Michele Lovallo

Analysis of the time dynamics in wind records by means of multifractal detrended fluctuation analysis and the Fisher?Shannon information plane

The time structure of more than 10 years of hourly wind data measured in one site in northern Italy from April 1996 to December 2007 is analysed. The data are recorded by the Sodar Rass system, which measures the speed and the direction of the wind at several heights above the ground level. To investigate the wind speed time series at seven heights above the ground level we used two different approaches: i) the Multifractal Detrended Fluctuation Analysis (MF-DFA), which permits the detection of multifractality in nonstationary series, and ii) the Fisher-Shannon (FS) information plane, which allows to discriminate dynamical features in complex time series. Our results point out to the existence of multifractal time fluctuations in wind speed and to a dependence of the results on the height of the wind sensor. Even in the FS information plane a height-dependent pattern is revealed, indicating a good agreement with the multifractality. The obtained results could contribute to a better understanding of the complex dynamics of wind phenomenon.

Complexity measures and information planes of x-ray astrophysical sources

The complex dynamics of x-ray astrophysical sources is investigated by analyzing their daily light curves in four different energy bands by using three information-theoretic measures: Fisher information measure, the Shannon entropy and the disequilibrium. The obtained results suggest a universal complex behavior in the x-ray light, independent of the source and of the energy band.

Revealing competitive behaviours in music by means of the multifractal detrended fluctuation analysis: application to Bach's Sinfonias

The one-, two- and three-dimensional multifractal detrended fluctuation analysis (MF-DFA) was applied to Bachs Sinfonias, which are characterized by the superposition of three different voices. Each voice, represented as a time series, can be considered as a component of a one-, two- or three-dimensional vector. The one-dimensional MF-DFA was applied to any single voice, while the two- and three-dimensional MF-DFA was applied to the couples of voices and to the triple, respectively. Each voice is characterized by a multifractal degree (MD), indicated by the range of the generalized Hurst exponents; the higher the MD, the larger the amount of heterogeneity and irregularity. Competitive scaling multifractal behaviours in Bachs Sinfonias were revealed; although one (or two) voices showed a relatively high MD, the other two voices, or voice, are characterized by a low MD. Nevertheless, the overall effect of the Sinfonia, measured by the MD of the triple, tends towards homogeneity, or at least to an average between the different competitive scaling behaviour shown by the different voices.

Relationship between the Frequency Magnitude Distribution and the Visibility Graph in the Synthetic Seismicity Generated by a Simple Stick-Slip System with Asperities

By using the method of the visibility graph (VG) the synthetic seismicity generated by a simple stick–slip system with asperities is analysed. The stick–slip system mimics the interaction between tectonic plates, whose asperities are given by sandpapers of different granularity degrees. The VG properties of the seismic sequences have been put in relationship with the typical seismological parameter, the b-value of the Gutenberg-Richter law. Between the b-value of the synthetic seismicity and the slope of the least square line fitting the k-M plot (relationship between the magnitude M of each synthetic event and its connectivity degree k) a close linear relationship is found, also verified by real seismicity.

Visibility Graph Analysis of the 2003–2012 Earthquake Sequence in the Kachchh Region of Western India

A visibility graph (VG) is a rather novel statistical method in earthquake sequence analysis; it maps a time series into networks or graphs, converting dynamical properties of the time series into topological properties of networks. By using the VG approach, we defined the parameter window mean interval connectivity time , that informs about the mean linkage time between earthquakes. We analysed the time variation of in the aftershock-depleted catalogue of Kachchh Gujarat (Western India) seismicity from 2003 to 2012, and we found that : i) changes through time, indicating that the topological properties of the earthquake network are not stationary; and, ii) appeared to significantly decrease before the largest shock (M5.7) that occurred on March 7, 2006 near the Gedi fault, an active fault in the Kachchh region.

