From weather to system extremes - how much data is enough?

Extreme periods in highly renewable energy systems will be shaped as much by internal system interactions as by meteorological anomalies, yet most studies assess them in isolation. This gap is critical for sector-coupled systems, where cross-sector dynamics can trigger stress even under moderate weather conditions. Using six decades of simulations of a net-zero, sector-coupled networked European energy system, we evaluate different stress indicators comparing their ability to identify extreme events against their modeling requirements. System-aware indicators, such as Consumers Cost and Positive Residual Energy Demand, are computationally demanding but reproduce benchmark extremes, defined by Unmet Energy Demand, more consistently. Purely meteorological indicators (Wind Capacity Factors and Heading Demand) are easy to calculate but often highlight less relevant periods. Our classification of historic weather years supports efficient scenario selection and reveals how sector coupling fundamentally reshapes stress patterns.