2026-04-16T08:28:02Zhttp://doidb.wdc-terra.org/oaip/oai

oai:doidb.wdc-terra.org:62442017-01-16T11:33:59ZDOIDBDOIDB.SDDB

false3DOIDB.SDDB 10.5880/ICDP.5054.001 Hierold, Johannes GFZ German Research Centre for Geosciences, Potsdam, Germany Körting, Friederike GFZ German Research Centre for Geosciences, Potsdam, Germany Kollaske, Tina Bundesanstalt für Geowissenschaften und Rohstoffe, Berlin, Germany Rogass, Christian GFZ German Research Centre for Geosciences, Potsdam, Germany Harms, Ulrich GFZ German Research Centre for Geosciences, Potsdam, Germany Analysis of element behavior in mylonites of the Seve Nappe of the Scandinavian Caledonides using different core scanning methods (Datasets) GFZ Data Services 2016 caledonides COSC deep hydrosphere dynamics europe heat flow himalaya ICDP-2011/03 microbiology norway orogen scandes scandinavia seismic sweden XRF LIBS Hyperspectral Analysis Hierold, Johannes GFZ German Research Centre for Geosciences, Potsdam, Germany Hierold, Johannes GFZ German Research Centre for Geosciences, Potsdam, Germany /2017-03-01 2016-02-16 2013-09-05/2014-10-11 eng Dataset 10273/ICDP5054EHW1001 10.2312/ICDP.5054.001 10.1594/GFZ.SDDB.ICDP.5054.2015 10.2312/ICDP.2015.002 10.5194/sd-19-1-2015 10.2312/GFZ.b103-16070 1063435999 Bytes 4 Files application/zip application/x-zip-compressed application/x-zip-compressed application/zip CC BY 4.0 The International Continental Scientific Drilling Program (ICDP) performed a dual-phase scientific drilling project to investigate mountain-building processes called Collisional Orogeny in the Scandinavian Caledonides (COSC). The borehole COSC-1 was drilled through the Lower Seve Nappe, as the first of two 2.5 km deep drill holes close to Åre, central Sweden. The recovered rocks comprise a 1650 m thick suite of high grade gneisses and amphibolites with clear Seve Nappe affinities, while the lower 850 m comprise rather homogenous mylonitic gneisses with interfingered K-rich phyllonite bands of cm to several m size and some intercalated amphibolites. The different lithologies all crosscut the core in a subhorizontal direction with foliation of gneisses and phyllonites in the same direction. Albite and garnet porphyroblasts with pressure shadows show syn-deformational growth and the same sub-horizontal alignment. The focus of this study was to detect chemical and mineralogical differences in mylonitic and host rocks and to relate these differences to either metasomatism and deformation or inherited source rock variance. Another goal of this work is to compare chemical core scanning instruments. For this purpose two different X-Ray Fluorescence (XRF) techniques, Laser Induced Breakdown Spectroscopy (LIBS) and hyperspectral imaging served to measure seven samples from the lower 850 m of the COSC-1 core. This data publication comprises the datasets gained in the course of this study. The metadata (OF WHAT?) will be presented in an additional file including XRF data from the Avaatech XRF core scanner in a txt.file as well as datasets of the other used devices in original file formats. 63.4063 13.203057 Åre, Jämtlands län, Sweden

oai:doidb.wdc-terra.org:62202017-04-27T16:14:12ZDOIDBDOIDB.GFZ

false3DOIDB.GFZ 10.5880/GFZ.2.1.2016.002 Richter, Nicole GFZ German Research Centre for Geosciences, Potsdam, Germany Nikkhoo, Mehdi GFZ German Research Centre for Geosciences, Potsdam, Germany de Zeeuw-van Dalfsen, Elske GFZ German Research Centre for Geosciences, Potsdam, Germany Walter, Thomas. R. GFZ German Research Centre for Geosciences, Potsdam, Germany Terrestrial laser scanner data covering the summit craters of Láscar Volcano, Chile GFZ Data Services 2016 Lascar Volcano Terrestrial Laser Scanner (TLS) Geomorphology Nested craters eng Dataset 10.1016/j.jvolgeores.2016.09.018 10.1080/01431160903154416 http://seal.web.cern.ch/seal/documents/minuit/mnusersguide.pdf 56055973 Bytes 2 Files application/pdf application/x-zip-compressed CC BY 4.0 The datasets included in this data publication are: (1) the TLS combined point cloud (consisting of ∼15 million data points), (2) a Digital Elevation Model (DEM) with 1 m pixel spacing which was generated from (1), and (3) a shaded relief of (2) in kmz format. These datasets are supplement to de Zeeuw-van Dalfsen et al. (2017), who used them to study structural and geomorphological features at the nested summit craters of Láscar Volcano, Chile. However, in the paper the data were used in a local reference frame while we here provide both the TLS point cloud and the DEM product in global coordinates (WGS 1984 UTM Zone 19 South). Light detection and ranging (LiDAR) is a technique where a laser pulse is actively emitted from a LiDAR instrument and the echo that returns from a target object is recorded. The distances between the instrument and the target points are calculated from the round-trip travel time of the laser pulse (Fornaciai et al., 2010). A terrestrial laser scanner (TLS) uses this technique in a scanning mode where the laser beam is deflected into different directions by an oscillating mirror while at the same time the scanner’s head is rotating. We used a long-range RIEGL LMS-Z620 instrument with a field of view of up to 80° by 360° in the vertical and horizontal plane, respectively. The maximum repeatability of this instrument is 5 mm, but this value increases with increasing distance between the scanner and the target, when viewing geometries or the target reflectivity are not optimal or when atmospheric conditions vary and are not ideal. From the acquired 3D point cloud topographic details can be retrieved over a maximum distance of 2 km. However, newer instruments can reach distances of 6 km or more. Georeferencing (local coordinate system) In total, four TLS scans were acquired on two days in November 2013 (two at each day to overcome shadowing effects). The two point clouds from each view point were combined using tie points, i.e. reflectors that were placed in the field, and the RiSCAN Pro Software (http://www.riegl.com). For the two point clouds from day 1, we achieved a standard deviation of 0.0023 m using 6 tie points, while for the two point clouds acquired on day 2 we reached a standard deviation of 0.0052 m using 3 tie points. In addition to the TLS measurement, the reflectors’ positions were also measured using a total station. This additional data allowed us to 1) orientate each of the two point clouds to a local geodetic reference frame in the XY plane using a 3D affine transformation with a remaining RMSE of ∼1 cm and 2) estimate the orientation about Z and the full translation parameters using hand-held GPS coordinates of a common point and the individual tie points. Following this procedure we produced a combined point cloud of all four TLS scans in a local geodetic reference frame. Georeferencing (global coordinate system) In order to derive the coordinates of the TLS point cloud in a global coordinate system, we used the open-source software Minuit2 5.18/00 which was developed at CERN (James and Winkler, 2004 and references therein). This tool finds the minimum value of multi-parameter functions and was in our case employed to find the minimum root mean square residuals (in elevation) between the TLS point clouds and a reference DEM featuring a 1 m pixel spacing that was calculated from tri-stereo optical Pléiades-1 satellite imagery. When applying this minimization technique, the data are transferred to the same coordinate system as the reference data (WGS 1984 UTM Zone 19 South). In a first step, we minimized the two TLS point clouds from the two different acquisition dates separately. We masked out areas from the Pléiades reference DEM that we know are very different when compared to the TLS point data. For instance, areas along the steep crater walls are interpolated to a high degree in the Pléiades DEM, while the scanner-facing crater walls are expected to have comparably precise point values in the TLS dataset. Thereafter, we combined the TLS point clouds and ran another Minuit RMSE minimization onto the masked Pléiades DEM. -23.3667 -67.7333

oai:doidb.wdc-terra.org:62412017-09-15T11:25:13ZDOIDBDOIDB.GFZ

false3DOIDB.GFZ 10.5880/GFZ.2.1.2016.001 Richter, Nicole GFZ German Research Centre for Geosciences, Potsdam Favalli, Massimiliano Istituto Nazionale di Geofisica e Vulcanologia (INGV), Pisa de Zeeuw-van Dalfsen, Elske GFZ German Research Centre for Geosciences, Potsdam Fornaciai, Alessandro Istituto Nazionale di Geofisica e Vulcanologia (INGV), Pisa, Dipartimento di Fisica e Astronomia (DIFA), Alma Mater Studiorum – Università di Bologna, Bologna da Silva Fernandes, Rui Manuel Instituto D. Luiz, University of Beira Interior, Covilhã Pérez, Nemesio M. Instituto Volcanológico de Canarias (INVOLCAN), Puerto de la Cruz, Instituto Tecnológico y de Energías Renovables (ITER), Granadilla de Abona Levy, Judith GFZ German Research Centre for Geosciences, Potsdam Silva Victória, Sónia Universidade de Cabo Verde, Praia, Cabo Verde Walter, Thomas R. GFZ German Research Centre for Geosciences, Potsdam A post-2015 lava flow hazard map for Fogo Volcano, Cabo Verde GFZ Data Services 2016 en 10.5194/nhess-16-1925-2016 10.5194/nhess-16-1925-2016-supplement 39518743 Bytes 2 Files application/pdf application/pdf CC BY 4.0 We provide an updated lava flow hazard map for Fogo Volcano, Cabo Verde that is valid after the 2014-2015 eruptive crises. The hazard map shows the probability of lava flow invasion within the Chã das Caldeiras and on the eastern flank of the volcano. This probability is defined as the likelihood that a future lava flow will inundate a specific point before the vent location is known. The hazard map is calculated on the basis of a 5 m resolution digital elevation model generated from contours on the base of photogrammetric data that was updated for the 2014-2015 lava flow using combined terrestrial laser scanner (TLS) and camera data. The lava flow hazard map in printable A0 poster format is available in two versions, an English-Kreolu version (blue) and an English-Portugese version (green). Please refer to Richter et al. (2016) for more information and scientific background, as well as for supplementary material in kml format. 14.812060061226388 -24.514617919921875 15.056210365453422 -24.2742919921875 Foco Island, Capo Verdean Archipelago

oai:doidb.wdc-terra.org:65842018-12-10T16:08:13ZDOIDBDOIDB.FID

false4DOIDB.FID 10.5880/fidgeo.2018.016 Siegert, Susann Susann Siegert 0000-0002-4157-863X Museum für Naturkunde - Leibniz Institute for Evolution and Biodiversity Science, Berlin, Germany Hecht, Lutz Lutz Hecht 0000-0001-8904-0217 Museum für Naturkunde - Leibniz Institute for Evolution and Biodiversity Science, Berlin, Germany Geochemical data of impactites of the Ries impact structure, Germany GFZ Data Services 2018 Ries impact crater geochemistry melt-brearing impact breccia suevite impact melt breccia impact melt bomb electron microprobe analysis laser ablation ICP-MS X-ray fluorescence ICP-MS ICP-AES Siegert, Susann Susann Siegert 0000-0002-4157-863X Museum für Naturkunde - Leibniz Institute for Evolution and Biodiversity Science, Berlin, Germany Hecht, Lutz Lutz Hecht 0000-0001-8904-0217 Museum für Naturkunde - Leibniz Institute for Evolution and Biodiversity Science, Berlin, Germany en 10.1111/maps.13210 10.1046/j.1365-2494.1998.53202081.x-i1 10.1111/j.1751-908X.1980.tb00273.x 10.1111/j.1751-908X.2011.00120.x 10.1111/maps.12087 10.1111/maps.12086 6313516 Bytes 3 Files application/x-zip-compressed application/pdf application/vnd.openxmlformats-officedocument.spreadsheetml.sheet CC BY 4.0 The Ries impact structure in Southern Germany is one of the best-preserved impact structures on Earth. Melt-bearing impact breccia appears in a variety of well accessible exposures around the inner ring up to 10 km beyond the crater rim (so-called outer suevite) overlying a ballistically ejected lithic breccia (so-called ‘Bunte Breccia’). Occasionally individual melt bombs occur in the ‘Bunte Breccia’. Coherent impact melt rock outside the inner crater is located in the eastern megablock zone (Stöffler et al., 2013 and references therein). This data set comprises major and trace element geochemistry of samples from eight outer suevite exposures, one impact melt rock exposure, and one melt bomb of the Ries impact crater. Two analytical method approaches were performed: i) in-situ analysis using electron microprobe (EMP) and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), and ii) analysis of whole-rock, melt separates, and suevite matrix separates using X-ray fluorescence (XRF), and inductively coupled plasma atomic emission spectroscopy (ICP-AES)/ inductively coupled plasma mass spectrometry (ICP-MS). 10.557469238760063 48.88667960100579

oai:doidb.wdc-terra.org:65662019-03-23T10:01:00ZDOIDBDOIDB.GFZ

false4DOIDB.GFZ 10.5880/GFZ.3.3.2018.002 Frick, Daniel A. Daniel A. Frick 0000-0002-8530-3064 GFZ German Research Centre for Geosciences, Potsdam, Germany Schuessler, Jan A. Jan A. Schuessler 15726782000 GFZ German Research Centre for Geosciences, Potsdam, Germany Sommer, Michael Michael Sommer 55671655600 Leibniz-Centre for Agricultural Landscape Research (ZALF) e. V., Müncheberg, Germany University of Potsdam, Institute of Earth and Environmental Sciences, Potsdam, Germany von Blanckenburg, Friedhelm Friedhelm von Blanckenburg 0000-0002-2964-717X GFZ German Research Centre for Geosciences, and GFZ German Research Centre for Geosciences, Potsdam, Germany Freie Universität Berlin, Institute of Geological Sciences, Berlin, Germany Data supplement to: Laser ablation in situ silicon stable isotope analysis of phytoliths GFZ Data Services 2018 In-situ silicon isotope ratios analysis phytolith laser ablation inductively coupled plasma mass spectrometry biogenic silica en 10.1111/ggr.12243 10.1016/j.sab.2014.05.002 758605 Bytes 4 Files application/vnd.openxmlformats-officedocument.spreadsheetml.sheet application/pdf application/vnd.ms-excel application/pdf CC BY 4.0 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. Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung http://doi.org/10.13039/501100001711 P2EZP2-168836 In situ Ge/Si and d30Si determination in phytoliths – advancing laser ablation ICP-MS techniques to analyse novel biogeochemical weathering archives

oai:doidb.wdc-terra.org:67552019-11-14T13:28:12ZDOIDBDOIDB.CRC1211

false4DOIDB.CRC1211 10.5880/CRC1211DB.30 Kuiper, Klaudia Klaudia Kuiper Vrije Universiteit Amsterdam, Department of Earth Science Medialdea, Alicia Alicia Medialdea University of Cologne, Institute of Geography May, Matthias Matthias May University of Cologne, Institute of Geography Brill, Dominik Dominik Brill University of Cologne, Institute of Geography King, Georgina Georgina King University of Cologne, Institute of Geography Wennrich, Volker Volker Wennrich University of Cologne, Institute of Geology and Mineralogy CRC1211 Database (CRC1211DB) 2019 Dating Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659 CRC 1211 Earth - Evolution at the Dry Limit 2019-11-12 English 1 Analytical data of Ar/Ar sanidine dating of tephra SALAR T6 (20°59.862'S, 70°01.630'W). Sample was collected from Salar Grande site during the field campaign of March 2017. These data compliment and support the results presented in the journal article "Identification of humid periods in the Atacama Desert through hillslope activity established by infrared stimulated luminescence (IRSL) dating". Medialdea et al., 2019. Global and Planetary Change. Volcanic horizon T6 was processed for using standard mineral separation procedures. After crushing and washing, heavy liquid mineral separation with densities of 2.54 and 2.59 g/cm3 was performed to obtain the sanidine from the sample. Mineral fractions were further purified by hand-picking under an optical microscope. The selected mineral separate was packed in a 6 mm ID AI packages and loaded together with Fish Canyon Tuff sanidine (FCs) standard in a 25 mm ID Al cup. Sample and standard were irradiated at the Oregon State University TRIGA reactor in the cadmium shielded CLICIT facility for 7 hours (irradiation code VU114). After irradiation, samples and standards were unpacked and loaded in a 185 hole Cu tray and baked overnight at 250 °C under vacuum. This tray was then placed in a doubly pumped vacuum chamber with Zn-Se window and baked overnight at 120 °C under high vacuum. This chamber was connected to a ThermoFisher NGPrep gas purification line equipped with a hot GP50, a cold finger (Lauda at -70 °C) and hot St707 getter. Sample (1-3 grains/fusion) and standards (1 grain/fusion) were fused using a 25W Synrad CO2 laser. Released gas was analysed on an ARGUS VI+ noble gas mass spectrometer at the Vrije Universiteit Amsterdam, The Netherlands, equipped with four Faraday cups at the H2, H1, AX and L1 positions and two compact discrete dynodes (CDDs) at positions L2 and L3. The system was equipped with a 1012 Ohm amplifier on H2 and 1013 Ohm amplifiers on H1, AX and L1 cups. Samples were run on H1-L3 collectors. Similar to Phillips and Matchan (2013) we did not apply bias corrections, but analysed samples and standards in the same tray (and thus at more or less the same time) alternating with air pipettes with intensities in the same range as the samples and standards. Line blanks were measured every 2-3 unknowns and were subtracted from succeeding sample data. Data reduction is done in ArArCalc (Koppers, 2002). Ages are calculated with decay constants from Min et al., 2000 and 28.201 Ma for FCs (Kuiper et al., 2008). The atmospheric 40Ar/36Ar air value of 298.56 is used (Lee et al., 2006). The correction factors for neutron interference reactions are (2.64 ± 0.02) x10-4 for (36Ar/37Ar)Ca, (6.73 ± 0.04) x10-4 for (39Ar/37Ar)Ca, (1.21 ± 0.003) x10-2 for (38Ar/39Ar)K and (8.6 ± 0.7) x10-4 for (40Ar/39Ar)K. Full analytical data is included in the table. Chile -70.02738 -70.02738 -20.99751 -20.99751

oai:doidb.wdc-terra.org:68152020-03-02T11:39:42ZDOIDBDOIDB.FID

false4DOIDB.FID 10.5880/fidgeo.2020.007 Ohl, Markus Markus Ohl 0000-0002-8135-1915 Utrecht University Plümper, Oliver Oliver Plümper 0000-0001-9726-0885 Utrecht University Chatzaras, Vasileios Vasileios Chatzaras 0000-0001-9759-4754 The University of Sydney Wallis, David David Wallis 0000-0001-9212-3734 Utrecht University Vollmer, Christian Christian Vollmer 0000-0002-7768-7651 Westfälische Wilhelms-Universität Münster Drury, Martyn Martyn Drury 0000-0002-2246-2009 Utrecht University Nanoscale structures and properties of carbonate fault mirrors revealed by scanning electron and scanning transmission electron microscope images, electron energy loss and Raman spectra GFZ Data Services 2020 Nanogeoscience decarbonation calcite deformation earthquakes carbon hybridisation electron microscopy EARTH SCIENCE > SOLID EARTH > TECTONICS > PLATE TECTONICS > PLATE BOUNDARIES EARTH SCIENCE > SOLID EARTH > TECTONICS > PLATE TECTONICS > FAULT MOVEMENT EARTH SCIENCE > SOLID EARTH > TECTONICS > EARTHQUAKES > EARTHQUAKE OCCURRENCES EARTH SCIENCE > SOLID EARTH > ROCKS/MINERALS/CRYSTALS > MINERALS > MINERAL FORMATION Ohl, Markus Markus Ohl 0000-0002-8135-1915 Utrecht University Ohl, Markus Markus Ohl 0000-0002-8135-1915 Utrecht University Ohl, Markus Markus Ohl 0000-0002-8135-1915 Utrecht University Plümper, Oliver Oliver Plümper 0000-0001-9726-0885 Utrecht University Plümper, Oliver Oliver Plümper 0000-0001-9726-0885 Utrecht University Chatzaras, Vasileios Vasileios Chatzaras 0000-0001-9759-4754 The University of Sydney Wallis, David David Wallis 0000-0001-9212-3734 Utrecht University Vollmer, Christian Christian Vollmer 0000-0002-7768-7651 Westfälische Wilhelms-Universität Münster Vollmer, Christian Christian Vollmer 0000-0002-7768-7651 Westfälische Wilhelms-Universität Münster Drury, Martyn Martyn Drury 0000-0002-2246-2009 Utrecht University Drury, Martyn Martyn Drury 0000-0002-2246-2009 Utrecht University 2020-01-20 en 10.1016/j.epsl.2019.115886 3 Files application/octet-stream application/octet-stream application/octet-stream major CC BY 4.0 This data publication contains scanning electron microscope (SEM) and (scanning) transmission electron microscope ((S)TEM) images as well as electron energy loss spectra (EELS) and Raman spectra of the principal slip surface of carbonate fault mirrors. We analysed a total of eleven samples to investigate the formation mechanisms of fault mirrors in carbonates. The samples were taken as drill cores in Central Greece from two different outcrop locations. The first location, close to Arkitsa, is a large anthropogenic outcrop exposing three large fault planes. The second location is close to Schinos and was also formed by human interaction at the side of a gravel road. The data set contains supplemental material to the publication "Mechanisms of fault mirror formation and fault healing in carbonate rocks" by Ohl et al., (2020). In addition to the electron microscopy images we provide the spectra files of the Raman and EELS measurements for the identification of the carbon species in relation to the principal slip surface. The publication concludes that decarbonation of calcite during fault slip and the subsequent reaction of the decarbonation products produces fault mirror surfaces. Post-seismic hybridization of carbon results in partly-hybridised amorphous carbon and contributes to connecting hanging wall and footwall. In addition, post-seismic carbonation of portlandite produces secondary nano-sized calcite crystals < 50 nm facilitating fault healing. The SEM images were acquired on an FEI Helios Nanolab G3 DualBeam focused ion beam scanning electron microscope (FIB-SEM). For the preparation of TEM foils, prior to ion-beam deposition of platinum, a 200-nm layer of platinum was deposited by electron-beam precipitation. TEM imaging was carried out with an FEI Talos F200X at 200 kV acceleration voltage and 5 – 10 nA beam current. Electron imaging was done at the Utrecht University electron microscope center, The Netherlands. EELS data was acquired using a Zeiss Libra 200FE at 200kV with an in-column Omega energy filter at the Westfälische Wilhelms-Universität (WWU) in Münster. The energy resolution of the EELS analyses was 0.7 eV, measured at the full width at half maximum (FWHM) of the zero-loss peak. Energy loss spectra were obtained at 250,000× magnification with a 100 μm filter-entrance aperture giving an effective aperture of about 40 nm on the sample. Raman spectroscopy was carried out using a WiTec ALPHA300R confocal microscope and a 532-nm wavelength laser and a spectrometer grating of 600 grooves/cm. This data publication consists of SEM and (S)TEM images organized in folders named Figure X, where X is the number of the supplemental figure referred to in Ohl et al. (2020). The contents of these folders are described in the 2020-007_Ohl-2020-List_of_files.xls. In addition, the untreated Raman spectroscopy and electron energy loss spectroscopy spectra are provided as tab-separated files containing the XY coordinates for Arkitsa and Schinos. For the Raman spectroscopy measurements, the first column is the wavenumber shift in [rel. cm-1] and the second column refers to counts per second [cts/s] acquired on the spectrometer. In case of the EELS measurements, the first column is the electron energy loss in [eV] and the second column represents the intensity in counts per second [cts/s] on the CCD camera. 23.008158237599446 38.732134982040606 23.00607223457473 38.03728865238465 Nederlandse Organisatie voor Wetenschappelijk Onderzoek http://doi.org/10.13039/501100003246 ALWOP.2015.082

