Spatiotemporal characteristics and variability in the thermal state of permafrost on the Qinghai–Tibet Plateau

Permafrost degradation on the Qinghai–Tibet Plateau (QTP) has significant impacts on climate, hydrology, and engineering and environmental systems. To understand the temporal and spatial characteristics of permafrost on the QTP, we quantified the variation in active layer thickness (ALT), permafrost thermal state, and future permafrost change under different scenarios using observational data, reanalysis data, and the numerical permafrost model. Generally, ALT ranged from 0.5 to 6.0 m with an average of 2.39 m, and mean annual ground temperature (at a depth of zero annual amplitude for ground temperature) mainly ranged between 0 and −3°C with an average of −0.85°C. The soil temperatures in different layers based on the ERA5‐Land data revealed even stronger increasing trends, for example, 0.245, 0.245, 0.244, and 0.238°C/decade at depths of 0–7, 7–28, 28–100, and 100–289 cm from 1980 to 2021, compared to those during the period from 1960 to 2021, which were 0.153, 0.156, 0.155, and 0.149°C/decade, respectively. The average warming trends in annual mean soil temperature were 0.153 and 0.243°C/decade from 1960 to 2021 and 1980 to 2021, respectively. The average rate of thickening of the ALT among the 10 active layer observation sites was 2.84 cm/year. There was a significant warming trend in ground temperature above ~15 m with warming of 0.063 to 0.120, 0.026 to 0.182, 0.101 to 0.314, and 0.189 to 0.303°C/decade at the QTB01, QTB06, QTB08, and XDTGT sites, respectively, and yearly minimum ground temperatures exhibited stronger warming trends than maximum ground temperatures. In addition, the simulation revealed significant increases in ground temperature at the Xidatan (XDT) and Tanggula (TGL) sites under both historical and future Representative Concentration Pathway (RCP) scenarios, but the increases in ground temperature were significantly greater at TGL than XDT. These findings provide important information for understanding the variability in permafrost degradation processes and improving simulations of permafrost change under climate change on the QTP.