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.

The map shows the mean wind speed at a height of 225 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.

Mean average wind speeds in metres per second (m/s) at 100 m height. These datasets cover the land area and coastal waters of Ireland. Data Compilation was completed in 2003. 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 policymakers. 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 50 m, 75 m and 100 m, Spanning onshore and offshore. (Larger heights of 125 m and 150 m were later covered in SEAI’s 2013 wind-mapping project.) The resulting GIS maps cover onshore in 200 m grids, and offshore in 400 m grids. Generally, wind maps extend to 15 km offshore, or occasionally 20 km. 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.

The map shows the average wind speed at an altitude of 225 m above ground. This was modelled throughout North Rhine-Westphalia in a resolution of 100 x 100 m and validated with the yields of existing wind turbines in North Rhine-Westphalia. The mean wind speed is an average of the wind speeds occurring over the year. The mean wind speed gives an indication of how a site is suitable for wind energy use.

A shapefile of annual average wind resource potential for New York, United States at a 50 meter height. This data set has been validated by NREL and wind energy meteorological consultants. Note: This data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 18, datum WGS 84 projection system. The wind power resource estimates were produced by AWS TrueWind using their MesoMap system and historical weather data under contract to Wind Powering America/NREL. This map has been validated with available surface data by NREL and wind energy meteorological consultants.

For updated gridded long-term average wind data please see the "Global Wind Atlas" resource below. For more information on NREL's wind resource data development, see the "Wind Integration National Dataset (WIND) Toolkit" and the "WIND Toolkit Long-Term Ensemble Dataset" resources.

A shapefile of annual average wind resource potential for Minnesota, United States at a 50 meter height. This data set has been validated by NREL and wind energy meteorological consultants. Note: This data is not suitable for micro-siting potential development projects. This map has been validated with available surface data by NREL and wind energy meteorological consultants. The 30m and 80m wind speed data values from the Minnesota state portal were averaged, then converted to power density assuming a Weibull K of 2.0 and using elevation to estimate air density. For updated gridded long-term average wind data please see the "Global Wind Atlas" resource below. For more information on NREL's wind resource data development, see the "Wind Integration National Dataset (WIND) Toolkit" and the "WIND Toolkit Long-Term Ensemble Dataset" resources.

A shapefile of annual average wind resource potential for Illinois, United States at a 50 meter height. This data set has been validated by NREL and wind energy meteorological consultants. Note: This data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 1000 m resolution, in a Transverse Mercator projection. The wind power resource estimates were produced by AWS TrueWind using their MesoMap system and historical weather data under contract to Wind Powering America/NREL. This map has been validated with available surface data by NREL and wind energy meteorological consultants. For updated gridded long-term average wind data please see the "Global Wind Atlas" resource below. For more information on NREL's wind resource data development, see the "Wind Integration National Dataset (WIND) Toolkit" and the "WIND Toolkit Long-Term Ensemble Dataset" resources.

Abstract:Monash University under commission of Geoscience Australia produced an offshore wind capacity factor map assessed at a 150m hub height applying the Bureau of Meteorology 10 year (2009-2018) “Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia” (BARRA) hindcast model. The wind capacity factor has been calculated using the bounding curve of all scaled power curves for wind turbines available within the Open Energy Platform as of 2021. Average wind capacity factor values were also calculated for the Vestas V126 3.45MW and the GE V130 3.2MW wind turbines and are available in this web map service.Lineage:The Monash University project report (Offshore wind capacity factor maps - evaluating Australia's offshore wind resources potential) which is associated to this metadata record, details the method used to produce the offshore wind capacity factor maps. The method included geospatial alignment of the raw data, wind speed interpolation at 150m, calculation of the mean and standard deviation for hourly wind speeds at 150m from 2009 to 2018, the application of the methods of moments technique to calculate the shape and scale parameter of the wind Weibull distribution and calculation of a bounding curve for the power curves of wind turbines.The maximum offshore wind generation potential was calculated through the generation of a bounding curve for the currently, as of 2021, wind turbine power curves within the Open Energy Platform. The Weibull distribution parameters and the bounding curve were then combined to calculate the wind capacity factor values.Average wind capacity factor values were also calculated for the Vestas V126 3.45MW and the GE V130 3.2MW wind turbines.© Commonwealth of Australia (Geoscience Australia) 2022.Downloads and Links:Web ServicesOffshore Wind Capacity Factor Maps (Map Server)Offshore wind Capacity Factor Maps (WMS)Downloads available from the expanded catalogue link, belowMetadata URL:https://pid.geoscience.gov.au/dataset/ga/146703

Map of average wind speeds at 180 m altitude above ground as average from 2001 to 2020 in a resolution of 10 x 10 m.

Map of average wind speeds at 200 m altitude above ground as average from 2001 to 2020 in a resolution of 10 x 10 m.

