Abstract
Abstract. Wind gusts are a key driver of aerodynamic loading, especially for tall structures such a bridges and wind turbines. However, gust characteristics in complex terrain are not well understood and common approximations used to describe wind gust behavior may not be appropriate at heights relevant to wind turbines and other structures. Data collected in the Perdigão experiment are analyzed herein to provide a foundation for improved wind gust characterization and process-level understanding of flow intermittency in complex terrain. High-resolution observations from sonic anemometers and vertically pointing Doppler lidars are used to conduct a detailed study of gust characteristics with a specific focus on the parent distributions of nine gust parameters (that describe velocity, time, and length scales), their joint distributions, height variation, and coherence in the vertical and horizontal planes. Best-fit distributional forms for varying gust properties show good agreement with those from previous experiments in moderately complex terrain but generate nonconservative estimates of the gust properties that are of key importance to structural loading. Probability distributions of gust magnitude derived from vertically pointing Doppler lidars exhibit good agreement with estimates from sonic anemometers despite differences arising from volumetric averaging and the terrain complexity. Wind speed coherence functions during gusty periods (which are important to structural wind loading) are similar to less complex sites for small vertical displacements (10 to 40 m), but do not exhibit an exponential form for larger horizontal displacements (800 to 1500 m).
Highlights
Introduction and objectivesTopographic channeling or enhancement of the near-surface flow can lead to local increases in wind speed (Wagenbrenner et al, 2016) and enhance the wind resource (Clifton et al, 2014; Barthelmie et al, 2016; Jubayer and Hangan, 2018)
The gust parameters and probability distributions used to describe the behavior of wind gusts in complex terrain are designed to mirror those used in Hu et al (2018), so that clear comparisons can be made between the results of the current study and those derived from measurements in less complex terrain
Consistent with measurements from moderately complex terrain (Hu et al, 2018), when Ugust is conditionally sampled for Umean > 3 m s−1, it is best fit by a lognormal distribution
Summary
Introduction and objectivesTopographic channeling or enhancement of the near-surface flow can lead to local increases in wind speed (Wagenbrenner et al, 2016) and enhance the wind resource (Clifton et al, 2014; Barthelmie et al, 2016; Jubayer and Hangan, 2018). Terrain inhomogeneity induces complex flow conditions (Wood, 2000), in the presence of vegetation (Suomi et al, 2013), that have implications for wind loading on structures, pollutant dispersion, wildfire propagation, and wind turbine siting and operation (Sanz Rodrigo et al, 2017; Wagenbrenner et al, 2016; Butler et al, 2015). Wind gusts represent an important source of structural engineering loads for tall buildings, towers, bridges, and wind turbines (Solari, 1987; IEC, 2005; Cheynet et al, 2016), and are known to be of larger magnitude in complex terrain due in part to the factors listed above (Tieleman, 1992; Verheij et al, 1992). The gust parameters and probability distributions used to describe the behavior of wind gusts in complex terrain are designed to mirror those used in Hu et al (2018), so that clear comparisons can be made between the results of the current study and those derived from measurements in less complex terrain
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