14 datasets found
  1. United States tornado data

    • kaggle.com
    Updated Sep 17, 2020
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    WxExplorer (2020). United States tornado data [Dataset]. https://www.kaggle.com/datasets/wxexplorer/yearly-united-states-tornado-data-per-state
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 17, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    WxExplorer
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    United States
    Description

    Context

    This data set contains the number of confirmed tornadoes for each state for each year and their responding affects.

    Content

    Current table includes number of confirmed tornadoes in each state for each year from 1951 to 2019. Future datasets will be related to Fujita/Enhanced Fujita rank, total damage (reported and inflation corrected), and fatalities/injuries. Data is from National Centers for Environmental Information's Storm Events Database.

    Inspiration

    I am curious about the trend of sever weather occurring in the United States over time. This started with tornadic events but will evolve to severe thunderstorm and hail events as well.

  2. Data from: Tornado Tracks

    • gis-fema.hub.arcgis.com
    • prep-response-portal.napsgfoundation.org
    • +3more
    Updated Feb 7, 2020
    + more versions
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    Esri U.S. Federal Datasets (2020). Tornado Tracks [Dataset]. https://gis-fema.hub.arcgis.com/datasets/fedmaps::tornado-tracks-1/about
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    Dataset updated
    Feb 7, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri U.S. Federal Datasets
    Area covered
    Description

    Tornado TracksThis feature layer, utilizing data from the National Oceanic and Atmospheric Administration (NOAA), displays tornadoes in the United States, Puerto Rico and U.S. Virgin Islands between 1950 and 2024. A tornado track shows the route of a tornado. Per NOAA, "A tornado is a narrow, violently rotating column of air that extends from a thunderstorm to the ground. Because wind is invisible, it is hard to see a tornado unless it forms a condensation funnel made up of water droplets, dust and debris. Tornadoes can be among the most violent phenomena of all atmospheric storms we experience. The most destructive tornadoes occur from supercells, which are rotating thunderstorms with a well-defined radar circulation called a mesocyclone. (Supercells can also produce damaging hail, severe non-tornadic winds, frequent lightning, and flash floods.)"EF-5 Tornado Track (May 3, 1999) near Oklahoma City, OklahomaData currency: December 30, 2024Data source: Storm Prediction CenterData modifications: Added fields Calculated Month and DateFor more information: Severe Weather 101 - Tornadoes; NSSL Research: TornadoesSupport documentation: SPC Tornado, Hail, and Wind Database Format SpecificationFor feedback, please contact: ArcGIScomNationalMaps@esri.comNational Oceanic and Atmospheric AdministrationPer NOAA, its mission is "To understand and predict changes in climate, weather, ocean, and coasts, to share that knowledge and information with others, and to conserve and manage coastal and marine ecosystems and resources."

  3. Tornadoes

    • hub.arcgis.com
    • cest-cusec.hub.arcgis.com
    Updated Feb 6, 2020
    + more versions
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    Esri U.S. Federal Datasets (2020). Tornadoes [Dataset]. https://hub.arcgis.com/datasets/0db253f3e83a4c5f9f5ab9577f2dcb49
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    Dataset updated
    Feb 6, 2020
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri U.S. Federal Datasets
    Area covered
    Description

    TornadoesThis feature layer, utilizing data from the National Oceanic and Atmospheric Administration (NOAA), displays tornadoes in the United States, Puerto Rico and U.S. Virgin Islands between 1950 and 2024. Per NOAA, "A tornado is a narrow, violently rotating column of air that extends from a thunderstorm to the ground. Because wind is invisible, it is hard to see a tornado unless it forms a condensation funnel made up of water droplets, dust and debris. Tornadoes can be among the most violent phenomena of all atmospheric storms we experience. The most destructive tornadoes occur from supercells, which are rotating thunderstorms with a well-defined radar circulation called a mesocyclone. (Supercells can also produce damaging hail, severe non-tornadic winds, frequent lightning, and flash floods.)"EF-5 Tornado (May 22, 2011) near Joplin, MissouriData currency: December 30, 2024Data source: Storm Prediction CenterData modifications: Added fields Calculated Month and DateFor more information: Severe Weather 101 - Tornadoes; NSSL Research: TornadoesSupport documentation: SPC Tornado, Hail, and Wind Database Format SpecificationFor feedback, please contact: ArcGIScomNationalMaps@esri.comNational Oceanic and Atmospheric AdministrationPer NOAA, its mission is "To understand and predict changes in climate, weather, ocean, and coasts, to share that knowledge and information with others, and to conserve and manage coastal and marine ecosystems and resources."

