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Entropy 2016, 18(11), 408;

Global Atmospheric Dynamics Investigated by Using Hilbert Frequency Analysis

Departament de Física, Universitat Politècnica de Catalunya, Edifici Gaia, Terrassa, Barcelona 08222, Spain
Instituto de Física, Facultad de Ciencias, Universidad de la República, Iguá 4225, Montevideo 11400, Uruguay
Author to whom correspondence should be addressed.
Academic Editors: Raúl Alcaraz Martínez and Kevin H. Knuth
Received: 7 September 2016 / Revised: 19 October 2016 / Accepted: 14 November 2016 / Published: 16 November 2016
(This article belongs to the Special Issue Applications of Information Theory in the Geosciences)
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The Hilbert transform is a well-known tool of time series analysis that has been widely used to investigate oscillatory signals that resemble a noisy periodic oscillation, because it allows instantaneous phase and frequency to be estimated, which in turn uncovers interesting properties of the underlying process that generates the signal. Here we use this tool to analyze atmospheric data: we consider daily-averaged Surface Air Temperature (SAT) time series recorded over a regular grid of locations covering the Earth’s surface. From each SAT time series, we calculate the instantaneous frequency time series by considering the Hilbert analytic signal. The properties of the obtained frequency data set are investigated by plotting the map of the average frequency and the map of the standard deviation of the frequency fluctuations. The average frequency map reveals well-defined large-scale structures: in the extra-tropics, the average frequency in general corresponds to the expected one-year period of solar forcing, while in the tropics, a different behaviour is found, with particular regions having a faster average frequency. In the standard deviation map, large-scale structures are also found, which tend to be located over regions of strong annual precipitation. Our results demonstrate that Hilbert analysis of SAT time-series uncovers meaningful information, and is therefore a promising tool for the study of other climatological variables. View Full-Text
Keywords: time-series analysis; Hilbert transform; atmospheric phenomena; climate dynamics; variability; complex systems; external forcing; noise time-series analysis; Hilbert transform; atmospheric phenomena; climate dynamics; variability; complex systems; external forcing; noise

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Zappalà, D.A.; Barreiro, M.; Masoller, C. Global Atmospheric Dynamics Investigated by Using Hilbert Frequency Analysis. Entropy 2016, 18, 408.

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