Editorial Type:
Article
Article Type:
Research Article

Effects of Roughness Length Parameterizations on Regional-Scale Land Surface Modeling of Alpine Grasslands in the Yangtze River Basin

Ying Huang Faculty of Geo-Information Science and Earth Observation, and Faculty of Engineering Technology, University of Twente, Enschede, Netherlands

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M. Suhyb Salama Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, Netherlands

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Zhongbo Su Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, Netherlands

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Rogier van der Velde Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, Netherlands

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Donghai Zheng Faculty of Geo-Information Science and Earth Observation, and Faculty of Engineering Technology, University of Twente, Enschede, Netherlands

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Maarten S. Krol Faculty of Engineering Technology, University of Twente, Enschede, Netherlands

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Arjen Y. Hoekstra Faculty of Engineering Technology, University of Twente, Enschede, Netherlands

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Yunxuan Zhou State Key Laboratory of Estuarine and Coastal Research, East China Normal University, Shanghai, China

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Print Publication:
01 Apr 2016
DOI:
https://doi.org/10.1175/JHM-D-15-0049.1
Page(s):
1069–1085
Restricted access

Abstract

Current land surface models (LSMs) tend to largely underestimate the daytime land surface temperature 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 and heat 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 (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 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 simulations are discussed. This study stresses the importance of proper parameterizations of and for LSMs and highlights the need for regional adaptation of the and values.

Corresponding author address: Ying Huang, Faculty of Geo-Information Science and Earth Observation, University of Twente, P.O. Box 217, 7500 AE Enschede, Netherlands. E-mail: yinghuangje@gmail.com

Abstract

Current land surface models (LSMs) tend to largely underestimate the daytime land surface temperature 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 and heat 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 (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 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 simulations are discussed. This study stresses the importance of proper parameterizations of and for LSMs and highlights the need for regional adaptation of the and values.

Corresponding author address: Ying Huang, Faculty of Geo-Information Science and Earth Observation, University of Twente, P.O. Box 217, 7500 AE Enschede, Netherlands. E-mail: yinghuangje@gmail.com
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