60 datasets found
  1. National Weather Service Precipitation Forecast

    • disasterpartners.org
    • atlas.eia.gov
    • +18more
    Updated Aug 16, 2022
    + more versions
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    Esri (2022). National Weather Service Precipitation Forecast [Dataset]. https://www.disasterpartners.org/maps/f9e9283b9c9741d09aad633f68758bf6
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    Dataset updated
    Aug 16, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This map displays the Quantitative Precipitation Forecast (QPF) for the next 72 hours across the contiguous United States. Data are updated hourly from the National Digital Forecast Database produced by the National Weather Service.The dataset includes incremental and cumulative precipitation data in 6-hour intervals. In the ArcGIS Online map viewer you can enable the time animation feature and select either the "Amount by Time" (incremental) layer or the "Accumulation by Time" (cumulative) layer to view a 72-hour animation of forecast precipitation. All times are reported according to your local time zone.Where is the data coming from?The National Digital Forecast Database (NDFD) was designed to provide access to weather forecasts in digital form from a central location. The NDFD produces forecast data of sensible weather elements. NDFD contains a seamless mosaic of digital forecasts from National Weather Service (NWS) field offices working in collaboration with the National Centers for Environmental Prediction (NCEP). All of these organizations are under the administration of the National Oceanic and Atmospheric Administration (NOAA).Source: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.qpf.binWhere can I find other NDFD data?The Source data is downloaded and parsed using the Aggregated Live Feeds methodology to return information that can be served through ArcGIS Server as a map service or used to update Hosted Feature Services in Online or Enterprise.What can you do with this layer?This map service is suitable for data discovery and visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the time-enabled data using the time slider by Enabling Time Animation.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

  2. National Weather Service Snowfall Forecast

    • geospatial-nws-noaa.opendata.arcgis.com
    • prep-response-portal.napsgfoundation.org
    • +6more
    Updated Jun 7, 2019
    + more versions
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    Esri (2019). National Weather Service Snowfall Forecast [Dataset]. https://geospatial-nws-noaa.opendata.arcgis.com/datasets/esri2::national-weather-service-snowfall-forecast
    Explore at:
    Dataset updated
    Jun 7, 2019
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This map displays the expected total accumulation of new snow over the next 72 hours across the contiguous United States. Data are updated hourly from the National Digital Forecast Database produced by the National Weather Service.The dataset includes incremental and cumulative snowfall data in 6-hour intervals. In the ArcGIS Online map viewer you can enable the time animation feature and select either the amount by time (incremental) or accumulation by time (cumulative) layers to view a 72-hour animation of forecast precipitation. All times are reported according to your local time zone.Where is the data coming from?The National Digital Forecast Database (NDFD) was designed to provide access to weather forecasts in digital form from a central location. The NDFD produces gridded forecasts of sensible weather elements. NDFD contains a seamless mosaic of digital forecasts from National Weather Service (NWS) field offices working in collaboration with the National Centers for Environmental Prediction (NCEP). All of these organizations are under the administration of the National Oceanic and Atmospheric Administration (NOAA).Source: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.snow.binWhere can I find other NDFD data?The Source data is downloaded and parsed using the Aggregated Live Feeds methodology to return information that can be served through ArcGIS Server as a map service or used to update Hosted Feature Services in Online or Enterprise.What can you do with this layer?This map service is suitable for data discovery and visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the time-enabled data using the time slider by Enabling Time Animation.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

  3. National Weather Service 3-Day Min/Max Temperature Forecast

    • heat.gov
    • resilience.climate.gov
    • +9more
    Updated Aug 16, 2022
    + more versions
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    Esri (2022). National Weather Service 3-Day Min/Max Temperature Forecast [Dataset]. https://www.heat.gov/maps/0ae7cf18df0a4b4d9e7eea665f00500d
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    Dataset updated
    Aug 16, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Pacific Ocean, North Pacific Ocean, Proliv Longa, Proliv Longa, Arctic Ocean, Bering Sea
    Description

