11 documents found in 497ms
# 1
Reyer, Christopher • Asrar, Gassem • Betts, Richard • Chang, Jinfeng • Chen, Min • (et. al.)
Abstract: The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically-relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate change impacts across sectors. ISIMIP2a is the second ISIMIP simulation round, focusing on historical simulations (1971-2010) of climate impacts on agriculture, fisheries, permafrost, biomes, regional and global water and forests. This will serve as a basis for model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. The focus topic for ISIMIP2a is model validation, in particular with respect to the representation of impacts of extreme weather events and climate variability. During this phase, four common global observational climate data sets were provided across all impact models and sectors. In addition, appropriate observational data sets of impacts for each sector were collected, against which the models can be benchmarked. Access to all these data is provided through a central ISIMIP archive (see https://www.isimip.org/gettingstarted/#input-data-bias-correction). The ISIMIP2a biome outputs are based on simulations from 8 global vegetation (biomes) models (CARAIB, DLEM, JULES-B1, LPJ-GUESS, LPJmL, ORCHIDEE, VEGAS, VISIT) according to the ISIMIP2a protocol (https://www.isimip.org/protocol/#isimip2a).
The ISIMIP2a biome outputs are based on simulations by different global vegetation models (CARAIB, DLEM, JULES-UoE, LPJ-GUESS, LPJmL, ORCHIDEE, VEGAS, VISIT) following the ISIMIP2a protocol. The biome models simulate biogeochemical processes, biogeography and ecosystem dynamics of natural vegetation and managed lands based on soil, climate and land-use information. A more detailed description of the models and model-specific amendments of the protocol are available here: https://www.isimip.org/impactmodels/.
# 2
Gosling, Simon • Müller Schmied, Hannes • Betts, Richard • Chang, Jinfeng • Ciais, Philippe • (et. al.)
Abstract: The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically-relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate change impacts across sectors. ISIMIP2a is the second ISIMIP simulation round, focusing on historical simulations (1971-2010 approx.) of climate impacts on agriculture, fisheries, permafrost, biomes, regional and global water and forests. This may serve as a basis for model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. The focus topic for ISIMIP2a is model evaluation and validation, in particular with respect to the representation of impacts of extreme weather events and climate variability. During this phase, four common global observational climate data sets were provided across all impact models and sectors. In addition, appropriate observational data sets of impacts for each sector were collected, against which the models can be benchmarked. Access to the input data for the impact models is provided through a central ISIMIP archive (see https://www.isimip.org/gettingstarted/#input-data-bias-correction). This entry refers to the ISIMIP2a simulation data from global hydrology models: CLM4, DBH, H08, JULES_W1, JULES_B1, LPJmL, MATSIRO, MPI-HM, ORCHIDEE, PCR-GLOBWB, SWBM, VIC, WaterGAP2.
The ISIMIP2a water (global) outputs are based on simulations from 13 global hydrology models (see listing) according to the ISIMIP2a protocol (https://www.isimip.org/protocol/#isimip2a). The models simulate hydrological processes and dynamics (part of the models also considering human water abstractions and reservoir regulation) based on climate and physio-geographical information. A more detailed description of the models and model-specific amendments of the protocol are available here: https://www.isimip.org/impactmodels/.
# 3
Sembroni, Andrea • Kiraly, Agnes • Faccenna, Claudio • Funiciello, Francesca • Becker, Thorsten W. • (et. al.)
