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Estimation of key surface parameters in semi-arid region and their impacts on improvement of surface fluxes simulation

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Abstract

Uncertainties in some key parameters in land surface models severely restrict the improvement of model capacity for successful simulation of surface-atmosphere interaction. These key parameters are related to soil moisture and heat transfer and physical processes in the vegetation canopy as well as other important aerodynamic processes. In the present study, measurements of surface-atmosphere interaction at two observation stations that are located in the typical semi-arid region of China, Tongyu Station in Jilin Province and Yuzhong Station in Gansu Province, are combined with the planetary boundary layer theory to estimate the value of two key aerodynamic parameters, i.e., surface roughness length z 0m and excess resistance κB -1. Multiple parameterization schemes have been used in the study to obtain values for surface roughness length and excess resistance κB -1 at the two stations. Results indicate that z 0m has distinct seasonal and inter-annual variability. For the type of surface with low-height vegetation, there is a large difference between the default value of z 0m in the land surface model and that obtained from this study. κB -1 demonstrates a significant diurnal variation and seasonal variability. Using the modified scheme for the estimation of z 0m and κB -1 in the land surface model, it is found that simulations of sensible heat flux over the semi-arid region have been greatly improved. These results suggest that it is necessary to further evaluate the default values of various parameters used in land surface models based on field measurements. The approach to combine field measurements with atmospheric boundary layer theory to retrieve realistic values for key parameters in land surface models presents a great potential in the improvement of modeling studies of surface-atmosphere interaction.

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Liu, Y., Guo, W. & Song, Y. Estimation of key surface parameters in semi-arid region and their impacts on improvement of surface fluxes simulation. Sci. China Earth Sci. 59, 307–319 (2016). https://doi.org/10.1007/s11430-015-5140-4

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