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In this dataset we report exemplary, representative mineral chemistry data of two metapelite samples (PG61 and PG89) from the Modereck Nappe in the central Tauern Window. The dataset is supplemental to the publication by Groß et al. (2020). For further details on the sample mineralogy and microstructure not provided in the data description file, we refer to this publication. The data was initially collected for a thermobarometry study of the region in the framework of the priority programme SPP 4DMB, funded by the German Research Association (DFG). Sample description:Sample PG61 is an example of a chloritoid-micaschist from the Piffkar Formation. Sample coordinates are UTM Zone 33N: 337044 E, 5216460 N (WGS84, 12.85326 E, 47.081526 N). It contains quartz, phengite, chloritoid, some chlorite, ilmenite (mix of ilmenite, geikielite, Fe-oxide) and relicts of sceletal garnet (as palisades along quartz grain boundaries) and accessory allanite. Rutile occurs as inclusions in quartz and no lawsonite, kyanite or carpholite were found. Sample PG89 is an example of a garnet-micaschist from the Brennkogel Formation. Sample coordinates are UTM Zone 33N: 341888 E, 5207230 N. (WGS 84, 12.920259 E, 46.999701 N) It contains quartz, phengite, garnet, chlorite, albite, tourmaline and rutile (often with ilmenite margins). No lawsonite, paragonite, glaucophane or omphacite was found. Analytical procedure:The compositions of rock forming minerals (white mica, garnet, chloritoid and chlorite) were aquired on a JEOL JXA 8200 SuperProbe at Freie Universität Berlin, Institut für Geologische Wissenschaften. Measurement conditions for spot analyses were 15 kV acceleration voltage, 20 nA beam current and <1 μm beam diameter. We used natural and synthetic reference materials for instrument calibration.
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  • Dataset
Assess of the feasibility of magnetotelluric measurements for geothermal exploration in northern Bavaria despite of the high level of cultural electromagnetic noise. This data publication encompasses a detailed report in pdf format with a description of the project, information on the experimental setup, data collection, instrumentation used, recording configuration and data quality. The folder structure and content of the data repository are described in detail in Ritter et al. (2019). Time-series data are provided in EMERALD format (Ritter et al., 2015).,The Geophysical Instrument Pool Potsdam (GIPP) provides field instruments for (temporary) seismological studies (both controlled source and earthquake seismology) and for magnetotelluric (electromagnetic) experiments. The GIPP is operated by the GFZ German Research Centre for Geosciences. The instrument facility is open for academic use. Instrument applications are evaluated and ranked by an external steering board. See Haberland and Ritter (2016) and https://www.gfz-potsdam.de/gipp for more information.,
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  • Dataset
Magnetotellurics (MT) is a geophysical deep sounding tool that can help decipher the deep hydrology and geology of Antarctica, in concert with more established and already applied geophysical methods, such as seismology, gravity, and magnetics. Electrical conductivity is an important physical parameter to identify properties of rocks and, perhaps more importantly, constituents within, such as fluids or mineralisation.The unique conditions of Antarctica, which is largely covered with ice cause technical issues, particularly with the electric field recordings, as highly resistive snow and ice at surface of Antarctica hampers contact of the E-field sensors (telluric electrodes) with the ground. The project was a feasibility study to address this principal problem and to test modified MT equipment of the Geophysical Instrument Pool Potsdam (GIPP) in the vicinity of the Neumayer Station III (NMIII) on the Ekström Ice Shelfon. This data publication encompasses a detailed report in .pdf format with a description of the project, information on the experimental setup, data collection, instrumentation used, recording configuration and data quality. The folder structure and content of the data repository are described in detail in Ritter et al. (2019). Time-series data are provided in EMERALD format (Ritter et al., 2015).,The Geophysical Instrument Pool Potsdam (GIPP) provides field instruments for (temporary) seismological studies (both controlled source and earthquake seismology) and for magnetotelluric (electromagnetic) experiments. The GIPP is operated by the GFZ German Research Centre for Geosciences. The instrument facility is open for academic use. Instrument applications are evaluated and ranked by an external steering board. See Haberland and Ritter (2016) and https://www.gfz-potsdam.de/gipp for more information.,