Abstract: We present videos and figures from 22 scaled analogue models used to investigate the interactions between a density anomaly rising in the mantle and the lithosphere in a Newtonian system. The experimental setup consists of a two layers viscous lithosphere-upper mantle system obtained by using silicone putty-glucose syrup in a tank sized 40 cm × 40 cm× 50 cm. Glucose syrup (i.e., mantle) is a Newtonian, low viscosity, high-density fluid while silicone putty (i.e., lithosphere) is a visco-elastic material that behaves in a quasi-Newtonian fashion. The mantle upwelling (i.e., plume head) is produced by a high viscosity, low-density silicone sphere with a constant radius (15 mm) rising through the mantle at an average rise velocity of ~2.6 mm/s. A side-view camera images the ascending path of the sphere, allowing to track the sphere location and compute its velocity. A top-view, 3-D scanner records the evolution of topography from which the lithospheric uplift rate is inferred. All details about the model set-up, modeling results and interpretation are detailed in Sembroni et al. (2017). The additional material presented in this publication includes 2 tables, 5 figures, and 23 time-lapse movie. The rheological properties of materials used in each model are listed in Table 1.Table 2 is an excel file where the raw data of the models are specified (i.e., bulge width, topography, and uplift rate). Such data have been obtained by the 3-D scanner and then processed by a MATLAB code.Figure 1, Figure 2, Figure 3, Figure 4, Figure 5 represent the 2-D topography evolution of the bulge in each experiment. Images have been grouped by considering the different experimental setups (i.e., homogeneous continental lithosphere - Figure 1, homogeneous oceanic lithosphere - Figure 2, low viscous decoupling layer - Figure 3, intermediate viscous decoupling layer - Figure 4, high viscous decoupling layer - Figure 5). Such figures consist of topographic profiles extracted from the surface obtained by the 3-D scanner in four different time steps (red numbers in the figures). 22 side-view videos (from Movie 1 to Movie 22) show the progress of the models from the releasing to the impingement of the sphere beneath the plate. The velocity of the video has been accelerated by a factor of 7. While, the first 22 movies show the evolution of the experiments, Movie 23 shows the mantle convective flow associated to the ascending path of the mantle upwelling. Such flow has been detected by tracking the bubbles inside the syrup. In this model, no lithosphere has been placed on top of the syrup.
# 4
Ritter, Malte Christian • Santimano, Tasca • Rosenau, Matthias • Leever, Karen • Oncken, Onno
Abstract: This dataset is supplementary to the article of Ritter et al. (2017). In this article, a new experimental device is presented that facilitates precise measurements of boundary forces and surface deformation at high temporal and spatial resolution. This supplementary dataset contains the measurement data from two experiments carried out in this new experimental device: one experiment of an accretionary critical wedge and one of Riedel-type strike-slip deformation. For a detailed description of the set-up and an analysis of the data, please see Ritter et al. (2017). The data available for either experiment are:• A video showing deformation in top view together with the evolution of boundary force. This file is in AVI-format.• A time-series of 2D vector fields describing the surface deformation. These vector fields were obtained from top-view video images of the respective experiment by means of digital image correlation (DIC). Each vector field is contained in a separate file; the files are consecutively numbered. The vector fields are stored in *.mat-files that can be opened using e.g. the software Matlab or the freely available GNU Octave. They take the form of Matlab structure arrays and are compatible to the PIVmat-toolbox by Moisy (2016) that is freely available. The most important fields of the structure are: x and y, that are vectors spanning a coordinate system, and vx and vy, which are arrays containing the actual vector components in x- and y-direction, respectively.• A file containing the measurements of the boundary force applied to drive deformation. This file is also a *.mat-file, containing a structure F with fields force, velocity and position. These fields are vectors describing the force applied by the indenter, the indenter velocity and the indenter position
# 5
Brizzi, Silvia • Funiciello, Francesca • Corbi, Fabio • Di Giuseppe, Erika • Mojoli, Giorgio
Abstract: Gelatin is a versatile material commonly used in analogue modelling because of its complex rheology, which allows simulating a wide range of tectonic processes requiring either elastic (e.g., dyke intrusions models) and viscoelastic behavior (e.g., analog earthquakes models). Salt (NaCl) is generally added to gelatin to improve the scaling of the models by increasing the density of the material. The addition of salt results also in a weakening of the gelatin structure, which in turn can dramatically affect its rheological properties. Here, we provide raw data of rheometric measurements performed to test the rheological properties of type A (pig-skin) 2.5 wt% gelatin at T=10°C as a function of salt concentration and ageing time. Each sample was analyzed using dynamical oscillation tests (i.e., amplitude, frequency and time sweep tests) in shear strain controlled mode. All details about sample preparation procedure, measuring protocol, as well as results and data interpretation can be found in Brizzi et al. (2016). The data are provided as Excel files in *.xlsx format and comma-separated files in *.csv format. Each contains multiple measurements. In the Excel files, each measurement is presented as a table in different spreadsheets. In the comma-separated files, each measurement start with its own data series information, followed by the actual data. All files can be opened using MS Excel or equivalent software. An overview of tested salt concentrations and performed measurements can be found in the Explanation_Brizzi_et_al_2016.pdf file. A full list of the files included is given in List_of_files_Brizzi_et_al_2016.pdf.
