2023
DOI: 10.1029/2022jd038021
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Improved Performance of CLM5.0 Model in Frozen Soil Simulation Over Tibetan Plateau by Implementing the Vegetation Emissivity and Gravel Hydrothermal Schemes

Abstract: The land surface process plays a critical role in land-air mass and energy exchanges, which greatly affects the weather and climate at local and regional scales (

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Cited by 4 publications
(4 citation statements)
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“…Winter biases likely occurred due to the development of a deeper early season snowpack in moist and wet meadow communities in CLM compared to observations (Figures 2a and 2b, and S2 in Supporting Information ). Work at other sites suggests that snow thermal conductivity in CLM5 is too high, resulting in cold wintertime soil temperature biases (Dutch et al., 2022; Luo et al., 2023). Preliminary results from our simulations at Niwot Ridge, however, suggest that thermal conductance of snow may be too low, resulting in warm winter soil temperature biases in moist and wet meadow columns.…”
Section: Resultsmentioning
confidence: 99%
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“…Winter biases likely occurred due to the development of a deeper early season snowpack in moist and wet meadow communities in CLM compared to observations (Figures 2a and 2b, and S2 in Supporting Information ). Work at other sites suggests that snow thermal conductivity in CLM5 is too high, resulting in cold wintertime soil temperature biases (Dutch et al., 2022; Luo et al., 2023). Preliminary results from our simulations at Niwot Ridge, however, suggest that thermal conductance of snow may be too low, resulting in warm winter soil temperature biases in moist and wet meadow columns.…”
Section: Resultsmentioning
confidence: 99%
“…Broadly, our findings underscore the challenges of representing biophysical and biogeochemical processes in sophisticated land models with high dimensionality parameter space (Dagon et al., 2020). For example, the generalized pedotransfer functions that are used in global scale, coarse resolution climate simulations with CLM may need more careful evaluation for local application in ecosystem‐scale studies (Dai et al., 2019; Luo et al., 2023). Such detailed measurements of soil thermal and hydraulic properties, however, are not commonly collected in sites with co‐located measurements of plant traits (for model parameterization) and long‐term measurements of ecosystem fluxes (for model calibration and evaluation).…”
Section: Resultsmentioning
confidence: 99%
“…The current version of Noah‐MP selectively estimates the soil hydraulic properties by partly adopting scheme of Saxton and Rawls (2006), which uses soil texture and organic matter, while the calculations of soil thermal properties only depend on soil texture. Nevertheless, studies (e.g., Liu et al., 2021; Luo et al., 2023; Luo, Lü, & Zhang, 2009; Luo, Lyu, et al., 2009; Sun et al., 2021; Zheng et al., 2015) suggested that influences of organic matter and gravel in soil hydraulic and thermal properties cannot be overlooked, especially when soil is frozen, soil with gravel has higher thermal conductivity and lower hydraulic conductivity (He et al., 2017; Peck & Watson, 1979). Organic matter and gravel widely distribute over high latitude and altitude regions (Lawrence & Slater, 2008; Shangguan et al., 2014), which should be important for calculations of soil hydraulic and thermal properties.…”
Section: Methodsmentioning
confidence: 99%
“…The detail can be referred to Table 1 in the paper by Saxton and Rawls (2006). It is worth noted that, distinguished from the incorporation into CLM (e.g., Liu et al., 2021; Luo et al., 2023), under the framework of Saxton and Rawls (2006) scheme, influences of gravel on soil porosity and matric potential cannot be directly considered, nevertheless, it can be indirectly achieved through feedback of k sat .…”
Section: Methodsmentioning
confidence: 99%