    This map displays the minimum and maximum air temperature forecast over the next 3 days across the Contiguous United States, Alaska, Guam, Hawaii, and Puerto Rico in daily increments. Minimum temperatures are typically at night, while maximum temperatures are typically afternoon. The original raster data has been processed into 1-degree contours and both Layers include a Time Series set to a 24-hour time interval.The minimum and maximum temperatures are the forecasted ambient air temperature in °F.See sister data product for Apparent and Expected Hourly TemperaturesRevisionsApr 21, 2022: Added Forecast Period Number 'Interval' field for an alternate query method to the Timeline of data.Apr 22, 2022: Set 'Min Temperature' layer visibility to False by default, so only Max temperature is visible when initially viewed.Sep 1, 2022: Updated renderer Arcade logic on layers to correctly symbolize on values greater than 120 and less than -60 degrees.DetailService Data update interval is: HourlyWhere is the data coming from?The National Digital Forecast Database (NDFD) was designed to provide access to weather forecasts in digital form from a central location. The NDFD produces gridded forecasts of sensible weather elements. NDFD contains a seamless mosaic of digital forecasts from National Weather Service (NWS) field offices working in collaboration with the National Centers for Environmental Prediction (NCEP). All of these organizations are under the administration of the National Oceanic and Atmospheric Administration (NOAA).Overnight Minimum Temperature Source:CONUS: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.mint.binALASKA: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.alaska/VP.001-003/ds.mint.binHAWAII: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.hawaii/VP.001-003/ds.mint.binGUAM: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.guam/VP.001-003/ds.mint.binPUERTO RICO: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.puertori/VP.001-003/ds.mint.binDaytime Maximum Temperature Source:CONUS: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.maxt.binALASKA: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.alaska/VP.001-003/ds.maxt.binHAWAII: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.hawaii/VP.001-003/ds.maxt.binGUAM: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.guam/VP.001-003/ds.maxt.binPUERTO RICO: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.puertori/VP.001-003/ds.maxt.binWhere can I find other NDFD data?The Source data is downloaded and parsed using the Aggregated Live Feeds methodology to return information that can be served through ArcGIS Server as a map service or used to update Hosted Feature Services in Online or Enterprise.What can you do with this layer?This feature service is suitable for data discovery and visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the time-enabled data using the time slider by Enabling Time Animation.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page.

  4. Open data

    • ecmwf.int
    application/x-grib
    Updated Nov 3, 2024
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    European Centre for Medium-Range Weather Forecasts (2024). Open data [Dataset]. https://www.ecmwf.int/en/forecasts/datasets/open-data
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    application/x-grib(1 datasets)Available download formats
    Dataset updated
    Nov 3, 2024
    Dataset authored and provided by
    European Centre for Medium-Range Weather Forecastshttp://ecmwf.int/
    License

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

    Description

    subject to appropriate attribution.

  5. National Weather Service Smoke Forecast

    • resilience.climate.gov
    • disasterpartners.org
    • +14more
    Updated Aug 16, 2022
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    Esri (2022). National Weather Service Smoke Forecast [Dataset]. https://resilience.climate.gov/maps/a98fd08751a5480c898b7cebe38807f4
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    Dataset updated
    Aug 16, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    This map displays projected visible surface smoke across the contiguous United States for the next 48 hours in 1 hour increments. It is updated every 24 hours by NWS. Concentrations are reported in micrograms per cubic meter.Where is the data coming from?The National Digital Guidance Database (NDGD) is a sister to the National Digital Forecast Database (NDFD). Information in NDGD may be used by NWS forecasters as guidance in preparing official NWS forecasts in NDFD. The experimental/guidance NDGD data is not an official NWS forecast product.Source: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndgd/GT.aq/AR.conus/ds.smokes01.binSource data archive can be found here: https://www.ncei.noaa.gov/products/weather-climate-models/national-digital-guidance-database look for 'LXQ...' files by date. These are the Binary GRIB2 files that can be decoded via DeGRIB tool.Where can I find other NDGD data?The Source data is downloaded and parsed using the Aggregated Live Feeds methodology to return information that can be served through ArcGIS Server as a map service or used to update Hosted Feature Services in Online or Enterprise.What can you do with this layer?This map service is suitable for data discovery and visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the time-enabled data using the time slider by Enabling Time Animation.RevisionsJuly 11, 2022: Feed updated to leverage forecast model change by NOAA, whereby the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) forecast model system was replaced with the Rapid Refresh (RAP) forecast model system. Key differences: higher accuracy with RAP now concentrated at 0-8 meter detail vs HYSPLIT at 0-100 meter; earlier data delivery by 6 hrs; forecast output extended to 51 hrs.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

  6. National Weather Service Ice Accumulation Forecast

    • geospatial-nws-noaa.opendata.arcgis.com
    • prep-response-portal.napsgfoundation.org
    • +4more
    Updated Jun 7, 2019
    + more versions
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    Esri (2019). National Weather Service Ice Accumulation Forecast [Dataset]. https://geospatial-nws-noaa.opendata.arcgis.com/maps/esri2::national-weather-service-ice-accumulation-forecast
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    Dataset updated
    Jun 7, 2019
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Ross Sea, South Pacific Ocean, Pacific Ocean, North Pacific Ocean, Proliv Longa, Proliv Longa, Arctic Ocean, Bering Sea
    Description

