Bulletin of Volcanology

, 76:848 | Cite as

Characterization of volcanic regimes and identification of significant transitions using geophysical data: a review

Review Article

Abstract

A volcano can be considered as a dynamical system, and each time series recorded at a volcano can be interpreted as one of its observables. It is therefore theoretically possible to extract, even from a single time series, information about the underlying governing system. This is done through a procedure called “embedding” that is based on the intuitive statement that the only time series available carries with it information also about the time evolution of other parameters that we are not able to sample or observe. Carrying out this embedding procedure requires estimates of key parameters such as the optimal delay time and a proper embedding dimension. Other independent but often conceptually similar procedures allow decompositions of the time series into components that may in turn be associated to different source processes. The key to the characterization of volcanic regimes is a process of data reduction, aimed at parsing the amount of data into its most useful components which can then facilitate the interpretation of the system. The approaches presented here can be used to conduct such a data reduction phase, and the reduced data stream can be used not only for characterizing different volcanic regimes but also for determining transitions between them, examining their relationship with external or internal events such as tectonic or volcano-tectonic seismic events, looking for precursors of paroxysmal eruptive phases etc. These results can become additional inputs for physical models in order to understand in detail the physical changes that occurred in the volcanic system and their possible consequences. In this paper, the existing literature on this subject will be reviewed and the prospects of future research will be discussed.

Keywords

Time series data reduction Dynamical analysis Embedding Precursors Volcanic regimes Pattern recognition 

Notes

Acknowledgments

The author wishes to acknowledge the invaluable help resulted from discussions with his coauthors and former students of the last couple of decades. The methods described here were studied and/or developed also during several research periods spent by the author in foreign institutions, including the following:

-Instituto de Geofísica, Universidad Nacional Autónoma de México (UNAM), México D.F., México

-Earthquake Research Institute, The University of Tokyo, Tokyo, Japan

-ITMO University, St. Petersburg, Russia

-Centro de Investigaciones en Ciencias de la Tierra (CICTERRA)—Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Universidad Nacional de Córdoba, Córdoba, Argentina

Figures are based on original drawings by my former students Fausto Barazza and Luca Barbui.

The paper was improved substantially by the thoughtful comments of the reviewers, Art Jolly and Servando De la Cruz Reyna, and of the editor Steve Self; their help is warmly acknowledged.

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© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Laboratorio di misure e trattamento dei segnali, DICAUniversità di UdineUdineItaly
  2. 2.ITMO UniversitySt. PetersburgRussia
  3. 3.CICTERRA–CONICET, Facultad de Ciencias Exactas, Físicas y NaturalesUniversidad Nacional de CórdobaCórdobaArgentina

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