Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Prolonged wind droughts in a warming climate threaten global wind power security

Abstract

Prolonged low-wind events, termed wind droughts, threaten wind turbine electricity generation, yet their future trajectories remain poorly understood. Here, using hourly data from 21 IPCC models, we reveal robust increasing trends in wind drought duration at both global and regional scales by 2100, across low- and high-CO2 scenarios. These trends are primarily driven by declining mid-latitude cyclone frequencies and Arctic warming. Notably, the duration of 25-year return events is projected to increase by up to 20% under low warming scenarios and 40% under very high warming scenarios in northern mid-latitude countries, threatening energy security in these densely populated areas. Additionally, record-breaking wind drought extremes will probably become more frequent in a warming climate, particularly in eastern North America, western Russia, northeastern China and north-central Africa. Our analysis suggests that ~20% of existing wind turbines are in regions at high future risk of record-breaking wind drought extremes, a factor not yet considered in current assessments.

This is a preview of subscription content, access via your institution

Access options

Buy this article

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Reported wind droughts worldwide in the past decades and definition of wind droughts.
Fig. 2: Changes in WDF and duration from 2015 to 2100.
Fig. 3: Drivers of future changes in WDD.
Fig. 4: Record-breaking wind droughts.
Fig. 5: Current wind turbines locations and their future risk of RWD.

Similar content being viewed by others

Data availability

All the data used in this study are available online via the following links. The data for quantifying wind drought changes are available via the ERA5 at https://doi.org/10.24381/cds.adbb2d47 (ref. 66) and the MERRA2 at https://doi.org/10.5067/VJAFPLI1CSIV (ref. 67). Projected wind drought changes in CMIP6 are available at the Program for Climate Model Diagnosis and Intercomparison (https://aims2.llnl.gov/search). The land-cover map was obtained from the MCD12C1 (https://doi.org/10.5067/MODIS/MCD12C1.006) and the Ecoregions 2017 (https://ecoregions.appspot.com). The terrain elevation is from GTOPO30 at https://doi.org/10.5066/F7DF6PQS. Global wind power density was derived from the Global Wind Atlas (https://globalwindatlas.info/en/download/gis-files). The global dataset of wind farm locations and power are available via Figshare at https://doi.org/10.6084/m9.figshare.11310269.v2 (ref. 85). All data generated in this study are available via the Peking University Open Research Data Platform at https://doi.org/10.18170/DVN/50VDAL (ref. 86).

Code availability

All codes used in this study are available via the Peking University Open Research Data Platform at https://doi.org/10.18170/DVN/50VDAL (ref. 86).

References

  1. Antonini, E. G. A. et al. Identification of reliable locations for wind power generation through a global analysis of wind droughts. Commun. Earth Environ. 5, 103 (2024).

    Article  Google Scholar 

  2. ECHO. 31 January 2014: Eastern–Central Europe—Severe Weather. Reliefweb https://reliefweb.int/map/romania/31-january-2014-eastern-central-europe-severe-weather (2014).

  3. Robbins, J. Gone with the winds? What happens if there is a ‘global terrestrial stilling’. Bulletin of the Atomic Scientists https://thebulletin.org/2022/09/gone-with-the-winds-what-happens-if-there-is-a-global-terrestrial-stilling/ (2022).

  4. Ram, R. S. What is behind the curious decline in generation of renewable energy. mint www.livemint.com/market/mark-to-market/what-is-behind-the-curious-decline-in-generation-of-renewable-energy-11569864546939.html (2019).

  5. Staffell, I., Green, R., Green, T. & Jansen, M. Q1 (2021). Electric Insights Quarterly Reports https://reports.electricinsights.co.uk/reports/q1-2021/ (2021)

  6. Pechlivanidis, I. et al. Benchmarking Skill Assessment of Current Sub-Seasonal and Seasonal Forecast Systems for Users’ Selected Case Studies (S2S4E, 2019); https://s2s4e.eu/sites/default/files/2020-06/s2s4e_d41.pdf

  7. Truyts, J. & Vandervelden, J. België telde negen dagen ‘Dunkelflaute’ in januari. vrtnws.be www.vrt.be/vrtnws/nl/2017/02/24/belgie_telde_negendagendunkelflauteinjanuari-1-2900900/ (2017).

  8. Li, B., Basu, S., Watson, S. J. & Russchenberg, H. W. J. A brief climatology of Dunkelflaute events over and surrounding the North and Baltic Sea areas. Energies 14, 6508 (2021).

