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87 results for “energy simulation”
Supporting data set for: On the challenge of obtaining an accurate solvation energy estimate in simulations of electrocatalysis
<p>The data set generated for the article: "On the challenge of obtaining an accurate solvation energy estimate in<br> simulations of electrocatalysis".</p> <p>Consists of subfolders for various sets of calculations. The data analysis procedure is shown in detail on <a href="https://bjk24.gitlab.io/bg-solvation/intro.html">this website</a>. If you want to peform the data analysis yourself, follow the instructions on the <a href="https://bjk24.gitlab.io/bg-solvation/docs/setup.html">setup page</a> of the website to download the repository, insert this data set into it, and run the Jupyter book.</p>
Simulation of convergent-beam low-energy electron diffraction on Si(001) reconstructions
<p>Research results based upon this code and data are published at <a href="http://doi.org/10.1016/j.apsusc.2019.05.274">http://doi.org/10.1016/j.apsusc.2019.05.274</a>.</p> <p>The image simulation of convergent beam low energy electron diffraction (CBLEED) patterns are used to determine the sensitivity of CBLEED to atomic-scale displacements of several reconstructed variants of the Si(001) surface. The CAVATN code is used to determine the dynamical LEED intensities as a function of the incident electron energy (E<sub>i</sub>), angle (theta, phi) and at each of the miller indices (h,k), up to the third order. The CBLEED code then maps these intensities into reciprocal space, allowing the visualisation of CBLEED patterns to be made as a function of incident electron energy (E<sub>i</sub>). The data files for the CBLEED simulations are stored in a .txt format, with an accompanying .png image displaying the result of the simulation. This data is then analysed to determine the sensitivity of CBLEED patterns to small atomic displacements.</p> <p><strong>CAVATN code:</strong> Relevant documentation, electron beam files and the crystal structure files are all included. The CAVATN dynamical LEED package, developed from the CAVLEED code, is also included, where the code employs the muffin-tin potential approximation and involves a set of phase shifts for each atom type (which are treated as spherically symmetric scatterers in a crystal) that can be evaluated using phase shift calculation packages or tables. In the simulations performed here, complex phase shifts were used to simulate temperature dependent scattering effects at T = 293<em>K</em>. The inner potential is treated as energy independent and is split into real U<sub>or</sub> = 5 <em>eV </em>and imaginary U<sub>oi</sub> = 10 <em>eV </em>parts to respectively treat refraction (via the vacuum and muffin-tin zero difference) and absorption (due to in- elastic processes). Multiple scattering between atoms within a layer is calculated using the chain method and the multiple scattering between layers is included by the renormalized forward scattering perturbation method to evaluate the wave amplitudes of diffracted beams at the surface, and hence the intensities of the LEED pattern.</p> <p><strong>CBLEED code:</strong> The dynamical CBLEED package is included as ‘cbleed_analysis_script.py’, where the CBLEED patterns are simulated by uniformly partitioning the convergent cone into square areas as shown in Figure 1. An incident electron beam is located at the centre of these squares and defined directionally by and . Each of the incident electron beams of the sampled convergent cone was then used as input to the dynamical LEED program CAVATN, so that the corresponding multiply scattered intensities could be determined and mapped into reciprocal space. All the output data files from the CBLEED code is available for the following structures in the ‘output’ folder; Si(001)-1x1-ideal, Si(001)-2x1-symmetric, Si(001)-2x1-buckled, Si(001)-2x1-dH (for dimer height displacements) and Si(001)-2x1-dL (for dimer length displacements). The data for the sensitivity to atomic-scale displacements is included in the ‘sensitivity_output’ folder, which determines both the partial and whole pattern sensitivities.</p>
Input files for the MD simulations and free energy calculations for the article "Water Dissolved in a Variety of Polymers Studied by Molecular Dynamics Simulation and a Theory of Solutions"
<p>Article:<em> </em><a href="https://pubs.acs.org/doi/10.1021/acs.jpcb.1c04818">J. Phys. Chem. B. 125, 9357–9371 (2021) [DOI: 10.1021/acs.jpcb.1c04818]</a></p> <p>The structures of the homopolymers and copolymers simulated are shown in Figures 1 and S1 and Tables 2 and 3. All-atom MD simulation was carried out using GROMACS, and this repository provides the input files with the GAFF/RESP force and initial coordinate files. The free energy of water dissolution was obtained with <a href="https://sourceforge.net/projects/ermod/">ERmod</a>, and the input files for the free-energy calculations are also contained. See the README files for details.</p>
Data from: Free energy analysis of peptide-induced pore formation in lipid membranes by bridging atomistic and coarse-grained simulations
Open the record for dataset details and reuse information.
