The pragmatic blending approach of Boutle et al. (2014) treats sub‐grid turbulent mixing using a weighted average of a 1D mesoscale‐model and a 3D Smagorinsky formulation. Here the approach is modified and extended to incorporate a scale‐dependent dynamic Smagorinsky scheme instead of a static Smagorinsky scheme. Results from simulating ...
The pragmatic blending approach of Boutle et al. (2014) treats sub‐grid turbulent mixing using a weighted average of a 1D mesoscale‐model and a 3D Smagorinsky formulation. Here the approach is modified and extended to incorporate a scale‐dependent dynamic Smagorinsky scheme instead of a static Smagorinsky scheme. Results from simulating an evolving convective boundary layer show that the new scheme is able to improve the representation of turbulence statistics and potential temperature profiles at grey‐zone resolutions during the transition from the shallow morning to the deep afternoon boundary layer. This is achieved mainly because the new scheme enables and controls an improved spin‐up of resolved turbulence. The dynamic blending scheme is shown to be more adaptive to the evolving flow and somewhat less sensitive to the blending parameters. The new approach appears to offer a more robust and more flexible formulation of blending and the results are strongly encouraging of further assessment and development.
