A scale-dependent dynamic Smagorinsky model is implemented in the Met Office/NERC cloud model (MONC) using two averaging flavours, along Lagrangian pathlines
and local moving averages. The dynamic approaches were compared against the conventional
Smagorinsky-Lilly scheme in simulating the diurnal cycle of shallow cumulus convection. ...
A scale-dependent dynamic Smagorinsky model is implemented in the Met Office/NERC cloud model (MONC) using two averaging flavours, along Lagrangian pathlines
and local moving averages. The dynamic approaches were compared against the conventional
Smagorinsky-Lilly scheme in simulating the diurnal cycle of shallow cumulus convection. The
simulations spanned from the LES to the near-grey-zone and grey-zone resolutions and revealed the
adaptability of the dynamic model across the scales and different stability regimes. The dynamic
model can produce a scale and stability dependent profile of the subfilter turbulence length-scale
across the chosen resolution range. At grey-zone resolutions the adaptive length scales can better
represent the early pre-cloud boundary layer leading to temperature and moisture profiles closer to
the LES compared to the standard Smagorinsky. As a result the initialisation and general representation of the cloud field in the dynamic model is in good agreement with the LES. In contrast, the
standard Smagorinsky produces a less well-mixed boundary-layer which fails to ventilate moisture
from the boundary layer resulting in the delayed spin-up of the cloud layer. Moreover, strong
down-gradient diffusion controls the turbulent transport of scalars in the cloud layer. However,
the dynamic approaches rely on the resolved field to account for non-local transports, leading to
over-energetic structures when the boundary layer is fully developed and the Lagrangian model is
used. Introducing the local averaging version of the model or adopting a new Lagrangian time
scale provides stronger dissipation without significantly affecting model behaviour.