Community Land Model version 4.5 (CLM4.5) simulations of water, energy, and carbon fluxes for Saddle vegetation communities, 2008 - 2013
Single point simulations of CLM4.5 that include (1) forcing data that were input to the model and subsequent (2) model output for simulations that approximate conditions in fellfield, dry meadow, moist meadow, wet meadow, and snowbed vegetation communities. Forcing data were generated with observed atmospheric conditions from Tvan, Saddle precipitation, and incoming shortwave radiation measured from the AmeriFlux tower site (US-NR1) from 2008-2013. Wintertime precipitation inputs were modified to approximate average snow depth for each vegetation community observed across the Saddle grid. Land models, like CLM, provide a cohesive framework to investigate biogeophysical and biogeochemical effects of environmental change on ecosystem processes. We used CLM4.5 to investigate if a global-scale model can represent local-scale patterns of water, energy, and carbon fluxes in a heterogeneous mountain environment. Specifically, we were interested in generating testable projections of potential ecosystem responses to climate change. Model output includes half-hourly data on fluxes of energy, water, and carbon, as well as vegetation carbon stocks and edaphic conditions. We also conducted sensitivity analyses to look at ecosystem responses to modifications intended to extend growing season length by decreasing snow albedo and warming air temperatures (black sand and M-A warm, respectively). Information on the variables, units, and data are included as attributed in the network Common Data Form (NetCDF) files for this dataset. For users unfamiliar with using NetCDF files, we have included R scripts that write (forcing data) and read (model output) .nc files include in this data archive. More information about NetCDF files is available at http://www.unidata.ucar.edu/software/netcdf/docs/index.html.
Post-processed output from WACCM: historical simulation of 1957–2005 with medium energy electrons (compset B55TRWCN) and sensitivity studies (compset FW)
<p>This dataset contains post-processed monthly output from WACCM (version 4) simulations:</p> <ol> <li>historical simulation of 1957–2005 with medium energy electrons (compset B55TRWCN, B55TRWCN.zip)</li> <li>sensitivity study: 50-years experiments designed with different geomagnetic and solar conditions (compset FW, FW.zip)</li> </ol> <p>The postprocessing involved (1) zonal averaging, (2) Transformed Eulerian mean (TEM) budget calculation in log-pressure coordindates from model output (h0 files).</p> <p><strong>Contact</strong><br> Monika Szelag (monika.szelag@fmi.fi)</p> <p><strong>Raw data</strong><br> The raw, ungridded monthly data (2TB, h0 files) are currently available on FMI storage system, under path /ibrix/arch/waccm, and can be requested through the contact person. </p> <p><strong>Dataset contents</strong></p> <pre><code>B55TRWCN.zip files: vdk.zonal.002.1957-2005.nc vdk.zonal.003.1957-2005.nc vdk.zonal.004.1957-2005.nc tem.vdk.zonal.002.1957-2005.nc tem.vdk.zonal.003.1957-2005.nc tem.vdk.zonal.004.1957-2005.nc</code></pre> <p>WACCM output: historical simulations, zonal averages, 3 ensemble members of 49 years each (002,003,004).</p> <p>Variables are <strong>NOY, O3, OH, QJOULE, QRL_TOT, QRLNLTE, QRS_TOT, T, U</strong> (vdk.zonal.00[234].1957-2005.nc) and <strong>delf, fphi, fz, vres, wres, z3</strong> (tem.vdk.zonal.00[234].1957-2005.nc</p> <pre><code>FW.zip files: zonal_F2000_max.nc zonal_F2000_avg.nc zonal_F2000_min.nc tem_zonal_F2000_max.nc tem_zonal_F2000_avg.nc tem_zonal_F2000_min.nc</code></pre> <p>WACCM output: perpetual year 2000, zonal averages, 50 years experiments with 3 different solar and geomagnetic conditions (min, max, avg).</p> <p>Variables are <strong>NOY, NOX, O3, OH, QRL_TOT, QRS_TOT, T, U, V, CO, CO2, PS, TS</strong> (zonal_F2000_*.nc) and <strong>delf, fphi, fz, vres, wres, z3</strong> (tem_zonal_F2000_*.nc)</p> <p> </p>
Data set related to the manuscript "Simulations of ionic liquids confined in surface-functionalized nanoporous carbons: Implications for energy storage"
