Accompaying scripts for Schleussner et al. Overconfidence in Climate Overshoot

This repository contains the scripts that accompany the paper

Schleussner, C.-F., Ganti, G, Lejeune, Q., Zhu, B., Pfleiderer, P., et al.,

Overconfidence in Climate Overshoot

Data and citations

The IPCC AR6 WG III scenario data that is used in this paper can be obtained from here. The data file should be placed in the data folder. Please cite the following:

Chapter 3 of the WG III contribution to the IPCC's 6th Assessment Report

Riahi, K. et al. Mitigation pathways compatible with long-term goals. in IPCC, 2022: Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (eds. Shukla, P. R. et al.) (Cambridge University Press, 2022). doi:10.1017/9781009157926.005.

The AR6 scenario database hosted by IIASA

Byers, E. et al. AR6 Scenarios Database. (2022) doi:10.5281/zenodo.5886912.

You will need to place the folder fair_temperatures and the file tier1_emissions.csv from here in the data folder.

To reproduce figure 3, E5, E6: Please execute 301_NorESM2-LM_GFDL-ESM2M.ipynb using the provided data.

To reproduce figure E7, E8: Please download CMIP6 runs for the scenarios SSP119 and SSP534-over from https://esgf-data.dkrz.de/search/cmip6-dkrz/ and change paths in the scripts analysis/302_, analysis/303_ and analyis/304_ according to your download loactions.

Note

Please refer to the README.md document in the analysis folder for instructions on the individual analysis steps. It documents the content in each notebook.

Installation

The analyis has been performed in python and is documented in Jupyter Notebooks. A conda environment with the required dependencies has been created to facilitate installation. 

$ conda env create --file environment.yml

$ conda activate provide_perspective