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2,322 results for “precipitations”
Spatiotemporally-completed reconstruction of precipitation during the Holocene over the Northern Hemisphere using paleoclimate data assimilation
<div>(1) <strong>Data Content</strong>: Spatiotemporally complete reconstruction of annual precipitation during the Holocene (i.e., 12-0 ka BP) over the Northern Hemisphere. Based on the sources of the prior ensembles, the dataset comprises three distinct reconstructions, namely PDA (TraCE), PDA (HadCM) and PDA (Mixed), each of which contains: 1) 200 precipitation reconstructions derived from the Monte Carlo realizations for each experimental group, and 2) the corresponding mean and ±1 standard deviation calculated from each set of 200 reconstructions. <strong>(2) Data Production Method</strong>: We reconstructed annual precipitation fields for the Northern Hemisphere during the Holocene using a paleoclimate data assimilation system. This involved assimilating 2,421 Holocene precipitation records from the LegacyClimate 1.0 dataset. In our experiment, we utilized the time-averaged Ensemble Optimal Interpolation (EnIO) data assimilation algorithm. The static prior ensemble of states was constructed from either the TraCE 21 ka BP or the HadCM 23 ka transient climate simulations, or a combination of both in a mixed approach. The data have a temporal resolution of 100 years and a spatial resolution of 3.75°. </div> <div> </div> <div>All prerequisite materials for conducting the PDA-based reconstruction experiments - including prior model simulations, Holocene precipitation records, and Matlab codes- are publicly available on Zenodo repository (<span lang="EN-US">https://doi.org/10.5281/zenodo.17354887</span>). Please contact the author Miao Fang (E-mail: mfang@lzb.ac.cn) for more information about the details of the reconstructions.</div>
Data on: Dynamics of short-term ecosystem carbon fluxes induced by precipitation events in a semiarid grassland
<p>Data correspond to mean daytime net ecosystem carbon exchange (NEE) obtained through the eddy covariance method along six years from 2011 to 2016 (For more details of data see <a href="https://doi.org/10.1029/2018JG004799">https://doi.org/10.1029/2018JG004799</a>).</p> <p>Database contain changes of daytime NEE after a precipitation event (difference between previous day and the day after a precipitation event). Moreover, environmental and soil variables are included: 1) daily mean, previous and the change of soil water content at 2.5 and 15 cm depth, 2) previous NEE rate, 3) change of photosynthetic photon flux density, and 4) air temperature.</p> <p>Data was used to test the effect of environmental and soil variables on the daytime net ecosystem exchange. We was interested in short-term effects, i.e. the priming effect or the Birch effect.</p> <p>Manuscript where this database was used is under review.</p> <p> </p>
WRF Geographic Files for Cordillera Mountain Range Precipitation Experiments
<p>These WRF geographic files (in netcdf format) were used as input for experiments to evaluate the sensitivity of Tropical Cyclone precipitation to the height of the Cordillera Mountain Range in Luzon, Philippines. A total of six files are included, for two domains (d01 and d02) and three different orographic experiments (orig, redu, enha).</p> <p>These are provided to allow reproduction of the said sensitivity experiments.</p>
Long-term atmospheric precipitation monitoring in Hornsund region (Fuglebekken) - raw data
<p>Since 2004, snow and rain samples have been collected in the Fuglebekken catchment in close vicinity of the Polish Polar Station Hornsund. The rain and snow samples are collected after every event. The pH, conductivity and chemical composition (major ions) are analysed at the Polish Polar Station’s chemical laboratory. The rain gauge is checked approximately once a day.</p> <p>Presented data from 2016 to 2022</p> <p>The data has not been checked, which means that it is raw data.</p>
Changes in community-weighted trait mean, functional diversity, precipitation, temperature and surface area along an elevational gradient in Tenerife, Canary Islands
