Courses
CURRENT COURSES
ATS 780-A8: Weather-to-Climate Data Driven Forecasting
Data-driven approaches (e.g. machine learning) for forecasting are proving to be incredibly powerful – transforming prediction science. This course covers the scientific basis for data-driven forecasting methods from days-to-decades and explains how these methods are applied and evaluated for use in research and forecasting of Earth system processes (e.g. weather, climate, air quality, wildfires). Throughout the course, students will design, build, analyze and evaluate their own data-driven prediction systems.
Taught Fall 2024
ATS 655: Objective Analysis for the Atmospheric Sciences
The course provides an overview of the methods used to interpret data sets in the atmospheric and oceanic sciences, including basic statistics, matrix methods, spectral filtering & time series analysis, and basic machine learning methods. Emphasis is placed on applications to real world Earth system data.
typed notes [link]
Taught Spring 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024, 2025
ATS 780A7: Machine Learning for the Atmospheric Sciences
An overview of machine learning methods used to interpret data sets in the atmospheric/Earth sciences with an emphasis on implementation and interpretation of the results, including learning new science. Topics include foundational concepts in machine learning, random forests, basic neural networks, advanced neural networks, unsupervised learning, and new frontiers in the field.
Taught Spring 2022, Fall 2023
PAST COURSES
ATS 601: Atmospheric Dynamics I
Basics of atmospheric dynamics and geophysical fluid dynamics on a rotating sphere.
typed notes [link]
Taught Fall 2016, 2017, 2018, 2020, 2021
Machine Learning Tutorial
Slides and code to introduce applied machine learning methods to earth scientists.
ATS 780: Atmosphere's Response to Climate Change
link to course webpage for Fall 2014