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.
53
datasets available to search
ShareScore release 0.7.1
Dataset results
53 results for “Hail”
Hail Event on 2022-06-28 in Locarno-Monti (TI), Switzerland: Drone Photogrammetry Imagery, Mask R-CNN Model and Analysis Data of Hailstones
<p>This hail data collection belongs to a drone hail survey performed on 2022-06-28 in Locarno-Monti (TI, Switzerland). The supercell reached the location around 07:50 UTC in the morning. Only one photogrammetry flight could be performed and thus no estimation of the hail melting process is available. The orthophoto is masked to ignore parts where detection of hail is unwanted.</p> <p> </p> <p>Expert 1 (lai, mlainer), Expert 2 (jtm), Expert 3 (por, jportmann)</p>
Quantifying hail and lightning risk factors using long-term observations around Australia - Hail and Lightning Datasets
<p>These data accompany a paper referenced as doi: 10.1029/2020JD033101. Two spreadsheets are provided as used to derive the hourly and monthly occurrence of hail or lightning events within the domains of the ten radars sites (Melbourne, Wollongong, Gympie, Grafton, Canberra, Marburg, Adelaide, Namoi, Perth, Hobart). Lightning events as defined in this paper (derived from post-processed lightning information) were provided for 2005-2018 and hail data from 1997-2018 (noting that the start date of hail is dependent on when the respective radar site was established). A value of 1 indicates a lightning/hail event occurred during that hour (in UTC +0). Information on processing methods and data are provided in the published paper for the doi listed above.</p>
Radar data for 12 hail events in Switzerland
Radar-based daily hail hazard data at 1km spatial resolution for 12 hail days in Switzerland between 2017 and 2021 provided by the Swiss Federal Office of Meteorology and Climatology (MeteoSwiss). Included dates are the ones where hail damage information is available from <a href="https://doi.org/10.5281/zenodo.11064767">"Reported hail damage for 12 hail events in Switzerland"</a> (YYYY-MM-DD): 2017-06-27, 2017-07-08, 2017-08-01, 2019-06-15, 2019-06-30, 2019-07-01, 2021-06-20, 2021-06-21, 2021-06-28, 2021-07-12, 2021-07-13, 2021-07-24. The dataset contains two variables based on single-polarization radar data: the Maximum Expected Severe Hail Size (MESHS) and the Probability of Hail (POH).
Integrated Canadian Hail Database (2005-2022)
<p>This dataset combines hail reports in Canada between 2005 and 2022 from two internal sources in Environment and Climate Change Canada. Time is in UTC. See <a href="https://en.wikipedia.org/wiki/Provinces_and_territories_of_Canada">Provinces and territories of Canada - Wikipedia</a> for province codes. Common reference objects are used to compare with the diameter of the largest hail stone in vicinity. </p>
MCIT storm tracks with updraft radar data for large hail cases in the United States (2013 - 2023)
<p>Storm tracking data from 114 hail days in the United States between 2013 and 2023. Cases were selected based on the availability of abundant Storm Prediction Center (SPC) hail reports (either at least 20 reports of hail > 1 cm or five reports > 10 cm) in a range between 20 and 90 km from a NEXRAD radar site. Only cases in a geographic area from 28-48°N and 105-90°E, roughly corresponding to the U.S. Great Plains, were considered. Cells are quality filtered based on these criteria: (1) Cell center within 120 km of the radar range, and (2) continuous tracking for at least 6 timesteps (approx. 30 minutes, depending on radar scan rate). SPC hail data is matched to tracking timesteps. We used this data to train a Random Forest model for hail size nowcasting.</p> <p>Further metadata can be requested from the authors.</p>
Reported hail damage for 12 hail events in Switzerland
Hail damage to crops for 10-12 hail days (depending on the crop) between 2017 and 2021 from the Swiss Hail insurance company including the number of damaged fields at 1, 2, 4, and 8 km resolution for the following crop types: winter wheat, maize (incl. silage and forage maize), winter barley, rapeseed, and grapevine as well as an aggregate crop class field crops (incl. wheat, maize, barley, and rapeseed). The dataset can be used to calibrate and verify crop hail damage models.
