Effects of roughness length parameterizations on regional-scale land surface modeling of alpine grasslands in the Yangtze River basin

Current land surface models (LSMs) tend to largely underestimate the daytime land surface temperature T_sfc for high-altitude regions. This is partly because of underestimation of heat transfer resistance, which may be resolved through adequate parameterization of roughness lengths for momentum z_0m and heat z_0h transfer. In this paper, the regional-scale effects of the roughness length parameterizations for alpine grasslands are addressed and the performance of the Noah LSM using the updated roughness lengths compared to the original ones is assessed. The simulations were verified with various satellite products and validated with ground-based observations. More specifically, four experimental setups were designed using two roughness length schemes with two different parameterizations of z_0m (original and updated). These experiments were conducted in the source region of the Yangtze River during the period 2005-10 using the Noah LSM. The results show that the updated parameterizations of roughness lengths reduce the mean biases of the simulated daytime T_sfc in spring, autumn, and winter by up to 2.7 K, whereas larger warm biases are produced in summer. Moreover, model efficiency coefficients (Nash-Sutcliffe) of the monthly runoff results are improved by up to 26.3% when using the updated roughness parameterizations. In addition, the spatial effects of the roughness length parameterizations on the T_sfc simulations are discussed. This study stresses the importance of proper parameterizations of z_0m and z_0h for LSMs and highlights the need for regional adaptation of the z_0m and z_0h values.