<p>This dataset comprises community-weighted trait means and functional diversity of leaf traits, precipitation, temperature and surface area of the elevational belt recorded in roadside (disturbed) and interior (less disturbed) plots, along an elevational gradient of 2,300 m in Tenerife, Canary Islands. The leaf traits measured were specific leaf area (SLA), nitrogen, carbon, phosphorous, nitrogen to carbon ratio, leaf dry matter content (LDMC), sodium, potassium and magnesium. The environmental variables measured are total precipitation of the growing season, mean temperature of the growing season and surface area of the elevation belt. This dataset has been used for the analysis presented in Ratier Backes et al. (in press). Mechanisms behind elevational plant species richness patterns revealed by a trait-based approach. <em>Journal of Vegetation Science</em>.</p>
Text-fig. 3. Synchrotron radiation X-ray tomographic microscopy (SRXTM) images of fruits of Canrightia foveolata sp. nov.; Catefica locality, Portugal. a) Volume rendering of fruit showing prominent rim around the middle of the fruit with reduced tepals (arrowheads) and partly abraded fruit wall exposing the pitted endotesta surface of one of two seeds (arrow); note two of the vascular bundles (vb) extending from the base of the fruit to the tepals; b) Voltex of fruit showing prominent rim around the fruit (arrowhead) and dense precipitation of crystals in the endothelium cells of one of the two seeds in the fruit; c) Longitudinal section of fruit (orthoslice yz0520) showing the inferred hypanthium rim (arrow head) and two seeds, one with a dense precipitation of crystals; note the prominent endothelium cells (asterisks) of the inner integument and the well-developed fruit wall above the seeds; d) Transverse section through basal part of fruit and seeds close to the micropyle (orthoslice xy0312) showing partly abraded fruit wall with five vascular bundles (vb) and details of the seed coat with endotesta (oi-end) surrounding the tegmen consisting of an outer epidermis (ii-o), middle layer (ii-m) and a distinct inner epidermis (endothelium) consisting of radially elongated cells (asterisk); e) Transverse section (orthoslice xy1680) through apical part of the fruit close to chalaza showing the tips of two seeds; note the endotesta (oi-end) surrounded by thick-walled cells of the exotesta (oi-o); f) Transverse section (orthoslice xy1485) through fruit in the region of the hypanthium rim showing sections through the two seeds close to the chalazal region; note endotesta (oi-end) surrounded by larger cells of exotesta (oi-o) and fruit wall (fr). Specimen, Catefica 49-S174249 (holotype, a–f). Scale bars = 300 Μm (a–c, e, f), 100 Μm (d). in The Early Cretaceous Mesofossil Flora Of Catefica, Portugal: Angiosperms
Text-fig. 3. Synchrotron radiation X-ray tomographic microscopy (SRXTM) images of fruits of Canrightia foveolata sp. nov.; Catefica locality, Portugal. a) Volume rendering of fruit showing prominent rim around the middle of the fruit with reduced tepals (arrowheads) and partly abraded fruit wall exposing the pitted endotesta surface of one of two seeds (arrow); note two of the vascular bundles (vb) extending from the base of the fruit to the tepals; b) Voltex of fruit showing prominent rim around the fruit (arrowhead) and dense precipitation of crystals in the endothelium cells of one of the two seeds in the fruit; c) Longitudinal section of fruit (orthoslice yz0520) showing the inferred hypanthium rim (arrow head) and two seeds, one with a dense precipitation of crystals; note the prominent endothelium cells (asterisks) of the inner integument and the well-developed fruit wall above the seeds; d) Transverse section through basal part of fruit and seeds close to the micropyle (orthoslice xy0312) showing partly abraded fruit wall with five vascular bundles (vb) and details of the seed coat with endotesta (oi-end) surrounding the tegmen consisting of an outer epidermis (ii-o), middle layer (ii-m) and a distinct inner epidermis (endothelium) consisting of radially elongated cells (asterisk); e) Transverse section (orthoslice xy1680) through apical part of the fruit close to chalaza showing the tips of two seeds; note the endotesta (oi-end) surrounded by thick-walled cells of the exotesta (oi-o); f) Transverse section (orthoslice xy1485) through fruit in the region of the hypanthium rim showing sections through the two seeds close to the chalazal region; note endotesta (oi-end) surrounded by larger cells of exotesta (oi-o) and fruit wall (fr). Specimen, Catefica 49-S174249 (holotype, a–f). Scale bars = 300 Μm (a–c, e, f), 100 Μm (d).