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  • Dataset
In September 2017 three crustal-scale seismic profiles were acquired in southern Iran covering the subaerial accretionary wedge of the western part of the Makran Subduction zone. Each of the roughly north-south trending profiles was approximately 200 km long, and on each profile 9 to 10 artificial shots with charges between 400 and 800 kg of explosives were fired. The seismic signals were observed by 300 autonomous digital recorders with geophones on each profile. This dataset consists of the raw (continuous) data of the recorders (in proprietary cube format and MSEED-format) and the shot records in SEGY-format (standard exchange formats).,The Geophysical Instrument Pool Potsdam (GIPP) provides field instruments for (temporary) seismological studies (both controlled source and earthquake seismology) and for magnetotelluric (electromagnetic) experiments. The GIPP is operated by the GFZ German Research Centre for Geosciences. The instrument facility is open for academic use. Instrument applications are evaluated and ranked by an external steering board. See Haberland and Ritter (2016) and https://www.gfz-potsdam.de/gipp for more information.,
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  • Dataset
During the 2018 “Mackenzie Delta Permafrost Field Campaign” (mCan2018), a test campaign within the “Modular Observation solutions for Earth Systems” (MOSES) program, ambient seismic noise recordings at the sea bottom were acquired along two 300 m long transects from the shoreline to shallow marine area close to Tuktoyaktuk Island (Canada). In total, 21 measurements were taken. Raw data is provided in proprietary “Cube” format and standard mseed format.,The Geophysical Instrument Pool Potsdam (GIPP) provides field instruments for (temporary) seismological studies (both controlled source and earthquake seismology) and for magnetotelluric (electromagnetic) experiments. The GIPP is operated by the GFZ German Research Centre for Geosciences. The instrument facility is open for academic use. Instrument applications are evaluated and ranked by an external steering board. See Haberland and Ritter (2016) and https://www.gfz-potsdam.de/gipp for more information.,
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  • Dataset
The here provided data are part of a broader analysis of past and present stimulation projects, revealing that the temporal evolution and growth of maximum observed moment magnitudes may be linked directly to the injected fluid volume and hydraulic energy. Analyzed projects include the most prominent European Enhanced Geothermal System (EGS) projects in Basel, Switzerland (BAS) and Soultz-sous-Forêts (STZ), France. In Soultz, three different stimulations over the course of 10 years were performed in different wells and different depths. Therefore, we differentiate between the injections in 1993 (STZ93), 2000 (STZ00), and in 2003 (STZ03). We also included the deepest EGS Project to date (St1), located in Helsinki, Finland. Furthermore, we included the fluid-injection experiment from the German super deep scientific drilling hole (KTB), two Australian EGS projects, located at Paralana (Para) and the 2003 Cooper Basin (CBN) injection, as well as the EGS project near Pohang, South Korea. Finally, we also considered a single well injection period at the Berlín geothermal field (BGF), El Salvador, representing the only hydrothermal site considered here. For each project the cumulative volume injected is provided along with the applied hydraulic energy, maximum observed seismic moment, cumulative seismic moment, and injection efficiency as tab separated ASCII files with the .csv extension. All stimulation files are combined into a single .zip archive. More details on processing steps and references herein can be found in the accompanying data description.
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  • Dataset
In the data set we provide both mantle velocity and maximum principal stress orientation resulting from a geodynamical model. The data are calculated with use of the ProSpher 3D code in a spectral domain by spherical harmonics decomposition. The resolution of the model is of 120 spherical harmonics laterally and 50 km in depth. For velocity data (file set: Petrunin-etal19-Vel_XXX.dat), the 1st column represents longitude, 2nd column – latitude, 3d, 4th , 5th – longitudinal, latitudinal, and radial components of velocity in mm/yr, correspondingly. For maximum principal stress orientation data (file set: Petrunin-etal19-SH_XXX.dat), the 1st column represents longitude, 2nd column – latitude, 3d, 4th – longitudinal and latitudinal components of the unit vector representing maximum principal stress direction.
