The Wind Integration National Dataset (WIND) Toolkit, developed by the National Renewable Energy Laboratory (NREL), provides modeled wind speeds at multiple elevations. Instantaneous wind measurements were analyzed from more than 126,000 sites in the continental United States for the years 2007–2013. The model results were mapped on a 2-km grid. A subset of the contiguous United States data for 2012 is shown here. Offshore data is shown to 50 nautical miles.Time Extent: Annual 2012Units: m/sCell Size: 2 kmSource Type: StretchedPixel Type: 32 Bit FloatData Projection: GCS WGS84Mosaic Projection:  WGS 1984 Web MercatorExtent: Contiguous United StatesSource: NREL Wind Integration National Dataset v1.1WIND is an update and expansion of the Eastern Wind Integration Data Set and Western Wind Integration Data Set. It supports the next generation of wind integration studies.Accessing Elevation InformationEach of the 9 elevation slices can be accessed, visualized, and analyzed. In ArcGIS Pro, go to the Multidimensional Ribbon and use the Elevation pull-down menu. In ArcGIS Online, it is best to use Web Map Viewer Classic where the elevation slider will automatically appear on the righthand side. The elevation slider will be available in the new Map Viewer in an upcoming release. What can you do with this layer?This layer may be added to maps to visualize and quickly interrogate each pixel value. The pop-up provides the pixel’s wind speed value.This analytical imagery tile layer can be used in analysis. For example, the layer may be added to ArcGIS Pro and proposed wind turbine locations can be used to Sample the layer at multiple elevation to determine the optimal hub height. Source data can be accessed on Amazon Web ServicesUsers of the WIND Toolkit should use the following citations:Draxl, C., B.M. Hodge, A. Clifton, and J. McCaa. 2015. Overview and Meteorological Validation of the Wind Integration National Dataset Toolkit (Technical Report, NREL/TP-5000-61740). Golden, CO: National Renewable Energy Laboratory.Draxl, C., B.M. Hodge, A. Clifton, and J. McCaa. 2015. "The Wind Integration National Dataset (WIND) Toolkit." Applied Energy 151: 355366.King, J., A. Clifton, and B.M. Hodge. 2014. Validation of Power Output for the WIND Toolkit (Technical Report, NREL/TP-5D00-61714). Golden, CO: National Renewable Energy Laboratory.

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.

There is no description for this dataset.

Zipped collections of shapefiles are available in two spatial reference or coordinate systems: 1) Irish Transverse Mercator (ITM, EPSG:2157) 2) WGS 84 Web Mercator (EPSG:3857) The Sustainable Energy Authority of Ireland (SEAI) offers the same data in its Wind Atlas, a digital map of Ireland's wind energy resource (http://gis.seai.ie/wind). SEAI's 2003 datasets of wind characteristics assist wind energy planners, developers and policy makers. Background on 2003 wind maps The 2003 wind-mapping project was completed by ESB International and TrueWind Solutions for SEAI (then SEI). It predicted wind characteristics, at heights of 50m, 75m and 100m, spanning onshore and offshore. (Larger heights of 125m and 150m were later covered in SEAI’s 2013 wind-mapping project.) The resulting GIS maps cover onshore in 200m grids, and offshore in 400m grids. Generally, wind maps extend to 15km offshore, or occasionally 20km. About the 2003 methodology, it iterated a MesoMap system and a faster WindMap model through reducing grid sizes. MesoMap is built on MASS (Mesoscale Atmospheric Simulation System), a numerical weather model that embodied the fundamental physics of the atmosphere. Iterations through the nested grids accounted for local land elevation, land cover and roughness. Final iterations accounted for increased wind shear and reduced near-surface wind speed at less windy sites. The 2003 Wind-mapping Project Report is available here.

Data on daily mean wind speed (Please visit the reference link for other climate information). The multiple file formats are available for datasets download in API.

Multi-year (2007-2013) Annual Average Wind Speed at 10 - 200 meters above the surface level.