CR2MET: A high-resolution precipitation and temperature dataset for the period 1960-2021 in continental Chile.
<p>The Center for Climate and Resilience Research Meteorological dataset (CR2MET) includes two spatially-distributed products of daily precipitation and maximum/minimum near surface temperatures. The dataset covers the domain of continental Chile over a regular 0.05 degree latitude-longitude grid, and spans the period 1960-2021. Both a products are built on statistical models of the corresponding variables, calibrated against quality-controlled observational records. The CR2MET models are nurtured with a combination of data that includes different variables from ECMWF reanalysis ERA5, topographic parameters and land-surface temperature estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor.</p>
Sustainable recovery of critical elements from seawater saltworks bitterns by integration of high selective sorbents and reactive precipitation and crystallisation: Developing the probe of concept with on-site produced chemicals and energy
<p>The availability of raw mineral resources containing elements included in the Critical Raw Materials (CRMs) list is a growing concern for the European Union. Sea mining has been identified as a promising secondary source. In particular, brines obtained in solar saltworks (bitterns) contain relevant amounts of valuable CRMs such as Mg(II), B(III), other alkaline/alkaline earth metals (Rb(I), Cs(I), Sr(II)) and transition/post-transition elements (Co(II), Ga(III), Ge(IV)). However, the low concentration of some of these elements (µg/L) requires an effort to develop recovery routes that are sustainable and economically feasible where the required chemicals and energy are produced on-site from the saltworks bitterns (i.e. HCl and NaOH). Even the conventional recovery processes such as ion exchange, sorption and precipitation, which have proved to be competitive for metals recovery, are challenged in the case of Trace Elements (TEs). This work studies the recovery of TEs included in the CRMs list from saltworks bitterns after ion exchange processes. First, batch crystallisation and reactive precipitation were tested for some target elements in single-component solutions: Sr(II), Co(II), Ga(III), Ge(IV) and B(III). Then, the experiments were carried out with multi-component synthetic solutions assuming different scenarios of bittern streams coming out a selective extraction stage using sorption and ion exchange processes. The targeted elements were recovered except for Ge(IV), where alternative routes need to be evaluated, as its precipitation involves the use of tannic acid or sulphide solutions that could not be produced from the bitterns. However, a further concentration step would be necessary to achieve element concentrations closer to the mineral phases saturation. Moreover, model simulations were performed using the PHREEQC program, which provided a good prediction of the experimental trends obtained in most cases.</p>
Codes and data related to the article: Renard et al. Floods and Heavy Precipitation at the Global Scale: 100-year Analysis and 180-year Reconstruction. Journal of Geophysical Research - Atmospheres.
<p>This package contains R codes and data related to the article:</p> <p>B. Renard, D. McInerney, S. Westra, M. Leonard, D. Kavetski, M. Thyer and J.-P. Vidal. Floods and Heavy Precipitation at the Global Scale: 100-year Analysis and 180-year Reconstruction. <em>Journal of Geophysical Research - Atmospheres</em>. DOI: <a href="https://doi.org/10.1029/2022JD037908">10.1029/2022JD037908</a></p> <p><strong>Analyses</strong></p> <p>This folder contains the R scripts used to set up models, analyse results and prepare figures. See README file for details.</p> <p><strong>ShinyApp</strong></p> <p>This folder contains an interactive Shiny App to explore the data and the results from the article.</p> <p>An online version can be found at <a href="https://hydroapps.recover.inrae.fr/HEGS-paper">https://hydroapps.recover.inrae.fr/HEGS-paper</a></p> <p> </p>
Global reconstruction of flood and heavy precipitation probabilities, 1836-2015
