Abstract

Meandering is generally defined in terms of largevariation of the wind direction due to a complex mix of motions on scales between the main turbulent eddiesand the smallest mesoscale motions. There is not a general consensus on the physical causes of the motionsresponsible of the wind meandering during low-wind speed conditions. They include internal gravity waves,quasi-2D pancake motions, cold air drainage, solitons, vortices with either a horizontal axis or a vertical axis.In this work we present the analysis of wind and temperature data measured with two sonic anemometers ina low-wind stably stratified night observed during the Urban Turbulent Project (Torino, Italy). An originalapproach to estimate the meandering time scales of the wind velocity and temperature using two complementarymethodologies is proposed.In the literature the meandering time-scale is evaluated fitting the Eulerian auto-correlation functions of the windvelocity with an oscillating theoretical behaviour on hourly datasets. First we extend this method consideringthe dependence of the time-scale on the dataset length considering longer datasets (1, 2, 3, 4 hours) and then wecompare these results with a wavelet analysis. The continuous wavelet transform based on the Morlet basis isused to detect and characterize the time-scale of the wavelike oscillations both in the wind velocity and in thetemperature signals. Moreover cross-wavelet spectra are used to identify the nature of the wavy patterns in orderto discriminate the presence of gravity waves.The wavelet analysis corroborates the results obtained with the auto-correlation functions and opens newpromising perspectives for the study of the meandering phenomenon.

Autore Pugliese

• Cava Daniela

Tutti gli autori

• Mortarini L.; Cava D.; Giostra U.; Anfossi; D.

Titolo volume/Rivista

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Anno di pubblicazione

2016

ISSN

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ISBN

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Numero di citazioni Wos

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Settori ERC

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