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195 results for “Coupled models”
Data from: Estimating range expansion of wildlife in heterogeneous landscapes: a spatially explicit state-space matrix model coupled with an improved numerical integration technique
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Model simulation data used in "Coupling aerosols to (cirrus) clouds in the global aerosol-climate model EMAC-MADE3" (Righi et al., Geosci. Model Dev., 2020)
<p>This dataset contains the output of the EMAC global model simulations analysed and discussed in Righi et al. (<i>Geosci. Model Dev.</i>, 2020). An overview of the numerical experiments performed for this study is given in the file "experiments.dat".</p>
The potential of sector coupling in future European energy systems soft linking between the Dispa-SET and JRC-EU-TIMES models - Dataset
<p>Supporting dataset and Dispa-SET version used within "The potential of sector coupling in future European energy systems soft linking between the Dispa-SET and JRC-EU-TIMES models" paper.</p>
Data archive for paper "WRF‐TEB: Implementation and Evaluation of the Coupled Weather Research and Forecasting (WRF) and Town Energy Balance (TEB) Model"
<p><strong>WRF-TEB data archive</strong></p> <p>This archive contains data and tools to reproduce results as included in <a href="https://doi.org/10.1029/2019ms001961">Meyer et al. (2020)</a>.</p> <p><strong>Prerequisites</strong></p> <ul> <li><a href="https://sylabs.io/">Singularity</a> version >= 3.</li> </ul> <p><strong>Usage</strong></p> <p>To run all models and plotting scripts included in integration test and meteorological evaluation, run the following command from your command-line interface.</p> <pre><code>NPROC=8 TYPE=evaluate tools/singularity/run.sh</code></pre> <p>where <code>NPROC=8</code> is the maximum number of processes to use. The output can be found in the <code>work/</code> folder.</p> <p><strong>HPC</strong></p> <p>If you want to use this in an HPC environment, use <code>tools/hpc</code> as a template. As an example, to run the evaluation on Imperial HPC using PBS (Portable Batch System), use:</p> <pre><code>qsub -v REPO_ROOT=$(pwd),TYPE=evaluate tools/hpc/job_imperial.sh</code></pre> <p><strong>Copyright and License</strong></p> <p>Copyright and licensing information are included at the top of source files or as separate files in folders.</p> <p><strong>References</strong></p> <p>Meyer, D., Schoetter, R., Riechert, M., Verrelle, A., Tewari, M., Dudhia, J., Masson, V., Reeuwijk, M., & Grimmond, S. (2020). WRF‐TEB: implementation and evaluation of the coupled Weather Research and Forecasting (WRF) and Town Energy Balance (TEB) model. Journal of Advances in Modeling Earth Systems. <a href="https://doi.org/10.1029/2019ms001961">https://doi.org/10.1029/2019ms001961</a></p>
Data from: In silico study of the role of cell growth factors in photosynthesis using a virtual leaf tissue generator coupled to a microscale photosynthesis gas exchange model
Computational tools that allow in silico analysis of the role of cell growth and division on photosynthesis are scarce. We present a freely available tool that combines a virtual leaf tissue generator and a two-dimensional microscale model of gas transport during C3 photosynthesis. A total of 270 mesophyll geometries were generated with varying degree of growth anisotropy, growth extent and extent of schizogenous airspace formation in the palisade mesophyll. The anatomical properties of the virtual leaf tissue and microscopic cross sections of actual leaf tissue of tomato (Solanum lycopersicum L.) were statistically compared. Model equations for transport of CO2 in the liquid phase of the leaf tissue were discretized over the geometries. The virtual leaf tissue generator produced a leaf anatomy of tomato that was statistically similar to real tomato leaf tissue. The response of photosynthesis to intercellular CO2 predicted by a model that used the virtual leaf tissue geometry compared well with measured values. The results indicate that the light-saturated rate of photosynthesis was influenced by interactive effects of extent and directionality of cell growth and degree of airspace formation through the exposed surface of mesophyll per leaf area. The tool could be used further in investigations of improving photosynthesis and gas exchange in relation to cell growth and leaf anatomy.
