Denoising gravity and geomagnetic signals from Etna volcano (Italy) using multivariate methods

Abstract

Abstract.Multivariate methods were applied to denoise the gravity and geomagnetic signals continuously recorded by the permanent monitoring networks on the Etna volcano. Gravity and geomagnetic signals observed in volcanic areas are severely influenced by meteorological variables (i.e. pressure, temperature and humidity), whose disturbances can make the detection of volcanic source effects more difficult. For volcano monitoring it is necessary, therefore, to reduce the effects of these perturbations. To date filtering noise is a very complex problem since the spectrum of each noise component has wide intervals of superposition and, some times, traditional filtering techniques provide unsatisfactory results. We propose the application of two different approaches, the adaptive neuro-fuzzy inference system (ANFIS) and the Independent Component Analysis (ICA) to remove noise effects from gravity and geomagnetic time series. Results suggest a good efficiency of the two proposed approaches since they are capable of finding and effectively representing the underlying factors or sources, and allow local features of the signal to be detected.

Multidisciplinary investigation on a lava fountain preceding a flank eruption: The 10 May 2008 Etna case

“…Continuously recording gravity stations, located at Serra La Nave (SLN) and Belvedere (BVD), on the S flank of the volcano (at 1740 and 2920 m asl, respectively) were operative throughout the period encompassing the 2008 eruption (Figure 1). These stations are equipped with LaCoste & Romberg spring gravimeters, acquire gravity data at 1 point per minute sampling rate (resolution better than 1 microGal), tilt along two perpendicular axes and several meteorological parameters (pressure, humidity and temperature), which are used to reduce the gravity signal in order to acquire the volcano‐related signal [ Carbone et al , 2003c; Del Negro et al , 2008].…”