The wind resource has been mapped on a 3 km x 3 km grid across Victoria. Average annual wind speeds have been modelled using the WindScape wind resource mapping tool that was developed by the Wind Energy Research Unit of CSIRO Land and Water in 2002. WindScape uses atmospheric data, and regional topography to model the wind resource at 65 metres above ground level to a resolution of 3 kilometres. The resolution of the modelled wind resource means that it does not incorporate the effects of local landscape features smaller than 3 kilometres in size, like small hills and ridges. This dataset is derived from the same data used to create the overview map of the Victorian wind atlas published by the Sustainable Energy Authority Victoria, c2003

Annual average wind resource potential for the state of Nevada, United States at a 50 meter height.

The wind power resource estimates were produced by TrueWind Solutions using their MesoMap system and historical weather data under contract to Wind Powering America/NREL. This map has been validated with available surface data by NREL and wind energy meteorological consultants.

A shapefile of annual average wind resource potential for Iowa, United States at a 50 meter height. This data set has been validated by NREL and wind energy meteorological consultants. Note: This data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 12, datum WGS 84 projection system. The wind power resource estimates were produced by AWS TrueWind using their MesoMap system and historical weather data under contract to Wind Powering America/NREL. This map has been validated with available surface data by NREL and wind energy meteorological consultants. For updated gridded long-term average wind data please see the "Global Wind Atlas" resource below. For more information on NREL's wind resource data development, see the "Wind Integration National Dataset (WIND) Toolkit" and the "WIND Toolkit Long-Term Ensemble Dataset" resources.

The plate contains four maps: Annual Winds, March Winds, August Winds and Annual Maximum Wind Speed. For each of the first three maps the frequency of wind, the mean speed of wind, and the frequency of calms are shown. On all three maps the frequency scale is 1 millimetre equals 2 percent. These values are presented for 50 locations across Canada. The map on the annual maximum wind speed shows the annual maximum hourly wind speeds in kilometres per hour for 30 year return period. Various types of anemometers can be used to measure wind. In Canada, two types are used; both employ a set of rotating cups mounted on a mast to indicate wind speed and a weather vane to indicate direction. There are about 200 anemometers of each type in use at the present time. Most anemometers are mounted according to World Meteorological Organization standards, at a height of 10 metres above the effective terrain. That is to say, the anemometer would be 10 metres above ground level over grassland, and 10 metres above the tree tops in a heavily treed area. Some wind observations were taken in Canada as early as 1840. Hourly observations became very useful with the advent of aircraft, and stations taking hourly observations of wind proliferated in Canada under the Commonwealth Air Training Program during the Second World War. Wind is air in motion. This motion is initiated by the air pressure gradient. The pressure distribution over the earth's surface is controlled by the temperature regime which, generally speaking, is hot near the equator and cold at the poles. The tendency for the wind to blow from high to low pressure is modified by the rotation of the earth. This effect, known as the Coriolis force, causes the wind to deflect to the right in the northern hemisphere. Because of the unequal heating of the earth's surface and the Coriolis force, three main wind zones can be identified in the northern hemisphere. There is a zone of persistent northeast trade winds between the equator and approximately 20oN. From approximately 30oN to 60oN is a zone of mainly westerly winds and from approximately 65°N to the pole is a zone of north-easterly winds. Winds in the latter two zones are not nearly as persistent as the trade winds in either speed or direction.

The map shows the average wind speed at 200 m above ground level. This was modelled throughout North Rhine-Westphalia in a resolution of 100 x 100 m and validated with the yields of existing wind turbines in North Rhine-Westphalia. The mean wind speed is an average of the wind speeds occurring over the year. The mean wind speed gives an indication of how a site is suitable for wind energy use.

A shapefile of annual average wind resource potential for Tennessee, United States at a 50 meter height. This data set has been validated by NREL and wind energy meteorological consultants. Note: This data is not suitable for micro-siting potential development projects. This shapefile was generated from a raster dataset with a 200 m resolution, in a UTM zone 12, datum WGS 84 projection system. The wind power resource estimates were produced by AWS TrueWind using their MesoMap system and historical weather data under contract to Wind Powering America/NREL. This map has been validated with available surface data by NREL and wind energy meteorological consultants. For updated gridded long-term average wind data please see the "Global Wind Atlas" resource below. For more information on NREL's wind resource data development, see the "Wind Integration National Dataset (WIND) Toolkit" and the "WIND Toolkit Long-Term Ensemble Dataset" resources.

GeoTIFF of Wind Power Class values for the state of Alaska. This map shows the annual average wind power estimates at a height of 50 meters. It is a combination of high resolution and low resolution datasets produced by NREL and other organizations. The data was screened to eliminate areas unlikely to be developed onshore due to land use or environmental issues. In many states, the wind resource on this map is visually enhanced to better show distribution on ridge crests and other features.

Map of the capped average wind power density at 120 m altitude above ground. The capping value is 15 m/s. The mean wind power density is composed of the wind speeds occurring at one location in the corresponding frequency as well as the air density.

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.