In this paper, high frequency wind time series measured at different heights from the ground (from 5.5 to 25.5 m) 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. (C) 2019 Elsevier Ltd. All rights reserved.

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

Telesca Luciano;
2019

Abstract

In this paper, high frequency wind time series measured at different heights from the ground (from 5.5 to 25.5 m) 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. (C) 2019 Elsevier Ltd. All rights reserved.
2019
Istituto di Metodologie per l'Analisi Ambientale - IMAA
High frequency wind
Detrended fluctuation analysis
Time series
Magnitude and sign decomposition
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/388908
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