<p>As part of the <a href="https://globxblog.inrae.fr/hegs/">HEGS project</a>, an attempt was made at reconstructing flood and heavy precipitation probabilities for thousands of stations worldwide and for the period 1836-2015. This repository contains the precipitation/streamflow data underlying this reconstruction (<a href="https://vimeo.com/802751683">https://vimeo.com/802751683</a>), and the reconstruction itself. Details can be found in <a href="https://doi.org/10.1029/2022jd037908">this publication</a>.</p> <p><strong>Data</strong></p> <p>Seasonal maxima of daily precipitation or streamflow. One file for each season, with the following columns:</p> <ol> <li>"var": variable 'Rx1day' (heavy precipitation) or 'Qx' (flood).</li> <li>"year": year. For the DJF season, year e.g. 1998 spans from December 1998 to February 1999.</li> <li>"siteID": ID of the site, as used in the original <a href="https://www.metoffice.gov.uk/hadobs/hadex2/">HadEX2</a>/<a href="https://www.metoffice.gov.uk/hadobs/hadex3/">HadEX3</a> and <a href="https://doi.pangaea.de/10.1594/PANGAEA.887470">GSIM</a> datasets.</li> <li>"lon": longitude.</li> <li>"lat": latitude.</li> <li>"value": seasonal maximum value, in mm (precipitation) or m<sup>3</sup>.s<sup>-1</sup> (streamflow).</li> <li>"returnPeriod": return period T associated with the value above.</li> <li>"nonExceedanceProb": non-exceedance probability associated with the return period (p=1-1/T).</li> </ol> <p><strong>Reconstructions</strong></p> <p>Probability of exceeding T-year events and predictive quantiles, estimated at all stations and for the period 1836-2015. One file for each season, with the following columns:</p> <ol> <li>"var": variable 'Rx1day' (heavy precipitation) or 'Qx' (flood).</li> <li>"year": year. For the DJF season, year e.g. 1998 spans from December 1998 to February 1999.</li> <li>"siteID": ID of the site, as used in the original <a href="https://www.metoffice.gov.uk/hadobs/hadex2/">HadEX2</a>/<a href="https://www.metoffice.gov.uk/hadobs/hadex3/">HadEX3</a> and <a href="https://doi.pangaea.de/10.1594/PANGAEA.887470">GSIM</a> datasets.</li> <li>"lon": longitude.</li> <li>"lat": latitude.</li> <li>"Pr[exceeding the 2-year event]": estimated probability of exceeding the 2-year event at this site during this season.</li> <li>"Pr[exceeding the 10-year event]": estimated probability of exceeding the 10-year event at this site during this season.</li> <li>"Pr[exceeding the 100-year event]": estimated probability of exceeding the 100-year event at this site during this season.</li> <li>"q5": 5%-quantile of the predictive distribution at this site during this season.</li> <li>"q10": 10%-quantile of the predictive distribution at this site during this season.</li> <li>"q25": 25%-quantile of the predictive distribution at this site during this season.</li> <li>"q50": 50%-quantile of the predictive distribution at this site during this season.</li> <li>"q75": 75%-quantile of the predictive distribution at this site during this season.</li> <li>"q90": 90%-quantile of the predictive distribution at this site during this season.</li> <li>"q95": 95%-quantile of the predictive distribution at this site during this season.</li> </ol>
Data for: Emigration and survival correlate with different precipitation metrics throughout a grassland songbird's annual cycle
<p>Many exogenous factors may influence demographic rates (i.e., births, deaths, immigration, emigration), particularly for migratory birds that must cope with variable weather and habitat throughout their range and annual cycle. In midcontinental grasslands, disturbance (e.g., fire and grazing) and precipitation influence variation in grassland structure and function, but we know little about when and why precipitation is associated with grassland species' vital rates. We related estimates of detection, survival, and emigration to <em>a priori </em>sets of precipitation metrics to test the putative alternative factors influencing movement and mortality in grasshopper sparrows (<em>Ammodramus savannarum</em>). This species is a migratory songbird that exhibits exceptionally high rates of within-season and between-season dispersal. Between 2013 and 2020, we captured and resighted grasshopper sparrows in northeastern Kansas, USA, compiling capture histories for 1,332 adult males. We tested predictions of climatic hypotheses explaining variation in survival and emigration throughout a grasshopper sparrow's annual cycle; both survival and emigration were associated with the El Niño-Southern Oscillation precipitation index (ESPI). Survival was positively related with