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Donghai Zheng, Rogier van der Velde, Zhongbo Su, Martin J. Booij, Arjen Y. Hoekstra, and Jun Wen
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Donghai Zheng, Rogier van der Velde, Zhongbo Su, Martijn J. Booij, Arjen Y. Hoekstra, and Jun Wen

ABSTRACT

Current land surface models still have difficulties with producing reliable surface heat fluxes and skin temperature (T sfc) estimates for high-altitude regions, which may be addressed via adequate parameterization of the roughness lengths for momentum (z 0m) and heat (z 0h) transfer. In this study, the performance of various z 0h and z 0m schemes developed for the Noah land surface model is assessed for a high-altitude site (3430 m) on the northeastern part of the Tibetan Plateau. Based on the in situ surface heat fluxes and profile measurements of wind and temperature, monthly variations of z 0m and diurnal variations of z 0h are derived through application of the Monin–Obukhov similarity theory. These derived values together with the measured heat fluxes are utilized to assess the performance of those z 0m and z 0h schemes for different seasons. The analyses show that the z 0m dynamics are related to vegetation dynamics and soil water freeze–thaw state, which are reproduced satisfactorily with current z 0m schemes. Further, it is demonstrated that the heat flux simulations are very sensitive to the diurnal variations of z 0h. The newly developed z 0h schemes all capture, at least over the sparse vegetated surfaces during the winter season, the observed diurnal variability much better than the original one. It should, however, be noted that for the dense vegetated surfaces during the spring and monsoon seasons, not all newly developed schemes perform consistently better than the original one. With the most promising schemes, the Noah simulated sensible heat flux, latent heat flux, T sfc, and soil temperature improved for the monsoon season by about 29%, 79%, 75%, and 81%, respectively. In addition, the impact of T sfc calculation and energy balance closure associated with measurement uncertainties on the above findings are discussed, and the selection of the appropriate z 0h scheme for applications is addressed.

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Donghai Zheng, Rogier van der Velde, Zhongbo Su, Xin Wang, Jun Wen, Martijn J. Booij, Arjen Y. Hoekstra, and Yingying Chen

Abstract

This is the first part of a study focusing on evaluating the performance of the Noah land surface model (LSM) in simulating surface water and energy budgets for the high-elevation source region of the Yellow River (SRYR). A comprehensive dataset is utilized that includes in situ micrometeorological and profile soil moisture and temperature measurements as well as laboratory soil property measurements of samples collected across the SRYR. Here, the simulation of soil water flow is investigated, while Part II concentrates on the surface heat flux and soil temperature simulations. Three augmentations are proposed: 1) to include the effect of organic matter on soil hydraulic parameterization via the additivity hypothesis, 2) to implement the saturated hydraulic conductivity as an exponentially decaying function with soil depth, and 3) to modify the vertical root distribution to represent the Tibetan conditions characterized by an abundance of roots in the topsoil. The diffusivity form of Richards’ equation is further revised to allow for the simulation of soil water flow across soil layers with different hydraulic properties. Usage of organic matter for calculating the porosity and soil suction improves the agreement between the estimates and laboratory measurements, and the exponential function together with the Kozeny–Carman equation best describes the in situ . Through implementation of the modified hydraulic parameterization alone, the soil moisture underestimation in the upper soil layer under wet conditions is resolved, while the soil moisture profile dynamics are better captured by also including the modified root distribution.

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Donghai Zheng, Rogier van der Velde, Zhongbo Su, Xin Wang, Jun Wen, Martijn J. Booij, Arjen Y. Hoekstra, and Yingying Chen

Abstract

This is the second part of a study on the assessment of the Noah land surface model (LSM) in simulating surface water and energy budgets in the high-elevation source region of the Yellow River. Here, there is a focus on turbulent heat fluxes and heat transport through the soil column during the monsoon season, whereas the first part of this study deals with the soil water flow. Four augmentations are studied for mitigating the overestimation of turbulent heat flux and underestimation of soil temperature measurements: 1) the muting effect of vegetation on the thermal heat conductivity is removed from the transport of heat from the first to the second soil layer, 2) the exponential decay factor imposed on is calculated using the ratio of the leaf area index (LAI) over the green vegetation fraction (GVF), 3) Zilitinkevich’s empirical coefficient for turbulent heat transport is computed as a function of the momentum roughness length , and 4) the impact of organic matter is considered in the parameterization of the thermal heat properties. Although usage of organic matter for calculating improves the correspondence between the estimates and laboratory measurements of heat conductivities, it is shown to have a relatively small impact on the Noah LSM performance even for large organic matter contents. In contrast, the removal of the muting effect of vegetation on and the parameterization of greatly enhances the soil temperature profile simulations, whereas turbulent heat flux and surface temperature computations mostly benefit from the modified formulation. Further, the nighttime surface temperature overestimation is resolved from a coupled land–atmosphere perspective.

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Ying Huang, M. Suhyb Salama, Zhongbo Su, Rogier van der Velde, Donghai Zheng, Maarten S. Krol, Arjen Y. Hoekstra, and Yunxuan Zhou

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.

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