<p>Graphical files in the agr format for all the figures in the manuscript entitled "Simulations of ionic liquids confined in surface-functionalized nanoporous carbons: Implications for energy storage". Examples of input files for the three systems simulated.</p>
COSIPY distributed simulations of Mera Glacier mass and energy balance (20161101-20201101)
<p>The four netCDF files contain outputs from COSIPY model (Sauter et al., 2020) for Mera Glacier for the period 20161101 to 20201101. The model is run on a 0.003°*0.003° grid, and forced with meteological variables collected locally and distributed with constant gradients. The "constants.py" is the python file that contains the specific model settings.</p>
Energy simulation outputs for different mitigation scenarios
<p><span>Advanced urban heat mitigation technologies that involve the use of super cool materials combined with properly designed green infrastructure, lower the urban ambient and land surface temperatures and reduce the cooling consumption at the city scale. We present the </span>results of the <span>world's largest heat mitigation project in Riyadh, KSA. Daytime radiative coolers as well as cool materials combined with irrigated or non-irrigated greenery, have been used to design eight holistic heat mitigation scenarios. We assessed the climatic impact of the scenarios as well as the corresponding energy benefits </span>of <span>3,323 urban buildings. An impressive decrease of the peak ambient temperature, up to 4.5°C, is calculated, consisting of the highest reported urban ambient temperature reduction, while the annual sum of the differences of the ambient temperature against a standard temperature base, (cooling degree hours), in the city decrease by up to 26%. We found that innovative urban heat mitigation strategies contribute to </span>remarkable cooling energy conservation by up to 16%, while the combined implementation of heat mitigation and energy adaptation technologies decreases the cooling demand by up to 35%. <span>It is the first article investigating the large-scale energy benefits of modern heat mitigation technologies when they are implemented in cities. </span></p>
Model America - Summer 2020 Arizona Building Energy Simulation Results from ORNL's AutoBEM
<p>Oak Ridge National Laboratory (ORNL) has developed the Automatic Building Energy Modeling (AutoBEM) software suite to process multiple types of data, extract building-specific descriptors, generate building energy models, and simulate them on High Performance Computing (HPC) resources. For more information, see AutoBEM-related publications (<a href="https://bit.ly/AutoBEM">bit.ly/AutoBEM</a>).</p> <p>Data is provided for 2,555,152 buildings located within the boundary of Arizona in the United States:</p> <p><strong>Data (1.48GB *.csv) - Arizona 2,555,152 building information data with simulation results separated by county. (Simulation results are for June 1st-August 31st, 2020)<br></strong></p> <p><strong>Building Information Data Fields:</strong></p> <ul> <li>ID</li> <li>CZ</li> <li>Centroid</li> <li>State_Abbr</li> <li>Footprint2D</li> <li>Height,Area2D</li> <li>BuildingType</li> <li>NumFloors</li> <li>Area</li> <li>Standard</li> <li>NumWalls</li> <li>WWR_surfaces</li> </ul> <p><strong>Energy Simulation Data Fields:</strong></p> <ul> <li>Electricity_Facility[kBTU]</li> <li>NaturalGas_Facility[kBTU]</li> <li>Heating_Electricity[kBTU]</li> <li>Cooling_Electricity[kBTU]</li> <li>Heating_NaturalGas[kBTU]</li> <li>Heating_Total[kBTU]</li> <li>WaterSystems_Electricity[kBTU]</li> <li>Lighting_Electricity[kBTU]</li> <li>Equipment_Electricity[kBTU]</li> <li>Fans_Electricity[kBTU]</li> <li>Pumps_Electricity[kBTU]</li> <li>HeatRejection_Electricity[kBTU]</li> <li>HeatRecovery_Electricity[kBTU]</li> <li>Surface_Outside_Face_Heat_Emission[GJ]</li> <li>Zone_Exfiltration_Heat_Loss[GJ]</li> <li>Zone_Exhaust_Air_Heat_Loss[GJ]</li> <li>Heat_Rejection_Energy[GJ]</li> <li>Anthropogenic_Emissions[GJ]</li> </ul> <p>This data is made free and openly available in hopes of stimulating any simulation-informed use case. Data is provided as-is with no warranties, express or implied, regarding fitness for a particular purpose. We wish to thank our sponsors which include Oak Ridge National Laboratory (ORNL), U.S. Dept. of Energy’s (DOE) Building Technologies Office (BTO), Office of Electricity (OE), and Biological and Environmental Research (BER).</p>