Annual average wind speed (m/s) with 1km x 1km resolution. The dataset was obtained from IRENA Global Atlas for Renewable Energy (https://irena.masdar.ac.ae/gallery/#gallery), which collects the data from the Global Wind Atlas 2.0, a free, web-based application developed, owned and operated by the Technical University of Denmark (DTU) in partnership with the World Bank Group, utilizing data provided by Vortex, with funding provided by the Energy Sector Management Assistance Program (ESMAP). For future information: https://globalwindatlas.info.

Wind speed averages in the United Kingdom are generally highest in the first and fourth quarters of each calendar year – the winter months. Since 2010, the UK’s highest wind speed average was recorded in the first quarter of 2020, at 11.5 knots. During this period, 2010 was the only year that had the greatest wind speeds outside the winter months, with an average of 8.4 knots in the third quarter. In 2024, wind speeds ranged between a low of 7.9 knots in the third quarter and 9.4 knots in the first quarter. With few exceptions, UK wind speeds generally average at least eight knots annually. 2015 marked the year with the highest average wind speed in the UK (since the beginning of the reporting period in 2001), reaching an average of 9.4 knots. Wind power The UK has some of the best wind conditions in Europe for wind power. By 2023, there were 39 offshore wind farms operating across the UK, by far the most in Europe. Meanwhile, offshore wind power additions in the UK reached 1.14 gigawatts that same year. Quarterly rainfall Another weather phenomenon, UK rainfall also tends to be heaviest in the winter months. The average rainfall in the second quarter of 2024 was 254.5 millimeters, with figures in 2011 spiking to 738.6 millimeters. That year, precipitation levels in some parts of Scotland were the highest in one hundred years, while southern parts of England kept remarkably dry.

Wind speed raster file over the territory of Afghanistan. Aggregated annual average values. Spatial resolution 5km.

Abstract

This data provides modeled annual average wind speed for the contiguous United States both onshore and offshore for the period 2007–2013 derived from NREL's WIND Toolkit.

Publisher: National Renewable Energy Laboratory, Golden, Colorado Publication date: 2015

Methodology

EIDC converted the original multiple raster (GeoTiff) files into a single tabular table with polygon geometry.

Original files:

• Format: raster
• File Type: GeoTiff
• Projection: Lambert Conformal Conic
• Unit: meters / second
• Geodetic: WGS84, EPSG: 4326
• Data resolution: 2km x 2km
• Raster value: Multi-year (2007-2013) Annual Average Wind Speed, meters per second, at 10 - 100 meters above surface level

%3C!-- --%3E

This dataset:

• Format: Tabular data with a geometry (polygons) column
• File Type: This dataset can be downloaded as .csv and converted into .shp or .geojson based on the geometry column.
• Unit: meters / second
• Geodetic: WGS84, EPSG: 4326
• Data resolution: 2km x 2km
• Attributes: Multi-year (2007-2013) Annual Average Wind Speed, meters per second, at 10 - 200 meters above surface level

%3C!-- --%3E

Usage

This dataset was derived from the WIND Toolkit and may be used with the following citations:

Draxl, C., B.M. Hodge, A. Clifton, and J. McCaa. 2015. Overview and Meteorological Validation of the Wind Integration National Dataset Toolkit (Technical Report, NREL/TP-5000-61740). Golden, CO: National Renewable Energy Laboratory.

Draxl, C., B.M. Hodge, A. Clifton, and J. McCaa. 2015. "The Wind Integration National Dataset (WIND) Toolkit." Applied Energy 151: 355366.

Lieberman-Cribbin, W., C. Draxl, and A. Clifton. 2014. Guide to Using the WIND Toolkit Validation Code (Technical Report, NREL/TP-5000-62595). Golden, CO: National Renewable Energy Laboratory.

King, J., A. Clifton, and B.M. Hodge. 2014. Validation of Power Output for the WIND Toolkit (Technical Report, NREL/TP-5D00-61714). Golden, CO: National Renewable Energy Laboratory.

