Prof. Stephen Arrowsmith
Hamilton Chair in Earth Sciences
Huffington Department of Earth Sciences
Southern Methodist University
In geophysics, we use a variety of different types of signal to study the Earth. I specialize in using seismic and low-frequency acoustic (or ‘geoacoustic’) signals to study the geosphere and atmosphere, and to monitor both natural and human sources. Many of the most significant discoveries in geophysics were based on small numbers of observations and simple analytical models. To further the science, the emphasis today is on the development of computationally-intensive numerical models and/or the application of numerical methods to very large datasets. My research focuses on the development and application of numerical methods for modeling the generation and propagation of waves in the solid earth and atmosphere, processing large datasets, and inverting observations to improve our understanding of the solid earth or atmosphere. I also have a long-standing interest in the use of seismology and geoacoustics for national security applications, and enjoy putting geophysics techniques to use for important practical uses.
- To improve our fundamental understanding of the generation and propagation of seismic and geoacoustic waves.
- To design algorithms that get more out of data.
- To make practical contributions to important national and international challenges.
- To teach classes that improve critical thinking and help students develop relevant skills for future.
- To communicate the value of science to non-experts and the general public.
Recent publications include work I’ve done in seismology, infrasound, and data science.
Atmospheric waves and global seismoacoustic observations of the January 2022 Hunga eruption, Tonga
Matoza, R. et al.
Illuminating the North Korean nuclear explosion test in 2017 using remote infrasound observations
Che, Il-Young and Kim, Keehoon and Le Pichon, Alexis and Park, Junghyun and Arrowsmith, Stephen and Stump, Brian
A Data Driven Framework for Automated Detection of Aircraft Generated Signals in Seismic Array Data Using Machine Learning
Zhang, Xinxiang and Arrowsmith, Stephen and Tsongas, Sotirios and Hayward, Chris and Meng, Haoran and Ben-Zion, Yehuda
Evidence for Short Temporal Atmospheric Variations Observed by Infrasonic Signals: 1. The Troposphere
Averbuch, Gil and Ronac-Giannone, Miro and Arrowsmith, Stephen and Anderson, Jake