Simulated soil temperature and surface fluxes over the Tibetan Plateau using SSiB3-FSM

The dataset includes simulated soil temperature, albedo, and energy fluxes over the Tibetan Plateau, using a land surface model (SSiB3-FSM). Based on this dataset and other publicly archived observations, we found that: 1. Land surface temperature anomaly can sustain for seasons and is accompanied by persistent subsurface temperature, snow, and albedo anomalies. 2. With middle-layer subsurface temperature as a predictor, the land surface temperature is highly predictable, especially during the springtime. 3. Soil properties and soil column depth predominate subsurface temperature memory, which suggests the key processes to improve its prediction. More information can be found in the reference: Ye Liu, et al, 2020, Investigation of the variability of near-surface temperature anomaly and its causes over the Tibetan Plateau, Journal of Geophysical Research: Atmospheres.