Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/9399
AuthorsFalsaperla, S.* 
Behncke, B.* 
Langer, H.* 
Neri, M.* 
Salerno, G.G.* 
Giammanco, S.* 
Pecora, E.* 
Biale, E.* 
TitleFailed eruptions : examples revealed by a multidisciplinary study at Mt Etna in spring 2007
Issue Date2014
PublisherMISCELLANEA INGV
URIhttp://hdl.handle.net/2122/9399
KeywordsEtna
data mining
seismic data
thermal data
SO2 flux
in-situ Radon measurement
failed eruption
Subject Classification05. General::05.01. Computational geophysics::05.01.02. Cellular automata, fuzzy logic, genetic alghoritms, neural networks 
AbstractContinuous monitoring at Mt. Etna volcano usually unveils remarkable changes in geophysical and geochemical parameters before the onset of volcanic activity. However, signals of apparent impending volcanic unrest are sometimes recorded without being followed by any eruption. Based on data acquired by the permanent monitoring networks run by INGV, we present cases of "failed eruptions" at Mt Etna from February to April 2007. In the time span analyzed, there were recurrent seismic unrest episodes in the form of enhancements of the volcanic tremor amplitude, which did not culminate in eruptive activity. To explain the origin of these variations, we propose a multidisciplinary study, in which we analyze plume S02 flux, in­ soil radon and ambient parameters (pressure and temperature), thermal and volcanic tremor data. A pattern classification method based on Kohonen maps and fuzzy clustering sheds further light on changes in volcanic tremor, radon and ambient parameters. Overall, we conclude that the variations observed were the results of episodes of gas pulses and/or rock fracturing. The fluid pressure build up allowed upraise of magma batches that generally failed to reach the surface. Actually, only two "real eruptions" (with short­-lived lava fountains on March 29 and April 10-11) occurred during the studied period. In summary, the application of unsupervised classification techniques to volcanic tremor, radon data and ambient parameters represent a promising tool for the surveillance of active volcanoes.
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