oai:doidb.wdc-terra.org:67062020-04-07T10:10:04ZDOIDBDOIDB.FID

false4DOIDB.FID 10.5880/FIDGEO.2018.070 Neuper, Malte Malte Neuper Karlsruhe Institute of Technology (KIT) - Institute for Water and River Basin Management - Chair of Hydrology, Karlsruhe, Germany Ehret, Uwe Uwe Ehret 0000-0003-3454-8755 Karlsruhe Institute of Technology (KIT) - Institute for Water and River Basin Management - Chair of Hydrology, Karlsruhe, Germany CAOS rain rate and reflectivity data set of 6 disdrometres and 2 micro rain radars at 3 different heights at 6 stations in the Attert catchment, Luxembourg from Oct 2012 - Sept 2016 GFZ Data Services 2018 disdrometer MRR micro rain radar reflectivity Radar meteorology quantitative precipitation estimation QPE CAOS Luxembourg Attert drop size distribution DSD Catchment as organized systems KIT Karlsruhe Institute of Technology Hydrology Meteorology Radar rain rate on average to the ground directed hydrometeor fluxes atmosphere In Situ/Laboratory Instruments > Gauges > RAIN GAUGES EARTH SCIENCE > ATMOSPHERE > PRECIPITATION > PRECIPITATION RATE EARTH SCIENCE > ATMOSPHERE > PRECIPITATION > PRECIPITATION AMOUNT Neuper, Malte Malte Neuper Karlsruhe Institute of Technology (KIT) - Institute for Water and River Basin Management - Chair of Hydrology, Karlsruhe, Germany Neuper, Malte Malte Neuper Karlsruhe Institute of Technology (KIT) - Institute for Water and River Basin Management - Chair of Hydrology, Karlsruhe, Germany Neuper, Malte Malte Neuper Karlsruhe Institute of Technology (KIT) - Institute for Water and River Basin Management - Chair of Hydrology, Karlsruhe, Germany Neuper, Malte Malte Neuper Karlsruhe Institute of Technology (KIT) - Institute for Water and River Basin Management - Chair of Hydrology, Karlsruhe, Germany Neuper, Malte Malte Neuper Karlsruhe Institute of Technology (KIT) - Institute for Water and River Basin Management - Chair of Hydrology, Karlsruhe, Germany Ehret, Uwe Uwe Ehret 0000-0003-3454-8755 Karlsruhe Institute of Technology (KIT) - Institute for Water and River Basin Management - Chair of Hydrology, Karlsruhe, Germany Ehret, Uwe Uwe Ehret 0000-0003-3454-8755 Karlsruhe Institute of Technology (KIT) - Institute for Water and River Basin Management - Chair of Hydrology, Karlsruhe, Germany Ehret, Uwe Uwe Ehret 0000-0003-3454-8755 Karlsruhe Institute of Technology (KIT) - Institute for Water and River Basin Management - Chair of Hydrology, Karlsruhe, Germany Ehret, Uwe Uwe Ehret 0000-0003-3454-8755 Karlsruhe Institute of Technology (KIT) - Institute for Water and River Basin Management - Chair of Hydrology, Karlsruhe, Germany 2018-02-19 2012-10-01/2016-09-30T23:00:00 en 10.5194/hess-2018-606 1 Files application/octet-stream CC BY 4.0 The dataset consist of time series of hourly rain rates and mean radar reflectivity factor (herein after referred to as reflectivity) near the ground, 100 meter and 1500 meter above the ground at six locations in the Attert catchment in Luxembourg. The time series cover a time span of 4 years (from the 1st of October 2012 tor the 30th of September 2016). The dataset was derived from drop size measurements we conducted at six stations with six laser optical disdrometers and two micro rain radars (MRR) within the CAOS Project (DFG Research Group: From Catchments as Organized Systems to Models based on Functional Units (FOR 1598). The time series of rain rates and radar reflectivity factors (reflectivities) were calculated (derived) via the 3.5th and 6th statistical moments of the drop size distributions using the particular raw data of drop sizes and fall velocities. The primary reason for the measurements was to improve radar based quantitative precipitation estimation in general and the conversion of the reflectivity Z (measured by operational weather radar) to a rain rate R at the ground via the so-called Z-R relation within a mesoscale catchment. GENERAL CONVENTIONS:• Time extent: 1.10.2012 00:00 – 30.09.2016 23:00 (35064 values)• Time reference: UTC • Time stamp: end• Time resolution: 1h• Time series are equidistant and gapless• Missing values: NaN• Delimiter: ; (semicolon)• decimal separator: . (point) STATION LOCATIONS:Name; Abbreviation; Latitude (WGS-84); Longitude(WGS-84); height a.s.l; InstrumentationOberpallen;OPA; 49.73201°; 5.84712°;287 m; disdrometer Useldange;USL; 49.76738°; 5.96756°; 280 m; disdrometer and MRR Ell;ELL; 49.76558°; 5.84401°; 290 m; disdrometer Post;POS; 49.75394°; 5.75481°; 345 m; disdrometer Petit-Nobressart;PIN; 49.77938°; 5.80526°; 374 m; disdrometer and MRR Hostert-Folschette;HOF; 49.81267°; 5.87008°; 435 m; disdrometer HEADER – VARIABLES DESCRIPTION:Name - description:Date-UTC – Date as yyyy-mm-dd HH:MM (4 digit year-2 digit month – 2 digit day 2 digit hour: 2 digit minute)Time Zone: UTC. Decade – tenner day of the year (that is 1st to 10th of January = 1 ; 11th to 20th of January = 2 ; 21th to 30th of January = 3 ; … 21st to 31st of December = 36.Month – Month of the year (1: January, 2: February, 3:March,…, 12: December).dBZ0_DIS_ELL – reflectivity at ground level (in dBZ) at the station Ell derived from disdrometer measurements.dBZ0_DIS_HOF – reflectivity at ground level (in dBZ) at the station Hostert-Folschette derived from disdrometer measurements.dBZ0_DIS_OPA – reflectivity at ground level (in dBZ) at the station Oberpallen derived from disdrometer measurements.dBZ0_DIS_PIN – reflectivity at ground level (in dBZ) at the station Petit-Nobressart derived from disdrometer measurements.dBZ0_DIS_POS – reflectivity at ground level (in dBZ) at the station Post derived from disdrometer measurements.dBZ0_DIS_USL – reflectivity at ground level (in dBZ) at the station Useldange derived from disdrometer measurements.dBZ100_MRR_PIN – reflectivity 100 m above ground (in dBZ) at the station Petit-Nobressart derived from MRR measurements.dBZ100_MRR_USL – reflectivity 100 m above ground (in dBZ) at the station Useldange derived from MRR measurements.dBZ1500_MRR_PIN – reflectivity 1500 m above ground (in dBZ) at the station Petit-Nobressart derived from MRR measurements.dBZ1500_MRR_USL – reflectivity 1500 m above ground (in dBZ) at the station Useldange derived from MRR measurements.RR0_DIS_ELL – rain rate at ground level (in mm/h) at the station Ell derived from disdrometer measurements.RR0_DIS_HOF – rain rate at ground level (in mm/h) at the station Hostert-Folschette derived from disdrometer measurements.RR0_DIS_OPA – rain rate at ground level (in mm/h) at the station Oberpallen derived from disdrometer measurements.RR0_DIS_PIN– rain rate at ground level (in mm/h) at the station Petit-Nobressart derived from disdrometer measurements.RR0_DIS_POS – rain rate at ground level (in mm/h) at the station Post derived from disdrometer measurements.RR0_DIS_USL – rain rate at ground level (in mm/h) at the station Useldange derived from disdrometer measurements.RR100_MRR_PIN – rain rate 100 m above ground (in mm/h) at the station Petit-Nobressart derived from MRR measurements.RR100_MRR_USL – rain rate 100 m above ground (in mm/h) at the station Useldange derived from MRR measurements.RR1500_MRR_PIN – rain rate 1500 m above ground (in mm/h) at the station Petit-Nobressart derived from MRR measurements.RR1500_MRR_USL – rain rate 1500 m above ground (in mm/h) at the station Useldange derived from MRR measurements. The instruments were maintained and cleaned monthly. The data was quality checked. Cases with solid precipitation were excluded using the output form the Pasivel² present weather sensor software, which especially was needed since disdrometer data was contaminated by cobwebs. But since the present weather analyzer classified these (due to their slow movement within the wind) as snow, these then could easily be eliminated. DISDROMETER:We deployed six second generation OTT Particle Size and Velocity (PARSIVEL², see Löffler-Mang and Joss, 2000 - https://doi.org/10.1175/1520-0426(2000)017<0130:AODFMS>2.0.CO;2) optical disdrometers in the study area to measure drop size distributions at ground level in 1-minute resolution. Two were located at the same sites as the MRRs (Useldange and Petit-Nobressart). The others were placed such as to both capture the hydroclimatic variations in the study area and to cover it as uniformly as possible. We applied a quality control to the raw data as described by Friedrich et al. (2013 - https://doi.org/10.1175/JTECH-D-12-00254.1 and https://doi.org/10.1175/MWR-D-12-00116.1 ), converted the filtered data to drop-size concentrations per unit air volume to make them comparable to weather radar and MRR data, then converted them to reflectivity and rain rate using the 3.5th and 6th statistical moments of the drop size distributions and finally took 1-hour averages and sums thereof. MRR: From two vertical pointing K-band METEK micro rain radars (MRR) (Löffler-Mang et al. 1999 - https://doi.org/10.1175/1520-0426(1999)016<0379:OTPOAL>2.0.CO;2 and Peters et al. 2002 - Rain observations with a vertically looking Micro Rain Radar (MRR). Boreal Env. Res. 7: 353–362, 2002) measurements located at the sites Useldange and Petit-Nobressart drop size spectra were retrieved at 1500 meter and 100 meter above ground . We operated the MRR's at 100 vertical meters and 10 seconds temporal resolution, but for reasons of storage and processing efficiency did all further processing on 1-minute aggregations thereof. The raw Doppler spectra were transformed to drop size distributions via the drop size – fall velocity relation given in Atlas et al (1973 - https://doi.org/10.1029/RG011i001p00001). From the drop size distributions the rain rate and the reflectivity were calculated using the 3.5th and the 6th statistical moments of the drop size distributions. In doing so we assumed the vertical velocity of the air to be negligible. 5.668803125140585 6.06568422865621 49.698716522795124 49.889316007224735 Attert catchment, Luxembourg during the project phase of the CAOS Project (DFG Research Group: From Catchments as Organised Systems to Models based on Functional Units (FOR 1598) from 2012 to 2016 Deutsche Forschungsgemeinschaft http://doi.org/10.13039/501100001659

oai:doidb.wdc-terra.org:69202020-09-16T08:25:00ZDOIDBDOIDB.IGETS

false4DOIDB.IGETS 10.5880/igets.ru.l1.001 Boy, Jean-Paul Jean-Paul Boy 0000-0003-0259-209X INSU/EOST, Strasbourg, France Rosat, Séverine Séverine Rosat 0000-0003-4606-2170 INSU/EOST, Strasbourg, France Hinderer, Jacques Jacques Hinderer 0000-0003-3630-8077 INSU/EOST, Strasbourg, France Gaffet, Stéphane Stéphane Gaffet INSU/LSBB, Rustrel, France Littel, Frédéric Frédéric Littel INSU/EOST, Strasbourg, France GFZ Data Services 2020 Superconducting gravimetry Earth tides Geodynamics IGETS International Geodynamics and Earth Tide Service EARTH SCIENCE > SOLID EARTH > GRAVITY/GRAVITATIONAL FIELD > GRAVITY geodesy geophysics hydrology Boy, Jean-Paul Jean-Paul Boy 0000-0003-0259-209X INSU/EOST, Strasbourg, France Boy, Jean-Paul Jean-Paul Boy 0000-0003-0259-209X INSU/EOST, Strasbourg, France Rosat, Séverine Séverine Rosat 0000-0003-4606-2170 INSU/EOST, Strasbourg, France Hinderer, Jacques Jacques Hinderer 0000-0003-3630-8077 INSU/EOST, Strasbourg, France Gaffet, Stéphane Stéphane Gaffet INSU/LSBB, Rustrel, France Littel, Frédéric Frédéric Littel INSU/EOST, Strasbourg, France Voigt, Christian Christian Voigt 0000-0002-9988-965X GFZ German Research Centre for Geosciences, Potsdam, Germany Boy, Jean-Paul EOST/IPGS, 5 rue René Descartes, 67084 Strasbourg Cedex, France 2015-10-01 Dataset 10.1051/e3sconf/20198803001 10.1051/e3sconf/20161206003 10.1016/j.jog.2018.05.009 10.2312/GFZ.b103-16087 CC BY 4.0 The International Geodynamics and Earth Tide Service (IGETS) was established in 2015 by the International Association of Geodesy. IGETS continues the activities of the Global Geodynamics Project (GGP) between 1997 and 2015 to provide support to geodetic and geophysical research activities using superconducting gravimeter (SG) data within the context of an international network.

As part of this network, the Rustrel station (code RU) was established in 2015 thanks to the financial support of the EQUIPEX MIGA (Matter wave-laser based Interferometer Gravitation Antenna) ANR-11-EQPX-0028 and by the European FEDER 2006-2013 “PFM LSBB - Développement des qualités environnementales du LSBB”. Continuous time-varying gravity and atmospheric pressure data from RU are integrated in the IGETS data base hosted by ISDC (Information System and Data Centre) at GFZ.

The operation and maintenance of the RU instrumentation is done by staff at EOST/IPG Strasbourg. The RU station is located about 500 m beneath the surface in the underground research laboratory of the LSBB (« Laboratoire Souterrain à Bas Bruit ») built in 1997. The LSBB is located within the Regional Natural Park of Luberon (longitude: 5.4837 E, latitude: 43.9411 N, height above MSL: 499.3 m).

The LSBB gallery is located in the unsaturated zone of the Fontaine de Vaucluse karst hydrosystem. There is no industry around the site so the anthropogenic noise is very low. The time series of gravity and barometric pressure from iOSG-24 starts in October 2015 and is going on. The time sampling of the raw gravity and barometric pressure data of IGETS Level 1 is 1 minute. For a detailed description of the IGETS data base and the provided files see Voigt et al. (2016, https://doi.org/10.2312/GFZ.b103-16087).

Rustrel (LSBB) station: raw gravity and atmospheric pressure from OSG 024 - IGETS Level 1

oai:doidb.wdc-terra.org:66772020-09-26T12:19:02ZDOIDBDOIDB.FID

false4DOIDB.FID 10.5880/fidgeo.2019.005 Schimmel, Mariska Mariska Schimmel 0000-0002-9854-0552 Utrecht University, The Netherlands Hangx, Suzanne Suzanne Hangx 0000-0003-2253-3273 Utrecht University, The Netherlands Spiers, Chris Chris Spiers 0000-0002-3436-8941 Utrecht University, The Netherlands Compaction creep data uniaxial compaction of quartz sand in various chemical environments GFZ Data Services 2019 compaction creep quartz sand fluid-rock interactions microcracking subcritical crack growth stress corrosion cracking geological storage fluid injection EPOS multi-scale laboratories rock and melt physical properties physicochemical process compound material > unconsolidated material > natural unconsolidated material > sediment > non clastic siliceous sediment In Situ/Laboratory Instruments EARTH SCIENCE > SOLID EARTH > ROCKS/MINERALS/CRYSTALS > SEDIMENTS Rock/melt physical properties: Experimental rock deformation/HPT-Lab (Utrecht University, The Netherlands) Utrecht University, The Netherlands en 10.1029/2019JB017464 2 Files application/octet-stream application/octet-stream CC BY 4.0 We studied the effect of pore fluid chemistry on compaction creep in quartz sand aggregates, as an analogue for clean, highly porous, quartz-rich reservoir sands and sandstone. Creep is specifically addressed, because it is not yet well understood and can potentially cause reservoir compaction even after production has ceased. Going beyond previous work, we focused on fluids typically considered for pressure maintenance or for permanent storage, e.g. water, wastewater, CO2 and N2, as well as agents, such as AlCl3, a quartz dissolution inhibitor, and scaling inhibitors used in water treatment facilities and geothermal energy production. Uniaxial (oedometer) compaction experiments were performed on cylindrical sand samples at constant effective stress (35 MPa) and constant temperature (80 °C), simulating typical reservoir depths of 2-4 km. Insight into the deformation mechanisms operating at the grain scale was obtained via acoustic emission (AE) counting, and by means of microstructural study and grain size analysis applied before and after individual compaction tests. Data logging and output:The present data was obtained using an Instron loading frame employed with a uniaxial (oedometer) compaction vessel located in the HPT laboratory at Utrecht University. A complete description of the machine is provided by Schimmel et al., (2019). Mechanical and acoustic emission (AE) data were recorded at 1 Hz using National Instrument (NI) VI Logger software, an overview is presented in Table 1. Table 1. Overview of recorded data Name Unit Description Row - - Instron load V Load externally measured by the Instron loading frame Instron position V Position of the Instron loading ramp measured by the Instron LVDT Local load V Load internally measured by the local load cell Local position V Position of the top measured by the local LVDT Temperature V Sample temperature measured close to the sample Count A - Number of AE counts from counter A Count B - Number of AE counts from counter B Data processingAll measured quantities were converted to realistic units using the following conversions: - Time [s] = row * 1 - Instron load [kN]= Instron load [V] * 10 - Instron position [mm] = Instron position [V] * 5 - Local load [kN] = local load [V] * 33.3 - Local position [mm]= local position [V] * -0.100684133 - Temperature [°C] = temperature [V] * 100 The displacement data were calculated from the Instron and local position, which were corrected for apparatus distortion and thermal expansion using calibrations carried out in an empty vessel at pressure and temperature conditions covering the present experiments. The displacement data (D) were corrected according to Dsample = Dtotal – D¬distortion Where D¬distortion = 1.126e-09 * x8 - 7.744e-08 * x7 + 2.059e-06 * x6 - 2.5e-05 * x5 + 9.109e-05 * x4 + 0.0009916 * x3 - 0.01238 * x2 + 0.066 * x And is x is the applied load (Instron load). Microstructural dataGrain size analysis was performed on one undeformed and several deformed samples using a Malvern laser diffraction particle sizer. This allowed determination of the average grain size and grain size distribution before and after deformation. Laser particle size analysis systematically overestimates grain size by approximately 25 %, due to fines adhering to coarse grains. Stitched micrographs are given for one sample that was only pre-compacted and several samples that were allowed to creep after pre-compaction. Portions of these micrographs were used for crack density analysis.

oai:doidb.wdc-terra.org:69332020-10-09T07:54:28ZDOIDBDOIDB.FID

false4DOIDB.FID 10.5880/fidgeo.2020.021 Reitano, Riccardo Riccardo Reitano 0000-0002-6295-5588 Università degli Studi Roma Tre, Dip. Scienze, Sez. Geologia Faccenna, Claudio Claudio Faccenna 0000-0003-0765-4165 Università degli Studi Roma Tre, Dip. Scienze, Sez. Geologia Funiciello, Francesca Francesca Funiciello 0000-0001-7900-8272 Università degli Studi Roma Tre, Dip. Scienze, Sez. Geologia Corbi, Fabio Fabio Corbi 0000-0003-2662-3065 Università degli Studi Roma Tre, Dip. Scienze, Sez. Geologia Willett, Sean D. Sean D. Willett 0000-0002-8408-0567 Department of Earth Sciences, ETH-Zürich, Sonneggstrasse 5, 8092 Zürich, Switzerland GFZ Data Services 2020 Landscape evolution Analogue modelling Quantitative geomorphological analysis EPOS European Plate Observing System analogue models of geologic processes analogue modelling results software tools multi-scale laboratories alluvial and fluvial features base slope CloudCompare crest degradation feature destructional feature drainage pattern EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > FLUVIAL LANDFORMS > FLOOD PLAIN EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > FLUVIAL LANDFORMS > RIVER EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > FLUVIAL LANDFORMS > STREAM EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > FLUVIAL LANDFORMS > WATERSHED/DRAINAGE BASINS EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > FLUVIAL PROCESSES > LANDSLIDE EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > FLUVIAL PROCESSES > SEDIMENT TRANSPORT EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > FLUVIAL PROCESSES > WEATHERING EARTH SCIENCE > SOLID EARTH > GRAVITY/GRAVITATIONAL FIELD > GRAVITY earth surface setting earth surface setting > hillslope setting erosion surface erosional features Generic camera geolocical hydrogeological > landslide geologic process head slope Laser scanner Matlab (Mathworks) mountain mountains mountainslope natural geomorphologic feature Plastic Rainfall system Sand Sand > Quartz Sand Sandbox Sandbox > Sandbox (cm scale) slope and gravitational features Surface image Water Water saturated paste weathering Reitano, Riccardo Riccardo Reitano 0000-0002-6295-5588 Università degli Studi Roma Tre, Dip. Scienze, Sez. Geologia Reitano, Riccardo Riccardo Reitano 0000-0002-6295-5588 Università degli Studi Roma Tre, Dip. Scienze, Sez. Geologia Reitano, Riccardo Riccardo Reitano 0000-0002-6295-5588 Università degli Studi Roma Tre, Dip. Scienze, Sez. Geologia Faccenna, Claudio Claudio Faccenna 0000-0003-0765-4165 Università degli Studi Roma Tre, Dip. Scienze, Sez. Geologia Willett, Sean D. Sean D. Willett 0000-0002-8408-0567 Department of Earth Sciences, ETH-Zürich, Sonneggstrasse 5, 8092 Zürich, Switzerland Laboratory of Experimental Tectonics (University of Roma TRE, Italy) 3f93794e1a57b5c3906698aab2c630bc Universitá degli studi "Roma TRE", Rome, Italy Reitano, Riccardo Università degli Studi Roma Tre, Dip. Scienze, Sez. Geologia Dataset 10.5194/esurf-2-1-2014 https://www.danielgm.net/cc/ https://www.paraview.org/ CC BY 4.0 This dataset includes raw data used in the paper by Reitano et al. (2020), focused on the effect of different analogue materials on the mechanical and erosional properties of some defined samples. The samples are mixes of three different analogue materials in various proportions. The experiments have been carried out at Laboratory of Experimental Tectonics (LET), University “Roma Tre” (Rome). Detailed descriptions of the experimental apparatus and experimental procedures implemented can be found in the paper to which this dataset refers. We used the MATLAB toolbox “TopoToolbox” (Schwanghart and Scherler, 2014).


Here we present:
- Pictures recording the evolution of the models.
- Laser scans used for further analysis.
- Scripts created ad hoc by the authors and used for analyzing and plotting the data.


A detailed methodological description can be found in the associated "2020-021_Reitano-et-al_Dataset decription" pdf file.

oai:doidb.wdc-terra.org:69972020-12-23T15:36:53ZDOIDBDOIDB.FID

false4DOIDB.FID 10.5880/fidgeo.2020.025 Hornby, Adrian Adrian Hornby 0000-0002-4969-6163 Ludwig-Maximilians-University (LMU), Munich, Germany Küppers, Ulrich Ulrich Küppers 6602381567 Ludwig-Maximilians-University (LMU), Munich, Germany Maurer, Benedikt M. Benedikt M. Maurer Ludwig-Maximilians-University (LMU), Munich, Germany Poetsch, Carina Carina Poetsch Ludwig-Maximilians-University (LMU), Munich, Germany Dingwell, Donald B. Donald B. Dingwell 0000-0002-3332-789X Ludwig-Maximilians-University (LMU), Munich, Germany GFZ Data Services 2020 Abrasion Volcanic ash Pyroclastic density current Rotary tumbling Experiment Granular flow EPOS European Plate Observing System multi-scale laboratories rock and melt physical properties compound material > igneous material > fragmental igneous material > pyroclastic material > pyroclastic rock > ash tuff lapillistone and lapilli tuff compound material > igneous material > fragmental igneous material > pyroclastic material > Tephra > ash and lapilli compound material > igneous material > igneous rock > fine grained igneous rock > basalt compound material > igneous material > igneous rock > fine grained igneous rock > phonolitoid > phonolite EARTH SCIENCE > ATMOSPHERE > AEROSOLS > DUST/ASH/SMOKE EARTH SCIENCE > HUMAN DIMENSIONS > NATURAL HAZARDS > VOLCANIC ERUPTIONS EARTH SCIENCE > SOLID EARTH > TECTONICS > VOLCANIC ACTIVITY EARTH SCIENCE > SOLID EARTH > TECTONICS > VOLCANIC ACTIVITY > ERUPTION DYNAMICS > ASH/DUST DISPERSION EARTH SCIENCE > SOLID EARTH > TECTONICS > VOLCANIC ACTIVITY > ERUPTION DYNAMICS > PYROCLASTIC PARTICAL SIZE DISTRIBUTION EARTH SCIENCE > SOLID EARTH > TECTONICS > VOLCANIC ACTIVITY > ERUPTION DYNAMICS > PYROCLASTICS COMPOSITION/TEXTURE Hornby, Adrian Adrian Hornby 0000-0002-4969-6163 Ludwig-Maximilians-University (LMU), Munich, Germany Küppers, Ulrich Ulrich Küppers 6602381567 Ludwig-Maximilians-University (LMU), Munich, Germany Rock/melt physical properties: Melt and magma thermal analysis lab/High temperature melt lab (Ludwig-Maximilians-University Munich, Germany) Ludwig-Maximilians-University Munich, Munich, Germany Hornby, Adrian Ludwig-Maximilians-University (LMU), Munich, Germany 2020-04-30 Dataset 10.30909/vol.03.02.263283 10.1103/PhysRevE.74.031309 10.1103/PhysRevE.83.051305 10.1146/annurev.fluid.40.111406.102142 10.1093/bioinformatics/btw413 10.1016/j.grj.2015.09.001 10.1086/626836 10.5334/jors.ae 10.1007/s00445-014-0855-1 CC BY 4.0 Data supporting the publication Hornby, AJ, Kueppers U, Maurer BM, Poetsch C and Dingwell DB (2020) "Experimental constraints on volcanic ash generation and clast morphometrics in pyroclastic density currents and granular flows". In this study, fine ash is generated from lapilli-sized volcanic pumice and scoria in rotary tumbler experiments. We seek to explore ash production processes and clast attrition in natural PDCs, and gain insight into the controlling parameters for particle production efficiency with PDC transport distance. We vary the starting mass, apparatus size, and material properties and tumble clasts over multiple transport distance steps from 0.2-6 km.

