiments in the Helmholtz Laboratory for Tectonic Modelling (HelTec) at the GFZ German Research Centre for Geosciences in Potsdam
ISO19139(INSPIRE)
DIF
DataCite
Dataset

Rosenau, Matthias
• Pohlenz, Andre
• Kemnitz, Helga
• Warsitzka, Michael

__Abstract:__This dataset provides friction data from ring-shear tests (RST) for a quartz sand (type “G23”). This material is used in various types of analogue experiments in the Helmholtz Laboratory for Tectonic Modelling (HelTec) at the GFZ German Research Centre for Geosciences in Potsdam for simulating brittle rocks in the upper crust (e,g. Kenkmann et al., 2007; Contardo et al., 2011; Reiter et al., 2011;Warsitzka et al., 2013; Santimano,et al., 2015; Warsitzka et al., 2015; Ritter et al., 2016; 2018 a,b). The material has been characterized by means of internal friction coefficients µ and cohesions C. According to our analysis the material shows a Mohr-Coulomb behaviour characterized by a linear failure envelope and peak, dynamic and reactivation friction coefficients of µP = 0.73, µD = 0.57 and µR = 0.65, respectively. Cohesions C are in the order of 10 – 120 Pa. The material shows a minor rate-weakening of <1% per ten-fold change in shear velocity v. Further information about materical characteristics, measurement procedures, sample preparation, the RST (Ring-shear test) and VST (Velocity stepping test) procedure, as well as the analysed method is proviced in the data description file. The list of files explains the file and folder structure of the data set.

Ring-shear test data of quartz sand G12 used for analogue experiments in the Helmholtz Laboratory for Tectonic Modelling (HelTec) at the GFZ German Research Centre for Geosciences in Potsdam
ISO19139(INSPIRE)
DIF
DataCite
Dataset

Rosenau, Matthias
• Pohlenz, Andre
• Kemnitz, Helga
• Warsitzka, Michael

__Abstract:__This dataset provides friction data from ring-shear tests (RST) for a quartz sand (“G12”). This material is used in various types of analogue experiments in the Helmholtz Laboratory for Tectonic Modelling (HelTec) at the GFZ German Research Centre for Geosciences in Potsdam for simulating brittle rocks in the upper crust. The material has been characterized by means of internal friction coefficients µ and cohesions C. According to our analysis the material shows a Mohr-Coulomb behaviour characterized by a linear failure envelope and peak, dynamic and reactivation friction coefficients of µP = 0.69, µD = 0.55 and µR = 0.62, respectively. Cohesions C are in the order of 50 – 110 Pa. The material shows a minor rate-weakening of <1% per ten-fold change in shear velocity. Further information about materical characteristics, measurement procedures, sample preparation, the RST (Ring-shear test) and VST (Velocity stepping test) procedure, as well as the analysed method is proviced in the data description file. The list of files explains the file and folder structure of the data set.

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