Guignard Fabian, Mauree Dasaraden, Lovallo Michele, Kanevski Mikhail, Telesca Luciano
IDYST, Faculty of Geosciences and Environment, University of Lausanne, CH-1015 Lausanne, Switzerland.
Solar Energy and Building Physics Laboratory, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland.
Entropy (Basel). 2019 Jan 10;21(1):47. doi: 10.3390/e21010047.
One-hertz wind time series recorded at different levels (from 1.5-25.5 m) in an urban area are investigated by using the Fisher-Shannon (FS) analysis. FS analysis is a well-known method to gain insight into the complex behavior of nonlinear systems, by quantifying the order/disorder properties of time series. Our findings reveal that the FS complexity, defined as the product between the Fisher information measure and the Shannon entropy power, decreases with the height of the anemometer from the ground, suggesting a height-dependent variability in the order/disorder features of the high-frequency wind speed measured in urban layouts. Furthermore, the correlation between the FS complexity of wind speed and the daily variance of the ambient temperature shows a similar decrease with the height of the wind sensor. Such correlation is larger for the lower anemometers, indicating that ambient temperature is an important forcing of the wind speed variability in the vicinity of the ground.
利用Fisher-Shannon（FS）分析方法，对在城市区域不同高度（1.5 - 25.5米）记录的1赫兹风时间序列进行了研究。FS分析是一种通过量化时间序列的有序/无序特性来深入了解非线性系统复杂行为的著名方法。我们的研究结果表明，FS复杂度定义为Fisher信息测度与Shannon熵功率的乘积，它随着风速仪离地面高度的增加而降低，这表明在城市布局中测量的高频风速的有序/无序特征存在高度依赖性变化。此外，风速的FS复杂度与环境温度日变化之间的相关性也随风速传感器高度的增加而呈现类似的下降趋势。对于较低高度的风速仪，这种相关性更大，这表明环境温度是地面附近风速变化的一个重要驱动力。
