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Evaluation of Noah Frozen Soil Parameterization for Application to a Tibetan Meadow Ecosystem

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  • 1 Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, Netherlands
  • | 2 Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China
  • | 3 Department of Earth System Science, Tsinghua University, Beijing, China
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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 bl 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 θliq 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 ck to zero. The numerical experiments performed with the Noah model run show that in comparison to the default Noah LSM, adoption of ck = 0 and site-specific bl values reduces the overestimation of θliq 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.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Donghai Zheng, d.zheng@utwente.nl

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 bl 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 θliq 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 ck to zero. The numerical experiments performed with the Noah model run show that in comparison to the default Noah LSM, adoption of ck = 0 and site-specific bl values reduces the overestimation of θliq 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.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Donghai Zheng, d.zheng@utwente.nl
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