  4. NCDC Storm Events Database

    • catalog.data.gov
    • data.globalchange.gov
    • +3more
    Updated Sep 19, 2023
    + more versions
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    NOAA National Centers for Environmental Information (Point of Contact) (2023). NCDC Storm Events Database [Dataset]. https://catalog.data.gov/dataset/ncdc-storm-events-database2
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    Dataset updated
    Sep 19, 2023
    Dataset provided by
    National Centers for Environmental Informationhttps://www.ncei.noaa.gov/
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Description

    Storm Data is provided by the National Weather Service (NWS) and contain statistics on personal injuries and damage estimates. Storm Data covers the United States of America. The data began as early as 1950 through to the present, updated monthly with up to a 120 day delay possible. NCDC Storm Event database allows users to find various types of storms recorded by county, or use other selection criteria as desired. The data contain a chronological listing, by state, of hurricanes, tornadoes, thunderstorms, hail, floods, drought conditions, lightning, high winds, snow, temperature extremes and other weather phenomena.

  5. f

    Tornadoes and Waterspouts in Chile / Tornados y Trombas en Chile

    • figshare.com
    xlsx
    Updated Apr 22, 2025
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    Cristian Bastías-Curivil; Roberto Rondanelli; Jose Vicencio; Felipe Matus; Victoria Caballero; Francisca Munoz; José Barraza; Diego Campos; Raúl Valenzuela; Alejandro de la Maza (2025). Tornadoes and Waterspouts in Chile / Tornados y Trombas en Chile [Dataset]. http://doi.org/10.6084/m9.figshare.25119566.v3
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    xlsxAvailable download formats
    Dataset updated
    Apr 22, 2025
    Dataset provided by
    figshare
    Authors
    Cristian Bastías-Curivil; Roberto Rondanelli; Jose Vicencio; Felipe Matus; Victoria Caballero; Francisca Munoz; José Barraza; Diego Campos; Raúl Valenzuela; Alejandro de la Maza
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Chile
    Description

    We provide a dataset of tornadoes and waterspouts in Chile from 1554 to present based in chronicles, newspaper articles, social media, scientific literature and books. The database includes only those events that have been qualified as more than likely a tornado or waterspout based on a subjective qualification by the researchers. For each tornado we provide at least one geographical location point, the local and UTC hour (if known) and for most cases an estimation of the intensity based on the Enhanced Fujita damage scale.The following are the parameters contained in the database:N°: This is the entry number or identifier for each record in the file.Location: The name of the place where the weather event occurred.Latitude: The geographical latitude coordinate of the event's location.Longitude: The geographical longitude coordinate of the event's location.Date (Gregorian Calendar): The date when the event occurred, according to the Gregorian calendar.Hour (local): The local time when the event occurred.Hour (UTC): The time of the event in Coordinated Universal Time (UTC).Sound: A binary indicator (usually 1 for 'Yes' and 0 for 'No') showing whether there was a notable sound associated with the event.Hail: A binary indicator showing whether hail was a feature of the weather event.Electric Storm: A binary indicator showing whether the event involved an electric storm.Damage: A binary indicator showing whether there was any damage resulting from the event.Tornado: A binary indicator showing whether a tornado was a part of the event.Waterspout: A binary indicator showing whether a waterspout was observed during the event.Register: This column refers to the existence of some witness account or visual material of a rotating column.Max. EF Rating: The maximum Enhanced Fujita Scale rating assigned to the tornado, indicating its intensity.Analyst: The name or initials of the person who analyzed or reported the event.Fatalities: The number of fatalities (deaths) caused by the event.Injured: The number of injuries reported due to the event.Link to Documents: References or links to documents where the event is described or recorded.Sources: The sources or references from where the information about the event is derived.Comments: Additional remarks or notes about the event, providing context or extra details.

  6. A

    Twister Dashboard: Exploring Three Decades of Violent Storms

    • data.amerigeoss.org
    • amerigeo.org
    • +2more
    esri rest, html
    Updated Oct 23, 2018
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    AmeriGEO ArcGIS (2018). Twister Dashboard: Exploring Three Decades of Violent Storms [Dataset]. https://data.amerigeoss.org/de/dataset/twister-dashboard-exploring-three-decades-of-violent-storms
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    esri rest, htmlAvailable download formats
    Dataset updated
    Oct 23, 2018
    Dataset provided by
    AmeriGEO ArcGIS
    Description

    Although tornadoes can occur throughout the year, prime time for twisters in the U.S. is spring and early summer. Larger symbols show more violent tornadoes. Zoom into the map to see approximate tornado tracks.


    This custom story map design was produced by Esri's story maps team for Smithsonian. It was published by Smithsonian on March 24, 2014. For more information on story maps, visit storymaps.arcgis.com. This story doesn't use one of the Story Map app templates.

    Data is from the National Oceanic and Atmospheric Administration.

  7. d

    Data from: Catastrophic storms, forest disturbance, and the natural history...

    • datadryad.org
    • data.niaid.nih.gov
    • +1more
    zip
    Updated Apr 1, 2024
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    Gary Graves (2024). Catastrophic storms, forest disturbance, and the natural history of Swainson’s warbler [Dataset]. http://doi.org/10.5061/dryad.gmsbcc2w8
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    zipAvailable download formats
    Dataset updated
    Apr 1, 2024
    Dataset provided by
    Dryad
    Authors
    Gary Graves
    Description

    Catastrophic storms, forest disturbance, and the natural history of Swainson’s warbler

    https://doi.org/10.5061/dryad.gmsbcc2w8

    Description of the data and file structure

    The spreadsheet presents the song recording field number, location (state and county or parish), date, and geographic coordinates of 1717 territorial Swainson's warblers (Limnothlypis swainsonii) documented from 1986 to 2014 in the southeastern United States. Records are ordered by state, county or parish, date, and song recording field number. All recordings were made by the author.

