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Abstract
Permafrost degradation in the Source Area of the Yellow River (SAYR) has intensified under climate warming. Yet, the spatiotemporal patterns of freeze-thaw (F-T) dynamics remain poorly understood due to the limited availability of high-resolution data. Here, we integrate ERA5-Land reanalysis with a Digital Elevation Model (DEM) to develop a 1 km-resolution monthly surface temperature dataset (1981–2020), corrected for topographic bias using elevation-dependent temperature lapse rates. Based on this dataset, we calculate F-T indices (freezing/thawing index, thaw duration) and analyze their trends. Results show DEM correction significantly improves temperature accuracy (RMSE = 1.22 °C, ubRMSE = 0.38 °C). Over 40 years, air and surface freezing indices declined by –100.43 and –141.85 °C·d/10a, while thawing indices increased by 83.74 and 98.47 °C·d/10a, respectively. Thaw duration extended by 1.17 days/decade, with stronger trends in low-elevation zones. Freeze-thaw ratios (N-factor) exceeded 1 across all sites, indicating accelerated permafrost degradation. Spatial heterogeneity reveals thaw dominance in southeastern valleys (N > 5) versus residual freezing capacity in northwestern highlands (N < 2), driven by altitude and vegetation insulation. This study provides the first long-term, high-resolution F-T dataset for SAYR, demonstrating that topo-climatic gradients and vegetation feedbacks critically regulate permafrost stability. Our findings advance regional permafrost modeling and inform infrastructure resilience strategies in the context of climate change.

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