Mean-state warming loads Germany's extreme summer heat burden

European summers are warming rapidly, increasing the frequency and intensity of hazardous heat. Here, we quantify how mean-state warming has increased Germany's extreme summer heat burden and how that risk scales with global-warming level (GWL). We develop OMS (Observation-based Mean-Shift), an observation-based counterfactual framework that preserves observed day-to-day weather variability while shifting only the seasonal mean state. Using OMS, we estimate Germany's JJA mean-temperature sensitivity to global mean surface temperature (GMST) and translate observed summers to pre-industrial, +1.5 °C, and +2.0 °C climates by shifting the observed daily JJA series by beta times the change in GMST. Because only the seasonal mean is adjusted, OMS isolates the weather-preserving mean-state contribution to heat burden while leaving circulation statistics unchanged. Germany exhibits strong regional amplification, with an estimated sensitivity of 2.63 °C of local summer warming per 1 °C of global warming (95% confidence interval: 1.62–3.62). To connect warming to exposure-relevant outcomes, we define the extreme-heat burden (EHD), measured in °C day, as the cumulative degrees above a fixed national summer 95th-percentile threshold for 1991–2020. We apply OMS to the selected extreme summers of 2018, 2019, and 2022 within the 2004–2024 study period to construct GWL-consistent counterfactual realizations for each case while retaining intra-seasonal variability. Across all three summers, anthropogenic warming yields a substantial increase in EHD from pre-industrial to present-day conditions, with further marked increases toward +1.5 °C and +2.0 °C. Subnational analyses show coherent increases across all federal states, but substantial heterogeneity in magnitude, highlighting where risk intensifies most strongly as warming progresses. We additionally quantify per-capita EHD using population data and assess distributional equity across states. These observation-based estimates provide a transparent basis for heat-risk planning and adaptation by separating the realized anthropogenic contribution from the additional mean-state burden associated with higher global-warming levels.