  8. Data from: NSSFC Severe Local Storms Log, January 1955 to June 1972

    • oidc.rda.ucar.edu
    • rda-web-prod.ucar.edu
    • +2more
    Updated Jan 11, 1980
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    Storm Prediction Center/ National Centers for Environmental Prediction/ National Weather Service/NOAA/U.S. Department of Commerce (1980). NSSFC Severe Local Storms Log, January 1955 to June 1972 [Dataset]. https://oidc.rda.ucar.edu/datasets/d808000/citation/
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    Dataset updated
    Jan 11, 1980
    Dataset provided by
    University Corporation for Atmospheric Research
    Authors
    Storm Prediction Center/ National Centers for Environmental Prediction/ National Weather Service/NOAA/U.S. Department of Commerce
    Time period covered
    Jan 1955 - Jun 1972
    Description

    This dataset contains the log maintained by the National Severe Storms Forecast Center (NSSFC), of severe local storm event reports, from 1955 through June 1972. It has one line entries for tornadoes, funnel clouds, surface wind gusts, hail and aircraft turbulence. There are about 3800 reports per year, from about 600 surface airways stations.

  9. National Risk Index Annualized Frequency Tornado

    • resilience-fema.hub.arcgis.com
    • impactmap-smudallas.hub.arcgis.com
    Updated Jul 6, 2021
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    FEMA AGOL (2021). National Risk Index Annualized Frequency Tornado [Dataset]. https://resilience-fema.hub.arcgis.com/maps/fbb6914cabe4446e88ca5cace1bcd28c
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    Dataset updated
    Jul 6, 2021
    Dataset provided by
    Federal Emergency Management Agencyhttp://www.fema.gov/
    Authors
    FEMA AGOL
    Area covered
    Description

    National Risk Index Version: March 2023 (1.19.0)A Tornado is a narrow, violently rotating column of air that extends from the base of a thunderstorm to the ground and is visible only if it forms a condensation funnel made up of water droplets, dust and debris. Annualized frequency values for Tornadoes are in units of events per year.The National Risk Index is a dataset and online tool that helps to illustrate the communities most at risk for 18 natural hazards across the United States and territories: Avalanche, Coastal Flooding, Cold Wave, Drought, Earthquake, Hail, Heat Wave, Hurricane, Ice Storm, Landslide, Lightning, Riverine Flooding, Strong Wind, Tornado, Tsunami, Volcanic Activity, Wildfire, and Winter Weather. The National Risk Index provides Risk Index values, scores and ratings based on data for Expected Annual Loss due to natural hazards, Social Vulnerability, and Community Resilience. Separate values, scores and ratings are also provided for Expected Annual Loss, Social Vulnerability, and Community Resilience. For the Risk Index and Expected Annual Loss, values, scores and ratings can be viewed as a composite score for all hazards or individually for each of the 18 hazard types.Sources for Expected Annual Loss data include: Alaska Department of Natural Resources, Arizona State University’s (ASU) Center for Emergency Management and Homeland Security (CEMHS), California Department of Conservation, California Office of Emergency Services California Geological Survey, Colorado Avalanche Information Center, CoreLogic’s Flood Services, Federal Emergency Management Agency (FEMA) National Flood Insurance Program, Humanitarian Data Exchange (HDX), Iowa State University's Iowa Environmental Mesonet, Multi-Resolution Land Characteristics (MLRC) Consortium, National Aeronautics and Space Administration’s (NASA) Cooperative Open Online Landslide Repository (COOLR), National Earthquake Hazards Reduction Program (NEHRP), National Oceanic and Atmospheric Administration’s National Centers for Environmental Information (NCEI), National Oceanic and Atmospheric Administration's National Hurricane Center, National Oceanic and Atmospheric Administration's National Weather Service (NWS), National Oceanic and Atmospheric Administration's Office for Coastal Management, National Oceanic and Atmospheric Administration's National Geophysical Data Center, National Oceanic and Atmospheric Administration's Storm Prediction Center, Oregon Department of Geology and Mineral Industries, Pacific Islands Ocean Observing System, Puerto Rico Seismic Network, Smithsonian Institution's Global Volcanism Program, State of Hawaii’s Office of Planning’s Statewide GIS Program, U.S. Army Corps of Engineers’ Cold Regions Research and Engineering Laboratory (CRREL), U.S. Census Bureau, U.S. Department of Agriculture's (USDA) National Agricultural Statistics Service (NASS), U.S. Forest Service's Fire Modeling Institute's Missoula Fire Sciences Lab, U.S. Forest Service's National Avalanche Center (NAC), U.S. Geological Survey (USGS), U.S. Geological Survey's Landslide Hazards Program, United Nations Office for Disaster Risk Reduction (UNDRR), University of Alaska – Fairbanks' Alaska Earthquake Center, University of Nebraska-Lincoln's National Drought Mitigation Center (NDMC), University of Southern California's Tsunami Research Center, and Washington State Department of Natural Resources.Data for Social Vulnerability are provided by the Centers for Disease Control (CDC) Agency for Toxic Substances and Disease Registry (ATSDR) Social Vulnerability Index, and data for Community Resilience are provided by University of South Carolina's Hazards and Vulnerability Research Institute’s (HVRI) 2020 Baseline Resilience Indicators for Communities.The source of the boundaries for counties and Census tracts are based on the U.S. Census Bureau’s 2021 TIGER/Line shapefiles. Building value and population exposures for communities are based on FEMA’s Hazus 6.0. Agriculture values are based on the USDA 2017 Census of Agriculture.

