This map displays the wind forecast over the next 72 hours across the contiguous United States, in 3 hour increments, including wind direction, wind gust, and sustained wind speed.Zoom in on the Map to refine the detail for a desired area. The Wind Gust is the maximum 3-second wind speed (in mph) forecast to occur within a 2-minute interval within a 3 hour period at a height of 10 meters Above Ground Level (AGL). The Wind Speed is the expected sustained wind speed (in mph) for the indicated 3 hour period at a height of 10 meters AGL. Data are updated hourly from the National Digital Forecast Database produced by the National Weather Service.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).Wind Speed Source: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.wspd.binWind Gust Source: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.wgust.binWind Direction Source: https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/AR.conus/VP.001-003/ds.wdir.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.Alternate SymbologyFeature Layer item that uses Vector Marker Symbols to render point arrows, easily altered by user. The color palette uses the Beaufort Scale for Wind Speed. https://www.arcgis.com/home/item.html?id=45cd2d4f5b9a4f299182c518ffa15977 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!

The UK mean wind data contain the mean wind speed and direction, and the direction, speed and time of the maximum gust, all during 1 or more hours, ending at the stated time and date. The data were collected by observation stations operated by the Met Office across the UK and transmitted within the following message types: SYNOP, HCM, AWSHRLY, DLY3208, HWNDAUTO and HWND6910. The data spans from 1949 to 2022.

This version supersedes the previous version of this dataset and a change log is available in the archive, and in the linked documentation for this record, detailing the differences between this version and the previous version. The change logs detail new, replaced and removed data. These include the addition of data for calendar year 2022.

For further details on observing practice, including measurement accuracies for the message types, see relevant sections of the MIDAS User Guide linked from this record (e.g. section 3.3 details the wind network in the UK, section 5.5 covers wind measurements in general and section 4 details message type information).

This dataset is part of the Midas-open dataset collection made available by the Met Office under the UK Open Government Licence, containing only UK mainland land surface observations owned or operated by the Met Office. It is a subset of the fuller, restricted Met Office Integrated Data Archive System (MIDAS) Land and Marine Surface Stations dataset, also available through the Centre for Environmental Data Analysis - see the related dataset section on this record.

Data repository for measurements from 12 wind masts in Pakistan. Data transmits daily reports for wind speed, wind direction, air pressure, relative humidity and temperature. Please refer to the country project page for additional outputs and reports, including the installation reports: http://esmap.org/node/3058. For access to maps and GIS layers, please visit the Global Wind Atlas: https://globalwindatlas.info/ Please cite as: [Data/information/map obtained from the] “World Bank via ENERGYDATA.info, under a project funded by the Energy Sector Management Assistance Program (ESMAP).

Herewith we present the dataset of wind measurements from a Skipheia meteorological station on the island of Frøya on the western coast of Norway, Trondelag.

The site represents an exposed coastal wind climate with open sea, land and mixed fetch from various directions. UTM-coordinates of the Met-mast: 8.34251 E and 63.66638 N.

Presented data were gathered between years 2009-2015;

Hardware summary: 6 pairs of 2D sonic anemometers at 10, 16, 25, 40, 70, 100 m above the ground, independent temperature measurements at the same heights and near the ground; pressure and relative humidity from local meteostation (Sula, 20 km away).

Database summary: approx. 180 000 of 10 min data samples of full data recovery. Wind speed and direction, temperature, pressure & relative humidity (from a nearby meteostation).

Data description: Two data files of different formats are available: a ‘*.txt’ comma-separated values file and a native MATLAB ‘*.mat’ file. Both contain the same data, starting with the first column: timestamp, wind speed (m/s, columns WS1-WS12) for 6 anemometers pairs, wind direction (360 deg, columns WD1-WD12) for 6 anemometers pairs, temperature at 0.2 m (AT0), temperatures at levels of wind measurement (deg C, AT1-AT6), data from nearby meteostation Sula, pressure (hPa, PressureSula), relative humidity (%, RelHumSula), temperature (deg C, TempSula), wind direction (360 deg, WDSula) and wind speed (m/s, WSSula). Columns have headers describing the data (first row).

Detailed site description with wind climate description can be found in attached analysis: Site analysys.pdf.

