Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
17
datasets available to search
ShareScore release 0.7.1
Dataset results
17 results for “Potential evapotranspiration”
Monthly time series of rainfall, potential evapotranspiration and streamflow for 201 catchments in South-East Australia
<p>The data set contains data for 201 catchments located in South-Eastern Australia. The data was extracted from the datasets collated by Lerat, Thyer et al. (2020) including rainfall and potential-evapotranspiration data obtained from the Bureau of Meteorology Australian Water Outlook website (Frost, Ramchurn et al. 2016) and streamflow data obtained from the Bureau of Meteorology Water Data Online website (Bureau of Meteorology 2019). The data was collected over the period from 1980 to 2018, split into the two sub-periods 1980-1999 (Period 1) and 1999-2018 (Period 2).</p><p> </p><p>Bureau of Meteorology. (2019). "Water Data Online." from <a href="http://www.bom.gov.au/waterdata">http://www.bom.gov.au/waterdata</a>.</p><p>Frost, A. J., A. Ramchurn and A. Smith (2016). "The bureau's operational AWRA landscape (AWRA-L) Model." Bureau of Meteorology Technical Report.</p><p>Lerat, J., M. Thyer, D. McInerney, D. Kavetski, F. Woldemeskel, C. Pickett-Heaps, D. Shin and P. Feikema (2020). "A robust approach for calibrating a daily rainfall-runoff model to monthly streamflow data." Journal of Hydrology<strong>591</strong>: 125129.</p>
Saddle catchment Distributed Hydrology Soil Vegetation Model Simulation (DHSVM) precipitation and transpiration variable outputs (precipitation, total, potential and actual evapotranspiration), 2 meter, 2000-2019.
The Saddle Catchment of the Niwot Ridge LTER is a densely observed, high elevation site that is ideal for hydrological model simulation and calibration. The files produced are the result of a calibration of the Distributed Hydrology Soil Vegetation model (DHSVM) using observationally based states and forcings. Input state files of vegetation, soil properties, shading, and elevation were generated using ground and satellite observations, which, in the case of coarse-resolution or point scale observations, were then interpolated to match the high resolution of the model (2-meter grid cells). Temporally continuous meteorological forcings at the hourly time-step were used to force the model to produce an hourly simulation of the surface and subsurface hydrology within the Saddle catchment. DHSVM was calibrated to effectively reproduce the annual cycle (r^2) and total volume (percent bias) of observed runoff using observations of streamflow at the outflow pour point of the Saddle Catchment from 2001-2019. Calibrated parameters include the lateral conductivity of soil types, exponential decrease of soil conductivity, snow roughness, the snow melting temperature threshold, and the vertical conductivity of the soils. The resulting simulation generated spatially distributed time series of the snow water equivalent, snow melt, precipitation, total evapotranspiration, potential evapotranspiration, and a time-series of the total runoff generated at the outflow pour-point of the Saddle catchment. This data package contains the spatially distributed time series of precipitation, total evapotranspiration and actual evapotranspiration Outputs of snow water equivalent, snow melt, and runoff, as well as the model configuration file, as well as model inputs are archived separately on the Environmental Data Initiative.
WaterGAP2.2d model derived Potential evapotranspiration and Renewable water resources variables with standard and modified PET calculation methods
<p>This data set is produced as a part of the ''Improving the quantification of climate change hazards by hydrological models: A simple ensemble approach for considering the uncertain effect of vegetation response to climate change on potential evapotranspiration" journal publication (in preparation). WaterGAP2.2d global hydrological model with two different settings; 1) with standard PET method Priestley-Taylor (PT) and 2) with modified approach (PT-MA) (please refer to the publication for more details on the method) used to derive the data set. The bias-adjusted GCM-derived (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, and MIROC5) climate data under RCP2.6 and RCP8.5 emission scenarios were used as the input. The model-derived potential evapotranspiration and the renewable water resources variables are available from 1981 to 2099 on the monthly scale for each land grid cell (spatial resolution: 0.5 degrees x 0.5 degrees). The data files are in the netCDF format (.nc4). </p>
Projected changes in droughts and extreme droughts in Great Britain are strongly influenced by the choice of drought index: UKCP18-based bias adjusted potential evapotranspiration
