Linearity versus non-linearity in high frequency multilevel wind time series measured in urban areas

TL;DR

This study analyzes high-frequency urban wind speed data at various heights, revealing power-law spectral behavior and different linear and nonlinear dynamics across timescales, with implications for understanding urban wind fluctuations.

Contribution

It provides new insights into the linear and nonlinear characteristics of high-frequency wind speed time series at different heights in urban environments.

Findings

Spectral exponent around 1.5, consistent with Kolmogorov turbulence.

Distinct timescale ranges for sign and magnitude series.

Magnitude scaling exponent varies with sensor height.

Abstract

In this paper, high frequency wind time series measured at different heights from the ground (from 5.5 to 25.5 meters) in an urban area were investigated. The spectrum of each series is characterized by a power-law behaviour at low frequency range, with a mean spectral exponent of about 1.5, which is rather consistent with the Kolmogorov spectrum of atmospheric turbulence. The detrended fluctuation analysis was applied on the magnitude and sign series of the increments of wind speed, in order to get information about the linear and nonlinear dynamics of the time series. Both the sign series and magnitude series are characterized by two timescale ranges; in particular the scaling exponent of the magnitude series in the high timescale range seems to be related with the height of the sensor. This study aims to understand better high frequency wind speed in urban areas and to disclose the underlying mechanism governing the wind fluctuations at different heights.