501 documents found in 383ms
# 1
Heit, B. • Weber, M. • Tilmann, F. • Haberland, C. • Jia, Y. • (et. al.)
Abstract: The SWATH-D experiment is dense deployment of 154 seismic stations in the Central and Eastern Alps between Italy and Austria, complementing the larger-scale sparser AlpArray Seismic Network (AASN). SWATH-D will provide high resolution images from the surface into the upper mantle, and allow observations of local seismicity. SWATH-D focuses on a key area of the Alps where the hypothesized flip in subduction polarity has been suggested, and where an earlier seismic profile (TRANSALP) has imaged a jump in the Moho. Where mains power is available (at ca. 80 sites) stations are providing realtime data via the cellphone network and are equipped with Güralp CMG-3EPSC (60s) seismometers and Earth Data Recorders EDR-210. The rest of the stations are offline and consist mainly of Nanometrics Trillium Compact (120s) and Güralp CMG-3EPSC (60s) seismometers equipped with either Omnirecs CUBE3 or PR6-24 Earth Data Loggers. All stations are equipped with external GPS antennas and the sampling rate is 100 Hz (Heit, et al., 2018). The network will operate for 2 years starting in July 2017. The Swath-D data will be used directly by 20 individual proposals of the MB-4D Priority Program (Mountain Building Processes in Four Dimensions, 2017) of the German Research Foundation (DFG) and data products derived from it will contribute to additional 13 proposals. SWATH-D is thus an important link between the MB-4D Priority Program and the international AlpArray communities and a scientific service to many of the proposals within the DFG Priority Program. Waveform data are available from the GEOFON data centre, under network code ZS, and are embargoed until August 2023. After the end of embargo, data will be openly available under CC-BY 4.0 license according to GIPP-rules.
# 2
Sakic, Pierre • Mansur, Gustavo • Chaiyaporn, Kitpracha • Ballu, Valérie
Abstract: Operations such as time and coordinate conversions and data cleaning are routine tasks in geodesy and geophysics. Nevertheless, simple and efficient high-level functions to help those kinds of jobs are barely available, and has to be developed, again and again, by each student, engineer for each new project, and even by senior scientists. On another hand, Python became little by little within the last decade a well-used programming language in the academic world. Despite the fact that countless toolboxes already exist in Python for scientific purposes, none really exists for geodetic-oriented purposes. The geodeZYX toolbox aims to fill this gap. The objective of this toolbox, written in Python 3, is to provide a simple but useful and efficient set of functions to help geodesists and geophysicists to spend less time on the pre-processing steps and focus faster on their research, according to the KISS Principle. A static version of the geodeZYX toolbox is available via the "Files" section on this DOI Landing Page and via github (https://github.com/GeodeZYX/GeodeZYX-Toolbox_v4).
# 3
Menges, Johanna • Hovius, Niels • Andermann, Christoff • Dietze, Michael • Swoboda, Charlie • (et. al.)
Abstract: This data publication contains the data sets of a study aiming to reconstruct environmental conditions during the Holocene in the upper part of the Kali Gandaki valley, Nepal. The data are for samples taken from paleosol sections in the Upper Mustang region (Menges et al. 2019). On these samples we measured the grain size distribution to gain information about the depositional processes, pollen data to reconstruct past vegetation, 14C isotopes in the humin fraction of organic matter for soil formation ages, and hydrogen isotopic composition on n-alkanes to reconstruct past hydrological conditions. This is complemented with optically stimulated luminescence data for additional depositional age information, surface water samples and modern soil samples to constrain modern hydrological conditions, and sediment concentration data to gain insights into erosion processes. The data was generated between 2013-02 and 2018-12. The data files are provided in Excel and tab-delimited text versions.
# 4
Koellner, Nicole • Koerting, Friederike • Horning, Marcel • Mielke, Christian • Altenberger, Uwe
Abstract: The data set contains mineral chemical analyses of 20 different copper bearing minerals and their corresponding hyperspectral spectra. The hyperspectral data were acquired with the HySpex system in a range of 400 – 2500 nm and are presented in a spectral library. Detailed information about the mineral specimen, sample area and geochemistry is presented in the data sheets and associated data description. The spectral library presented here is part of a bigger collection of spectral libraries including samples from rare-earth minerals, rare-earth-oxides (Koerting et al., 2019a, http://doi.org/10.5880/GFZ.1.4.2019.004) and field samples from a copper-gold-pyrite mine in the Republic of Cyprus (Koerting et al., 2019b, http://doi.org/10.5880/GFZ.1.4.2019.005).
# 5
Koerting, Friederike • Herrmann, Sabrina • Boesche, Nina Kristin • Rogass, Christian • Mielke, Christian • (et. al.)
