Improved simulation of the terrestrial hydrological cycle in permafrost regions by the Community Land Model
By S. Swenson, D. Lawrence, Hanna Lee. 2012
165 citations recorded by the source corpus.
Plausible predictions of future climate require realistic representations of past and current climate. Simulations of the distribution of permafrost in the 21st century made with the Community Climate System Model (CCSM4) indicate that substantial decreases in permafrost extent can be expected, especially under high emissions scenarios. One of the implications of permafrost loss is the potential release of carbon from newly thawed soils into the atmosphere, thus raising its concentration of greenhouse gases and amplifying the initial warming trend. However, the biogeochemical cycle simulated by CCSM4 presents significant biases in carbon fluxes such as gross primary production, net primary production, and vegetation carbon storage in permafrost regions. The biases in the carbon cycle simulated \by CCSM4 are in part due to excessively dry soils in permafrost regions. In this study, we show that the CCSM4 dry soil bias results from the model's formulation of soil hydraulic permeability when soil ice is present. The calculation of the hydraulic properties of frozen soils is first modified by replacing their dependence on total water content with liquid water content only. Then an ice impedance function having a power‐law form is incorporated. When the parameterization of the hydraulic properties of frozen soil is corrected, the model simulates significantly higher moisture contents in near‐surface soils in permafrost regions, especially during spring. This result is validated qualitatively by comparing soil moisture profiles to descriptions based on field studies, and quantitatively by comparing simulated hydrographs of two large Siberian rivers to observed hydrographs. After the dry soil bias is reduced, the vegetation productivity simulated by the model is improved, which is manifested in leaf area indices that at some locations are twice as large as in the original model.
Subfields: Atmospheric Science
View Paper: https://www.semanticscholar.org/paper/60a17c0154e5b08d6644ac93cabd333624222880
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In Atmospheric Science
Citations in the corpus
- Permafrost thaw and resulting soil moisture changes regulate projected high-latitude CO2 and CH4 emissions (2015, methodology): “…of soil ice. Specifically, hydraulic conductivity for each soil layer (K; mm s−1) is calculated using an ice impedance factor with a power law form (Swenson et al 2012): K z K z z z 10 , 1F z B z sat liq 2 3 ice( ) ( ) ( ) ( ) ( )( ) ( )⎛ ⎝⎜ ⎞ ⎠⎟f= Q-W + where Fice= icef Q is the ice-filled…”
- Effects of model structural uncertainty on carbon cycle projections: biological nitrogen fixation as a case study (2015, methodology): “Key model improvements pertinent to the C cycle are revisions to the leaf photosynthesis and canopy integration (Bonan et al 2011, Bonan et al 2012), vertically resolved soil C and N biogeochemistry (Koven et al 2013), and permafrost hydrology (Swenson et al 2012).”
- The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty (2019, background): “Hydrology updates included modifications such that hydraulic properties of frozen soils are determined by liquid water content only rather than total water content, introduction of an ice impedance function and allows for a perched water table above icy permafrost ground (Swenson et al., 2012).”
- Global Mean Climate and Main Patterns of Variability in the CMCC‐CM2 Coupled Model (2018, background): “The hydrology processes list modifications related with treatment of icy permafrost ground (Swenson et al., 2012) and improve the simulation of snow cover fraction (Swenson & Lawrence, 2012), by separating the processes governing snowmelt (i.e., depletion) and snowfall (i.e., accumulation).”