Global Burned Area Increasingly Explained By Climate Change

Python code accompanying ISIMIP3a burned area attribution. (updated August 2024)

Chantelle Burton & Seppe Lampe

Full author list: Chantelle Burton¹ and Seppe Lampe^{1 2}, Douglas I. Kelley, Wim Thiery, Stijn Hantson, Nikos Christidis, Lukas Gudmundsson, Matthew Forrest, Eleanor Burke, Jinfeng Chang, Huilin Huang, Akihiko Ito, Sian Kou-Giesbrecht, Gitta Lasslop, Wei Li, Lars Nieradzik, Fang Li, Yang Chen, Jim Randerson, Christopher P.O. Reyer & Matthias Mengel

¹ Equal contribution

² Corresponding author: seppe.lampe@vub.be

Article under review. Preprint available.

Code availability

This repository contains 5 notebooks that contain the entire workflow of our analysis.

We make use of two observational burned area datasets, FireCCI5.1 and GFED5. We also use simulations by seven models of the ISIMIP framework.

How to run this code

1. Navigate to a desired directory and clone this repository (in terminal)

   git clone https://github.com/SeppeLampe/Global-Burned-Area-Increasingly-Explained-By-Climate-Change.git
   

2. Download the data in the corresponding folders

   Download the FireCCI5.1 filestructure to Data\Observations\FireCCI5.1\Original.
   Download the GFED5 filestructure to Data\Observations\GFED5\Original.
   Download the ISIMIP3a Fire Sector OutputData to Data\ISIMIP\OutputData\fire.
   

3. Create a new conda environment

   conda env create --file=environment.yml
   

4. Launch Jupyter Lab

   jupyter lab