Date of Award
2014
Document Type
Master's Thesis
Degree Name
Master of Science in Geology (MS)
College, School or Department Name
Department of Geological and Mining Engineering and Sciences
Advisor
Greg Waite
Abstract
How can we calculate earthquake magnitudes when the signal is clipped and over-run? When a volcano is very active, the seismic record may saturate (i.e., the full amplitude of the signal is not recorded) or be over-run (i.e., the end of one event is covered by the start of a new event). The duration, and sometimes the amplitude, of an earthquake signal are necessary for determining event magnitudes; thus, it may be impossible to calculate earthquake magnitudes when a volcano is very active. This problem is most likely to occur at volcanoes with limited networks of short period seismometers. This study outlines two methods for calculating earthquake magnitudes when events are clipped and over-run.
The first method entails modeling the shape of earthquake codas as a power law function and extrapolating duration from the decay of the function. The second method draws relations between clipped duration (i.e., the length of time a signal is clipped) and the full duration. These methods allow for magnitudes to be determined within 0.2 to 0.4 units of magnitude. This error is within the range of analyst hand-picks and is within the acceptable limits of uncertainty when quickly quantifying volcanic energy release during volcanic crises. Most importantly, these estimates can be made when data are clipped or over-run.
These methods were developed with data from the initial stages of the 2004-2008 eruption at Mount St. Helens. Mount St. Helens is a well-studied volcano with many instruments placed at varying distances from the vent. This fact makes the 2004-2008 eruption a good place to calibrate and refine methodologies that can be applied to volcanoes with limited networks.
Recommended Citation
Wellik, John J. II, "DOING MORE WITH SHORT PERIOD DATA: DETERMINING MAGNITUDES FROM CLIPPED AND OVER-RUN SEISMIC DATA AT MOUNT ST. HELENS", Master's Thesis, Michigan Technological University, 2014.