Robust Satellite Technique Detection of Extreme Heat Events in Italy: A 26-Year (2000–2025) Study of Non-Stationary Thermal Baselines

Extreme heat events pose significant socio-ecological risks across the Mediterranean region, with Italy being particularly vulnerable due to its complex topographies, microclimates, and non-stationary land surface temperature (LST) patterns driven by accelerating climate change. To overcome the limitations of fixed baseline thermal monitoring in non-stationary thermal environments, this study applies the Robust Satellite Technique (RST) to a 26-year record (2000–2025) of Moderate Resolution Imaging Spectroradiometer (MODIS) Terra daytime LST data to systematically detect and characterize extreme heat events across Italy. By deploying a leave-one-out baseline climatology and multi-criteria event definitions (\(\Omega_{\mathrm{SAT}} \ge 2.0\), minimum 3-day duration, and ≥10% spatial coverage), we isolate thermal anomalies while excluding seismically active years (2008, 2009, 2013) that corrupt baseline statistics. Validation against major historical heat waves (2003, 2017, 2021) confirms that the framework reliably captures regional heat footprints, showing peak cumulative heat wave frequency concentrated across the Po Valley, southern Alpine foothills, and the Adriatic coastal corridor. Analysis of peak spatial events shows that while extreme anomalies can extend into spring (e.g., March 2001, covering 43% of land area) vulnerability remains most acute during summer. Although national seasonal mean anomalies display no statistically significant trend due to high interannual variability, pixel-wise trend analysis uncovers a localized July warming hotspot (Sen slope > +0.03 \(\Omega_{\mathrm{SAT}}\) year\(^{-1}\), \(p \le 0.05\)) across 8.0% of land pixels, heavily centered in the northeastern Po Valley. These findings highlight the strength of high-quality satellite remote sensing in delineating non-stationary sub-regional heat vulnerability and guiding targeted climate adaptation strategies across heterogeneous landscapes.