Data from: Fruiting strategies of perennial plants: a resource budget model to couple mast seeding to pollination efficiency and resource allocation strategies
Masting, a breeding strategy common in perennial plants, is defined by seed production that is highly variable over years and synchronized at the population level. Resource budget models (RBMs) proposed that masting relies on two processes: (i) the depletion of plant reserves following high fruiting levels, which leads to marked temporal fluctuations in fruiting; and (ii) outcross pollination that synchronizes seed crops among neighboring trees. We revisited the RBM approach to examine the extent to which masting could be impacted by the degree of pollination efficiency, by taking into account various logistic relationships between pollination success and pollen availability. To link masting to other reproductive traits, we split the reserve depletion coefficient into three biological parameters related to resource allocation strategies for flowering and fruiting. While outcross pollination is considered to be the key mechanism that synchronizes fruiting in RBMs, our model counterintuitively showed that intense masting should arise under low-efficiency pollination. When pollination is very efficient, medium-level masting may occur, provided that the costs of female flowering (relative to pollen production) and of fruiting (maximum fruit set and fruit size) are both very high. Our work highlights the powerful framework of RBMs, which include explicit biological parameters, to link fruiting dynamics to various reproductive traits and to provide new insights into the reproductive strategies of perennial plants.
Coupling a large-scale glacier and hydrological model (OGGM v1.5.3 and CWatM V1.08) - Data Set
<p>GENERAL INFORMATION</p> <p>The data and scripts used for the analysis of the paper "Coupling a large-scale glacier and hydrological model (OGGM v1.5.3 and CWatM V1.08) – Towards an improved representation of mountain water resources in global assessments"</p> <p><strong>When using this dataset, please refer to the original publication in addition to this Zenodo repository.</strong></p> <p><strong>Hanus, S., Schuster, L., Burek, P., Maussion, F., Wada, Y., and Viviroli, D.: Coupling a large-scale glacier and hydrological model (OGGM v1.5.3 and CWatM V1.08) – towards an improved representation of mountain water resources in global assessments, Geosci. Model Dev., 17, 5123–5144, https://doi.org/10.5194/gmd-17-5123-2024, 2024.</strong></p> <p>DATA & FILE OVERVIEW</p> <p>please have a look at readme.txt </p> <p>Don't hesitate to contact us in case of any questions (sarah.hanus@geo.uzh.ch)</p>
Data for "Richardson model with complex level structure and spin-orbit coupling for hybrid superconducting islands: Stepwise suppression of pairing and magnetic pinning"
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Coupling deep learning and physically-based hydrological models for monthly streamflow predictions
<p>Revision in journal Water Resources Research, Paper # <strong><span>2023WR035618R</span></strong></p>
COMSOL - Modeling of a groundwater sampling event in a monitoring well incorporates the coupled effects of well storage and wellbore mixing.
<p>This is a coupled multiphysics flow and transport model that accounts for laminar flow and solute transport within the wellbore, and Darcy flow in the aquifer to investigate groundwater sampling events. The numerical model was developed and constructed in COMSOL Multiphysics® 6.0, a commercial finite element analysis and solver software. See <a href="https://www.comsol.com/">https://www.comsol.com/</a>. Simulation data is provided for homogenous and heterogenous aquifer conditions. </p>
Deep carbon cycling in subduction zones: 1. Coupled thermo-metamorphic-dissolution model in open versus closed system
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Dataset for Analysis of Various Spatial Resolutions for Modelling Sector-Coupled Energy Systems
<p>Dataset for preprocessing Balmorel data in this Danish case study.</p>
Sector-coupled model for the German energy system in 2019
