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855 results for “model system”

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zenodo40/100

Observational datasets for validation of Mediterranean Biogeochemical Copernicus Modelling System, period 2018-2020

<p>Datasets used for the validation of the biogeochemical component of the Mediterranean Analysis and Forecast center of the EU Copernicus Marine Service for the period 2018-2020.</p> <p>The list of datasets includes:</p> <p>1) the Delay Mode Satellite chlorophyll from https://data.marine.copernicus.eu/product/OCEANCOLOUR_MED_BGC_L3_NRT_009_141/description after interpolation to the 1/24&deg; horizontal resolution, weekly averages and quality check with internal climatology</p> <p>2) the BGC-Argo float profiles of nitrate, chlorophyll and oxygen from Coriolis DAC (ftp://ftp.ifremer.fr/ifremer/argo; https://doi.org/10.17882/42182#76230) after an internal quality check procedure which is described in Salon et al., 2019.&nbsp;</p> <p>3) the climatological profiles for 16 subbasins of nitrate, phosphate, silicate, oxygen, DIC, alkalinity, pCO2 and pH computed from the Emodnet 2018 data collection and additional scientific datasets as described in Salon et al., 2019.</p> <p>&nbsp;</p> <p>Ref.:&nbsp;Salon, S., Cossarini, G., Bolzon, G., Feudale, L., Lazzari, P., Teruzzi, A., Solidoro, C. and Crise, A., 2019. Novel metrics based on Biogeochemical Argo data to improve the model uncertainty evaluation of the CMEMS Mediterranean marine ecosystem forecasts.&nbsp;<em>Ocean Science</em>,&nbsp;<em>15</em>(4), pp.997-1022.</p> <p>&nbsp;</p>

opencc-by-4.0Sep 2023View details →
zenodo40/100

Supplementary Material to 'Exploring the power of data-driven models for groundwater system conceptualization: A case study of the Grazer Feld Aquifer, Austria'

<p>This folder contains the supplementary materials to reproduce the results, tables, and figures from the following publication submitted to the Hydrogeology Journal:&nbsp;</p> <p>Kokimova A., Collenteur, R.A. &amp; Birk, S. Exploring the power of data-driven models for groundwater system conceptualization: A case study of the Grazer Feld Aquifer, Austria.</p>

opencc-by-4.0Oct 2023View details →
zenodo40/100

Impact of Convection-permitting and Model Resolution on the Simulation of Mesoscale Convective System Properties over East Asia: companion dataset

<p>This folder includes the intermediate data for the following manuscript:</p><p>Ding et al., Impact of Convection-permitting and Model Resolution on the Simulation of Mesoscale Convective System Properties over East Asia</p><p>The simulations were done&nbsp;using ICON-NWP (ICON Numerical Weather Prediction) model, version 2.6.1, over Asian monsoon region (62E–150E, 5.5N–54.5N) for 2020 summer. At the moment, we upload the intermediate data for MCS tracking. For more data, please contact the authors.</p>

opencc-by-4.0Oct 2023View details →
dryad40/100

Asymmetry in kinematic generalization between visual and passive lead-in movements are consistent with a forward model in the sensorimotor system

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publicFeb 2020View details →
dryad40/100

Modeling phenological and physiological responses to climate warming in a hypothetical migratory songbird-mosquito system

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publicDec 2025View details →
dryad40/100

Finite Element model data for Academic Rotor bladed-disc system

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publicApr 2022View details →
dryad40/100

Modelling system for computing the tropospheric O3 and CH4 perturbations from South Korean Emissions (KORUS-AQ period)

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publicJan 2026View details →
dryad40/100

Data for: Water system simulation modeling with hydropower optimization and environmental flows: An example with Pywr

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publicApr 2023View details →
dryad40/100

Data from: The PDI model system for parameterizing soil hydraulic properties

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publicMay 2024View details →
edi40/100

SBC LTER: Regional Oceanic Modeling System (ROMS) Setup Files, Code, and Lagrangian Model Setup Files