Additional information and analysis can be found in listed below works, using data from Frøya site, or nearby sites:

Møller, M., Domagalski, P., and Sætran, L. R.: Comparing Abnormalities in Onshore and Offshore Vertical Wind Profiles, Wind Energ. Sci. https://wes.copernicus.org/articles/5/391/2020/

IEA Wind TCP Task 27 Compendium of IEA Wind TCP Task 27 Case Studies, Technical Report, Prepared by Ignacio Cruz Cruz, CIEMAT, Spain Trudy Forsyth, WAT, United States, October 2018; Chapter 1.8. https://community.ieawind.org/HigherLogic/System/DownloadDocumentFile.ashx?DocumentFileKey=8afc06ec-bb68-0be8-8481-6622e9e95ae7&forceDialog=0

Domagalski, P., Bardal, L. M., & Satran, L. Vertical Wind Profiles in Non-neutral Conditions-Comparison of Models and Measurements from Froya. Journal of Offshore Mechanics and Arctic Engineering, doi: 10.1115/1.4041816, http://offshoremechanics.asmedigitalcollection.asme.org/article.aspx?articleid=2711333&resultClick=3

Mathias Møller , Piotr Domagalski and Lars Roar Sætran, Characteristics of abnormal vertical wind profiles at a coastal site, Journal of Physics: Conference Series, IOPscience, under review (Feb 2019), DeepWind2019 conference poster available at: https://www.sintef.no/globalassets/project/eera-deepwind-2019/posters/c_moller_a4.pdf

Bardal, L. M., Onstad, A. E., Sætran, L. R., & Lund, J. A. (2018). Evaluation of methods for estimating atmospheric stability at two coastal sites. Wind Engineering, 0309524X18780378, https://doi.org/10.1177/0309524X18780378

Bardal, L. M., & Sætran, L. R. (2016, September). Spatial correlation of atmospheric wind at scales relevant for large scale wind turbines. In Journal of Physics: Conference Series (Vol. 753, No. 3, p. 032033). IOP Publishing, doi:10.1088/1742-6596/753/3/032033, https://iopscience.iop.org/article/10.1088/1742-6596/753/3/032033/pdf

Bardal, L. M., & Sætran, L. R. (2016). Wind gust factors in a coastal wind climate. Energy Procedia, 94, 417-424, https://doi.org/10.1016/j.egypro.2016.09.207

Maps with wind speed, wind rose and wind power density potential in India. The GIS data stems from the Global Wind Atlas (http://globalwindatlas.info/). GIS data is available as JSON and CSV. The second link provides poster size (.pdf) and midsize maps (.png).

The following is excerpted from an unpublished report by Michael Brower (2004): "Using the MesoMap system, TrueWind has produced maps of mean wind speed in Indiana for heights of 30, 50, 70, and 100 m above ground, as well as a map of wind power at 50 m. TrueWind has also produced data files of the predicted wind speed frequency distribution and speed and energy by direction. The maps and data files are provided on a CD with the ArcReader software, which will enable users to view, print, copy, and query the maps and wind rose data. "The MesoMap system consists of an integrated set of atmospheric simulation models, databases, and computers and storage systems. At the core of MesoMap is MASS (Mesoscale Atmospheric Simulation System), a numerical weather model, which simulates the physics of the atmosphere. MASS is coupled to a simpler wind flow model, WindMap, which is used to refine the spatial resolution of MASS and account for localized effects of terrain and surface roughness. MASS simulates weather conditions over a region for 366 historical days randomly selected from a 15-year period. When the runs are finished, the results are input into WindMap. In this project, the MASS model was run on a grid spacing of 1.7 km and WindMap on a grid spacing of 200 m. "The wind maps show that the best wind resource in Indiana is found in the northcentral part of the state. The mean wind speed at 50 m height between Indianapolis, Kokomo, and Lafayette, and to the northwest of Lafayette, is predicted to be in the range of 6.5 to 7 m/s, and the mean wind power is predicted to be about 250 to 350 W/m2, or NREL class 2 to 3. In the rest of northern Indiana, the wind speed tends to be around 0.5 m/s lower, and the wind power is a solid class 2. In southern Indiana, a wind speed of 4.5 to 6 m/s and a wind power class of 1 to 2 prevails. The main reason for this wind resource distribution pattern is that the land is much more forested in the southern half of the state than in the northern half. Topography also plays a role, as does the track of the jet stream."

