The Global Wind Atlas: A high-resolution dataset of climatologies and associated web-based application

Neil N. Davis*, Jake Badger, Andrea N. Hahmann, Brian O. Hansen, Niels G. Mortensen, Mark Kelly, Xiaoli G. Larsén, Bjarke T. Olsen, Rogier Floors, Gil Lizcano, Pau Casso, Oriol Lacave, Albert Bosch, Ides Bauwens, Oliver James Knight, Albertine Potter van Loon, Rachel Fox, Tigran Parvanyan, Søren Bo Krohn Hansen, Duncan HeathfieldMarko Onninen, Ray Drummond

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

The Global Wind Atlas (GWA) provides high-resolution databases and maps of the wind resource for all land points within 200 km of the coastline, excluding Antarctica. The GWA is used to identify and understand the global, national, regional, and local potential for wind energy and to guide energy specialists, policymakers, and planners in the transition to a sustainable energy system. This information is vital to ensuring the growth of wind energy, helping to transition to a sustainable energy system, which will mitigate climate change and meet the world’s need for reliable, affordable, and clean energy. The GWA uses the established numerical wind atlas methodology to downscale coarse-resolution wind data to microscale, using linearized flow modeling and high-resolution topographic data. There have been three versions of the GWA, each using mesoscale model data at successively higher spatial resolution. A website and Geographic Information System (GIS) files support quick and in-depth analysis. Validation data and analysis, using measurements from tall masts located worldwide, are also provided through the web application. The development process of the GWA involves a dialogue between meteorological modelers, wind energy development experts, web designers, and representatives of the end-users to provide accurate data in a dynamic and relevant way. This article outlines the general method, specific development, and application of the Global Wind Atlas.
Original languageEnglish
JournalBulletin of the American Meteorological Society
Volume104
Issue number8
Pages (from-to)E1507-E1525
Number of pages19
ISSN0003-0007
DOIs
Publication statusPublished - 2023

Keywords

  • Wind
  • Coupled models
  • Model evaluation/performance
  • Geographic information systems (GIS)
  • Planning
  • Renewable energy

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