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 Please tell us about your educational background and early research experiences.

My educational background is quite eclectic. I attended a secondary school specializing in classics studying Philosophy, Latin, Ancient Greek, Art, and Literature—Mathematics and Physics too, but with much less dedicated time. After I got my diploma, instead of enrolling at a humanistic faculty, I decided to study Electronic Engineering, and after less than five years I earned my MSc degree.

Then, I had to do my military service (I was a second lieutenant in the Army for 15 months), and in the meantime I earned my second MSc degree in Mathematics. After that, I was involved in the geophysical research activity of my Institute, beginning with an annual research fellowship, later with temporary research contracts for several years until 2001, when I became part of the permanent research staff.

"...I think that earthquake prediction or the feasibility of earthquake precursors still represents the big challenge of earthquake research."

I'm now a research scientist at my Institute, and my research interests are statistical methodologies for the investigation of geophysical and environmental phenomena.

 What first drew your interest to earthquakes?

Can earthquakes be predicted? Can some precursory signatures in signals measured in areas with high seismic risk be revealed? I think that trying to answer these questions is the main reason why many researchers direct their interests to earthquakes. Anyway, even if a certain answer is still far out of reach, earthquakes represent an interesting natural phenomenon to be studied dynamically.

In fact, one of my first papers dealing with earthquakes was "Investigating clustering structures in time-occurrence sequences of seismic events observed in the Irpinia-Basilicata Region (Southern Italy)," (Telesca L, et al., Fractals 7: 221-234, 1999). This paper revealed the potential of some second-order fractal tools (Allan Factor, Fano Factor, Count-based Periodogram...) to gain insight into the time dynamics of earthquakes. This paper opened a field of investigation of seismic processes, dealing with the identification and quantification of time-clustering behavior.

Moreover, I think there is also a personal reason why I started to study earthquakes. My birthplace is located in a highly seismic area of southern Italy. I remember very well when, still a child, I felt the strong earthquake (of magnitude 6.9) that struck this area on November 23, 1980, causing more than 3,000 fatalities and damaging most of the buildings. Probably, this experience furnished the context in which my interests in earthquakes grew up many years later.

 Your most-cited paper in our analysis is the 2001 Geophysical Research Letters paper, "Depth-dependent time-clustering behaviour in seismicity of southern California." This is one of the few papers you've written related to California, so what prompted you to look at that region for this work?

Southern California is surely the most studied area by geophysicists. Anyone involved in earthquakes has analyzed some earthquake-related phenomena occurring in Southern California, at least once in his/her life!

In this paper, I applied two fractal methods, the detrended fluctuation analysis (DFA) and the Allan Factor (AF), quite novel in the seismic research field at that time, to analyze the time-clustering behavior of seismic sequences that occurred in southern California. It found a non-trivial relationship between the scaling exponent estimated by means of the DFA and the AF and the earthquake depth, with a tendency toward Poissonian behavior at around 14-16 km, this implying that shallower and deeper earthquakes are more correlated.

 Another of your highly cited papers is from the same issue of Geophysical Research Letters, "A new approach to investigate the correlation between geoelectrical time fluctuations and earthquakes in a seismic area of southern Italy." Please tell us about your methods and findings in this paper.

In this paper the correlation between seismicity and geoelectrical signal measured in southern Italy was investigated, by using the power spectral density of the hourly electrical signals and the Hurst analysis of the seismic interevent intervals (interval between two successive earthquakes).

The power spectral density of the geoelectrical signal informs about the content of the signal power at various frequency bands, and if its shape is a power-law or scaling, this means that the signal is characterized by the presence of correlated structures and is not purely random; the value of the power-law exponent, which is the spectral exponent, quantifies the strength of such correlations.

The Hurst analysis of the seismic interevent times is based on the calculation of the so-called "rescaled range," which can behave as a power-law, and the value of the power-law exponent, called the Hurst exponent, gives information about the persistence of the seismic sequence. Persistence means that long (short) interevent times are very likely followed by long (short) interevent times.

It was found that the power-law spectral exponent of the geoelectrical signal and the power-law Hurst exponent of the seismicity converge to unity before the occurrence of the strongest earthquake in the monitored area. This result was then interpreted in terms of the self-organized criticality (SOC), which represented the physical and statistical framework of many papers dealing with earthquakes for several years.

 In April of this year, you published a paper in Terra Nova on the 2009 L'Aquila earthquake in central Italy. What were you able to discover about this incident?

The L'Aquila earthquake (local magnitude 5.8) was a strong event that occurred in central Italy on April 6, 2009. The analysis of the seismicity of the area struck by this event was analyzed by means of the Tsallis nonextensive statistics, which leads to a relationship between a threshold magnitude and the cumulative number of earthquakes with magnitude larger than that threshold, different from the well-known Gutenberg-Richter law.

"...earthquakes represent an interesting natural phenomenon to be studied dynamically."

So far, the application of the nonextensive approach to earthquakes was rather occasional and generally presented in theoretical physics journals. In this paper, it was shown that before the occurrence of the L'Aquila earthquake, the nonextensive parameter increased significantly, suggesting the increase of the degree of an out-of-equilibrium state before that event.

The increase of this parameter could indicate that the system is preparing to release energy for a strong event. Anyway, this is only a reasonable interpretation of the behavior of the nonextensive parameter, and further studies for different cases and in different seismotectonic settings will be necessary.

 How much have we learned about earthquakes in the past decade? What advances would you like to see in the future of earthquake research?

I think that in the last decade many advances have been made in terms of observations, experiments, and models. Regarding my specific field, which is mainly statistical and methodological, the use of the fractal concept (whose most important fingerprint is the power-law shape of the statistics used to describe a natural phenomenon) has led to the development of a variety of methods and applications, aiming at a better understanding of many features of seismic processes.

Also the nonextensive statistics, first developed by Costantino Tsallis in 1988 but only very recently applied to earthquakes, seem to have great potential in terms of a more complete description of earthquake magnitude distribution.

But I think that earthquake prediction or the feasibility of earthquake precursors still represents the big challenge of earthquake research. Both questions are still debated and discussed with arguments for and against, and both convincing. And this implies only one thing: We have learned very much, but we need to learn much more!

Dr. Luciano Telesca
IMAA-CNR
Tito (PZ), Italy

KEYWORDS: EARTHQUAKES, PREDICTION, SEISMIC RISK, FRACTAL TOOLS, TIME DYNAMICS, DETRENDED FLUCTUATION ANALYSIS, ALLAN FACTOR, EARTHQUAKE DEPTH, GEOELECTRICAL SIGNAL, HURST EXPONENT, L'AQUILA, MAGNITUDE DISTRIBUTION.

Citing URL: http://sciencewatch.com/ana/st/earthquakes2/10augeqTele/

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