A case study utilising forecast-based event attribution to study the response of storm Babet (October 2023) to climate change. Also included are some plotting routines to compare to other attribution methods.
How do midlatitude cyclones such as storm Babet respond to climate change? How do the results of attribution methods differ and how can they be synthesised?
PGW_analysis: Plotting routines for the analysis of pseudo-global warming simulationsanalogues: initial code to calculate flow analogues from ERA5babet: Contains classes and functions that are used in the data post-processing and analysisdata: some smaller data files, not tracked in gitdata_scripts: python scripts to calculate post-processed variables such as vertically integrated advection. These can then be used with slurm.docs: environment file which creates a virtual environment to run the code in this reponotebooks: main data analysis on forecast-based runs in python notebooks, includes folder of figures. Notebooks were numbered sequentially and figures are numbered based on the notebook that created them.