  10. NOAA Next Generation Radar (NEXRAD) Level 3 Products

    • ncei.noaa.gov
    • s.cnmilf.com
    • +1more
    kmz
    Updated 1992
    + more versions
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    NOAA National Weather Service (NWS) Radar Operations Center (1992). NOAA Next Generation Radar (NEXRAD) Level 3 Products [Dataset]. https://www.ncei.noaa.gov/access/metadata/landing-page/bin/iso?id=gov.noaa.ncdc:C00708
    Explore at:
    kmzAvailable download formats
    Dataset updated
    1992
    Dataset provided by
    National Centers for Environmental Informationhttps://www.ncei.noaa.gov/
    National Oceanic and Atmospheric Administrationhttp://www.noaa.gov/
    Authors
    NOAA National Weather Service (NWS) Radar Operations Center
    Time period covered
    May 7, 1992 - Present
    Area covered
    Ocean > Pacific Ocean > Western Pacific Ocean > Yellow Sea, Continent > North America > United States Of America, Ocean > Pacific Ocean > North Pacific Ocean > Gulf Of Alaska, Ocean > Pacific Ocean > Western Pacific Ocean > East China Sea, Geographic Region > Northern Hemisphere, Ocean > Atlantic Ocean > North Atlantic Ocean > Caribbean Sea > Puerto Rico, Ocean > Pacific Ocean > Central Pacific Ocean > Kiribati, geographic bounding box, Geographic Region > Mid-Latitude, Ocean > Pacific Ocean > North Pacific Ocean > Bering Sea
    Description

    This dataset consists of Level 3 weather radar products collected from Next-Generation Radar (NEXRAD) stations located in the contiguous United States, Alaska, Hawaii, U.S. territories and at military base sites. NEXRAD is a network of 160 high-resolution Doppler weather radars operated by the NOAA National Weather Service (NWS), the Federal Aviation Administration (FAA), and the U.S. Air Force (USAF). Doppler radars detect atmospheric precipitation and winds, which allow scientists to track and anticipate weather events, such as rain, ice pellets, snow, hail, and tornadoes, as well as some non-weather objects like birds and insects. NEXRAD stations use the Weather Surveillance Radar - 1988, Doppler (WSR-88D) system. This is a 10 cm wavelength (S-Band) radar that operates at a frequency between 2,700 and 3,000 MHz. The radar system operates in two basic modes: a slow-scanning Clear Air Mode (Mode B) for analyzing air movements when there is little or no precipitation activity in the area, and a Precipitation Mode (Mode A) with a faster scan for tracking active weather. The two modes employ nine Volume Coverage Patterns (VCPs) to adequately sample the atmosphere based on weather conditions. A VCP is a series of 360 degree sweeps of the antenna at pre-determined elevation angles and pulse repetition frequencies completed in a specified period of time. The radar scan times 4.5, 5, 6 or 10 minutes depending on the selected VCP. During 2008, the WSR-88D radars were upgraded to produce increased spatial resolution data, called Super Resolution. The earlier Legacy Resolution data provides radar reflectivity at 1.0 degree azimuthal by 1 km range gate resolution to a range of 460 km, and Doppler velocity and spectrum width at 1.0 degree azimuthal by 250 m range gate resolution to a range of 230 km. The upgraded Super Resolution data provides radar reflectivity at 0.5 degree azimuthal by 250 m range gate resolution to a range of 460 km, and Doppler velocity and spectrum width at 0.5 degree azimuthal by 250 m range gate resolution to a range of 300 km. Super resolution makes a compromise of slightly decreased noise reduction for a large gain in resolution. In 2010, the deployment of the Dual Polarization (Dual Pol) capability to NEXRAD sites began with the first operational Dual Pol radar in May 2011. Dual Pol radar capability adds vertical polarization to the previous horizontal radar waves, in order to more accurately discern the return signal. This allows the radar to better distinguish between types of precipitation (e.g., rain, hail and snow), improves rainfall estimates, improves data retrieval in mountainous terrain, and aids in removal of non-weather artifacts. The NEXRAD products are divided in two data processing levels. The lower Level 2 data are base products at original resolution. Level 2 data are recorded at all NWS and most USAF and FAA WSR-88D sites. From the Level 2 quantities, computer processing generates numerous meteorological analysis Level 3 products. The Level 3 data consists of reduced resolution, low-bandwidth, base products as well as many derived, post-processed products. Level 3 products are recorded at most U.S. sites, though non-US sites do not have Level 3 products. There are over 40 Level 3 products available from the NCDC. General products for Level 3 include the base and composite reflectivity, storm relative velocity, vertical integrated liquid, echo tops and VAD wind profile. Precipitation products for Level 3 include estimated ground accumulated rainfall amounts for one and three hour periods, storm totals, and digital arrays. Estimates are based on reflectivity to rainfall rate (Z-R) relationships. Overlay products for Level 3 are alphanumeric data that give detailed information on certain parameters for an identified storm cell. These include storm structure, hail index, mesocyclone identification, tornadic vortex signature, and storm tracking information. Radar messages for Level 3 are sent by the radar site to users in order to know more about the radar status and special product data. NEXRAD data are provided to the NOAA National Centers for Environmental Information (NCEI) for archiving and dissemination to users. Data coverage varies by station and ranges from May 1992 to 1 day from present. Most stations began observing in the mid-1990s, and most period of records are continuous.

