Spatiotemporal distribution variation of extreme temperatures under elevation-dependent warming and its response characteristics to regional warming in Qinling-Daba Mountains, China.

This study analyzed daily temperature data from 114 meteorological stations in the Qinling-Daba Mountains from 1980 to 2017, focusing on core zones (CE I ≥ 2274 m, CE II 1321-2274 m) and peripheral zones (PE I 668-1321 m, PE II < 668 m). Using 15 extreme temperature indices computed with RClimDex, we assessed the spatiotemporal patterns, trends, and response to climate warming of extreme temperature events across different elevation zones. The Mann-Kendall test and Sen's slope estimator were employed to quantify trends, and the driving mechanisms of extreme temperature indices in different altitudinal zones were explored through Random Forest models and Pearson correlation analysis. Results indicate a significant warming trend in extreme temperatures in the study area from 1980 to 2017, characterized by an increase in extreme high-temperature events, a decrease in extreme low-temperature events, and an asymmetrical warming pattern. The regional sensitivity ranking is CE II ≈ CE I > PE I > PE II, suggesting that CE I and CE II are most sensitive to warming, while the lower‑elevation PE I and PE II exert a buffering effect. Extreme temperature changes are jointly influenced by latitude and topography: heat events display a "strong south, weak north" pattern, while cold events show the opposite distribution; diurnal temperature range exhibits a "large north, small south" pattern. From west to east, extreme high temperatures and growing season length increase, while extreme low temperatures and frost days decrease. Notably, the Qinling-Daba Mountainsexhibit positive elevation-dependent warming (EDW) effect, with stronger extreme warming at higher elevations than at lower elevations. Factor analysis reveals that extreme temperature indices in the all zones are mainly controlled by temperature and large‑scale atmospheric-oceanic circulation. In contrast, CE II and PE I zones are influenced by the synergistic effects of multiple factors, including temperature, moisture conditions, sunshine duration, and topography. This results highlight climatic anomalies in mountainous regions caused by complex topography and multi-factor interactions, clarifying how regional hydrothermal conditions and large-scale atmospheric circulation regulate climate change in high-altitude mountainous areas. This study deepens understanding of climatic processes in Chinese mountain systems, offering high-resolution, multi-factor case study and theoretical basis for extreme climate response, hazard risk assessment, and adaptation management in global mountainous regions.