American Meteorological Society, Journal of the Atmospheric Sciences, 12(67), p. 3835-3853, 2010
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Abstract Previous large-eddy simulations (LES) of stratocumulus-topped boundary layers have been exclusively set in marine environments. Boundary layer stratocumulus clouds are also prevalent over the continent but have not been simulated previously. A suite of LES runs was performed for a case of continental post-cold-frontal stratocumulus observed by the Atmospheric Radiation Measurement Program (ARM) Climate Research Facility (ACRF), located in northern Oklahoma. Comparison with fixed, ground-based sensors necessitated an Eulerian approach in which it was necessary to supply to the model estimates of synoptic-scale advection and vertical motion, particularly given the quickly evolving, baroclinic nature of the synoptic environment. Initial analyses from the Rapid Update Cycle model supplied estimates for these forcing terms. Turbulent statistics calculated from the LES results are consistent with large-eddy observations obtained from millimeter-wave cloud radar. The magnitude of turbulence is weaker than in typical marine stratocumulus, a result attributed to highly decoupled cloud and subcloud circulations associated with a deep layer of negative buoyancy flux arising from the entrainment of warm, free-tropospheric air. Model results are highly sensitive to variations in advection of temperature and moisture and much less sensitive to changes in synoptic-scale vertical velocity and surface fluxes. For this case, moisture and temperature advection, rather than entrainment, tend to be the governing factors in the analyzed cloud system maintenance and decay. Typical boundary layer entrainment scalings applied to this case do not perform very well, a result attributed to the highly decoupled nature of the circulation. Shear production is an important part of the turbulent kinetic energy budget. The dominance of advection provides an optimistic outlook for mesoscale, numerical weather prediction, and climate models because these classes of models represent these grid-scale processes better than they do subgrid-scale processes such as entrainment.