  11. a

    Multiple Hazard Index for United States Counties

    • hub.arcgis.com
    Updated Jul 29, 2016
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    jjs2154_columbia (2016). Multiple Hazard Index for United States Counties [Dataset]. https://hub.arcgis.com/maps/800f684ebadf423bae4c669cb0a1d7da
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    Dataset updated
    Jul 29, 2016
    Dataset authored and provided by
    jjs2154_columbia
    Area covered
    Description

    OverviewThe multiple hazard index for the United States Counties was designed to map natural hazard relating to exposure to multiple natural disasters. The index was created to provide communities and public health officials with an overview of the risks that are prominent in their county, and to facilitate the comparison of hazard level between counties. Most existing hazard maps focus on a single disaster type. By creating a measure that aggregates the hazard from individual disasters, the increased hazard that results from exposure to multiple natural disasters can be better understood. The multiple hazard index represents the aggregate of hazard from eleven individual disasters. Layers displaying the hazard from each individual disaster are also included.

    The hazard index is displayed visually as a choropleth map, with the color blue representing areas with less hazard and red representing areas with higher hazard. Users can click on each county to view its hazard index value, and the level of hazard for each individual disaster. Layers describing the relative level of hazard from each individual disaster are also available as choropleth maps with red areas representing high, orange representing medium, and yellow representing low levels of hazard.Methodology and Data CitationsMultiple Hazard Index

    The multiple hazard index was created by coding the individual hazard classifications and summing the coded values for each United States County. Each individual hazard is weighted equally in the multiple hazard index. Alaska and Hawaii were excluded from analysis because one third of individual hazard datasets only describe the coterminous United States.

    Avalanche Hazard

    University of South Carolina Hazards and Vulnerability Research Institute. “Spatial Hazard Events and Losses Database”. United States Counties. “Avalanches United States 2001-2009”. < http://hvri.geog.sc.edu/SHELDUS/

    Downloaded 06/2016.

    Classification

    Avalanche hazard was classified by dividing counties based upon the number of avalanches they experienced over the nine year period in the dataset. Avalanche hazard was not normalized by total county area because it caused an over-emphasis on small counties, and because avalanches are a highly local hazard.

    None = 0 AvalanchesLow = 1 AvalancheMedium = 2-5 AvalanchesHigh = 6-10 Avalanches

    Earthquake Hazard

    United States Geological Survey. “Earthquake Hazard Maps”. 1:2,000,000. “Peak Ground Acceleration 2% in 50 Years”. < http://earthquake.usgs.gov/hazards/products/conterminous/

    . Downloaded 07/2016.

    Classification

    Peak ground acceleration (% gravity) with a 2% likelihood in 50 years was averaged by United States County, and the earthquake hazard of counties was classified based upon this average.

    Low = 0 - 14.25 % gravity peak ground accelerationMedium = 14.26 - 47.5 % gravity peak ground accelerationHigh = 47.5+ % gravity peak ground acceleration

    Flood Hazard

    United States Federal Emergency Management Administration. “National Flood Hazard Layer”. 1:10,000. “0.2 Percent Annual Flood Area”. < https://data.femadata.com/FIMA/Risk_MAP/NFHL/

    . Downloaded 07/2016.

    Classification

    The National Flood Hazard Layer 0.2 Percent Annual Flood Area was spatially intersected with the United States Counties layer, splitting flood areas by county and adding county information to flood areas. Flood area was aggregated by county, expressed as a fraction of the total county land area, and flood hazard was classified based upon percentage of land that is susceptible to flooding. National Flood Hazard Layer does not cover the entire United States; coverage is focused on populated areas. Areas not included in National Flood Hazard Layer were assigned flood risk of Low in order to include these areas in further analysis.

    Low = 0-.001% area susceptibleMedium = .00101 % - .005 % area susceptibleHigh = .00501+ % area susceptible

    Heat Wave Hazard

    United States Center for Disease Control and Prevention. “National Climate Assessment”. Contiguous United States Counties. “Extreme Heat Events: Heat Wave Days in May - September for years 1981-2010”. Downloaded 06/2016.

