Physics-guided machine learning approach for reconstructing air temperature in warm permafrost on the Qinghai‒Xizang Plateau
C.H. Peng, Dong-Liang Luo, Yu Sheng, Ji-Chun Wu et autres
High-resolution air temperature data are essential for quantifying eco-hydrological processes in climate-sensitive regions like the Qinghai‒Xizang Plateau. However, in-situ observations are frequently interrupted by extended data gaps. To address this, we developed a physics-guided machine learning (PGML) framework to reconstruct a 9-mon …
cn (code pays fourni par la source)