373 documents found in 273ms
# 1
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.
# 2
Corbi, Fabio • Xu, Wenbin • Rivalta, Eleonora • Jonsson, Sigurjon
Abstract: This dataset is supplementary material to the article by Xu et al. (2016) ‘Graben formation and dike arrest during the 2009 Harrat Lunayyir dike intrusion in Saudi Arabia: Insights from InSAR, stress calculations and analog experiments’. The Authors described the spatial and temporal effects of a propagating dike on crustal deformation, including the interaction with faulting, using a multidisciplinary approach. This supplementary material concerns the analog modelling part only. For a detailed description of the experimental procedure, set-up and materials used, please refer to the article of Xu et al. (2016; paragraph 5). The data available in this supplementary publication are: - A folder (2019-003_Corbi-et-al_Fig6.zip) containing: 1. top-view pictures (e.g. ‘lunayyr1_0025.JPG’) and displacement data obtained with MatPiv (e.g. ‘uun25.mat’ and ‘uvn25.mat’; dike parallel and orthogonal components; respectively) shown in figure 6 of Xu et al 2016. 2. a Matlab script (‘fig6_a_h.m’) that allows reproducing the same figure setup as in figure 6 panels a-h of Xu et al 2016. The thick red line highlights dike position. The background shading refers to dike orthogonal displacement. - A folder (2019-003_Corbi-et-al_PIV_data.zip) containing: 1. surface deformation data obtained with MatPiv. Each file (‘vel_fine_piv#.mat’) contains 4 elements (x, y, u, v) representing the coordinates and horizontal and vertical component of incremental velocity field organized in a 143 x 215 matrix; 2. the run_movie.m Matlab script. Running it the user can visualize the space-time evolution of cumulative surface displacement. The background shading refers to dike orthogonal component of displacement. The thick red line highlights dike position. - A folder (2019-003_Corbi-et-al_pictures.zip) containing the whole set of pictures from the experiment shown in Xu et al., 2016. - A movie (2019-003_Corbi-et-al_graben formation.mp4) obtained using the whole set of pictures (96 photos). The thick red line highlights dike position. The amount of dike opening is reported as header. - A movie (2019-003_Corbi-et-al_cum_displacement.mp4) showing the space-time evolution of cumulative surface displacement, where the background shading refers to dike orthogonal component of displacement. The thick red line highlights dike position.
# 3
Lu, Biao • Luo, Zhicai • Zhong, Bo • Zhou, Hao • Förste, Christoph • (et. al.)
Abstract: IGGT_R1 is a static gravity field model based on the second invariant of the GOCE gravitational gradient tensor, up to degree and order 240. Based on tensor theory, three invariants of the gravitational gradient tensor (IGGT) are independent of the gradiometer reference frame (GRF). Compared to traditional methods for calculation of gravity field models based on GOCE data, which are affected by errors in the attitude indicator, using IGGT and least squares method avoids the problem of inaccurate rotation matrices. IGGT_R1 is the first experiment to use this method to build a real gravity field model by using GOCE gravitational gradients. This new model has been developed by Wuhan University (WHU), GFZ German Research Centre for Geosciences (GFZ), Technical University of Berlin (TUB), Huazhong University of Science and Technology (HUST) and Zhengzhou Information Engineering University (IEU). More details about the gravity field model IGGT_R1 is given in our paper “The gravity field model IGGT_R1 based on the second invariant of the GOCE gravitational gradient tensor” (Lu et al., 2017, http://doi.org/10.1007/s00190-017-1089-8). This work is supported by the Chinese Scholarship Council (No. 201506270158), the Natural Science Foundation of China (Nos. 41104014, 41131067, 41374023, 41474019 and 41504013) and the Key Laboratory of Geospace Environment and Geodesy, Ministry Education, Wuhan University (No. 16-02-07).
# 4
Pilz, Marco • Woith, Heiko • Festa, Gaetano
Abstract: This data set contains continuous recordings of seismic noise, which have been made on the surface of a shallow volcanic crater in the Phlegrean Fields volcanic complex near Naples, Italy, where a significant level of volcanic-hydrothermal activity is presently concentrated (MED-SUV = Mediterranean Supersite Volcanoes). As part of the Phlegrean Fields, the Solfatara crater is a 0.4 × 0.5 km sub-rectangular structure whose geometry is mainly due to the control exerted by N40–50W and N50E trending normal fault systems, along which geothermal fluids can ascend. These systems crosscut the study area and have been active several times in the past.