    Classification

    Heat wave was classified by dividing counties based upon the number of heat wave days they experienced over the 30 year time period described in the dataset.

    Low = 126 - 171 Heat wave DaysMedium = 172 – 187 Heat wave DaysHigh = 188 – 255 Heat wave Days

    Hurricane Hazard

    National Oceanic and Atmospheric Administration. Coastal Services Center. “Historical North Atlantic Tropical Cyclone Tracks, 1851-2004”. 1: 2,000,000. < https://catalog.data.gov/dataset/historical-north-atlantic-tropical-cyclone-tracks-1851-2004-direct-download

    . Downloaded 06/2016.

    National Oceanic and Atmospheric Administration. Coastal Services Center. “Historical North Pacific Tropical Cyclone Tracks, 1851-2004”. 1: 2,000,000. < https://catalog.data.gov/dataset/historical-north-atlantic-tropical-cyclone-tracks-1851-2004-direct-download

    . Downloaded 06/2016.

    Classification

    Atlantic and Pacific datasets were merged. Tropical storm and disturbance tracks were filtered out leaving hurricane tracks. Each hurricane track was assigned the value of the category number that describes that event. Weighting each event by intensity ensures that areas with higher intensity events are characterized as being more hazardous. Values describing each hurricane event were aggregated by United States County, normalized by total county area, and the hurricane hazard of counties was classified based upon the normalized value.

    Landslide Hazard

    United States Geological Survey. “Landslide Overview Map of the United States”. 1:4,000,000. “Landslide Incidence and Susceptibility in the Conterminous United States”. < https://catalog.data.gov/dataset/landslide-incidence-and-susceptibility-in-the-conterminous-united-states-direct-download

    . Downloaded 07/2016.

    Classification

    The classifications of High, Moderate, and Low landslide susceptibility and incidence from the study were numerically coded, the average value was computed for each county, and the landslide hazard was classified based upon the average value.

    Long-Term Drought Hazard

    United States Drought Monitor, Drought Mitigation Center, United States Department of Agriculture, National Oceanic and Atmospheric Administration. “Drought Monitor Summary Map”. “Long-Term Drought Impact”. < http://droughtmonitor.unl.edu/MapsAndData/GISData.aspx >. Downloaded 06/2016.

    Classification

    Short-term drought areas were filtered from the data; leaving only long-term drought areas. United States Counties were assigned the average U.S. Drought Monitor Classification Scheme Drought Severity Classification value that characterizes the county area. County long-term drought hazard was classified based upon average Drought Severity Classification value.

    Low = 1 – 1.75 average Drought Severity Classification valueMedium = 1.76 -3.0 average Drought Severity Classification valueHigh = 3.0+ average Drought Severity Classification value

    Snowfall Hazard

    United States National Oceanic and Atmospheric Administration. “1981-2010 U.S. Climate Normals”. 1: 2,000,000. “Annual Snow Normal”. < http://www1.ncdc.noaa.gov/pub/data/normals/1981-2010/products/precipitation/

    . Downloaded 08/2016.

    Classification

    Average yearly snowfall was joined with point location of weather measurement stations, and stations without valid snowfall measurements were filtered out (leaving 6233 stations). Snowfall was interpolated using least squared distance interpolation to create a .05 degree raster describing an estimate of yearly snowfall for the United States. The average yearly snowfall raster was aggregated by county to yield the average yearly snowfall per United States County. The snowfall risk of counties was classified by average snowfall.

    None = 0 inchesLow = .01- 10 inchesMedium = 10.01- 50 inchesHigh = 50.01+ inches

    Tornado Hazard

    United States National Oceanic and Atmospheric Administration Storm Prediction Center. “Severe Thunderstorm Database and Storm Data Publication”. 1: 2,000,000. “United States Tornado Touchdown Points 1950-2004”. < https://catalog.data.gov/dataset/united-states-tornado-touchdown-points-1950-2004-direct-download

    . Downloaded 07/2016.

    Classification

    Each tornado touchdown point was assigned the value of the Fujita Scale that describes that event. Weighting each event by intensity ensures that areas with higher intensity events are characterized as more hazardous. Values describing each tornado event were aggregated by United States County, normalized by total county area, and the tornado hazard of counties was classified based upon the normalized value.

    Volcano Hazard

    Smithsonian Institution National Volcanism Program. “Volcanoes of the World”. “Holocene Volcanoes”. < http://volcano.si.edu/search_volcano.cfm

    . Downloaded 07/2016.

    Classification

    Volcano coordinate locations from spreadsheet were mapped and aggregated by United States County. Volcano count was normalized by county area, and the volcano hazard of counties was classified based upon the number of volcanoes present per unit area.

