- Emission mitigation and carbon dioxide removal to minimize climate suffering
6
- Mitigation, Removal, Geo-engineering
7
- Adaptation: Henri explaining the equations
8
- Mitigating emissions
9
- Cost & damages
10
- Henri on net cost & net benefit
11
- Picking up the slack carbon dioxide removal
12
- Alan on climate model incorporating economic variables
13
- David on Solving inverse problems
14
- Modeling with JuMP
15
- Example of JuMP (Unconstrained optimization)
16
- Constrained optimization
17
- MARGO source code with JuMP
18
- MARGO's automated optimization
19
- Henri on how optimal policy depends on the model's assumptions
20
- Wrap up (advice for interested CS students)
Description:
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.