ESPI during winter, and temporary emigration was curvilinearly related to breeding season ESPI lagged 2 years, with the highest site fidelity associated with intermediate rainfall values. The relationship between rainfall and temporary emigration likely reflects the influence of weather over multiple years on vegetation structure with consequent effects on local demography. This study provides compelling support for the idea that grassland species respond to high interannual variability by adopting dispersal strategies unlike those of many well-studied migrant birds. Furthermore, the results imply that the consequences of increasing climatic extremes may not be immediately apparent, with demographic consequences lasting for at least a few years.</p>
GPM-GMI full-swath precipitation type flag
<p>This project includes the full-swath GPM-GMI precipitation type flag retrieval for the year 2014. Due to file size limit, only March, April, June, July, August, November and December data are uploaded. Users are encouraged to contact the publisher for more days of retrievals. Retrieval is available at each GMI 1CR footprint as a probability. The reference paper is:</p> <p>Das, S., Y. Wang, <a href="https://science.gsfc.nasa.gov/sed/index.cfm?fuseAction=people.jumpBio&iphonebookid=40680">J. Gong</a>, <a href="https://science.gsfc.nasa.gov/sed/#">et al.</a> 2022. "A Comprehensive Machine Learning Study to Classify Precipitation Type over Land from Global Precipitation Measurement Microwave Imager (GPM-GMI) Measurements." <em>Remote Sensing</em>, <strong>14 </strong> <strong>(15):</strong> 3631 [<a href="http://dx.doi.org/10.3390/rs14153631">10.3390/rs14153631</a>]</p> <p>Note that in the paper, retrievals are only available over land, but we made it available globally later on and are included in these data files.</p> <p>Users are directed to read the "README" file for details on how to screen and use the data. Two plotting sample codes are provided in IDL and Python respectively.</p>
Global transportation infrastructure exposure to the change of precipitation in a warmer world
<p>This repository provides the base data to perform a global transport asset exposure analysis for extreme precipitation under climate change.In this study, we comprehensively analyze the exposure of road and railway infrastructure assets to changes in precipitation return periods globally.</p> <p>For more details, please see:</p> <p>Liu, K., Wang, Q., Wang, M. <em>et al.</em> Global transportation infrastructure exposure to the change of precipitation in a warmer world. <em>Nat Commun</em> <strong>14</strong>, 2541 (2023). https://doi.org/10.1038/s41467-023-38203-3</p>
Spatiotemporal variability of stable isotopes in precipitation and stream water in a high elevation tropical catchment in the Central Andes of Colombia
<p>Stable isotopes data set for the manuscript "Spatio-temporal variability of stable isotopes in precipitation and stream water of a high elevation tropical catchment in the Central Andes of Colombia".</p> <p>Data also used by Andrés Tangarife-Escobar for the thesis "Analysis of the spatial and temporal distribution of stable isotopes and their driving factors in the Upper Claro River Basin, Colombian Andes" to obtain the title of MSc in "Tropical Hydrogeology and Environmental Engineering" at the Technische Universität Darmstadt (Germany) in 2019. </p> <p>Samples collected by Jorge Ceballos from IDEAM (Colombia) and analyzed by the Servicio Geologico Colombiano. </p> <p> </p> <p> </p> <p> </p> <p> </p>
Tahoe rain or snow precipitation phase observations
<p>These data include observations of rain, snow, and mixed precipitation from the Tahoe Rain or Snow citizen science project. Included with each observation is a set of ancillary variables, including latitude and longitude, elevation, modeled meteorological data, and additional info. Please see the metadata file for the description and units of each data column.</p> <p>For more info, please see Jennings et al. (2023) and Arienzo et al. (2021):</p> <ul> <li>Jennings, Keith S., Monica M. Arienzo, Meghan Collins, Benjamin Hatchett, Anne W. Nolin, and Graeme Aggett. "Crowdsourced Data Highlight Precipitation Phase Partitioning Variability in Rain-Snow Transition Zone." Earth and Space Science (2023). <a href="https://doi.org/10.1029/2022EA002714">https://doi.org/10.1029/2022EA002714</a> </li> <li>Arienzo, Monica M., Meghan Collins, and Keith S. Jennings. "Enhancing engagement of citizen scientists to monitor precipitation phase." Frontiers in Earth Science 9 (2021): 617594. <a href="https://doi.org/10.3389/feart.2021.617594">https://doi.org/10.3389/feart.2021.617594</a> </li> </ul> <p>For the code used to process these data: <a href="https://github.com/SnowHydrology/MountainRainOrSnow/tree/tahoe_ros">https://github.com/SnowHydrology/MountainRainOrSnow/tree/tahoe_ros</a></p>