    This map displays the predicted ice accumulation for the next 72 hours across the contiguous United States. Data are updated hourly from the National Digital Forecast Database (NDFD) produced by the National Weather Service. The dataset includes incremental and cumulative precipitation data in 6-hour intervals. In the ArcGIS Online map viewer you can enable the time animation feature and select either the "Amount by Time" (incremental) layer or the "Accumulation by Time" (cumulative) layer to view a 72-hour animation of forecast precipitation. All times are reported according to your local time zone.Where is the data coming from?The National Digital Forecast Database (NDFD) was designed to provide access to weather forecasts in digital form from a central location. The NDFD produces forecast data of sensible weather elements. NDFD contains a seamless mosaic of digital forecasts from National Weather Service (NWS) field offices working in collaboration with the National Centers for Environmental Prediction (NCEP). All of these organizations are under the administration of the National Oceanic and Atmospheric Administration (NOAA).Source: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.iceaccum.binWhere can I find other NDFD data?The Source data is downloaded and parsed using the Aggregated Live Feeds methodology to return information that can be served through ArcGIS Server as a map service or used to update Hosted Feature Services in Online or Enterprise.What can you do with this layer?This map service is suitable for data discovery and visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the time-enabled data using the time slider by Enabling Time Animation.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

  7. Atmospheric Model high resolution 15-day forecast

    • ecmwf.int
    application/x-grib
    Updated Sep 20, 2016
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    European Centre for Medium-Range Weather Forecasts (2016). Atmospheric Model high resolution 15-day forecast [Dataset]. https://www.ecmwf.int/en/forecasts/datasets/set-i
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    application/x-grib(1 datasets)Available download formats
    Dataset updated
    Sep 20, 2016
    Dataset authored and provided by
    European Centre for Medium-Range Weather Forecastshttp://ecmwf.int/
    License

    https://www.ecmwf.int/sites/default/files/ECMWF_Standard_Licence.pdfhttps://www.ecmwf.int/sites/default/files/ECMWF_Standard_Licence.pdf

    Description

    Single prediction that uses

    observations
    prior information about the Earth-system
    ECMWF's highest-resolution model
    

    HRES Direct model output Products offers "High Frequency products"

    4 forecast runs per day (00/06/12/18) (see dissemination schedule for details)
    Hourly steps to step 144 for all four runs
    

    Not all post-processed Products are available at 06/18 runs or in hourly steps.

  8. Rainfall data from 172 weather stations in Vietnam

    • data.amerigeoss.org
    • data.subak.org
    • +3more
    pdf, xls, zip
    Updated Jul 24, 2024
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    World Bank (2024). Rainfall data from 172 weather stations in Vietnam [Dataset]. https://data.amerigeoss.org/fi/dataset/wps5491-rainfall-data-172-weather-stations-vietnam
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    pdf, zip, xlsAvailable download formats
    Dataset updated
    Jul 24, 2024
    Dataset provided by
    World Bankhttp://worldbank.org/
    License

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

    Area covered
    Vietnam
    Description

    The rainfall data are obtained from Vietnam's HydroMeteorological Data Center, and cover daily observations from 172 weather stations. Most of them were actively operated through out the period 1975-2006. The list of weather stations with GIS coordinates is also provided.

  9. National Weather Service 72 Hour Temperature Forecast

    • resilience-fema.hub.arcgis.com
    • heat.gov
    • +3more
    Updated Aug 16, 2022
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    Esri (2022). National Weather Service 72 Hour Temperature Forecast [Dataset]. https://resilience-fema.hub.arcgis.com/maps/1c8e963bc94c4026bc67488e954d1cb7
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    Dataset updated
    Aug 16, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Pacific Ocean, North Pacific Ocean
    Description