    None = 0 volcanoes/100 kilometersLow = 0.000915 - 0.007611 volcanoes / 100 kilometersMedium = 0.007612 - 0.018376 volcanoes / 100 kilometersHigh = 0.018377- 0.150538 volcanoes / 100 kilometers

    Wildfire Hazard

    United States Department of Agriculture, Forest Service, Fire, Fuel, and Smoke Science Program. “Classified 2014 Wildfire Hazard Potential”. 270 meters. < http://www.firelab.org/document/classified-2014-whp-gis-data-and-maps

    . Downloaded 06/2016.

    Classification

    The classifications of Very High, High, Moderate, Low, Very Low, and Non-Burnable/Water wildfire hazard from the study were numerically coded, the average value was computed for each county, and the wildfire hazard was classified based upon the average value.

  12. County

    • resilience-fema.hub.arcgis.com
    Updated Jul 6, 2021
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    FEMA AGOL (2021). County [Dataset]. https://resilience-fema.hub.arcgis.com/datasets/county-62
    Explore at:
    Dataset updated
    Jul 6, 2021
    Dataset provided by
    Federal Emergency Management Agencyhttp://www.fema.gov/
    Authors
    FEMA AGOL
    Area covered
    Description

    National Risk Index Version: March 2023 (1.19.0)A Tornado is a narrow, violently rotating column of air that extends from the base of a thunderstorm to the ground and is visible only if it forms a condensation funnel made up of water droplets, dust and debris. Annualized frequency values for Tornadoes are in units of events per year.The National Risk Index is a dataset and online tool that helps to illustrate the communities most at risk for 18 natural hazards across the United States and territories: Avalanche, Coastal Flooding, Cold Wave, Drought, Earthquake, Hail, Heat Wave, Hurricane, Ice Storm, Landslide, Lightning, Riverine Flooding, Strong Wind, Tornado, Tsunami, Volcanic Activity, Wildfire, and Winter Weather. The National Risk Index provides Risk Index values, scores and ratings based on data for Expected Annual Loss due to natural hazards, Social Vulnerability, and Community Resilience. Separate values, scores and ratings are also provided for Expected Annual Loss, Social Vulnerability, and Community Resilience. For the Risk Index and Expected Annual Loss, values, scores and ratings can be viewed as a composite score for all hazards or individually for each of the 18 hazard types.Sources for Expected Annual Loss data include: Alaska Department of Natural Resources, Arizona State University’s (ASU) Center for Emergency Management and Homeland Security (CEMHS), California Department of Conservation, California Office of Emergency Services California Geological Survey, Colorado Avalanche Information Center, CoreLogic’s Flood Services, Federal Emergency Management Agency (FEMA) National Flood Insurance Program, Humanitarian Data Exchange (HDX), Iowa State University's Iowa Environmental Mesonet, Multi-Resolution Land Characteristics (MLRC) Consortium, National Aeronautics and Space Administration’s (NASA) Cooperative Open Online Landslide Repository (COOLR), National Earthquake Hazards Reduction Program (NEHRP), National Oceanic and Atmospheric Administration’s National Centers for Environmental Information (NCEI), National Oceanic and Atmospheric Administration's National Hurricane Center, National Oceanic and Atmospheric Administration's National Weather Service (NWS), National Oceanic and Atmospheric Administration's Office for Coastal Management, National Oceanic and Atmospheric Administration's National Geophysical Data Center, National Oceanic and Atmospheric Administration's Storm Prediction Center, Oregon Department of Geology and Mineral Industries, Pacific Islands Ocean Observing System, Puerto Rico Seismic Network, Smithsonian Institution's Global Volcanism Program, State of Hawaii’s Office of Planning’s Statewide GIS Program, U.S. Army Corps of Engineers’ Cold Regions Research and Engineering Laboratory (CRREL), U.S. Census Bureau, U.S. Department of Agriculture's (USDA) National Agricultural Statistics Service (NASS), U.S. Forest Service's Fire Modeling Institute's Missoula Fire Sciences Lab, U.S. Forest Service's National Avalanche Center (NAC), U.S. Geological Survey (USGS), U.S. Geological Survey's Landslide Hazards Program, United Nations Office for Disaster Risk Reduction (UNDRR), University of Alaska – Fairbanks' Alaska Earthquake Center, University of Nebraska-Lincoln's National Drought Mitigation Center (NDMC), University of Southern California's Tsunami Research Center, and Washington State Department of Natural Resources.Data for Social Vulnerability are provided by the Centers for Disease Control (CDC) Agency for Toxic Substances and Disease Registry (ATSDR) Social Vulnerability Index, and data for Community Resilience are provided by University of South Carolina's Hazards and Vulnerability Research Institute’s (HVRI) 2020 Baseline Resilience Indicators for Communities.The source of the boundaries for counties and Census tracts are based on the U.S. Census Bureau’s 2021 TIGER/Line shapefiles. Building value and population exposures for communities are based on FEMA’s Hazus 6.0. Agriculture values are based on the USDA 2017 Census of Agriculture.

