In this thesis I combine data from 29 volcanic earthquake swarms that follow the pattern predicted by the Generic Volcanic Earthquake Swarm Model (GVESM; Benoit and McNutt, 1996) to investigate whether the relative timing of various parameters of pre-eruptive volcanic earthquake swarms could be used to forecast the time of an impending eruption. Based on the analysis of seismic unrest preceding many eruptions, the GVESM suggests that it is common to see an increase first in high-frequency earthquakes, then low-frequency earthquakes, then the onset of volcanic tremor. While this pattern is useful to volcano-seismologists, the relative timing and durations of these three different types of volcanic seismicity, is explored here for the first time. The parameters investigated are the onset times of (i) low-frequency (LF) events and of (ii) tremor, and the time at which (iii) the peak rate (PR) of volcano-tectonic (VT) events and (iv) the maximum magnitude (MM) earthquake occur in relation to normalized time defined by swarm onset and end (i.e., eruption). The normalized time starts at the swarm onset (0%) and ends with the eruption (100%) allowing a comparison and joint consideration of parameter occurrences across swarms of different actual duration. We identify the normalized onset time of for each parameter (LF, tremor, PR, MM) with respect to the duration of each swarm. Each swarm has onset time uncertainties of the swarm itself and of its parameters. A swarm with large onset uncertainty could bias the normalized onset time of each parameter and we use weighted means to decrease the influence of swarms with large uncertainties on overall results. The weighted means of LF onset, tremor onset, MM and PR occurrence are 79% ± 23%, 96% ± 10%, 78% ± 29% and 75% ± 34%, respectively. Errors are the standard deviation of each parameter. The uncertainties for LF, MM and PR are large because their normalized onset times have the characteristics of a uniform distribution and therefore seem to have no predictive value. In contrast, tremor onset has a narrow distribution towards the end of swarms. A possible tremor mechanism consistent with this observation could be boiling of groundwater as magma nears the surface. LF onset always seems to precede tremor onset. LF and tremor start early (at less than 80% of normalized time) at five volcanoes with high SiO2 content possibly related to lower density and higher gas content of the resulting magma.

Deep non-volcanic tremor is a newly discovered seismic phenomenon with low amplitude, long duration, and no clear P- and S-waves as compared with regular earthquake. Tremor has been observed at many major plate-boundary faults, providing new information about fault slip behaviors below the seismogenic zone. While tremor mostly occurs spontaneously (ambient tremor) or during episodic slow- slip events (SSEs), sometimes tremor can also be triggered during teleseismic waves of distance earthquakes, which is known as "triggered tremor". The primary focus of my Ph.D. work is to understand the physical mechanisms and necessary conditions of triggered tremor by systematic investigations in different tectonic regions. These include Taiwan, California, southwest Japan, Alaska and the Aleutian Arc, Cascadia, and New Zealand. In the first chapter of my dissertation, I conduct a systematic survey of triggered tremor beneath the Central Range (CR) in Taiwan for 45 teleseismic earthquakes from 1998 to 2009 with Mw ≥ 7.5. Triggered tremors are visually identified as bursts of high-frequency (2-8 Hz), non-impulsive, and long-duration seismic energy that are coherent among many seismic stations and modulated by the teleseismic surface waves. A total of 9 teleseismic earthquakes has triggered clear tremor in Taiwan. The peak ground velocity (PGV) of teleseismic surface waves is the most important factor in determining tremor triggering potential, with an apparent threshold of ~0.1 cm/s, or 7-8 kPa. However, such threshold is partially controlled by the background noise level, preventing triggered tremor with weaker amplitude from being observed. In addition, I find a positive correlation between the PGV and the triggered tremor amplitude, which is consistent with the prediction of the 'clock-advance' model. This suggests that triggered tremor can be considered as a sped-up occurrence of ambient tremor under fast loading from the passing surface waves. Finally, the incident angles of surface waves also play an important rule in controlling the tremor triggering potential. The next chapter focuses on a systematic comparison of triggered tremor around the Calaveras Fault (CF) in northern California (NC), the Parkfield-Cholame section of the San Andreas Fault (SAF) in central California (CC), and the San Jacinto Fault (SJF) in southern California (SC). Out of 42 large (Mw ≥7.5) earthquakes between 2001 and 2010, only the 2002 Mw 7.9 Denali fault earthquake triggered clear tremor in NC and SC. In comparison, abundant triggered and ambient tremor has been observed in CC. Further analysis reveal that the lack of triggered tremor observations in SC and NC is not simply a consequence of their different background noise levels as compared to CC, but rather reflects different background tremor rates in these regions. In the final chapter, I systematically search