Improving the Estimation of Extreme Wind Speeds

Extreme winds derived from simulations using mesoscale models are underestimated due to the effective spatial and temporal resolutions. This is reflected in the spectral domain as an energy deficit in the mesoscale range. This phenomenon has been investigated from the Wind Energy Division departmnent at the National Laboratory of Denmark. Their investigation reveals that the energy deficit, implies smaller spectral moments and thus, an underestimation in the extreme wind speed estimation. By taking into account the difference between the modeled and measured wind spectra in the high frequency range, two approaches for correcting the smoothing effect have been presented in their study report named Recipes for correcting the impact of effective mesoscale resolution on the estimation of extreme winds . In this article, we prsent a comparative evaluation and improvement proposals on the Mesoscale Models extreme wind speed prognosis. However, further investigation is suggested for a much more holistic approach.

Abstract

To establish an accurate and reliable wind climatology, the implementation of mesoscale meteorological models, requires a thorough understanding of the critical parameters and the synergistic interactions involved during the simulation and modeling process. However, because of the averaging spatial and temporal resolution effects, modelled winds are smeared out in a non-homogeneous continuum. The spectrum domain analysis, illustrates a critical energy deficit in the mesoscale range and thus an underestimation of the extreme wind speeds is revealed. This paper provides evidence about the critical difference between the measured and simulated spectrum in the mesoscale range and re-validate the extreme wind speeds variability under-prediction as it is observed from a similar study from RISØ-DTU. We also propose potential solutions to improve the spectral correction approach. While the investigation results are promising, further research is needed to build ever more precise and persuasive methodologies and determine the efficacy and applicability of these methods.