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Abstract The Tibetan Plateau (TP) region experiences strong land‐atmosphere interactions, and as an elevated heating source, significantly influences the formation of the Asian monsoon. Those interactions are not well represented in current land‐surface models (LSMs), partly due to difficulties in representing heterogeneities in soil structures in LSM. Simulations using the Noah with multiparameterization options (Noah‐MP) LSM are employed to assess the relative importance of parameterizing vertical soil heterogeneity, organic matter, and soil rhizosphere and their impacts on seasonal evolution of soil temperature, soil moisture, and surface energy and water budgets at the sparsely vegetated Amdo site located in central TP. The LSM spin‐up time at the central TP depends on the complexity of the model physics, ranging from 4 years with simplest soil physics to 30 years with the addition of organic matter and spare to dense rhizosphere parameterization in Noah‐MP. Representing layered soil texture and organic matter does not improve low biases in topsoil moisture. Reducing the saturated conductivity from the mucilage in the rhizosphere produces better results. Surface sensible and latent heat fluxes are better simulated in the monsoon season as well. Adding layered soil texture and organic matter in Noah‐MP retard the thawing in deep soil layers, and the rhizosphere effect delays thawing even more in the transient season. Uncertainties in soil initialization significantly affect deep‐soil temperature and moisture, but uncertainties in atmospheric forcing conditions mainly affect topsoil variables and consequently the surface energy fluxes. Differing land‐surface physics cause 36% uncertainty in the accumulated evapotranspiration and subsurface runoff.
Gao et al. (Sat,) studied this question.