121 documents found in 428ms
# 1
Brunke, Heinz-Peter
Abstract: This data publication includes a matlab software package as described in Brunke (2017). In addition to the Matlab software, we provide three test dataset from the Niemegk magnetic observatories (NGK). We present a numerical method, allowing for the evaluation of an arbitrary number (minimum 5 as there are 5 independent parameters) of telescope orientations. The traditional measuring schema uses a fixed number of eight orientations (Jankowski et al, 1996). Our method provides D, I and Z base values and calculated uncertitudes of them. A general approach has significant advantages. Additional measurements may by seamlessly incorporate for higher accuracy. Individual erroneous readings are identified and can be discarded without invalidating the entire data set, a-priory information can be incorporated. We expect the general method to ease requirements also for automated DI-flux measurements. The method can reveal certain properties of the DI-theodolite, which are not captured by the conventional method. Based on the alternative evaluation method, a new faster and less error prone measuring schema is presented. It avoids the need to calculate the magnetic meridian prior to the inclination measurements. Measurements in the vicinity of the magnetic equator become possible with theodolites without zenith ocular.
# 2
Heidbach, Oliver • Ziegler, Moritz
Abstract: The World Stress Map (WSM) is the global compilation of information on the present-day stress field in the Earth's crust. The current WSM database release 2016 (Heidbach et al., 2016) has 42,870 data records, but the data are unevenly distributed and clustered.To analyse the wave-length of the crustal stress pattern of the orientation of maximum horizontal stress Shmax, we use so-called smoothed stress maps that show the mean SHmax orientation on regular grids. The mean SHmax orientation is estimated with the Matlab® script stress2grid (Ziegler and Heidbach, 2017) which is based on the statistics of bi-polar data. The script provides two different approaches to calculate the mean SHmax orientation on regular grids.The first is using a constant search radius around the grid point and computes the mean SHmax orientation if sufficient data records are within the given fixed search radius. This can result in mean SHmax orientations with a high standard deviation of the individual mean SHmax orientation and it may hide local perturbations. Thus, the mean SHmax orientation is not necessarily reliable for a local stress field analysis.The second approach is using variable search radii and determines the search radius for which the standard deviation of the mean SHmax orientation is below a user-defined threshold. This approach delivers the mean SHmax orientations with a user-defined degree of reliability. It resolves local stress perturbations and is not available in areas with no data or conflicting information that result in a large standard deviation.The search radius starts with 1000 km and is decreased in 100 km steps down to 100 km. Mean SHmax orientation is taken and plotted here for the largest search radius when the standard deviation of the mean SHmax orientation at the individual grid points is smaller than 25°. For the estimation of the mean Shmax we selected the following data: A-C quality data without PBE flag.Furthermore, only data records located on the same tectonic plate as the grid point is used to calculate the mean SHmax orientation. Minimum number of data records within the search radius is n = 5 and data records within a distance of d ≤ 200 km to the nearest plate boundary are not used. Plate boundaries are taken from the global model PB2002 from Bird (2003).Furthermore, a distance and data quality weight is applied; the distance threshold is set to 10% of the search radius. We provide the resulting smoothed stress data for four global grids (0.2°, 0.5°, 1°, and 2° grid spacing) using two fixed search radii (250 and 500 km) and the approach with variable search radii. Details on the format of the data files with the mean SHmax orientation are provided in the 2018-002_readme file.
# 3
Ullah, Shahid • Abdrakhmatov, Kanat • Sadykova, Alla • Ibragimov, Roman • Ishuk, Anatoly • (et. al.)