The text file "Wind speed.txt" contains hourly wind speed data in miles per hour and associated data source flags from January 1, 1948, to September 30, 2021. The primary data for water year 2021 (a water year is the 12-month period, October 1 through September 30, designated by the calendar year in which it ends) were downloaded from the Argonne National Laboratory (ANL) (Argonne National Laboratory, 2022) and processed following the guidelines documented in Over and others (2010). The processed data were appended to ARGN20.WDM (Bera, 2021) and renamed as ARGN21.WDM. Missing and apparently erroneous data values were replaced with adjusted values from nearby weather stations used as "backup." The hourly wind speed data from the Illinois Climate Network (Water and Atmospheric Resources Monitoring Program, 2022) station at St. Charles, Illinois, and the National Weather Service station at O'Hare International Airport were used as "backup." Midwestern Regional Climate Center (Midwestern Regional Climate Center, 2022) provided the data collected by National Weather Service from the station at O'Hare International Airport. Each data source flag is of the form "xyz", which allows the user to determine its source and the methods used to process the data (Over and others, 2010). References Cited: Argonne National Laboratory, 2022, Meteorological data, accessed on January 17, 2022, at https://www.atmos.anl.gov/ANLMET/numeric/. Bera, M., 2021, Meteorological Database, Argonne National Laboratory, Illinois, January 1, 1948 - September 30, 2020: U.S. Geological Survey data release, https://doi.org/10.5066/P9GP8COF. Midwestern Regional Climate Center, 2022, Meteorological data, accessed on March 2, 2022, at https://mrcc.purdue.edu/CLIMATE/. Over, T.M., Price, T.H., and Ishii, A.L., 2010, Development and analysis of a meteorological database, Argonne National Laboratory, Illinois: U.S. Geological Survey Open-File Report 2010-1220, 67 p., http://pubs.usgs.gov/of/2010/1220/. Water and Atmospheric Resources Monitoring Program. Illinois Climate Network, 2022. Illinois State Water Survey, 2204 Griffith Drive, Champaign, IL 61820-7495. Data accessed on January 4, 2022, at http://dx.doi.org/10.13012/J8MW2F2Q.

Herewith we present the extended 1Hz dataset of wind measurements from a Skipheia meteorological station on the island of Frøya on the western coast of Norway, Trondelag.

The data binned in 10 min averages can be find at: https://doi.org/10.5281/zenodo.2557500

The site represents an exposed coastal wind climate with open sea, land and mixed fetch from various directions. UTM-coordinates of the Met-mast: 8.34251 E and 63.66638 N. See the map for details (NorwegianMapping Authority): https://www.norgeskart.no/#!?project=norgeskart&layers=1003&zoom=3&lat=7035885.49&lon=539601.41&markerLat=7077031.483032227&markerLon=170902.83203125&panel=searchOptionsPanel&sok=Titranveien

Presented data were gathered between years 2009-2016.

Data&hardware summary:

Years 2009-2016: Mast2 equipped with 6 pairs of 2D sonic anemometers at 10, 16, 25, 40, 70, 100 m above the ground, independent temperature measurements at the same heights and near the ground; pressure and relative humidity from local meteostation (Sula, 20 km away).

Years 2014-2016: Mast4 equipped with 2 pairs of 2D sonic anemometers at 40 and 100 m above the ground. The distance between the masts is 79 m.

Data is binned in years and months and stored in a ‘*.txt’ tab-separated values file.

Data column order is described in SkipheiaMast2_header.txt and SkipheiaMast4_header.txt, where WSx is the wind speed (m/s), WDx is the wind direction (360 deg), ATx is the air temperature (deg C) and x designates the instrument number. The instruments are numbered starting from the ground.

Example: For Mast2 (6 pairs of anemometers, ground temperature + 6 temperature sensors on the mast) that means that AT0 is the ground temperature. WS1 and WS2 are wind speed records at 10 m level. WS3 and WS4 are wind speed records at 16 m. For Mast4 (2 pairs of anemometers) that means that WS1 and WS2 are wind speed records at 40 m level. WS3 and WS4 are wind speed records at 100 m.

Detailed site description with wind climate description can be found in attached analysis: Site analysys.pdf.