    This map displays the Apparent and Expected Air Temperature forecast over the next 72 hours across the Contiguous United States, Alaska, Guam, Hawaii, and Puerto Rico in 3 hour increments. The original raster data has been processed into 1-degree contours.Two layers are included: apparent and expected temperature, both include a Time Series set to a 3-hour time interval. The apparent temperature is the perceived (or feels like) temperature derived from either a combination of temperature and wind (wind chill) or temperature and humidity (heat index) for the indicated hour. When the temperature at a particular grid point falls to 50 °F or less, wind chill will be used for that point for the apparent temperature. When the temperature at a grid point rises above 80 °F, the heat index will be used for apparent temperature.
    Between 51 and 80 °F, the apparent temperature will be the ambient air temperature.The expected temperature is the forecasted ambient air temperature in °F.See sister data product for Min and Max Daily TemperaturesRevisionsApr 21, 2022: Added Forecast Period Number 'Interval' field for an alternate query method to the Timeline of data. Disabled Time Series by default to improve initial Map Viewer exprience and added a Filter for 'interval = 1' to display initial forecast time data (current time period).Apr 22, 2022: Set 'Apparent Temperature' layer visibility to True by default, so content is visible when initially viewed.Sep 1, 2022: Updated renderer Arcade logic on layers to correctly symbolize on values greater than 120 and less than -60 degrees.DetailService Data update interval is: HourlyWhere is the data coming from?The National Digital Forecast Database (NDFD) was designed to provide access to weather forecasts in digital form from a central location. The NDFD produces gridded forecasts of sensible weather elements. NDFD contains a seamless mosaic of digital forecasts from National Weather Service (NWS) field offices working in collaboration with the National Centers for Environmental Prediction (NCEP). All of these organizations are under the administration of the National Oceanic and Atmospheric Administration (NOAA).Apparent Temperature Source:CONUS: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.apt.binALASKA: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.alaska/VP.001-003/ds.apt.binHAWAII: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.hawaii/VP.001-003/ds.apt.binGUAM: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.guam/VP.001-003/ds.apt.binPUERTO RICO: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.puertori/VP.001-003/ds.apt.binExpected Temperature Source:CONUS: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.temp.binALASKA: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.alaska/VP.001-003/ds.temp.binHAWAII: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.hawaii/VP.001-003/ds.temp.binGUAM: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.guam/VP.001-003/ds.temp.binPUERTO RICO: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.puertori/VP.001-003/ds.temp.binWhere can I find other NDFD data?The Source data is downloaded and parsed using the Aggregated Live Feeds methodology to return information that can be served through ArcGIS Server as a map service or used to update Hosted Feature Services in Online or Enterprise.What can you do with this layer?This feature service is suitable for data discovery and visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the time-enabled data using the time slider by Enabling Time Animation or add a Filter using the 'Forecast Period Number'.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page.

  10. ECMWF Reanalysis v5

    • ecmwf.int
    application/x-grib
    Updated Dec 31, 1969
    + more versions
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    European Centre for Medium-Range Weather Forecasts (1969). ECMWF Reanalysis v5 [Dataset]. https://www.ecmwf.int/en/forecasts/dataset/ecmwf-reanalysis-v5
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    application/x-grib(1 datasets)Available download formats
    Dataset updated
    Dec 31, 1969
    Dataset authored and provided by
    European Centre for Medium-Range Weather Forecastshttp://ecmwf.int/
    License

    http://apps.ecmwf.int/datasets/licences/copernicushttp://apps.ecmwf.int/datasets/licences/copernicus

    Description

    land and oceanic climate variables. The data cover the Earth on a 31km grid and resolve the atmosphere using 137 levels from the surface up to a height of 80km. ERA5 includes information about uncertainties for all variables at reduced spatial and temporal resolutions.

  11. Severe Weather Web Map

    • national-government.esrij.com
    • disasters.amerigeoss.org
    • +2more
    Updated Jun 18, 2012
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    Esri’s Disaster Response Program (2012). Severe Weather Web Map [Dataset]. https://national-government.esrij.com/maps/d16d53126f1243a3a7a7f1d0dff39662
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    Dataset updated
    Jun 18, 2012
    Dataset provided by
    Esrihttp://esri.com/
    Authors
    Esri’s Disaster Response Program
    Area covered
    Description

    This map is intended to provide general awareness of severe weather. It is not intended to replace authoritative government websites but rather to provide situational awareness. This map can be used as a template for agencies wanting to add their own custom data.This map contains layers from Esri's Living Atlas of the World including Storm Reports, Short-Term Weather Warnings, Weather Watches and Warnings, and Snowfall Forecast. Click on the title of the layers below for more information about each layer and it's source as well as update frequency. Weather Radar Data courtesy of DTN, for more info click here.This map is provided by the Esri Disaster Response Program. For other severe weather related content and data, please visit the DRP Hub Severe Weather Page.