Surface drifters and high resolution global simulations mapping of internal tide surface energy
<p>File " gdp_energy.nc " contains surface semidiurnal internal tides binned-averaged energy levels estimated from the Global Drifter Program dataset. </p> <p>File " <a href="../api/records/10851200/draft/files/energy_SSV_hf_binned_dl1.0_attrs.nc/content" target="_blank" rel="noopener noreferrer">energy_SSV_hf_binned_dl1.0_attrs.nc</a> " contains semidiurnal internal tides squared binned-averaged surface meridional velocity estimated from LLC4320 outputs and simulated drifters. Bins size is 1deg x 1deg .</p> <p>File " <a href="../api/records/10851200/draft/files/energy_SSV_hf_binned_dl1.0_attrs.nc/content" target="_blank" rel="noopener noreferrer">energy_SSU_hf_binned_dl1.0_attrs.nc</a> " contains semidiurnal internal tides squared binned-averaged surface zonal velocity estimated from LLC4320 outputs and simulated drifters. Bins size is 1deg x 1deg .</p> <p>File " <a href="../api/records/10851200/draft/files/energy_SSV_hf_binned_dl1.0_attrs.nc/content" target="_blank" rel="noopener noreferrer">energy_SSV_hf_binned_dl2.0_attrs.nc</a> " contains semidiurnal internal tides squared binned-averaged surface meridional velocity estimated from LLC4320 outputs and simulated drifters. Bins size is 2deg x 2deg .</p> <p>File " <a href="../api/records/10851200/draft/files/energy_SSV_hf_binned_dl1.0_attrs.nc/content" target="_blank" rel="noopener noreferrer">energy_SSU_hf_binned_dl2.0_attrs.nc</a> " contains semidiurnal internal tides squared binned-averaged surface zonal velocity estimated from LLC4320 outputs and simulated drifters. Bins size is 2deg x 2deg .</p> <p>File " <a href="../api/records/10851200/draft/files/energy_SSV_hf_binned_dl1.0_attrs.nc/content" target="_blank" rel="noopener noreferrer">energy_hf_binned_dl1.0_attrs.nc</a> " contains semidiurnal internal tides binned-averaged kinetic energy levels estimated from LLC4320 outputs and simulated drifters. Bins size is 1deg x 1deg .</p> <p>For all files semidiurnal signal is obatined from band-pass filtering.</p>
Weather dataset (Typical Downscaled Year, Extreme Cold Year, Extreme Warm Year) for building energy simulations (.epw format) in recent past climate, Kortrijk Kennedy Park, Belgium
<p>Typical Downscaled Year (TDY), Extreme Cold Year and Extreme Warm Year based on the methodology of Nik (2016), is extracted for the location of Kortrijk Kennedy Park (50°48'2"N 3°16'13" E) from the EC-Earth driven convection-permitting climate model COSMO-CLM for the Belgian domain extended with land-surface scheme TERRA_URB(v2.0) making use of the SURY (Semi-empirical URban canopY) parameterization ( Wouters et al. 2016). The integrations are identical to the ones which are described in Vanden Broucke et al. (2019). The climate model has a spatial resolution of 2.8 km and an hourly temporal resolution and is available for the recent past (1976-2004) and future (2070-2098) as 30-year datasets. For this dataset, the TDY, ECY, and EWY are extracted for the recent past period. A bias correction is applied for the following variables: temperature (as described in Ramon et al. 2020), solar radiation and relative humidity as described in Ramon et al. (202X).</p>
Weather dataset (Typical Downscaled Year, Extreme Cold Year, Extreme Warm Year) for building energy simulations (.epw format) in recent past climate, Antwerp Berchem, Belgium
<p>Typical Downscaled Year (TDY), Extreme Cold Year and Extreme Warm Year based on the methodology of Nik (2016), is extracted for the location of Antwerp Berchem (51°12'00"N 4°26'24" E) from the EC-Earth driven convection-permitting climate model COSMO-CLM for the Belgian domain extended with land-surface scheme TERRA_URB(v2.0) making use of the SURY (Semi-empirical URban canopY) parameterization ( Wouters et al. 2016). The integrations are identical to the ones which are described in Vanden Broucke et al. (2019). The climate model has a spatial resolution of 2.8 km and an hourly temporal resolution and is available for the recent past (1976-2004) and future (2070-2098) as 30-year datasets. For this dataset, the TDY, ECY, and EWY are extracted for the recent past period. A bias correction is applied for the following variables: temperature (as described in Ramon et al. 2020), solar radiation and relative humidity as described in Ramon et al. (202X).</p>
