Volcanic tremor has attracted considerable attention by seismologists because of its potential value as a tool for forecasting eruptions and better understanding the physical processes that occur inside active volcanoes. However, unlike tectonic earthquakes where the dominant source process is brittle failure of rock, the driving mechanism of tremor seems to involve complex interactions of magmatic fluids with the surrounding bedrock. These interactions are responsible for the following distinct characteristics found in volcanic tremor recorded at many volcanoes worldwide: (a) the onset of tremor may be emergent or impulsive, with its amplitude showing in many cases a direct relationship to the volcanic activity; (b) in the frequency domain the spectra consist of a series of sharp peaks in the band 0.1^7 Hz, representing either a fundamental frequency and its harmonics, or a random distribution, while quite often they exhibit temporal variations in their content; (c) the depth of the source can vary considerably from one volcano to another in the range of a few hundred metres to 40 km; (d) tremor may occur prior to and/or after eruptions with a duration that ranges from several minutes to several days or months. The methods used to study tremor include spectral analysis using both the Fast Fourier Transform and the Maximum Entropy Method, polarisation analysis of the wavefield and methods that make use of array data to deduce the backazimuth and type of the seismic waves as well as the location of the source. Visual and/or recorded acoustic observations of the ongoing volcanic activity have assisted in many cases to further constrain proposed physical mechanisms for the generation of tremor. The models suggested as possible sources of tremor can be grouped as follows: (a) fluid-flow-induced oscillations of conduits transporting magmatic fluids; (b) excitation and resonance of fluid-filled cracks; (c) bubble growth or collapse due to hydrothermal boiling of groundwater; (d) a variety of models involving the oscillations of magma bodies with different geometries. It has been proposed by many authors that the source of tremor is not unique and may differ from one volcano to another, a fact that adds more difficulty in the source modelling efforts. As data quality, computer power and speed are improving, it may be possible in the near future to decipher and accurately model tremor source processes at different volcanic environments. ß 2002 Elsevier Science B.V. All rights reserved.

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Summary Observations and theoretical considerations have cast doubt on the suggestion that volcanic tremor source processes may be modelled by a linear oscillator that is set into resonance by a sustained disturbance. Volcanic tremor signals that accompanied the 1996 Vatnajökull subglacial eruption, central Iceland, have been analysed using methods from the discipline of non‐linear dynamics in order to investigate the possibility that they originated from a non‐linear source. The volcano‐seismic phenomena associated with the eruption were recorded by a permanent network equipped with broad‐band seismometers (HOTSPOT) using a sampling rate of 20 samples s−1. The eruption was preceded by increased seismic activity for a period of 2 days, which also included a large earthquake with a moment magnitude of 5.6. The tremor during the first 2 days of the eruption has a high signal‐to‐noise ratio at the nearest station to the eruption site and starts as a continuous signal, later evolving to low‐amplitude background tremor interrupted by high‐amplitude, cigar‐shaped bursts having an average duration of 250 s. The phase space, which describes the evolution of the behaviour of a non‐linear system, was reconstructed from the original tremor seismograms using the delay embedding theorem suggested by Takens. The delay time used for the reconstruction was selected after examining the autocorrelation function, which showed a first zero crossing at a timelag of 4 samples and the average mutual information that showed no minimum, indicating that the tremor process may have been undersampled. Based also on phase space portraits for different delay times, a delay time of one sample interval (0.05 s) was used. The sufficient embedding dimension for phase space reconstruction was selected by applying the false nearest‐neighbours method, which revealed complete unfolding of the tremor attractor at dimensions 7–8, implying upper bounds of its fractal dimension in the range 3.5–4.0. The phase space prediction errors of different segments of the tremor time‐series were compared in order to check whether the attractor dynamics change substantially with time. It was found that for continuous tremor there was almost no dynamic variation, in contrast to the background tremor and the superposed bursts that gave a maximum prediction error when the former was used to predict the latter. This difference in dynamics also had an effect on their spectra: the amplitude spectrum of a burst or continuous tremor has a much sharper decay at high frequencies than that of the background tremor. A possible physical mechanism that may explain these observed characteristics involves turbulent slug flow of magma in a narrow cylindrical conduit, generating the different dynamic regimes as the Reynolds number varies.

In this study we utilize regional and teleseismic earthquake moment tensor solutions in order to infer the contemporary crustal stress in the Greek region. We focus on crustal earthquakes and select only solutions with good waveform fits and well‐resolved nodal planes. A data set of 1614 focal mechanisms is used as input to a regional‐scale damped stress inversion algorithm over a grid whose node spacing is 0.35°. Several resolution and sensitivity tests are performed in order to ascertain the robustness of our results. Our findings show that for most of the Greek region the largest principal stress σ1 is vertically oriented and that the minimum principal stress axis σ3 are subhorizontal with a predominant N‐S orientation. In the SW Peloponnese the orientation of σ3 axes rotates clockwise and in SE Aegean counterclockwise. These results are in agreement with the generally accepted model that slab rollback combined with gravitational spreading of the Aegean lithosphere are the main causes of the extension. Transitions between different faulting types in NW Greece or in the Aegean occur within narrow zones in the order of tens of kilometers. A visual comparison of the principal horizontal stress axes and the principal strain axes derived from GPS observations shows good agreement, suggesting that the crust in the Greek region behaves largely in an elastic manner.