The data are provided in ASCII or image formats as one zipped folder (2020-025_Hornby-et-al_data.zip) and organised in the following sub-folder structure (for more information please consult the associated data description and Hornby et al (2020):

(1) Experimental methods, apparatus and data collections
(2) Ash generation data for tumbling experiments
(3) Laser particle size distribution data for ash generated in tumbling experiments
(4) Post-experimental lapilli size (generated via 3-axis caliper measurements), mass, bulk density and dense rock equivalent (DRE) porosity results
(5) 2D image analysis morphology results
(6) 2D image analysis size results
(7) Cropped, scaled and thresholded images lapilli used for morphometric analysis
(8) Image analysis macros and workflow for ImageJ
(9) Integrated analysis of results

This project has received funding from the European Union's Horizon 2020 research and innovation programme.
In each experiment we collected the following data at each distance step:
- Mass of ash produced (<2 mm diameter);
- Grain size distribution of produced ash;
- Clast morphometrics (via photographs and image analysis) and average mass

We ran two sets of experiments (Type I and II) under identical starting conditions. In Type I experiments we returned ash and clasts to the drum, while in Type II experiments we stored the ash and returned only clasts to the drum after every distance step. Further details of the methodology and the apparatuses can be found in the “Methods and materials” file.

We also collected 3-axis volume, mass and density measurements of post-experimental clasts for a subset of experiments. We use the median values for material properties to characterise the different samples (two pumice samples and one scoria sample) and to analyse the results. We calculate the ash production rate and estimate the average change in clast size and bedload volume at each tumbling distance. We use clast and bedload dimensions to scale our results. We calculate the flow rate and inertial number for each experiment, as well as a set of associated parameters.
H2020 Marie Skłodowska-Curie Actions http://doi.org/10.13039/100010665 753900 AVAST

oai:doidb.wdc-terra.org:70372021-02-11T10:56:56ZDOIDBDOIDB.SFB806

false3DOIDB.SFB806 dataset 10.5880/SFB806.62 Janina J. Nett Wei Chu Peter Fischer Ulrich Hambach Nicole Klasen Christian Zeeden Igor Obreht Lea Obrocki Stephan Pötter Milivoj B. Gavrilov Vött Dusan Mihailovic Slobodan B. Markovic Frank Lehmkuhl CRC806-Database 2021 These datasets contain the color and grain size data for trenches 3, 3A, and 5 of the At site described in Nett et al. (2021). Sampling depths and laboratory numbers are given. Grain size was measured with a Laser Diffraction Particle Size Analyzer (Beckman Coulter LS 13 320) calculating the percentaged size frequency of 116 classes within a size range of 0.04–2000.00 µm (2% uncertainty). The measurement accuracy was increased by measuring each sample four times in two different concentrations. The grain size distributions were determined using the Mie theory (ISO International Standard 13320, 2009; Fluid RI: 1.33; Sample RI: 1.55; Imaginary RI: 0.1; Özer et al., 2010; cf. Schulte et al., 2016). The colorimetric properties of the sediments were determined as described in e.g. Eckmeier et al. (2013) and Vlaminck et al. (2016) using a Konica Minolta CM-5 spectrophotometer after the samples were homogenized and dried. The L*a*b* values indicate the extinction of light, on a scale from L* 0 (absolute black) to L* 100 (absolute white) and express color as chromaticity coordinates on red-green (a*) and blue-yellow (b*) scales. References Eckmeier, E., Mavris, C., Krebs, R., Pichler, B., and Egli, M. (2013). Black carbon contributes to organic matter in young soils in the Morteratsch proglacial area (Switzerland). Biogeosciences 10, 1265–1274. doi:10.5194/bg-10-1265-2013. Nett, J.J., Chu, W., Fischer, P., Hambach, U., Klasen, N., Zeeden, C., Obreht, I., Obrocki, L., Pötter, S., Gavrilov, M.B., Vött, A., Mihailovic, D., Markovic, S.B., and Lehmkuhl, F. (2021). The Early Upper Paleolithic site Crvenka-At, Serbia - The First Aurignacian Lowland Occupation Site in the southern Carpathian Basin. Front. Earth Sci. 9: 599986. Doi: 10.3389/feart.2021.599986. Özer, M., Orhan, M., and Işik, N. S. (2010). Effect of particle optical properties on size distribution of soils obtained by laser diffraction. Environ. Eng. Geosci. 16, 163–173. Schulte, P., Lehmkuhl, F., Steininger, F., Loibl, D., Lockot, G., Protze, J., et al. (2016). Influence of HCl pretreatment and organo-mineral complexes on laser diffraction measurement of loess–paleosol-sequences. Catena 137, 392–405. doi:10.1016/j.catena.2015.10.015. Vlaminck, S., Kehl, M., Lauer, T., Shahriari, A., Sharifi, J., Eckmeier, E., et al. (2016). Loess-soil sequence at Toshan (Northern Iran): Insights into Late Pleistocene climate change. Quat. Int. 399, 122–135. doi:10.1016/j.quaint.2015.04.028. Grain size analysis color data

oai:doidb.wdc-terra.org:63852021-02-15T15:07:20ZDOIDBDOIDB.GFZ

false4DOIDB.GFZ 10.5880/GFZ.2.1.2017.003 Darmawan, Herlan Herlan Darmawan 0000-0002-5361-5194 GFZ German Research Centre for Geosciences, Potsdam, Germany Walter, Thomas Thomas Walter 0000-0002-9925-4486 GFZ German Research Centre for Geosciences, Potsdam, Germany Richter, Nicole Nicole Richter GFZ German Research Centre for Geosciences, Potsdam, Germany Nikkoo, Mehdi Mehdi Nikkoo 0000-0002-1077-454X GFZ German Research Centre for Geosciences, Potsdam, Germany High resolution Digital Elevation Model of Merapi summit in 2015 generated by UAVs and TLS GFZ Data Services 2017 Digital Elevation Model LiDAR UAV Photogrammetry Merapi volcano Terrestrial Laser Scanning TLS Darmawan, Herlan Herlan Darmawan 0000-0002-5361-5194 GFZ German Research Centre for Geosciences, Potsdam, Germany Darmawan, Herlan Herlan Darmawan 0000-0002-5361-5194 GFZ German Research Centre for Geosciences, Potsdam, Germany Darmawan, Herlan Herlan Darmawan 0000-0002-5361-5194 GFZ German Research Centre for Geosciences, Potsdam, Germany Walter, Thomas Thomas Walter 0000-0002-9925-4486 GFZ German Research Centre for Geosciences, Potsdam, Germany Richter, Nicole Nicole Richter GFZ German Research Centre for Geosciences, Potsdam, Germany Nikkoo, Mehdi Mehdi Nikkoo 0000-0002-1077-454X GFZ German Research Centre for Geosciences, Potsdam, Germany /d 2017-11-15 2014-09-14/2015-10-06 en 10.1016/j.jvolgeores.2017.11.006 80487522 Bytes 2 Files image/tiff image/tiff 2015 CC BY 4.0 This data publication is a high resolution Digital Elevation Model (DEM) generated for the Merapi summit by combining terrestrial laser scanning (TLS) and unmanned aerial vehicles (UAVs) photogrammetry data acquired in 2014 and 2015, respectively. The structures of the data are further analysed in Darmawan et al. 2017 (http://doi.org/10.1016/j.jvolgeores.2017.11.006). The published datasets consist of combined point clouds with ~65 million data points and a DEM with a resampled resolution of 0.5 m. The DEM data covers the complexity of the Merapi summit with area of 2 km2. The coordinate of the datasets is projected to global coordinates (WGS 1984 UTM Zone 49 South). TLS is a topography mapping technique which exploits the travel time of a laser beam to measure the range between the ground-based scanning instrument and the earth’s surface. TLS provides high accuracy, precision, and resolution for topography mapping, however, it requires different scan position to obtain accurate topography model in a complex topography. The TLS dataset was acquired by using a long-range RIEGL VZ-6000 instrument with a Pulse Repetition Rate (PRR) of 30 kHz. The Merapi data includes an observation range of 0.129 – 4393.75 m, a theta range (vertical) of 73 – 120° with a sampling angle of 0.041°, a phi range (horizontal) of 33° - 233° with a sampling angle of 0.05°, and 12 reflectors for each scan. The used TLS dataset was achieved by combining two scan positions, both realized in September 2014. In order to reduce still eminent shadowing, we conducted additionally a UAV photogrammetry survey. The UAV data allows to fill data gaps and generate a complete 3D point cloud. The UAV photogrammetry was conducted by using DJI Phantom 2 quadcopter drone in October 2015. The drone carried GoPro HERO 3+ camera and a H3-3D gimbal to reduce image shaking. We obtained over 300 images which cover the summit area of Merapi. By applying the Structure from Motion algorithm, we are able to generate a 3D point cloud model of Merapi summit. Further details on this procedure are provided in Darmawan et al. (2017). Structure from Motion is a technique to generate a 3D model based on 2D overlapped images. The algorithm detects and matches the same ground features of 2D images, reconstructs a 3D scene, and calculates a depth map for each camera frame. The algorithm used is implemented in Agisoft Photoscan Professional software. After importing the images in Agisoft, we used the ‘align image’ function with high accuracy setting to generate 3D sparse point cloud and ‘build dense cloud’ function with high quality to generate 3D dense point cloud. The 3D point clouds of TLS and UAV photogrammetry were then georeferenced to our georeferenced 3D point cloud which acquired in 2012. The RMS of TLS and UAV photogrammetry during georeferenced is 0.60 and 0.44 m, respectively, as described in Further details on this procedure are provided in Darmawan et al. (2017). After georeferencing, both 3D point clouds were merged and interpolated to a raster format in the ArcMap software. 110.439711 110.455147 -7.554412 -7.536093 The data cover area of 2 km square at Merapi summit Horizon 2020 Framework Programme http://doi.org/10.13039/100010661 ERC-CoG 646858 VOLCAPSE

oai:doidb.wdc-terra.org:70392021-02-16T17:41:00ZDOIDBDOIDB.GFZ

false4DOIDB.GFZ 10.5880/GFZ.2.1.2020.008 Walter, Thomas R. Thomas R. Walter 0000-0002-9925-4486 GFZ German Research Centre for Geosciences, Potsdam, Germany Darmawan, Herlan Herlan Darmawan 0000-0002-5361-5194 GFZ German Research Centre for Geosciences, Potsdam, Germany GFZ Data Services 2021 Merapi Aircraft > UAV Earth Observation Satellites > TDX Earth Observation Satellites > TSX Earth Remote Sensing Instruments > Active Remote Sensing > Profilers/Sounders > Lidar/Laser Sounders > LIDAR EARTH SCIENCE SERVICES > MODELS > DIGITAL ELEVATION/DIGITAL TERRAIN MODELS science > natural science > earth science > geology > volcanology Walter, Thomas R. Thomas R. Walter 0000-0002-9925-4486 GFZ German Research Centre for Geosciences, Potsdam, Germany Darmawan, Herlan Herlan Darmawan 0000-0002-5361-5194 GFZ German Research Centre for Geosciences, Potsdam, Germany Walter, Thomas R. GFZ German Research Centre for Geosciences, Potsdam, Germany 2015-10-06 2014-09-14 Dataset 10.5880/GFZ.2.1.2017.003 10.1016/j.jvolgeores.2017.11.006 1 CC BY 4.0 This data is an high resolution Digital Elevation Model (DEM) generated for the Merapi summit by combining terrestrial laser scanning (TLS) and unmanned aerial vehicles (UAVs) photogrammetry data and TanDEM-X data acquired in the years between 2012 and 2017. The structures of the data are further analysed in Darmawan et al. 2017a (http://doi.org/10.1016/j.jvolgeores.2017.11.006), and a previous DEM was available in Darmawan et al. 2017b (https://doi.org/10.5880/GFZ.2.1.2017.003). The 3D point clouds of the different data were merged and interpolated to a raster format (Geotiff format).
110.431 110.461 -7.55471 -7.5268

oai:doidb.wdc-terra.org:71042021-05-21T11:33:37ZDOIDBDOIDB.GFZ

false4DOIDB.GFZ 10.5880/GFZ.3.1.2020.005 Rieger, Philip Philip Rieger 0000-0001-7888-0077 GFZ German Research Centre for Geosciences, Potsdam, Germany Institute of Geological Sciences, Freie Universität Berlin, Berlin, Germany Magnall, Joseph M. Joseph M. Magnall 0000-0002-7868-3038 GFZ German Research Centre for Geosciences, Potsdam, Germany Gleeson, Sarah A. Sarah A. Gleeson 0000-0002-5314-4281 GFZ German Research Centre for Geosciences, Potsdam, Germany Institute of Geological Sciences, Freie Universität Berlin, Berlin, Germany Oelze, Marcus Marcus Oelze 0000-0002-3950-6629 GFZ German Research Centre for Geosciences, Potsdam, Germany Wilke, Franziska D.H. Franziska D.H. Wilke 0000-0002-3463-6176 GFZ German Research Centre for Geosciences, Potsdam, Germany Lilly, Richard Richard Lilly 0000-0001-9111-2056 Department of Earth Sciences, University of Adelaide, Adelaide, Australia GFZ Data Services 2021 rare earth elements CD-type massive sulphide deposit SEDEX massive sulphide deposit hydrothermal alteration hydrothermal ore formation Proterozoic sedimentary basin Mount Isa George Fisher Carpentaria Province EARTH SCIENCE > OCEANS > OCEAN CHEMISTRY > MARINE GEOCHEMISTRY In Situ/Laboratory Instruments > Spectrometers/Radiometers > LA-ICP-MS Elemental Mapping by LA-ICP-MS (GFZ German Research Centre for Geosciences, Germany) GFZ German Research Centre for Geosciences, Potsdam, Germany Rieger, Philip GFZ German Research Centre for Geosciences, Potsdam, Germany Dataset 10.1007/s00126-021-01056-1 10.1039/C1JA10172B 10.1111/j.1751-908X.2007.00104.x CC BY 4.0 Carbonate minerals are ubiquitous in most sediment-hosted mineral deposits. These deposits can contain a variety of carbonate types with complex paragenetic relationships. When normalized to chondritic values (CN), rare-earth elements and yttrium (REE+YCN) can be used to constrain fluid chemistry and fluid-rock interaction processes in both low- and high-temperature settings. Unlike other phases (e.g., pyrite), the application of in situ laser ablation-inductively coupled plasma-mass spectroscopy (LA-ICP-MS) data to the differentiation of pre-ore and hydrothermal carbonates remains relatively untested. To assess the potential applicability of carbonate in situ REE+Y data, we combined transmitted light and cathodoluminescence (CL) petrography with LA-ICP-MS analysis of carbonate mineral phases from (1) the Proterozoic George Fisher clastic dominated (CD-type) massive sulfide deposit and from (2) correlative, barren host rock lithologies (Urquhart Shale Formation).

The REE+YCN composition of pre-ore calcite suggests it formed during diagenesis from diagenetic pore fluids derived from ferruginous, anoxic seawater. Hydrothermal and hydrothermally altered calcite and dolomite from George Fisher is generally more LREE depleted than the pre-ore calcite, whole-rock REE concentrations, and shale reference values. We suggest this is the result of hydrothermal alteration by saline Cl--rich mineralizing fluids.

Furthermore, the presence of both positive and negative Eu/Eu* values in calcite and dolomite indicates that the mineralizing fluids were relatively hot (>250°C) and cooled below 200-250°C during ore formation. This study confirms the hypothesis that in situ REE+Y data can be used to differentiate between pre-ore and hydrothermal carbonate and provide important constraints on the conditions of ore formation.

oai:doidb.wdc-terra.org:63702022-01-17T18:26:04ZDOIDBDOIDB.GFZ

false4DOIDB.GFZ 10.5880/GFZ.1.2.2018.001 Rudenko, Sergei Sergei Rudenko 0000-0001-5149-3827 GFZ German Research Centre for Geosciences, Deutsches Geodätisches Forschungsinstitut der Technischen Universität München (DGFI-TUM) Schöne, Tilo Tilo Schöne GFZ German Research Centre for Geosciences Neumayer, Karl-Hans Karl-Hans Neumayer GFZ German Research Centre for Geosciences Esselborn, Saskia Saskia Esselborn GFZ German Research Centre for Geosciences Raimondo, Jean-Claude Jean-Claude Raimondo SpaceTech GmbH Dettmering, Denise Denise Dettmering Deutsches Geodätisches Forschungsinstitut der Technischen Universität München (DGFI-TUM) GFZ VER11 SLCCI precise orbits of altimetry satellites ERS-1, ERS-2, Envisat, TOPEX/Poseidon, Jason-1 and Jason-2 in the ITRF2008 GFZ Data Services 2016 Jason-1 Jason-2 ERS-1 ERS-2 Envisat ESA CCI Sea Level Altimetry satellite Low Earth Orbit satellites sea level TOPEX/POSEIDON ITRF2008 Earth Remote Sensing Instruments > Active Remote Sensing > Altimeters > Radar Altimeters equipment > artificial satellite > observation satellite EARTH SCIENCE > SOLID EARTH > GRAVITY/GRAVITATIONAL FIELD > SATELLITE ORBITS/REVOLUTION > ORBITAL POSITION EARTH SCIENCE > OCEANS > SEA SURFACE TOPOGRAPHY > SEA SURFACE HEIGHT 2016-05-12/2 2014-01-01 1991-08-01/2015-04-04T23:59:59 eng 10.1109/TGRS.2017.2670061 ftp://igs.org/pub/data/format/sp3c.txt 10.1093/gji/ggv545 10.1016/j.asr.2014.03.010 10.1016/j.asr.2012.01.021 10.5194/os-14-205-2018 6 Files application/octet-stream application/octet-stream application/octet-stream application/octet-stream application/octet-stream application/octet-stream VER11 CC BY 4.0 The data set provides GFZ VER11 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),Jason-1 (January 13, 2002 - July 5, 2013) andJason-2 (July 5, 2008 - April 5, 2015)TOPEX/Poseidon (September 23, 1992 - October 8, 2005), derived at the time spans given at Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences 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 and the Altimeter Database and processing System (ADS, http://adsc.gfz-potsdam.de/ads/) developed at GFZ. The orbits were computed in the same (ITRF2008) 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. The orbit files are available in the Extended Standard Product 3 Orbit Format (SP3-c, ftp://igscb.jpl.nasa.gov/igscb/data/format/sp3c.txt) 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 stands for month and DD stands for day of the beginning of the file. More details on these orbits are provided in Rudenko et al. (2017) -180 180 -82.00000 82.000000 European Space Agency http://doi.org/10.13039/501100000844 Climate Change Initiative Sea Level Phase II project Deutsche Forschungsgemeinschaft http://doi.org/10.13039/501100001659 Consistent estimate of ultra-high resolution Earth surface gravity data (UHR-GravDat)

oai:doidb.wdc-terra.org:66152022-01-17T18:27:04ZDOIDBDOIDB.GFZ

false4DOIDB.GFZ 10.5880/GFZ.1.2.2018.003 Rudenko, Sergei Sergei Rudenko https://orcid.org/0000-0001-5149-3827 GFZ German Research Centre for Geosciences, Potsdam, Germany Deutsches Geodätisches Forschungsinstitut der Technischen Universität München (DGFI-TUM) Schöne, Tilo Tilo Schöne https://orcid.org/0000-0003-4118-9578 GFZ German Research Centre for Geosciences, Potsdam, Germany Esselborn, Saskia Saskia Esselborn https://orcid.org/0000-0002-1924-4449 GFZ German Research Centre for Geosciences, Potsdam, Germany Neumayer, Karl Hans Karl Hans Neumayer GFZ German Research Centre for Geosciences, Potsdam, Germany 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 GFZ Data Services 2018 Altimetry satellite Low Earth Orbit satellites ESA CCI Sea Level sea level ITRF2014 ERS-1 ERS-2 Envisat TOPEX/Poseidon Jason-1 Jason-2 Orbit Earth Observation Satellites > ENVISAT Earth Observation Satellites > OSTM/JASON-2 Earth Observation Satellites > TOPEX/POSEIDON Earth Observation Satellites > JASON-1 Earth Observation Satellites > ERS Earth Resource Satellite > ERS-2 Earth Observation Satellites > ERS Earth Resource Satellite > ERS-1 Earth Remote Sensing Instruments > Active Remote Sensing > Altimeters > Radar Altimeters EARTH SCIENCE > SOLID EARTH > GRAVITY/GRAVITATIONAL FIELD > SATELLITE ORBITS/REVOLUTION > ORBITAL POSITION EARTH SCIENCE > OCEANS > SEA SURFACE TOPOGRAPHY > SEA SURFACE HEIGHT 1991-08-01/2015-05-06 eng ftp://igs.org/pub/data/format/sp3c.txt 10.5194/se-10-293-2019 10.5880/GFZ.1.2.2018.001 10.1109/TGRS.2017.2670061 10.5194/os-14-205-2018 10.1007/s00190-004-0379-0 1 Files application/octet-stream CC BY 4.0 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. -180 180 -82 82 alongtrack European Space Agency http://doi.org/10.13039/501100000844 ESA CCI Sea Level Phase II project

oai:doidb.wdc-terra.org:71012022-01-19T15:43:09ZDOIDBDOIDB.GFZ

false4DOIDB.GFZ 10.5880/GFZ.3.1.2021.003 Pan, Mengdi Mengdi Pan 0000-0003-0632-1799 GFZ German Research Centre for Geosciences, Potsdam, Germany Schicks, Judith M. Judith M. Schicks 0000-0003-1106-0693 GFZ German Research Centre for Geosciences, Potsdam, Germany GFZ Data Services 2021 mixed gas hydrates in situ Raman spectroscopy Earth Remote Sensing Instruments > Active Remote Sensing > Spectrometers/Radiometers > Lidar/Laser Spectrometers EARTH SCIENCE > SOLID EARTH > ROCKS/MINERALS/CRYSTALS > GAS HYDRATES > GAS HYDRATES FORMATION EARTH SCIENCE > SOLID EARTH > ROCKS/MINERALS/CRYSTALS > GAS HYDRATES > GAS HYDRATES PHYSICAL/OPTICAL PROPERTIES > STABILITY resource > energy resource Pan, Mengdi Mengdi Pan 0000-0003-0632-1799 GFZ German Research Centre for Geosciences, Potsdam, Germany Pan, Mengdi Mengdi Pan 0000-0003-0632-1799 GFZ German Research Centre for Geosciences, Potsdam, Germany Schicks, Judith M. Judith M. Schicks 0000-0003-1106-0693 GFZ German Research Centre for Geosciences, Potsdam, Germany Schicks, Judith M. Judith M. Schicks 0000-0003-1106-0693 GFZ German Research Centre for Geosciences, Potsdam, Germany Micro-Raman Spectroscopy Laboratory (GFZ German Research Centre for Geosciences, Germany) GFZ German Research Centre for Geosciences, Potsdam, Germany Schicks, Judith M. GFZ German Research Centre for Geosciences, Potsdam, Germany Dataset 10.3390/molecules26103039 10.1016/S0024-4937(00)00043-8 10.1002/9783527615438 10.1007/978-3-642-81279-8_4 CC BY 4.0 Natural gas hydrates encase predominantly methane, but also higher hydrocarbons as well as CO2 and H2S. The formation of gas hydrates from a changing gas mixture, either due to the preferred incorporation of certain components into the hydrate phase or an inadequate gas supply, may lead to significant changes in the composition of the resulting hydrate phase. To determine the overall composition of a hydrate phase during the hydrate formation process, Raman spectroscopy is regarded as a non-destructive and powerful tool. This technique enables to distinguish between guest molecules in the free gas or liquid phase, encased into a clathrate cavity or dissolved in an aqueous phase, therefore providing time-resolved information about the guest molecules during the hydrate formation process.
Experiments were carried out at the Micro-Raman Spectroscopy Laboratory, GFZ. Mixed gas hydrates were synthesized in a high-pressure cell from pure water and a specific gas flow containing CH4, C2H6, C3H8, iso-C4H10 and n-C4H10 at 274 K and 2.20 MPa. Three potential different gas supply conditions were selected for the formation of mixed gas hydrates, namely an open system (test scenario 1) with a continuous gas supply, a closed system (test scenario 2) with no gas supply after initial pressurization with the gas mixture, and a semi-closed system (test scenario 3) with only an incoming gas but a disrupted outlet. In situ Raman spectroscopic measurements and microscopic observations were applied to record changes in both gas and hydrate compositions over the whole formation period until it reached a steady state. In all three test scenarios, 12 hydrate crystals were selected and continuously characterized for 5 days with single point Raman measurements to record the formation process of mixed gas hydrates. Each test scenario was repeated for 3 times, therefore resulting in 9 separate experimental tests.
This dataset encompasses raw Raman spectra of the 9 experimental tests (.txt files) which contained Raman shifts and the respective measured intensities. Each Raman spectrum was fitted to Gauss/Lorentz function after an appropriate background correction to estimate the band areas and positions (Raman shift). The Raman band areas were then corrected with wavelength-independent cross-sections factors for each specific component. The concentration of each guest molecule in the hydrate phase / gas phase was given as mol% in separate spreadsheet for three different test scenarios. Further details on the analytical setup, experimental procedures and composition calculation are provided in the following sections.