    Article  Google Scholar 

  9. Wetzel, D. Die, Dunkelflaute‘ bringt Deutschlands Stromversorgung ans Limit. WELT www.welt.de/wirtschaft/article161831272/Die-Dunkelflaute-bringt-Deutschlands-Stromversorgung-ans-Limit.html (2017).

  10. Li, B., Basu, S., Watson, S. J. & Russchenberg, H. W. J. Quantifying the predictability of a ‘Dunkelflaute’ event by utilizing a mesoscale model. J. Phys. Conf. Ser. 1618, 062042 (2020).

    Article  Google Scholar 

  11. Bloomfield, H. What Europe’s exceptionally low winds mean for the future energy grid. The Conversation http://theconversation.com/what-europes-exceptionally-low-winds-mean-for-the-future-energy-grid-170135 (2021).

  12. Rife, D., Krakauer, N., Cohan, D. & Collier, C. A new kind of drought: U.S. record low windiness in 2015. Earthzine https://earthzine.org/a-new-kind-of-drought-u-s-record-low-windiness-in-2015/ (2016).

  13. Lledó, L., Bellprat, O., Doblas-Reyes, F. J. & Soret, A. Investigating the effects of Pacific sea surface temperatures on the wind drought of 2015 over the United States. J. Geophys. Res. Atmos. 123, 4837–4849 (2018).

    Article  Google Scholar 

  14. Hingtgen, J., Le, D., Davis, B. & Huang, B. Productivity and Status of Wind Generation in California (California Energy Commission, 2019). https://doi.org/10.13140/RG.2.2.35900.90244

  15. The February 2021 Cold Weather Outages in Texas and the South Central United States (FERC, 2021); www.ferc.gov/media/february-2021-cold-weather-outages-texas-and-south-central-united-states-ferc-nerc-and

  16. Liu, F., Wang, X., Sun, F. & Wang, H. Wind resource droughts in China. Environ. Res. Lett. 18, 094015 (2023).

    Article  Google Scholar 

  17. Ohba, M., Kanno, Y. & Bando, S. Effects of meteorological and climatological factors on extremely high residual load and possible future changes. Renew. Sust. Energ. Rev. 175, 113188 (2023).

    Article  Google Scholar 

  18. Ohba, M., Kanno, Y. & Nohara, D. Climatology of dark doldrums in Japan. Renew. Sust. Energ. Rev. 155, 111927 (2022).

    Article  Google Scholar 

  19. Shekhar, J., Saji, S., Agarwal, D., Ahmed, A. & Joseph, T. Assessing and Planning for Variability in India’s Wind Resource (CEEW, 2021); www.ceew.in/publications/studying-the-impact-of-unexpected-climate-change-on-wind-energy-sector-in-india

  20. Dawkins, L. C. Weather and Climate Related Sensitivities and Risks in a Highly Renewable UK Energy System: A Literature Review (Met Office, 2019).

  21. Zheng, D. et al. Climate change impacts on the extreme power shortage events of wind–solar supply systems worldwide during 1980–2022. Nat. Commun. 15, 5225 (2024).

    Article  CAS  Google Scholar 

  22. Future of Wind: Deployment, Investment, Technology, Grid Integration and Socio-Economic Aspects (International Renewable Energy Agency, 2019).

  23. Martinez, A. & Iglesias, G. Global wind energy resources decline under climate change. Energy 288, 129765 (2024).

    Article  Google Scholar 

  24. Pryor, S. C., Barthelmie, R. J., Bukovsky, M. S., Leung, L. R. & Sakaguchi, K. Climate change impacts on wind power generation. Nat. Rev. Earth Environ. 1, 627–643 (2020).

    Article  Google Scholar 

  25. Pryor, S. C., Barthelmie, R. J. & Kjellström, E. Potential climate change impact on wind energy resources in northern Europe: analyses using a regional climate model. Clim. Dynam. 25, 815–835 (2005).

    Article  Google Scholar 

  26. Reyers, M., Moemken, J. & Pinto, J. G. Future changes of wind energy potentials over Europe in a large CMIP5 multi-model ensemble. Int. J. Climatol. 36, 783–796 (2016).

    Article  Google Scholar 

  27. Hueging, H., Haas, R., Born, K., Jacob, D. & Pinto, J. G. Regional changes in wind energy potential over Europe using regional climate model ensemble projections. J. Appl. Meteorol. Climatol. 52, 903–917 (2013).

    Article  Google Scholar 

  28. Tobin, I. et al. Assessing climate change impacts on European wind energy from ENSEMBLES high-resolution climate projections. Clim. Change 128, 99–112 (2015).

