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136 results for “Model Versioning”
Dataset of AI-generated code created by various versions of GPT model
<p>This is the dataset used for the paper "<span>Human vs AI: Investigation of Security Risks in AI-generated </span><span>Code via Comparison with Human-written Code".</span></p>
iCESM1.2 restart file from "The Connected Isotopic Water Cycle in the Community Earth System Model Version 1"
<p>iCESM1.2 restart file at year 1850</p> <p><strong>Citation: </strong>Brady, E. C., Stevenson, S., Bailey, D., Liu, Z., Noone, D., Nusbaumer, J., … Zhu, J. (2019). The Connected Isotopic Water Cycle in the Community Earth System Model Version 1. <em>Journal of Advances in Modeling Earth Systems</em>, <em>11</em>, 2547–2566. https://doi.org/10.1029/2019MS001663</p> <p><strong>iCESM1.2 GitHub:</strong> https://github.com/NCAR/iCESM1.2</p> <p>A CLM land surface data set is included: surfdata_1.9x2.5_simyr1850_c140303.nc.</p>
Supporting Materials for Modeling Multicomponent Gas Adsorption in Nanoporous Materials with Two Versions of Nonlocal Classical Density Functional Theory
<p>This web page archives the simulation input and output used in RASPA related to the publication. Please visit the GitHub repository (https://github.com/MusenZhou/GPU-accelerated-cDFT) and contact Jianzhong Wu (jwu@engr.ucr.edu) and Musen Zhou (mzhou035@ucr.edu) if interested in cDFT code.</p>
Dataset produced by MOCAGE-1D model version R1.18.1 for volcanic halogen chemistry study
<p>The file data_files_MOCAGE_R1_18_1.tar contains the files produced by MOCAGE 1D model version R1.18.1 for the study of halogen chemistry in volcanic plumes. The data corresponds to the model experiments described in the preprint (https://doi.org/10.5194/gmd-2022-180). For each experiment (stored in a separate directory), hourly files are available and include the 1D profile of the chemical variables shown in the preprint. The files are called HMGLOB05+DATETIME.nc. For the experiments using the representation of the sub-grid scale plume chemistry, an additional set of files is produced that is called HMGLOB05+DATETIME_XCEN.nc. The HMGLOB05+DATETIME.nc and HMGLOB05+DATETIME_XCEN.nc files need to be combined to get the concentrations of chemical species at the model grid resolution as shown in the preprint (see additional notes section for explanation how to combine the files).</p>
A Model Instability Issue in the NCEP Global Forecast System Version 16 and Potential Solutions
<p>This dataset includes the GFSv16 model source code and the scripts and data to plot the figures for the manuscript</p> <p>" A Model Instability Issue in the NCEP Global Forecast System Version 16 and Potential Solutions" submitted to GMD</p>
Assessment of equilibrium climate sensitivity of the Community Earth System Model version 2 through simulation of the Last Glacial Maximum
<p>Simulation data (TS, FSNT, and FLNT) and apap cloud feedback analysis for CESM2 LGM simulation</p> <p><strong>Simulation boundary condition files in 1-degree resolution: boundary_condition_files.zip</strong></p> <p><strong>Please cite: </strong></p> <p>Zhu, J., Otto-Bliesner, B. L., Brady, E. C., Poulsen, C. J., Tierney, J. E., Lofverstrom, M., & DiNezio, P. (2021). Assessment of equilibrium climate sensitivity of the Community Earth System Model version 2 through simulation of the Last Glacial Maximum. <em>Geophysical Research Letters</em>, <em>n/a</em>(n/a), e2020GL091220. https://doi.org/10.1029/2020GL091220</p>
Worldclim 2.1 versus Worldclim 1.4: climatic niche and grid resolution affect between-version mismatches in habitat suitability models predictions across Europe
Open the record for dataset details and reuse information.
ECCO Ocean 3D Gent-Mcwilliams, Redi, and Background Vertical Diffusivity Coefficients for the Lat-Lon-Cap 90 (llc90) Native Model Grid (Version 4 Release 4)
This dataset provides 3D coefficients for the Gent-McWilliams and Redi parameterizations and background vertical diffusivity on the lat-lon-cap 90 (llc90) native model grid from the ECCO Version 4 Release 4 (V4r4) ocean and sea-ice state estimate. Each of these three time-invariant, spatially-varying terms are estimated during the ECCO V4r4 optimization. Estimating the Circulation and Climate of the Ocean (ECCO) state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of a global, nominally 1-degree configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g., research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.
