The Application of Hilbert-Huang Transforms to Meteorological Datasets

Abstract Recently a new spectral technique has been developed for the analysis of aperiodic signals from nonlinear systems—the Hilbert–Huang transform. It is shown how this transform can be used to discover synoptic and climatic features: For sea level data, the transforms capture the oceanic tides as well as variations in precipitation patterns. In the case of solar radiation, variations in the diurnal and seasonal cycles are observed. Finally, from barographic data, the Hilbert–Huang transform reveals the passage of extratropical cyclones, fronts, and troughs. Thus, this technique can detect signals on synoptic to interannual time scales.

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