Climate, Environment, and Sustainability Infusion Fellowship (CESIF)

Studio 12: Climate change attribution and multivariate regression

This studio explores how temperature is driven by natural (solar) and anthropogenic (greenhouse gases, aerosols) forcing, using multivariate linear regression to fit these factors to the observed temperature data and estimate (attribute) how each has contributed to global warming. Students read the Studio 12 Instructions file and complete Studio 12 (R). Solution code is in Studio 12 Solutions (R). Output images are saved for reference.

Studio 12 Instructions (PDF)

Studio 12 (R)

Studio 12 Solutions (R)

Data File

Climate Data (CSV)

Output Images

Climate Time Series (PDF)

Climate Time Series Fits (PDF)