  12. USA Short-Term Weather Warnings

    • prep-response-portal.napsgfoundation.org
    • geodata.colorado.gov
    • +11more
    Updated Jun 11, 2019
    + more versions
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    Esri (2019). USA Short-Term Weather Warnings [Dataset]. https://prep-response-portal.napsgfoundation.org/maps/bba3d0a070d34cea9a303c24a71d5190
    Explore at:
    Dataset updated
    Jun 11, 2019
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Description

    The National Weather Service issues warnings for severe weather that are imminent or actively occurring. This layer shows shorter-term warnings for the following events:Special Marine Warnings - potentially hazardous weather conditions of short duration (up to 2 hours) that may include sustained winds or gusts of 39 mph or greater, hail 0.75” or greater in diameter, or waterspouts.Severe Thunderstorm Warnings - storms with winds of 58 mph or higher or hail 1” or greater in diameter.Tornado Warnings - imminent or active tornados.Extreme Wind Warnings - surface winds of 115 mph or greater associated with non-convective, downslope, derecho, or sustained hurricane winds are expected to occur within one hour.Flash Flood Warnings - conditions are favorable for flash flooding. It does not mean that flash flooding will occur, but it is possible.SourceCurrent Warnings: https://www.weather.gov/source/crh/shapefiles/CurrentWarnings.tar.gzSample DataSee Sample Layer Item for sample data during Weather inactivity!Update FrequencyThe service is updated every 5 minutes using the Aggregated Live Feeds methodology.Area CoveredContiguous United StatesWhat can you do with this layer?Customize the display of each attribute by using the Change Style option for any layer.Query the layer to display only specific types of weather watches and warnings.Add to a map with other weather data layers to provide inside on hazardous weather events.Use ArcGIS Online analysis tools, such as Enrich Data, to determine the potential impact of weather events on populations.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

  13. Temperature and precipitation gridded data for global and regional domains...

    • cds.climate.copernicus.eu
    netcdf
    Updated Mar 9, 2025
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    ECMWF (2025). Temperature and precipitation gridded data for global and regional domains derived from in-situ and satellite observations [Dataset]. http://doi.org/10.24381/cds.11dedf0c
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    netcdfAvailable download formats
    Dataset updated
    Mar 9, 2025
    Dataset provided by
    European Centre for Medium-Range Weather Forecastshttp://ecmwf.int/
    Authors
    ECMWF
    License

    https://object-store.os-api.cci2.ecmwf.int:443/cci2-prod-catalogue/licences/insitu-gridded-observations-global-and-regional/insitu-gridded-observations-global-and-regional_15437b363f02bf5e6f41fc2995e3d19a590eb4daff5a7ce67d1ef6c269d81d68.pdfhttps://object-store.os-api.cci2.ecmwf.int:443/cci2-prod-catalogue/licences/insitu-gridded-observations-global-and-regional/insitu-gridded-observations-global-and-regional_15437b363f02bf5e6f41fc2995e3d19a590eb4daff5a7ce67d1ef6c269d81d68.pdf

    Time period covered
    Jan 1, 1750 - Mar 1, 2021
    Description

    This dataset provides high-resolution gridded temperature and precipitation observations from a selection of sources. Additionally the dataset contains daily global average near-surface temperature anomalies. All fields are defined on either daily or monthly frequency. The datasets are regularly updated to incorporate recent observations. The included data sources are commonly known as GISTEMP, Berkeley Earth, CPC and CPC-CONUS, CHIRPS, IMERG, CMORPH, GPCC and CRU, where the abbreviations are explained below. These data have been constructed from high-quality analyses of meteorological station series and rain gauges around the world, and as such provide a reliable source for the analysis of weather extremes and climate trends. The regular update cycle makes these data suitable for a rapid study of recently occurred phenomena or events. The NASA Goddard Institute for Space Studies temperature analysis dataset (GISTEMP-v4) combines station data of the Global Historical Climatology Network (GHCN) with the Extended Reconstructed Sea Surface Temperature (ERSST) to construct a global temperature change estimate. The Berkeley Earth Foundation dataset (BERKEARTH) merges temperature records from 16 archives into a single coherent dataset. The NOAA Climate Prediction Center datasets (CPC and CPC-CONUS) define a suite of unified precipitation products with consistent quantity and improved quality by combining all information sources available at CPC and by taking advantage of the optimal interpolation (OI) objective analysis technique. The Climate Hazards Group InfraRed Precipitation with Station dataset (CHIRPS-v2) incorporates 0.05° resolution satellite imagery and in-situ station data to create gridded rainfall time series over the African continent, suitable for trend analysis and seasonal drought monitoring. The Integrated Multi-satellitE Retrievals dataset (IMERG) by NASA uses an algorithm to intercalibrate, merge, and interpolate “all'' satellite microwave precipitation estimates, together with microwave-calibrated infrared (IR) satellite estimates, precipitation gauge analyses, and potentially other precipitation estimators over the entire globe at fine time and space scales for the Tropical Rainfall Measuring Mission (TRMM) and its successor, Global Precipitation Measurement (GPM) satellite-based precipitation products. The Climate Prediction Center morphing technique dataset (CMORPH) by NOAA has been created using precipitation estimates that have been derived from low orbiter satellite microwave observations exclusively. Then, geostationary IR data are used as a means to transport the microwave-derived precipitation features during periods when microwave data are not available at a location. The Global Precipitation Climatology Centre dataset (GPCC) is a centennial product of monthly global land-surface precipitation based on the ~80,000 stations world-wide that feature record durations of 10 years or longer. The data coverage per month varies from ~6,000 (before 1900) to more than 50,000 stations. The Climatic Research Unit dataset (CRU v4) features an improved interpolation process, which delivers full traceability back to station measurements. The station measurements of temperature and precipitation are public, as well as the gridded dataset and national averages for each country. Cross-validation was performed at a station level, and the results have been published as a guide to the accuracy of the interpolation. This catalogue entry complements the E-OBS record in many aspects, as it intends to provide high-resolution gridded meteorological observations at a global rather than continental scale. These data may be suitable as a baseline for model comparisons or extreme event analysis in the CMIP5 and CMIP6 dataset.

