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# 11
Billing, Maik • Thonicke, Kirsten • von Bloh, Werner • Sakschewski, Boris
Abstract: LPJmL-FIT is process- and trait-based vegetation model. It is a subversion of the model LPJmL simulating patches of competing individual trees with flexible functional traits and empirically derived relations between these traits. Trait composition, productivity and stability of a forest are a result of environmental and competitive filtering. A detailed description of LPJmL-FIT (basic features and differences to LPJmL) is given by Sakschewski et al. (Sakschewski et al., 2015, https://doi.org/10.1111/gcb.12870). LPJmL-FIT was originally developed for tropical forests and has been adapted to European forests by Thonicke et al. (2020). The data covers southern and central Europe (29.5°N – 62°N, 11°W – 36°O) on a spatial resolution of 0.5° covering the years 1901-2013. Tree height, leaf and stem traits (specific leaf area, wood density, leaf longevity; aggregated), individual traits of simulated trees, vegetation distribution (foliage projected cover, FPC), vegetation carbon and fire carbon emissions are given on an annual basis. Gross primary productivity is provided monthly. Tree height and leaf and stem traits are biomass weighted. For evaluation of the dataset R- and MATLAB-scripts are provided.An overview and description of all variables are found in the file description.
# 12
Ulbricht, Damian • Klump, Jens • Conze, Ronald
Abstract: These files generate data catalogue pages from ISO19139, GMCD-DIF and Datacite metadata by using XSLT stylesheet transformation on XML metadata. This supplement contains four files: * The file "datasetoverview.xslt" is the conversion stylesheet in XSLT 1.0. It is a minified version of the stylesheet we use at GFZ to produce Hypertext Markup Language for presentation in internet browsers.* The file "datasetoverview.css" is the cascading style sheet with the layout definitions.* The file "10.1594.GFZ.SDDB.1409.xml" contains example data from the eSciDoc repository. At the document start there is a reference to the conversion stylesheet to allow an in-browser conversion.* A "README.txt" file.
# 13
Dielforder, Armin • Hetzel, Ralf • Oncken, Onno
Abstract: The data are the source data for Figures 2, 3, and 4 in the paper "Megathrust shear force controls mountain height at convergent plate margins" by Dielforder, Hetzel, and Oncken (2020). Details on the calculation of the data are given in the methods section of this paper. The archive "2020-002_Dielforder-et-al_shear_stress_envelopes.zip" includes ten csv-files entitled "n_shear_stress_envelope.csv", where n is a number from 1 to 10 and refers to the margin transects studied in the paper (for labeling see below). The files provide the source data for the ten shear stress envelopes shown in Figure 2. In each file, the values in the first, second, and third column are depth (m), shear stress (MPa), and the one standard deviation of the shear stress (MPa), respectively. The archive "2020-002_Dielforder-et-al_shear_force_solutions.zip" contains one csv-file including 100,000 model solutions for the megathrust shear force (TN m-1). Columns 1 to 10 contain the solutions for the respective margin transects. The archive "2020-002_Dielforder-et-al_force_balance_solutions.zip" includes ten csv-files entitled "n_force_balance_solutions.csv" following the same labeling scheme as above. The values in the first, second, and third column are the 100,000 model solutions for the tectonically supported elevation TSE (m), the shear-force component required to support the submarine margin topography F_SMT (TN m-1), and the shear-force component available to support subaerial mountain height [delta]F_s (TN m-1), respectively. For the Himalayas (10_force_balance_solutions.csv), there are only values in the first column, because the Himalayas have no submarine margin topography. The 100,000 model solutions were used to calculate the mean values and one standard deviation shown in Figures 3 and 4 and listed in Table 1 and Extended Data Table 3. Labeling: 1, Northern Cascadia; 2, 3, and 4, Andes at 23º S, 34º S, and 36º S, respectively; 5, Northern Sumatra; 6, Kamchatka; 7, Japan Trench; 8, Nankai Trough; 9, Northern Hikurangi; 10, Himalayas. The references listed below provide the input parameters used to calculate the shear stress envelopes, F_s, TSE, F_SMT and [delta]Fs.
# 14
Baes, Marzieh • Sobolev, Stephan • Gerya, Taras • Brune, Sascha
Abstract: The data are the numerical modeling results to investigate plume-induced subduction initation on which the figures of the paper "Plume-induced subduction initiation: single- or multi-slab subduction?" by Baes, Sobolev, Gerya and Brune are based. Detailed description on how they are obtained is given in that article (Baes et al., 2020). The naming of the files is based on the number of figures in the paper. Each zipped file contains input files (init.t3c and mode.t3c) and output files (*.vtr).
# 15
Stromeyer, Dietrich • Heidbach, Oliver
Abstract: For the visualization and analysis of the stress field from 4D thermo-hydro-mechanical (THM) numerical model results two main technical steps are necessary. First, one has to derive from the six independent components of the stress tensor scalar and vector values such as the ori-entation and magnitude of the maximum and minimum horizontal stress, stress ratios, differential stress. It is also of great interest to display e.g. the normal and shear stress with respect to an arbitrarily given surface. Second, an appropriate geometry has to be given such as cross sections, profile e.g. for borehole pathways or surfaces on which the model results and further derived values are interpolated. This includes the three field variables temperature, pore pressure and the displacement vector.To facilitate and automate these steps the add-on GeoStress for the professional visualization software Tecplot 360 EX has been programmed. Besides the aforementioned values derived from the stress tensor the tool also allows to calculate the values of Coulomb Failure Stress (CFS), Slip and Dilation tendency (ST and DT) and Fracture Potential (FP). GeoStress also estimates kinematic variables such as horizontal slip, dip slip, rake vector of faults that are implemented as contact surfaces in the geomechanical-numerical model as well as the true vertical depth. Furthermore, the add-on can export surfaces and polylines and map on these all availble stress values.The technical report describes the technical details of the visualization tool, its usage and ex-emplifies its application using the results of a 3D example of a geomechanical-numerical model of the stress field. The numerical solution is achieved with the finite element software Abaqus version 6.11. It also presents a number of special features of Tecplot 360 EX in combination with GeoStress that allow a professional and efficient analysis. The Add-on and a number of example and input files are provided at http://doi.org/10.5880/wsm.2017.001.
