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# 6591
Itzerott, Sibylle • Hohmann, Christian • Stender, Vivien • Maass, Holger • Borg, Erik • (et. al.)
Abstract: This data collection compiles the soil moisture stations of the DEMMIN test site operated by the GFZ German Research Centre for Geosciences in cooperation with the National Ground Segment Neustrelitz (Remote Sensing Data Center, German Aerospace Center DLR). The site was originally installed by the DLR in 2000 and has become part of the TERENO Northeastern German Lowland Observatory in 2011. This data collection only comprises the GFZ soil moisture stations. Climate stations operated by DLR and GFZ are published as separate data compilations (Borg et al. 2018, Itzerott et al., 2018). The DEMMIN test site is located within the central monitoring sites of the TERENO Northeastern German Lowland Observatory. It covers 900 km² and exhibits mostly glacial formed lowlands with terminal moraines in the southern part, containing the highest elevation of 83m a.s.l. The region between the rivers Tollense and Peene consists of flat ground moraines, whereas undulating ground moraines determine the landscape character north of the river Peene. The lowest elevation is located near the town Loitz with 0.5m a.s.l. The region is characterized by intense agricultural use and the three rivers Tollense and Trebel which confluence into the Peene River at the Hanseatic city Demmin. The present climate is characterized by a long-term (1981–2010) mean temperature of 8.7 °C and mean precipitation of 584 mm/year, measured at the Teterow weather station by Deutscher Wetterdienst (DWD). The Northeastern German Lowland Observatory is situated in a region shaped by recurring glacial and periglacial processes since at least half a million years. Within this period, three major glaciations covered the entire region, the last time this happened approximately 25-15 k ago (Weichselian glaciation). Since that time, a young morainic landscape developed characterized by many lakes and river systems that are connected to the shallow ground water table. The test site is instrumented with more than 40 environmental measurement stations (DLR, GFZ) and 63 soil moisture stations (GFZ). A lysimeter-hexagon (DLR, FZJ) was installed near to the village Rustow and is part of the SOILCan project. A crane completes the measurement infrastructure currently available in the test site installed by GFZ/ DLR in 2011. Data is automatically collected via a telemetry network by DLR. The quality control of all environmental data is carried out by DLR using visual inspection and automatic quality processing is performed by GFZ since 2012. The delivered dataset contains the measured data and quality flags indicating the validity of each measured value and detected reasons for exclusion. The dataset is also available through the TERENO Data Discovery Portal. The dataset will be dynamically extended as more data is acquired at the stations. New data will be added after a delay of several months to allow manual interference with the quality control process. The TERENO (TERrestrial ENvironmental Observatories) is an initiative of the Helmholtz Centers (Forschungszentrum Jülich – FZJ, Helmholtz Centre for Environmental Research – UFZ, Karlsruhe Institute of Technology – KIT, Helmholtz Zentrum München - German Center for Environmental Health – HMGU, German Research Centre for Geosciences - GFZ, and German Aerospace Center – DLR) (http://www.tereno.net/overview-de)..TERENO spans an Earth observation network across Germany that extends from the North German lowlands to the Bavarian Alps. This unique large-scale project aims to catalogue the longterm ecological, social and economic impact of global change at regional level. Further specific goals of the TERENO remote sensing research group at GFZ are (1) supplying environmental data for algorithm development in remote sensing and environmental modelling, with a focus on soil moisture and evapotranspiration, and (2) practical tests of remote sensing data integration in agricultural land management practices.
# 6592
Arzhanov, Maxim • Betts, Richard • Eliseev, Alexey • Morfopoulos, Catherine • Schaphoff, Sibyll • (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 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 ISIMIP 2a Input Data & Bias Correction at https://www.isimip.org/gettingstarted/#input-data-bias-correction). This entry refers to the ISIMIP2a simulation data from permafrost models: JULES-B1 (formerly JULES_UoE), LPJmL, IAPRAS-DSS.