Additional information and analysis can be found in listed below works, using data from Frøya site:

Bardal, L. M., & Sætran, L. R. (2016, September). Spatial correlation of atmospheric wind at scales relevant for large scale wind turbines. In Journal of Physics: Conference Series (Vol. 753, No. 3, p. 032033). IOP Publishing, doi:10.1088/1742-6596/753/3/032033, https://iopscience.iop.org/article/10.1088/1742-6596/753/3/032033/pdf

Bardal, L. M., & Sætran, L. R. (2016). Wind gust factors in a coastal wind climate. Energy Procedia, 94, 417-424, https://doi.org/10.1016/j.egypro.2016.09.207

IEA Wind TCP Task 27 Compendium of IEA Wind TCP Task 27 Case Studies, Technical Report, Prepared by Ignacio Cruz Cruz, CIEMAT, Spain Trudy Forsyth, WAT, United States, October 2018; Chapter 1.8. https://community.ieawind.org/HigherLogic/System/DownloadDocumentFile.ashx?DocumentFileKey=8afc06ec-bb68-0be8-8481-6622e9e95ae7&forceDialog=0

Domagalski, P., Bardal, L. M., & Sætran, L. Vertical Wind Profiles in Non-neutral Conditions-Comparison of Models and Measurements from Froya. Journal of Offshore Mechanics and Arctic Engineering, doi: 10.1115/1.4041816, http://offshoremechanics.asmedigitalcollection.asme.org/article.aspx?articleid=2711333&resultClick=3

Møller, M., Domagalski, P., & Sætran, L. R. (2019, October). Characteristics of abnormal vertical wind profiles at a coastal site. In Journal of Physics: Conference Series (Vol. 1356, No. 1, p. 012030). IOP Publishing. https://iopscience.iop.org/article/10.1088/1742-6596/1356/1/012030

Møller, M., Domagalski, P., and Sætran, L. R.: Comparing Abnormalities in Onshore and Offshore Vertical Wind Profiles, Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2019-40 , in review, 2019.

The following is excerpted from an unpublished report by Michael Brower (2004): "Using the MesoMap system, TrueWind has produced maps of mean wind speed in Indiana for heights of 30, 50, 70, and 100 m above ground, as well as a map of wind power at 50 m. TrueWind has also produced data files of the predicted wind speed frequency distribution and speed and energy by direction. The maps and data files are provided on a CD with the ArcReader software, which will enable users to view, print, copy, and query the maps and wind rose data. "The MesoMap system consists of an integrated set of atmospheric simulation models, databases, and computers and storage systems. At the core of MesoMap is MASS (Mesoscale Atmospheric Simulation System), a numerical weather model, which simulates the physics of the atmosphere. MASS is coupled to a simpler wind flow model, WindMap, which is used to refine the spatial resolution of MASS and account for localized effects of terrain and surface roughness. MASS simulates weather conditions over a region for 366 historical days randomly selected from a 15-year period. When the runs are finished, the results are input into WindMap. In this project, the MASS model was run on a grid spacing of 1.7 km and WindMap on a grid spacing of 200 m. "The wind maps show that the best wind resource in Indiana is found in the northcentral part of the state. The mean wind speed at 50 m height between Indianapolis, Kokomo, and Lafayette, and to the northwest of Lafayette, is predicted to be in the range of 6.5 to 7 m/s, and the mean wind power is predicted to be about 250 to 350 W/m2, or NREL class 2 to 3. In the rest of northern Indiana, the wind speed tends to be around 0.5 m/s lower, and the wind power is a solid class 2. In southern Indiana, a wind speed of 4.5 to 6 m/s and a wind power class of 1 to 2 prevails. The main reason for this wind resource distribution pattern is that the land is much more forested in the southern half of the state than in the northern half. Topography also plays a role, as does the track of the jet stream."

Maps with wind speed, wind rose and wind power density potential in Vietnam. The GIS data stems from the Global Wind Atlas (http://globalwindatlas.info/).

GIS data is available as JSON and CSV. The second link provides poster size (.pdf) and midsize maps (.png).

Maps with wind speed, wind rose and wind power density potential in The Republic of Korea. The GIS data stems from the Global Wind Atlas (http://globalwindatlas.info/). GIS data is available as JSON and CSV. The second link provides poster size (.pdf) and midsize maps (.png).

Three-dimensional windspeed and direction measured by sonic anemometer; air temperature measured by the 3-D sonic anemometer. This data product is bundled into DP4.00200, Bundled data products - eddy covariance, and is not available as a stand-alone download.

The Department for Business, Enterprise & Regulatory Reform's wind speed database is available from this website. It contains estimates of the annual mean wind speed throughout the UK. The data is the result of an air flow model that estimates the effect of topography on wind speed. There is no allowance for the effect of local thermally driven winds such as sea breezes or mountain/valley breezes. The model was applied with 1km square resolution and takes no account of topography on a small scale or local surface roughness (such as tall crops, stone walls or trees), both of which may have a considerable effect on the wind speed. The data can only be used as a guide and should be followed by on-site measurements for a proper assessment. Each value stored in the database is the estimated average for a 1km square at either 10m, 25m or 45m above ground level (agl). The database uses the Ordnance Survey grid system for Great Britain and the grid system of the Ordnance Survey of Northern Ireland.