# 16
van Schaik, Nicolette Loes M.B. • Zangerlé, Anne • Hohenbrink, Tobias L. • Reck, Arne • Schneider, Anne-Kathrin • (et. al.)
Abstract: This dataset consists of spatially and temporally resolved data of dye-infiltration patterns, earthworms and macropores as well as supporting data, such as land use, soil moisture content, soil temperature, bulk density, and soil texture, in the Wollefsbach area of the Attert Catchment in Luxembourg (Pfister et al., 2005). The data was gathered in six measurement campaigns in the period from May 2015 to March 2016. During each measurement campaign we measured at five random sites on each of six chosen fields: three grasslands and three agricultural fields. At each measurement site a combination of measurements was performed: infiltration patterns of blue stained water, earthworm abundance (species level), macropore counts on horizontal soil profiles (in three depths, discriminating three size classes and stained or non-stained), soil temperature and moisture contents in three depths. Finally, undisturbed soil core samples were taken during one campaign for the determination of the texture and bulk density at different sampling sites. In the data table we also include GIS derived values of elevation, slope, aspect, heat load index, and topographical wetness index. Details on all the measurement methods, GIS-analysis methods and units of the data are given below. This data was gathered as part of the Joint Research Project “Catchments as Organised Systems” (CAOS, Zehe et al., 2014) funded by the German Research Foundation. ---------------------------------------------------Version history: 10 February 2020, release of Version 1.1.: The authors discovered that some rows in the data table “Earthworms_Macropores_Data.csv” for September Field 3 and Field 4 were accidentally exchanged. Compared to version 1.0, the data in rows 71 to 75 (Sept_3_1 to Sept_3_5) were exchanged with the data in rows 76 to 80 (Sept_4_1 to Sept_4_5). The authors apologise for this and ask everyone who downloaded the data of version 1.0 are advised to only use version 1.1, because there was an error which could lead to wrong results. Nevertheless, version 1.0 of the data table is available in the "previous-versions" subfolder via the Data Download link. The infiltration data included in “2019-022_vanSchaik-et-al_Infiltration_patterns.zip” remain unchanged.
# 17
Petrunin, Alexey • Kaban, Mikhail
Abstract: 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.
# 18
Cooke, Michele • Toenenboehn, Kevin • Hatch, Jennifer
Abstract: Experiments of oblique convergence at angles of 5, 10, 15, 20, 25 and 30 degrees from the margin within wet kaolin. One suite of experiments, denoted as ‘precut’, has a vertical surface precut within the clay with an electrified wire. The precut surface lies directly above the basal oblique dislocation. The other suite of experiments is ‘uncut’. Regardless of whether the experiments have a precut surface, slip partitioned fault systems, develop and persist in the experiments. Such systems have two simultaneously active faults with similar strike but different slip sense. Slip partitioning also develops regardless of whether the system first grows a reverse fault or strike slip fault in the experiment. The sequence and nature of strike-slip and reverse fault development depends on present of existing cut and convergence angle. This data set includes time series of incremental displacement maps for eleven experiments performed at the University of Massachusetts Amherst in January 2017 and March 2018 as well as animations of strain and uplift. The dataset includes the 30˚ convergence experiment with precut vertical surface but the 30˚ uncut experiment has not yet been performed. The time series data are organized into 11 netCDF files. The name of each file states the obliquity of convergence and whether the vertical surface was precut or not. Each netCDF file contains the following • ux = the incremental displacement field within the ROI (Region Of Interest) parallel to the margin (x-direction). The third dimension in the array corresponds to increment of deformation through the experiment. Units are mm.• uy = the incremental displacement field within the ROI perpendicular to the margin (y-direction). The third dimension in the array corresponds to increment of deformation through the experiment. Units are mm.• x = position parallel to the margin. Units are mm.• y = position perpendicular to the margin. Units are mm. The incremental displacements are calculated from DIC of photographs taken every 30 seconds using PIVlab (Thielicke, 2019). The net stepper motor speed is ~0.5 mm/min. The animations show strain evolution of all eleven experiments and uplift evolution of the 10 degree precut experiment. The strain evolution experiments overlay colormaps of incremental strain between successive photos on photographs of the experiment. Color saturation indicates the strain rate and hue indicates the slip vector. The uplift maps were made from stereovision analysis from pairs of photos. In most experiments, decorrelation of portions of the map prevented us from producing high quality uplift evolution animations from the start to the end of the experiment. Only the 10 degree convergence with precut vertical surface experiment had full coherence of uplift signal throughout the experiment and that animation.
# 19
Groß, Philip • Handy, Mark • John, Timm • Pestal, Gerhard • Pleuger, Jan
Abstract: 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.
# 20
Haberland, Christian • Mokhtari, Mohammad • Babaei, Hassan Ali • Ryberg, Trond • Masoodi, Mehdi • (et. al.)
Abstract: 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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