This data contains all the necessary code, grid, forcing, initial, and boundary condition files for running the UCLA version of the Regional Oceanic Modeling System (ROMS) for the Santa Barbara Channel nested solution set that is analyzed in Dauhajre and McWilliams (2019): Nearshore Lagrangian Connectivity: Resolution Sensitivity and Submesoscale Influence. Along with this abstract and separate methods, a brief readme file (README_ROMS) contains other relevant details for running the simulations. The ROMS files in this data correspond to a one-way grid-nesting with the following horizontal resolutions: dx=1km, 300m, 100m, 36m that correspond to R1km, R300m, R100m, and R36m in the publication. In the data directories here, these grids have the following prefixes for all relevant files (grids, forcing, initial condition, and boundary conditions): “usw1” (dx=1km), “usw2” (dx=300m), “usw3” (dx=100m), and “usw4sbc” (dx=36m). The ROMS code is in fortran and requires compilation, with compilation instructions in the directory /src_ROMS_UCLA_2018 in the file “compile.sh”. All grid, forcing, initial, and boundary condition files are in netcdf form. The grid files are in the directory “grids”. Note that the R1km grid has 2 files: usw1_grd.nc and usw1_grd_samp.nc. The latter is a smaller version of the grid that focuses on the Santa Barbara Channel that can be used for the offline Lagrangian model for faster computation (which requires an analogous sub-sampling of the ROMS output). For running ROMS, usw1_grd.nc needs to be used as it corresponds to the entire domain. The atmospheric forcing, derived from a Weather Research and Forecasting model at dx=6km resolution is given in the directory “forcing_files”; all atmospheric forcing files are interpolated to the relevant ROMS grid and formatted to be used as inputs in ROMS. Each grid contains a file corresponding to precipitation (e.g., usw1_prec.nc), radiation (e.g., usw1_rad.nc), atmospheric temperature and specific humidity (

openCC (other)Jul 2019View details →
zenodo36/100

A 3D resistivity model of the Acoculco high temperature geothermal system, Mexico

<p>The dataset is the final three-dimensional resistivity model of the high temperature geothermal field Acoculco, in Mexico.</p> <p>The model is described in deliverable 5.2 of the GEMex Project, funded by the European Union&rsquo;s Horizon 2020 research and innovation programme under grant agreement No. 727550, and by the Mexican Energy Sustainability Fund<br> CONACYT-SENER, Project 2015-04-268074.</p>

opencc-by-4.0Dec 2019View details →
zenodo36/100

TESTAR State Model extracted while executing MyThaiStar as web system under test

<p>TESTAR extracted State Model datasets with TESTAR tool using MyThaiStar web application as System Under Test (SUT). This&nbsp;State Models has&nbsp;been generated to be used as an example to&nbsp;be automatically generated&nbsp;and introduced locally in DECODER PKM, from H2020 DECODER Project.</p> <p>TESTAR tool&nbsp;is an open source tool (www.testar.org) for automated testing through graphical user interface (GUI) currently &nbsp;being &nbsp;developed &nbsp;by &nbsp;the Universitat Politecnica de Valencia and the Open University of the Netherlands.</p> <p>MyThaiStar (<a href="https://github.com/devonfw/my-thai-star">github.com/devonfw/my-thai-star</a>) is the reference application that Capgemini uses internally to promote best programming practices and the correct use of last technologies.&nbsp;It&rsquo;s is developed with Devon Framework, the standard tool for development at the company.</p> <p>PKM is the Persistent Knowledge Monitor developed as main infrastructure from H2020 DECODER Project (www.decoder-project.eu)&nbsp;under grant agreement number 824231.</p> <p>As TESTAR explores automatically the SUT, it will use the Document Object Model (DOM) information extracted from MyThaiStar SUT, to generate and save a TESTAR State Model in the OrientDB graph database. This model contains information about the Widgets, States and Actions, that were found in the SUT.<br> <br> - MyThaiStar.json.gz: JSON file exported from OrientDB that contains a database with the TESTAR State Model. It can be imported into OrientDB using the TESTAR tool, to analyze and interact with the State Model.<br> <br> - ArtefactStateModel_MyThaiStar_2020.1_zpnffj5c3407972370_2020-06-15_12h14m24s: for DECODER project purposes, the knowledge extracted with TESTAR in the generation of the State Model has been summarized and referenced in an artifact JSON file to be adapted to PKM input requirements.</p>

opencc-by-4.0Jun 2020View details →
dryad36/100

Model output for: Attributing causes of future climate change in the California Current System with multi-model downscaling

<p>Regional Ocean Modeling System outputs from dynamic downscaling of Coupled Model Intercomparison Project climate forcings in the California Current system, including projections with full climate forcings, as well as attribution experiments with only changes in wind, heat fluxes and other properties changing stratification, and boundary biogeochemical forcings. Output variables include euphotic zone integrated net primary productivity, and incident photosytnehtically available radiation, and ocean temperature, salinity, vertical velocity, and dissolved oxygen and nitrate concentrations at select depths.</p>

opencc-zeroOct 2020View details →
zenodo36/100

Unstructured global to coastal wave modeling for the Energy Exascale Earth System Model - Simuation results and observed data

<p>This data set contains the simulation results and observed data at NDBC buoy locations.</p> <ul> <li>wave_data.pickle <ul> <li>File containing python data objects which store: station ID data, observed data, model data, and model output dates. Requires python 3.8.</li> </ul> </li> <li>data_access.py <ul> <li>Example python script which reads in a prints the data from wave_data.pickle. It also demonstrates how to access data from the objects stored in the pickle file.</li> </ul> </li> </ul>

opencc-by-4.0Oct 2020View details →
zenodo36/100

Unstructured global to coastal wave modeling for the Energy Exascale Earth System Model - 2 degree WaveWatchIII configuration files