Data Types:
  • Dataset
Sampling large river´s sediment at outlets for cosmogenic nuclide analysis yields mean denudation rates of the sediment producing areas that average local variations in denudation commonly found in small rivers. Using this approach, we measured in situ cosmogenic 26Al and 10Be concentrations in sands of >50 large rivers over a range of climatic and tectonic regimes covering 32% of Earth’s terrestrial surface. River samples were processed in the Helmholtz Laboratory for the Geochemistry of the Earth Surface (HELGES) (von Blanckenburg et al., 2016). 10Be/9Be ratios were measured by Accelerator Mass Spectrometry (AMS) at the University of Cologne and normalized to the KN01-6-2 and KN01-5-3 standards. Denudation rates were calculated using a time-dependent scaling scheme according to Lal/Stone ”Lm” scaling (see Balco et al., 2008) together with a sea level high latitude (SLHL) production rate of 4.13 at/(gxyr) as reported by Martin et al. (2017). Measured in the mineral quartz, the cosmogenic nuclides 26Al and 10Be provide information on how fast Earth´s surface is lowering through denudation. If sediment is however stored in catchments over time spans similar to the nuclides half-lives (being 0.7 Myr and 1.4 Myr for 26Al and 10Be, respectively), the nuclide´s budget is disturbed, and meaningful denudation rates cannot be calculated. The ratio of 26Al/10Be informs us about these disturbances. In 35% of analyzed rivers, we find 26Al/10Be ratios significantly lower than these nuclides´ surface production rate ratio of 6.75 in quartz, indicating sediment storage and burial exceeding 0.5 Myr. We invoke mainly a combination of slow erosion, long transport, and low runoff for these low ratios. In the other 65% of rivers we find 26Al/10Be ratios within uncertainty of their surface production-rate ratio, indicating cosmogenic steady state, and hence meaningful denudation rates can be calculated. For these rivers, we derive a global source-area denudation rate of 140 t/km^2/yr that translates to a flux of 3.10 Gt/yr. By assuming that this sub-dataset is geomorphically representative of the global land surface, we upscale this value to the total surface area for exorheic basins, thereby obtaining a global denudation flux from cosmogenic nuclides of 15.1 Gt/yr that integrates over the past 5 kyr. In Table S1, we provide detailed 10Be nuclide production rates and their correction due to ice shielding and carbonates that are necessary to calculate denudation rates. We provide International GeoSample Numbers (ISGN) for samples used in the analysis, except values that were compiled from published sources. We then compare these denudation rates, converted to sediment fluxes, to published values of sediment fluxes from river load gauging. We find that our cosmogenic nuclide-derived sediment flux value is similar, within uncertainty, to published values from cosmogenic nuclides from small river basins (23 Gt/yr) upscaled using a global slope model, and modern sediment and dissolved loads exported to the oceans (23.6 Gt/yr). In Table S3, we compiled these modern sediment loads and give their references. We also compiled runoff values (mm/yr) from published sources (Table S2) that are used to infer what controls denudation rates. For more details on the sampling and analytical methods, please consult the data description part of this publication.
Data Types:
  • Dataset
Multi-temporal landslide inventories are important information for the understanding of landslide dynamics and related predisposing and triggering factors, and thus a crucial prerequisite for probabilistic hazard and risk assessment. Despite the great importance of these inventories, they do not exist for many landslide prone regions in the world. In this context, the recently evolving global-scale availability of high temporal and spatial resolution optical satellite imagery (RapidEye, Sentinel-2A/B, planet) has opened up new opportunities for the creation of these multi-temporal inventories. Taking up on these at the time still to be evolving opportunities, a semi-automated spatiotemporal landslide mapper was developed at the Remote Sensing Section of the GFZ Potsdam being capable of deriving post-failure landslide objects (polygons) from optical satellite time series data (Behling et al., 2014). The developed algorithm was applied to a 7500 km² study area using RapidEye time series data which were acquired in the frame of the RESA project (Project ID 424) for the time period between 2009 and 2013. A multi-temporal landslide inventory from 1986 to 2013 derived from multi-sensor optical satellite time series data is available as separate publications (Behling et al., 2016; Behling and Roessner, 2020). The resulting multi-temporal landslide inventory being subject of this data publication is supplementary to the article of Behling et al. (2014), which describes the developed spatiotemporal landslide mapper in detail. This landslide mapper detects landslide objects by analyzing temporal NDVI-based vegetation cover changes and relief-oriented parameters in a rule-based approach combining pixel- and object-based analysis. Typical landslide-related vegetation changes comprise abrupt disturbances of the vegetation cover in the result of the actual failure as well as post-failure revegetation which usually happens at a slower pace compared to vegetation growth in the surrounding undisturbed areas, since the displaced landslide masses are susceptible to subsequent erosion and reactivation processes. The resulting landslide-specific temporal surface cover dynamics in form of temporal trajectories is used as input information to detect freshly occurred landslides and to separate them from other temporal variations in the surrounding vegetation cover (e.g., seasonal vegetation changes or changes due to agricultural activities) and from permanently non-vegetated areas (e.g., urban non-vegetated areas, water bodies, rock outcrops). For a detailed description of the methodology of the spatiotemporal landslide mapper, please see Behling et al. (2014). The data are provided in vector format (polygons) in form of a standard shapefile contained in the zip-file Behling_et-al_2014_landslide_inventory_SouthernKyrgyzstan_2009_2013.zip and are described in more detail in the data description file.
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  • Dataset
The European exposure data for BN-FLEMO models contains three datasets that can be used with BN-FLEMO models for the estimation of flood loss. The dataset contains: (1) European asset map with unit area values of residential and commercial buildings in EURO per square meter based on reconstruction cost and NUTS-3 regions or national GDP per capita. The values are mapped on CORINE land cover classes for urban areas (111 and 112). (2) Residential building areas in Europe with building area sizes in square meter for each NUTS-3 region. The building area sizes were calculated based on the building geometries extracted from the OSM database. (3) Flood experience in Europe with geometries of historic flood events (1985- 2015) with start date of the events. This dataset can be used to calculate the number of past flood events in an area.
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  • Dataset