Abstract: Area Source model for Central AsiaThe area sources for Central Asia within the EMCA model are defined by mainly considering the pattern of crustal seismicity down to 50 km depth. Although tectonic and geological information, such as the position and strike distribution of known faults, have also been taken into account when available. Large area sources (see, for example source_id 1, 2, 5, 45 and 52, source ids are identified by parameter “source_id” in the related shapefile) are defined where the seismicity is scarce and there are no tectonic or geological features that would justify a further subdivision. Smaller area sources (e.g., source_id values 36 and 53) have been designed where the seismicity can be assigned to known fault zones. In order to obtain a robust estimation of the necessary parameters for PSHA derived by the statistical analysis of the seismicity, due to the scarcity of data in some of the areas covered by the model, super zones are introduced. These super zones are defined by combining area sources based on similarities in their tectonic regime, and taking into account local expert’s judgments. The super zones are used to estimate: (1) the completeness time of the earthquake catalogue, (2) the depth distribution of seismicity, (3) the tectonic regime through focal mechanisms analysis, (4) the maximum magnitude and (5) the b values via the GR relationship.The earthquake catalogue for focal mechanism is extracted from the Harvard Global Centroid Moment Tensor Catalog (Ekström and Nettles, 2013). For the focal mechanism classification, the Boore et al. (1997) convention is used. This means that an event is considered to be strike-slip if the absolute value of the rake angle is <=30 or >=150 degrees, normal if the rake angle is <-30 or >-150 and reverse (thrust) if the rake angle is >30 or <150 degrees. The distribution of source mechanisms and their weights are estimated for the super zones. For area sources, the maximum magnitude is usually taken from the historical seismicity, but due to some uncertainties in the magnitudes of the largest events, the opinions of the local experts are also included in assigning the maximum magnitude to each super zone. Super zones 2 and 3, which belongs to stable regions, are each assigned a maximum magnitude of 6, after Mooney et al. (2012), which concludes after analyses and observation of modern datasets that at least an event of magnitude 6 can occur anywhere in the world. For hazard calculations, each area source is assigned the maximum magnitude of their respective super zone.For processing the GR parameters (a and b values) for the area sources, the completeness analysis results estimated for the super zones are assigned to the respective smaller area sources. If the individual area source has at least 20 events, the GR parameters are then estimated for the area source. Otherwise, the b value is adopted from the respective super zone to which the smaller area source belongs, and the a value is estimated based on the Weichert (1980) method. This ensures the stability in the b value as well as the variation of activity rate for different sources. The hypocentral depth distribution is estimated from the seismicity inside each super zone. The depth distribution is considered for maximum up to three values. Based on the number of events, the weights are assigned to each distribution. These depth distributions, along with corresponding weights, are further assigned to the area sources within the same super zones.
Distribution file: "EMCA_seismozonesv1.0_shp.zip"Version: v1.0Release date: 2015-07-30Format: ESRI ShapefileGeometry type: polygonsNumber of features: 63Spatial Reference System: +proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs Distribution file: "EMCA_seismozonesv1.0_nrml.zip"Version: v1.0Release date: 2015-07-30Format: NRML (XML) Format compatible with the GEM OpenQuake platform (http://www.globalquakemodel.org/openquake/about/platform/) Feature attributes:src_id : Id of the seismic sourcesrc_name : Name of the seismic sourcetect_reg: Tectonic regime of the seismic sourceupp_seismo : Upper level of the the seismogenic depth (km)low_seismo : Lower level of the seismogenic depth (km)mag_scal_r: Magnitude scaling relationshiprup_asp_ra: Rupture aspect ratiomfd_type : Magnitude frequency distribution typemin_mag: Minimum magnitude of the magnitude frequency relationshipmax_mag: Maximum magnitude of the magnitude frequency relationshipa_value: a value of the magnitude frequency relationshipb_balue : b value of the magnitude frequency relationshipnum_npd: number of nodal plane distributionweight_1 : weight of 1st nodal plane distributionstrike_1: Strike of the seismic source (degrees)rake_1: rake of the seismic source (degrees)dip_1: dip of the seismic source (degrees)num_hdd: number of hypocentral depth distributionhdd_d_1: Depth of 1st hypocentral depth distribution (km)hdd_w_1: Weight of 1st hypocentral depth distribution
# 4
Reiter, Karsten • Heidbach, Oliver • Müller, Birgit • Reinecker, John • Röckel, Thomas
Abstract: Die Spannungskarte Deutschland zeigt die Orientierung der gegenwärtigen maximalen horizontalen Spannung (SHmax) in der Erdkruste. Unter der Annahme, dass die vertikale Spannung (SV) eine Hauptspannung ist, legt SHmax die Orientierung des 3D Spannungstensors festgelegt; die minimale horizontale Spannung Shmin ist entsprechend senkrecht zu SHmax. In der Spannungskarte sind die SHmax Orientierungen als Linien unterschiedlicher Länge dargestellt. Die Länge der Linie ist dabei ein Maß für die Datenqualität und das Symbol zeigt die Methode und die Farbe das Spannungsregime an. Daten mit E-Qualität sind ohne weitere Information als Punkte in der Karte dargestellt. Die Spannungsdaten sind frei zugänglich und Bestandteil des World Stress Map (WSM) Projektes. Weitere Informationen zu den Daten und Kriterien der Datenanalyse und Qualitätszuordnung befinden sich auf der WSM Internetseite unter http://www.world-stress-map.org. The English version of the World Stress Map Germany is available via http://doi.org/10.5880/WSM.Germany2016_en.