    Article  Google Scholar 

  29. Pryor, S. C., Barthelmie, R. J. & Schoof, J. T. Past and future wind climates over the contiguous USA based on the North American Regional Climate Change Assessment Program model suite. J. Geophys. Res. Atmos. https://doi.org/10.1029/2012JD017449 (2012).

  30. Greene, J. S., Chatelain, M., Morrissey, M. & Stadler, S. Projected future wind speed and wind power density trends over the western US High Plains. Atmos. Clim. Sci. 02, 32–40 (2012).

    Google Scholar 

  31. Pryor, S. C., Shepherd, T. J., Bukovsky, M. & Barthelmie, R. J. Assessing the stability of wind resource and operating conditions. J. Phys. Conf. Ser. 1452, 012084 (2020).

    Article  Google Scholar 

  32. Karnauskas, K. B., Lundquist, J. K. & Zhang, L. Southward shift of the global wind energy resource under high carbon dioxide emissions. Nat. Geosci. 11, 38–43 (2018).

    Article  CAS  Google Scholar 

  33. IPCC. Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) (Cambridge Univ. Press, 2021).

  34. Zha, J. et al. Projected changes in global terrestrial near-surface wind speed in 1.5 °C–4.0 °C global warming levels. Environ. Res. Lett. 16, 114016 (2021).

    Article  Google Scholar 

  35. Deng, K., Azorin-Molina, C., Minola, L., Zhang, G. & Chen, D. Global near-surface wind speed changes over the last decades revealed by reanalyses and CMIP6 model simulations. J. Clim. 34, 2219–2234 (2021).

    Article  Google Scholar 

  36. Russo, M. A., Carvalho, D., Martins, N. & Monteiro, A. Future perspectives for wind and solar electricity production under high-resolution climate change scenarios. J. Clean. Prod. 404, 136997 (2023).

    Article  Google Scholar 

  37. Claro, A., Santos, J. A. & Carvalho, D. Assessing the future wind energy potential in Portugal using a CMIP6 model ensemble and WRF high-resolution simulations. Energies 16, 661 (2023).

    Article  Google Scholar 

  38. Carvalho, D., Rocha, A., Costoya, X., deCastro, M. & Gómez-Gesteira, M. Wind energy resource over Europe under CMIP6 future climate projections: what changes from CMIP5 to CMIP6. Renew. Sust. Energ. Rev. 151, 111594 (2021).

    Article  Google Scholar 

  39. deCastro, M. et al. An overview of offshore wind energy resources in Europe under present and future climate. Ann. NY Acad. Sci. 1436, 70–97 (2019).

    Article  Google Scholar 

  40. Haupt, S. E. et al. A method to assess the wind and solar resource and to quantify interannual variability over the United States under current and projected future climate. J. Appl. Meteorol. Climatol. 55, 345–363 (2016).

    Article  Google Scholar 

  41. Hersbach, H. et al. The ERA5 global reanalysis. Q. J. R. Meteorol. Soc. 146, 1999–2049 (2020).

    Article  Google Scholar 

  42. Gelaro, R. et al. The modern-era retrospective analysis for research and applications, version 2 (MERRA-2). J. Clim. 30, 5419–5454 (2017).

    Article  Google Scholar 

  43. Eyring, V. et al. Overview of the coupled model intercomparison project phase 6 (CMIP6) experimental design and organization. Geosci. Model Dev. 9, 1937–1958 (2016).

    Article  Google Scholar 

  44. O’Neill, B. C. et al. The scenario model intercomparison project (ScenarioMIP) for CMIP6. Geosci. Model Dev. 9, 3461–3482 (2016).

    Article  Google Scholar 

  45. Brown, P. T., Farnham, D. J. & Caldeira, K. Meteorology and climatology of historical weekly wind and solar power resource droughts over western North America in ERA5. SN Appl. Sci. 3, 814 (2021).

    Article  Google Scholar 

  46. Davis, N. N. et al. The global wind atlas: a high-resolution dataset of climatologies and associated web-based application. Bull. Am. Meteorol. Soc. 104, E1507–E1525 (2023).

    Article  Google Scholar 

  47. Seltzer, A. M., Blard, P.-H., Sherwood, S. C. & Kageyama, M. Terrestrial amplification of past, present, and future climate change. Sci. Adv. 9, eadf8119 (2023).

    Article  Google Scholar 

  48. Rudeva, I., Gulev, S. K., Simmonds, I. & Tilinina, N. The sensitivity of characteristics of cyclone activity to identification procedures in tracking algorithms. Tellus A 66, 24961 (2014).

