The study of seismo-acoustic events is by no means new. Observations of earthquake-induced infrasound signals are dated back to the 1950s. However, the relative recent deployment of the International Monitoring System (IMS) by the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) provided world coverage for such signals. The continuous monitoring led to many detections of seismo-acoustic events and brought interest in this field back. Driven by unique and complex seismo-acoustic observations, this study uses array processing techniques to analyze the recorded data, back-projections to determine the origins of the infrasonic signals and numerical models to simulate infrasound wave propagation in coupled geophysical systems. The North Korean underground nuclear tests in 2013, 2016, and 2017 generated atmospheric infrasound. Detections were made in the Russian Federation (I45RU) and Japan (I30JP) IMS microbarometers arrays. These detections formed the basis of the presented empirical studies on the seismo-acoustic wavefield. It is shown that atmospheric variability can explain only part of the observations; therefore, changes in the source characteristics must be considered. Moreover, back-projections show that infrasound radiation is not confined to the epicentral region. More distant regions are found to be consistent with locations of topography, sedimentary basins, and underwater evanescent sources. A seismo-acoustic numerical model is used to simulate long-range infrasound propagation from underwater and underground sources. The Fast Field Program (FFP) is used to model the seismo-acoustic coupling between the solid Earth, the ocean, and the atmosphere under the variation of source and media parameters. A thorough analysis of the seismo-acoustic coupling mechanisms reveals that evanescent wave coupling and leaky surface waves are the main energy contributors to long-range infrasound propagation. Moreover, it is found that source depth affects the relative amplitude of the tropospheric and stratospheric phases. This characteristic is further employed in an infrasound based inversion for the source parameters. A Bayesian inversion scheme is tested on synthetic data under the variations of the number of stations, the signals frequency band, and the signal-to-noise ratio (SNR). Also, an ensemble of realistic perturbed atmospheric profiles is used to investigate the effect of atmospheric uncertainties on the inversion results. Results show that variations in the number of stations, their positions, and SNRs, lead to source strength estimations with uncertainties up to 50%. However, all of the estimated depths were within a 100 m range from the original source depth.
|Qualification||Doctor of Philosophy|
|Award date||9 Mar 2020|
|Publication status||Published - 2020|
- wave propagation
- array processing