Related Literature

Wang, Y.-H., Walter, R. K., White, C., Farr, H., & Ruttenberg, B. I. (2019). Assessment of surface wind datasets for estimating offshore wind energy along the Central California Coast. Renewable Energy, 133, 343–353. https://doi.org/10.1016/j.renene.2018.10.008

Slusarewicz, J. H., & Cohan, D. S. (2018). Assessing solar and wind complementarity in Texas. Renewables: Wind, Water, and Solar, 5(1), 7. https://doi.org/10.1186/s40807-018-0054-3Lopez, A., Mai, T., Lantz, E., Harrison-Atlas, D., Williams, T., & Maclaurin, G. (2021). Land use and turbine technology influences on wind potential in the United States. Energy, 223, 120044. https://doi.org/10.1016/j.energy.2021.120044

Satkauskas, I., Maack, J., Reynolds, M., Sigler, D., Panda, K., & Jones, W. (2022). Simulating impacts of extreme events on grids with high penetrations of wind power resources. 2022 IEEE/PES Transmission and Distribution Conference and Exposition (T&D), 01–05. https://doi.org/10.1109/TD43745.2022.9816884

Feng, C., Sun, M., Cui, M., Chartan, E. K., Hodge, B.-M., & Zhang, J. (2019). Characterizing forecastability of wind sites in the United States. Renewable Energy, 133, 1352–1365. https://doi.org/10.1016/j.renene.2018.08.085

In February 2025, the average wind speed was 0.7 knots below the long-term mean (from 2002 to 2021). The largest deviation occurred in February 2020, when winds increased by 4.2 knots compared to the average speed.

Mean Wind Speed by Month (Knot)

These data represent the predicted mean annual wind speeds at 90-meter height presented at a spatial resolution of 200 meters. Areas with annual average wind speed of 7 meters per second (m/s) and greater at 90-meter height are generally considered to have a wind resource suitable for offshore development.Direct data download | MetadataThis item is curated by the MarineCadastre.gov team. Find more information at marinecadastre.gov.

This statistic shows cities in the United States with the highest average wind speeds. In San Francisco the average wind speed in 2011 was 10.6 miles per hour. In Chicago, Illinois the average wind speed was 10.3 miles per hour.

These data represent the average monthly wind speed and direction at the surface of the ocean. Source data includes values from January 1, 1979, to December 31, 2010, at hourly temporal resolution, with a spatial resolution of 0.313 degrees latitude x 0.312 degrees longitude. Values for wind speed are in meters per second and wind direction in degrees from True North.

These data represents the predicted mean annual wind speeds at 90 m height presented at a spatial resolution of 200 m. Areas with annual average wind speed of 7 meters per second (m/s) and greater at 90 m height are generally considered to have a wind resource suitable for offshore development. The source data is from 2002 through 2008.

The map shows the mean wind speed at a height of 200 m above ground. This was modeled across NRW with a resolution of 100 x 100 m and validated with the yields of existing wind turbines in NRW. The mean wind speed is an average of the wind speeds occurring over the year. The average wind speed gives an indication of how suitable a location is for wind energy use.

These data depict the predicted mean annual wind speed in meters per second at 100 meters elevation above sea level. The source data is from 2007 through 2013, and is based on a 2 km sample resolution. The source data was generalized and transformed into a polygon format for planning purposes.

The average mean wind speed in Tokyo, Japan amounted to 2.7 meters per second in 2022. Figures peaked in 2013, reaching 3.1 meters per second. In 2022, the monthly mean wind speed in Tokyo was highest in between July and August.

Mean average wind speeds in metres per second (m/s) at 20m above ground level. These datasets cover the geographic land area of Ireland and Irish Internal Waters. Data compilation was completed in 2013, by analysing measurements taken during 2001--2010.

Zipped collections of shapefiles are available in two spatial reference or coordinate systems:
1) Irish Transverse Mercator (ITM, EPSG:2157)
2) WGS 84 Web Mercator (EPSG:3857)

The Sustainable Energy Authority of Ireland (SEAI) offers the same data in its Wind Atlas, a digital map of Ireland's wind energy resource (http://gis.seai.ie/wind). SEAI's wind speed datasets assist wind energy planners, developers and policy makers.