Code and data for "Global representation of extratropical cyclone precipitation and future trends in CMIP6 models" by M. Jucker et al., QJRMS (2025)

Code and derived data required to reproduce all published figures, including supplementary. How to run Requires xarray, pandas, seaborn, scipy, cartopy, parmap, aostools (provided here). Also requires local access to CMIP6 and ERA5 data to attach precipitation and 2-metre temperature to cyclones. To set up your working directory: this has to be called "stormtrack". Then cd into the stormtrack directory, download all files, then: tar -xf data.tar tar -xf aostools.tar tar -xf code.tar The hardest part is to get the script to read CMIP6 and reanalysis data. The code uses intake paths to find the data for each model and member. If that's not an option for you, you will need to provide file paths for all CMIP6 data in stormtrack/functions.py -> GetCMIPData(). Custom paths are used for ERA5 in the script, so look for the case model == 'ERA5' to see how to change the code to access your version of CMIP6 data. The same applies to ERA5 and JRA55 data. Once everything is in place, run sh code/create_data.sh Note, this will take several hours if not days. To create all the paper figures, run sh code/create_paper_figures.sh