# 6
Souloumiac, Pauline • Maillot, Bertrand • Herbert, Justin W. • McBeck, Jessica A. • Cooke, Michele L.
Abstract: The data set includes photos, force measurements, and incremental displacement fields captured in experiment E240 run at the physical modeling laboratory (GEC) at the Université de Cergy-Pontoise. We built the accretionary wedge using a novel sedimentation device [Maillot, 2013] that distributes sand in planar layers and creates homogeneous sandpacks. We include photos of the side of the accretionary wedge in a zipped folder (E240_sideviews). Throughout the experiment, we took a photo every 5 seconds. We include the incremental displacement fields calculated from digital image correlation of sequential photos [Adam et al., 2005; Hoth, 2005] as matlab (.mat) files in a zipped folder (E240_001-062_DIC_MAT), and as .csv files in a zipped folder (E240_001-062_DIC_CSV). The .mat and .csv files are numbered to indicate which sequential photo pairs were used to calculate the displacements. For example, E240_001-062_0001_CSV.csv (and E240_001-062_0001.mat) contain the incremental displacements between photo 001.jpg and 002.jpg. All files are included in a single zip folder (Souloumiac-et-al-2017-supplementary-datasets.zip). The matlab files include the variable arrays x, y, u, v, which are the x and y coordinates (in pixels relative to the upper left corner of the image), and the horizontal (u) and vertical (v) incremental displacement fields (in pixels), respectively. The .csv files contain four columns of data with the x and y coordinates in the first two columns, and the horizontal (u) and vertical (v) displacements in the last two columns. We include force measurements in a text file (E240_force_corrected) with two columns: the first column is the total displacement of the backwall in millimeters at the time that the force measurement was recorded, and the second column is the normal force exerted on the backwall, in Newtons. The force measurements are calculated from measurements of strain gauges mounted on a wall of the sand box (i.e., the backwall) [e.g., Souloumiac et al., 2012].
# 7
Krysanova, Valentina • Hattermann, Fred • Aich, Valentin • Alemayehu, Tadesse • Arheimer, Berit • (et. al.)
Abstract: The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically-relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate change impacts across sectors. ISIMIP2a is the second ISIMIP simulation round, focusing on historical simulations (1971-2010) of climate impacts on agriculture, fisheries, permafrost, biomes, regional and global water and forests. This will serve as a basis for model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. In the regional water sector, future simulations of climate-change impacts were also carried out, using climate data from five global climate models (GCMs: HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, GFDL-ESM2M and NorESM1-M) for the four Representative Concentration Pathways (RCPs: RCP2.6, RCP4.5, RCP6.0 and RCP8.5). The focus topic for ISIMIP2a is model evaluation and validation, in particular with respect to the representation of impacts of extreme weather events and climate variability. During this phase, four common global observational climate data sets were provided across all impact models and sectors. In addition, appropriate observational data sets of impacts for each sector were collected, against which the models can be benchmarked. Access to the input data for the impact models is provided through a central ISIMIP archive (see https://www.isimip.org/gettingstarted/#input-data-bias-correction). This entry refers to the ISIMIP2a simulation data from regional hydrology models (river basins in brackets):HBV-CMA (Yangtze)HBV-IWW (Tagus)HBV-JLU (Rhine, Ganges, Mississippi)HBV-PIK (Rhine, Niger, Yellow, Blue Nile, Amazon)HYMOD-JLU (Rhine, Ganges, Mississippi)HYMOD-UFZ (Rhine, Niger, Blue Nile, Ganges, Yellow, Darling, Mississippi, Amazon)HYPE (Rhine, Tagus, Niger, Ganges, Lena, Mackenzie)mHM (Rhine, Niger, Blue Nile, Ganges, Yellow, Darling, Mississippi, Amazon)SWAP (Rhine, Tagus, Niger, Ganges, Yellow, Yangtze; Lena, Darling, MacKenzie, Mississippi, Amazon)SWAT (Yangtze; Darling; Blue Nile; Amazon; Mississippi; Niger)SWIM (Rhine, Yellow, Mississippi; Niger; Lena; Tagus; Blue Nile; Yangtze; Ganges, Amazon)VIC (Tagus, Blue Nile, Yellow, Lena, Darling, Amazon, MacKenzie; Rhine, Niger, Mississippi; Ganges; Yangtze)VIP (Yellow)WaterGAP3 (Rhine, Tagus, Niger, Blue Nile, Ganges, Yellow, Lena, Mississippi)ECOMAG (Lena, MacKenzie)
The ISIMIP2a water (regional) outputs are based on simulations from 15 regional hydrology models (see listing) according to the ISIMIP2a protocol (https://www.isimip.org/protocol/#isimip2a). The models simulate hydrological processes and dynamics (part of the models also considering human water abstractions and reservoir regulation) based on climate and physio-geographical information. A more detailed description of the models and model-specific amendments of the protocol are available here: https://www.isimip.org/impactmodels/.