Investigating the Tsunamigenic Potential of Earthquakes from Analysis of the Informational and Multifractal Properties of Seismograms

Revealing the tsunamigenic potential of an earthquake is very challenging in regards to minimizing the casualties a tsunami can provoke. Thus, development of methodologies that can reliably furnish a early warnings of a tsunami is crucial. In order to accomplish this aim it is important to preliminarily identify the characteristics of seismograms that can be used to distinguish tsunamigenic (TS) earthquakes from non-tsunamigenic (NTS) earthquakes. In this paper P-wave time dynamic of 17 seismograms of TS earthquakes and 26 NTS seismograms are analysed by means of two advanced statistical tools: the Fisher–Shannon method and the multifractal detrended fluctuation analysis (MFDFA). Both methods are well suited to disclosing the inner time properties of complex signals, as seismograms appear to be. Using these two methods jointly, we defined a classifier, the performance of which was tested by means of the receiver-operating characteristic curve that plots true positive rate versus false positive rate. This classifier shows a discrimination power that can be considered acceptable in comparison with the devastating effects caused by a non-alarmed tsunami. Our findings indicate that proper choice of the classifier’s threshold allows correctly identification of approximately 69 % of the NTS seismograms and approximately 76 % of the TS seismograms. The presented results presented may be helpful in addressing the complex problem of early tsunami warning.

Investigating the time dynamics of monthly rainfall time series observed in northern Lebanon by means of the detrended fluctuation analysis and the Fisher-Shannon method

We investigate the time dynamics of monthly rainfall series intermittently recorded on seven climatic stations in northern Lebanon from 1939 to 2010 using the detrending fluctuation analysis (DFA) and the Fisher-Shannon (FS) method. The DFA is employed to study the scaling properties of the series, while the FS method to analyze their order/organization structure. The obtained results indicate that most all the stations show a significant persistent behavior, suggesting that the dynamics of the rainfall series is governed by positive feedback mechanisms. Furthermore, we found that the Fisher Information Measure (the Shannon entropy power) seems to decrease (increase) with the height of the rain gauge; this indicates that the rainfall series appear less organized and less regular for higher-located stations. Such findings could be useful for a better comprehension of the climatic regimes governing northern Lebanon.

FISHER-SHANNON ANALYSIS OF WIND RECORDS

The informational properties of hourly wind data measured in one site in northern Italy from April 1996 to December 2007 were investigated. The data were recorded by a Sodar Rass system, which measures the speed and the direction of the wind at several heights above the ground level. The Fisher-Shannon method was applied to allow discriminating dynamical features in complex time series. The findings point out to height-dependent informational properties of the wind speed. The obtained results shed light on a new perspective which contributes to a better understanding of the complex dynamics of wind phenomenon.

Multifractal analysis of time series generated by discrete Ito equations.

In this study, we show that discrete Ito equations with short-tail Gaussian marginal distribution function generate multifractal time series. The multifractality is due to the nonlinear correlations, which are hidden in Markov processes and are generated by the interrelation between the drift and the multiplicative stochastic forces in the Ito equation. A link between the range of the generalized Hurst exponents and the mean of the squares of all averaged net forces is suggested.

Comparing seismicity declustering techniques by means of the joint use of Allan Factor and Morisita index

In this paper, we propose to compare different declustering methods on the basis of the time-correlation and the space-clustering of the residual earthquake catalog after the declustering techniques have been applied. To this aim, we applied two point process clustering measures, the Allan Factor and the Morisita Index, for the identification and quantification of temporal correlation and spatial clustering in point processes, respectively. We used our joint space–time approach to study the earthquake space–time point processes of southern California and Switzerland with surrounding area, declustered by using the method of Gardner and Knopoff (with Grünthal and Uhmhammer window) and that of Reasenberg (with different setting parameters). Our results show that the residual declustered catalog is still characterized by time-correlated structures at long timescales; however, the cutoff timescale that is the lowest timescale above which the time-correlation is visible is higher with the Reasenberg method while is smaller with the Gardner and Knopoff method with Grünthal window. The space-clustering analysis performed by means of the Morisita Index suggests that the declustering technique effectively reduces the spatial clustering of the seismicity of Switzerland, but does not change the spatial properties of the residual seismic catalogue of the southern California.