Project 1: Reproducibility in Climate Studies

• Statistics 159/259, Fall 2025

• Due 10/23/2025, 11:59PM PT

• Prof. F. Pérez, GSI J. Butler, and GSI S. Andrade, Department of Statistics, UC Berkeley.

• Your score for this assignment is out of 50 points. This project as a whole accounts for 10% of the final course grade.

• Assignment type: group project assignment

The assignment content is located in proj01-climate.ipynb.

Deliverables: For this assignment, you will have a single GitHub repository for your group. Your repository should contain the following:

• One notebook PER QUESTION in the assignment notebook that includes code to create the plots and simulations the question asks for, along with your written responses and discussion. Please remember to use markdown headings for each section/subsection so the entire notebook document is readable. All figures should be both rendered in the notebook and saved in a separate folder called outputs.

• Complete the contribution statement in contribution_statement.md, briefly and qualitatively detailing each group member’s contributions to the assignment.

• An ai_documentation.txt file where your group will put any prompts and output from AI companions.

There are two parts to this homework:

1. Reproducing the lecture result using the Mauna Loa CO2 data (Questions 1-3).

2. Reproducing Figures 1-3 in this paper (Questions 4-6).

We have provided you with the Matlab code that was used to generate such figures, in the matlab folder. This may help you as a guide for running the analysis, but it is not expected that you use the Matlab code as a template for yours.

The total grade for this homework is divided between:

• [15 Points] The Manua Loa CO2 Data.

• [30 Points] The West Coast Heat Wave.

• [5 Points] Project Structure. See next section for mode details

When running your analyses and making plots, it may be useful to save xarray datasets as netcdf files and then read them in order to make just the plots. You can do this with xarray.Dataset.to_netcdf.

Project Structure¶

In this homework we are going to evaluate your overall workflow using git and GitHub. Be sure that you repository includes clear commit messages as you make progress on the homework, and not include any other file or folder that those needed for the project. To ensure that extraneous files are ignored by git, we have added a .gitignore where you can either specify single files, or all files with a particular file extension. Additionally, the code in each notebook must be well organized. Use different cells for different operations and functions and markdown cells to explain the analysis. You can also use different branches or make a fork of the main repository (and then a pull request) in order to work collaboratively on the same notebook.

You will have to divide the notebook hw03-climate.ipynb into six different notebooks, one for each question. Name each one of these notebooks climate-QXX.ipynb, with XX corresponding to the number of the question (eg, climate-Q02.ipynb). You will have to move the code from hw03-climate.ipynb to each notebook in such a way that each notebook can be executed. You will have to take a look at which imports to make and what data to read in each notebook. For the final deliverable, remove the notebook hw03-climate.ipynb from the repository. Also, please include the ai_documentation.txt file.

Acknowledgment: Large part of the contents in this homework assignment were done by Dr. Chelle Gentemann.