Employing the Hilbert–Huang Transform to analyze observed natural complex signals: Calm wind meandering cases

Luis Gustavo Nogueira Martins, Michel Baptistella Stefanello, Gervásio Annes Degrazia, Otávio Costa Acevedo, Franciano Scremin Puhales, Giuliano Demarco, Luca Mortarini, Domenico Anfossi, Débora Regina Roberti, Felipe Denardin Costa and Silvana Maldaner

Physica A: Statistical Mechanics and its Applications, 2016, vol. 462, issue C, 1189-1196

Abstract: In this study we analyze natural complex signals employing the Hilbert–Huang spectral analysis. Specifically, low wind meandering meteorological data are decomposed into turbulent and non turbulent components. These non turbulent movements, responsible for the absence of a preferential direction of the horizontal wind, provoke negative lobes in the meandering autocorrelation functions. The meandering characteristic time scales (meandering periods) are determined from the spectral peak provided by the Hilbert–Huang marginal spectrum. The magnitudes of the temperature and horizontal wind meandering period obtained agree with the results found from the best fit of the heuristic meandering autocorrelation functions. Therefore, the new method represents a new procedure to evaluate meandering periods that does not employ mathematical expressions to represent observed meandering autocorrelation functions.

Keywords: Natural complex signals; Wind meandering; Hilbert–Huang Transform; Low-wind; Stable boundary layer (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:462:y:2016:i:c:p:1189-1196

DOI: 10.1016/j.physa.2016.06.147

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