Weather dataset (Typical Downscaled Year, Extreme Cold Year, Extreme Warm Year) for building energy simulations (.epw format) in future climate (2069-2098, RCP 8.5), Sint-Katelijne-Waver, Belgium
<p>Typical Downscaled Year (TDY), Extreme Cold Year and Extreme Warm Year based on the methodology of Nik (2016), is extracted for the location of Sint-Katelijne-Waver (51°3'25"N 4°11'24" E) from the EC-Earth driven convection-permitting climate model COSMO-CLM for the Belgian domain extended with land-surface scheme TERRA_URB(v2.0) making use of the SURY (Semi-empirical URban canopY) parameterization ( Wouters et al. 2016). The integrations are identical to the ones which are described in Vanden Broucke et al. (2019). The climate model has a spatial resolution of 2.8 km and an hourly temporal resolution and is available for the recent past (1976-2004) and future (2070-2098, RCP 8.5 climate change scenario) as 30-year datasets. For this dataset, the TDY, ECY, and EWY are extracted for the future period. A bias correction is applied for the following variables: temperature (as described in Ramon et al. 2020), solar radiation and relative humidity as described in Ramon et al. (202X).</p>
Weather dataset (Typical Downscaled Year, Extreme Cold Year, Extreme Warm Year) for building energy simulations (.epw format) in future climate (2069-2098, RCP 8.5), Uccle KMI, Belgium
<p>Typical Downscaled Year (TDY), Extreme Cold Year and Extreme Warm Year based on the methodology of Nik (2016), is extracted for the location of Uccle KMI (50°47'49"N, 4°21'29" E) from the EC-Earth driven convection-permitting climate model COSMO-CLM for the Belgian domain extended with land-surface scheme TERRA_URB(v2.0) making use of the SURY (Semi-empirical URban canopY) parameterization ( Wouters et al. 2016). The integrations are identical to the ones which are described in Vanden Broucke et al. (2019). The climate model has a spatial resolution of 2.8 km and an hourly temporal resolution and is available for the recent past (1976-2004) and future (2070-2098, RCP 8.5 climate change scenario) as 30-year datasets. For this dataset, the TDY, ECY, and EWY are extracted for the future period. A bias correction is applied for the following variables: temperature (as described in Ramon et al. 2020), solar radiation and relative humidity as described in Ramon et al. (202X).</p>
Weather dataset (Typical Downscaled Year, Extreme Cold Year, Extreme Warm Year) for building energy simulations (.epw format) in future climate (2069-2098, RCP 8.5), Leuven City centre, Belgium
<p>Typical Downscaled Year (TDY), Extreme Cold Year and Extreme Warm Year based on the methodology of Nik (2016), is extracted for the location of Leuven City Centre (50°52'48"N 4°42'0" E) from the EC-Earth driven convection-permitting climate model COSMO-CLM for the Belgian domain extended with land-surface scheme TERRA_URB(v2.0) making use of the SURY (Semi-empirical URban canopY) parameterization ( Wouters et al. 2016). The integrations are identical to the ones which are described in Vanden Broucke et al. (2019). The climate model has a spatial resolution of 2.8 km and an hourly temporal resolution and is available for the recent past (1976-2004) and future (2070-2098, RCP 8.5 climate change scenario) as 30-year datasets. For this dataset, the TDY, ECY, and EWY are extracted for the future period. A bias correction is applied for the following variables: temperature (as described in Ramon et al. 2020), solar radiation and relative humidity as described in Ramon et al. (202X).</p>
Weather dataset (Typical Downscaled Year, Extreme Cold Year, Extreme Warm Year) for building energy simulations (.epw format) in future climate (2069-2098, RCP 8.5), Leuven Casa Blanca, Belgium