ECCO Geometry Parameters for the 0.5 degree Lat-Lon Model Grid (Version 4 Release 4)
This dataset provides geometric parameters for the regular 0.5-degree lat-lon grid from the ECCO Version 4 Release 4 (V4r4) ocean and sea-ice state estimate. Parameters include areas and lengths of grid cell sides and the horizontal and vertical coordinates of grid cell centers and corners. Additional information related to the global domain geometry (e.g., bathymetry and land/ocean masks) are also included. However, users should note these domain geometry fields are approximations because they have been interpolated from the ECCO lat-lon-cap 90 (llc90) native model grid. Users interested in exact budget closure calculations for volume, heat, salt, or momentum should use ECCO fields provided on the llc90 grid. Estimating the Circulation and Climate of the Ocean (ECCO) state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of a global, nominally 1-degree configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g., research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.
ECCO Geometry Parameters for the Lat-Lon-Cap 90 (llc90) Native Model Grid (Version 4 Release 4)
This dataset provides geometric parameters for the lat-lon-cap 90 (llc90) native model grid from the ECCO Version 4 Release 4 (V4r4) ocean and sea-ice state estimate. Parameters include areas and lengths of grid cell sides; horizontal and vertical coordinates of grid cell centers and corners; grid rotation angles; and global domain geometry including bathymetry and land/ocean masks. Estimating the Circulation and Climate of the Ocean (ECCO) state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of a global, nominally 1-degree configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g., research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.
ECCO Ocean 3D Gent-Mcwilliams, Redi, and Background Vertical Diffusivity Coefficients for the 0.5 degree Lat-Lon Model Grid (Version 4 Release 4)
This dataset provides 3D coefficients for the Gent-McWilliams and Redi parameterizations and background vertical diffusivity interpolated to a regular 0.5-degree grid from the ECCO Version 4 Release 4 (V4r4) ocean and sea-ice state estimate. Each of these three time-invariant, spatially-varying terms are estimated during the ECCO V4r4 optimization. Estimating the Circulation and Climate of the Ocean (ECCO) state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of a global, nominally 1-degree configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g., research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.
Model parameters trained using the Component Contribution method (legacy version)
<p>A Numpy (.npz) file containing all model parameters needed for applying the component contribution method to estimate the standard Gibbs energies of biochemical reactions.</p> <p>This is a <strong>legacy version</strong>, and should only be used for consistency testing. Otherwise, please use the newer version (<a href="https://zenodo.org/record/4013789">10.5281/zenodo.4013789</a>).</p> <p>This model is identical to the one stored on <a href="https://legacy.quiltdata.com/package/equilibrator/component_contribution/revisions">Quilt</a> with the following parameters:</p> <ul> <li>date: April 9, 2020, 3:03 PM</li> <li>hash: 2c14d76366ba17dc876f2fc10612db41cae65c0411d8a654b762faa2beb3b055</li> <li>author: equilibrator</li> <li>tags: versions 0.2.18</li> </ul>
Contrasting aerosol effects on longwave cloud forcing in South East Asia and Amazon simulated with Community Atmosphere Model version 5.3
<p>Aerosols modify cloud microphysical and radiative properties and thus impact the shortwave (SW) and longwave cloud forcing (LWCF). This study first reports the finding of contrasting aerosol effects on LWCF in South East Asia and Amazon in the Community Atmosphere Model version 5.3 (CAM5.3), which corresponds to the sum of LW indirect and semi-direct effects investigated in Ghan et al., (2012). A series of numerical experiments is conducted to decompose the complex aerosol effects on LWCF. Our analysis indicates that the cooling (negative aerosol effects on LWCF) in Amazon is due mainly to the aerosol effects on warm clouds and the inhibition of vertical motion by the aerosol-induced radiative cooling. In contrast, the warming (positive aerosol effects on LWCF) in South East Asia is due mainly to the aerosol effect on homogeneous freezing, thus reducing the ice particle size and prolonging the existence of ice cloud. Our results emphasize that a comprehensive analysis of integrated aerosol effects on both warm and ice clouds is necessary for better understanding the aerosol effects on LWCF.</p>
Replication Package for "On the Practice of Semantic Versioning for Ansible Galaxy Roles: An Empirical Study and a Change Classification Model"
