Estimation of Full Moment Tensors, Including Uncertainties, for Nuclear Explosions, Volcanic Events, and Earthquakes
Abstract
A seismic moment tensor is a 3 × 3 symmetric matrix that provides a compact representation of a seismic source. We develop an algorithm to estimate moment tensors and their uncertainties from observed seismic data. For a given event, the algorithm performs a grid search over the six‐dimensional space of moment tensors by generating synthetic waveforms for each moment tensor and then evaluating a misfit function between the observed and synthetic waveforms. “The” moment tensor M0 for the event is then the moment tensor with minimum misfit. To describe the uncertainty associated with M0, we first convert the misfit function to a probability function. The uncertainty, or rather the confidence, is then given by the “confidence curve” , where is the probability that the true moment tensor for the event lies within a certain neighborhood of M that has fractional volume V. The area under the confidence curve provides a single, abbreviated “confidence parameter” for M0. We apply the method to data from events in different regions and tectonic settings: 17 nuclear explosions and 12 earthquakes at the Nevada Test Site, 63 small (MwMw>4) earthquakes in the southern Alaska subduction zone. Characterization of moment tensor uncertainties puts us in better position to discriminate among moment tensor source types and to assign physical processes to the events.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jun 01, 2018
- Source ID
- 10.1029/2017jb015325
Entities
People
- Carl Tape
- Celso Alvizuri
- Lion Krischer
- Vipul Silwal
Organizations
- Air Force Research Laboratory
- ETH Zurich
- National Science Foundation
- Swiss National Science Foundation
- University of Alaska System
- University of Lausanne