Supplementary Python code for:
Carlier, N., Vandelanotte, K., Van de Vyver, H., Van Schaeybroeck, B., & Caluwaerts, S. (2026). Once upon a future heatwave: A practical storyline chain from existing climate data to stakeholder engagement. Climate Services, 43, 100681. https://doi.org/10.1016/j.cliser.2026.100681
If you use this code in your work, please cite the paper above.
hw.ipynb provides a general object-oriented framework for automatically processing daily temperature series.
anomalies.ipynb is a Python notebook in which the LGWR is calculated as described in the article.
scaling.ipynb is a Python notebook in which the LGWR is applied in scaling an observational temperature series for Brussels to GWL2.0.
mining_selected_sims.ipynb contains code for mining years of extreme heat from the KS-filtered set of EURO-CORDEX simulations using GWS targets.
WBGT and productivity loss calculations for the demo year are contained in productivity_2060.ipynb.
Fire hazard calculations for the demo year are contained in fwi_2060.ipynb.
Modelling of Zeeschelde water temperatures during the demo year is done in Zeeschelde_temp2060.ipynb.
All necessary data can be accessed freely or can be made available upon request. Some external Python packages may need to be installed for the impact analysis.