Mixed gas hydrates were synthesized in a custom-made pressure cell in the laboratory from water and a certified gas mixture containing CH4, C2H6, C3H8, iso-C4H10, and n-C4H10. Initially, the sample cell was filled with 150 μl deionized and degassed water, carefully sealed and pressurized with the respective gas mixture. When the pressure reached 2.20 MPa and the flowrate was constant, the cell was cooled down to 253 K to induce the spontaneous crystallization of hydrate and ice. After the formation of hydrates and ice, the cell was slowly warmed up to allow the dissociation of ice and most hydrate crystals until only a few hydrate crystals were left. Subsequently, the cell was cooled down again to a temperature within the stability field of the hydrate phase, but above the melting temperature of the ice. Under these conditions set, euhedral gas hydrate crystals were allowed to grow. This “melting-cooling” process was carried out three times before the p-T condition was fixed at 2.20 MPa and 274 K for the formation of mixed gas hydrates.
To investigate the hydrate formation process, three different test scenarios were carried out with different gas flows but under identical p-T conditions. The inlet and outlet valves located outside the pressure cell were set to the desired position once the mixed gas hydrates started to form. In test scenario 1 (open system), the inlet and outlet valves were kept open throughout the whole experiment. Test scenario 2 (closed system) was carried out with the inlet and outlet valves being closed right after initial pressurization to mimic a system with a limited gas supply. The outlet valve was closed in test scenario 3 (semi-closed system) while the inlet valve was open. These changes on the gas flow were maintained throughout the whole formation process. Each test scenario was repeated for 3 times during the experiments.
A confocal Raman spectrometer (LABRAM HR Evolution, Horiba Jobin Yvon) with 1800-grooves/mm grating and a 20× microscope Olympus BX-FM objective was used for the in situ Raman measurements on the mixed gas hydrates. The excitation source was a frequency-doubled Nd:YAG solid-state laser with an output power of 100 mW working at 532 nm. With a focal length of 800 mm, the spectral resolution reached around 0.6 cm-1. A motorized pinhole in the analyzing beam path enabled to variably increase the spatial resolution of laser-spot measurements which in x-y-direction was 0.5 µm and 1.5 µm in z-direction. Before the experiments, the Silicon band (521 cm-1) was employed for the calibration of Raman band positions. During the experiments, a pinhole size of 50 µm was chosen for measurements on the hydrate surface while a pin hole size of 100 µm was set for the gas phase measurements. The acquisition time was 5 seconds with 2 averaged exposures. Neutral density filters that adjusted the output laser power was selected at 100% for the experiment since it provided the best signal-to-noise ratio while laser irradiation damage at the sample was not observed.
For each experimental test, 12 hydrate crystals were randomly selected in the pressure cell. With the help of a motorized, software controlled Märzhauser Scan+ sample stage attached to the microscope, which allowed for the positioning of the sample cell at defined coordinates, the selected hydrate crystals could be monitored over the entire duration of the experiment. Single point Raman spectroscopic measurements were performed right after initial pressurization on hydrate crystal surface. For the following 4 days, a continuous characterization on these crystals were carried out to record the changes of hydrate composition during the formation process.

oai:doidb.wdc-terra.org:72782022-01-20T11:38:23ZDOIDBDOIDB.FID

false4DOIDB.FID 10.5880/fidgeo.2021.041 Reitano, Riccardo Riccardo Reitano 0000-0002-6295-5588 Universitá degli studi "Roma TRE", Rome, Italy Faccenna, Claudio Claudio Faccenna 0000-0003-0765-4165 Universitá degli studi "Roma TRE", Rome, Italy Funiciello, Francesca Francesca Funiciello 0000-0001-7900-8272 Universitá degli studi "Roma TRE", Rome, Italy Corbi, Fabio Fabio Corbi 0000-0003-2662-3065 National Research Council - CNR, Istituto di Geologia Ambientale e Geoingegneria Sternai, Pietro Pietro Sternai 0000-0003-1891-6474 Università degli Studi di Milano-Bicocca, Milano, Italy Willett, Sean D. Sean D. Willett 0000-0002-8408-0567 Swiss Federal Institute of Technology in Zurich, Zurich, Switzerland Sembroni, Andrea Andrea Sembroni 0000-0003-4672-6125 Università di Bologna “Alma mater studiorum” Lanari, Riccardo Riccardo Lanari 0000-0002-8304-6367 Università degli Studi di Firenze Dipartimento di Scienze della Terra, Firenze, Toscana, Italy GFZ Data Services 2021 Tectonics Erosion Sedimentation Mass Balance Analogue models EPOS multi-scale laboratories analogue models of geologic processes property data of analogue modelling materials analogue modelling results software tools EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > FLUVIAL LANDFORMS > FLOOD PLAIN EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > FLUVIAL LANDFORMS > RIVER EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > FLUVIAL LANDFORMS > STREAM EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > FLUVIAL LANDFORMS > VALLEY EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > FLUVIAL LANDFORMS > WATERSHED/DRAINAGE BASINS EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > FLUVIAL PROCESSES > SEDIMENT TRANSPORT EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > FLUVIAL PROCESSES > SEDIMENTATION EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > FLUVIAL PROCESSES > WEATHERING EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > TECTONIC LANDFORMS > MOUNTAINS EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > TECTONIC PROCESSES > OROGENIC MOVEMENT EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > TECTONIC PROCESSES > TECTONIC UPLIFT hydrosphere > water (geographic) > surface water science > natural science > earth science > geology > tectonics Reitano, Riccardo Riccardo Reitano 0000-0002-6295-5588 Universitá degli studi "Roma TRE", Rome, Italy Reitano, Riccardo Riccardo Reitano 0000-0002-6295-5588 Universitá degli studi "Roma TRE", Rome, Italy Laboratory of Experimental Tectonics (University of Roma TRE, Italy) 3f93794e1a57b5c3906698aab2c630bc Universitá degli studi "Roma TRE", Rome, Italy Reitano, Riccardo Universitá degli studi "Roma TRE", Rome, Italy Dataset 10.1029/2021TC006951 10.3390/geosciences11100412 10.1016/j.crte.2008.01.005 10.1016/j.tecto.2011.09.029 10.1016/j.tecto.2016.04.016 10.1029/2020TC006515 10.5194/esurf-8-973-2020 10.1016/j.geomorph.2016.02.022 10.5194/esurf-2-1-2014 10.1016/j.tecto.2011.10.005 CC BY 4.0 This dataset includes raw data used in the paper by Reitano et al. (2022), focused on the effect of boundary conditions on the evolution of analogue accretionary wedges affected by both tectonics and surface processes; the paper also focuses on the balance between tectonics and surface processes as a function of the boundary conditions applied. These boundary conditions are convergence velocity and basal slope (i.e., the tilting toward the foreland imposed prior the experimental run). The experiments have been carried out at Laboratory of Experimental Tectonics (LET), University “Roma Tre” (Rome). Detailed descriptions of the experimental apparatus and experimental procedures implemented can be found in the paper to which this dataset refers. Here we present:
• Pictures recording the evolution of the models.
• GIFs showing time-lapses of models.
• Raw DEMs of the models and Incision DEMs, used for extracting data later discusses in the paper.
We took digital images during the evolution of the experiments. These images are stored in the “2021-041_Reitano-et-al_Pictures_and_GIFs” folder.

Digital Images
The qualitative evolution of the analogue models has been recorded using a digital oblique-view camera (Canon EOS 200D). Digital pictures have not been modified with other imaging software.

Data from models' surface
Laser scan provides a point cloud, composed by x, y, z coordinated of the points composing the model surface (the number of points is function of the laser resolution). The laser scans are converted to raw DEMs, here stored in the “DEMs” folder. For making the file easily readable to GIS software, data are expressed in m (100 m = 1 mm, see scaling section in the main paper). Bottom left corner in the DEMs is randomly chosen to be -70 ∙ 103 m. No data values equal to -9999. Cell size is 100 m (1 mm in the models).

Incision and Mass Balance
The .txt files inside the “2021-041_Reitano-et-al_DEMs” folder named “CR****_dem**clip” has been used for producing Fig. 6, 8, 10, and S3 in Reitano et al. (2021). From these DEMs we calculated the Mass Balance, as described in the paper this repository refers to. The .txt files named “CR****_inc**ok” have been used for calculating the incision values shown in Fig. 5 and 7 in Reitano et al. (2021). To obtain incision maps and incision over time, the volume of material incised was computed by comparing the actual topography with the reconstructed non-eroded surface at every shortening step. The non-eroded surface has been calculated by creating an envelope surface using crest lines between valleys as constraints (the assumption is that crests do not erode). The results are then a minimum estimate of the amount of incision.

oai:doidb.wdc-terra.org:71992022-02-04T19:45:09ZDOIDBDOIDB.GFZ

false4DOIDB.GFZ 10.5880/GFZ.1.4.2021.003 Koellner, Nicole Nicole Koellner 0000-0002-4282-8979 GFZ German Research Centre for Geosciences, Potsdam, Germany Kuras, Agnieszka Agnieszka Kuras GFZ German Research Centre for Geosciences, Potsdam, Germany Hildebrand, Constantin Constantin Hildebrand GFZ German Research Centre for Geosciences, Potsdam, Germany Koerting, Friederike Friederike Koerting 0000-0002-0759-5655 Norsk Elektro Optikk AS – HySpex division, Oslo, Norway Kaestner, Friederike Friederike Kaestner 0000-0003-2654-3866 GFZ German Research Centre for Geosciences, Potsdam, Germany GFZ Data Services 2021 hyperspectral spectral library geochemical Li-bearing minerals LIBS Laser-Induced Breakdown Spectroscopy Earth Remote Sensing Instruments > Passive Remote Sensing > Spectrometers/Radiometers EARTH SCIENCE > SOLID EARTH > ROCKS/MINERALS/CRYSTALS > IGNEOUS ROCKS > IGNEOUS ROCK PHYSICAL/OPTICAL PROPERTIES EARTH SCIENCE > SOLID EARTH > ROCKS/MINERALS/CRYSTALS > SEDIMENTARY ROCKS > SEDIMENTARY ROCK PHYSICAL/OPTICAL PROPERTIES Spectroscopy Laboratory (GFZ German Research Centre for Geosciences, Germany) GFZ German Research Centre for Geosciences, Potsdam, Germany Koellner, Nicole GFZ German Research Centre for Geosciences, Potsdam, Germany Dataset 10.5194/essd-13-923-2021 10.1017/CBO9780511541261 http://lights.univ-lorraine.fr/ https://sciaps.com/libs-handheld-laser-analyzers/z-300 10.5880/GFZ.1.4.2019.003 10.5880/GFZ.1.4.2019.004 CC BY 4.0 The data set contains LIBS (Laser-Induced Breakdown Spectroscopy) emission spectra of 18 lithium-bearing minerals and their corresponding hyperspectral reflectance spectra. The data were collected within the research project LIGHTS (Lightweight Integrated Ground and Airborne Hyperspectral Topological Solutions, http://lights.univ-lorraine.fr/) which aims at developing a new exploration process for Li targets combining drone-borne hyperspectral data and field observations. Hyperspectral data were acquired with the HySpex system in a wavelength range of 414 - 2498 nm and are presented in a spectral library. Detailed information about the samples and area of spectral retrieval is presented in the data sheet below. The spectral library presented here expands the collection of spectral libraries including samples from rare-earth minerals, rare-earth-oxides (Koerting et al., 2019a) and copper-bearing minerals (Koellner et al., 2019) which are fully described in Koerting et al. (2021). These libraries aim to give a spectral overview of important resources and deposit mineralizations.

18 samples taken partly from the collections of the University of Potsdam (UP) and the Federal Institute for Geosciences and Natural Resources (BGR) and partly in the field during previous measurement campaigns were hyperspectrally measured and geochemically analysed by using a LIBS handheld analyzer. A description of the HySpex system in lab use can be found in Koerting et al. (2021).

The lithium-bearing mineral samples were measured without prior sample preparation as the surface of the minerals and the influence of the mineral structure were of interest (Figure 1). Figure 1 shows one HySpex scan of four lepidolite samples (Lep1, Lep2, Lep3, Lep4) displayed as a true color RGB image in order to show the untreated samples and the white reflectance (WR) panel needed for the hyperspectral measurements (WR 90%).

oai:doidb.wdc-terra.org:73602022-05-11T16:46:48ZDOIDBDOIDB.FID

false4DOIDB.FID 10.5880/fidgeo.2022.020 Erdbrügger, Jana Jana Erdbrügger 0000-0002-7238-9583 Universität Zürich, Zurich, Switzerland van Meerveld, Ilja Ilja van Meerveld 0000-0002-7547-3270 Universität Zürich, Zurich, Switzerland Seibert, Jan Jan Seibert 0000-0002-6314-2124 Universität Zürich, Zurich, Switzerland Swedish University of Agricultural Sciences: Uppsala, Sweden Bishop, Kevin Kevin Bishop Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Uppsala, Sweden GFZ Data Services 2022 boreal catchment EARTH SCIENCE > TERRESTRIAL HYDROSPHERE > GROUND WATER > GROUNDWATER CHEMISTRY hydrosphere > hydrologic cycle > hydrologic balance > runoff > drainage > drainage system > natural drainage system hydrosphere > water (geographic) > groundwater science > natural science > water science > hydrology Erdbrügger, Jana Jana Erdbrügger 0000-0002-7238-9583 Universität Zürich, Zurich, Switzerland Erdbrügger, Jana Jana Erdbrügger 0000-0002-7238-9583 Universität Zürich, Zurich, Switzerland Erdbrügger, Jana Jana Erdbrügger 0000-0002-7238-9583 Universität Zürich, Zurich, Switzerland Erdbrügger, Jana Jana Erdbrügger 0000-0002-7238-9583 Universität Zürich, Zurich, Switzerland Erdbrügger, Jana Jana Erdbrügger 0000-0002-7238-9583 Universität Zürich, Zurich, Switzerland van Meerveld, Ilja Ilja van Meerveld 0000-0002-7547-3270 Universität Zürich, Zurich, Switzerland van Meerveld, Ilja Ilja van Meerveld 0000-0002-7547-3270 Universität Zürich, Zurich, Switzerland van Meerveld, Ilja Ilja van Meerveld 0000-0002-7547-3270 Universität Zürich, Zurich, Switzerland van Meerveld, Ilja Ilja van Meerveld 0000-0002-7547-3270 Universität Zürich, Zurich, Switzerland Seibert, Jan Jan Seibert 0000-0002-6314-2124 Universität Zürich, Zurich, Switzerland Swedish University of Agricultural Sciences: Uppsala, Sweden Seibert, Jan Jan Seibert 0000-0002-6314-2124 Universität Zürich, Zurich, Switzerland Swedish University of Agricultural Sciences: Uppsala, Sweden Seibert, Jan Jan Seibert 0000-0002-6314-2124 Universität Zürich, Zurich, Switzerland Swedish University of Agricultural Sciences: Uppsala, Sweden Seibert, Jan Jan Seibert 0000-0002-6314-2124 Universität Zürich, Zurich, Switzerland Swedish University of Agricultural Sciences: Uppsala, Sweden Seibert, Jan Jan Seibert 0000-0002-6314-2124 Universität Zürich, Zurich, Switzerland Swedish University of Agricultural Sciences: Uppsala, Sweden Bishop, Kevin Kevin Bishop Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Uppsala, Sweden Bishop, Kevin Kevin Bishop Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Uppsala, Sweden Bishop, Kevin Kevin Bishop Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Uppsala, Sweden Bishop, Kevin Kevin Bishop Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, Uppsala, Sweden Erdbrügger, Jana Universität Zürich, Zurich, Switzerland 2022-05-06 2018-07-18/2020-11-01 Dataset DOI of paper when available CC BY 4.0 Groundwater can respond quickly to precipitation and is the main contribution to streamflow in most catchments in humid, temperate climates. To better understand shallow groundwater dynamics in a boreal headwater catchment, we installed a network of groundwater wells in two areas in the Krycklan catchment in Northern Sweden. This dataset contains groundwater level data and sampling data from a small headwater catchment (3.5 ha, 54 wells) and a hillslope (1 ha, 21 wells).

The dataset is arranged in to subsets, Dataset 1 and 2, the first containing groundwater levels and related information while the second contains information on the chemical sampling procedure and laboratory results.

The average wells depth was 274 cm (range: 70 - 581 cm) and recorded the groundwater level variation at a 10-30 min interval between 18. July 2018 – 1. November 2020. Manual water level measurements (0 - 26 per well) during the summer seasons in 2018 and 2019 were used to confirm and re-calibrate the water level logger results.

The groundwater level data for each well was carefully processed and quality controlled, using six data labels. The location and depths of the wells are in the file 2022-020_Erdbruegger-et-al_Krycklan_gw_wells.csv and the groundwater levels and classifications 2022-020_Erdbruegger-et-al_Krycklan_gw_levels.csv.

The absolute and relative positions of the wells were measured with a high-precision GPS and terrestrial laser scanner (TLS) to determine differences in groundwater levels and thus groundwater gradients (the report of the registration of the point clouds can be found in the files 2022-020_Erdbruegger-et-al_TSL_registration_report_[A/B].rtf). During the summer of 2019, all wells with sufficient water were sampled and analyzed for electrical conductivity, pH, absorbance, anion and cation concentrations, as well as δ18O and δ2H (information on the sampling and the laboratory results can be found in the files 2022-020_Erdbruegger-et-al_Krycklan_gw_chemistry.csv, 2022-020_Erdbruegger-et-al_Field_protocol.csv, 2022-020_Erdbruegger-et-al_Lab_analysis_description.pdf). This combined hydrometric and hydrochemical dataset can be useful to test models that simulate groundwater dynamics and to evaluate subsurface hydrological connectivity. The full description of the data and methods is provided in citation of article XX when available.

Krycklan catchment 19.7576 19.7913 64.2502 64.2637

oai:doidb.wdc-terra.org:73702022-05-18T07:11:53ZDOIDBDOIDB.GFZ

false4DOIDB.GFZ 10.5880/GFZ.1.4.2022.007 Hildebrand, Constantin Constantin Hildebrand 0000-0003-3057-0621 GFZ German Research Centre for Geosciences, Potsdam, Germany Koellner, Nicole Nicole Koellner 0000-0002-4282-8979 GFZ German Research Centre for Geosciences, Potsdam, Germany Kaestner, Friederike Friederike Kaestner 0000-0003-2654-3866 GFZ German Research Centre for Geosciences, Potsdam, Germany Koerting, Friederike Friederike Koerting 0000-0002-0759-5655 GFZ German Research Centre for Geosciences, Potsdam, Germany Mielke, Christian Christian Mielke GFZ German Research Centre for Geosciences, Potsdam, Germany GFZ Data Services 2022 Hyperspectral Imagery Imaging spectroscopy Mineral mapping 3D reconstruction non-ferrous metals EARTH SCIENCE > SOLID EARTH > ROCKS/MINERALS/CRYSTALS > IGNEOUS ROCKS > IGNEOUS ROCK PHYSICAL/OPTICAL PROPERTIES EARTH SCIENCE > SOLID EARTH > ROCKS/MINERALS/CRYSTALS > SEDIMENTARY ROCKS > SEDIMENTARY ROCK PHYSICAL/OPTICAL PROPERTIES Koellner, Nicole GFZ German Research Centre for Geosciences, Potsdam, Germany Dataset https://sciaps.com/libs-handheld-laser-analyzers/ 10.5194/isprsarchives-XL-7-1-2014 10.48440/gfz.b103-22036 CC BY 4.0 This data publication presents data from a solaroptical spectral investigation in the area of the Rammelsberg non-ferrous metal mine in the Harz Mountains near the city of Goslar. The investigation refers to the local communion stone quarry (“Kommunionssteinbruch”) above the former mining area. As this is a nature conservation zone, all measurements were carried out in-situ without any physical sampling action. The field measurements were carried out in June 2019 in cooperation with Bergbau Goslar GmbH and the German Research Centre for Geosciences (GFZ). The data were collected within the research project ReMon (Remote Monitoring of Tailings Using Satellites and Drones, https://www.gfz-potsdam.de/en/section/remote-sensing-and-geoinformatics/projects/remon/) which aims at developing a prototypical monitoring system for mine tailings by using different sensors scaling from satellite- to drone-based.

The data were analysed in the unpublished B.Sc. thesis of Constantin Hildebrand (Hildebrand, 2019). Sixteen different surface materials were determined and examined on-site. Point and imaging hyperspectral data were acquired (with the spectroradiometer PSR+ 3500 operating in the range of 350 - 2500 nm and with the Cubert FireflEYEUHD-185 hyperspectral camera with a range of 450 - 950 nm, respectively), both data sets are presented as spectral libraries. Chemical analyses of the samples were performed by using Laser-Induced Breakdown Spectroscopy (LIBS). LIBS data were collected using a handheld LIBS analyzer, the SciAps Z-300.

In this data publication the different in-situ measurements are presented for each of the sixteen samples. Detailed information about the analysed material, the area of spectral sampling and geochemical analyses are explained in this report and can also be found in the additional Excel® sheet provided with the data.
Study area at Rammelsberg Mine 10.4159 10.4285 51.8882 51.8927

oai:doidb.wdc-terra.org:74092022-07-15T08:56:55ZDOIDBDOIDB.GFZ

false4DOIDB.GFZ 10.5880/GFZ.3.1.2021.005 Webb, Peter Peter Webb 0000-0003-2467-5953 Formerly of the Department of Environment, Earth and Ecosystems, The Open University, Walton Hall, Milton Keynes, MK7 6AA, UK Wiedenbeck, Michael Michael Wiedenbeck GFZ German Research Centre for Geosciences, Potsdam, Germany Glodny, Johannes Johannes Glodny 0000-0002-7812-5933 GFZ German Research Centre for Geosciences, Potsdam, Germany GFZ Data Services 2021 G-Chron 2019 geochronology EARTH SCIENCE > SOLID EARTH > GEOCHEMISTRY Wiedenbeck, Michael GFZ German Research Centre for Geosciences, Potsdam, Germany Dataset 10.48440/GFZ.b103-21061 DOI of paper when available 10.1021/ac00238a002 10.1016/0012-821X(77)90060-7 CC BY 4.0 This data publication consists of two parts:
(1) the questionnaire for round 1 of the G-Chron proficiency test as provided to the participating laboratories via the on-line data submission portal, and
(2) the complete data set of submitted results.
The results of the survey are published as Scientific Technical Report - Data (STR 21/06, Webb et al., 2020).