<p>Typical Downscaled Year (TDY), Extreme Cold Year and Extreme Warm Year based on the methodology of Nik (2016), is extracted for the location of Casa Blanca neighbourhood Leuven (50°52'48"N, 4°43'48"E) from the EC-Earth driven convection-permitting climate model COSMO-CLM for the Belgian domain extended with land-surface scheme TERRA_URB(v2.0) making use of the SURY (Semi-empirical URban canopY) parameterization ( Wouters et al. 2016). The integrations are identical to the ones which are described in Vanden Broucke et al. (2019). The climate model has a spatial resolution of 2.8 km and an hourly temporal resolution and is available for the recent past (1976-2004) and future (2070-2098, RCP 8.5 climate change scenario) as 30-year datasets. For this dataset, the TDY, ECY, and EWY are extracted for the future period. A bias correction is applied for the following variables: temperature (as described in Ramon et al. 2020), solar radiation and relative humidity as described in Ramon et al. (202X).</p>
Weather dataset (Typical Downscaled Year, Extreme Cold Year, Extreme Warm Year) for building energy simulations (.epw format) in recent past climate, Leuven Casa Blanca, Belgium
<p>Typical Downscaled Year (TDY), Extreme Cold Year and Extreme Warm Year based on the methodology of Nik (2016), is extracted for the location of the Casa Blanca Neighbourhood Leuven (50°52'48"N 4°43'48"E) from the EC-Earth driven convection-permitting climate model COSMO-CLM for the Belgian domain extended with land-surface scheme TERRA_URB(v2.0) making use of the SURY (Semi-empirical URban canopY) parameterization ( Wouters et al. 2016). The integrations are identical to the ones which are described in Vanden Broucke et al. (2019). The climate model has a spatial resolution of 2.8 km and an hourly temporal resolution and is available for the recent past (1976-2004) and future (2070-2098) as 30-year datasets. For this dataset, the TDY, ECY, and EWY are extracted for the recent past period. A bias correction is applied for the following variables: temperature (as described in Ramon et al. 2020), solar radiation and relative humidity as described in Ramon et al. (202X).</p>
Weather dataset (Typical Downscaled Year, Extreme Cold Year, Extreme Warm Year) for building energy simulations (.epw format) in recent past climate, Uccle KMI, Belgium
<p>Typical Downscaled Year (TDY), Extreme Cold Year and Extreme Warm Year based on the methodology of Nik (2016), is extracted for the location of Uccle KMI (50°47'49"N 4°21'29" E) from the EC-Earth driven convection-permitting climate model COSMO-CLM for the Belgian domain extended with land-surface scheme TERRA_URB(v2.0) making use of the SURY (Semi-empirical URban canopY) parameterization ( Wouters et al. 2016). The integrations are identical to the ones which are described in Vanden Broucke et al. (2019). The climate model has a spatial resolution of 2.8 km and an hourly temporal resolution and is available for the recent past (1976-2004) and future (2070-2098) as 30-year datasets. For this dataset, the TDY, ECY, and EWY are extracted for the recent past period. A bias correction is applied for the following variables: temperature (as described in Ramon et al. 2020), solar radiation and relative humidity as described in Ramon et al. (202X).</p>
Weather dataset (Typical Downscaled Year, Extreme Cold Year, Extreme Warm Year) for building energy simulations (.epw format) in recent past climate, Leuven City centre, Belgium
<p>Typical Downscaled Year (TDY), Extreme Cold Year and Extreme Warm Year based on the methodology of Nik (2016), is extracted for the location of city centre of Leuven (50°52'48"N, 4°42'0"E) from the EC-Earth driven convection-permitting climate model COSMO-CLM for the Belgian domain extended with land-surface scheme TERRA_URB(v2.0) making use of the SURY (Semi-empirical URban canopY) parameterization ( Wouters et al. 2016). The integrations are identical to the ones which are described in Vanden Broucke et al. (2019). The climate model has a spatial resolution of 2.8 km and an hourly temporal resolution and is available for the recent past (1976-2004) and future (2070-2098) as 30-year datasets. For this dataset, the TDY, ECY, and EWY are extracted for the recent past period. A bias correction is applied for the following variables: temperature (as described in Ramon et al. 2020), solar radiation and relative humidity as described in Ramon et al. (202X).</p>
ScienceDex guides
Understand access before you commit
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.