Parameterization improvements and functional and structural advances in Version 4 of the Community Land Model

By D. Lawrence, K. Oleson, Mark G. Flanner, P. Thornton, S. Swenson, P. Lawrence, X. Zeng, Zong‐Liang Yang, Sam Levis, K. Sakaguchi and 2 more. 2011

1,514 citations recorded by the source corpus.

The Community Land Model is the land component of the Community Climate System Model. Here, we describe a broad set of model improvements and additions that have been provided through the CLM development community to create CLM4. The model is extended with a carbon‐nitrogen (CN) biogeochemical model that is prognostic with respect to vegetation, litter, and soil carbon and nitrogen states and vegetation phenology. An urban canyon model is added and a transient land cover and land use change (LCLUC) capability, including wood harvest, is introduced, enabling study of historic and future LCLUC on energy, water, momentum, carbon, and nitrogen fluxes. The hydrology scheme is modified with a revised numerical solution of the Richards equation and a revised ground evaporation parameterization that accounts for litter and within‐canopy stability. The new snow model incorporates the SNow and Ice Aerosol Radiation model (SNICAR) ‐ which includes aerosol deposition, grain‐size dependent snow aging, and vertically‐resolved snowpack heating – as well as new snow cover and snow burial fraction parameterizations. The thermal and hydrologic properties of organic soil are accounted for and the ground column is extended to ∼50‐m depth. Several other minor modifications to the land surface types dataset, grass and crop optical properties, surface layer thickness, roughness length and displacement height, and the disposition of snow‐capped runoff are also incorporated. The new model exhibits higher snow cover, cooler soil temperatures in organic‐rich soils, greater global river discharge, and lower albedos over forests and grasslands, all of which are improvements compared to CLM3.5. When CLM4 is run with CN, the mean biogeophysical simulation is degraded because the vegetation structure is prognostic rather than prescribed, though running in this mode also allows more complex terrestrial interactions with climate and climate change.

Subfields: Global and Planetary Change, Plant Science

View Paper: https://www.semanticscholar.org/paper/9a47312e05660a70202b80e92dcd15ba3694c747

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Citations in the corpus

The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty (2019, methodology): “CLM4 is described in Lawrence et al. (2011), and a full technical description is available in Oleson et al. (2010; http://www. cesm.ucar.edu/models/cesm1.2/clm/CLM4_Tech_Note.pdf).”
Vegetation demographics in Earth System Models: A review of progress and priorities (2018, methodology): “Model (CLM) (Lawrence et al., 2011; Oleson et al., 2013), integrating the ED concept within the architecture of the Community Earth Sys-”
Modeling Soil Processes: Review, Key Challenges, and New Perspectives (2016, background): “The CLM includes surface heterogeneities and consists of submodels that represent the hydrologic cycle, biogeochemical cycling, and ecosystem dynamics (Lawrence et al., 2011), many of which fit neatly into the framework of Dominati (2013) that connects soil capital to ecosystem processes and service”
A Description of the Advanced Research WRF Model Version 4 (2019, background): “Some of the graupel-related terms follow Lin et al. (1983), but its ice-phase behavior is much different due to the changes of Hong et al.”
Permafrost response to increasing Arctic shrub abundance depends on the relative influence of shrubs on local soil cooling versus large-scale climate warming (2011, methodology): “When CLM4 is coupled to CAM4, biases in the climate, especially an excessive snowfall bias that is prevalent across much of the pan-Arctic region, degrade the permafrost simulation resulting in deeper ALT and warmer deep ground temperatures than observed (Lawrence et al 2011a).”
Perspectives on the Future of Land Surface Models and the Challenges of Representing Complex Terrestrial Systems (2020, background): “The representation of plant community ecology has proceeded from the static plant functional types (Bonan, 1996; D. M. Lawrence et al., 2011; Zeng et al., 2002), through mean individual dynamic models with simple rules governing competition (Arora & Boer, 2006; Cox, 2001; Sitch et al., 2003), to…”
Biological and Chemical Diversity of Biogenic Volatile Organic Emissions into the Atmosphere (2013, methodology): “The CLM4 scheme includes just three shrub PFTs: broadleaf deciduous temperate, broadleaf evergreen temperate and broadleaf deciduous boreal.”
Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends (2013, neutral): “, 2011), NCAR_CLM4CN (Oleson et al., 2010; Lawrence et al., 2011), OCN (Zaehle & Friend, 2010), and VEGAS (Zeng et al.”