Learn the basics of climate physics and coding
Prerequisites: High School Math and Physics with a grade of C or higher, and basic understanding of programming
Building climate models is designed to engage students to investigate the physical basis of climate change and learn Python coding skills to solve mathematical and physical equations. Topics covered will include, principles of the conservation of energy, theories and observations of Earth’s energy balance and climate feedbacks. Throughout the course, a mixture of lectures and interactive Python exercises with Jupyter notebook to introduce scientific principles and step-by-step Python practices to students will be introduced. This course is unique in several ways: 1) it provides hands-on exercises for students to explore the physical principles of Earth’s energy balance and climate feedbacks; 2) it allows students to learn Python coding with Jupyter notebook and apply it to study a societally relevant scientific question, i.e., the physical basis of climate change.
This course will advance students’ understanding of dynamical models and the concept of climate change through hands-on practices of building dynamical models and exploring physical principles driving climate change. In addition, this course will also advance students' computer literacy through introductions and exercises on writing Python code to solve and visualize simple dynamical models.
These outcomes directly contribute to students’ college application success by providing students with the experience of taking a college-level class. Students will also gain demonstrative coding skills to computationally solve mathematic equations. Climate Change and/or environmental literacy is one of the core knowledge requirements of the general education at many universities. This course will prepare students for college-level courses that teach this literacy. Moreover, through coding exercises, students are also exposed to Python programming, which may inspire their interests and prepare them for the continued education in data science and computational physics and climate sciences.
Sessions Offered
Session 5: July 23 - July 29
Course Fees
Format
Residential, Non-Credit
Related Courses
This class is meant to be immersive and students will:
- Apply the concepts of energy balance and climate feedbacks to explain the Earth's temperature evolution
- Construct models that describe Earth’s energy balance and climate feedbacks
- Code and solve equations and make visualizations with Python coding and Jupyter Notebook
- Lead or participate in collaborative group projects and make presentations
Meet the Professor
Ran Feng, Ph.D., Assistant Professor
Growing up in southwest China, Ran studied meteorology and climate at Nanjing University, and Institute of Atmospheric Physics, Chinese Academy of Sciences. Ran became fascinated by climate change and decided to work towards a PhD at the University of Michigan. Ran is currently interested in cloud and precipitation processes in warm climate states, and feedbacks that determine the sensitivity of climate system to forcings from greenhouse gases and other geological changes. Ran is currently teaching two courses separately on how to apply multivariate statistic methods to study observations of the Earth, and how climate models are constructed and implemented to make projections.
