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

David M Lawrence, Keith W Oleson, Mark G Flanner, Peter E Thornton, Sean C Swenson, Peter J Lawrence, Xubin Zeng, Zong-Liang Yang, Samuel Levis, Koichi Sakaguchi, Gordon B Bonan, Andrew G Slater
2011 Journal of Advances in Modeling Earth Systems  
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
more » ... 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.
doi:10.1029/2011ms00045 fatcat:4rnl6fpqfzaetjxlebkcgoezx4