Business process models for a ride fulfilment process in a ride-hailing company enabled by an autonomous driving system
<p>The repository contains the business process models of a ride fulfilment process in a ride-hailing company enabled by an autonomous driving system. The models are depicted using BPMN.2.0 language and are extended with annotations for usage in the <a href="https://dpotool.cs.ut.ee/">DPO tool</a>. The models, which contain "Pleak" as a part of the title, are created using PE-BPMN language and some of them are annotated for usage in the <a href="https://pleak.io/">Pleak</a> tool set. </p> <p>The repository also contains two .csv files which contain the results of the simple disclosure analysis ("<em>6_RideFulfillment_PK_SecSharing_combined-Simple-Disclosure-results.csv</em>") and the results of the leak-when analysis ("<em>7_Pleak_RideFulfillment_PK_SecrSharing_BPMN_Leak_When-results.csv</em>") in the ride fulfilment process. Both analyses have been conducted using the <a href="https://pleak.io/">Pleak</a> tool set and the business process models with respective names from this repository.</p>
ERA5 data by Canadian hail event 2005-2022
<p>This dataset is in HDF5 format. The data was pulled from the ECMWF reanalysis datasets "<a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview"><strong>ERA5 hourly data on single levels from 1940 to present</strong></a>" and "<a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-pressure-levels?tab=overview"><strong>ERA5 hourly data on pressure levels from 1940 to present</strong></a>." </p><p>Each file in "era5_by_canadian_hail_event" is associated to a specific Canadian hail event and combines the relevant data from both ERA5 datasets. The hail events were created based on the 7000 Canadian hail reports contained in "<a href="https://zenodo.org/records/8015925">Integrated Canadian Hail Database (2005-2022)</a>", where we considered reports to be of the same event if they were within a specified window in time and space (7 hours by 256 km). The 7000 reports were grouped into 2092 hail events. Thus, our ERA5 based dataset <strong>contains 2092 files</strong>. For more information on how the data was handled, see the GitHub repository "<a href="https://github.com/aconlon-eccc/era5-based-hail">era5-based-hail</a>." </p><p>Each file in this dataset contains the following variables from "<a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview"><strong>ERA5 hourly data on single levels from 1940 to present</strong></a>" : </p><ul><li>cp [m]: <a href="https://codes.ecmwf.int/grib/param-db/?id=143">Convective precipitation </a></li><li>d2m [K]: <a href="https://codes.ecmwf.int/grib/param-db/?id=168">Dewpoint temperature at 2m height </a></li><li>sp [Pa]: <a href="https://codes.ecmwf.int/grib/param-db/?id=134">Surface pressure</a></li><li>t2m [K]: Temperature at 2m height</li><li>tcc [100%]: <a href="https://codes.ecmwf.int/grib/param-db/?id=164">Total cloud cover</a></li><li>tciw [kg m-2]: <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview">Total column vertically-integrated cloud ice water</a></li><li>tclw [kg m-2]: <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview">Total column vertically-integrated cloud liquid water </a></li><li>tcrw [kg m-2]: <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview">Total column rain water</a></li><li>tcsw [kg m-2]: <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview">Total column snow water</a></li><li>tcwv [kg m-2]: <a href="https://codes.ecmwf.int/grib/param-db/?id=137">Total column vertically-integrated water vapour</a></li><li>tcw [kg m-2]: <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview">Total column water</a></li><li>tp [m]: <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview">Total precipitation</a></li><li>u10 [m/s]: <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview">u-component of wind at 10m height</a></li><li>v10 [m/s]: <a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-single-levels?tab=overview">v-component of wind at 10m height</a></li></ul><p>And following variables from "<a href="https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-pressure-levels?tab=overview"><strong>ERA5 hourly data on pressure levels from 1940 to present</strong></a>" :</p><ul><li>r [%]: <a href="https://codes.ecmwf.int/grib/param-db/?id=157">Relative humidity</a></li><li>t [K]: <a href="https://codes.ecmwf.int/grib/param-db/?id=130">Temperature</a></li><li>u [m/s]: <a href="https://codes.ecmwf.int/grib/param-db/?id=131">Longitudinal wind</a></li><li>v [m/s]: <a href="https://codes.ecmwf.int/grib/param-db/?id=132">Latitudinal wind</a></li><li>z [m^2/s^2]: <a href="https://codes.ecmwf.int/grib/param-db/?id=129">Geopotential</a></li></ul><p>at pressure levels [hPa]: 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 775, 800, 825, 850, 875, 900, 925, 950, 975, 1000.</p>
Proxy-based hail-prone-day climatology and trends for Australia 1979-2021
