Towards a global classification of volcanic tremor

• Main Author: Unglert, Katharina Claudia
• Language: English
• Published: University of British Columbia 2016
• Online Access: http://hdl.handle.net/2429/58710

Volcanic tremor, a seismic signal with longer durations and lower frequency content compared to local earthquakes, is often observed before or during eruptions and may consequently be useful for eruption forecasting. However, the processes generating volcanic tremor are still poorly understood. The main goal of this thesis is to assess systematic similarities and differences among tremor from a global sample of volcanoes, which is crucial to successfully constrain plausible source mechanisms. Using time series analysis of seismic signals accompanying three eruptive episodes at Kīlauea Volcano, Hawai‘i, I show that two characteristic phases of seismicity accompany dike intrusions, and that a different type of tremor occurs during a period of explosive activity. The signals differ in their spatial, temporal, and most strongly in their spectral properties. I thus construct a synthetic dataset of spectra that mimic the different spectral shapes observed in Hawai‘i. I use this dataset to evaluate the performance of two pattern recognition algorithms that may facilitate a global comparison of volcanic tremor spectra. A variety of tests with the synthetic spectra including different numbers and character of spectral patterns, as well as increasing levels of noise reveal that Principal Component Analysis and hierarchical clustering, in combination with a newly developed criterion to determine the ideal number of groupings in the data, can successfully identify the correct number and character of the known spectra. I thus develop a detection algorithm for volcanic tremor and apply the pattern recognition approach to detect patterns in tremor spectra from Kīlauea, Okmok, Pavlof, and Redoubt volcanoes. By analyzing the station network for each volcano individually, I show that tremor has distinct spatial and temporal characteristics for each of the volcanic settings. A subsequent comparative analysis suggests that several volcanic settings share common spectral tremor characteristics. I identify at least four types of volcanic tremor with systematic variations among the four settings, which indicates relationships to volcanic controls such as magma storage depth and viscosity. Further analysis of tremor from a larger sample of volcanoes will help to constrain plausible source processes and ultimately improve eruption forecasting. === Science, Faculty of === Earth, Ocean and Atmospheric Sciences, Department of === Graduate