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

Zhao, Jianting; Zhao, Lin; Sun, Zhe; Hu, Guojie; Zou, Defu; Xiao, Minxuan; Liu, Guangyue; Pang, Qiangqiang; Du, Erji; Li, Zhibin; Wu, Xiaodong; Xiao, Yao; Wang, Lingxiao; Zhang, Wenxin

doi:https://doi.org/10.5194/tc-19-4211-2025

Articles | Volume 19, issue 10

https://doi.org/10.5194/tc-19-4211-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-19-4211-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 19, issue 10

Research article

|

02 Oct 2025

Research article |

| 02 Oct 2025

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

Jianting Zhao, Lin Zhao, Zhe Sun, Guojie Hu, Defu Zou, Minxuan Xiao, Guangyue Liu, Qiangqiang Pang, Erji Du, Zhibin Li, Xiaodong Wu, Yao Xiao, Lingxiao Wang, and Wenxin Zhang

Data sets

synthesis dataset of permafrost for the Qinghai-Xizang (Tibet) Plateau, China (2002-2018) L. Zhao et al. https://doi.org/10.11888/Geocry.tpdc.271107

HRLT: A high-resolution (1 day, 1 km) and long-term (1961–2019) gridded dataset for temperature and precipitation across China Rongzhu Qin and Feng Zhang https://doi.org/10.1594/PANGAEA.941329

ERA5-Land hourly data from 1950 to present Copernicus Climate Change Service https://doi.org/10.24381/cds.e2161bac

NCEP Climate Forecast System Reanalysis (CFSR) 6-hourly Products, January 1979 to December 2010 S. Saha et al. https://doi.org/10.5065/D69K487J

CLARA-A3: CM SAF cLoud, Albedo and surface RAdiation dataset from AVHRR data - Edition 3 Karl-Göran Karlsson et al. https://doi.org/10.5676/EUM_SAF_CM/CLARA_AVHRR/V003

Short summary

We used the Moving-Grid Permafrost Model (MVPM) to simulate the permafrost thermal regime in West Kunlun (55,669 km², NW Qinghai–Tibet Plateau), driven by remote-sensing-based land surface temperature (LST; 1980–2022). The model showed high accuracy and stability. Despite ongoing warming (+0.40 °C per decade), permafrost extent remained stable, reflecting delayed deep responses. The permafrost thermal regime reveals altitude- and soil-dependent responses to climate change and offers valuable insights into thermal states in data-scarce regions.