Oahu Bulk Precipitation Major Ions April 2018 to May 2021
<p>Precipitation major ion concentrations from 20 bulk precipitation collectors located across the island of Oahu, Hawaii, USA. Sampling occurred approximately quarterly from April 2018 to May 2021. Samples were analyzed for concentration of major inorganic ions by the Water Resources Research Center laboratory at the University of Hawaiʻi at Mānoa. Sampling was funded by the NSF Hawaiʻi EPSCoR Program through the National Science Foundation’s Research Infrastructure Improvement award (RII) Track-1: ‘Ike Wai: Securing Hawaiʻi’s Water Future Award # OIA-1557349. </p>
UKCP18 RCM precipitation and temperature bias corrected using ISIMIP3BA change-preserving quantile mapping.
<p>We present bias-corrected UK Climate Projections 2018 (UKCP18; Met Office Hadley Centre, 2018) regional datasets for temperature, precipitation, and potential evapotranspiration (1981-2080). All 12 members of the 12 km ensemble were corrected using quantile mapping and a change-preserving variant (Lange, 2019; Lange, 2020). Both methods effectively reduce biases in multiple statistics, while maintaining projected climatic changes. We provide guidance on using the bias-corrected datasets for climate change impact assessment. Please find a detailed description and evaluation in the metadata and accompanying data paper (Reyniers et al., 2025).</p> <p>---</p> <p>Met Office Hadley Centre (2018): UKCP18 Regional Projections on a 12km grid over the UK for 1980-2080. CEDA, <em>8 March 2022</em>. <a href="https://catalogue.ceda.ac.uk/uuid/589211abeb844070a95d061c8cc7f604">https://catalogue.ceda.ac.uk/uuid/589211abeb844070a95d061c8cc7f604</a></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> <p>Lange, S. (2020). ISIMIP3BASD (2.4.1). Zenodo. https://doi.org/10.5281/zenodo.3898426</p> <p>Reyniers, N., Zha, Q., Addor, N., Osborn, T. J., Forstenhäusler, N., & He, Y. (2025). Two sets of bias-corrected regional UK Climate Projections 2018 (UKCP18) of temperature, precipitation and potential evapotranspiration for Great Britain. <em>Earth System Science Data</em>, <em>2025, 17(5)</em>, 2113–2133.</p>
CubaPrec1: A 48 years long term gridded daily precipitation dataset at very high-resolution for Cuba.
<p>CubaPrec1 is a new high-resolution gridded dataset for daily precipitation across Cuba from 1961-2008. The dataset was built using the information from the data series of 630 stations from the network operated by the National Institute of Water Resources. The original station data series were quality controlled using a spatial coherence process of the data, and the missing values were estimated on each day and location independently. Using the filled data series, a grid of 3 × 3 km spatial resolution was constructed by estimating daily precipitation and their corresponding uncertainties at each grid box. This new product represents a precise spatiotemporal distribution of precipitation in Cuba and provides a useful baseline for future studies in hydrology, climatology, and meteorology.</p>
Figure S50 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S50. Optimisation of tropical and temperate niches across the Mimosoid phylogeny. Ancestral niches were estimated using a complete metachronogram for Caesalpinioideae, including non-Mimosoid Caesalpinioideae taxa, but only the Mimosoid clade is shown here.
Figure S48 in Supplementary Materials for Precipitation is the main axis of tropical plant phylogenetic turnover across space and time
Figure S48. Speciation rates estimated across the Caesalpinioideae metachronogram under eight scenarios with different fixed extinction rates. Extinction rates are shown above each subfigure, while speciation rates are indicated by branch colours.
ScienceDex guides
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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.