Producing reliable profile soil moisture and temperature (SMST) simulations for the Tibetan Plateau (TP) is challenging with current model-based products. This study examines error sources in GLDAS-2.1 Noah through numerical experiments focusing on impact of soil properties, meteorological forcing, and model physics. Profile SMST observations from the Maqu network characterized by grassland with humid climate and Shiquanhe network dominated by bare ground with arid climate serve as ground truth. The control experiment running the default Noah model with GLDAS-2.1 meteorological data and FAO soil data mirrors the GLDAS-2.1 Noah product, both of which underestimate profile SM in Maqu and overestimate them in Shiquanhe, with profile ST underestimated in both areas. Using realistic soil types from in situ samples reduces RMSD by 27% and 57% on average in simulating profile SM for Maqu and Shiquanhe, respectively. Adoption of improved meteorological forcing further alleviates remaining overestimation in Shiquanhe during warm season with RMSD reduced by 45%. Implementation of augmented model physics largely addresses remaining deficiencies, which further reduces RMSD by more than 40% in both network via improving parameterizations of soil hydraulic properties and freezing characteristics. Implementation of improved soil type and meteorological forcing shows minor impact on profile ST simulations, while the augmented model physics improving the parameterization of surface heat exchange largely reduces the RMSD by 34% and 51% for Maqu and Shiquanhe, respectively. These findings provide valuable insights for understanding and addressing the uncertainties of profile SMST simulations on the TP.