Articles | Volume 27, issue 2
https://doi.org/10.5194/npg-27-239-2020
https://doi.org/10.5194/npg-27-239-2020
Research article
 | 
23 Apr 2020
Research article |  | 23 Apr 2020

Vertical profiles of wind gust statistics from a regional reanalysis using multivariate extreme value theory

Julian Steinheuer and Petra Friederichs

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Cited articles

Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer, M., and Reinhardt, T.: Operational Convective-Scale Numerical Weather Prediction with the COSMO Model: Description and Sensitivities, Mon. Weather Rev., 139, 3887–3905, https://doi.org/10.1175/MWR-D-10-05013.1, 2011. a
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Bentzien, S. and Friederichs, P.: Decomposition and graphical portrayal of the quantile score, Q. J. Roy. Meteor. Soc., 140, 1924–1934, https://doi.org/10.1002/qj.2284, 2014. a, b
Bollmeyer, C., Keller, J. D., Ohlwein, C., Wahl, S., Crewell, S., Friederichs, P., Hense, A., Keune, J., Kneifel, S., Pscheidt, I., Redl, S., and Steinke, S.: Towards a high-resolution regional reanalysis for the European CORDEX domain, Q. J. Roy. Meteor. Soc., 141, 1–15, https://doi.org/10.1002/qj.2486, 2014. a, b, c
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Many applications require wind gust estimates at very different atmospheric altitudes, such as in the wind energy sector. However, numerical weather prediction models usually only derive estimates for gusts at 10 m above the land surface. We present a statistical model that gives the hourly peak wind speed. The model is trained based on a weather reanalysis and observations from the Hamburg Weather Mast. Reliable predictions are derived at up to 250 m, even at unobserved intermediate levels.