<p>Potential evapotranspiration calculated from the UKCP18 RCM ensemble using the Penman-Monteith method as implemented by Robinson et al. (2017) and bias adjusted using Lange et al. (2019). This dataset was used for analysis of future drought characteristics in Reyniers et al. (2022). Details on the bias adjustment of this potential evapotranspiration dataset, as well as bias-adjusted precipitation and temperature from the same climate model ensemble, can be found in Reyniers et al. (2025).</p> <p>---</p> <p>Reyniers, N., Osborn, T. J., Addor, N., and Darch, G.: Projected changes in droughts and extreme droughts in Great Britain strongly influenced by the choice of drought index, Hydrol. Earth Syst. Sci., 27, 1151–1171, https://doi.org/10.5194/hess-27-1151-2023, 2023.</p> <p>Reyniers, N., Zha, Q., Addor, N., Osborn, T. J., Forstenhäusler, N., and He, Y.: Two sets of bias-corrected regional UK Climate Projections 2018 (UKCP18) of temperature, precipitation and potential evapotranspiration for Great Britain, Earth Syst. Sci. Data, 17, 2113–2133, https://doi.org/10.5194/essd-17-2113-2025, 2025. </p> <p>Robinson, E. L., Blyth, E. M., Clark, D. B., Finch, J., Rudd, A. C. (2017). Trends in atmospheric evaporative demand in Great Britain using high-resolution meteorological data. HESS, <em>21</em>(2), 1189-1224.</p> <p>Lange, S. (2019). Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1. 0). <em>GMD,</em> <em>12</em>(7), 3055-3070.</p>
Long term mean Potential Evapotranspiration (PET) and Actual Evapotranspiration (EAT) estimates using World-Wide HYPE and different PET-formula
<p>Data of the article "<strong>Which Potential Evapotranspiration Formula to Use in Hydrological Modelling World-wide? </strong>" (Pimentel et al. 2023, <em>Water Resources Research, </em><a href="https://doi.org/10.1029/2022WR033447">https://doi.org/10.1029/2022WR033447</a>)</p>
CMIP6 derived ensemble of global vapor pressure deficit, potential evapotranspiration, and reference evapotranspiration
<p>Climate change induced trends in long-term aridity—via changes to atmospheric water demand for have the potential to impact surface water availability across the globe by altering efficiency by which precipitation is converted to runoff. Quantification of aridity requires estimates of evaporative demand, often using vapor pressure deficit, potential evapotranspiration, and/or reference evapotranspiration, but no comprehensive estimate of these climate variables exists to date from the Coupled Model Intercomparison Project 6 (CMIP6). Here we present global monthly estimates of the Penman-Monteith short grass reference evapotranspiration, its advective and radiation components, Priestley-Taylor potential evapotranspiration, and vapor pressure deficit from 16 CMIP6 general circulation models (GCM) for the historical period and four future emission scenarios ranging from low to high projected emissions. The purpose of this dataset is to offer structured and well-documented estimates of historical and future projected evaporative demand derived from the state-of-the-science CMIP6 climate models for use in hydrologic and ecological analyses. We produce a single file for all monthly values of each variable for individual GCM/emission scenario combination gridded at the given GCMs native resolution. Produced alongside all of the files are descriptions of each of the variables and generated python scripts that contain the functions used to estimate vapor pressure deficit, potential evapotranspiration, and reference evapotranspiration.</p>
Irrigation-induced potential evapotranspiration decrease in the Heihe River Basin, Northwest China, as simulated by the WRF model
<p>This dataset is for the plots in the article titled "Irrigation-induced potential evapotranspiration decrease in the Heihe River Basin, Northwest China, as simulated by the WRF model", which was published by Journal of Geophysical Research: Atmospheres. There are totally nine files in the ".mat" format for Matlab. The nine data files are corresponding to nine Figures in the article.</p>
CHclim25 - potential evapotranspiration (etp)
<p>Potential evapotranspiration is calculated according to the Turc method from <a href="https://www.wsl.ch/staff/niklaus.zimmermann/programs/aml1_7.html">solar radiation</a>, and CHclim25 average temperature (Tave) and CHclim25 relative sunshine duration (Srel) . Monthly and yearly current average (1981-2010) and future average (2020-2049, 2045-2074, and 2070-2099)<strong> </strong>layers can be downloaded from separate zip files. </p> <p>Future layers are based on the transient daily time series of gridded climate scenarios of temperature at 0.02°D (~2.2 km) provided by the <a href="https://www.nccs.admin.ch/nccs/en/home/climate-change-and-impacts/swiss-climate-change-scenarios/ch2018---climate-scenarios-for-switzerland.html">CH2018 initiative</a>. We calculated future climatic layers for 4 GCMs (HADGEM, ECEARTH, MPIESM, and IPSL), 3 time slices (2020-2049, 2045-2074, and 2070-2099) and 3 representative concentration pathways (RCP 2.6, 4.5 and 8.5)</p> <p>The layer files are stored in compressed GeoTIFF format with the “deflate” algorithm with option “predictor2” from the GDAL. This format has a high compression ratio but allows direct import in most GIS softwares. All the maps are projected in the Swiss coordinate system CH 1903+ LV95 (epsg:2056) with a resolution of 25x25m using the extent of the digital height model DHM25 of the Swiss office for topography (swisstopo).</p>