In this dataset the anther's analysis is based on data from NREL about Solar & Wind energy generation by operation areas.

NASA Prediction of Worldwide Energy Resources

Solar

Monthly averages for global horizontal radiation over 22-year period (Jul 1983

• Jun 2013)

Wind

Monthly average wind speed at 50m above the surface of earth over a 30-year period (Jan 1984 - Dec 2013)Year: Averaged Over 10 to 15 years

COA = central operating area.

EOA = eastern operating area.

SOA = southern operating area.

WOA = western operating area. Source: NRELSource Link

Maps with wind speed, wind rose and wind power density potential in Poland. The GIS data stems from the Global Wind Atlas (http://globalwindatlas.info/). GIS data is available as JSON and CSV. The second link provides poster size (.pdf) and midsize maps (.png).

Over the past two decades, the average wind speed in the United Kingdom has remained relatively stable. In 2024, the average wind speed in the UK was 8.4 knots. Speeds peaked during this period in 2015 at 9.4 knots, before falling to 8.4 knots the following year. One knot is equivalent to one nautical mile per hour. Overall, wind speeds have mostly remained between eight and nine knots, dropping to a low of 7.8 in 2010. The first and fourth quarters were the windiest Since 2010, the first and fourth quarters of each year generally recorded the highest wind speeds. The highest quarterly wind speed averages occurred in the first quarter of 2020, with speeds of approximately 11.5 knots. Between 2015 and 2023, the most noticeable deviation from the 10-year mean was recorded in February 2020. In this month wind speeds were 4.2 knots higher than normal. Optimal wind conditions for wind energy The United Kingdom has some of the best wind conditions in Europe for wind power, so it is no surprise that it plays an important role in the country's energy mix. As of 2023, there were 39 offshore wind farms operating in the UK, by far the most in Europe. Furthermore, in the same year, offshore wind power additions in the UK reached 1.14 gigawatts.

[Metadata] Description: Wind Energy Resource Data collected using the MesoMap system. Wind speed in the state of Hawaii for the height of 100 meters above ground.Source: Wind Energy Resource Maps of Hawaii, AWS Truewind, https://files.hawaii.gov/dbedt/op/gis/data/hawaii_wind_mapping_report.pdf. Apr. 2024: Hawaii Statewide GIS Program staff removed extraneous fields that had been added as part of the 2016 GIS database conversion and were no longer needed.For additional information, please refer to complete metadata at https://files.hawaii.gov/dbedt/op/gis/data/wind_data.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

Climate data have been collected at Scott Base continuously since 1957 and more recently from Arrival Heights and is one of the longest continuous climate records in Antarctica. Climate parameters measured include: wind speed and direction, air temperature, relative humidity, barometric pressure, and global, diffuse and direct solar radition. Climate data are collected on a daily basis from both sites. At Scott Base, this takes two forms: a standard daily observation at 0900 NZDT, and continuous data collection at 10 minute and hourly intervals using a CR10X data logger. The initial record of the 0900 daily observations began on 1 March 1957 with air temperature, air pressure, wind speed and direction, and global solar radiation being measured with standard instrumentation (wind measurements since 1972). This record constitutes the reference record. In January 1997 an electronic weather station (EWS) was added to collect and archive 10 minute and hourly data. The daily manual observations continued so as to provide a continuous reference and daily record. Historically, Arrival Heights only had a wind recorder (since January 1984). A data logger was installed in January 1999 and measured air temperature, relative humidity and global solar radition using a secondary network sensor, as well as wind speed and direction. A barometric pressure sensor was installed in 2001. A standard 10m mast was installed and all sensors were moved to the new Arrival Heights laboratory in 2007. 10-minute and hourly data are recorded. Data are retrieved and archived from both automatic stations daily, as well as manual observations from Scott Base and available on New Zealand's national climate database.

This map displays the forecasted wind speeds over the next 72 hours across the contiguous United States. Wind Speed is the expected 10-meter Above Ground Level (AGL) sustained wind speed (in knots) for the indicated hour. Wind speed forecasts are valid at the top of the indicated hour. Data are updated hourly from the National Digital Forecast Database produced by the National Weather Service.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.wspd.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!

Mean Wind Speed by Month (Knot)