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

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 u 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 5 0 and site-specific b l values reduces the overestimation of u 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.

The Improved Freeze–Thaw Process of a Climate‐Vegetation Model: Calibration and Validation Tests in the Source Region of the Yellow River

“…Similar results have also been demonstrated in other simulations, such as Zheng et al () simulated Maqu station using the NOAH model and Bao et al () simulation in a typical cold region in northwestern China using the HydroSib2 frozen soil model. There are different explanations for this phenomenon, such as the effect of snow and organic matter (Bao et al, ; Zheng et al, ). Additionally, the heat change in the soil introduced by thermal conductivity, heat capacity, and vapor transfer may affect the soil temperature, as discussed later.…”

“…The average plant height is approximately 5 cm in the cold season and approximately 20 cm in the warm season. The soil starts freezing around the beginning of November and starts to thaw around the beginning of March (Zheng et al, ). Recently, continued warming has been observed in this region, which may lead to permafrost degradation, and both the frozen soil area and depth have decreased (Cheng & Wu, ; Wu et al, ).…”

“…In summary, to improve the simulation of the freeze–thaw process, it is necessary to utilize reasonable governing equations, introduce a freeze–thaw parameterization scheme, and use accurate parameter sets. However, past studies only focus on improving one of these aspects (Bao et al, ; Zhang et al, ; Zheng et al, ); in particular, there are still too few studies on the calibration of freeze–thaw‐related parameters. Hence, it is difficult to improve the freeze–thaw process simulation.…”

Improved Simulation of Frozen‐Thawing Process in Land Surface Model (CLM4.5)

“…The soil ice prominently affects the soil water and heat transport. Many studies (e.g., Decker & Zeng, ; Koren et al, ; Niu & Yang, ; Zheng et al, ) have discussed the effects of soil ice on relationship between soil liquid water and soil temperature (equation ). The relationship of soil hydrological and thermal states proposed by Koren et al () and Decker and Zeng () is where c k = 8.…”

“…The previous studies (e.g., Niu & Yang, ) focused on the relationship between soil temperature and moisture in soil freezing process and have greatly improved it. However, some disagreements between model simulations and observations still exist; for example, study of Zheng et al () indicated that incorporating parameterizations of phase change from CLM (Oleson et al, ) into Noah‐MP (Yang et al, ) degraded the simulations of soil water during FT process. Analyzing and assessing FT parameterization in FT processes on different temporal scales can be useful for improving LSM performance.…”