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.

In this study, we perform two regional climate simulations with the Weather Research and Forecasting model driven by outputs from the Community Climate System Model (CCSM-WRF) to investigate the role of soil moisture feedbacks in summer surface air temperature variability over East Asia for the period of 1976À2005. Strong soil moisture feedbacks on the daily mean and maximum temperatures identified by the CCSM-WRF model system mainly appear over the region from southern Siberia through eastern Mongolia to northeast China, the Tibetan Plateau, and most areas of central and east China, accounting for 30%À70% of the total variances. Meanwhile, the simulated soil moisture feedbacks on daily minimum temperature are shown to be much weaker than those on daily mean and maximum temperatures. The soil moisture-temperature feedbacks in the CCSM-WRF model system are generally well validated with those from two reanalysis products. The analysis of the physical processes shows that soil moisture feedback strength is mainly determined by the ability of soil moisture to influence the local surface heat fluxes and planetary boundary layer processes. The reasonable simulations of present soil moisture-temperature feedbacks indicate that the CCSM-WRF model system can be further applied to understand the role of soil moisture in influencing projected climate change over East Asia.

No abstract