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https://doi.org/10.5194/hess-2020-360
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-2020-360
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  25 Aug 2020

25 Aug 2020

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This preprint is currently under review for the journal HESS.

Variations of surface roughness on inhomogeneous underlying surface at Nagqu Area over the Tibetan Plateau

Maoshan Li1, Lei Shu1, Xiaoran Liu1, Shucheng Yin1, Lingzhi Wang1, Wei Fu1, Yaoming Ma2, and Fanglin Sun3 Maoshan Li et al.
  • 1School of Atmospheric Sciences/Plateau Atmosphere and Environment Key Laboratory of Sichuan Province/Joint Laboratory of Climate and Environment Change, Chengdu University of Information Technology, Chengdu 610225, Sichuan China
  • 2Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing, China
  • 3Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Chinese Academy of Sciences. Lanzhou, China

Abstract. Using the MODIS satellite data and station atmospheric turbulence observation data in Nagqu area of northern Tibetan plateau in 2008, 2010 and 2012, with the Massman retrieved model and an independent method to determine aerodynamic surface roughness, the temporal and spatial variation characteristics of the surface roughness was analyzed. The results show that the surface roughness has obvious seasonal variation characteristics. From February to August, Z0m increases constantly with the ablation of snow and vegetation growth, and the maximum value reaches 4–5 cm at BJ site. From September to February, Z0m gradually decreased because of the post-monsoon over the plateau, and the values decreased to about 1–2 cm. The snowfall in abnormal years is the main reason why Z0m is obviously lower than that in normal. The underlying surface can be divided into four categories according to the different values of Z0m: snow and ice, sparse grassland, lush grassland and town. Among them, lush grassland and sparse grassland account for 62.49 % and 33.74 % respectively in the region, which are the main categories, and their Z0m annual changes are between 2–6 cm and 1–4 cm. The correlation between the two methods are positively related to each other, and the retrieved data are smaller than the measured results due to the average sliding action. On the whole, Z0m calculated by satellite data retrieved algorithm is feasible, it can be applied to improve the model parameters of land surface model parameters and the accuracy of model simulation, better reveal the heat flux exchange.

Maoshan Li et al.

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Short summary
In this study, using the MODIS satellite data and station atmospheric turbulence observation data in Nagqu area of northern Tibetan plateau, with the Massman retrieved model and an independent method to determine aerodynamic surface roughness, the temporal and spatial variation characteristics of the surface roughness was analyzed. The result is feasible, it can be applied to improve the model parameters of land surface model parameters and the accuracy of model simulation in the future work.
In this study, using the MODIS satellite data and station atmospheric turbulence observation...
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