Model simulations for " Potential impacts of LUCC and climate change on evapotranspiration and gross primary productivity in the Haihe River Basin, China"
<p>Experiment_1.rar, Experiment_2.rar, and Experiment_3.rar are the model simulations from experiment 1, experiment 2, and experiment 3, respectively. All the simulations are original from the CLM5 model in netcdf format.</p> <p>More details on these data can be found in the paper "Potential impacts of LUCC and climate change on evapotranspiration and gross primary productivity in the Haihe River Basin, China". </p>
VIIRS/NPP Actual and Potential Evapotranspiration Gap-Filled Yearly L4 Global 500m SIN Grid V002
The NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Actual and Potential Evapotranspiration product is a gap-filled yearly composite dataset produced at 500 meter (m) pixel resolution. The VIIRS ET and PET algorithm is based on the Penman-Monteith equation, which includes inputs of daily meteorological reanalysis data along with VIIRS remotely sensed data products such as 8-day vegetation property dynamics and daily surface albedo.The VNP16A3GF will be generated at the end of each year when the entire yearly 8-day VNP15A2H is available. Hence, the gap-filled VNP16A3GF is the improved VNP16A2, which has cleaned the poor-quality inputs from 8-day Leaf Area Index and Fraction of Photosynthetically Active Radiation (LAI/FPAR) based on the Quality Control (QC) label for every pixel. If any LAI/FPAR pixel did not meet the quality screening criteria, its value is determined through linear interpolation. However, users cannot get VNP16A3GF in near-real time because it will be generated only at the end of a given year.Provided in the VNP16A3GF product are layers for composited Evapotranspiration (ET), Latent Heat Flux (LE), Potential ET (PET) and Potential LE (PLE) along with a quality control layer. Two low resolution browse images, ET and LE, are also available for each VNP16A3GF granule.The pixel values for the two Evapotranspiration layers (ET and PET) are the sum for all days within the defined year, and the pixel values for the two Latent Heat layers (LE and PLE) are the average of all days within the defined year.Known Issues* Please refer to the [VIIRS Land Products website](https://viirsland.gsfc.nasa.gov/Products/NASA/ET_ESDR.html) and [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=VIIRS) for information about VNP16A3GF known issues.
RM-OBS/PU Potential Evapotranspiration and Supporting Forcing L4 3-hourly 0.25x0.25 degree V002 (PET_PU_3H025) at GES DISC
This is version 2 of Princeton University MEaSUREs Potential Evapotranspiration (PET) dataset, which provides a set of estimates of PET based on near surface meteorology and surface radiation data derived from a combination of reanalysis, satellite and gridded gauge data. The rationale of the project is to reduce the error from the input meteorological forcing and provide a variety of widely-used PET methods for different research and application purposes.PET is estimated using three methods: Penman open-water method (Penman), Priestley-Taylor method (PT), Reference crop evapotranspiration using the UN Food and Agricultural Organization approach (FAO). The Penman equation assumes PET occurs from an open water surface and calculates PET based on observations of surface net radiation, near-surface air temperature, wind speed, and specific humidity (Shuttleworth, 1993). The PT equation calculates PET based on surface net radiation and near-surface air temperature and does not account for the aerodynamic component (Priestley and Taylor, 1972). The FAO equation is a specific application of the Penman-Monteith equation for crop and short-grass reference surfaces and is based on surface net radiation, near-surface air temperature, wind speed, and specific humidity (Allen, 1998). As a follow-on to PET_PU_3H025 Version 1, PET_PU_3H025 Version 2 seeks to continue to reduce the error from the input meteorological forcing and provide a variety of widely-used PET methods for different research and application purposes. The modifications include the addition of the FAO tall reference crop equation, an extension of the radiation data and temporal coverage, the usage of the GLASS satellite albedo to estimate upward short-wave radiation and the estimation of ground heat flux based on diurnal phase shift of net radiation.This second version of the dataset is estimated at a 3 hourly temporal resolution and 0.25x0.25 degrees spatial resolution globally, spanning the 33-year period 1984-2016. Datasets are stored as a 3-dimensional array with dimension 720 x 1440 x 8 for each day, in NetCDF-4 format.The DOI for version 1 of the data is: 10.5067/GPZDZYELYG1A.