<p>This repository contains input data for the open-source Python tool <a href="https://github.com/openego/eTraGo">eTraGo</a> (<strong>e</strong>lectricity <strong>Tra</strong>nsmission <strong>G</strong>rid <strong>o</strong>ptimization) version 0.10.0.<br>This data will be uploaded to the <a href="https://openenergy-platform.org/">OpenEnergy Platform</a> which can be accessed by eTraGo. This dataset is an intermediate solution until the data is uploaded.</p> <p>The published data includes the sector-coupled transmission grid data for the scenario <em>status2019</em>. It was created with the open-source tool <a href="https://github.com/openego/powerd-data">powerd-data</a> within the research project <a href="https://h2-powerd.de/">PoWerD</a>. All input data sets as well as the code are available under open source licenses.</p> <p>We thank the Federal Ministry for Economic Affairs and Climate Action for funding the research project PoWerD (grant number: 03EI1042C)</p> <p>The data is stored as a PostgreSQL database in the attached backup file. First, the required schemas and extensions have to be created within the database by running the following SQL statements:</p> <p><code>CREATE EXTENSION postgis;</code></p> <p>Afterwards, the data can be restored by using e.g. pgAdmin or via PostgreSQL's <a href="https://www.postgresql.org/docs/current/app-pgrestore.html">pg_restore</a> command (replace <code>HOST</code>, <code>DATABASE_NAME</code>, <code>PORT</code> and <code>USER</code> by your settings):</p> <p><code>pg_restore --host HOST --port PORT --username USER --no-password --dbname </code><code>DATABASE_NAME --no-owner --no-privileges --verbose "PoWerD_status2019_v3.backup"</code></p>
Wind profile in the wave boundary layer and its application in a coupled atmosphere-wave model
<p>The simulation data for the study</p>
Data for the article entitled "Strongly Coupled Data Assimilation of Ocean Observations into an Ocean-Atmosphere Model" by Tang et al. 2021, GRL
<p>We stored the output data for the free run and the data assimilation experiments. All the data is stored in netCDF format and named by XX1_ensmean_XX2_monmean.nc. The prefix XX1 indicates the simulation scenarios, where 'free_run' refers to the free run, 'wcda' the weakly coupled assimilation run, 'scda' the strongly coupled data assimilation run without vertical localization for atmosphere, and 'scda_vert' the strongly coupled assimilation run with vertical localization for atmosphere. The XX2 represents variables from the simulations, where 'temp2' refers to 2 meter temperature, 'u10' 10 metre U wind component, 'v10' 10 metre V wind component, 'st_p' temperature at pressure levels, 'uv_p' U and V component of wind at pressure levels, and 'q_p' specific humidity at pressure levels.</p>
Coupling Multiple Models For Dynamic Simulation Of Geological Hazard Chains: A Case Study Of Baige Landslide, Jinsha River, China
<p><strong>Coupling Multiple Models For Dynamic Simulation Of Geological Hazard Chains: A Case Study Of Baige Landslide, Jinsha River, China </strong></p>
A GDM-GTWR Coupled Model for Spatiotemporal Heteroge-neity Quantification of CO2 Emissions: A case of the Yangtze River Delta Urban Agglomeration from 2000 to 2017
<p>The compressed package contains some pictures and data on the paper.</p>
Data from: A multifactor coupling prediction model for the failure depth of floor rocks in fully mechanized caving mining: a numerical and in situ study
To study the mining-induced failure depth of floor rocks in a fully-mechanized mining caving field affected by different coal seam pitches, mining face lengths, burial depths and aquifer water pressures, multifactor coupled orthogonal numerical tests on the failure depth of floor rocks were conducted. The numerical results show that the failure depth of floor rocks increases with increasing mining face length, coal seam pitch and burial depth. According to the relationship between failure depth and these impact factors, a multifactor coupled prediction model for the failure depth of floor rocks was established. In addition, the in-situ measurement of the failure depth of floor rocks in the Yitang Coal Mine in Huoxi coal field in Shanxi Province, China, was performed, and the in-situ failure depths of floor rocks in the 100502 (80 m) and 100502 (180 m) mining faces were approximately 12.50~14.65 m and 17.50~19.20 m, in good agreement with the results of the multifactor prediction model. Furthermore, the sensitivity of each impact factor in the prediction model of the floor failure depth was further analysed by F-test and range analysis, and the impact order of studied factors on the floor failure depth is coal seam pitch>mining face length>burial depth>aquifer water pressure.
Supporting information for " Modeling Injection-Induced Fracture Propagation in Crystalline Rocks by a Fluid-Solid Coupling Grain-Based Model "
<p>This Excel files contain the experimental and simulation data for " Modeling Injection-Induced Fracture Propagation in Crystalline Rocks by a Fluid-Solid Coupling Grain-Based Model " (JGR: Solid Earth). The paper is authored by Song Wang, Jian Zhou, Luqing Zhang, Thomas Nagel, Zhenhua Han, and Yanlong Kong.</p>
Figures and tables with datasets in "A wind-induced snow redistribution study considering contact based on a bidirectional coupled model of wind and discrete snow particles"
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.