This is an I-Series course. Therefore, it does not present a survey of humanity’s knowledge about natural hazards. Instead, GEOL200 stresses basic concepts, approaches, and vocabulary of geology, while focusing on helping you to understand how experts in natural hazards research, planning, and response employ terms, concepts, and approaches.
This course aims to introduce advanced undergraduate students to instrument design/performance, signal processing, data analysis and inverse theory in geophysics.
Students will learn how geophysical instruments work, how to relate their output to physical quantities, how to identify and apply a variety of signal processing and data analysis techniques. Students will learn to formulate, solve and evaluate geophysical inverse problems and will develop MATLAB programming skills.
The course is typically offered in the Fall semester.
Taught in: Fall 2012, 2013, 2014, 2015, 2016, 2017
These courses aim to introduce undergraduate and beginning graduate students to earthquakes as well as seismic wave generation and propagation.
Students will learn about stress and strain, the seismic wave equation, methods for calculating wave propagation through layered and heterogeneous media, imaging of shallow structure using seismic reflection, converted-wave and tomographic imaging of global structure. The final third of the course will focus on describing seismic sources – earthquakes, tremor, slip – understanding rate-and-state friction and ways of characterizing seismic hazard.
The course is typically offered in the Spring semester.
Taught in: Spring 2013, 2014, 2016, 2018
GEOL 789E – Inverse Theory Seminar
Prerequisite: By permission of instructor; this course assumes a working knowledge of multivariable calculus, linear algebra, basic statistics, and experience with computer programming.
This graduate level seminar will focus on the theory and practice of inferring unknown quantities from noisy geophysical observations. Particular emphasis will be placed on understanding uncertainty, both in describing the effects of noise on the observations and quantifying the errors on and trade-offs among the inferred parameters. Topics covered will include iterative-linearization and model-space-search approaches to non-linear problems, Bayesian formulations, and trans-dimensional inversion. Students will be expected to read and discuss articles from peer-reviewed scientific literature. Coursework and assignments will be built around a group, research-level, inversion project of the students’ own design, aimed at resolving quantities of interest to terrestrial and Martian geophysics.
Sivia, D.S., Data Analysis: A Bayesian Tutorial, Oxford University Press Inc., New York, 2006.
Tarantola, A., Inverse Problem Theory and Methods for Model Parameter Estimation, SIAM, Philadelphia, 2005.
Taught in: Spring 2015, 2017.