# 5
Heidbach, Oliver • Rajabi, Mojtaba • Reiter, Karsten • Ziegler, Moritz • WSM Team
Abstract: The World Stress Map (WSM) database is a global compilation of information on the crustal present-day stress field. It is a collaborative project between academia and industry that aims to characterize the stress pattern and to understand the stress sources. It commenced in 1986 as a project of the International Lithosphere Program under the leadership of Mary-Lou Zoback. From 1995-2008 it was a project of the Heidelberg Academy of Sciences and Humanities headed first by Karl Fuchs and then by Friedemann Wenzel. Since 2009 the WSM is maintained at the GFZ German Research Centre for Geosciences and since 2012 the WSM is a member of the ICSU World Data System. All stress information is analysed and compiled in a standardized format and quality-ranked for reliability and comparability on a global scale. The WSM database release 2016 contains 42,870 data records within the upper 40 km of the Earth’s crust. The data are provided in three formats: Excel-file (wsm2016.xlsx), comma separated fields (wsm2016.csv) and with a zipped google Earth input file (wsm2016_google.zip). Data records with reliable A-C quality are displayed in the World Stress Map (doi:10.5880/WSM.2016.002). Further detailed information on the WSM quality ranking scheme, guidelines for the various stress indicators, and software for stress map generation and the stress pattern analysis is available at www.world-stress-map.org.
# 6
Heidbach, Oliver • Rajabi, Mojtaba • Reiter, Karsten • Ziegler, Moritz
Abstract: The World Stress Map (WSM) is a global compilation of information on the crustal present-day stress field. It is a collaborative project between academia and industry that aims to characterize the stress pattern and to understand the stress sources. It commenced in 1986 as a project of the International Lithosphere Program under the leadership of Mary-Lou Zoback. From 1995-2008 it was a project of the Heidelberg Academy of Sciences and Humanities headed first by Karl Fuchs and then by Friedemann Wenzel. Since 2009 the WSM is maintained at the GFZ German Research Centre for Geosciences and since 2012 the WSM is a member of the ICSU World Data System. All stress information is analysed and compiled in a standardized format and quality-ranked for reliability and comparability on a global scale. The stress map displays A-C quality stress data records of the upper 40 km of the Earth’s crust from the WSM database release 2016 (doi:10.5880/WSM.2016.001). Focal mechanism solutions determined as being potentially unreliable (labelled as Possible Plate Boundary Events in the database) are not displayed. Further detailed information on the WSM quality ranking scheme, guidelines for the various stress indicators, and software for stress map generation and the stress pattern analysis is available at http://www.world-stress-map.org.
# 7
Reiter, Karsten • Heidbach, Oliver • Müller, Birgit • Reinecker, John • Röckel, Thomas
Abstract: The stress map of Germany shows the orientation of the current maximum horizontal stress (SHmax) in the earth's crust. Assuming that the vertical stress (SV) is a principal stress, SHmax defines the orientation of the 3D stress tensor; the minimum horizontal stress Shmin is than perpendicular to SHmax. In the stress map the SHmax orientations are represented as lines of different lengths. The length of the line is a measure of the quality of data and the symbol shows the stress indicator and the color the stress regime. Data with E-Quality are shown without additional information as dots on the map. The stress data are freely available and part of the World Stress Map (WSM) project. For more information about the data and criteria of data analysis and quality mapping are plotted along the WSM website at http://www.world-stress-map.org.The German version of the World Stress Map Germany is available via http://doi.org/10.5880/WSM.Germany2016.