  13. True Color Imagery (Planet) for the Southeast US Severe Storms January 2024

    • hub.arcgis.com
    Updated Jan 11, 2024
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    NASA ArcGIS Online (2024). True Color Imagery (Planet) for the Southeast US Severe Storms January 2024 [Dataset]. https://hub.arcgis.com/datasets/70a3d70d1fe84512b193bd29dbaa46b7
    Explore at:
    Dataset updated
    Jan 11, 2024
    Dataset provided by
    Authors
    NASA ArcGIS Online
    Area covered
    Description

    Date of Images:1/10/2024Date of Next Image:UnknownSummary:This PlanetScope imagery captured by Planet Labs Inc. on January 10, 2024 shows the post-event conditions after the Southeast United States severe storms.The true Color RGB provides a product of how the surface would look to the naked eye from space. The True Color RGB is produced using the 3 visible wavelength bands (red, green, and blue) from the respective sensor. Some minor atmospheric corrections have occurred.Suggested Use:True Color RGB provides a product of how the surface would look to the naked eye from space. The True Color RGB is produced using the 3 visible wavelength bands (red, green, and blue) from the respective sensor. Some minor atmospheric corrections have occurred.Satellite/Sensor:PlanetScopeResolution:3 metersCredits:NASA Disasters Program, Includes copyrighted material of Planet Labs PBC. All rights reserved.Esri REST Endpoint:See URL section on right side of pageWMS Endpoint:https://maps.disasters.nasa.gov/ags03/services/se_us_severestorms_202401/planet_truecolor_20240110/ImageServer/WMSServer

  14. a

    ARIA Damage Proxy Map (Copernicus Sentinel-1) on 12/16/2021 for the December...

    • disaster-amerigeoss.opendata.arcgis.com
    • hub.arcgis.com
    Updated Apr 15, 2022
    + more versions
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    NASA ArcGIS Online (2022). ARIA Damage Proxy Map (Copernicus Sentinel-1) on 12/16/2021 for the December 10-11, 2021 Tornado Outbreak [Dataset]. https://disaster-amerigeoss.opendata.arcgis.com/datasets/NASA::aria-damage-proxy-map-copernicus-sentinel-1-on-12-16-2021-for-the-december-10-11-2021-tornado-outbreak
    Explore at:
    Dataset updated
    Apr 15, 2022
    Dataset authored and provided by
    NASA ArcGIS Online
    Area covered
    Description

    Date of Image:12/16/2021Date of Next Image:UnknownSummary:The Advanced Rapid Imaging and Analysis (ARIA) team at NASA's Jet Propulsion Laboratory and California Institute of Technology in Southern California created this Damage Proxy Map (DPM) depicting areas that are likely damaged by the Tornadoes (December 10, 2021) in Kentucky state, US. The map was derived from synthetic aperture radar (SAR) images on Dec 11, 2021 by the Copernicus Sentinel-1 satellites operated by the European Space Agency (ESA). The pre-event images were taken from June 26, 2021 to Nov 17, 2021. Preliminary validation was done by comparing with the Media reports and drone images.Suggested Use:The color variation from yellow to red indicates increasingly more significant surface change.This damage proxy map should be used as guidance to identify damaged areas, and may be less reliable over vegetated. For example, the scattered colored pixels over vegetated areas may be false positives, and the lack of colored pixels over vegetated areas does not necessarily mean no damage. This map is most sensitive to building damage, but small-scale change or partial structural damage may not be detected by this map.Satellite/Sensor:Copernicus Sentinel-1 Synthetic Aperture Radar (SAR)Resolution:30 metersCredits:Sentinel-1 data were accessed through the Copernicus Open Hub and the Alaska Satellite Facility server. The product contains modified Copernicus Sentinel data (2021), processed by ESA and analyzed by the NASA-JPL/Caltech ARIA team. Part of the funding was provided by NASA's Earth Applied Sciences Disasters Program.For more information about ARIA, visit: http://aria.jpl.nasa.govEsri REST Endpoint:See URL section on right side of pageWMS Endpoint:https://maps.disasters.nasa.gov/ags04/services/tornado_outbreak_20211210/aria_dpm_sentinel1_20211216/ImageServer/WMSServerData Download:https://aria-share.jpl.nasa.gov/20211210-Tornados_AR_KY/DPM/

  15. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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WxExplorer (2020). United States tornado data [Dataset]. https://www.kaggle.com/datasets/wxexplorer/yearly-united-states-tornado-data-per-state
Organization logo

United States tornado data

Tornadic data for each year for each U.S. states from 1951 to 2019.

Explore at:
29 scholarly articles cite this dataset (View in Google Scholar)
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Sep 17, 2020
Dataset provided by
Kagglehttp://kaggle.com/
Authors
WxExplorer
License

https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

Area covered
United States
Description

Context

This data set contains the number of confirmed tornadoes for each state for each year and their responding affects.

Content

Current table includes number of confirmed tornadoes in each state for each year from 1951 to 2019. Future datasets will be related to Fujita/Enhanced Fujita rank, total damage (reported and inflation corrected), and fatalities/injuries. Data is from National Centers for Environmental Information's Storm Events Database.

Inspiration

I am curious about the trend of sever weather occurring in the United States over time. This started with tornadic events but will evolve to severe thunderstorm and hail events as well.

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