Decrypting geophysical signals at Stromboli Volcano (Italy): Integration of seismic and Ground‐Based InSAR displacement data

Abstract

We present the integration of seismic and Ground-Based Interferometric Synthetic Aperture Radar system (GBInSAR) displacement data at Stromboli Volcano. Ground deformation in the area of summit vents is positively correlated with both seismic tremor amplitude and cumulative amplitudes of very long period (VLP) signals associated with Strombolian explosions. Changes in VLP amplitudes precede by a few days the variations in ground deformation and seismic tremor. We propose a model where the arrival of fresh, gas-rich magma from depth enhances gas slug formation, promoting convection and gas transfer throughout the conduit system. At the shallowest portion of the conduit, an increase in volatile content causes a density decrease, expansion of the magmatic column and augmented degassing activity, which respectively induce inflation of the conduit, and increased tremor amplitudes. The temporal delay between increase of VLP and tremor amplitudes/conduit inflation can be interpreted in terms of the different timescales characterizing bulk gas transfer versus slug formation and ascent.

The 2014 Effusive Eruption at Stromboli: New Insights from In Situ and Remote-Sensing Measurements

“…The pre-2014 LiDAR-DEM was obtained elaborating the 3D point cloud acquired during an airborne survey carried on May 2012 by "BLOM Compagnia Generale Ripreseaeree S.P.A." (www.blomasa.com). The data were acquired using the Leica ADS80 sensor which has instrumental vertical and horizontal accuracy of ±10/20 cm and ±25 cm, respectively (see [36] for 2012 DEM features). The acquired point cloud has a mean point density of 8 pt/m 2 .…”

A statistical-based approach for determining the intensity of unrest phases at Stromboli volcano (Southern Italy) using one-step-ahead forecasts of displacement time series

“…This temporal delay between the changes in tremor amplitude of the VLP signals and the GBInSAR displacements is interpreted in terms of the different timescales characterizing bulk gas transfer versus slug formation and ascent (Di Traglia et al 2014c). Moreover, discrete Fourier transform analysis of the same displacement time series shows that the most energetic peaks correspond to a period of 256 days, comparable to the residence time in the very shallow magma storage system (10-213 days; Gauthier and Condomines 1999;Gauthier et al 2000).…”

“…Ground deformation analysis by Di Traglia et al (2014c) revealed that changes in the displacement time series extracted in this area are coupled with variations in seismic tremor amplitude and are anticipated by few days by the changes in the amplitude of the very-long-period (VLP) signals. This temporal delay between the changes in tremor amplitude of the VLP signals and the GBInSAR displacements is interpreted in terms of the different timescales characterizing bulk gas transfer versus slug formation and ascent (Di Traglia et al 2014c).…”

“…Displacements can be estimated with high accuracy by stacking the phase of the interferograms, i.e., by processing many images together rather than adopting a more classic two-image approach. At Stromboli, the GBInSAR combines all the 8-hour-averaged images (Zebker et al 1997;Antonello et al 2004;Intrieri et al 2013a), producing cumulative displacement maps and displacement time series with an accuracy of ±0.5 mm (Di Traglia et al 2014c. Interferometric stacks are useful to highlight persistent deformation, suppressing other random signals, like atmospheric anomalies (Pinel et al 2014).…”

“…The time series in Fig. 1 are those used by Di Traglia et al (2014cTraglia et al ( , 2015. Time series data were synthesized to daily displacement values spanning from January 1, 2010, to August 7, 2014.…”