This repository contains the code used to analyze model output and make the figures for Goldblatt et al 2021: 'Earth's Long Term Climate Stabilized by Low Clouds', https://doi.org/10.1038/s41561-021-00691-7
Model output from this experiment is available and can be downloaded from https://doi.org/10.20383/101.0308
Code is written in python and makes use of the Climate Data Operators (CDO) version 1.7.0 for processing the model output. For most scripts, CDO is used to extract the variable(s) from the model output, process it by time averaging, selecting a pressure level, or calculating a new variable, and then saves this processed output to a new NetCDF file, which is then plotted using Matplotlib.
These processing steps can be time intensive, taking up to ~20 minutes before the figure will be plotted. The processing for Figure 6 and ED Figure 2 may take ~1 hr. Intervening steps will be written to the terminal to track progress. There are certainly lots of ways this could be better optimized.
Since processing the model output is the more time-intensive step, saving the processed variables to their own files means that the processing only needs to be done once, and then subsequent changes to the figures are much faster.
Also included is an environment.yml file - this describes the python libraries required to run the scripts and it is recommended to make a new conda environment using this yaml file before you run the scripts.
Importantly, you will also need to download and install the Climate Data Operators (https://code.mpimet.mpg.de/projects/cdo/wiki#Installation-and-Supported-Platforms), NetCDF (https://www.unidata.ucar.edu/downloads/netcdf/), and HDF5 (https://www.hdfgroup.org/downloads/hdf5/source-code/) manually. These three installations can be a bit troublesome but if you install HDF5 first, then NetCDF, then finally configure CDO before installing, it should go smoothly. ** Please consult the support pages for these software packages if you have trouble.
Note that to read the large NetCDF2 files version 1.7.0 of CDO must be used. If you have other versions of CDO installed, you may need to change the commands in processing_functions.py to the location of version 1.7.0 instead, ie: replace instances of r"//usr//bin//cdo " with "cdo" if that is the only installed version, or the path to version 1.7.0 if different.
Also, the processed model output will be saved to new netCDF files that are then used to make the figures. The variable outfileloc in each figure script points to the location where these processed files will be saved, and the directory must already exist on your system, so please create a new directory (we recommend outside of this repository), or change to point to an existing directory.
Figure 3, and Extended Data Figures 2, and 6 rely on MATLAB scripts for some of the processing and plotting, although in all cases some processing is done using python first. We recommend running the .py script associated with each figure, then run the associated MATLAB scripts to complete the processing or figure plotting. For Fig 3 and ED Fig2, you will then need to rerun the .py files to finish plotting the figures.
NOTE: there are currently some problems with the code for the histograms in Extended Data Figure 6. These will be updated soon, but please get in touch if you need them in the meantime.
General correspondence about the paper and methods should be directed to corresponding authors Colin Goldblatt ([email protected]) and Victoria McDonald ([email protected]).
Questions about the code in this repository can be sent to Victoria McDonald ([email protected]), or open an issue in the GitHub repository.