The World Stress Map (WSM) is a global compilation of information on the crustal present-day stress field. It is a collaborative project between academia and industry that aims to characterize the stress pattern and to understand the stress sources. It commenced in 1986 as a project of the International Lithosphere Program under the leadership of Mary-Lou Zoback. From 1995-2008 it was a project of the Heidelberg Academy of Sciences and Humanities headed first by Karl Fuchs and then by Friedemann Wenzel. Since 2009 the WSM is maintained at the GFZ German Research Centre for Geosciences and since 2012 the WSM is a member of the ICSU World Data System. All stress information is analysed and compiled in a standardized format and quality-ranked for reliability and comparability on a global scale.
# 8
Heidbach, Oliver • Custodio, Susana • Kingdon, Andrew • Mariucci, Maria Theresa • Montone, Paola • (et. al.)
Abstract: The Stress Map of the Mediterranean and Central Europe 2016 displays 5011 A-C quality stress data records of the upper 40 km of the Earth’s crust from the WSM database release 2016 (Heidbach et al, 2016, http://doi.org/10.5880/WSM.2016.001). Focal mechanism solutions determined as being potentially unreliable (labelled as Possible Plate Boundary Events in the database) are not displayed. Further detailed information on the WSM quality ranking scheme, guidelines for the various stress indicators, and software for stress map generation and the stress pattern analysis is available at www.world-stress-map.org.
The World Stress Map (WSM) is a global compilation of information on the crustal present-day stress field. It is a collaborative project between academia and industry that aims to characterize the stress pattern and to understand the stress sources. It commenced in 1986 as a project of the International Lithosphere Program under the leadership of Mary-Lou Zoback. From 1995-2008 it was a project of the Heidelberg Academy of Sciences and Humanities headed first by Karl Fuchs and then by Friedemann Wenzel. Since 2009 the WSM is maintained at the GFZ German Research Centre for Geosciences and since 2012 the WSM is a member of the ICSU World Data System. All stress information is analysed and compiled in a standardized format and quality-ranked for reliability and comparability on a global scale.
# 9
Ziegler, Moritz • Rajabi, Mojtaba • Hersir, Gylfi • Ágústsson, Kristján • Árnadóttir, Sigurveig • (et. al.)
Abstract: The stress map of Iceland shows the orientation of the current maximum horizontal stress (SHmax) in the earth's crust. Assuming that the vertical stress (SV) is a principal stress, SHmax defines the orientation of the 3D stress tensor; the minimum horizontal stress Shmin is than perpendicular to SHmax. In the stress map the SHmax orientations are represented as lines of different lengths. The length of the line is a measure of the quality of data and the symbol shows the stress indicator and the color the stress regime. Data with E-Quality are shown without additional information as dots on the map. The stress data are freely available and part of the World Stress Map (WSM) project. For more information about the data and criteria of data analysis and quality mapping are plotted along the WSM website at http://www.world-stress-map.org.
The World Stress Map (WSM) is a global compilation of information on the crustal present-day stress field. It is a collaborative project between academia and industry that aims to characterize the stress pattern and to understand the stress sources. It commenced in 1986 as a project of the International Lithosphere Program under the leadership of Mary-Lou Zoback. From 1995-2008 it was a project of the Heidelberg Academy of Sciences and Humanities headed first by Karl Fuchs and then by Friedemann Wenzel. Since 2009 the WSM is maintained at the GFZ German Research Centre for Geosciences and since 2012 the WSM is a member of the ICSU World Data System. All stress information is analysed and compiled in a standardized format and quality-ranked for reliability and comparability on a global scale.
# 10
Meeßen, Christian
Abstract: This code is a python implementation of the p- and s-wave velocity to density conversion approach after Goes et al. (2000). The implementation has been optimised for regular 3D grids using lookup tables instead of Newton iterations. Goes et al. (2000) regard the expansion coefficient as temperature dependent using the relation by Saxena and Shen (1992). In `Conversion.py`, the user can additionally choose between a constant expansion coefficient or a pressure- and temperature dependent coefficient that was derived from Hacker and Abers (2004).For detailed information on the physics behind the approach have a look at the original paper by Goes et al. (2000). Up-to-date contact information are given on the author's github profile https://github.com/cmeessen.
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