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Improving snow processes in the Noah land model

Snow is one of the most crucial land surface processes over middle and high latitudes. A widely known deficiency of the Noah land model as used in the National Centers for Environmental Prediction (NCEP) operational models and the Weather Research and Forecasting model (WRF) at the National Center f...

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Bibliographic Details
Published in:Journal of Geophysical Research: Atmospheres 2010-10, Vol.115 (D20), p.1T-n/a
Main Authors: Wang, Zhuo, Zeng, Xubin, Decker, Mark
Format: Article
Language:English
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Summary:Snow is one of the most crucial land surface processes over middle and high latitudes. A widely known deficiency of the Noah land model as used in the National Centers for Environmental Prediction (NCEP) operational models and the Weather Research and Forecasting model (WRF) at the National Center for Atmospheric Research is that snowmelt occurs much too early. Through detailed diagnostics of the Noah output over the high‐altitude Niwot Ridge forest site (40.03°N, 105.55°W) and a boreal forest site (53.9°N, 104.7°W), six deficiencies in Noah model physics are identified along with improved formulations that (1) consider the vegetation shading effect on snow sublimation and snowmelt; (2) consider under‐canopy resistance; (3) revise the ground heat flux computation when snow is deep; (4) revise the momentum roughness length computation when snow is present; (5) revise the snow density computation near 0°C; and (6) increase the maximum iteration number from five to 30 in the turbulence computation. These revisions significantly improve Noah simulations of all snow processes such as snow water equivalent (SWE), snow depth, and sensible and latent heat fluxes over these two forest sites. The revisions were also evaluated (without tunings) with an independent forest site and a grassland site, further confirming the robust and positive impacts of these revisions on Noah snow simulations. These modifications maintain the Noah model structure and do not introduce new prognostic variables, allowing easy implementation into NCEP operational models and into WRF. Furthermore, they are found to be as good as, or slightly better than, a much more complicated land model in the snow simulation over the three forest sites.
ISSN:0148-0227
2169-897X
2156-2202
2169-8996
DOI:10.1029/2009JD013761