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Research Article | Open Access

Prevailing thermal models underestimate permafrost thermal state in the Tibetan Plateau: Implications for cryosphere adaptation

Yu-Feng ZHAOaYing-Ying YAOa( )Hui-Jun JINb,c,dTai-Hua WANGeXiao-Dong WUfXian-Hong MENGg,hChun-Miao ZHENGiDa-Wen YANGe
Institute of Global Environmental Change, Xi’an Jiaotong University, Xi’an 710049, China
School of Civil Engineering and Transportation, China‒Russia Joint Laboratory of Cold Regions Engineering and Environment, and Permafrost Institute, Northeast Forestry University, Harbin 150040, China
State Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Ministry of Natural Resources Field Observation and Research Station of Permafrost and Cold Regions Environment in the Da Xing’anling Mountains at Mo’he, Natural Resources Survey Institute of Heilongjiang Province, Harbin 150036, China
State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
Cryosphere Research Station On the Qinghai‒Tibet Plateau, State Key Laboratory of Cryospheric Science and Frozen Soil Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Zoige Plateau Wetland Ecosystem Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
School of the Environment and Sustainable Engineering, Eastern Institute of Technology, Ningbo 315201, China

Peer review under responsibility of National Climate Centre (China Meteorological Administration)

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Abstract

Understanding thermal dynamics of permafrost is essential for maintaining the cryosphere eco-hydrological system and infrastructure. The mean annual ground temperature (MAGT) serves as a key indicator calculated by thermal models to assess the extent of permafrost degradation. However, the ability of these models to accurately represent real thermal changes, along with the uncertainties and sensitivities involved, remains unclear limiting global permafrost projection and adaptations. This study focuses on a representative permafrost basin in the Tibetan Plateau to quantify the biases, sensitivities, and uncertainties of two widely used thermal models—empirical equilibrium models and transient numerical models using the Generalized Likelihood Uncertainty Estimation (GLUE) framework. Our results reveal that thermal models originally developed for Arctic permafrost may underestimate the MAGT of permafrost on the Tibetan Plateau, particularly in mountainous areas, due to the underestimation of soil water and ice content in thick unsaturated zones. Uncertainty analysis indicates that variations in thermal parameters can induce a MAGT variation range exceeding 6 ℃, driven primarily by the parameter associated ground surface temperature to air temperature during freezing days. The models show different sensitivities to climate warming, under 1 ℃ warming, the empirical model’s MAGT response is 0.6 ℃, double that of the transient model’s 0.3 ℃ response, which amplifies uncertainty in future projections. These findings highlight biases in widely used models for Tibetan Plateau permafrost, affecting tipping point projections and downstream ecohydrology, and call for the development of thermal models tailored to the region’s climate and hydrogeological conditions, supporting the global cryosphere modeling community.

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Advances in Climate Change Research
Pages 324-337

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Cite this article:
ZHAO Y-F, YAO Y-Y, JIN H-J, et al. Prevailing thermal models underestimate permafrost thermal state in the Tibetan Plateau: Implications for cryosphere adaptation. Advances in Climate Change Research, 2026, 17(2): 324-337. https://doi.org/10.1016/j.accre.2025.12.009

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Received: 27 March 2025
Revised: 13 December 2025
Accepted: 14 December 2025
Published: 19 December 2025
© 2025 The Authors.

This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).