VIIRS/JPSS1 Actual and Potential Evapotranspiration 8-Day L4 Global 500m SIN Grid V002
The NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) Actual and Potential Evapotranspiration product is an 8-day composite dataset produced at 500 meter (m) pixel resolution. The VJ116A2 algorithm is based on the Penman-Monteith equation, which includes inputs of daily meteorological reanalysis data along with VIIRS remotely sensed data products such as 8-day vegetation property dynamics and daily surface albedo.Provided in the VJ116A2 product are layers for composited Evapotranspiration (ET), Latent Heat Flux (LE), Potential ET (PET) and Potential LE (PLE) along with a quality control layer. Two low resolution browse images, ET and LE, are also available for each VJ116A2 granule.The pixel values for the two Evapotranspiration layers (ET and PET) are the summation of 8-day total water loss within the composite period and the pixel values for the two Latent Heat layers (LE and PLE) are the average total energy over a unit area for a day during the composite period. Note that the last acquisition period of each year is a 5 or 6-day composite period, depending on the year.Known Issues* Please refer to the [VIIRS Land Products website](https://viirsland.gsfc.nasa.gov/Products/NASA/ET_ESDR.html) and [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=VIIRS) for information about VJ116A2 known issues.
VIIRS/NPP Actual and Potential Evapotranspiration 8-Day L4 Global 500m SIN Grid V002
The NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Actual and Potential Evapotranspiration (VNP16A2) data product is an 8-day composite dataset produced at 500 meter (m) pixel resolution. The VNP16A2 algorithm is based on the Penman-Monteith equation, which includes inputs of daily meteorological reanalysis data along with VIIRS remotely sensed data products such as 8-day vegetation property dynamics and daily surface albedo.Provided in the VNP16A2 product are layers for composited Evapotranspiration (ET), Latent Heat Flux (LE), Potential ET (PET) and Potential LE (PLE) along with a quality control layer. Two low resolution browse images, ET and LE, are also available for each VNP16A2 granule.The pixel values for the two Evapotranspiration layers (ET and PET) are the summation of 8-day total water loss within the composite period and the pixel values for the two Latent Heat layers (LE and PLE) are the average total energy over a unit area for a day during the composite period. Note that the last acquisition period of each year is a 5 or 6-day composite period, depending on the year.Known Issues* Please refer to the [VIIRS Land Products website](https://viirsland.gsfc.nasa.gov/Products/NASA/ET_ESDR.html) and [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=VIIRS) for information about VNP16A2 known issues.
RM-OBS/PU Potential Evapotranspiration and Supporting Forcing L4 3-hourly 0.25x0.25 degree V001 (PET_PU_3H025) at GES DISC
The Princeton University MEaSUREs Potential Evapotranspiration (PET) dataset provides a set of estimates of PET based on near surface meteorology and surface radiation data derived from a combination of reanalysis, satellite and gridded gauge data. The rationale of the project is to reduce the error from the input meteorological forcing and provide a variety of widely-used PET methods for different research and application purposes.PET is estimated using three methods: Penman open-water method (Penman), Priestley-Taylor method (PT), Reference crop evapotranspiration using the UN Food and Agricultural Organization approach (FAO). The Penman equation assumes PET occurs from an open water surface and calculates PET based on observations of surface net radiation, near-surface air temperature, wind speed, and specific humidity (Shuttleworth, 1993). The PT equation calculates PET based on surface net radiation and near-surface air temperature and does not account for the aerodynamic component (Priestley and Taylor, 1972). The FAO equation is a specific application of the Penman-Monteith equation for crop and short-grass reference surfaces and is based on surface net radiation, near-surface air temperature, wind speed, and specific humidity (Allen, 1998). This first version of dataset is estimated at a 3 hourly temporal resolution and 0.25x0.25 degrees spatial resolution globally, spanning the 23-year period 1984-2006. Datasets are stored as a 3-dimensional array with dimension 720 x 1440 x 8 for each day, in NetCDF-4 format.