The ISIMIP2a Permafrost outputs are based on simulations from 3 permafrost models (see listing) according to the ISIMIP2a Simulation Protocol (https://www.isimip.org/protocol/#isimip2a). The models simulate coupled water and carbon processes, like the soil carbon storage on permafrost soils, non-linear effects in changing vegetation and fire, and the physical state of the permafrost based on soil, 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/.
# 6593
Ziegler, Moritz O.
Abstract: The 3D geomechanical-numerical modelling of the in-situ stress state requires observed stress information at reference locations within the model area to be compared to the modelled stress state. This comparison of stress states and the ensuing adaptation of the displacement boundary conditions provide a best fit stress state in the entire model region that is based on the available stress information. This process is also referred to as calibration. Depending on the amount of available information and the complexity of the model the calibration is a lengthy process of trial-and-error modelling and analysis. The Fast Automatic Stress Tensor Calibration (FAST Calibration) is a method and a Matlab script that facilitates and speeds up the calibration process that has been developed in the framework of the World Stress Map (WSM, Heidbach et al., 2010; 2016). The method requires only three model scenarios with different boundary conditions. The modelled stress states at the locations of the observed stress state are extracted. Then they are used to compute the displacement boundary conditions that are required in order to achieve the best fit of the modelled to the observed stress state. Furthermore, the influence of the individual observed stress information on the resulting stress state can be weighted. The FAST-Calibration (Fast Automatic Stress Tensor Calibration) is a Matlab tool that controls the statistical calibration of a 3D geomechanical-numerical model of the stress state following the approach described by Reiter and Heidbach (2014), Hergert et al. (2015), and Ziegler et al. (2016). It is mainly designed to support the multi-stage modelling procedure presented by Ziegler et al. (2016). However, it can also be used for the calibration of a single-stage model. The tools run in Matlab 2017a and higher and are meant to work with the visualization software Tecplot 360 EX 2015 R2 and higher (https://www.tecplot.com/products/tecplot-360/) in conjunction with the Tecplot 360 Add-on GeoStress (Stromeyer and Heidbach, 2017). The user should be familiar with 3D geomechanical-numerical modelling, Matlab, Tecplot 360 EX, including a basic knowledge of Tecplot 360 EX macro functions, and the Tecplot 360 EX Add-on GeoStress. This FAST Calibration manual provides an overview of the scripts and is designed to help the user to adapt the scripts for their own needs.
# 6594
Arzhanov, Maxim • Betts, Richard • Eliseev, Alexey • Morfopoulos, Catherine • Schaphoff, Sibyll • (et. al.)
Abstract: Description of changes in the new version:- On October 18, 2018 we republished all simulation data for all impact models to get the data sets into the new search facet structure. There were no changes to the simulation data.- Files for JULES-B1 (formerly JULES_UoE) were not available since the date of issuing the DOI until March 13, 2019. Until that date, these files were only available in the ISIMIP DKRZ server. ---------------------------------------------------------------------The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) simulation data is under continuous review and improvement, and updates are thus likely to happen. All changes and caveats are documented under https://www.isimip.org/outputdata/output-data-changelog/. For accessing the data set as in http://doi.org/10.5880/PIK.2018.006 before March 13, 2019 please write to the ISIMIP Data Management Team: isimip-data[at]pik-potsdam.de--------------------------------------------------------------------- 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 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 ISIMIP 2a Input Data & Bias Correction at https://www.isimip.org/gettingstarted/#input-data-bias-correction). This entry refers to the ISIMIP2a simulation data from permafrost models: JULES-B1 (formerly JULES_UoE), LPJmL, IAPRAS-DSS.
The ISIMIP2a Permafrost outputs are based on simulations from 3 permafrost models (see listing) according to the ISIMIP2a Simulation Protocol (https://www.isimip.org/protocol/#isimip2a). The models simulate coupled water and carbon processes, like the soil carbon storage on permafrost soils, non-linear effects in changing vegetation and fire, and the physical state of the permafrost based on soil, 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/.
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