for triggered tremor following the 2011 Mw9.0 Tohoku-Oki earthquake in the regions where ambient or triggered tremor has been found before. The main purpose is to check whether triggered tremor is observed in regions when certain conditions (e.g., surface wave amplitudes) are met. Triggered tremor is observed in southwest Japan, Taiwan, the Aleutian Arc, south-central Alaska, northern Vancouver Island, the Parkfield-Cholame section of the SAF in CC and the SJF in SC, and the North Island of New Zealand. Such a widespread triggering of tremor is not too surprising because of the large amplitude surface waves (minimum peak value of ~0.1 cm/s) and the associated dynamic stresses (at least ~7-8 kPa), which is one of the most important factors in controlling the triggering threshold. The triggered tremor in different region is located close to or nearby the ambient tremor active area. In addition, the amplitudes of triggered tremor have positive correlations with the amplitudes of teleseismic surface waves among many regions. Moreover, both Love and Rayleigh waves participate in triggering tremor in different regions, and their triggering potential is somewhat controlled by the incident angles. In summary, systematically surveys of triggered tremor in different tectonic regions reveal that triggered tremor shares similar physical mechanism (shear failure on the fault interface) as ambient tremor but with different loading conditions. The amplitude of the teleseismic surface wave is one of the most important factors in controlling the tremor triggering threshold. In addition, the frequency contents and incident angles of the triggering waves, and local fault geometry and ambient conditions also play certain roles in determining the triggering potential. On the other hand, the background noise level and seismic network coverage and station quality also could affect the apparent triggering threshold. Because triggered tremor occurs almost instantaneously during the teleseismic surface waves, and the tremor amplitude is somewhat controlled by the amplitude of the triggering waves, the occurrence time and the size of the triggered tremor could be somewhat predictable, so long as we know the amplitude and period of surface waves and associated time-varying dynamic stresses. Hence, further analysis of triggered tremor may provide important new clues on the nucleation and predictability of seismic events.

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This dissertation is a comprehensive summary of four papers on the development and application of new strategies for locating tremor and relocating events in earthquake catalogs. In the first paper, two new strategies for relocating events in a catalog are introduced. The seismicity pattern of an earthquake catalog is often used to delineate seismically active faults. However, the delineation is often hindered by the diffuseness of earthquake locations in the catalog. To reduce the diffuseness and simplify the seismicity pattern, a relocation and a collapsing method are developed and applied. The relocation method uses the catalog event density as an a priori constraint for relocations in a Bayesian inversion. The catalog event density is expressed in terms of the combined probability distribution of all events in the catalog. The collapsing method uses the same catalog density as an attractor for focusing the seismicity in an iterative scheme. These two strategies are applied to an aftershock sequence after a pair of earthquakes which occurred in southwest Iceland, 2008. The seismicity pattern is simplified by application of the methods and the faults of the mainshocks are delineated by the reworked catalog. In the second paper, the spatial distribution of seismicity of the Hengill region, southwest Iceland is analyzed. The relocation and collapsing methods developed in the first paper and a non-linear relocation strategy using empirical traveltime tables are used to process a catalog collected by the Icelandic Meteorological Office. The reworked catalog reproduces details of the spatial distribution of seismicity that independently emerges from relative relocations of a small subset of the catalog events. The processed catalog is then used to estimate the depth to the brittle-ductile transition. The estimates show that in general the northern part of the area, dominated by volcanic processes, has a shallower depth than the southern part, where tectonic deformation predominates. In the third and the fourth papers, two back-projection methods using inter-station cross correlations are proposed for locating tremor sources. For the first method, double correlations, defined as the cross correlations of correlations from two station pairs sharing a common reference station, are back projected. For the second method, the products of correlation envelopes from a group of stations sharing a common reference station are back projected. Back projecting these combinations of correlations, instead of single correlations, suppresses random noise and reduces the strong geometrical signature caused by the station configuration. These two methods are tested with volcanic tremor at Katla volcano, Iceland. The inferred source locations agree with surface observations related to volcanic events which occurred during the tremor period.