    Article  Google Scholar 

  49. McCabe, G. J., Clark, M. P. & Serreze, M. C. Trends in Northern Hemisphere surface cyclone frequency and intensity. J. Clim. 14, 2763–2768 (2001).

    Article  Google Scholar 

  50. Chang, E. K. M., Ma, C., Zheng, C. & Yau, A. M. W. Observed and projected decrease in Northern Hemisphere extratropical cyclone activity in summer and its impacts on maximum temperature. Geophys. Res. Lett. 43, 2200–2208 (2016).

    Article  Google Scholar 

  51. Gentile, E. S., Zhao, M. & Hodges, K. Poleward intensification of midlatitude extreme winds under warmer climate. npj Clim. Atmos. Sci. 6, 219 (2023).

  52. Tamarin-Brodsky, T. & Kaspi, Y. Enhanced poleward propagation of storms under climate change. Nat. Geosci. 10, 908–913 (2017).

    Article  CAS  Google Scholar 

  53. Seo, K.-H. et al. What controls the interannual variation of Hadley cell extent in the Northern Hemisphere: physical mechanism and empirical model for edge variation. npj Clim. Atmos. Sci. 6, 204 (2023).

    Article  Google Scholar 

  54. Shaw, T. A. et al. Storm track processes and the opposing influences of climate change. Nat. Geosci. 9, 656–664 (2016).

    Article  CAS  Google Scholar 

  55. Thompson, V. et al. The most at-risk regions in the world for high-impact heatwaves. Nat. Commun. 14, 2152 (2023).

    Article  CAS  Google Scholar 

  56. Fischer, E. M., Sippel, S. & Knutti, R. Increasing probability of record-shattering climate extremes. Nat. Clim. Change 11, 689–695 (2021).

    Article  CAS  Google Scholar 

  57. Dunnett, S., Sorichetta, A., Taylor, G. & Eigenbrod, F. Harmonised global datasets of wind and solar farm locations and power. Sci. Data 7, 130 (2020).

    Article  Google Scholar 

  58. Pryor, S. C., Nikulin, G. & Jones, C. Influence of spatial resolution on regional climate model derived wind climates. J. Geophys. Res. Atmos. 117, 2011JD016822 (2012).

    Article  Google Scholar 

  59. Gutowski, W. J. Jr. et al. WCRP COordinated Regional Downscaling EXperiment (CORDEX): a diagnostic MIP for CMIP6. Geosci. Model Dev. 9, 4087–4095 (2016).

    Article  Google Scholar 

  60. Lake, I., Gutowski, W., Giorgi, F. & Lee, B. CORDEX: climate research and information for regions. Bull. Am. Meteorol. Soc. 98, ES189–ES192 (2017).

    Article  Google Scholar 

  61. Chen, X. et al. Pathway toward carbon-neutral electrical systems in China by mid-century with negative CO2 abatement costs informed by high-resolution modeling. Joule 5, 2715–2741 (2021).

    Article  CAS  Google Scholar 

  62. Richardson, D., Pitman, A. J. & Ridder, N. N. Climate influence on compound solar and wind droughts in Australia. npj Clim. Atmos. Sci. 6, 184 (2023).

    Article  Google Scholar 

  63. Gernaat, D. E. H. J. et al. Climate change impacts on renewable energy supply. Nat. Clim. Change 11, 119–125 (2021).

    Article  Google Scholar 

  64. Chen, W.-H. & Hsieh, I.-Y. L. Techno-economic analysis of lithium-ion battery price reduction considering carbon footprint based on life cycle assessment. J. Clean. Prod. 425, 139045 (2023).

    Article  CAS  Google Scholar 

  65. Staffell, I. et al. The role of hydrogen and fuel cells in the global energy system. Energy Environ. Sci. 12, 463–491 (2019).

    Article  CAS  Google Scholar 

  66. ERA5: Fifth Generation of ECMWF Atmospheric Reanalyses of the Global Climate (Copernicus Climate Data Store, accessed 8 May 2023); https://doi.org/10.24381/cds.adbb2d47

  67. MERRA-2 tavg1_2d_slv_Nx: 2d,1-Hourly, Time-Averaged, Single-Level, Assimilation,Single-Level Diagnostics V5.12.4 (GES DISC, accessed 28 October 2022); https://doi.org/10.5067/VJAFPLI1CSIV

  68. Jourdier, B. Evaluation of ERA5, MERRA-2, COSMO-REA6, NEWA and AROME to simulate wind power production over France. Adv. Sci. Res. 17, 63–77 (2020).

