Code underlying analysis performed in
Jan Wohland, Process-based climate change impact assessment for European winds using EURO-CORDEX and global models, Environmental Research Letters, Vol. 17, Number 12, 2022, https://doi.org/10.1088/1748-9326/aca77f
If you use content of this repository or code derived from it in academic work, please cite the above publication.
The intention of this repository is to document the analysis in an attempt to make scientific work more transparent and reproducible.
Most data is accessed using the intake package in the DKRZ ecosystem. Intermediate data is made available in the output folder to enable reproducibility at other institutions as well, see below for the link and instructions.
Land use change data is taken from LUH and can be retrieved by executing download_LUH1.sh.
The offshore assessment relies on the shapes of EEZ, in particular the World EEZ v11 (2019-11-18) shapefile provided by the Flanders Marine Institute and available at https://doi.org/10.14284/386
Download and extract the data to data/EEZ/ and remove everything except for the LICENSE and eez_v11.shp.
Intermediate data (i.e., results from running everything under Calculations in run_all.py) are provided in a zenodo data repository. Download the data from https://doi.org/10.5281/zenodo.7372998, extract the zipped output.zip folder and move it into the same folder as code.
The anaconda environment can be constructed from the provided files using
conda env create --file environment.yaml
You can activate it using
conda activate kliwist_modelchain
on a UNIX system. You might have to use source on other systems.
| Figure | Filename | Creating python function |
|---|---|---|
| Fig. 1 | windchange_mean.png | plot_s10_maps.make_joint_plots() |
| Fig. 2 a-c | diff_landuse.png | plot_lu_maps.make_LUH_maps() |
| Fig. 2d | pattern_correlation.png | compute_plot_pattern_correlation.make_plot() |
| Fig. 3 | heatmap_mean_countries.jpeg | plot_s10_country_heatmaps.make_s10_heatmaps(onshore=True) |
| Fig. 4 | heatmap_mean_countries_offshore.jpeg | plot_s10_country_heatmaps.make_s10_heatmaps(onshore=False) |
| Fig. 5 a-c | scatter_diff_United Kingdom_offshore.jpeg | plot_s10_scatter.make_s10_scatter(onshore=False) |
| Fig. 5d | Scatter_plot_United Kingdom_offshore_True.jpeg | plot_temperature_gradient.make_all_plots() |
| Fig. 6a | Correlation_map_Europe.jpeg | plot_temperature_gradient.make_all_plots() |
| Fig. 6b | Amplitude_map_Europe.jpeg | plot_temperature_gradient.make_all_plots() |
All Figures can be created at once by executing the script run_all.py or the Notebook run_all.ipynb. Script and notebook execute the same code, so feel free to choose whichever route you prefer.