  14. Datasets for African Center of Meteorological Application for Development

    • ecmwf.int
    Updated Apr 12, 2018
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    European Centre for Medium-Range Weather Forecasts (2018). Datasets for African Center of Meteorological Application for Development [Dataset]. https://www.ecmwf.int/en/forecasts/datasets/datasets-african-center-meteorological-application-development
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    application/x-grib;application/x-netcdf(1 datasets)Available download formats
    Dataset updated
    Apr 12, 2018
    Dataset authored and provided by
    European Centre for Medium-Range Weather Forecastshttp://ecmwf.int/
    Description

    These products are available to the African Center of Meteorological Application for Development (ACMAD) countries.

    Based on HRES
    

    The products outlined below are disseminated via EUMETCast

    Please refer to WMO Additional products for the equivalent products available on a global domain via the ECMWF's DCPC FTP server.

    Filenames follow the WMO standards The list of products that you see is based on your login credentials

  15. Luquillo Mountains meteorological and ceilometer data

    • agdatacommons.nal.usda.gov
    • catalog.data.gov
    • +4more
    bin
    Updated Jan 22, 2025
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    Grizelle González (2025). Luquillo Mountains meteorological and ceilometer data [Dataset]. http://doi.org/10.2737/RDS-2017-0023
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    binAvailable download formats
    Dataset updated
    Jan 22, 2025
    Dataset provided by
    U.S. Department of Agriculture Forest Servicehttp://fs.fed.us/
    Authors
    Grizelle González
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Sierra de Luquillo
    Description

    This data publication contains hourly laser ceilometer data from Sabana, and hourly meteorological data collected from two weather stations in Bisley and Sabana located on the Luquillo Experimental Forest (El Yunque National Forest) in Puerto Rico. Bisley and Sabana are two watersheds in the Luquillo Experimental Forest. The ceilometer data include: minimum cloud base level, first quartile cloud base level, mean cloud base level, and cover cloud from 2013-2016. Weather data include: total precipitation, mean temperature, mean relative humidity, mean sea level pressure, mean wind speed, and mean wind direction from 2000-2016 for the Bisley station, and 2013-2016 for the Sabana Station.The ceilometer data were collected to study the frequency of clouds immersing the relatively low-elevation Luquillo Mountains, and supporting the tropical montane cloud forests in these mountains. The weather data were collected to study the weather affecting the tropical montane cloud forest, and to compare weather patterns to cloud base altitude.

  16. CEOP Model Output : 3D Gridded ECMWF data

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    Tomas Kral, CEOP Model Output : 3D Gridded ECMWF data [Dataset]. https://search.diasjp.net/en/dataset/CEOP_Model_Grid_ECMWF
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    Dataset provided by
    European Centre for Medium-Range Weather Forecastshttp://ecmwf.int/
    Authors
    Tomas Kral
    Description

    Ten operational Numerical Weather Prediction (NWP) and two data assimilation centers are currently contributing analysis/assimilation and forecast model products from global and regional NWP suites, including both operational and reanalysis systems to this component of CEOP. The contributing centers include:

    BoM: Bureau of Meteorology CPTEC: Centro de Previsao de Tempo e Estudos Climaticos ECMWF: European Centre for Medium-Range Weather Forecasts ECPC: Experimental Climate Prediction Center EMC: EPSON Meteo Center (Centro EPSON Meteo) GLDAS: Global Land Data Assimilation System GMAO: NASA Global Modeling and Assimilation Office JMA: Japan Meteorological Agency MSC: Meteorological Service Canada NCEP: National Centers for Environmental Prediction NCMRWF: National Center for Medium Range Weather Forecasting UKMO: UK Met Office The Max-Planck Institute for Meteorology (MPIM) in coordination with the ICSU World Data Center for Climate (WDCC) in Hamburg, Germany was designated as the CEOP model output archive center. The WDCC is administered by the Model and Data Group (M&D) at MPIM and the German Climate Computing Center (DKRZ).

