Shallow soil refers to the soil layer within the 50 cm depth. Shallow soil temperature (ST) directly or indirectly affects many processes in the soil, such as seed germination, plant growth, and water evaporation. Therefore, the study of shallow ST is of great significance in understanding the surface energy, water cycle, ecology and climate change. This work collected observational data from 141 meteorological stations on the Qinghai-Tibet Plateau from 1981 to 2020 and ERA5 reanalysis data, used the "Moving Surface Spline Interpolation Algorithm Based on Green's Function" and "Fuzzy C-means algorithm", and analyzed the temporal and spatial change characteristics of ST at different levels. The results showed that 1) the temperature increase of 0-20 cm (the surface layer of the shallow soil) was roughly the same. The average annual ST was 9.15-9.57°, and the interdecadal variabilities were 0.49-0.53 K/10a. The average annual ST of 40 cm (the bottom layer) was 8.69°, and the interdecadal variability reached 0.98 K/10a. 2) Considering the 7 regions, the warming trend was obvious, and there were certain regional differences. The average annual ST in different regions ranged from 5.2 (northeastern Plateau) to 17.1 °C (western Sichuan Plateau), with a difference of nearly 12 K. The standard deviation ranged from 0.40 (western Sichuan Plateau) to 0.61 K (Qiangtang Plateau), with a difference of 0.21 K. 3) The errors of the obtained grid data were basically less than 3%, which were much smaller than the errors obtained from the ERA5 reanalysis data. This work is significant for understanding the characteristics of ST evolution and land‒atmosphere interactions on the Qinghai-Tibet Plateau and provides important data support for improving the underlying surface boundary conditions of models.
© 2022. The Author(s).