<p><strong>Climatology of and trends on hail-prone days over Australia from 1979-2021</strong></p> <p>Hail-prone day climatology is calculated using the proxy of Raupach et al., 2023a (DOI: 10.1175/MWR-D-22-0127.1) applied to ERA5 pressure-level reanalysis data (DOI: 10.24381/cds.bd0915c6) at gridded 0.25 degree resolution for 1979-2021 (daily) and March 1979-May 2022 (seasonally). A day was considered hail-prone if a hail-prone atmosphere was detected at 03, 06, or 09 UTC. Trends in hail-prone days are calculated as in Raupach et al., 2023b (DOI: 10.1038/s41612-023-00454-8).</p> <p>The climatology shows the mean annual hail-prone days per grid point over 1979-2021, while seasonal climatologies are over March 1979-May 2022. The trends information shows changes in annual hail-prone days over the same period.</p> <p>NB: The seasonal climatology values differ slightly from those in Supp. Figure 3 in Raupach et al 2023, owing to an improved calculation of the climatology. The differences for each season are less than hail-prone 0.5 days. For details of the change see https://github.com/traupach/era5_hail_climatology/blob/main/analysis/climatology_for_zenodo.ipynb.</p> <p>These data are licensed with a Creative Commons Attribution 4.0 International license (CC-BY-4.0, https://creativecommons.org/licenses/by/4.0/legalcode). These results contain modified Copernicus Climate Change Service information 2022. Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.</p> <p>If using these data, please inform T. Raupach at t.raupach@unsw.edu.au, and please cite the following paper for which these data were calculated: </p> <p>Raupach, T.H., Soderholm, J.S., Warren, R.A. <em>et al.</em> Changes in hail hazard across Australia: 1979–2021. <em>npj Clim Atmos Sci</em> <strong>6</strong>, 143 (2023). https://doi.org/10.1038/s41612-023-00454-8</p> <p>Acknowledgements: This research was undertaken with the assistance of resources and services from the National Computational Infrastructure (NCI), which is supported by the Australian Government.</p>
Haile Sand Fort - UK
A videogrammetry 3d scan of Haile Sand Fort made in Agisoft software from 119 frames from this video: https://www.youtube.com/watch?v=OSWSbicdOB0 Source: Objaverse 1.0 / Sketchfab
Datasets used in "A 23-Year Severe Hail Climatology Using GridRad MESH Observations"
<p>These datasets are those used in the Murillo et al. (2021) publication in the AMS journal of Monthly Weather Review. For any questions, please email Dr. Murillo at emurillo@ucar.edu.</p>
Dataset for the manuscript "Comparison of Spatiotemporal Distribution and Occurrence Conditions of Large and Small Hail Events in Beijing-Tianjin-Hebei Region"
<p>This data set is a supplement to the journal article " Comparison of Spatiotemporal Distribution and Occurrence Conditions of Large and Small Hail Events in Beijing-Tianjin-Hebei Region".</p> <p>The data set consists of</p> <ul> <li>Hail disaster information included the station NO., hail frequency and the maximum size of hailstone.</li> <li>The atmospheric environment data from ERA-interim data associated with the hail events in this study. </li> <li>VIL and meso-scale rotation parameters correspond to hailstorms. </li> </ul>
FIGURE 11. Coprolites from Haile 7C in New early Pleistocene Alligator (Eusuchia: Crocodylia) from Florida bridges a gap in Alligator evolution
FIGURE 11. Coprolites from Haile 7C (right, UF 162527, and top left, UF 162528) and Haile 7G (left middle, UF 310185, and left bottom, UF 310180) attributed to Alligator hailensis. Scale = 2 cm.
Spanish Supercell Dataset - Hail
Open the record for dataset details and reuse information.
Hydrodynamic data collected from Hailing Island
<p>Field observations of water dynamics at the Hailing Island, China<br>This dataset records water dynamics data (water depth, wave parameters) collected during the landing period of Typhoon Chaba at the Hailing Island, Guangdong province, China. There are three observation stations, p1, p2, and p3, located at coordinates (111.9665, 21.6498), (111.9652, 21.648), and (111.9667, 21.6504), respectively. Each station is equipped with pressure sensors (RBR solo3), and the instruments were installed on December 25, 2021. The data covers the period from June 30, 2022 to July 6, 2022.</p>
Hydrodynamic data of Hailing Island
<p>The file provides the hydrodynamic data (water depth, wave parameters, current velocity) measured from 30th June to 1st August 2022 at the Hailing Island, Guangdong province, China.</p>
Hydrodynamic data of Hailing Island
<p>This dataset records water dynamics data (water depth, wave parameters) collected during the landing period of Typhoon Chaba at the Hailing Island, Guangdong province, China. There are three observation stations, p1, p2, and p3, located at coordinates (111.9665, 21.6498), (111.9652, 21.648), and (111.9667, 21.6504), respectively. Each station is equipped with pressure sensors (RBR solo3). The data covers the period from June 30, 2022 to July 6, 2022.</p>
Obesity Pathway Intervention Among Overweight and Obese Adults at Primary Care Centers in Hail, Saudi Arabia
ClinicalTrials.gov study NCT05654337. IPD Sharing: NO. Countries: 1. Publications: 1.
Storm Interactions in Cases of EF2+ Tornadoes and EF3+ Hail (2008-2022)
<p>This is a quality-controlled dataset of 3"+ hail reports and EF3+ tornadoes (their genesis locations) within 90 km of a WSR-88D between 2008-2021. EF2+ tornadoes are also included west of -98 degrees longitude. Tornadoes are also included from 2022-2023. An analysis of nearby features accompanying the parent storms (performed by Nixon) is included. The orientation of storms are included. The positions of neighboring cells at 4 different times preceding hazard production (T-30, T-20, T-10, and T-0) are also included in the format "direction_distance" from the mesocyclone of the storm in question. </p>
Data and Code for Hail Study
Open the record for dataset details and reuse information.
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.