Integrating Remote Sensing Data into WRF to Improve 2 M Air Temperature Simulations in the Three-River Source Region of the Tibetan Plateau

The Three-River Source Region (TRSR) of the Tibetan Plateau (TP) is a critical headwater area with complex alpine terrain and significant climate variability. Accurately simulating 2 m air temperature (T2) in this region remains challenging for models such as the Weather Research and Forecasting (WRF) model. This study integrated remote sensing data into the WRF model to improve T2 simulations over the TRSR. Two simulations were conducted for 2020: a control simulation with default static vegetation parameters (EXPcontrol) and a sensitivity simulation with realistic vegetation and associated surface albedo of 2020 from the Global Land Surface Satellite (GLASS) datasets (EXPglass). Results showed that incorporating the GLASS-derived datasets significantly alleviated the cold bias in simulated T2 during winter and spring, while maintaining comparable performance in summer and autumn. The EXPglass run achieved better agreement with observations (R = 0.98, p < 0.01) and reduced root-mean-square error (RMSE) by 36.4% compared to EXPcontrol. Energy balance analysis indicated that the GLASS-derived datasets enhanced solar energy absorption and increased net radiation. Consequently, EXPglass produced greater turbulent heat fluxes and warmer surface skin temperature (TSK) and T2. This study underscores the importance of accurate land surface characterization and highlights the utility of remote sensing data for improving regional climate model performance in high-altitude regions.