Statistical identification of physical patterns which accompany eruptive activity on Mount Etna, Sicily

Abstract

Abstract A new statistical nonparametric pattern recognition algorithm is used to identify the phenomenology which accompanies summit and flank eruptions on Mount Etna, Sicily. This algorithm allows us to solve some of the operational problems typical of logic-type pattern recognition algorithms. Volcanic activity is parametrized through 12 variables concerning seismicity, past eruptive history, and precipitation, which practically exhaust the presently available data. In the 40 days which precede and follow the onset of each eruption, we identified no pattern whatsoever for summit eruptions, and a single significant pattern for flank activity. This indicates different eruptive mechanisms for flank and summit events. The latter appear to be independent of all the phenomena considered, and should therefore be ascribed either to magma feeding processes, a variable which we were not able to consider in our analysis due to the lack of data, or to random behaviour, without any repetitive scheme. Flank activity appears to be linked to the state of regional tectonic stress, but is independent of past eruptive history and groundwater level. This means that eruptions of the size Etna recently experienced, do not perturb the system, which must have a much larger capacity, at least of the order of 10 9 m 3 .