Abstract This paper discusses different strategies for the extraction of the time-varying mean from wind speed time histories. Due to the advantage of allowing analytical evaluations, the attention is focused on kernel regression techniques, considering different weighting functions, namely a constant, a Gaussian and a cardinal sine weighting function. The problem is firstly treated analytically, and the frequency-domain properties of the filter associated to different kinds of weighting functions in the definition of the slowly varying mean through kernel regression are analysed. Then, different weighting functions are adopted for the analysis of digitally-simulated stationary wind speed time histories and for the time histories of thunderstorm outflows recorded by a tri-axial anemometer. The consequences of the adoption of different weighting functions on the harmonic content and statistical properties of turbulence are studied. The same features are found also for thunderstorm outflow records.

中文翻译：

---

静止和非静止风的时变平均提取

摘要 本文讨论了从风速时程中提取时变均值的不同策略。由于允许分析评估的优势，注意力集中在核回归技术上，考虑不同的加权函数，即常数、高斯和基数正弦加权函数。首先对该问题进行解析处理，分析了通过核回归定义缓变均值时与不同加权函数相关的滤波器的频域特性。然后，采用不同的加权函数来分析数字模拟的静止风速时程和三轴风速计记录的雷暴流出时程。研究了采用不同加权函数对湍流的谐波含量和统计特性的影响。雷暴流出记录也发现了相同的特征。