A transparent workflow for selecting heatwave stress-test years for energy system modelling

Energy-system studies often rely on a small number of weather years to test system performance under extreme conditions. Translating observational and climate-projection datasets into traceable and model-ready stress-test scenarios is an important interface between climate information and energy-system modelling. However, the selection of heatwave stress-test years is difficult to reproduce because the link between climate data, heatwave definition, spatial aggregation and scenario year is not always documented. This study presents a transparent workflow for selecting heatwave years from gridded observations and climate-model projections. The workflow uses the Heat Wave Magnitude Index daily (HWMId) as an event-based metric that combines heatwave duration and locally normalized temperature anomaly and ranks years according to spatially aggregated heatwave severity. Applied to a Germany–France case study, the workflow identifies 2003 as the strongest completed historical heatwave year and shows that the June 2026 event, evaluated using ERA5 and NOAA CORe data through 1 July 2026, approaches but remains slightly below the 2003 benchmark. Future stress-test years vary across CORDEX-CMIP5 and CORDEX-CMIP6 projection chains, confirming that selected years should be reported together with the climate data product, model chain, spatial domain and ranking criterion defining them. Sensitivity analyses across temperature thresholds, reanalysis datasets, regional definitions, electricity-generation-capacity and population weightings show robust stress-test years per dataset and model chain, although their ordering can change. The workflow provides energy-system researchers and practitioners with a reproducible way to translate climate data into traceable heatwave stress-test scenarios while retaining information on the data product, climate-model chain, spatial domain and selection criterion.