The role of static stress diffusion in the spatio-temporal organization of aftershocks

We investigate the spatial distribution of aftershocks and we find that aftershock linear density exhibits a maximum, that depends on the mainshock magnitude, followed by a power law decay. The exponent controlling the asymptotic decay and the fractal dimensionality of epicenters clearly indicate triggering by static stress. The non monotonic behavior of the linear density and its dependence on the mainshock magnitude can be interpreted in terms of diffusion of static stress. This is supported by the power law growth with exponent $H\simeq 0.5$ of the average main-aftershock distance. Implementing static stress diffusion within a stochastic model for aftershock occurrence we are able to reproduce aftershock linear density spatial decay, its dependence on the mainshock magnitude and its evolution in time.Comment: 4 figure

Self-sustained oscillator as a model for explosion quakes at Stromboli Volcano

International audienceWe analyze seismic signals produced by explosion-quakes at Stromboli Volcano. We use standard nonlinear procedures to search a low-order effective dynam-ics. The dimension of the reconstructed phase space depends on the number of samples. Namely larger time lengths cor-respond to dynamical systems of different complexity. If we restrict the analysis to the signal associated directly to the source (Chouet et al., 1997), we obtain a phase space dimen-sion equal to two. We reproduce this part of the signal with a simple single self-sustained oscillator

An Automated Method for Mapping Independent Spatial b Values

We present an automated method for mapping the b values. The algorithm is very simple and presents three advantages: (a) it does not requires any tuning of the parameters like, for instance, a fixed cell size or a maximum radius of the cell; (b) it implies a more appropriate use of the catalog, by using almost all the events in the catalog used (with a tolerance of 1%) with no overlap; (c) it implies the full independence of the b values, thus allowing the statistical comparison of the results using standard tests. Although the resulting b values are comparable with those obtained by applying the other methods of common use in seismology, these latter (a) leave out many earthquakes from the analysis, with loose of useful information, (b) produce diffuse cells overlapping aiming at reaching many cells of the grid in order to get the correct number of events in each cell, and (c) results in correlated b values, which do not allow the test of significance for the differences in the b values. Finally, due to the independence from any ad hoc a-priori choice, our method is suitable for automatic and operator-free procedures.Plain Language Summary The methods usually used in seismology for mapping the b value require the tuning of some parameters depending on the analyzed catalog. Here we propose a method that only implies the choice of the minimum number of earthquakes needed to obtain reliable b value estimates, which does not depend on the specific cases. Due to the mutual complete independence of the resulting b values, the proposed method allows the use of standard statistical tests to compare the results

On the influence of time and space correlations on the next earthquake magnitude

A crucial point in the debate on feasibility of earthquake prediction is the dependence of an earthquake magnitude from past seismicity. Indeed, whilst clustering in time and space is widely accepted, much more questionable is the existence of magnitude correlations. The standard approach generally assumes that magnitudes are independent and therefore in principle unpredictable. Here we show the existence of clustering in magnitude: earthquakes occur with higher probability close in time, space and magnitude to previous events. More precisely, the next earthquake tends to have a magnitude similar but smaller than the previous one. A dynamical scaling relation between magnitude, time and space distances reproduces the complex pattern of magnitude, spatial and temporal correlations observed in experimental seismic catalogs.Comment: 4 Figure

Nonlinear convective motion of the asthenosphere and the lithosphere melting: a model for the birth of a volcano

The processes of heat transfer occurring between the Earth's asthenosphere and lithosphere are responsible for partial melting of rocks, leading to the magma generation and its migration and segregation in the crust and, possibly, to volcanoes generation at the surface. Convection is the dominant mechanism regulating the heat transfer from the asthenosphere to the lithosphere, although many aspects of the whole process are not yet clear. Therefore, the knowledge of the physical processes leading to the melting of the lithospheric rocks has important consequences in understanding the interior Earth dynamics, the surface volcanic dynamics, and its related hazards. Rock melting occurs when the temperature gradient meets the rock solidus. Here, we propose a nonlinear convective 1D analytical model (representing an approximation of more 3D complex models). The steady-state solution of our equation is in good agreement with the estimated geotherms of the asthenosphere. A perturbative approach leads to a heat swelling at the boundary between asthenosphere and lithosphere able to determine its melting and the birth of a volcano

