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April 23, 2026Scientific Data2 citationsOpen Access

A global dataset of onshore wind turbines with site-specific historical (1989–2018) and future (2030–2059) wind resources across 89 countries

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CJChristopher JungUniversity of FreiburgDSDirk SchindlerUniversity of Freiburg

Key Points

  • The aim is to create a comprehensive dataset of onshore wind turbines to facilitate the planning and deployment of wind energy resources.
  • Developed a global dataset of 416,417 horizontal-axis wind turbines (HAWT)
  • Included historical (1989-2018) and projected future (2030-2059) wind resource data
  • Utilized simulations from 13 climate models under different scenarios to characterize future wind resources.
  • Provided site-specific historical and future wind resources including mean wind speed and power density
  • Included comprehensive technical specifications for each turbine
  • Facilitated enhanced energy and climate research and informed policies for wind energy development.

Abstract

Abstract The expansion of wind energy is a key strategy for mitigating global climate change. To support this goal, consistent global-scale datasets of existing wind turbines are essential for planning the future deployment of wind energy. Here, we introduce GOWIRES, a comprehensive global dataset of onshore wind turbines. GOWIRES provides detailed information on 416,417 horizontal-axis wind turbines (HAWT) across 89 countries. The dataset includes geographic coordinates, key technical specifications, and site-specific environmental characteristics for each wind turbine. In addition, GOWIRES provides historical (1989–2018) and future (2030–2059) site-specific wind resource data. Wind resources are characterized by mean wind speed, mean wind power density, Weibull parameters, power law exponents, and air density. Future Weibull parameters are based on simulations from 13 statistically downscaled global climate models under the SSP2-4.5 and SSP5-8.5 scenarios. GOWIRES is a valuable resource for energy and climate research, as well as for applications in wind energy development, grid and infrastructure planning, and policy-making.

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Cite This Study

Jung et al. (2026) studied this question.

synapsesocial.com/papers/69e9b85585696592c86eb9abhttps://doi.org/10.1038/s41597-026-07290-4
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