The thermal state of permafrost under climate change on the Qinghai-Tibet Plateau (1980-2022): A case study of the West Kunlun

Abstract

The thermal regime is a key indicator of permafrost evolution and thaw trajectories in response to climate change but remains poorly represented in global models. In this study, we applied the Moving-Grid Permafrost Model (MGPM), an efficient numerical model, to simulate the permafrost thermal regime in West Kunlun (WKL), a 55 669 km2 region on the remote northwestern Qinghai-Tibet Plateau characterized by extreme cold arid conditions. To improve computational efficiency, we used clustering methods and parallel computing. The model was forced with remote-sensing-based land surface temperature (LST) data from 1980 onward (1 km × 1 km spatial, monthly temporal resolution), reconstructed using machine learning techniques that integrated field observations, satellite imagery, and reanalysis products. The MGPM demonstrated high stability throughout the simulation period, achieving high accuracy (±0.25 °C for ground temperature and ±0.25 m for active-layer thickness), outperforming previously reported results. From 1980 to 2022, LST increased by an average of 0.40 °C per decade. The responses of the permafrost regime to climate warming were closely related to the original thermal conditions shaped by historical climatic evolution. These responses exhibited a distinct altitude-dependent spatial variation and differed according to soil stratigraphic types. Despite ongoing thermal shifts, the spatial extent of permafrost in WKL has remained relatively stable over the last 43 years, reflecting the delayed response of deep permafrost to surface warming. These results offer valuable insights into permafrost thaw trajectories and support improved projections of future permafrost degradation in data-scarce, high-altitude regions.