Abstract: The data set contains mineral chemical analyses of 32 rare earth element (REE) -bearing minerals (REMin) and rare-earth oxides (REO) and their corresponding hyperspectral spectra. The hyperspectral data was acquired with the HySpex system in a range of 400 – 2500 nm and is presented in a spectral library. The two Rare Earth Element (REE) libraries consist of the spectra of 16 rare earth oxides powders (REO) and 14 REE-bearing minerals (REMin). In addition, it contains the spectra of niobium- and tantalum oxide, two elements technically not part of the REEs. The spectral library presented here is part of a bigger collection of spectral libraries including copper-bearing surface samples from Apliki copper-gold-pyrite mine (Koerting et al., 2019a, http://doi.org/10.5880/GFZ.1.4.2019.005) and copper-bearing minerals (Koellner et al., 2019, http://doi.org/10.5880/GFZ.1.4.2019.003). These libraries aim to give a spectral overview of important resources and ore mineralization.
# 6
Koerting, Friederike • Rogass, Christian • Koellner, Nicole • Kuras, Agnieszka • Horning, Marcel • (et. al.)
Abstract: The data set contains mineral chemical analyses of 37 different surface materials from the copper-gold-pyrite mine Apliki in the Republic of Cyprus and their corresponding hyperspectral spectra. The field samples were sampled in March 2018 in cooperation of the Cyprus Geological Survey Department of the Republic of Cyprus (GSD) and the German Research Centre for Geosciences (GFZ). The hyperspectral data was acquired with the HySpex system in a range of 400 – 2500nm and is presented in a spectral library. Detailed information about the mineral specimen, sample area and geochemistry is presented in the data sheets. The spectral library presented here is part of a bigger collection of spectral libraries including samples from rare-earth minerals, rare-earth-oxides (Koerting et al., 2019a, http://doi.org/10.5880/GFZ.1.4.2019.004) and copper-bearing minerals (Koellner et al., 2019, http://doi.org/10.5880/GFZ.1.4.2019.003).
# 7
Falchi, Fabio • Cinzano, Pierantonio • Duriscoe, Dan • Kyba, Christopher C. M. • Elvidge, Christopher D. • (et. al.)
Abstract: These are maps of artificial night sky radiance that were produced by the Light Pollution Science and Technology Institute (ISTIL), and described in the paper "The New World Atlas of Artificial Night Sky Brightness" (Falchi et al. 2016). The data are stored in a 2.9 Gb geotiff file, on a 30 arcsecond grid. The map reports simulated zenith radiance data in [mcd/m^2]. The map is based on data from the VIIRS Day Night Band (DNB, MIller et al. 2013), which has been propagated through the atmosphere using the radiative transfer code reported in (Cinzano and Falchi, 2012). The upward emission function and the radiance calibration were obtained using data from Sky Quality Meters (including data from Duriscoe et al. 2007; Falchi 2010; Kyba et al 2013, 2015 and Zamorano et al. 2016). Note that the maps report artificial light only! The zenith radiance from natural sources such as stars and the Milky Way are not included, and must be added in order to match the data that would be obtained from an actual outdoor measurement. A kmz file for quick view of the data is also provided. Access to the FTP site to download the data can be requested via the data request form on the landing page. Version History:13 November 2019: change of the licence to CC BY NC 4.0 (after end of embargo period).
Artificial lights raise the night sky luminance, creating the most visible effect of light pollution, artificial sky glow. Despite the increasing interest among scientists in fields such as ecology, astronomy, healthcare, land use planning, light pollution lacks a current quantification of its magnitude on a global scale. To overcome this, here we present the World atlas of the artificial sky luminance, computed with our light pollution propagation software using new high resolution satellite data and new precision sky brightness measurements. This atlas shows that more than 80% of the World and more than 99% of the U.S.A. and Europe populations live under light polluted skies. The Milky Way is hidden for more than one third of humanity, including 60% of Europeans and nearly 80% of North Americans. Moreover, 23% of World's lands between 75°N and 60°S, 88% of Europe and almost half of U.S.A. experience light polluted nights.