# 5
Förste, Christoph • Bruinsma, Sean • Abrikosov, Oleh • Rudenko, Sergiy • Lemoine, Jean-Michel • (et. al.)
Abstract: EIGEN-6S4 (Version 2) is a satellite-only global gravity field model from the combination of LAGEOS, GRACE and GOCE data. All spherical harmonic coefficients up to degree/order 80 are time variable. Their time variable parameters consist of drifts as well as annual and semi-annual variations per year. The time series of the time variable spherical harmonic coefficients are based on the LAGEOS-1/2 solution (1985 to 2003) and the GRACE-LAGEOS monthly gravity fields RL03-v2 (August 2002 to July 2014) from GRGS/Toulouse (Bruinsma et al. 2009). The herein included GRACE/LAGEOS data were combined with all GOCE data which have been processed via the direct numerical approach (Pail et al. 2011). The polar gap instabilty has been overcome using the Sperical Cap Regularization (Metzler and Pail 2005). That means this model is a combination of LAGEOS/GACE with GO_CONS_GCF_2_DIR_R5 (Bruinsma et al. 2013). Version History: This data set is an updated version of Foerste et al. (2016, http://doi.org/10.5880/icgem.2016.004) Compared to the first version, EIGEN-6S4v2 contains an improved modelling of the time variable part, in particular for C20.
# 6
Kufner, Sofia-Katerina • Kakar, Najibullah • Murodkulov, Shokhruhk • Schurr, Bernd • Yuan, Xiaohui • (et. al.)
Abstract: The Pamir-Hindu Kush region of Tajikistan and NE Afghanistan stands out due to its worldwide unique zone of intense intermediate depth seismicity, accommodating frequent Mw 7+ earthquakes with hypocenters reaching down to 250 km depth. With this network we aim to collect data allowing to characterize the active deformation within the Hindu Kush mountains and the Tajik-Afghan basin at the northwestern tip of the India-Asia collision zone. The network consists 15 sites (14 stations in Afghanistan, 1 station in Tajikistan), situated on top of the nest of intermediate depth seismicity and further west in the Afghan platform. The stations are equipped with short period Mark seismometers and Cube data recorders. Waveform data are available from the GEOFON data centre, under network code 4C, and are embargoed until 2023. After the end of embargo, data will be openly available under CC-BY 4.0 license according to GIPP-rules.
# 7
Hinzen, Klaus-G. • Fleischer, Claus
Abstract: Engineering seismological models (incl. ground amplification and topographic effects) of key structures in Tiryns and Midea, Greece, will be used to test the hypothesis of seismogenic causes of the decline of the Mycenaean settlements in the 12th century BC.
# 8
Bernd Schurr • Anke Dannowski • Branislav Glavatovic • Llambro Duni • Heidrun Kopp • (et. al.)
Abstract: Raw-, SEG-Y and other supplementary data of the landside deployment from the amphibious wide-angle seismic experiment ALPHA are presented. The aim of this project was to reveal the crustal and lithospheric structure of the subducting Adriatic plate and the external accretionary wedge in the southern Dinarides. Airgun shots from the RV Meteor were recorded along two profiles across Montenegro and northern Albania.
# 9
Andreas Köhler • Christian Weidle • Christopher Nuth
Abstract: Climatic change is of incredible importance in the polar regions as ice-sheets and glaciers respond strongly to change in average temperature. The analysis of seismic signals (icequakes) emitted by glaciers (i.e., cryo-seismology) is thus gaining importance as a tool for monitoring glacier activity. To understand the scaling relation between regional glacier-related seismicity and actual small-scale local glacier dynamics and to calibrate the identified classes of icequakes to locally observed waveforms, a temporary passive seismic monitoring experiment was conducted in the vicinity of the calving front of Kronebreen, one of the fastest tidewater glaciers on Svalbard (Fig. 1). By combining the local observations with recordings of the nearby GEOFON station GE.KBS, the local experiment provides an ideal link between local observations at the glacier to regional scale monitoring of NW Spitsbergen. During the 4-month operation period from May to September 2013, eight broadband seismometers and three 4-point short-period arrays were operating around the glacier front of Kronebreen.
# 10
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.
spinning wheel Loading next page