Technical University of Denmark
30 files

Global Wind Atlas v3

Version 2 2024-03-13, 14:10
Version 1 2019-10-09, 05:31
posted on 2024-03-13, 14:10 authored by Neil DavisNeil Davis, Jake BadgerJake Badger, Andrea N. HahmannAndrea N. Hahmann, Brian Ohrbeck HansenBrian Ohrbeck Hansen, Bjarke Tobias OlsenBjarke Tobias Olsen, Niels Gylling MortensenNiels Gylling Mortensen, Duncan Heathfield, Marko Onninen, Gil Lizcano, Oriol Lacave
The Global Wind Atlas version 3 data-sets contain microscale wind information at approximately 250m grid point spacing.

The data is created by first dynamically down-scaling ERA5 reanalysis data from 2008-2017 to 3km resolution using the WRF mesoscale model.

The WRF results are then generalized using DTU's generalization methodology, and then down-scaled using the WAsP model to the final 250m resolution.

The data in this directory consist of the entire global tiff at the full 0.0025 degree resolution on the WGS84 map projection. These data also include four sets of overview pyramids to improve the viewing of the data at low resolution.

Most of the data are named as follows: gwa_{variable}_{height}.tif, where variable is one of
* wind-speed - The mean wind speed at the location for the 10 year period

* power-density - The mean power density of the wind, which is related to the cube of the wind speed, and can provide additional information about the strength of the wind not found in the mean wind speed alone.

* combined-Weibull-A and combined-Weibull-k - These are the all sector combined Weibull distribution parameters for the wind speed. They can be used to get an estimate of the wind speed and power density at a site. However, caution should be applied when using these in areas with wind speeds that come from multiple directions as the shapes of those individual distributions may be quite different than this combined distribution.

* air-density - The air density is found by interpolating the air density from the CFSR reanalysis to the elevation used in the global wind atlas following the approach described in WAsP 12.

* RIX - The RIX (Ruggedness IndeX) is a measure of how complex the terrain is. It provides the percent of the area within 10 km of the position that have slopes over 30-degrees. A RIX value greater than 5 suggests that you should use caution when interpreting the results.

The files which do not follow the naming convention above are the capacity-factor layers. The capacity factor layers were calculated for 3 distinct wind turbines, with 100m hub height and rotor diameters of 112, 126, and 136m, which fall into three IEC Classes (IEC1, IEC2, and IEC3). Capacity factors can be used to calculate a preliminary estimate of the energy yield of a wind turbine (in the MW range), when placed at a location. This can be done by multiplying the rated power of the wind turbine by the capacity factor for the location (and the number of hours in a year):

AEP = Prated*CF*8760 hr/year,

where AEP is annual energy production, Prated is rated power, and CF is capacity factor.


Primarily funded by the Energy Sector Management Assistance Program (ESMAP) in the World Bank





Start Date: 2008-01-01 Stop Date: 2017-12-31


  • Siting;>Wind Atlases
  • Siting;>Wind Mapping
  • Siting;>Resource assessment


  • Meteorological;>Other
  • Flow;>Linearized


  • Modeling

External conditions

  • Location;>Offshore;>Nearshore
  • Location;>Offshore;>Offshore
  • Location;>Onshore;>Coastal
  • Location;>Onshore;>Inland
  • Location;>Offshore;>Other
  • Location;>Onshore;>Other
  • Location;>Other
  • Topography;>Forest
  • Topography;>Urban
  • Topography;>Rural
  • Topography;>Semi-urban
  • Topography;>Other
  • Terrain type;>Complex;>Hilly
  • Terrain type;>Complex;>Escarpment
  • Terrain type;>Complex;>Ridge
  • Terrain type;>Complex;>Other
  • Terrain type;>Flat
  • Terrain type;>Other
  • Water depth category;>Shallow water
  • Water depth category;>Deep water
  • Water depth category;>Other

Data category

  • Meteorological data

ORCID for corresponding depositor