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Wavelet Scale Variance Analysis of Wind Extremes in Mountainous Terrains

Author

Listed:
  • Luciano Telesca

    (Institute of Methodologies for Environmental Analysis, National Research Council, 85050 Tito (PZ), Italy)

  • Fabian Guignard

    (IDYST, Faculty of Geosciences and Environment, University of Lausanne, CH-1015 Lausanne, Switzerland)

  • Nora Helbig

    (WSL Institute for Snow and Avalanche Research SLF, 7260 Davos, Switzerland)

  • Mikhail Kanevski

    (IDYST, Faculty of Geosciences and Environment, University of Lausanne, CH-1015 Lausanne, Switzerland)

Abstract

The 10-min average wind speed series recorded at 130 stations distributed rather homogeneously in the territory of Switzerland are investigated. Fixing a percentile-based threshold of the wind speed distribution, a wind extreme is defined as the duration of the sequence of consecutive wind values above the threshold. This definition allows to analyze the sequence of extremes as a temporal point process marked by their duration. Representing the sequence of wind extremes by the inter-extreme interval series, the wavelet variance, a useful tool to investigate the variance of a time series across scales, was applied in order to find a link between the wavelet scales and several topographic parameters. Our findings suggest that the mean duration of wind extremes and mean inter-extreme time are positively correlated and that such relationship depends on the threshold of the wind speed. Furthermore, the threshold of the wind speed distribution correlates best with a terrain parameter related to the Laplacian of terrain elevations; and, in particular, for wavelet scales less than 3, the terrain exposure may explain the formation of extreme wind speeds.

Suggested Citation

  • Luciano Telesca & Fabian Guignard & Nora Helbig & Mikhail Kanevski, 2019. "Wavelet Scale Variance Analysis of Wind Extremes in Mountainous Terrains," Energies, MDPI, vol. 12(16), pages 1-10, August.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:16:p:3048-:d:255672
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    References listed on IDEAS

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    5. Telesca, Luciano & Lovallo, Michele & Kanevski, Mikhail, 2016. "Power spectrum and multifractal detrended fluctuation analysis of high-frequency wind measurements in mountainous regions," Applied Energy, Elsevier, vol. 162(C), pages 1052-1061.
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    Cited by:

    1. Stefano Lodetti & Jorge Bruna & Julio J. Melero & José F. Sanz, 2019. "Wavelet Packet Decomposition for IEC Compliant Assessment of Harmonics under Stationary and Fluctuating Conditions," Energies, MDPI, vol. 12(22), pages 1-15, November.

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