Time-energy correlations in solar flare occurrence

The existence of time-energy correlations in flare occurrence is still an open and much debated problem. This study addresses the question whether statistically significant correlations are present between energies of successive flares as well as energies and waiting times. We analyze the GOES catalog with a statistical approach based on the comparison of the real catalog with a reshuffled one where energies are decorrelated. This analysis reduces the effect of background activity and is able to reveal the role of obscuration. We show the existence of non-trivial correlations between waiting times and energies, as well as between energies of subsequent flares. More precisely, we find that flares close in time tend to have the second event with large energy. Moreover, after large flares the flaring rate significantly increases, together with the probability of other large flares. Results suggest that correlations between energies and waiting times are a physical property and not an effect of obscuration. These findings could give important information on the mechanisms for energy storage and release in the solar corona

Spatial and temporal distribution of vertical ground movements at Mt. Vesuvius in the period 1973-2009

Since the early ’70s vertical ground movements at Mount Vesuvius area have been investigated and monitored by the Osservatorio Vesuviano (Istituto Nazionale di Geofisica Vulcanologia - Osservatorio Vesuviano since 2001). This monitoring began with the installation of a high-precision leveling line in the region at medium-high elevations on the volcano. The deformation pattern and expected strain field assessment methods in the volcanic structure induced by inner sources has demanded in subsequent years the expansion of the leveling network up to cover the whole volcanic area, enclosing part of leveling lines of other institutions. As a result of this expansion, the Mt. Vesuvius Area Leveling Network (VALN) has today reached a length of about 270 km and consists of 359 benchmarks. It is configured in 21 circuits and is connected, westward, to the Campi Flegrei leveling network and, northward, to the Campania Plain leveling network. The data collected have been carefully re-analyzed for random and systematic errors and for error propagation along the leveling lines to identify the areas affected by significant ground movements. For each survey, the data were rigorously adjusted and vertical ground movements were evaluated by differentiating the heights calculated by the various measurements conducted by the Osservatorio Vesuviano from 1973 to 2009

Memory in Self Organized Criticality

Many natural phenomena exhibit power law behaviour in the distribution of event size. This scaling is successfully reproduced by Self Organized Criticality (SOC). On the other hand, temporal occurrence in SOC models has a Poisson-like statistics, i.e. exponential behaviour in the inter-event time distribution, in contrast with experimental observations. We present a SOC model with memory: events are nucleated not only as a consequence of the instantaneous value of the local field with respect to the firing threshold, but on the basis of the whole history of the system. The model is able to reproduce the complex behaviour of inter-event time distribution, in excellent agreement with experimental seismic data

Characterization of GPS time series at the Neapolitan volcanic area by statistical analysis

The GPS time series recorded at the Neapolitan volcanic area reveals a very peculiar behavior. When a clear deformation is observed, the amplitude distribution evolves from a super‐Gaussian to a broader distribution. This behavior can be characterized by evaluating the kurtosis. Spurious periodic components were evidenced by independent component analysis and then removed by filtering the original signal. The time series for all stations was modeled with a fifth‐order polynomial fit, which represents the deformation history at that place. Indeed, when this polynomial is subtracted from the time series, the distributions again become super‐Gaussian. A simulation of the deformation time evolution was performed by superposing a Laplacian noise and a synthetic deformation history. The kurtosis of the obtained signals decreases as the superposition increases, enlightening the insurgence of the deformation. The presented approach represents a contribution aimed at adding further information to the studies about the deformation at the Neapolitan volcanic area by revealing geologically relevant data