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Volcanic Electrification: A Multiparametric Case Study of Sakurajima Volcano, Japan

Electrical activity at volcanoes has been recently recognized as a potential new remote sensing technique for plume-forming eruptions. Volcanic electrical activity takes place in the conduit and plume and therefore has the benefit of being a direct indicator of surface activity. This is unlike seismic signals, which indicate magma/gas movement underground, and infrasound signals, which indicate a surface explosion but not necessarily the formation of an ash plume. There are two distinct types of volcanic electrical discharges: volcanic lightning and continual radio frequency (CRF) impulses. This dissertation explores the relationships between these two electrical signals and other commonly monitored volcanic parameters. For volcanic electrical activity to be widely adopted into monitoring platforms it is important to understand how electrical discharges at volcanoes are related to other monitored signals. I present a case study of the electrical activity at Sakurajima Volcano, Japan. The lightning mapping array (LMA) is used to record both lightning and CRF. I relate CRF to ash properties and show that CRF corresponds to eruptions containing more juvenile magma that has undergone milling as it is transported out of the conduit. Seismic, infrasound, and video data are used in conjunction with multivariable statistical methods on a suite of electrical parameters to show that high levels of volcanic electrical activity are related to eruptions with large infrasound signals (> 107 J), high initial velocities (> 55 m/s), and relatively tall plume heights (> 1 km). Finally, an examination of globally detected lightning at Bogoslof Volcano, AK shows the potential for volcanic lightning in plume tracking (0-100 km), even after the end of the explosive phase of the eruption.

Identiferoai:union.ndltd.org:USF/oai:scholarcommons.usf.edu:etd-9147
Date02 April 2019
CreatorsSmith, Cassandra M.
PublisherScholar Commons
Source SetsUniversity of South Flordia
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceGraduate Theses and Dissertations

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