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Snow cover in mountainous terrain plays an important role in regional and global water and energy balances, climate change, and ecosystems. Blowing snow is a frequent and important weather phenomenon over the Tibetan Plateau (TP); however, this process is neglected in most current land surface models, despite the consequential role it plays in the land surface and atmospheric water and energy budgets. In this paper, we present a blowing snow model PIEKTUK coupled with the Community Land Model (CLM4.5) to provide a better estimate of the snow dynamics for the consideration of snow redistribution induced by wind. Two simulations with a 0.065 degrees spatial resolution were performed in 2010 over the TP, namely, a sensitivity experiment with the inclusion of blowing snow effects (CLM_BS) and a control run with the original model (CLM). A specific objective of this study was to evaluate the improvements in the simulations of snow dynamics and other key variables in surface energy partitioning provided by the coupled model, such as the surface albedo and land surface temperature (LST). Compared with a variety of remote-sensing observations, the results show that the surface snow cover, snow depth, and surface albedo can be better reproduced in most of the TP region by CLM_BS than by the original CLM, particularly in the Kunlun Mountains, Hoh Xil area, and the southwestern TP. In areas with reduced bias, variations in the monthly mean snow cover fraction can be reflected particularly well by CLM_BS. For LST, however, a significant decrease in the nighttime LST bias was detected in CLM_BS, while the bias in the daytime LST increases. The results show considerable potential for the inclusion of the blowing snow process to promote the modeling of snow dynamics and land-atmosphere interactions on the TP.