Climate Change Sensitivity and Regional Differences of the Upper Limit of Montane Deciduous Broad‐Leaved Forests Across the Northern Hemisphere

ABSTRACT Montane deciduous broad‐leaved forests across the Northern Hemisphere serve as sensitive ecological indicators of climate change, yet the climate change drivers of the upper limit of montane deciduous broad‐leaved forests (ULMDBs) remain difficult to quantify. Here, we introduce a novel cloud model‐based analytical framework that integrates multisource remote sensing data to extract ULMDB locations and associated impact factors. Using the digital features of the weight coefficient cloud model, we derive a temperature sensitivity index (TSI), a precipitation sensitivity index (PSI), and a comprehensive sensitivity index (CSI), enabling a quantitative assessment of hemispheric‐scale differences in ULMDB climate change responses. Our results reveal pronounced regional differences. In humid regions, 70% of mountains show TSI contribution rates exceeding 50%, indicating temperature‐dominated controls. In arid and semi‐arid regions, more than 80% of mountains exhibit PSI contribution rates above 50%, demonstrating strong sensitivity to precipitation. ULMDBs in East Asian study region show notably higher climate change sensitivity, with a mean CSI of 9.909 and a distinct “increase–decrease” latitudinal pattern, whereas ULMDBs in European study region show a monotonic latitudinal decline. Most ULMDBs occur within humid continental climates (68% of the sample), where 58% show TSI contribution rates above 50%, reflecting greater sensitivity to temperature than to precipitation. Sensitivity indices further suggest that potential responses are most likely where TSI is high, followed by areas with high CSI, whereas PSI‐dominated regions show weaker upward potential. The widespread regional differences indicate that ULMDB climate change sensitivity is governed not by single factors but by the interactions among temperature, precipitation, and regional geographic conditions. The proposed cloud model framework provides a transferable approach for quantifying ecological boundary sensitivity under uncertainty and offers new tools and perspectives for understanding climate change responses of montane forest ecotones and other climate‐sensitive transition zones.