    To assist with the organization of this activity during the Coordinated Enhanced Observing Period ('CEOP'), a Model Output Management Document was drafted as a guide for the participating centers to use in setting up their processes for meeting their commitments to 'CEOP'. The Guidance Document addressed the two issues of (1) the model output variables requested by 'CEOP' and (2) the two types of requested model output, namely global gridded (in GRIB format) and site-specific Model Output Location Time Series (MOLTS) at each of the 'CEOP' Reference Sites.

    A new version of the Guidance Document will be compiled that clarifies what model output data will be generated by the NWP Centers and Groups contributing to the model output component of Coordinated Energy and Water Cycle Observations Project (CEOP) and how they will interface/transfer the data that will be handled and retained at the WDCC. The issues covered in the document will include: (1) global versus regional products; (2) desired assimilation output; Interval and length of free-running forecasts; (3) Operational versus reanalysis data; (4) the CEOP schedule/archive periods; (5) the number and locations of MOLTS sites; and (6) the homogenizing of the model output and metadata formats (i.e. standard parameters).

    Results up to this point in the CEOP model output generation effort make it clear that the transfer aspect of the data handling effort has been progressing well. Data from all twelve Centers participating in CEOP have been received at the data archive center and has either been placed into the database at the Hamburg facility, or is in the process of being entered into the database. The current data holdings in the MPIM archive can be viewed http://www.mad.zmaw.de/fileadmin/extern/wdc/ceop/Data_timeline_L_12.pdf.

  17. Data from: US States and Territories

    • disasterpartners.org
    • atlas.eia.gov
    • +17more
    Updated Aug 16, 2022
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    Esri (2022). US States and Territories [Dataset]. https://www.disasterpartners.org/datasets/esri2::us-states-and-territories
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    Dataset updated
    Aug 16, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Pacific Ocean, North Pacific Ocean, Proliv Longa, Proliv Longa, Arctic Ocean, South Pacific Ocean, Bering Sea
    Description

    Official NWS Advanced Weather Interactive Processing System (AWIPS) background US State and Territory designations.

    See: "http://www.nws.noaa.gov/geodata/index.html"

  18. Data from: Forecast Position

    • pacificgeoportal.com
    • prep-response-portal.napsgfoundation.org
    • +24more
    Updated Aug 16, 2022
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    Esri (2022). Forecast Position [Dataset]. https://www.pacificgeoportal.com/datasets/esri2::forecast-position
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    Dataset updated
    Aug 16, 2022
    Dataset authored and provided by
    Esrihttp://esri.com/
    Area covered
    Earth
    Description

    Forecast points represent the official NHC forecast locations of the center of a tropical cyclone.

  19. Thursday Island Automated Marine Weather And Oceanographic Station

    • geonetwork.apps.aims.gov.au
    • researchdata.edu.au
    Updated Oct 17, 2024
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    Australian Institute of Marine Science (AIMS) (2024). Thursday Island Automated Marine Weather And Oceanographic Station [Dataset]. https://geonetwork.apps.aims.gov.au/geonetwork/srv/api/records/911a0982-240e-4461-ac0c-107f6e59a355
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    www:link-1.0-http--downloaddata, www:link-1.0-http--linkAvailable download formats
    Dataset updated
    Oct 17, 2024
    Dataset provided by
    Australian Institute Of Marine Sciencehttp://www.aims.gov.au/
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    This dataset contains meteorological and sea temperature data from the weather station located on the channel marker on Madge Reef, located between Thursday Island and Horn Island in the Torres Strait, installed under the Tropical Ecosystems hub of the National Environmental Research Program (NERP) and supported by the Torres Strait Regional Authority (TSRA). These data are collected to support scientific research within the Tropical Ecosystems hub of the National Environmental Research Program (NERP - see: http://www.environment.gov.au/biodiversity/science/nerp/ ) Theme 1, Program 2.3 (Torres Strait).Data are made available on request to other researchers and to the public. This weather station is funded under the Tropical Ecosystems hub of the National Environmental Research Program (NERP) in conjunction with the Torres Strait Regional Authority (TSRA). The weather station is an AIMS Mk5 system consisting of a Vaisala WXT520 weather station, a LiCor 192 Light Sensor and a number of in-water sensors including a SeaBird SBE37 CTD (Conductivity, Temperature and Depth) and SeaBird SBE39 (Temperature and Depth).Data recorded: Water Temperature (3m, 6.4 at MSL), Barometric Pressure, Air Temperature, Humidity, Solar Radiation (PAR), Wind Direction True (vector averaged), Wind Speed True (30 min average).The weather stations collect and store data in electronic memory every ten minutes, the station uses the 3G phone network to send the data to AIMS where it is stored in a database and then made available via the web and other systems. The data are then checked for accuracy using a number of range and historical checks, longer term summeries are then calculated along with indicies of potential thermal stress.

