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A global assessment of extreme wind speeds for wind energy applications


Cost-effective expansion of the wind energy industry benefits from robust estimates of wind resource and operating conditions. Extreme design loads contribute to wind turbine selection and cost, and are determined in part by the fifty year return period sustained wind speed (U50). Here we derive a global, homogenized and geospatially explicit digital atlas of U50 and associated confidence intervals based on ERA5 reanalysis output at wind turbine hub heights. U50 estimates derived using ERA5 output and four different methods are shown to lie within an average of 9–13% of those from point measurements. The reference wind speed (Uref) derived using five times the mean wind speed as specified in the wind turbine design standards is generally a conservative estimate of U50. Particularly after application of additional safety factors, this may result in over-engineering of wind turbines and excess capital expenditures.

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Fig. 1: Installed capacity of wind turbines by country as of the end of 2019.
Fig. 2: Extreme sustained wind speed estimates (m s−1) at 100 m a.g.l. in each ERA5 grid cell computed using hourly output during 1979–2018.
Fig. 3: Divergence between Uref and U50 estimates.
Fig. 4: Uref and U50 for Weibull-distributed wind speeds.
Fig. 5: Scatterplots of the median and 10th to 90th percentile U50 or Uref estimates from the different approaches.
Fig. 6: Evaluation of Uref and U50 from ERA5 output relative to observations.
Fig. 7: Evaluation of the stationarity of U50 estimates.

Data availability

ERA5 data are available from Netcdf files containing the digital atlas are available for download from ZENODO ( An Excel spreadsheet containing U50 estimates from in situ observations is given as Supplementary Data 1.

Code availability

Matlab code used to compute Uref and U50 estimates can be downloaded from ZENODO at


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This work is supported by the US Department of Energy (DE-SC0016438 and DE-SC0016605). The research used computing resources from the National Science Foundation: Extreme Science and Engineering Discovery Environment (allocation award to S.C.P. is TG-ATM170024). We gratefully acknowledge the European Center for Medium Range Weather Forecasts staff who generated and support dissemination of the ERA5 data set, and the comments from four external reviewers.

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S.C.P. and R.J.B. jointly derived the concept for the research and obtained funding for the research. S.C.P. acquired the computational resources and developed and applied the research methodology and generated all figures. The authors jointly wrote the manuscript.

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Correspondence to Sara C. Pryor.

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Peer review information Nature Energy thanks Andrew Clifton, Julia Gottschall, Xiaoli Guo Larsén and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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

Supplementary information

Supplementary Data 1

Seventy-three observationally derived estimates of extreme wind speeds.

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

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