The questionnaire is structured into distinct segments. The first “metadata segment” allowed each laboratory to report key parameters describing their analytical technique. This part was structured as five independent tracks based on laboratory technique: isotope dilution thermal ionization mass spectrometry (ID-TIMS), secondary ion mass spectrometry (SIMS), laser ablation inductively coupled sector field mass spectrometry (LA-ICP-MS: SF), laser ablation inductively coupled quadrupole / time-of-flight mass spectrometry (LA-ICP-MS: Quad&ToF), and “other”. When reporting results a given laboratory was to select a single one of these options and then was provided a series of questions relevant to that specific method. The second segment of the questionnaire was provided to all laboratories for them to submit their determined age results. The on-line portal required submission of the determined age and uncertainty for both the 206Pb/238U and 207Pb/206Pb chronometers. Submission of results for the 208Pb/232Th chronometer was optional.

Both the April 2020 report and the subsequent manuscript for publication are based on the table that forms the second part of this document. This contains both the reported age values and information about key aspects of each laboratory’s analytical method. In a small number of cases the input data were corrupted due to an apparent incompatibility between the data portal and the character set used by the submitting laboratory. Where the intent of the laboratory reporting was obvious these have been corrected. For two of the reporting laboratories there a software malfunction resulted in their submissions being classified as “other technique”. These data have now been reassigned to their correct technique categories, but the report has not been accordingly modified. All age values are in Ma. The software specified that uncertainty values should be reported as 1s or 1SE, depending on the nature of the value being addressed, though in a number of instances this instruction appears not to have been applied.

oai:doidb.wdc-terra.org:76532022-12-21T11:23:44ZDOIDBDOIDB.CRC1211

false4DOIDB.CRC1211 10.5880/CRC1211DB.55 Walk, Janek Janek Walk RWTH Aachen, Department of Geography Schulte, Philipp Philipp Schulte RWTH Aachen, Department of Geography Bartz, Melanie Melanie Bartz University of Cologne, Institute of Geography Binnie, Ariane Ariane Binnie University of Cologne, Institute of Geology and Mineralogy Kehl, Martin Martin Kehl University of Cologne, Institute of Geography Mörchen, Ramona Ramona Mörchen University of Bonn, Institute of Crop Science and Resource Conservation (INRES) Sun, Xiaolei Xiaolei Sun Research Center Jülich, Institute of Bio- and Geosciences: Agrosphere (IBG-3) Stauch, Georg Georg Stauch https://orcid.org/0000-0002-8046-140X RWTH Aachen, Department of Geography Tittmann, Christopher Christopher Tittmann RWTH Aachen, Department of Geography Bol, Roland Roland Bol Research Center Jülich, Institute of Bio- and Geosciences: Agrosphere (IBG-3) Brückner, Helmut Helmut Brückner University of Cologne, Institute of Geography Lehmkuhl, Frank Frank Lehmkuhl RWTH Aachen, Department of Geography CRC1211 Database (CRC1211DB) 2022 Environment Soil Sciences Geomorphology Biogeochemistry of Soils Arid Zone Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659 CRC 1211 Earth - Evolution at the Dry Limit 15.12.2022 16.03.2018 17.03.2018 19.03.2018 20.03.2018 26.03.2018 24.08.2018 en Data table 1 Datasets CSV 1 [Creative Commons] Attribution-NonCommercial 4.0 International This dataset contains proportions of grain size classes, the median grain size, and the differential grain size distribution for the size fraction 40–311 nm of 32 soil samples sieved to <2 mm from 16 shallow soil profiles, which were sampled in two depth intervals (0–15 and 15–30 cm). Constituting a soil chronosequence at the south-central coast of the Atacama Desert, four shallow soil profiles were sampled from each of the four morphostratigraphic units of the coastal alluvial fan Paposo (25.03°S/70.47°W). Particle size measurements were conducted using laser diffraction analysis. Results are stored in a .csv table. Chile -70.47 -25.03

oai:doidb.wdc-terra.org:76542022-12-25T20:14:43ZDOIDBDOIDB.FID

false4DOIDB.FID 10.5880/fidgeo.2022.037 Heubeck, Christoph Christoph Heubeck 0000-0002-2632-2644 Friedrich-Schiller-Universität Jena, Department of Geosciences, Jena, Germany Thomsen, Tonny B. Tonny B. Thomsen 0000-0002-6233-7974 The Geological Survey of Denmark and Greenland (GEUS), Copenhagen, Denmark Heredia, Benjamin D. Benjamin D. Heredia 0000-0002-4625-2321 The Geological Survey of Denmark and Greenland (GEUS), Copenhagen, Denmark Zeh, Armin Armin Zeh 0000-0001-5599-7897 KIT - Karlsruher Institut für Technologie, Institut für Angewandte Geowissenschaften, Karlsruhe, Germany Balling, Philipp Philipp Balling 0000-0002-8439-6369 Friedrich-Schiller-Universität Jena, Department of Geosciences, Jena, Germany GFZ Data Services 2022 Archean Barberton Greenstone Belt Malolotsha Moodies Group klippe Eswatini LA-ICP-MS U-Pb zircon dating zircon EARTH SCIENCE > SOLID EARTH > ROCKS/MINERALS/CRYSTALS > AGE DETERMINATIONS EARTH SCIENCE > SOLID EARTH > ROCKS/MINERALS/CRYSTALS > MINERALS > MINERAL AGE DETERMINATIONS Heubeck, Christoph Friedrich-Schiller-Universität Jena, Department of Geosciences, Jena, Germany Dataset 10.1029/2022TECT21828 10.1016/j.chemgeo.2004.01.003 10.1016/j.epsl.2006.06.039 10.1016/j.chemgeo.2008.03.005 10.1126/science.1215507 10.1016/j.chemgeo.2004.06.017 10.1029/2009GC002618 10.1039/C1JA10172B 10.1111/j.1751-908X.2012.00158.x 10.1111/ggr.12167 10.1016/j.chemgeo.2007.11.005 10.1016/0012-821X(75)90088-6 10.1016/j.gsf.2018.04.001 10.5194/gchron-3-247-2021 10.1111/j.1751-908X.1995.tb00147.x 10.1111/j.1751-908X.2004.tb01041.x CC BY 4.0 The southern margin of the Barberton Greenstone Belt in Eswatini limits one of the world’s oldest well-preserved sedimentary and volcanic sequences, 3.57 to 3.2 Ga old. In a segment along that margin, older mafic and ultramafic volcanic rocks were thrust over the youngest strata (quartz-rich sandstones and conglomerates) before being folded and imbricated in thrust slices. Samples described in this publication comprise tabular data of (1) sample locations and crystallization ages of zircons which were extracted from thin tuffaceous units in the thrust sheet, (2) analytical data from laser ablation – inductively coupled plasma – mass spectrometry (LA-ICP-MS), supporting these ages, and (3) quantitative measurements of ductily deformed conglomerate clasts. Field data were collected 2012-2019; U-Pb analyses performed in 2020. The data presented here are the basis for geological maps and cross sections, and are visualized as concordia diagrams form part of in the related publication (Heubeck et al.. 2023).
Malolotsha Syncline at the southern margin of theBarberton Greenstone Belt in Eswatini Swaziland) 31.0395 31.1116 -26.1897 -26.0686

oai:doidb.wdc-terra.org:77802023-08-15T07:49:01ZDOIDBDOIDB.GFZ

false4DOIDB.GFZ 10.5880/GFZ.3.1.2022.004 Rieger, Philip Philip Rieger 0000-0001-7888-0077 iCRAG is the SFI Research Centre in Applied Geosciences, Dublin, Ireland GFZ German Research Centre for Geosciences, Potsdam, Germany Magnall, Joseph M. Joseph M. Magnall 0000-0002-7868-3038 GFZ German Research Centre for Geosciences, Potsdam, Germany Gleeson, Sarah A. Sarah A. Gleeson 0000-0002-5314-4281 GFZ German Research Centre for Geosciences, Potsdam, Germany Oelze, Marcus Marcus Oelze 0000-0002-3950-6629 Bundesanstalt für Materialforschung, Berlin, Germany GFZ German Research Centre for Geosciences, Potsdam, Germany GFZ Data Services 2022 pyrite trace element geochemistry CD-type massive sulphide deposit SEDEX massive sulphide deposit hydrothermal alteration hydrothermal ore formation Proterozoic sedimentary basin Mount Isa George Fisher Carpentaria Province EARTH SCIENCE > SOLID EARTH > GEOCHEMISTRY Rieger, Philip GFZ German Research Centre for Geosciences, Potsdam, Germany Dataset 10.3389/feart.2023.892759 10.1039/C1JA10172B 10.1007/s00126-021-01056-1 10.1111/j.1751-908X.2007.00104.x CC BY 4.0 Trace element (TE) analysis of pyrite via LA-ICP-MS can produce large, paragenetically-constrained datasets, which can be used to reconstruct the conditions of pyrite formation in complex mineral systems. The Carpentaria province in northern Australia is host to some of the world’s highest value Zn-Pb (+Ag, Cu) deposits. The genesis of many of these deposits in the southern part of the province is controversial due to tectonic overprinting, with competing models of single- vs. multi-stage ore formation.

In this study, LA-ICP-MS analysis of pyrite from the George Fisher Zn-Pb-Ag deposit and correlative unmineralized host rocks has been combined with paragenetic and whole rock lithogeochemical data. Paragenetically constrained pyrite TE data were then evaluated in the context of single- vs. multi-stage ore formation models and compared with recent data from undeformed clastic-dominated (CD-type) deposits of the northern Carpentaria province. Pre-ore diagenetic pyrite is compositionally similar to other Proterozoic diagenetic pyrite, with some evidence of minor hydrothermal anomalism that could help define distal alteration, but requires further analysis. Pyrite from the different ore stages is compositionally distinct, consistent with a multi-stage system. Ore stage 1 pyrite has high concentrations of Cu, Zn, As, Ag, Sb, Tl, and Pb as well as high Co/Ni ratios, whereas ore stage 2 pyrite contains Ni and Co, and ore stage 3 pyrite is dominated by Co with lesser concentrations of Ni and Cu. Ore stage 1 pyrite has a similar composition to hydrothermal pyrite in the undeformed northern Carpentaria CD-type deposits and likely formed syn-diagenesis. Ore stage 2 was syn-deformation, and resulted in replacement and recrystallization of pre-existing pyrite that also resulted in the expulsion of incompatible TEs. Ore stage 3 formed via a later Cu mineralizing event that resulted in a new geochemically distinct generation of Co-rich pyrite. This study demonstrates the value of pargenetically-constrained pyrite TE data for refining genetic models in complex sediment hosted mineral systems.

This data publication includes pyrite trace element compositions (in ppm) of 28 samples from the un-mineralized Urquhart Shale Formation and from the George Fisher deposit. Access to drill cores was granted by Mount Isa Mines (MIM) George Fisher operation and Mount Isa Mines Resource Development.
George Fisher deposit (Mount Isa, Australia)

oai:doidb.wdc-terra.org:68182023-10-04T11:10:49ZDOIDBDOIDB.ICGEM

false4DOIDB.ICGEM 10.5880/ICGEM.2019.008 Weigelt, Matthias Matthias Weigelt Leibniz University Hannover, Hannover, Germany Time series of monthly combined HLSST and SLR gravity field models to bridge the gap between GRACE and GRACE-FO: QuantumFrontiers_HLSST_SLR_COMB2019s GFZ Data Services 2019 HLSST SLR gravity field model variance component estimation ICGEM Geodesy satellite laser ranging temporal gravity model EARTH SCIENCE > SOLID EARTH > GEODETICS > GEOID CHARACTERISTICS EARTH SCIENCE > SOLID EARTH > GRAVITY/GRAVITATIONAL FIELD > GRAVITY Ince, Elmas Sinem Elmas Sinem Ince 0000-0002-3393-1392 GFZ German Research Centre for Geosciences, Potsdam, Germany Reißland, Sven Sven Reißland 0000-0001-6293-5336 GFZ German Research Centre for Geosciences, Potsdam, Germany eng Dataset 10.1029/2011JB008916 https://www.geoq.uni-hannover.de/383.html 10.1002/jgrb.50283 1 Files application/octet-stream CC BY 4.0 QuantumFrontiers_HLSST_SLR_COMB2019s is a series of monthly gravity field models based on high-low satellite-to-satellite (HLSST) tracking and satellite laser ranging (SLR) data up to degree and order 60. The combination of HLSST and SLR data is done on the normal equation level using Variance Component Estimation. The series spans from 2003 to 2018 and thus covers the entire period between GRACE and GRACE Follow-On. It is therefore a prime candidate to bridge the data gap between these two satellite mission considering long-wavelength features on a global scale. The model has been developed with data contributions from the Astronomical Institute, University Bern (AIUB), the Institute of Geodesy, Theoretical Geodesy and Satellite Geodesy, Graz University of Technology, the Institute for Geodesy, Leibniz University Hannover and the European Space Agency. More details on the processing can be found in "Time-Variable Gravity Signal in Greenland Revealed by High-Low Satellite-to-Satellite Tracking" (Weigelt et al, 2013, https://doi.org/10.1002/jgrb.50283) Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC-2123 QuantumFrontiers – 390837967. -180 180 -90 90 Deutsche Forschungsgemeinschaft http://doi.org/10.13039/501100001659 EXC-2123/1 CRC 1128: Relativistic Geodesy and Gravimetry with Quantum Sensors (geo-Q)

oai:doidb.wdc-terra.org:61612023-10-04T13:06:15ZDOIDBDOIDB.ICGEM

false4DOIDB.ICGEM 10.5880/icgem.2016.002 Ries, J. Center for Space Research The University of Texas at Austin, US Bettadpur, S. Center for Space Research The University of Texas at Austin, U Eanes, R. Center for Space Research The University of Texas at Austin, U Kang, Z. Center for Space Research The University of Texas at Austin, U Ko, U. Center for Space Research The University of Texas at Austin, US McCullough, C. Center for Space Research The University of Texas at Austin, US Nagel, P. Center for Space Research The University of Texas at Austin, US Pie, N. Center for Space Research The University of Texas at Austin, US Poole, S. Center for Space Research The University of Texas at Austin, US Richter, T. Center for Space Research The University of Texas at Austin, US Save, H. Center for Space Research The University of Texas at Austin, US Tapley, B. Center for Space Research The University of Texas at Austin, US The Combined Gravity Model GGM05C GFZ Data Services 2016 ICGEM global gravitational model GRACE GOCE Ries, J. Center for Space Research The University of Texas at Austin, US Ries, J. Center for Space Research The University of Texas at Austin, US Bettadpur, S. Center for Space Research The University of Texas at Austin, U Bettadpur, S. Center for Space Research The University of Texas at Austin, U Eanes, R. Center for Space Research The University of Texas at Austin, U Kang, Z. Center for Space Research The University of Texas at Austin, U Ko, U. Center for Space Research The University of Texas at Austin, US McCullough, C. Center for Space Research The University of Texas at Austin, US Nagel, P. Center for Space Research The University of Texas at Austin, US Pie, N. Center for Space Research The University of Texas at Austin, US Poole, S. Center for Space Research The University of Texas at Austin, US Richter, T. Center for Space Research The University of Texas at Austin, US Save, H. Center for Space Research The University of Texas at Austin, US Tapley, B. Center for Space Research The University of Texas at Austin, US Barthelmes, Franz GFZ German Research Centre for Geosciences, Potsdam, Germany Reißland, Sven GFZ German Research Centre for Geosciences, Potsdam, Germany eng Dataset ftp://ftp.csr.utexas.edu/pub/grace/GGM05/README_GGM05C.pdf ftp://podaac.jpl.nasa.gov/allData/grace/docs/L2-CSR0005_ProcStd_v4.0.pdf 10.1007/1345_2015_182 1734765 Bytes 3 Files application/octet-stream application/octet-stream application/octet-stream CC BY 4.0 GGM05C is an unconstrained global gravity model complete to degree and order 360 determined from 1) GRACE K-band intersatellite range-rate data, GPS tracking and GRACE accelerometer data, 2) GOCE gradiometer data (ZZ+YY+XX+XZ) spanning the entire mission using a band pass filter of 10-50 mHz and polar gap filled with synthetic gradients from GGM05S to degree/order 150 evaluated at 200-km altitude, and 3) terrestrial gravity anomalies from DTU13 (Andersen et al., 2014). The value for C20 has been replaced with a value derived from satellite laser ranging. No rate terms were modeled. For additional details on the background modeling, see the CSR RL05 processing standards document available at ftp://podaac.jpl.nasa.gov/allData/grace/docs/L2-CSR0005_ProcStd_v4.0.pdf (Bettadpur 2012). Detailed information about GGM05C is available at ftp://ftp.csr.utexas.edu/pub/grace/GGM05/README_GGM05C.pdf (Ries et al., 2016). -180 180 -90 90

oai:doidb.wdc-terra.org:77522023-11-13T17:32:19ZDOIDBDOIDB.FID

false4DOIDB.FID 10.5880/fidgeo.2022.029 Reitano, Riccardo Riccardo Reitano 0000-0002-6295-5588 Department of Science, University of Rome “Roma TRE”, Laboratory of Experimental Tectonics, Rome, Italy Clementucci, Romano Romano Clementucci 0000-0003-2332-5812 Department of Science, University of Rome “Roma TRE”, Laboratory of Experimental Tectonics, Rome, Italy Conrad, Ethan M. Ethan M. Conrad 0000-0002-4958-7274 Department of Geological Sciences, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX, USA Corbi, Fabio Fabio Corbi 0000-0003-2662-3065 National Research Council - CNR, Istituto di Geologia Ambientale e Geoingegneria, Italy Lanari, Riccardo Riccardo Lanari 0000-0002-8304-6367 Department of Earth Science, University of Florence, Florence, Italy Faccenna, Claudio Claudio Faccenna 0000-0003-0765-4165 Department of Science, University of Rome “Roma TRE”, Laboratory of Experimental Tectonics, Rome, Italy GFZ German Research Centre for Geosciences, Potsdam, Germany Bazzucchi, Chiara Chiara Bazzucchi 0000-0003-1003-2746 Department of Science, University of Rome “Roma TRE”, Laboratory of Experimental Tectonics, Rome, Italy GFZ Data Services 2022 Erosional laws Analogue modelling Tectonic geomorphology EPOS multi-scale laboratories analogue models of geologic processes property data of analogue modelling materials EARTH SCIENCE > CLIMATE INDICATORS > ATMOSPHERIC/OCEAN INDICATORS > PRECIPITATION INDICATORS > PRECIPITATION VARIABILITY EARTH SCIENCE > LAND SURFACE > GEOMORPHOLOGY > FLUVIAL LANDFORMS/PROCESSES EARTH SCIENCE > LAND SURFACE > GEOMORPHOLOGY > TECTONIC LANDFORMS/PROCESSES EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES EARTH SCIENCE > SOLID EARTH > GEOMORPHIC LANDFORMS/PROCESSES > TECTONIC LANDFORMS > MOUNTAINS hydrosphere > hydrologic cycle > hydrographic network Reitano, Riccardo Riccardo Reitano 0000-0002-6295-5588 Department of Science, University of Rome “Roma TRE”, Laboratory of Experimental Tectonics, Rome, Italy Reitano, Riccardo Riccardo Reitano 0000-0002-6295-5588 Department of Science, University of Rome “Roma TRE”, Laboratory of Experimental Tectonics, Rome, Italy Reitano, Riccardo Riccardo Reitano 0000-0002-6295-5588 Department of Science, University of Rome “Roma TRE”, Laboratory of Experimental Tectonics, Rome, Italy Reitano, Riccardo Department of Science, University of Rome “Roma TRE”, Laboratory of Experimental Tectonics, Rome, Italy Dataset 10.5194/esurf-11-731-2023 https://tel.archives-ouvertes.fr/tel-03630297/document 10.3390/geosciences11100412 10.1016/j.crte.2008.01.005 10.1016/j.tecto.2011.09.029 10.1016/j.tecto.2016.04.016 10.1029/2020TC006515 10.5194/esurf-8-973-2020 10.1029/2021TC006951 10.1016/j.geomorph.2016.02.022 10.5194/esurf-2-1-2014 10.1016/j.geomorph.2015.02.011 CC BY 4.0 This dataset includes raw data used in the paper by Reitano et al. (2022), focused on the effect of imposed boundary conditions (regional slope and rainfall rate) on the morphological evolution of analogue landscapes; the paper also focuses on applicability of stream power laws on analogue models, defining if and how the parametrization used in natural landscapes works in analogue ones. The experiments have been carried out at Laboratory of Experimental Tectonics (LET), University “Roma Tre” (Rome).

Detailed descriptions of the experimental apparatus and experimental procedures implemented can be found in the paper to which this dataset refers.

Here we present:
• Pictures recording the evolution of the models.
• GIFs showing time-lapses of models.
• Raw DEMs of the models, used for extracting data later discusses in the paper.
• Raw channels data (.mat files).
We took digital images during the evolution of the experiments. These images are stored in the “2022_029_Reitano-et-al_Pictures_and_GIFs” folder.

Digital Images The qualitative evolution of the analogue models has been recorded using a digital top-view camera (Canon EOS 200D). Digital pictures have not been modified with other imaging software.
Data from models' surface Laser scan provides a point cloud, composed by x, y, z coordinated of the points composing the model surface (the number of points is function of the laser resolution). The laser scans are converted to raw DEMs, here stored in the “DEMs” folder. Bottom left corner in the DEMs is randomly chosen to be -70 ∙ 103 m. No data values equal to -9999. Cell size is 1 mm. Channels data are collected into “Channels” folder. These data are .png channel longitudinal profiles and StreamOBJ files (.mat, TopoToolbox) containing all channels information. For every model and for every chosen time step (see Supplementary Information of the paper), we selected four rivers. These rivers are plotted together at the same time step.

Eroded volumes and Incision rates We create a numeric regular grid on the model surface. The eroded volumes are extracted calculating the cumulative difference in elevation (Δz) of the same cells at consecutive times. The cells dimension is function of the horizontal resolution of the laser scan (here 0.05 mm). Knowing the cell dimensions and the corresponding Δz, is it possible to obtain the total volume of eroded material at every time step. Incision rates are computed finding the value of incision for every point forming the selected channels. These values of incision are then divided for the time step at which they are collected, obtaining the incision rate through time.

oai:doidb.wdc-terra.org:78382024-02-14T19:07:32ZDOIDBDOIDB.GFZ

false4DOIDB.GFZ 10.5880/GFZ.1.4.2023.003 Brell, Maximilian Maximilian Brell 0000-0002-3759-7483 GFZ German Research Centre for Geosciences, Potsdam, Germany Roessner, Sigrid Sigrid Roessner 0000-0002-6940-9694 GFZ German Research Centre for Geosciences, Potsdam, Germany Dietze, Michael Michael Dietze 0000-0001-6063-1726 Georg-August-University, Göttingen, Germany Bell, Rainer Rainer Bell University of Bonn, Bonn, Germany Magnussen, Sylvia Sylvia Magnussen GFZ German Research Centre for Geosciences, Potsdam, Germany Schreck, Dana Dana Schreck MILAN Geoservice GmbH, Spremberg, Germany Jany, Sven Sven Jany MILAN Geoservice GmbH, Spremberg, Germany Ozturk, Ugur Ugur Ozturk 0000-0002-7641-4344 GFZ German Research Centre for Geosciences, Potsdam, Germany Merz, Bruno Bruno Merz 0000-0002-5992-1440 GFZ German Research Centre for Geosciences, Potsdam, Germany Thieken, Annegret Annegret Thieken 0000-0001-7068-2615 GFZ German Research Centre for Geosciences, Potsdam, Germany GFZ Data Services 2023 Airborne Laser Scanning ALS Orthophoto Eifel Flood 2021 Disaster mapping EARTH SCIENCE > HUMAN DIMENSIONS > NATURAL HAZARDS > FLOODS Brell, Maximilian Maximilian Brell 0000-0002-3759-7483 GFZ German Research Centre for Geosciences, Potsdam, Germany Brell, Maximilian Maximilian Brell 0000-0002-3759-7483 GFZ German Research Centre for Geosciences, Potsdam, Germany Brell, Maximilian Maximilian Brell 0000-0002-3759-7483 GFZ German Research Centre for Geosciences, Potsdam, Germany Roessner, Sigrid Sigrid Roessner 0000-0002-6940-9694 GFZ German Research Centre for Geosciences, Potsdam, Germany Dietze, Michael Michael Dietze 0000-0001-6063-1726 Georg-August-University, Göttingen, Germany Dietze, Michael Michael Dietze 0000-0001-6063-1726 Georg-August-University, Göttingen, Germany Bell, Rainer Rainer Bell University of Bonn, Bonn, Germany Schreck, Dana Dana Schreck MILAN Geoservice GmbH, Spremberg, Germany Jany, Sven Sven Jany MILAN Geoservice GmbH, Spremberg, Germany Ozturk, Ugur Ugur Ozturk 0000-0002-7641-4344 GFZ German Research Centre for Geosciences, Potsdam, Germany Brell, Maximilian GFZ German Research Centre for Geosciences, Potsdam, Germany Magnussen, Sylvia Dataset 10.5194/nhess-22-3005-2022 10.5194/nhess-14-279-2014 10.5194/nhess-22-1845-2022 https://www.dwd.de/DE/leistungen/besondereereignisse/niederschlag/ https://www.worldweatherattribution.org/wp-content/uploads/Scientific-report-Western-Europe-floods-2021-attribution.pdf 10.1002/hyp.1456 10.5194/nhess-23-973-2023 https://www.hywa-online.de/?p=5910# https://gfzpublic.gfz-potsdam.de/pubman/item/item_5022148 CC BY 4.0 The GFZ Potsdam HART (Hazard and Risk Team) in cooperation with the DFG research training group 2043 NatRiskChange at Potsdam University has enabled the acquisition of Airborne Laser Scanning (ALS) and high-resolution optical data which were acquired between 22 September 2021 and 24 October 2021 by the Milan Geoservice company, Spremberg, Germany. This data acquisition took place in the Eifel regions of North Rhine-Westphalia (NRW) and Rhineland-Palatinate (RLP), which were hit by the 14 July 2021 precipitation event leading to widespread severe inundations, flash floods and caused around 185 victims and massive damage to settlements, river geometry and other geomorphic features. The high-resolution ALS and optical data acquisitions aimed at the documentation and quantification of the extent of flood related changes and destructions as well as their reappraisal before diffusion erases traces. Thus, the generated data are valuable for forensic event analysis and future attempts on flood forecasting and warning in the context of scientific and practical purposes.
Eifel Flood 2021 - area of Airborne Laser Scanning (ALS) and Orthophoto data 6.37195 7.3121 50.1868 50.7155

oai:doidb.wdc-terra.org:78832024-03-06T15:56:52ZDOIDBDOIDB.FID

false4DOIDB.FID 10.5880/fidgeo.2023.051 Baneschi, Ilaria Ilaria Baneschi 0000-0001-6924-1599 Istituto di Geoscienze e Georisorse (IGG) – Consiglio Nazionale delle Ricerche (CNR), Pisa, Italy Furlanetto, Nicola Nicola Furlanetto Dipartimento di Scienze Agrarie, Alimentari ed Agro-Ambientali (DISAAA-a), Università di Pisa, Pisa, Italy Boschi, Chiara Chiara Boschi 0000-0001-8972-4432 Istituto di Geoscienze e Georisorse (IGG) – Consiglio Nazionale delle Ricerche (CNR), Pisa, Italy Pellegrini, Ferdinando Ferdinando Pellegrini Group of Agroecology, Institute of Life Sciences, Scuola Superiore Sant’Anna, Pisa, Italy Antichi, Daniele Daniele Antichi 0000-0002-5520-2510 Dipartimento di Scienze Agrarie, Alimentari ed Agro-Ambientali (DISAAA-a), Università di Pisa, Pisa, Italy Barberi, Paolo Paolo Barberi 0000-0003-1266-7024 Group of Agroecology, Institute of Life Sciences, Scuola Superiore Sant’Anna, Pisa, Italy GFZ Data Services 2024 EPOS multi-scale laboratories geochemistry and microscopy geochemistry data EARTH SCIENCE > BIOSPHERE > VEGETATION > NITROGEN Laboratory of Geochemistry and Stable Isotope (IGG-CNR, Italy) 9663fcbde23eac71f07cd28ac73e9cc0 IGG-CNR Baneschi, Ilaria Istituto di Geoscienze e Georisorse (IGG) – Consiglio Nazionale delle Ricerche (CNR), Pisa, Italy Dataset CC BY 4.0 Intercropping is the simultaneous growth of two or more crops in the same space for a significant part of their life cycle (Willey, 1979). In this context, samples from one farm experiments in the growing season 2015/2016 and 2016/2017, embedded in the cropping systems of one arable farm in the surrounding of Pisa, central-western part of Italy, were collected for analysis. The treatments were: PCW, a temporary intercropping system of wheat and persian clover, sown in paired rows; CONTROLSTRIP, unfertilized wheat as a sole crop, sown in paired rows.
The samples were collected from a farm located in Valtriano, around 20 km from Pisa (43°36’N 10°29’E). The temporary intercropping system comprises common wheat (Triticum aestivum L., cv. Bolero) and persian clover (Trifolium resupinatum L., cv. Laser). Sampling of above-ground plant biomass was done by hands in March 2016 and 2017. For each treatment, above-ground plant biomass was collected several plots which includes three subplots with dimension of 0.25m2 in 2016 and 0.075 m2 in 2017. The samples collected, only for the green part of the plant, were dried at 60°C for 48 h. Then, coarse grinding of the plant fibres (about 1 mm in diameter) was carried out, followed by further cryogenic grinding.
Sample location on a farm in Valtriano

oai:doidb.wdc-terra.org:66512024-05-15T11:59:30ZDOIDBDOIDB.GFZ

false4DOIDB.GFZ 10.5880/GFZ.GRAVIS_06_C20_SLR König, Rolf Rolf König 0000-0002-7155-6976 GFZ German Research Centre for Geosciences, Potsdam, Germany Schreiner, Patrick Patrick Schreiner GFZ German Research Centre for Geosciences, Potsdam, Germany Dahle, Christoph Christoph Dahle 0000-0002-4733-9242 GFZ German Research Centre for Geosciences, Potsdam, Germany Monthly estimates of C(2,0) generated by GFZ from SLR satellites based on GFZ GRACE/GRACE-FO RL06 background models GFZ Data Services 2019 Earth flattening SLR Satellite Laser Ranging Gravity Recovery And Climate Experiment (GRACE) GRACE-FO Gravitational Field GSM Geopotential Gravity Field Time Variable Gravity Satellite Geodesy EARTH SCIENCE > SOLID EARTH > GRAVITY/GRAVITATIONAL FIELD > GRAVITATIONAL FIELD EARTH SCIENCE > SOLID EARTH > GRAVITY/GRAVITATIONAL FIELD > GRAVITY eng Dataset 10.5880/GFZ.GRACE_06_GSM 1 Files application/octet-stream 1.0 CC BY 4.0 As a convenience to users who wish to use a replacement value for C(2,0) of GFZ's GRACE/GRACE-FO RL06 GSM products, a monthly GFZ C(2,0) estimate time series is provided. These estimates are obtained from the analysis of Satellite Laser Ranging (SLR) data to the following five geodetic satellites: LAGEOS-1 and 2, Starlette, Stella and Ajisai. Starting from March 2012, the LARES satellite is added so that six geodetic satellites are included. The individual satellites are combined on normal equation level using relative weights which are based on a variance component estimation. Gravity field coefficients up to degree and order 5 plus coefficients C(6,1) and S(6,1) have been simultaneously solved together with all other (non-gravity) parameters. The background models used in the SLR analysis is consistent with the GFZ GRACE/GRACE-FO RL06 processing, including the use of the same Atmosphere-Ocean De-aliasing product AOD1B RL06. IMPORTANT REMARKS: It is advised to use these estimates to replace the C(2,0) values from the GFZ RL06 GSM files. These estimates are not intended to be used with the GRACE RL05 or earlier products. This data set is regularly updated in order to extend the time series on an operational basis. As long as the version number has not changed, all previously available data records have not been changed! See line 'UPDATE HISTORY' in the header of the data file for details about the current time span and version. SPECIAL NOTES: C(2,0) estimates are provided continuously for each month. However, the SLR data was processed in 7-day batches aligned to GPS weeks. Several weekly SLR normal equations were then accumulated to obtain a monthly solution; GPS weeks covering two calendar months were assigned to that calendar month where the majority of days within the week belong to. Thus, the beginning date for these 'monthly' solutions does not necessarily match the first day of a calendar month, but will be within a few days of that corresponding date. Moreover, in most cases, a different number of days was used for the SLR solution than for the corresponding GRACE/GRACE-FO solution. For particular periods, the GRACE/GRACE-FO solutions might span significantly less than one month or cover more than one calendar month. In these cases, a specially dedicated SLR estimate was generated which is based on approximately the same interval so that the epoch of the SLR estimate is close to the epoch of the GRACE/GRACE-FO solution. To distinguish the different cases of C(2,0) estimates mentioned above (monthly vs. specially dedicated) and to easily recognize whether a C(2,0) estimate matches an existing GRACE/GRACE-FO solution, the following flags are appended to each data record:- ' m': C(2,0) estimate represents a monthly solution for a month where no GRACE/ GRACE-FO solution is available.- 'Gm': C(2,0) estimate represents a monthly solution and a corresponding GRACE/ GRACE-FO solution is available.- 'G*': C(2,0) estimate is specially dedicated for a GRACE/GRACE-FO solution as described above; the effective period of data used is additionally provided by a string '<yymmdd>_<YYMMDD>'.

oai:doidb.wdc-terra.org:80292025-01-17T14:09:35ZDOIDBDOIDB.DIGIS

false4DOIDB.DIGIS 10.5880/digis.2024.005 Shuaijie, Liu Liu Shuaijie 0000-0003-2939-6989 State Key Laboratory of Ore Deposit Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, Guizhou, China Mei-Fu, Zhou Zhou Mei-Fu State Key Laboratory of Ore Deposit Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, Guizhou, China Yang, Sun Sun Yang School of Geosciences, Yangtze University, Wuhan, Hubei 430100, China Wenjing, Li Li Wenjing Department of Earth and Space Sciences, Southern University of Science and Technology, Shenzhen 518055, Guangdong, China Bin, Chen Chen Bin 0000-0001-7694-9341 Department of Earth and Space Sciences, Southern University of Science and Technology, Shenzhen 518055, Guangdong, China Guochun, Zhao Zhao Guochun Department of Earth Sciences, The University of Hong Kong, Hong Kong, China GFZ Data Services 2024 Apatite; Li-mineralized pegmatites; Barren pegmatites; Ke’eryin; eastern Tibetan Plateau EARTH SCIENCE > SOLID EARTH > GEOCHEMISTRY Shuaijie, Liu Liu Shuaijie 0000-0003-2939-6989 State Key Laboratory of Ore Deposit Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, Guizhou, China Shuaijie, Liu Liu Shuaijie 0000-0003-2939-6989 State Key Laboratory of Ore Deposit Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, Guizhou, China Mei-Fu, Zhou Zhou Mei-Fu State Key Laboratory of Ore Deposit Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang 550081, Guizhou, China Yang, Sun Sun Yang School of Geosciences, Yangtze University, Wuhan, Hubei 430100, China Wenjing, Li Li Wenjing Department of Earth and Space Sciences, Southern University of Science and Technology, Shenzhen 518055, Guangdong, China Bin, Chen Chen Bin 0000-0001-7694-9341 Department of Earth and Space Sciences, Southern University of Science and Technology, Shenzhen 518055, Guangdong, China Guochun, Zhao Zhao Guochun Department of Earth Sciences, The University of Hong Kong, Hong Kong, China Shuaijie, Liu Liu Shuaijie State Key Laboratory of Ore Deposit Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences Shuaijie, Liu Liu Shuaijie State Key Laboratory of Ore Deposit Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences Bin, Chen Chen Bin Shuaijie, Liu State Key Laboratory of Ore Deposit Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences 2099-12-02 2024-12-02 2021-08-11/2024-02-04 Dataset PAPER DOI OR JOURNAL OF MANUSCRIPT SUBMISSION 10.26022/IEDA/112263 https://georoc.eu https://digis.geo.uni-goettingen.de CC BY 4.0 The DIGIS geochemical data repository is a research data repository in the Earth Sciences domain with a specific focus on geochemical data. The repository archives, publishes and makes accessible user-contributed, peer-reviewed research data in standardised form (EarthChem Team, 2022, https://doi.org/10.26022/IEDA/112263) that fall within the scope of the GEOROC database (https://georoc.eu). All submissions of new data will be considered for inclusion in the GEOROC database. It is hosted at GFZ Data Services through a collaboration between the Digital Geochemical Data Infrastructure (DIGIS) for GEOROC 2.0 (https://digis.geo.uni-goettingen.de) and the GFZ German Research Centre for Geosciences.
We report the major and trace elements and Nd isotopic compositions of apatite grains from the Triassic Li-mineralized and barren pegmatites in the Songpan-Ganzi orogen, eastern Tibetan Plateau. The major elements of apatite grains were measured using Electron Microprobe (EMP) at the Hefei University of Technology. The trace elements and Nd isotopic compositions of apatite grains were measured using Inductively Coupled Plasma Mass Spectrometry Laser Ablation (ICP: MS-LA) and Inductively Coupled Plasma Mass Spectrometry Laser Ablation Multicollector (ICP:MS-LA-MC), respectively. at the Wuhan Sample Solution Analytical Technology Co., Ltd., Wuhan, China. The apatite grains from mineralized and barren pegmatites have contrasting MnO, REE, Th and Li concentrations and REE patterns. These data are used to explore how melts that formed the mineralized and barren pegmatites evolved differently. This dataset is a supplementary for the manuscript (ID JPET-Jun-24-0119) submitted to Journal of Petrology.
Triassic; Songpan-Ganzi Orogenic belt, Eastern Tibetan Plateau 101.008 101.994 31.7228 31.7989 National Natural Science Foundation of China http://dx.doi.org/10.13039/501100001809 42030303

oai:doidb.wdc-terra.org:62842025-02-26T09:00:38ZDOIDBDOIDB.ENMAP

false4DOIDB.ENMAP 10.5880/enmap.2017.002 Jarmer, Thomas 0000-0002-4652-1640 University of Osnabrueck, Osnabrueck, Germany Siegmann, Bastian University of Osnabrueck, Osnabrueck, Germany GFZ Data Services 2017 Imaging Spectroscopy Precision Farming Yield Estimation EARTH SCIENCE > AGRICULTURE > SOILS > SOIL TEXTURE EARTH SCIENCE > AGRICULTURE > AGRICULTURAL PLANT SCIENCE > CROP/PLANT YIELDS EARTH SCIENCE > SPECTRAL/ENGINEERING > VISIBLE WAVELENGTHS > VISIBLE IMAGERY EARTH SCIENCE > SPECTRAL/ENGINEERING > INFRARED WAVELENGTHS > INFRARED IMAGERY Foerster, Saskia 0000-0001-7752-7394 GFZ German Research Centre for Geosciences, Potsdam, Germany Küster Theres 0000-0003-0596-5621 GFZ German Research Centre for Geosciences, Potsdam, Germany 2016-11-30 2011-05-10T09:32:18/2011-05-10T11:07:26 2011-06-27T08:35:23/2011-06-27T10:16:44 2012-05-24T09:06:57/2012-05-24T11:12:03 eng Dataset 10.2312/enmap.2017.002 10.3390/rs70708830 10.3390/rs8110927 10.3390/rs71012737 10.1080/01431161.2015.1084438 http://www.enmap.org/?q=flights CC BY-SA 4.0 The dataset is composed of hyperspectral imagery acquired during airplane overflights on May 10th, 2011, June 27th, 2011 and May 24th, 2012 consisting of 367 and 368 spectral bands, respective-ly, ranging from VIS to SWIR (400 - 2500 nm) wavelength regions. The hyperspectral image data was acquired in the framework of the EnMAP preparation project HyLand (Hyperspectral remote sensing for the assessment of crop and soil parameters in precision farming and yield estimation). Within the project, innovative techniques were developed to derive crop and soil parameters from hyper-spectral remote sensing and terrestrial laser scanning data, which served as input parameters for novel yield estimation models. The Environmental Mapping and Analysis Program (EnMAP) is a German hyperspectral satellite mission that aims at monitoring and characterizing the Earth’s environment on a global scale. EnMAP serves to measure and model key dynamic processes of the Earth’s ecosystems by extract-ing geochemical, biochemical and biophysical parameters, which provide information on the status and evolution of various terrestrial and aquatic ecosystems. In the frame of the EnMAP preparatory phase, pre-flight campaigns including airborne and in-situ measurements in different environments and for several application fields are being conducted. The main purpose of these campaigns is to support the development of scientific applications for EnMAP. In addition, the acquired data are input in the EnMAP end-to-end simulation tool (EeteS) and are employed to test data pre-processing and calibration-validation methods. The campaign data are made freely available to the scientific community under a Creative Commons Attribution-ShareAlike 4.0 International License. An overview of all available data is provided in in the EnMAP Flight Campaigns Metadata Portal (http://www.enmap.org/?q=flightbeta). 11.87 11.97 51.77 51.82 Campaign 1, Köthen 11.87 11.97 51.77 51.82 Campaign 2, Köthen 11.84 11.94 51.77 51.88 Campaign 3, Köthen Bundesministerium für Wirtschaft und Energie http://doi.org/10.13039/501100006360

oai:doidb.wdc-terra.org:67532025-03-13T14:53:37ZDOIDBDOIDB.GFZ

false4DOIDB.GFZ 10.5880/GFZ.2.3.2019.006 Rother, Martin Martin Rother GFZ German Research Centre for Geosciences, Potsdam, Germany Michaelis, Ingo Ingo Michaelis GFZ German Research Centre for Geosciences, Potsdam, Germany CH-ME-2-FGM-SCI - CHAMP 50 Hz Magnetic Field Vector Time Series in Sensor- and ECEF-(NEC)-System (Level 2) GFZ Data Services 2019 CHAMP magnetic field vector data level 2 Earth Observation Satellites > CHAMP Earth Remote Sensing Instruments > Passive Remote Sensing > Positioning/Navigation > ACS Earth Remote Sensing Instruments > Passive Remote Sensing > Magnetic Field/Electric Field Instruments > MAGNETOMETERS Solar/Space Observing Instruments > Magnetic Field/Electric Field Instruments > FGM EARTH SCIENCE > SOLID EARTH > GEOMAGNETISM > MAGNETIC FIELD Rother, Martin Martin Rother GFZ German Research Centre for Geosciences, Potsdam, Germany Michaelis, Ingo Ingo Michaelis GFZ German Research Centre for Geosciences, Potsdam, Germany Michaelis, Ingo Ingo Michaelis GFZ German Research Centre for Geosciences, Potsdam, Germany Rauberg, Jan Jan Rauberg GFZ German Research Centre for Geosciences, Potsdam, Germany 2000/2010 en 10.2312/GFZ.b103-19104 https://isdc.gfz-potsdam.de/champ-isdc/ 1 Files application/octet-stream CC BY 4.0 Earth's magnetic field vector time series from `LEO' satellite 'CHAMP' for the 'CHAMP' mission period in high, unaveraged 50 Hz time resolution, using measurements from the FGM vector magnetometers and `ASC' Star Sensors on the mid-boom optical bench. The vector data are corrected and calibrated (by using the Overhauser scalar magnetometer as reference). The magnetic field vector data are given both in the satellite-bound sensor (`FGM') system and in the Earth Centered Earth Fixed local `NEC' (North-East-Center) system. For the latter the attitude time series (`ASC'), processed and cleaned, represented by quaternions describing the satellite attitude related to the celestial system, were used for the transformation. The files with daily time coverage are in the (binary and self-describing) `CDF' file format and accompanied, beside the `CDF'-format generic timestamp, by the satellite's geocentric positions and utility information like quality flags. 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. -180 180 -90 90 Helmholtz-Gemeinschaft http://doi.org/10.13039/501100001656

oai:doidb.wdc-terra.org:80522025-03-18T09:40:28ZDOIDBDOIDB.DOME

false4DOIDB.DOME 10.5880/fidgeo.d.2025.001 Codeço, Marta Marta Codeço 0000-0003-3080-3923 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Lowell Institute for Mineral Resources, Geosciences Department, University of Arizona, Arizona, United States Gleeson, Sarah Sarah Gleeson 0000-0002-5314-4281 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Freie Universität Berlin, Institute for Geological Sciences, Berlin, Germany Barrote, Vitor Vitor Barrote 0000-0001-7442-9748 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Paul-Scherrer-Institut (PSI), Villigen PSI, Switzerland Harlov, Daniel Daniel Harlov 7004598345 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Koch-Müller, Monika Monika Koch-Müller 0000-0001-6973-4967 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Kusebauch, Christof Christof Kusebauch 0000-0002-8608-3913 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Relvas, Jorge Jorge Relvas 0000-0003-1228-2247 Universidade de Lisboa, Faculdade de Ciências, Instituto Dom Luiz, Lisboa, Portugal Schleicher, Anja Anja Schleicher 0000-0003-4052-8654 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Schmidt, Christian Christian Schmidt 7403164030 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Stammeier, Jessica Jessica Stammeier 0000-0002-3603-3272 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Syczewski, Marcin Marcin Syczewski 0000-0001-6434-3027 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Wilke, Franziska D. H. Franziska D. H. Wilke 0000-0002-3463-6176 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany GFZ Data Services 2023 Geochemistry hydrothermal alteration whole-rock chemistry apatite Florencite xenotime felsic volcanic rocks black shales trace elements in apatite Neves Corvo VMS mineralization Earth Remote Sensing Instruments > Passive Remote Sensing > Spectrometers/Radiometers > Spectrometers > FTIR SPECTROMETER EARTH SCIENCE > SOLID EARTH > GEOCHEMISTRY > GEOCHEMICAL PROPERTIES > CHEMICAL CONCENTRATIONS In Situ/Laboratory Instruments > Probes > ELECTRON MICROPROBES In Situ/Laboratory Instruments > Spectrometers/Radiometers > ICP-MS In Situ/Laboratory Instruments > Spectrometers/Radiometers > LA-ICP-MS In Situ/Laboratory Instruments > Spectrometers/Radiometers > XRF Solar/Space Observing Instruments > X-Ray/Gamma Ray Detectors > XRD Codeço, Marta Marta Codeço 0000-0003-3080-3923 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Lowell Institute for Mineral Resources, Geosciences Department, University of Arizona, Arizona, United States Gleeson, Sarah Sarah Gleeson 0000-0002-5314-4281 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Freie Universität Berlin, Institute for Geological Sciences, Berlin, Germany Barrote, Vitor Vitor Barrote 0000-0001-7442-9748 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Paul-Scherrer-Institut (PSI), Villigen PSI, Switzerland Koch-Müller, Monika Monika Koch-Müller 0000-0001-6973-4967 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Schleicher, Anja Anja Schleicher 0000-0003-4052-8654 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Schmidt, Christian Christian Schmidt 7403164030 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Stammeier, Jessica Jessica Stammeier 0000-0002-3603-3272 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Syczewski, Marcin Marcin Syczewski 0000-0001-6434-3027 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Wilke, Franziska D. H. Franziska D. H. Wilke 0000-0002-3463-6176 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Dittmann, Uwe Uwe Dittmann GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Liep, Hartmund Hartmund Liep GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Appelt, Oona Oona Appelt GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Roddatis , Vladimir Vladimir Roddatis 0002-9584-0808 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Gottsche , Andrea Andrea Gottsche GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Codeço, Marta Lowell Institute for Mineral Resources, Geosciences Department, University of Arizona, Arizona, United States 2023-06-03 Dataset DOI of paper when available 10.1111/ggr.12149 10.1107/S1600576715014685 10.1039/c1ja10172b 10.1016/j.oregeorev.2011.11.001 10.1111/j.1751-908X.2006.tb00910.x 10.1007/s001260100168 10.2113/gsecongeo.101.4.753 10.2113/gsecongeo.101.4.791 10.1016/j.gr.2009.09.004 https://www.geoanalyst.org/wp-content/uploads/2021/02/GP-21-report.pdf CC BY 4.0 Analyzing the chemical composition of rocks and minerals is an important tool for exploring and understanding mineral resources. The Neves Corvo Cu-Zn-Pb(-Sn) is one of the richest volcanogenic massive sulfide deposits in the work and is unique within the Iberian Pyrite Belt (IBP) in terms of size, Cu-Zn grades and tonnages, the notable occurrence of Sn mineralization (Relvas et al., 2001) and In and Se contents (Carvalho et al., 2018). The mineralization occurs in close association with felsic volcanic rocks and black shale, where three main types are defined: (1) stringer and massive cassiterite mineralization, (2) stockwork and massive sulfide mineralization, and (3) late tectonic-metamorphic remobilization. The Sn mineralization is structurally controlled and occurs along the so-called “tin corridor” in the Corvo orebody (e.g., Relvas et al., 2006a, 2006b).

We analyzed major, minor and trace element contents of the footwall metavolcanic and metasedimentary units by XRF, ICP-MS and ICP-OS. This data publication reports for the first-time apatite major, minor and trace element compositions by microprobe and laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) and Raman Spectroscopy, and microprobe analyses from florencite and xenotime, in previously characterized samples from the Corvo orebody (Relvas 2000 and Relvas et al. 2001, 2006a, 2006b).

This document describes the samples studied and the analytical methods
Deutsche Forschungsgemeinschaft http://doi.org/10.13039/501100001659 GL945/1-1 Melts-Fluids-Models: keys to understanding ore-forming processes at the world-class Neves Corvo massive sulphide deposit, Iberian Pyrite Belt

oai:doidb.wdc-terra.org:81212025-03-27T16:41:42ZDOIDBDOIDB.GFZ

false4DOIDB.GFZ 10.5880/GFZ.3.6.2024.001 Nikolenko, Anna M. Anna M. Nikolenko 0000-0003-4731-9134 GFZ German Research Centre for Geosciences, Potsdam, Germany Institute of Geosciences, University of Potsdam, Potsdam, Germany Schmidt, Christian Christian Schmidt GFZ German Research Centre for Geosciences, Potsdam, Germany Sieber, Melanie J. Melanie J. Sieber 0000-0001-6166-0094 GFZ German Research Centre for Geosciences, Potsdam, Germany Institute of Geosciences, University of Potsdam, Potsdam, Germany Van Schijndel, Valby Valby Van Schijndel 0000-0002-2823-8200 GFZ German Research Centre for Geosciences, Potsdam, Germany Veksler, Ilya V. Ilya V. Veksler 0000-0002-9692-363X GFZ German Research Centre for Geosciences, Potsdam, Germany GFZ Data Services 2024 experimental petrology alkaline silicate melts zirconium eudialyte EARTH SCIENCE > SOLID EARTH > GEOCHEMISTRY > GEOCHEMICAL PROPERTIES Nikolenko, Anna M. Anna M. Nikolenko 0000-0003-4731-9134 GFZ German Research Centre for Geosciences, Potsdam, Germany Institute of Geosciences, University of Potsdam, Potsdam, Germany Nikolenko, Anna M. Anna M. Nikolenko 0000-0003-4731-9134 GFZ German Research Centre for Geosciences, Potsdam, Germany Institute of Geosciences, University of Potsdam, Potsdam, Germany Van Schijndel, Valby Valby Van Schijndel 0000-0002-2823-8200 GFZ German Research Centre for Geosciences, Potsdam, Germany EleMap - Elemental mapping by LA-ICP-MS GFZ German Research Centre for Geosciences, Potsdam, Germany Institute of Geosciences, University of Potsdam, Potsdam, Germany Nikolenko, Anna M. Dataset 10.1111/j.1751-908X.2011.00120.x 10.1016/j.earscirev.2017.06.002 10.1039/C1JA10172B 10.1016/j.lithos.2008.07.018 10.1016/j.lithos.2024.107839 CC BY 4.0 Eudialyte and eudialyte-group minerals (EGM) are unique tracers of peralkaline silica-undersaturated melts. They receive global interest as potential resources for high-field-strength elements (HFSE) (e. g. Zr, Nb, Ta, and rare-earth elements; REE), i. e. critical materials for modern technologies. The main condition for magmatic crystallization of eudialyte and EGM is that the concentration of Zr in parental melt should reach the saturation level. Thus, the solubility of eudialyte was studied in the system at temperatures between 750 and 1000 °C and pressures of 100 and 200 MPa. Liquid phases in run products are eudialyte, parakeldyshite and albite. Eudialyte is stable between 750 and 900 °C, and decomposes to parakeldyshite between 900 and 1000°C. Eudialyte crystallization in dry peralkaline silica-undersaturated melt at 750 and -850 °C requires minimum 0.2-0.22 wt.% ZrO2 in the melt. In melts with high amounts of dissolved H2O the saturation level in within the same temperature interval is much higher, at 1.1-2.85 wt.% ZrO2. Thus, peralkaline melts should be dry to crystallize EGM at ZrO2 concentrations between 0.2 and 0.3 wt.%.
LA-ICP-MS results show that REEs and HFSEs are strongly compatible with eudialyte as the eudialyte-melt distribution coefficients (D) vary from 2 to 90. Light REEs and especially La tend to have lower D values than heavy REEs. The data reflect that the concentrations of REEs and HFSEs in the eudialyte solid solution are mainly determined by the Zr concentrations in the melt: the lowest partition coefficients are observed in experiments with the highest eudialyte solubility, i.e., in experiments at high temperature and with H2O content
This data report is the supplement to the publication (Nikolenko et al., 2024, in prep.). This study presents a combined experimental research, EPMA and LA ICP-MS studies. This document describes the LA-ICP-MS analytical methods, sample preparation and the in-situ LA-ICP-MS element composition of eudialyte and peralkaline silica-undersaturated melts.
Eudialyte, which was used in experiments is a natural mineral, that had been collected from a pegmatite body on mount Eveslogchorr in the Khibina Massif, Kola Peninsula, Russia. Eudialyte crystals were crushed in a mortar and clear, inclusion-free fragments were hand-picked under a binocular.
Three synthetic glasses with variable Na-Al molar ratios were prepared from finely ground mixtures of silica (p.a., Merck®), aluminium oxide (γ-phase, 99.97%, 3 μm powder, Alfa Aesar®), and sodiumcarbonate (anhydrous, p.a., Merck®). The glasses were synthesized by sintering starting mixtures in a platinum crucible first at 900 °C for 1 hour, then crushing of the sintered material and remelting it two or three times at 1100-1200 °C for about 2 hours, with intermediate quenching in cold water and grinding the crushed glass fragments to the grain size of less than 1 mm.
Mixtures of the Khibina eudialyte and one of the synthetic glasses were ground in agate mortar to fine powders under acetone, dried at 100 °C for 2 hours, loaded into platinum capsules (outer and inner diameters 4.4 and 4.0 mm respectively) and welded shut. In some runs, distilled water (Merck, Suprapur®) was added to the starting charges before welding.

Khibina Massif, Kola Peninsula, Russia Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659 SCHM2415/7-1

oai:doidb.wdc-terra.org:81512025-06-12T10:32:35ZDOIDBDOIDB.ICGEM

false4DOIDB.ICGEM 10.5880/ICGEM.2025.001 Löcher, Anno Anno Löcher 0000-0003-4831-6218 Institute for Geodesy and Geoinformation, University of Bonn, Bonn, Germany Kusche, Jürgen Jürgen Kusche 0000-0001-7069-021X Institute for Geodesy and Geoinformation, University of Bonn, Bonn, Germany Nie, Yufeng Yufeng Nie 0009-0007-8914-0294 Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong, China GFZ Data Services 2025 SLR DORIS monthly gravity field model geodesy EARTH SCIENCE > SOLID EARTH > GEODETICS EARTH SCIENCE > SOLID EARTH > GRAVITY/GRAVITATIONAL FIELD Löcher, Anno Anno Löcher 0000-0003-4831-6218 Institute for Geodesy and Geoinformation, University of Bonn, Bonn, Germany Löcher, Anno Institute for Geodesy and Geoinformation, University of Bonn, Bonn, Germany 2025-06-10 2016 1984-01/2023-12 Dataset 10.1016/j.asr.2025.05.089 10.1007/s00190-020-01460-x CC BY 4.0 IGG-SLR-DORIS is a series of GRACE-like gravity field solutions going back to 1984 based on tracking data to up to 16 satellites, observed either by satellite laser ranging (SLR) or by means of the Doppler Orbitography and Radiopositioning Integrated by Satellites (DORIS) system. The match with GRACE in spatial resolution is achieved by representing the gravity field by empirical orthogonal functions (EOFs) obtained by a principal component analysis of the GRACE/GRACE-FO solutions. To make the modelling more adaptive, the EOFs are supplemented by low-degree spherical harmonics. IGG-SLR-DORIS is intended to replace the previously released IGG-SLR-HYBRID solution which applied the same parametrization. It could be shown that the combined SLR/DORIS solution is clearly superior, reducing the average difference to the GRACE/GRACE-FO fields by 10.6 percent. As another enhancement, the beginning of the time series was advanced by eight years by extending the analysis to historical SLR data. The time series now also includes a degree-1 solution based on an own inversion approach and using the surface mass distribution from the SLR/DORIS fields.

monthly global gravity field solutions -180 180 -90 90 Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659 450058266 SFB 1502/1-2022 National Natural Science Foundation of China http://dx.doi.org/10.13039/501100001809 42394132

oai:doidb.wdc-terra.org:76652025-07-22T10:21:57ZDOIDBDOIDB.GFZ

false4DOIDB.GFZ 10.5880/nerograv.2023.001 Murböck, Michael Michael Murböck 0000-0002-4108-578X Technical University Berlin, Berlin, Germany GFZ German Research Centre for Geosciences, Potsdam, Germany Flechtner, Frank Frank Flechtner 0000-0002-3093-5558 Technical University Berlin, Berlin, Germany GFZ German Research Centre for Geosciences, Potsdam, Germany Abrykosov, Petro Petro Abrykosov 0000-0002-7316-2583 Technical University München. Munich, Germany Pail, Roland Roland Pail 0000-0002-4364-4012 Technical University München. Munich, Germany GFZ Data Services 2023 Flechtner, Frank GFZ German Research Centre for Geosciences, Potsdam, Germany Dataset 10.3390/rs15030563 CC BY 4.0 This data publication represents the main outcomes of WP4.100 of Individual Project IP4 and of the Deliverable D4.1 of the research unit NEROGRAV summarizing the analyses of the GRACE and GRACE-FO accelerometer (ACC) and satellite-to-satellite tracking data (Microwave instrument (MWI) or Laser Ranging Interferometer (LRI)) in order to derive a characterization of the instrument performance and a stochastic model. A detailed description and discussion focusing on the GRACE data is given in Murböck et al. (submitted to Remote Sensing).

This first version of the combined ACC+MWI/LRI noise models is provided with the ASCII-file NEROGRAV_Dataset_GRACE_GRACE-FO_ACC-MWI-LRI_StochasticModel_V01.dat containing header information (17 lines) and the square root power spectral densities (PSDs), i.e. the amplitude spectral densities (ASDs) for the combined accelerometer and ranging observations in terms of range-rates (cf. Fig. 1). It is given for 21600 frequencies from 1/86400 Hz up to 0.25 Hz. Above 0.1 Hz (Nyquist frequency of the 5 s sampled MWI data) the columns for the ACC+MWI models are zero. The five columns consist of the frequency in Hz (col. 1), the combined ACC+MWI models for GRACE 2007 (col. 2), GRACE 2014 (col. 3), GRACE-FO 2019 (col. 4) and the combined GRACE-FO 2019 ACC+LRI model (col. 5) in m/s/√Hz.
-180 180 -90 90

oai:doidb.wdc-terra.org:85292025-07-23T12:49:23ZDOIDBDOIDB.FID

false4DOIDB.FID 10.5880/fidgeo.2025.045 Zaid, Khadra Khadra Zaid 0000-0001-5013-2309 Mohamed I University, Oujda, Morocco Bouabdellah, Mohammed Mohammed Bouabdellah 0000-0001-6358-9279 Mohamed I University, Oujda, Morocco Université Mohammed VI Polytechnique, Ben Guerir, Morocco Frenzel, Max Max Frenzel 0000-0001-6625-559X Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany Helmholtz Institute Freiberg for Resource Technology, Freiberg, Germany van Schijndel, Valby Valby van Schijndel 0000-0002-2823-8200 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Levresse, Gilles Gilles Levresse 0000-0001-9290-9825 Universidad Nacional Autónoma de México, Querétaro, Mexico Idbaroud, Mohamed Mohamed Idbaroud 0000-0002-5890-8738 Laboratoire des Gîtes Minéraux, Hydrogéologie & Environnement, Faculté des Sciences, Oujda, Morocco Cadi Ayyad University, Marrakech, Morocco Yans, Johan Johan Yans 0000-0001-7590-0298 University of Namur, Namur, Belgium GFZ Data Services 2025 sphalerite chalcopyrite and pyrite trace element geochemistry; ore shoot mineralization; Aouli Ag-Pb-Zn-(Cu) deposit; Upper Moulouya district compound material > rock EARTH SCIENCE > SOLID EARTH > GEOCHEMISTRY > GEOCHEMICAL PROPERTIES > CHEMICAL CONCENTRATIONS EARTH SCIENCE > SOLID EARTH > ROCKS/MINERALS/CRYSTALS > ELEMENTS > TRACE ELEMENTS Zaid, Khadra Khadra Zaid 0000-0001-5013-2309 Mohamed I University, Oujda, Morocco Zaid, Khadra Khadra Zaid 0000-0001-5013-2309 Mohamed I University, Oujda, Morocco Bouabdellah, Mohammed Mohammed Bouabdellah 0000-0001-6358-9279 Mohamed I University, Oujda, Morocco Université Mohammed VI Polytechnique, Ben Guerir, Morocco Frenzel, Max Max Frenzel 0000-0001-6625-559X Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany Helmholtz Institute Freiberg for Resource Technology, Freiberg, Germany van Schijndel, Valby Valby van Schijndel 0000-0002-2823-8200 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany van Schijndel, Valby Valby van Schijndel 0000-0002-2823-8200 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Levresse, Gilles Gilles Levresse 0000-0001-9290-9825 Universidad Nacional Autónoma de México, Querétaro, Mexico Idbaroud, Mohamed Mohamed Idbaroud 0000-0002-5890-8738 Laboratoire des Gîtes Minéraux, Hydrogéologie & Environnement, Faculté des Sciences, Oujda, Morocco Cadi Ayyad University, Marrakech, Morocco Yans, Johan Johan Yans 0000-0001-7590-0298 University of Namur, Namur, Belgium Yans, Johan Johan Yans 0000-0001-7590-0298 University of Namur, Namur, Belgium EleMap LA-ICP-MS laboratory, GFZ Helmholtz Centre for Geosciences, Potsdam, DE GFZ Helmholtz Centre for Geosciences, Potsdam, DE Zaid, Khadra Laboratoire des Gîtes Minéraux, Hydrogéologie & Environnement, Faculté des Sciences, Oujda, Morocco Dataset 10.3390/min15070669 10.1111/ggr.12154 10.1039/C1JA10172B 10.1039/B108787H 10.1111/j.1751-908X.2007.00104.x CC BY 4.0 This data report presents the in-situ LA-ICP-MS trace element composition of sphalerite, pyrite, and chalcopyrite from the Aouli Ag-Pb-Zn-(Cu) vein system in the Upper Moulouya district, Morocco. The dataset contributes to a study focused on characterizing the element concentrations in sulfides and elucidating the ore-forming processes at the Aouli deposit. Located within the Hercynian inlier of the Upper Moulouya, this deposit hosts one of Morocco’s largest argentiferous Pb-Zn ± F ± Ba vein-type deposits. The mineralization occurs within polyphase hydrothermal veins, oriented NE-SW to E-W and WNW-ESE. These veins occur as lodes, ore shoots, or discontinuous vein infill, with their emplacement largely controlled by structural intersections. The deposit hosts a complex mineralogical assemblage, including Ni-Co-Fe arsenides and sulfarsenides, Pb-Zn-Cu sulfides, and Ag-Sb-As sulfosalts occurring in the same vein structures, which are described for the first time. Consequently, the characterization of pyrite, chalcopyrite, and particularly sphalerite will help constrain the ore-forming process and determine the physicochemical conditions (T–fS2) of the mineralizing fluids.
Locality of the Aouli inlier -4.97385 -4.53989 32.719 32.9475 Moroccan Ministry of Higher Education and Scientific Research and the European Union’s Learning Mobility Program AC 171 DFG UNAM NSF-EAR 2233425 NSF-EAR 2233426 CNRST 18UMP2020

oai:doidb.wdc-terra.org:85432025-08-25T07:34:08ZDOIDBDOIDB.FID

false4DOIDB.FID 10.5880/fidgeo.2025.044 Bunzula, Violeta Lavínia Violeta Lavínia Bunzula TU Bergakademie Freiberg, Freiberg, Germany Müller, Axel Axel Müller 0000-0002-1650-5762 Natural History Museum, University of Oslo, Oslo, Norway Erambert, Muriel Muriel Erambert University of Oslo, Oslo, Norway van Schijndel, Valby Valby van Schijndel 0000-0002-2823-8200 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Schulz, Bernhard Bernhard Schulz 0000-0001-5003-3431 TU Bergakademie Freiberg, Freiberg, Germany Götze, Jens Jens Götze TU Bergakademie Freiberg, Freiberg, Germany Gilbricht, Sabine Sabine Gilbricht 0000-0003-1113-2415 TU Bergakademie Freiberg, Freiberg, Germany Sláma, Jiří Jiří Sláma 0000-0001-6377-2225 Czech Academy of Sciences, Prague, Czech Republic Simonsen, Siri Siri Simonsen 34873561000 University of Oslo, Oslo, Norway GFZ Data Services 2025 Li-rich mica aluminosilicates trace elements pegmatite fractionation Pan-African compound material > igneous material > igneous rock > phaneritic igneous rock > pegmatite EARTH SCIENCE > SOLID EARTH > GEOCHEMISTRY > GEOCHEMICAL PROPERTIES > CHEMICAL CONCENTRATIONS EARTH SCIENCE > SOLID EARTH > ROCKS/MINERALS/CRYSTALS > ELEMENTS > TRACE ELEMENTS Bunzula, Violeta Lavínia Violeta Lavínia Bunzula TU Bergakademie Freiberg, Freiberg, Germany Bunzula, Violeta Lavínia Violeta Lavínia Bunzula TU Bergakademie Freiberg, Freiberg, Germany Müller, Axel Axel Müller 0000-0002-1650-5762 Natural History Museum, University of Oslo, Oslo, Norway Müller, Axel Axel Müller 0000-0002-1650-5762 Natural History Museum, University of Oslo, Oslo, Norway Erambert, Muriel Muriel Erambert University of Oslo, Oslo, Norway van Schijndel, Valby Valby van Schijndel 0000-0002-2823-8200 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany van Schijndel, Valby Valby van Schijndel 0000-0002-2823-8200 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany van Schijndel, Valby Valby van Schijndel 0000-0002-2823-8200 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Schulz, Bernhard Bernhard Schulz 0000-0001-5003-3431 TU Bergakademie Freiberg, Freiberg, Germany Götze, Jens Jens Götze TU Bergakademie Freiberg, Freiberg, Germany Gilbricht, Sabine Sabine Gilbricht 0000-0003-1113-2415 TU Bergakademie Freiberg, Freiberg, Germany Sláma, Jiří Jiří Sláma 0000-0001-6377-2225 Czech Academy of Sciences, Prague, Czech Republic Simonsen, Siri Siri Simonsen 34873561000 University of Oslo, Oslo, Norway EleMap LA-ICP-MS laboratory of GFZ Helmholtz Centre for Geosciences, Potsdam, DE GFZ Helmholtz Centre for Geosciences, Potsdam, DE Müller, Axel Laboratoire des Gîtes Minéraux, Hydrogéologie & Environnement, Faculté des Sciences, Oujda, Morocco Dataset 10.1016/j.gca.2012.01.009 10.1016/j.chemgeo.2013.07.013 10.1111/j.1751-908X.2011.00120.x 10.1039/C1JA10172B 10.1111/j.1751-908X.2007.00104.x 10.1016/j.gexplo.2025.107882 CC BY 4.0 This data report presents the in-situ LA-ICP-MS trace element geochemistry of the micas of the Pan-African rare-element pegmatites of the Alto Ligonha Pegmatite District in northern Mozambique. The pegmatites contain Li-rich micas and primary Li aluminosilicates, such as spodumene. Five Alto Ligonha pegmatites, Naípa, Muiâne, Napepesso West, Nanro, and Natxepo, were investigated to better understand the fractionation of pegmatite melts leading to Li enrichment, utilizing e.g. the trace element chemistry of mica from different parts of these pegmatites. Micas collected from the wall zone, intermediate zone and core zone of the studied pegmatites show high but also highly variable concentrations of the incompatible elements like Li, Rb, Cs, Be, and Ta. Very strong pegmatite-internal fractionation is recorded by the mica chemistry of the Naípa, Muiâne and Nanro pegmatites. In these pegmatites, Li2O in white micas measured with LA-ICP-MS increases from 0.1-1.4 wt.% in the wall zone, to 0.3-1.7 wt.% in the intermediate zone, 1.5-3.8 wt.% in the core zone and up to 5.4 wt.% in the pockets. The data record extreme Li enrichment during the final crystallization stage.
38.2 38.4 -16 -15.7 European Commission’s Horizon 2020 innovation program grant 869274 GREENPEG project ‘New Exploration Tools for European Pegmatite Green-Tech Resources’

oai:doidb.wdc-terra.org:81302025-09-08T11:56:55ZDOIDBDOIDB.FID

false4DOIDB.FID 10.5880/fidgeo.2025.004 Keltie, Erin Erin Keltie 0000-0003-2550-0055 Community Health and Epidemiology, Dalhousie University, Halifax, Nova Scotia, Canada Brenan, James James Brenan 0000-0003-4924-8288 Department of Earth and Environmental Sciences, Dalhousie University, Halifax, Nova Scotia, Canada GFZ Data Services 2025 chromite chromitite ore deposit chemical element > transition element > chromium In Situ/Laboratory Instruments > Probes > ELECTRON MICROPROBES In Situ/Laboratory Instruments > Spectrometers/Radiometers > LA-ICP-MS Brenan, James James Brenan 0000-0003-4924-8288 Department of Earth and Environmental Sciences, Dalhousie University, Halifax, Nova Scotia, Canada Brenan, James Department of Earth and Environmental Sciences, Dalhousie University, Halifax, Nova Scotia, Canada 2025-01-06 Dataset https://hdl.handle.net/10222/75040 10.1093/petrology/egaf076 10.1093/petrology/42.12.2279 10.1111/j.1751-908X.2015.00392.x 10.1039/C1JA10172B CC BY 4.0 The data were generated in two labotories of the Dalhousie University in Halifax during a series of experiments to determine the solubility of chromite in komatiite mixed with different crustal contaminants. The experiments were designed to determine the solubility of the mineral chromite in silicate melt, with the dominant variable being the silica and iron content of the melt. After equilibrating chromite with melt at 1192-1430 degrees Celcius, samples were quenched and the composition of the chromite, quenched melt (now glass), and olivine run-products were measured for major and minor elements by electron microprobe, and the chromium concentration in the glass was measured by laser ablation ICP-MS. Analytical procedures are included in the associated data description file. The data are provided in a series of Excel worksheets containing five data tables. Table 1 is a summary of the composition of the starting materials used in experiments. Table 2 is a summary of the conditions of temperature, oxygen fugacity, experiment duration and initial sample composition. Table 3 is a summary of the major and minor element composition of the glass measured by electron microprobe and laser ablation ICP-MS. Tables 4 and 5 are summaries of the major and minor element composition of the olivine and chromite, respectively, measured by electron microprobe. Natural Sciences and Engineering Research Council of Canada http://dx.doi.org/10.13039/501100000038 Discovery Grant

oai:doidb.wdc-terra.org:67522025-10-07T08:48:27ZDOIDBDOIDB.GFZ

false4DOIDB.GFZ 10.5880/GFZ.2.3.2019.004 Rother, Martin Martin Rother 0009-0007-0355-8551 GFZ German Research Centre for Geosciences, Potsdam, Germany Rauberg, Jan Jan Rauberg 0000-0002-7752-9960 GFZ German Research Centre for Geosciences, Potsdam, Germany Michaelis, Ingo Ingo Michaelis 0000-0001-9741-4063 GFZ German Research Centre for Geosciences, Potsdam, Germany GFZ Data Services 2019 CHAMP magnetic field time series combined product level 3 Earth Observation Satellites > CHAMP Earth Remote Sensing Instruments > Passive Remote Sensing > Magnetic Field/Electric Field Instruments > MAGNETOMETERS Earth Remote Sensing Instruments > Passive Remote Sensing > Positioning/Navigation > ACS EARTH SCIENCE > SOLID EARTH > GEOMAGNETISM > MAGNETIC FIELD Solar/Space Observing Instruments > Magnetic Field/Electric Field Instruments > FGM Rother, Martin Martin Rother 0009-0007-0355-8551 GFZ German Research Centre for Geosciences, Potsdam, Germany Rauberg, Jan Jan Rauberg 0000-0002-7752-9960 GFZ German Research Centre for Geosciences, Potsdam, Germany Michaelis, Ingo Ingo Michaelis 0000-0001-9741-4063 GFZ German Research Centre for Geosciences, Potsdam, Germany Rauberg, Jan Jan Rauberg GFZ German Research Centre for Geosciences, Potsdam, Germany Stolle, Claudia GFZ German Research Centre for Geosciences, Potsdam, Germany Stolle, Claudia GFZ German Research Centre for Geosciences, Potsdam, Germany 2000/2010 Dataset 10.2312/GFZ.b103-19104 https://isdc.gfz-potsdam.de/champ-isdc/ CC BY 4.0 This is a Level 3 data daily file product from various scientific and utility sensors on board of the `LEO' satellite 'CHAMP' with magnetic field data given by a time resolution of 1 Hz. Thise Level 3 data type is build to hold and merge finally corrected data, focusing on mature data calibration and corrections -- as well as internal consistency. This Level 3 data product is intended to supersede the various Level 2 versions with calibrated magnetic field readings from the CHAMP mission distributed hitherto and should be fitted for scientific use, assembling time series of scalar magnetic field values (but not directly readings from the scalar Overhauser sensor), vector magnetic field data from the boom-mounted Fluxgate 'FGM' sensors and attitude data from the ('ASC') boom-mounted Star Cameras. The vector data are given both in the satellite-bound sensor ('FGM') system and the Earth Centered Earth Fixed local 'NEC' (North-East-Center) system. The attitude time series, processed and cleaned, are represented by quaternions describing the satellite attitude related to the celestial system. The readings of the scalar OVM (Overhauser) absolute magnetometer at the top of the boom are not supplied directly, but were used during calibration of the vector magnetometer readings. The files with daily time coverage are in the (binary and self-describing) 'CDF' file format and accompanied, beside the generic 'CDF'-format timestamp, by the satellite's geocentric positions and utility information like quality flags.

The full product and format descriptions are provided in the associated Scientific Technical Report - Data (GFZ Section 2.3, 2019. https://doi.org/10.2312/GFZ.b103-19104).

----------
13 March 2025: addition of Jan Rauberg as co-author
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.
-180 180 -90 90

oai:doidb.wdc-terra.org:67502025-10-07T08:50:03ZDOIDBDOIDB.GFZ

false4DOIDB.GFZ 10.5880/GFZ.2.3.2019.005 Rother, Martin Martin Rother 0009-0007-0355-8551 GFZ German Research Centre for Geosciences, Potsdam, Germany Michaelis, Ingo Ingo Michaelis 0000-0001-9741-4063 GFZ German Research Centre for Geosciences, Potsdam, Germany GFZ Data Services 2019 CHAMP ASC star sensor Earth Observation Satellites > CHAMP Earth Remote Sensing Instruments > Passive Remote Sensing > Magnetic Field/Electric Field Instruments > MAGNETOMETERS Earth Remote Sensing Instruments > Passive Remote Sensing > Positioning/Navigation > ACS EARTH SCIENCE > SOLID EARTH > GEOMAGNETISM > MAGNETIC FIELD Solar/Space Observing Instruments > Magnetic Field/Electric Field Instruments > FGM Rother, Martin Martin Rother 0009-0007-0355-8551 GFZ German Research Centre for Geosciences, Potsdam, Germany Michaelis, Ingo Ingo Michaelis 0000-0001-9741-4063 GFZ German Research Centre for Geosciences, Potsdam, Germany Rauberg, Jan Jan Rauberg GFZ German Research Centre for Geosciences, Potsdam, Germany Stolle, Claudia GFZ German Research Centre for Geosciences, Potsdam, Germany 2000/2010 Dataset 10.2312/GFZ.b103-19104 https://isdc.gfz-potsdam.de/champ-isdc/ CC BY 4.0 Time series of processed, cleaned attitude readings in quaternion format of the two boom-mounted 'ASC' star sensors of the 'LEO' satellite 'CHAMP', describing the satellite system attitude in respect to the celestial background. The nominal time resolution of the time series in the 'ASCII'-file listing is 1 Hz.


The full product and format descriptions are provided in the associated Scientific Technical Report - Data 19/10 (GFZ Section 2.3, 2019. https://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.
-180 180 -90 90

oai:doidb.wdc-terra.org:67512025-10-07T08:51:22ZDOIDBDOIDB.GFZ

false4DOIDB.GFZ 10.5880/GFZ.2.3.2019.007 Rother, Martin Martin Rother 0009-0007-0355-8551 GFZ German Research Centre for Geosciences, Potsdam, Germany Rauberg, Jan Jan Rauberg 0000-0002-7752-9960 GFZ German Research Centre for Geosciences, Potsdam, Germany Michaelis, Ingo Ingo Michaelis 0000-0001-9741-4063 GFZ German Research Centre for Geosciences, Potsdam, Germany GFZ Data Services 2019 CHAMP Electron density electron temperature time series Earth Observation Satellites > CHAMP Earth Remote Sensing Instruments > Passive Remote Sensing > Positioning/Navigation > ACS EARTH SCIENCE > SOLID EARTH > GEOMAGNETISM > ELECTRICAL FIELD Solar/Space Observing Instruments > Magnetic Field/Electric Field Instruments > FGM Rother, Martin Martin Rother 0009-0007-0355-8551 GFZ German Research Centre for Geosciences, Potsdam, Germany Rauberg, Jan Jan Rauberg GFZ German Research Centre for Geosciences, Potsdam, Germany Stolle, Claudia GFZ German Research Centre for Geosciences, Potsdam, Germany 2000/2010 Dataset 10.2312/GFZ.b103-19104 https://isdc.gfz-potsdam.de/champ-isdc/ CC BY 4.0 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).

----------
13 March 2025: addition of Jan Rauberg as co-author

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.
-180 180 -90 90

oai:doidb.wdc-terra.org:85482025-10-13T23:18:20ZDOIDBDOIDB.GFZ

false4DOIDB.GFZ 10.5880/GFZ.KHAG.2025.004 Kalantar, Alireza Alireza Kalantar 0009-0009-3252-2499 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Hofmann, Hannes Hannes Hofmann 0000-0003-0778-6141 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Ji, Yinlin Yinlin Ji 0000-0001-9787-7164 School of Earth Science and Engineering, Nanjing University, China Blöcher, Guido Guido Blöcher 0000-0002-8589-9742 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Muhl, Lena Lena Muhl 0000-0002-7304-8676 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Zang, Arno Arno Zang 0000-0001-7670-5152 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany GFZ Data Services 2025 hydraulic shearing treatments fracture permeability fracture type Enhanced Geothermal Systems (EGS) shear-flow test self-propping granodiorite Permeability Roughness > Root Mean Square Triaxial Kalantar, Alireza Alireza Kalantar 0009-0009-3252-2499 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Kalantar, Alireza Alireza Kalantar 0009-0009-3252-2499 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Kalantar, Alireza Alireza Kalantar 0009-0009-3252-2499 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Kalantar, Alireza Alireza Kalantar 0009-0009-3252-2499 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Kalantar, Alireza Alireza Kalantar 0009-0009-3252-2499 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Kalantar, Alireza Alireza Kalantar 0009-0009-3252-2499 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Hofmann, Hannes Hannes Hofmann 0000-0003-0778-6141 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Hofmann, Hannes Hannes Hofmann 0000-0003-0778-6141 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Ji, Yinlin Yinlin Ji 0000-0001-9787-7164 School of Earth Science and Engineering, Nanjing University, China Ji, Yinlin Yinlin Ji 0000-0001-9787-7164 School of Earth Science and Engineering, Nanjing University, China Blöcher, Guido Guido Blöcher 0000-0002-8589-9742 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Muhl, Lena Lena Muhl 0000-0002-7304-8676 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Zang, Arno Arno Zang 0000-0001-7670-5152 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Mechanical Testing System Laboratory (GFZ Helmholtz Centre for Geosciences, Germany) https://labinfrastructure.geo-x.net/laboratories/96 GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Kalantar, Alireza GFZ Helmholtz Centre for Geosciences, Potsdam, Germany Dataset 10.1029/2025JB031938 10.1016/j.ijrmms.2023.105512 10.1016/j.earscirev.2021.103916 10.1007/s00603-022-02797-9 10.1029/2022GL100418 10.1029/2023GL104662 10.5880/GFZ.4.8.2022.016 10.1029/2018JB016045 CC BY 4.0 Enhanced Geothermal Systems (EGS) utilize artificially induced fracture networks to enable fluid circulation and heat extraction from high-temperature, low-permeability geological formations. Unlike conventional hydraulic fracturing in the hydrocarbon industry—which commonly employs proppants to keep fractures open—EGS stimulation primarily relies on hydraulic shear stimulation. This technique leverages the self-propping behavior of pre-existing fractures, eliminating the need for proppants. To replicate hydraulic shear stimulation in a controlled laboratory setting, we conducted shear-flow experiments on various fracture types, including shear fractures, tensile fractures, and saw-cut fractures. Most previous studies have focused on tensile and saw-cut fractures, typically treating them as idealized representations of smooth or rough fracture surfaces. However, shear fractures—due to their naturally formed characteristics—offer a more realistic simulation of in-situ conditions and better represent pre-existing fractures in the field. To evaluate fracture surface roughness, we employed a 3D laser scanner. The digitized surface data, captured both before and after the shear-flow tests, were recorded in .CSV files for subsequent analysis.
Study area 8.65729 8.67797 49.6395 49.6448 Helmholtz Association http://dx.doi.org/10.13039/501100009318 VH-NG-1516 Helmholtz Young Investigator Group ARES

oai:doidb.wdc-terra.org:86102026-01-05T11:06:38ZDOIDBDOIDB.FID

false4DOIDB.FID 10.5880/fidgeo.2025.061 Balestro, Gianni Gianni Balestro 0000-0001-5215-4659 University of Torino, Torino, Italy van Schijndel, Valby Valby van Schijndel 0000-0002-2823-8200 GFZ Helmholtz Center for Geosciences Gattiglio, Marco Marco Gattiglio 0000-0002-1885-2872 University of Torino, Torino, Italy Borghi, Alessandro Alessandro Borghi 0000-0002-2545-0396 University of Torino, Torino, Italy Stefano, Ghignone Ghignone Stefano 0000-0002-1295-6291 University of Torino, Torino, Italy GFZ Data Services 2025 Zircon U-Pb ages Continental crust Gondwana Rifting Western Alps EARTH SCIENCE > SOLID EARTH > ROCKS/MINERALS/CRYSTALS > AGE DETERMINATIONS Balestro, Gianni Gianni Balestro 0000-0001-5215-4659 University of Torino, Torino, Italy Balestro, Gianni Gianni Balestro 0000-0001-5215-4659 University of Torino, Torino, Italy van Schijndel, Valby Valby van Schijndel 0000-0002-2823-8200 GFZ Helmholtz Center for Geosciences van Schijndel, Valby Valby van Schijndel 0000-0002-2823-8200 GFZ Helmholtz Center for Geosciences van Schijndel, Valby Valby van Schijndel 0000-0002-2823-8200 GFZ Helmholtz Center for Geosciences Gattiglio, Marco Marco Gattiglio 0000-0002-1885-2872 University of Torino, Torino, Italy Borghi, Alessandro Alessandro Borghi 0000-0002-2545-0396 University of Torino, Torino, Italy Stefano, Ghignone Ghignone Stefano 0000-0002-1295-6291 University of Torino, Torino, Italy EleMap LA-ICP-MS laboratory of GFZ Helmholtz Centre for Geosciences, Potsdam, DE GFZ Helmholtz Centre for Geosciences, Potsdam, DE Balestro, Gianni University of Torino, Torino, Italy Dataset 10.1016/j.gsf.2025.102245 10.1016/j.chemgeo.2004.06.017 10.1039/C7JA00167C 10.1016/j.chemgeo.2007.11.005 10.1111/j.1751-908X.1995.tb00147.x 10.1016/j.gsf.2018.04.001 CC BY 4.0 Geochronological data allowed constraining the tectonostratigraphic evolution of a European terrane stacked in the Western Alps and consisting of a Palaeozoic basement overlain by a Mesozoic metasedimentary cover. Four samples belonging to the basement have been analyzed. They correspond to two metasediments (VS113: 7°9'0"E, 45°9'8"N; VS114: 7°7'26"E, 45°9'0"N) and two orthogneisses (VS60: 7°9'8"E, 45°9'5"N; VS77 7°15'52"E, 45°6'54"N). Zircons from the studied samples were separated and analyzed to obtain the younger population age of the metasediments, and the crystallization age of the orthogneiss.
7.12389 7.26444 45.115 45.1522

oai:doidb.wdc-terra.org:86152026-01-19T15:16:13ZDOIDBDOIDB.FID

false4DOIDB.FID 10.5880/fidgeo.2026.003 Lanari, Riccardo Riccardo Lanari 0000-0002-7296-2749 National Research Council of Italy (CNR), Florence, Italy Moumeni, Mohammad Mohammad Moumeni 0000-0003-4892-0546 Roma Tre University, Rome, Italy Reitano, Riccardo Riccardo Reitano 0000-0002-6295-5588 Roma Tre University, Rome, Italy GFZ Data Services 2026 EPOS multi-scale laboratories analogue models of geologic processes analogue modelling results magma emplacement uplift and erosion climate analogue rainfall Science Keywords > EARTH SCIENCE > LAND SURFACE > GEOMORPHIC LANDFORMS/PROCESSES > TECTONIC PROCESSES > TECTONIC UPLIFT Science Keywords > EARTH SCIENCE SERVICES > MODELS > DIGITAL ELEVATION/DIGITAL TERRAIN MODELS Science Keywords > EARTH SCIENCE SERVICES > MODELS > LAND SURFACE MODELS Science Keywords > EARTH SCIENCE SERVICES > MODELS > PHYSICAL/LABORATORY MODELS Laboratory of Experimental Tectonics (LET) Roma Tre University, Rome, Italy ILGE TNA/NOA MEET Project (Monitoring Earth's Evolution and Tectonics) Moumeni, Mohammad Roma Tre University, Rome, Italy Reitano, Riccardo Roma Tre University, Rome, Italy Dataset https://ilge.ct.ingv.it/ https://meet.ingv.it/ 10.1016/j.jvolgeores.2017.07.022 CC BY 4.0 This dataset documents a series of analogue experiments designed to investigate the coupled evolution of magma-driven surface uplift and rainfall-driven geomorphic processes. Seven controlled laboratory experiments were conducted, each combining shallow intrusion of a magma analogue with imposed rainfall of varying intensity, in order to systematically explore the role of surface processes under different forcing conditions. The experimental setup consists of a rigid Plexiglas container filled with a water-saturated granular mixture formulated to reproduce brittle crustal behaviour under wet conditions. Magmatic intrusion was simulated by injecting a fixed volume (360 cm³) of low-viscosity polyglycerine through a basal inlet at three distinct injection rates, while surface processes were imposed using an overhead rainfall system delivering three different rainfall intensities.
Topographic evolution during each experiment was monitored using a structured-light laser scanner (Artec Leo). For every model run, six Digital Elevation Models (DEMs) were generated at synchronised stages corresponding to 0%, 20%, 40%, 60%, 80% and 100% of the injected volume, yielding a total of 42 DEMs. Raw scans were processed through a triangulated irregular network (TIN) meshing workflow and subsequently rasterised to GeoTIFF format without additional post-processing, in order to preserve the original topographic signal. In parallel, time-lapse photographic documentation was acquired throughout each experiment using a digital camera, providing a complementary visual record of dome growth, surface incision and sediment redistribution.

The dataset is organised into two main components: (i) high-resolution topographic datasets (DEMs) and (ii) time-indexed photographic sequences, both linked to the temporal evolution of each experiment. Quality control procedures include scanner calibration prior to acquisition, verification of mesh consistency and raster resolution, and a closed-system experimental design ensuring mass conservation. All data are distributed in their original formats and accompanied by detailed documentation describing experimental procedures, data processing workflows, and file organisation, enabling reproducibility and reuse in quantitative analyses of coupled magmatic and surface processes.

This publication results from work conducted under the transnational access/national open access action at University Roma Tre, Laboratory of Experimental Tectonics (LET) supported by WP3 ILGE - MEET project, PNRR - EU Next Generation Europe program, MUR grant number D53C22001400005.
The samples in this dataset correspond to the topographic surfaces generated during the analogue experiments. No physical geological samples were produced, and therefore no International Geo Sample Numbers (IGSNs) apply. Instead, each “sample” represents a digital acquisition of the model surface at a specific injection step.

Topography was recorded using an Artec Leo structured-light 3D scanner. After each increment of injected analogue magma (corresponding to six discrete stages from 0% to 100% of the total injected volume), the evolving surface was scanned. Each scan was processed using the Artec Studio workflow to generate a triangulated irregular network (TIN), which was subsequently converted into a raster Digital Elevation Model (DEM) in GeoTIFF format. These DEMs represent the primary samples of this dataset.

In parallel, time-lapse photographs were obtained using a Canon EOS 200D digital camera. Images were collected every two minutes for all models, except for the Ri 21.2 experiment, where images were acquired every ten minutes due to the longer duration of the run. Photographs were used to visually document erosion, sediment transport and dome growth, and are included here as secondary data.
All DEMs and photographs retain their original resolution and were not altered beyond standard meshing and rasterisation steps required to convert the raw scanner output into usable elevation grids.
Topographic data were acquired using an Artec Leo structured-light laser scanner. The instrument performs real-time 3D reconstruction using a built-in projector–sensor system with an accuracy of up to 0.1 mm and 3D resolution of approximately 0.2–0.5 mm. Before each scanning session, the scanner was calibrated following the manufacturer’s internal calibration protocol to ensure consistent alignment and measurement stability.

For every experiment, scans were carried out at six successive stages corresponding to 0%, 20%, 40%, 60%, 80% and 100% of the total injected analogue magma volume. Each scan covers the entire model surface, with overlapping passes to minimise occlusions and improve point-cloud completeness.

Time-lapse images were obtained using a Canon EOS 200D DSLR camera equipped with a fixed focal-length lens. Photographs were taken at regular time intervals throughout each experiment: every 2 minutes for six of the seven models; every 10 minutes for the model with Ri 21.2 (due to the experiment’s longer duration). Images were saved in JPEG format at full camera resolution. No post-processing beyond file renaming and chronological ordering was applied.

European Commission http://dx.doi.org/10.13039/501100000780 MEET Ministero dell'Università e della Ricerca http://dx.doi.org/10.13039/501100021856 D53C22001400005 MEET

oai:doidb.wdc-terra.org:86322026-02-10T17:51:09ZDOIDBDOIDB.FID

false4DOIDB.FID 10.5880/fidgeo.2025.039 Di Vincenzo, Gianfranco Gianfranco Di Vincenzo 0000-0002-9669-9789 Istituto di Geoscienze e Georisorse – CNR, Pisa, Italy Dorsey, Rebecca J. Rebecca J. Dorsey 0000-0001-8390-052X Department of Earth Sciences, University of Oregon, Eugene, OR, USA Meschis, Marco Marco Meschis 0000-0001-9144-3031 Istituto Nazionale di Geofisica e Vulcanologia (INGV), Palermo, Italy Longhitano, Sergio G. Sergio G. Longhitano 0000-0003-4978-4582 Department of Basic and Applied Sciences, Università degli Studi della Basilicata, Potenza, Italy Cavazza, William William Cavazza 0000-0002-6030-9689 Department of Biological, Geological and Environmental Sciences, University of Bologna, Bologna, Italy Chiarella, Domenico Domenico Chiarella 0000-0003-2482-0081 Department of Biological, Geological and Environmental Sciences, University of Bologna, Bologna, Italy GFZ Data Services 2025 EPOS multi-scale laboratories geochemistry and microscopy geochemistry data Ar-40/Ar-39 geochronology dating volcanic rock Argille di Spadafora EARTH SCIENCE > SOLID EARTH > GEOCHEMISTRY > GEOCHEMICAL PROPERTIES > ISOTOPE MEASUREMENTS EARTH SCIENCE > SOLID EARTH > GEOCHEMISTRY > GEOCHEMICAL PROPERTIES > ISOTOPES EARTH SCIENCE > SOLID EARTH > ROCKS/MINERALS/CRYSTALS > AGE DETERMINATIONS In Situ/Laboratory Instruments > Spectrometers/Radiometers > MASS SPECTROMETERS Di Vincenzo, Gianfranco Gianfranco Di Vincenzo 0000-0002-9669-9789 Istituto di Geoscienze e Georisorse – CNR, Pisa, Italy Di Vincenzo, Gianfranco Gianfranco Di Vincenzo 0000-0002-9669-9789 Istituto di Geoscienze e Georisorse – CNR, Pisa, Italy Di Vincenzo, Gianfranco Gianfranco Di Vincenzo 0000-0002-9669-9789 Istituto di Geoscienze e Georisorse – CNR, Pisa, Italy Dorsey, Rebecca J. Rebecca J. Dorsey 0000-0001-8390-052X Department of Earth Sciences, University of Oregon, Eugene, OR, USA Meschis, Marco Marco Meschis 0000-0001-9144-3031 Istituto Nazionale di Geofisica e Vulcanologia (INGV), Palermo, Italy Longhitano, Sergio G. Sergio G. Longhitano 0000-0003-4978-4582 Department of Basic and Applied Sciences, Università degli Studi della Basilicata, Potenza, Italy Cavazza, William William Cavazza 0000-0002-6030-9689 Department of Biological, Geological and Environmental Sciences, University of Bologna, Bologna, Italy Chiarella, Domenico Domenico Chiarella 0000-0003-2482-0081 Department of Biological, Geological and Environmental Sciences, University of Bologna, Bologna, Italy Ar-Ar Geochronology laboratory (IGG-CNR, Italy) ea0ba15ea6bf983b1d8d8568829aa943 IGG-CNR, Italy Di Vincenzo, Gianfranco Istituto di Geoscienze e Georisorse – CNR, Pisa, Italy 2025-05-23 2024-09-17T14:17:00/2025-04-11T17:16:00 Dataset 10.1515/geoca-2016-0023 10.1016/j.chemgeo.2022.121026 10.1016/J.GCA.2021.01.046 10.1016/S0098-3004(01)00095-4 10.1016/j.gca.2006.06.1563 10.1016/S0016-7037(99)00204-5 10.1016/j.quageo.2016.09.004 10.1029/2025TC009008 CC BY 4.0 The dataset contain full 40Ar/39Ar geochronological data completed by multi collector noble gas mass spectrometry on plagioclase and glass separates from a tuff sample interbedded in Pleistocene marine claystone (Argille di Spadafora) of northeastern Sicily (Italy). Tuff unit VU7 was identified in the field using the published base map and stratigraphic nomenclature of Di Bella et al. (2016), which correlates to bathyal marine marl (Argille di Vito Superiore) in southern Calabria. The tuff contains stratified white lapilli with abundant fresh volcanic glass shards and was deposited by a submarine turbidity current from a single volcanic eruption.

The Ar laserprobe facility was realized with the financial support of CNR. The CO2 laser system was acquired within the PNRR – Mission 4, “Education and Research” - Component 2, “From research to business” - Investment line 3.1, “Fund for the creation of an integrated system of research and innovation infrastructures” - Project IR0000025 MEET. EPOS JRU Italia is acknowledged for support in the Laboratory maintenance.
Spatial coverage refers to site of sampling. Temporal coverage refers to the time interval of data acquisition. Consiglio Nazionale delle Ricerche http://dx.doi.org/10.13039/501100004462 European Commission http://dx.doi.org/10.13039/501100000780 MEET Ministero dell'Università e della Ricerca http://dx.doi.org/10.13039/501100021856 D53C22001400005 MEET 1776328082183,0001-01-01T00:00:00Z,9999-12-31T23:59:59Z,50,~cT1sYXNlciZmcT1yZXNvdXJjZVR5cGVHZW5lcmFsOmRhdGFzZXQK,oai_datacite