  20. Daily weather summaries (temperature, precipitation and wind) for station...

    • search.dataone.org
    • portal.edirepository.org
    Updated Apr 4, 2019
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    NOAA National Climatic Data Center (2019). Daily weather summaries (temperature, precipitation and wind) for station SAN DIEGO LINDBERGH FIELD, CA US (GHCND:USW00023188), obtained from NOAA National Climatic Data Center and re-published through CCE LTER data system for community use as regionally relevant data, 1939 - Apr 2017. [Dataset]. https://search.dataone.org/view/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fknb-lter-cce%2F13%2F7
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    Dataset updated
    Apr 4, 2019
    Dataset provided by
    Long Term Ecological Research Networkhttp://www.lternet.edu/
    Authors
    NOAA National Climatic Data Center
    Time period covered
    Jan 1, 1939 - Jan 1, 2017
    Area covered
    United States, San Diego
    Variables measured
    Date, Avg Temp, Max Temp, Min Temp, Precipitation, Max Temp M Flag, Max Temp Q Flag, Max Temp S Flag, Min Temp M Flag, Min Temp Q Flag, and 8 more
    Description

    Data provided here are obtained from the Global Historical Climatology Network - Daily (GHCN-Daily) database, provided by NOAA National Centers for Environmental Information (formerly NCDC). Data are periodically downloaded by CCE LTER Information Management and imported into the local data system for use by the local scientific community as regionally relevant data. The data contained in this dataset are from the SAN DIEGO LINDBERGH FIELD, CA US station (GHCND:USW00023188) at 32.7336°, -117.1831° beginning in July 1, 1939.

    The Global Historical Climatology Network - Daily (GHCN-Daily) dataset integrates daily climate observations from approximately 30 different data sources. Version 3 was released in September 2012 with the addition of data from two additional station networks. Changes to the processing system associated with the version 3 release also allowed for updates to occur 7 days a week rather than only on most weekdays. Version 3 contains station-based measurements from well over 90,000 land-based stations worldwide, about two thirds of which are for precipitation measurement only. Other meteorological elements include, but are not limited to, daily maximum and minimum temperature, temperature at the time of observation, snowfall and snow depth. Over 25,000 stations are regularly updated with observations from within roughly the last month. The dataset is also routinely reconstructed (usually every week) from its roughly 30 data sources to ensure that GHCN-Daily is generally in sync with its growing list of constituent sources. During this process, quality assurance checks are applied to the full dataset. Where possible, GHCN-Daily station data are also updated daily from a variety of data streams. Station values for each daily update also undergo a suite of quality checks.

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Esri (2022). National Weather Service Precipitation Forecast [Dataset]. https://www.disasterpartners.org/maps/f9e9283b9c9741d09aad633f68758bf6
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National Weather Service Precipitation Forecast

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11 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Aug 16, 2022
Dataset authored and provided by
Esrihttp://esri.com/
Area covered
Description

This map displays the Quantitative Precipitation Forecast (QPF) for the next 72 hours across the contiguous United States. Data are updated hourly from the National Digital Forecast Database produced by the National Weather Service.The dataset includes incremental and cumulative precipitation data in 6-hour intervals. In the ArcGIS Online map viewer you can enable the time animation feature and select either the "Amount by Time" (incremental) layer or the "Accumulation by Time" (cumulative) layer to view a 72-hour animation of forecast precipitation. All times are reported according to your local time zone.Where is the data coming from?The National Digital Forecast Database (NDFD) was designed to provide access to weather forecasts in digital form from a central location. The NDFD produces forecast data of sensible weather elements. NDFD contains a seamless mosaic of digital forecasts from National Weather Service (NWS) field offices working in collaboration with the National Centers for Environmental Prediction (NCEP). All of these organizations are under the administration of the National Oceanic and Atmospheric Administration (NOAA).Source: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.qpf.binWhere can I find other NDFD data?The Source data is downloaded and parsed using the Aggregated Live Feeds methodology to return information that can be served through ArcGIS Server as a map service or used to update Hosted Feature Services in Online or Enterprise.What can you do with this layer?This map service is suitable for data discovery and visualization. Identify features by clicking on the map to reveal the pre-configured pop-ups. View the time-enabled data using the time slider by Enabling Time Animation.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

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