# 8
Arneth, Almut • Balkovic, Juraj • Ciais, Philippe • de Wit, Allard • Deryng, Delphine • (et. al.)
Abstract: The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) provides a framework for the collation of a set of consistent, multi-sector, multi-scale climate-impact simulations, based on scientifically and politically-relevant historical and future scenarios. This framework serves as a basis for robust projections of climate impacts, as well as facilitating model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. It also provides a unique opportunity to consider interactions between climate change impacts across sectors. ISIMIP2a is the second ISIMIP simulation round, focusing on historical simulations (1971-2010) of climate impacts on agriculture, fisheries, permafrost, biomes, regional and global water and forests. This will serve as a basis for model evaluation and improvement, allowing for improved estimates of the biophysical and socio-economic impacts of climate change at different levels of global warming. The focus topic for ISIMIP2a is model evaluation and validation, in particular with respect to the representation of impacts of extreme weather events and climate variability. During this phase, four common global observational climate data sets were provided across all impact models and sectors. In addition, appropriate observational data sets of impacts for each sector were collected, against which the models can be benchmarked. Access to the input data for the impact models is provided through a central ISIMIP archive (see https://www.isimip.org/gettingstarted/#input-data-bias-correction). This entry refers to the ISIMIP2a simulation data from Agricultural Sector models: CGMS-WOFOST, CLM-Crop, EPIC-Boku, EPIC-IIASA, EPIC-TAMU, GEPIC, LPJ-GUESS, LPJmL, ORCHIDEE-CROP, pAPSIM, pDSSAT, PEGASUS, PEPIC, PRYSBI2.
The ISIMIP2a agriculture outputs are based on simulations from 14 agricultural sector models (see listing) according to the ISIMIP2a protocol (https://www.isimip.org/protocol/#isimip2a). The models simulate cop yields and irrigation water withdrawal (assuming unlimited water supply), based on planting dates, crop variety parameters, approximate maturity dates (to allow for spatially-explicit variety parameterization), as well as fertilizer use (N, P, K). A more detailed description of the models and model-specific amendments of the protocol are available here: https://www.isimip.org/impactmodels/.
# 9
van den Ende, Martijn
Abstract: Intergranular pressure solution creep is an important deformation mechanism in the Earth’s crust. The phenomenon has been frequently studied and several analytical models have been proposed that describe its constitutive behavior. These models require assumptions regarding the geometry of the aggregate and the grain size distribution in order to solve for the contact stresses, and often neglect shear tractions. Furthermore, analytical models tend to overestimate experimental compaction rates at low porosities, an observation for which the underlying mechanisms remain to be elucidated. Here we present a conceptually simple, 3D Discrete Element Method (DEM) approach for simulating intergranular pressure solution creep that explicitly models individual grains, relaxing many of the assumptions that are required by analytical models. The DEM model is validated against experiments by direct comparison of macroscopic sample compaction rates. Furthermore, the sensitivity of the overall DEM compaction rate to the grain size and applied stress is tested. The effects of the interparticle friction and of a distributed grain size on macroscopic strain rates are subsequently investigated. Overall, we find that the DEM model is capable of reproducing realistic compaction behavior, and that the strain rates produced by the model are in good agreement with uniaxial compaction experiments. Characteristic features, such as the dependence of the strain rate on grain size and applied stress, as predicted by analytical models, are also observed in the simulations. DEM results show that interparticle friction and a distributed grain size affect the compaction rates by less than half an order of magnitude. The zip-file Van-den-Ende_2017.018.zip contains several folders with raw data from the laboratory experiments, output data from Discrete Element Method simulations, and Python 2.7 script files that read and process these data. All data are stored in ASCII format.
# 10
Darmawan, Herlan • Walter, Thomas • Richter, Nicole • Nikkoo, Mehdi
Abstract: 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.
spinning wheel Loading next page