Explore climate change modeling in this comprehensive lecture from MIT's Computational Thinking Spring 2021 series. Dive into the MARGO (Mitigation, Adaptation, and Geoengineering Optimization) model, learning about emission mitigation, carbon dioxide removal, and geoengineering strategies to minimize climate suffering. Understand the equations behind adaptation, cost and damages calculations, and the concept of net benefit in climate policy. Discover how to solve inverse problems and use JuMP for both unconstrained and constrained optimization in climate modeling. Gain insights into incorporating economic variables into climate models and see how optimal policies depend on model assumptions. Conclude with valuable advice for computer science students interested in climate modeling.
Overview
Syllabus
- Welcome.
- Introduction to MARGO.
- Henri on the motivation behind MARGO.
- How to interact with the climate model.
- Emission mitigation and carbon dioxide removal to minimize climate suffering.
- Mitigation, Removal, Geo-engineering.
- Adaptation: Henri explaining the equations.
- Mitigating emissions.
- Cost & damages.
- Henri on net cost & net benefit.
- Picking up the slack carbon dioxide removal.
- Alan on climate model incorporating economic variables.
- David on Solving inverse problems.
- Modeling with JuMP.
- Example of JuMP (Unconstrained optimization).
- Constrained optimization.
- MARGO source code with JuMP.
- MARGO's automated optimization.
- Henri on how optimal policy depends on the model's assumptions.
- Wrap up (advice for interested CS students).
Taught by
The Julia Programming Language
