In the last decades, interest in the analysis of nonstationary and nonlinear signals has massively increased. However, many classical analysis techniques, such as Fourier and Wavelet Transforms, fail to capture the fundamental characteristics of these kind of time series.
After a brief introduction to the main physical characteristics of tsunami events, the recently developed Iterative Filtering technique is presented and applied to the decomposition of tsunami signals from pressure and tide gauges. It is shown how these signals are successfully decomposed into components of different physical origins. Then, the time-frequency representation of these time series is obtained by using the IMFogram algorithm, which computes instantaneous amplitudes and frequencies for the previously obtained components. Finally, possible applications to tsunami science are discussed, such as possible applications to real time detection in early warning context.
Cesare Angeli is a PhD student in Department of Physics and Astronomy at the University of Bologna.