Stochastic modelling at Stromboli: a volcano with remarkable memory

The assessment of potential volcanic eruptions is a critical aspect when evaluating the safety of populated areas. A stochastic approach has been developed for the analysis and simulation of data sampled at active volcanoes. This approach allows for the detection and quantification of time correlation, volcanic event forecasts using Cox model based simulations and volcanic tremor decomposition in order to identify potential precursors of major eruptions. The stochastic approach has been applied to data monitored at Stromboli volcano. Significant time correlation has been detected which makes Stromboli a volcano with a remarkable memory of its recent activity in comparison to other volcanoes. Forecasting of the number of strombolian events for the next few days has been performed by Monte Carlo simulations. Finally, kriging analysis of the tremor intensity has enabled time component estimation which could furnish additional monitoring variables for the forecast of paroxysmal phases at Stromboli.