TY  - Data
T1  - Simulated Spatio-temporal Variation Dataset of Permafrost (TTOP and ALT) on the Qinghai-Tibet Plateau (1982–2020)
A1  - Chen Fangfang
A1  - Luo Dongliang
DO  - 10.12072/ncdc.permafrost.db7851.2026
PY  - 2026
DA  - 2026-10-20
PB  - National Cryosphere Desert Data Center
AB  - Global warming is causing rapid degradation of permafrost across many regions. The Tibetan Plateau, being a key area for permafrost in mid-to-low latitude zones, is particularly vulnerable to the impacts of permafrost degradation on alpine ecosystems, regional water resources, and engineering safety. This dataset provides simulation results for the permafrost conditions in the Tibetan Plateau from 1982 to 2020. The data utilizes monthly temperature measurements from CRU’s downscaled datasets to calculate atmospheric freeze-thaw indices. Additionally, N coefficients and soil parameters are considered, along with the TTOP model to estimate the temperature of the permafrost surface layer. Actual thickness measurements of the active layer are collected, and these data are combined with factors such as topography, climate, soil, and vegetation to create a comprehensive dataset. Machine learning techniques are used to determine E parameters, while the Stefan formula is employed to simulate the thickness of the active layer. The results have been cross-verified through both field observations and literature studies. These findings can provide insights into the spatiotemporal variations in permafrost temperatures and active layer thicknesses, thereby supporting research in areas such as alpine ecosystem protection, water resource management, assessment of permafrost-related disasters, and engineering planning.
DB  - NCDC
UR  - https://www.ncdc.ac.cn/portal/metadata/e4e059d3-9dbc-482f-bd58-724c7e03727b
ER  -