    Article  Google Scholar 

  69. Olauson, J. ERA5: The new champion of wind power modelling? Renew. Energy 126, 322–331 (2018).

    Article  Google Scholar 

  70. General Electric GE 2.5-120. Wind-turbine-models.com https://en.wind-turbine-models.com/turbines/310-ge-vernova-ge-2.5-120 (2018).

  71. Gao, M. et al. Secular decrease of wind power potential in India associated with warming in the Indian Ocean. Sci. Adv. 4, eaat5256 (2018).

    Article  Google Scholar 

  72. Archer, C. L. & Jacobson, M. Z. Evaluation of global wind power. J. Geophys. Res. 110, D12110 (2005).

    Google Scholar 

  73. Walton, R. A., Takle, E. S. & Gallus, W. A. Characteristics of 50–200-m winds and temperatures derived from an Iowa tall-tower network. J. Appl. Meteorol. Climatol. 53, 2387–2393 (2014).

    Article  Google Scholar 

  74. Friedl, M. & Sulla-Menashe, D. MCD12C1 MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 0.05Deg CMG V006 (NASA Land Processes Distributed Active Archive Center, accessed 20 January 2023); https://doi.org/10.5067/MODIS/MCD12C1.006

  75. Greene, C. A., Blankenship, D. D., Gwyther, D. E., Silvano, A. & van Wijk, E. Wind causes Totten Ice Shelf melt and acceleration. Sci. Adv. 3, e1701681 (2017).

    Article  Google Scholar 

  76. Cushing, L. J., Li, S., Steiger, B. B. & Casey, J. A. Historical red-lining is associated with fossil fuel power plant siting and present-day inequalities in air pollutant emissions. Nat. Energy 8, 52–61 (2023).

    Article  Google Scholar 

  77. Deng, K. et al. The offshore wind speed changes in China: an insight into CMIP6 model simulation and future projections. Clim. Dynam. 62, 3305–3319 (2024).

    Article  Google Scholar 

  78. Pryor, S. C. & Barthelmie, R. J. A global assessment of extreme wind speeds for wind energy applications. Nat. Energy 6, 268–276 (2021).

    Article  Google Scholar 

  79. Zeng, Z. et al. A reversal in global terrestrial stilling and its implications for wind energy production. Nat. Clim. Change 9, 979–985 (2019).

    Article  Google Scholar 

  80. Eyring, V. et al. Reflections and projections on a decade of climate science. Nat. Clim. Change 11, 279–285 (2021).

    Article  Google Scholar 

  81. Tong, Y. et al. Bias correction of temperature and precipitation over China for RCM simulations using the QM and QDM methods. Clim. Dynam. 57, 1425–1443 (2021).

    Article  Google Scholar 

  82. Potisomporn, P., Adcock, T. A. A. & Vogel, C. R. Extreme value analysis of wind droughts in Great Britain. Renew. Energy 221, 119847 (2024).

    Article  Google Scholar 

  83. Coles, S. An Introduction to Statistical Modeling of Extreme Values (Springer, 2001).

  84. Shiau, J. T. Return period of bivariate distributed extreme hydrological events. Stoch. Environ. Res. Risk Assess. 17, 42–57 (2003).

    Article  Google Scholar 

  85. Dunnett, S. Harmonised global datasets of wind and solar farm locations and power. figshare https://doi.org/10.6084/m9.figshare.11310269.v2 (2020).

  86. Meng, Q. Prolonged wind droughts in a warming climate threaten global wind power security. Peking University Open Research Data Platform https://doi.org/10.18170/DVN/50VDAL (2024).

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (42275194) and National Key Research and Development Programme of China (2023YFC3707404).

Author information

Authors and Affiliations

Authors

Contributions

L.S. designed the experiments and M.Q. carried them out. Z.Z. and B.Y. contributed to the data analysis. H.Z., X.Y. and X.L. contributed to the result interpretation. M.Q. and L.S. prepared the paper with contributions from all co-authors.

Corresponding author

Correspondence to Lu Shen.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Climate Change thanks David Carvalho, Sue Ellen Haupt and Eugene Takle for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Notes 1–5, Figs. 1–19 and Tables 1–5.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Qu, M., Shen, L., Zeng, Z. et al. Prolonged wind droughts in a warming climate threaten global wind power security. Nat. Clim. Chang. 15, 842–849 (2025). https://doi.org/10.1038/s41558-025-02387-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41558-025-02387-x

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing