arXiv subjects

Luciano Telesca

Publications and source records attributed to Luciano Telesca.

14 recordsLinked to original sources

arXiv2019

Investigating the time dynamics of wind speed in complex terrains by using the Fisher-Shannon method

In this paper, the time dynamics of the daily means of wind speed measured in complex mountainous regions are investigated. For 293 measuring stations distributed over all Switzerland, the Fisher information measure and the Shannon entropy power are calculated. The results reveal a clear relationship between the computed measures and both the elevation of the wind stations and the slope of the measuring sites. In particular, the Shannon entropy power and the Fisher information measure have their highest (respectively lowest) values in the Alps, where the time dynamics of wind speed follows a more disordered pattern. The spatial mapping of the calculated quantities allows the identification of two regions, which is in agreement with the topography of the Swiss territory. The present study could contribute to a better characterization of the temporal dynamics of wind speed in complex mountainous terrain.

stat.AP↗

arXiv2018

Fisher-Shannon complexity analysis of high-frequency urban wind speed time series

1Hz wind time series recorded at different levels (from 1.5 to 25.5 meters) in an urban area are investigated by using the Fisher-Shannon (FS) analysis. FS analysis is a well known method to get insight of the complex behavior of nonlinear systems, by quantifying the order/disorder properties of time series. Our findings reveal that the FS complexity, defined as the product between the Fisher Information Measure and the Shannon entropy power, decreases with the height of the anemometer from the ground, suggesting a height-dependent variability in the order/disorder features of the high frequency wind speed measured in urban layouts. Furthermore, the correlation between the FS complexity of wind speed and the daily variance of the ambient temperature shows similar decrease with the height of the wind sensor. Such correlation is larger for the lower anemometers, indicating that ambient temperature is an important forcing of the wind speed variability in the vicinity of the ground.

stat.AP↗

arXiv2018

Wavelet variance scale-dependence as a dynamics discriminating tool in high-frequency urban wind speed time series

High frequency wind time series measured at different heights from the ground (from 1.5 to 25.5 meters) in an urban area were investigated by using the variance of the coefficients of their wavelet transform. Two ranges of scales were identified, sensitive to two different dynamical behavior of the wind speed: the lower anemometers show higher wavelet variance at smaller scales, while the higher ones are characterized by higher wavelet variance at larger scales. Due to the relationship between wavelet scale and frequency, the results suggest the existence of two frequency ranges, where the wind speed variability change according to the position of the anemometer from the ground. This study contributes to better understanding of the high frequency wind speed in urban areas and to a better knowledge of the underlying mechanism governing the wind fluctuations at different heights from the ground in particular in urban area.

stat.AP↗

arXiv2018

Community detection analysis in wind speed-monitoring systems using mutual information-based complex network

A mutual information-based weighted network representation of a wide wind speed monitoring system in Switzerland was analysed in order to detect communities. Two communities have been revealed, corresponding to two clusters of sensors situated respectively on the Alps and on the Jura-Plateau that define the two major climatic zones of Switzerland. The silhouette measure is used to evaluate the obtained communities and confirm the membership of each sensor to its cluster.

physics.soc-ph↗

arXiv2018

Analysis of temporal properties of wind extremes

The 10-minute average wind speed series recorded at 132 stations distributed rather homogeneously in the territory of Switzerland are investigated. Wind extremes are defined on the base of run theory: fixing a percentile-based threshold of the wind speed distribution, a wind extreme is defined as a sequence of consecutive wind values (or duration of the extreme) above the threshold. This definition allows to analyse the sequence of extremes as a temporal point process marked by the duration of the extremes. The average probability density function of the duration of the extremes of the wind speed measured in Switzerland does not depend on the percentile-based threshold and decrease with the increase of the extreme duration. The time-clustering behaviour of the sequences of the wind extremes was analysed by using the global and local coefficient of variation and the Allan Factor. The wind extremes are globally time-clustered, although they tend to behave as a Poisson process with the increase of the minimum extreme duration. Locally, the wind extremes tend to be clustered for any percentile-based threshold for stations located above about 2,000 m a.s.l. By using the Allan Factor, it was revealed that wind extremes tend to be clustered even at lower timescales especially for the higher stations.

stat.AP↗

arXiv2018

Linearity versus non-linearity in high frequency multilevel wind time series measured in urban areas

In this paper, high frequency wind time series measured at different heights from the ground (from 5.5 to 25.5 meters) in an urban area were investigated. The spectrum of each series is characterized by a power-law behaviour at low frequency range, with a mean spectral exponent of about 1.5, which is rather consistent with the Kolmogorov spectrum of atmospheric turbulence. The detrended fluctuation analysis was applied on the magnitude and sign series of the increments of wind speed, in order to get information about the linear and nonlinear dynamics of the time series. Both the sign series and magnitude series are characterized by two timescale ranges; in particular the scaling exponent of the magnitude series in the high timescale range seems to be related with the height of the sensor. This study aims to understand better high frequency wind speed in urban areas and to disclose the underlying mechanism governing the wind fluctuations at different heights.

stat.AP↗

arXiv2018

Long-range fluctuations and multifractality in connectivity density time series of a wind speed monitoring network

This paper studies the daily connectivity time series of a wind speed-monitoring network using multifractal detrended fluctuation analysis. It investigates the long-range fluctuation and multifractality in the residuals of the connectivity time series. Our findings reveal that the daily connectivity of the correlation-based network is persistent for any correlation threshold. Further, the multifractality degree is higher for larger absolute values of the correlation threshold

physics.data-an↗

arXiv2017

Periodic fluctuations in correlation-based connectivity density time series: application to wind speed-monitoring network in Switzerland

In this paper, we study the periodic fluctuations of connectivity density time series of a wind speed-monitoring network in Switzerland. By using the correlogram-based robust periodogram annual periodic oscillations were found in the correlation-based network. The intensity of such annual periodic oscillations is larger for lower correlation thresholds and smaller for higher. The annual periodicity in the connectivity density seems reasonably consistent with the seasonal meteo-climatic cycle.

stat.AP↗

arXiv2017

Multifractal analysis of the time series of daily means of wind speed in complex regions

In this paper, we applied the multifractal detrended fluctuation analysis to the daily means of wind speed measured by 119 weather stations distributed over the territory of Switzerland. The analysis was focused on the inner time fluctuations of wind speed, which could be more linked with the local conditions of the highly varying topography of Switzerland. Our findings point out to a persistent behaviour of all the measured wind speed series (indicated by a Hurst exponent significantly larger than 0.5), and to a high multifractality degree indicating a relative dominance of the large fluctuations in the dynamics of wind speed, especially in the Swiss plateau, which is comprised between the Jura and Alp mountain ranges. The study represents a contribution to the understanding of the dynamical mechanisms of wind speed variability in mountainous regions.

stat.AP↗

arXiv2011

Non-extensive analysis of seismicity: application to some seismic sequences of Morocco

The magnitude distribution of three seismic sequences occurred in Morocco were investigated by means of the Tsallis-based non-extensive analysis. The non-extensive parameters were estimated by means of the Levenberg-Marquadt nonlinear least square fitting method. It was found that the q value could be a good indicator of the complexity of seismic phenomena. Such findings could contribute in better understanding the dynamics of seismicity and suggesting a unifying view of earthquake occurrence.

physics.geo-ph↗

arXiv2011

Analysis of time dynamics in wind records by means of multifractal detrended fluctuation analysis and 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.

cond-mat.stat-mech↗

arXiv2011

Construction of Ito model for Geoelectrical Signals

Ito stochastic differential equation governs one-dimensional diffusive Markov process. Geoelectrical signals measured in seismic areas can be considered as the result of competitive and collective interactions among system elements. The Ito equation may constitute a good macroscopic model of such phenomenon in which microscopic interactions are adequately averaged. The present study shows how to construct Ito model for a geoelectrical time series measured in a seismic area of southern Italy. Our results reveal that Ito model describes quite well the whole time series, but performs better when one considers fragments of the data set with lower variability range (absent or rare large fluctuations) . Our findings show that generally detrended geoelectrical time series can be considered as an approximation of the Markov diffusion process.

physics.data-an↗

arXiv2007

Scaling and correlations in the dynamics of forest-fire occurrence

Forest-fire waiting times, defined as the time between successive events above a certain size in a given region, are calculated for Italy. The probability densities of the waiting times are found to verify a scaling law, despite that fact that the distribution of fire sizes is not a power law. The meaning of such behavior in terms of the possible self-similarity of the process in a nonstationary system is discussed. We find that the scaling law arises as a consequence of the stationarity of fire sizes and the existence of a non-trivial ``instantaneous'' scaling law, sustained by the correlations of the process.

physics.geo-ph↗

arXiv2005

Multifractal Fluctuations in Seismic Interspike Series

Multifractal fluctuations in the time dynamics of seismicity data have been analyzed. We investigated the interspike intervals (times between successive earthquakes) of one of the most seismically active areas of central Italy by using the Multifractal Detrended Fluctuation Analysis (MF-DFA). Analyzing the time evolution of the multifractality degree of the series, a loss of multifractality during the aftershocks is revealed. This study aims to suggest another approach to investigate the complex dynamics of earthquakes.

cond-mat.stat-mech↗