# 8
Petereit, Johannes • Saynisch, Jan • Irrgang, Christopher • Thomas, Maik
Abstract: An electric current is induced by the motion of electrical conducting seawater through the ambient geomagnetic field. The periodic oceanic tidal flow induces an electric current that emits periodical time-variable electromagnetic field signals. The radial component of the ocean tide induced magnetic field signals has successfully been extracted from magnetic field observations of the satellite missions CHAMP and Swarm. It is known that the amplitudes of these electromagnetic signals are modulated by, among other influences, variations of the electrical seawater conductivity distribution of the ocean. The electrical seawater conductivity in return depends on seawater temperature and salinity. In order to analyse the influence of variations in oceanic temperature and salinity, we modelled a complete set of monthly time slices of three dimensional global complex amplitudes of these electromagnetic field signals for the years 1990 to 2016. In order to analyse solely the influence of variations in the climate sensitive seawater temperature and salinity on the ocean tide induced magnetic field signals, the influences of the secular variation of the geomagnetic field and temporal variations in ocean tide transports have been neglected. The data set is a supplement to the article of Petereit et al. (2019). The detailed method used to create this data set can be found in the data and methods section of the article and the associated data description file. Several datasets and models have been combined in order to compute the necessary models for the electrical conductivity of the Earth's surface and the ocean tide induced electric currents. These are the two main components needed for the modelling of the electromagnetic field signals that are emitted by the ocean tide induced electric currents. The model for the electrical conductivity of the Earth is composed of three components: a 1-D mantle conductivity distribution (Grayver et al., 2017), the time constant sediment conductivity (Laske & Masters, 1997) and the time-varying ocean conductivity. Ocean conductivity values were derived from a dataset of monthly global seawater temperature and salinity distributions that were derived from in-situ observations (Cabanes et al., 2013) using the TEOS-10 Toolbox (IOC, SCOR & APSO, 2010) to solve the Gibbs-seawater equation. The ocean-tide induced electric current density was computed as the vector product of the oceanic seawater conductivity, the tidal transports of the TPXO8-atlas (Egbert & Erofeeva, 2002) and ambient geomagnetic field of the IGRF-12 (Thébault et al., 2015). While, the oceanic seawater conductivity was variable in time, the tidal transports and the field strength of the ambient geomagnetic field have been kept constant.
# 9
Encarnacao, Joao • Visser, Pieter • Jaeggi, Adrian • Bezdek, Ales • Mayer-Gürr, Torsten • (et. al.)
Abstract: Although the knowledge of the gravity of the Earth has improved considerably with CHAMP, GRACE and GOCE satellite missions, the geophysical community has identified the need for the continued monitoring of its time-variable component with the purpose of estimating the hydrological and glaciological yearly cycles and long-term trends. Currently, the GRACE-FO satellites are the sole provider of this data, while previously the GRACE mission collected these data for 15 years. Between the GRACE and GRACE-FO data periods lies a gap spanning from July 2017 to May 2018, while the Swarm satellites have collected gravimetric data with its GPS receivers since December 2013. This project aims at providing high-quality gravity field models from Swarm data that constitute an alternative and independent source of gravimetric data, which could help alleviate the consequences of the 10-month gap between GRACE and GRACE-FO, as well as the short gaps in the existing GRACE and GRACE-FO monthly time series. The geodetic community has realized that the combination of the different gravity field solutions is superior to any individual model. This project exploits this fact and delivers to the highest quality monthly-independent gravity field models, resulting from the combination of 4 different gravity field estimation approaches. All solutions are unconstrained and estimated independently from month to month. Preliminary comparison with GRACE data has demonstrated that the signal in the Swarm gravity field models is restricted to degrees 12-15 and below, while the temporal correlations decrease considerably above degree 10. The 750km smoothed models are suitable to retrieve the global annual temporal variations of Earth's gravity field and the agreement with GRACE over large basins (e.g. Amazon, Congo-Zambezi, Ganges-Brahmaputra) is within 1cm RMS in terms of Equivalent Water Height. The global RMS relative to a bias, trend, an annual and semi-annual model derived from GRACE over deep ocean areas (those roughly 1000km from shorelines) is under 1mm geoid height during periods of low ionospheric activity. More information about this project can be found at https://www.researchgate.net/project/Multi-approach-gravity-field-models-from-Swarm-GPS-data and ESA's Swarm DISC (the Data, Innovation and Science Cluster) Website (https://earth.esa.int/web/guest/missions/esa-eo-missions/swarm/activities/scientific-projects/disc#MAGF). This project is funded by ESA via the Swarm DISC, Sub-Contract No. SW-CO-DTU-GS-111.
# 10
Rother, Martin • Michaelis, Ingo
Abstract: Electron density and electron temperature time series from 'LEO' satellite 'CHAMP' for the CHAMP mission period at satellite position in low time resolution of 15 second and given in daily files. This are processed readings from the Planar Langmuir probe, which, in normal flight mode, was exposed in flight direction at the front of the `CHAMP' satellite body. The files are formatted as simple 'ASCII'-listings with white-space delimited columns. The full product and format descriptions are provided in the associated Scientific Technical Report - Data (GFZ Section 2.3, 2019. http://doi.org/10.2312/GFZ.b103-19104).
CHAMP (CHAllenging Minisatellite Payload) was a German small satellite mission for geoscientific and atmospheric research and applications, managed by GFZ . With its highly precise, multifunctional and complementary payload elements (Overhauser scalar magnetometer (OVM) and Fluxgate vector magnetometer (FGM), accelerometer, star sensor (ASC), GPS receiver, laser retro reflector, ion drift meter) and its orbit characteristics (near polar, low altitude, long duration) CHAMP generated highly precise gravity and magnetic field measurements simultaneously for the first time and over a 10 years period. CHAMP launched by a Russian COSMOS launch vehicle on July 15, 2000 and an initial altitude of 454 km. The mission ended on September 19 2010 after ten years, two month and four days, or after 58277 orbits.
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