<p>This dataset contains the mesh and model configuration information for a WaveWatchIII run using a 2 degree structured grid.</p> <ul> <li>glo_2d.bot <ul> <li>Bottom depth file for 2 degree structured grid</li> </ul> </li> <li>glo_2d.mask <ul> <li>Mask file for 2 degree structured grid</li> </ul> </li> <li>obstructions_local.glo_2d.in <ul> <li>local obstructions file for use with UOST source term switch</li> </ul> </li> <li>obstructions_shadow.glo_2d.in <ul> <li>shadow obstructions file for use with UOST source term switch</li> </ul> </li> <li>ww3_grid.inp <ul> <li>Input file for the ww3_grid pre-processing program. This file specifies many of the model configuration settings.</li> </ul> </li> <li>ww3_shel.inp <ul> <li>Input file for the ww3_shel program.</li> </ul> </li> </ul>

opencc-by-4.0Oct 2020View details →
zenodo36/100

Unstructured global to coastal wave modeling for the Energy Exascale Earth System Model - unstructured (2 degree to 1/2 degree) WaveWatchIII configuration files

<p>This dataset contains the mesh and model configuration information for a WaveWatchIII run using a global ustructured grid.</p> <ul> <li>mesh.msh <ul> <li>Unstructured mesh file in gmsh format. The unstructured mesh has 2 degree resolution globally with 1/2 degree resolution around the U.S. coastlines. The transition in resolution occurs at 4000m depth with a 10% resolution grading.</li> </ul> </li> <li>obstructions_local.glo_unst.in <ul> <li>local obstructions file for use with UOST source term switch</li> </ul> </li> <li>obstructions_shadow.glo_unst.in <ul> <li>shadow obstructions file for use with UOST source term switch</li> </ul> </li> <li>ww3_grid.inp <ul> <li>Input file for the ww3_grid pre-processing program. This file specifies many of the model configuration settings.</li> </ul> </li> <li>ww3_shel.inp <ul> <li>Input file for the ww3_shel program.</li> </ul> </li> </ul>

opencc-by-4.0Oct 2020View details →
zenodo36/100

VIBeS Case Studies: Featured Transition Systems and Feature Models

<p>Featured Transition Systems and Feature Models&nbsp;used in the different evaluations presented in: <a href="https://researchportal.unamur.be/en/studentTheses/behavioural-model-based-testing-of-software-product-lines">Behavioural model-based testing of software product lines Devroey, X. (Author). 30 Aug 2017</a></p>

opengpl-2.0Oct 2020View details →
zenodo36/100

Input data for performing chemistry coupled PALM model system 6.0 simulations with different chemical mechanisms

<p>The data presented here comprised of input files that have been used to run chemistry coupled PALM model system 6.0 simulations for the article entitled &quot;Development of an atmospheric chemistry model coupled to the PALM model system 6.0: Implementation and&nbsp; first applications&quot;.&nbsp;In this article we describe the implementation of an online-coupled gas-phase chemistry model in the turbulence resolving PALM model system 6.0.</p> <p>List of the input data required for performing chemistry model&nbsp;simulations with different chemical mechanisms&nbsp;is given below.&nbsp; A text file comprised of measured concentrations of NO, NO<sub>2</sub> and O<sub>3</sub> is also added.</p> <ol> <li>Fortran parameter (PARIN)&nbsp;files for four mechanisms and one meteorology-only simulation.</li> <li>Static file</li> <li>Dynamic file</li> <li>Two files (shortwave and longwave input data) for rrtmg radiation model</li> <li>Observation from two air quality stations in Berlin, Germany .</li> <li>PALM model source code revision 4450 (palm_trunk_rev-4450.tar.gz)</li> <li>PALM model source code revision 4601 (palm_trunk_rev-4601.tar.gz)</li> </ol> <p>The PALM model system 6.0 revision 4451 and 4601 (for chemistry flux profiles only) have been used for these simulations.&nbsp;</p>

opencc-by-4.0Sep 2020View details →
zenodo36/100

Optimal parameters of GR4J and HBV hydrological models used in the OpenForecast v2 system

<p>The database contains optimal parameters of GR4J and HBV hydrological models, which are operationally used in the second version of the OpenForecast system (openforecast.github.io).</p>

opencc-by-4.0Dec 2020View details →
zenodo36/100

Dataset accompanying paper submission for "Toward data-driven generation and evaluation of model structure for integrated representations of human behavior in water resources systems"

<p>This data set accompanies code archived at DOI:&nbsp;<a href="https://doi.org/10.5281/zenodo.3833186">10.5281/zenodo.3833186</a>, which was used in the experiments for the paper submission &quot;Toward data-driven generation and evaluation of model structure for integrated representations of human behavior in water resources systems&quot;</p>

opencc-by-4.0Dec 2020View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record