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Jing Sun, Yingying Chen, Kun Yang, Hui Lu, Long Zhao, and Donghai Zheng

Abstract

In the central-eastern Tibetan Plateau (TP) there is abundant organic matter in topsoils, which plays a crucial role in determining soil hydraulic properties that need to be properly described in land surface models. Limited soil parameterizations consider the impacts of soil organic matter (SOM), but they still show poor performance in the TP. A dedicated field campaign is therefore conducted by taking undisturbed soil samples in the central TP to obtain in situ soil hydraulic parameters and to advance SOM parameterizations. The observed findings are twofold: 1) The SOM pore-size distribution parameter, derived from measured soil water retention curves, has been demonstrated to be much underestimated in previous studies. 2) SOM saturated hydraulic conductivity is overestimated. Accordingly, a new soil hydraulic parameterization is established by modifying a commonly used one based on observations, which is then evaluated by incorporating it into Noah-MP. Compared with the original ones, the new parameterization significantly improves surface soil liquid water simulations at stations with high surface SOM content, especially in the warm season. A further application with the revised Noah-MP indicates that SOM can enhance sensible heat flux but decrease evaporation and subsurface soil temperature in the warm season and tends to have a much weak effect in the cold season. This study provides insights into the role of SOM in modulating soil state and surface energy budget. Note that, however, there are many other factors at play and the new parameterization is not necessarily applicable beyond the TP.

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Donghai Zheng, Rogier van der Velde, Zhongbo Su, Jun Wen, Xin Wang, and Kun Yang

Abstract

This study evaluates the Noah land surface model (LSM) in its ability to simulate water and heat exchanges over frozen ground in a Tibetan meadow ecosystem. A comprehensive dataset including in situ micrometeorological and soil moisture–temperature profile measurements collected between November and March is utilized, and analyses of the measurements reveal that the measured soil freezing characteristics are better captured by 1) modifying the parameter b l implemented in the current Noah LSM that constrains the shape parameter of soil water retention curve utilized by the water potential freezing point depression equation to produce appropriate liquid water content θ liq under subzero temperature conditions and 2) neglecting the ice effect on soil-specific surface and thus matric potential via setting the empirical parameter that accounts for the effect of increase in specific surface of soil particles and ice–liquid water c k to zero. The numerical experiments performed with the Noah model run show that in comparison to the default Noah LSM, adoption of c k = 0 and site-specific b l values reduces the overestimation of θ liq across the soil profile. Implementation of augmentations such as the parameterization of diurnally varying thermal roughness length resolves the overestimation of daytime turbulent heat fluxes and underestimation of surface temperature. Further adoption of a new heat conductivity parameterization reduces the overestimation of nighttime surface temperature. An appropriate treatment of phase change efficiency that accounts for changing freezing rate with varying liquid water contents is also needed to reduce the temperature underestimation across soil profiles.

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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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Shi Liu, Song Yang, Yi Lian, Dawei Zheng, Min Wen, Gang Tu, Baizhu Shen, Zongting Gao, and Donghai Wang

Abstract

The time–frequency characteristics of the variations of temperature and precipitation over the city of Changchun in northeast China and their associations with large-scale atmospheric and oceanic conditions are analyzed. It is found that the variations of the regional climate are characterized by strong semiannual signals. For precipitation, the amplitude of semiannual signal is about half of that of the annual cycle. The relationships of the Changchun temperature and precipitation with local winds and large-scale patterns of atmospheric circulation and sea surface temperature are also strongest on annual and semiannual time scales. These strong semiannual signals are potentially helpful for improving the prediction of the regional climate.

On the annual time scale, the northeast China climate is affected by both the thermal contrast between the Asian continent and the tropical Indo-Pacific Oceans and that between the continent and the extratropical North Pacific. These effects are manifested by the cyclonic (anticyclonic) pattern over the Asian continent (North Pacific) and the strong southerly flow over East Asia and northwestern Pacific associated with increases in temperature and precipitation. On the semiannual time scale, the northeast China climate is mainly related to the large-scale circulation pattern centered over the North Pacific, with its western portion over northeast China, North and South Korea, and Japan. While temperature signals are related to extratropical atmospheric process more apparently, both extratropical and tropical influences are seen in the semiannual variation of precipitation.

There exist strong relationships between Changchun temperature and precipitation and the North Pacific Oscillation (NPO) in the frequency band up to 7 months. Temperature increases and precipitation decreases when NPO is positive. The relationships were weak before 1980 but became stronger afterward, associated with the strengthening of the East Asian trough.

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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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