<p>Replication package for our analysis of Semantic Versioning in Ansible Galaxy role repositories.</p> <p>This replication package consists of three parts:</p> <ul> <li> <p>Classification Model: Contains Jupyter notebooks used to train and evaluate a Random Forest classification model based on structural features. Training and evaluation data is included.</p> </li> <li> <p>Quantitative Notebooks: Contains Jupyter notebooks used to perform quantitative analyses of versions and changes.</p> </li> <li> <p>data: CSV files of the data used in the Quantitative Notebooks, and the source data for the classification model. Should be downloaded separately fromthe classification model. Should be downloaded separately from <a href="https://doi.org/10.5281/zenodo.4991955">https://doi.org/10.5281/zenodo.4991955</a>.</p> </li> </ul> <p>The data is under the Creative Commons Attribution Share-Alike 4.0 license. The source code is under the GNU General Public License.</p>
Data for "Improvements in wintertime surface temperature variability in the Community Earth System Model version 2 (CESM2) related to the representation of snow density"
<p>This dataset contains all the postprocessed data required to reproduce the figures in the publication Simpson et al (2022) "Improvements in wintertime surface temperature variability in the Community Earth System Model version 2 (CESM2) related to the representation of snow density", in the Journal of Advances in Modelling the Earth System.</p>
Radarsat Antarctic Mapping Project Digital Elevation Model, Version 2
The high-resolution Radarsat Antarctic Mapping Project (RAMP) Digital Elevation Model (DEM) combines topographic data from a variety of sources to provide consistent coverage of all of Antarctica.
CLPX-Model: Land Data Assimilation System (LDAS) Data, Version 1
The LDAS data set contains 43 model and observation-based fields produced by the LDAS uncoupled modeling system at the NASA Goddard Space Flight Center using the Mosaic Land Surface Model (LSM).
Daily 4 km Gridded SWE and Snow Depth from Assimilated In-Situ and Modeled Data over the Conterminous US, Version 1
This data set provides daily 4 km snow water equivalent (SWE) and snow depth over the conterminous United States. It was developed at the University of Arizona (UA) under the support of the NASA MAP and SMAP Programs. The data were created by assimilating in-situ snow measurements from the National Resources Conservation Service's SNOTEL network and the National Weather Service's COOP network with modeled, gridded temperature and precipitation data from PRISM.
NACP MsTMIP: Global 0.5-degree Model Outputs in Standard Format, Version 1.0
This data set provides global gridded estimates of carbon, energy, and hydrologic fluxes between the land and atmosphere from 15 Terrestrial Biosphere Models (TBMs) in a standard format. Model estimates are at monthly and yearly time steps for the period 1900 to 2010, with a spatial resolution of 0.5 degree x 0.5 degree globally, excluding Antarctica.
Integrated Biosphere Simulator Model (IBIS), Version 2.5
The Integrated Biosphere Simulator (or IBIS) is designed to be a comprehensive model of the terrestrial biosphere; the model represents a wide range of processes, including land surface physics, canopy physiology, plant phenology, vegetation dynamics and competition, and carbon and nutrient cycling. The model generates global simulations of the surface water balance (e.g., runoff), the terrestrial carbon balance (e.g., net primary production, net ecosystem exchange, soil carbon, aboveground and belowground litter, and soil CO2 fluxes), and vegetation structure (e.g., biomass, leaf area index, and vegetation composition). IBIS was developed by Center for Sustainability and the Global Environment (SAGE) researchers as a first step toward gaining an improved understanding of global biospheric processes and studying their potential response to human activity [Foley et al., 1996]. IBIS was constructed to explicitly link land surface and hydrological processes, terrestrial biogeochemical cycles, and vegetation dynamics within a single, physically consistent framework. Furthermore, IBIS was one of a new generation of global biosphere models, termed Dynamic Global Vegetation Models (or DGVMs), that consider transient changes in vegetation composition and structure in response to environmental change. Previous global ecosystem models have typically focused on the equilibrium state of vegetation and could not allow vegetation patterns to change over time.Version 2.5 of IBIS includes several major improvements and additions [Kucharik et al. 2000]. SAGE continues to test the performance of the model, assembling a wide range of continental- and global-scale data, including measurements of river discharge, net primary production, vegetation structure, root biomass, soil carbon, litter carbon, and soil CO2 flux. Using these field data and model results for the contemporary biosphere (1965-1994), their evaluation shows that simulated patterns of runoff, NPP, biomass, leaf area index, soil carbon, and total soil CO2 flux agreed reasonably well with measurements that have been compiled from numerous ecosystems. These results also compare favorably to other global model results [Kucharik et al. 2000].
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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.