VIIRS/NPP Actual and Potential Evapotranspiration Gap-Filled 8-Day L4 Global 500m SIN Grid V002
The NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Actual and Potential Evapotranspiration product is a gap-filled 8-day composite dataset produced at 500 meter (m) pixel resolution. The VIIRS ET and PET algorithm is based on the Penman-Monteith equation, which includes inputs of daily meteorological reanalysis data along with VIIRS remotely sensed data products such as 8-day vegetation property dynamics and daily surface albedo.The VNP16A2GF will be generated at the end of each year when the entire yearly 8-day VNP15A2H is available. Hence, the gap-filled VNP16A2GF is the improved VNP16A2, which has cleaned the poor-quality inputs from 8-day Leaf Area Index and Fraction of Photosynthetically Active Radiation (LAI/FPAR) based on the Quality Control (QC) label for every pixel. If any LAI/FPAR pixel did not meet the quality screening criteria, its value is determined through linear interpolation. However, users cannot get VNP16A2GF in near-real time because it will be generated only at the end of a given year.Provided in the VNP16A2GF product are layers for composited Evapotranspiration (ET), Latent Heat Flux (LE), Potential ET (PET) and Potential LE (PLE) along with a quality control layer. Two low resolution browse images, ET and LE, are also available for each VNP16A2GF granule.The pixel values for the two Evapotranspiration layers (ET and PET) are the summation of 8-day total water loss within the composite period and the pixel values for the two Latent Heat layers (LE and PLE) are the average total energy over a unit area for a day during the composite period. Note that the last acquisition period of each year is a 5 or 6-day composite period, depending on the year. Known Issues* Please refer to the [VIIRS Land Products website](https://viirsland.gsfc.nasa.gov/Products/NASA/ET_ESDR.html) and [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=VIIRS) for information about VNP16A2GF known issues.
VIIRS/JPSS1 Actual and Potential Evapotranspiration Gap-Filled Yearly L4 Global 500m SIN Grid V002
The NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) Actual and Potential Evapotranspiration product is a gap-filled yearly composite dataset produced at 500 meter (m) pixel resolution. The VIIRS ET and PET algorithm is based on the Penman-Monteith equation, which includes inputs of daily meteorological reanalysis data along with VIIRS remotely sensed data products such as 8-day vegetation property dynamics and daily surface albedo.The VJ116A3GF will be generated at the end of each year when the entire yearly 8-day VJ115A2H is available. Hence, the gap-filled VJ116A3GF is the improved VJ116A2, which has cleaned the poor-quality inputs from 8-day Leaf Area Index and Fraction of Photosynthetically Active Radiation (LAI/FPAR) based on the Quality Control (QC) label for every pixel. If any LAI/FPAR pixel did not meet the quality screening criteria, its value is determined through linear interpolation. However, users cannot get VJ116A3GF in near-real time because it will be generated only at the end of a given year.Provided in the VJ116A3GF product are layers for composited Evapotranspiration (ET), Latent Heat Flux (LE), Potential ET (PET) and Potential LE (PLE) along with a quality control layer. Two low resolution browse images, ET and LE, are also available for each VJ116A3GF granule.The pixel values for the two Evapotranspiration layers (ET and PET) are the sum for all days within the defined year, and the pixel values for the two Latent Heat layers (LE and PLE) are the average of all days within the defined year.Known Issues* Please refer to the [VIIRS Land Products website](https://viirsland.gsfc.nasa.gov/Products/NASA/ET_ESDR.html) and [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=VIIRS) for information about VJ116A3GF known issues.
VIIRS/JPSS1 Actual and Potential Evapotranspiration Gap-Filled 8-Day L4 Global 500m SIN Grid V002
The NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) Actual and Potential Evapotranspiration product is a gap-filled 8-day composite dataset produced at 500 meter (m) pixel resolution. The VIIRS ET and PET algorithm is based on the Penman-Monteith equation, which includes inputs of daily meteorological reanalysis data along with VIIRS remotely sensed data products such as 8-day vegetation property dynamics and daily surface albedo.The VJ116A2GF will be generated at the end of each year when the entire yearly 8-day VJ115A2H is available. Hence, the gap-filled VJ116A2GF is the improved VJ116A2, which has cleaned the poor-quality inputs from 8-day Leaf Area Index and Fraction of Photosynthetically Active Radiation (LAI/FPAR) based on the Quality Control (QC) label for every pixel. If any LAI/FPAR pixel did not meet the quality screening criteria, its value is determined through linear interpolation. However, users cannot get VJ116A2GF in near-real time because it will be generated only at the end of a given year.Provided in the VJ116A2GF product are layers for composited Evapotranspiration (ET), Latent Heat Flux (LE), Potential ET (PET) and Potential LE (PLE) along with a quality control layer. Two low resolution browse images, ET and LE, are also available for each VJ116A2GF granule.The pixel values for the two Evapotranspiration layers (ET and PET) are the summation of 8-day total water loss within the composite period and the pixel values for the two Latent Heat layers (LE and PLE) are the average total energy over a unit area for a day during the composite period. Note that the last acquisition period of each year is a 5 or 6-day composite period, depending on the year.Known Issues* Please refer to the [VIIRS Land Products website](https://viirsland.gsfc.nasa.gov/Products/NASA/ET_ESDR.html) and [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=VIIRS) for information about VJ116A2GF known issues.
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.