Proceedings - C-SRNWP Project

the Met Office Large Eddy Model (LEM). The tests cover a range of grid resolutions from 50
m up to the scale of a few kilometres to test the convergence properties of the solution and
allow appropriate modifications to be made to bring the lower resolution models closer to the
high resolution solution.
Figure 8 shows the close comparison between the two models for a dry convective boundary
layer simulation using a “large eddy resolving” grid of dx=dy=dz=50m.
Figure 9 shows the timeseries of total hydrometeor content for the first few hours of an
idealised diurnal cycle of convection case study with the results from a 200m resolution
simulation of the Met Office LEM for comparison. With the Smagorinsky scheme the high
resolution UM runs are much closer to the high resolution LEM. As the resolution is
degraded, there is an increasing delay in the onset of convection followed by an overshoot in
the convective intensity. However, the delay and overshoot are substantially reduced with the
Smagorinsky scheme compared to the standard 1D boundary layer scheme.
Figure 10 shows an example of the impact of the Smagorinsky scheme for a real case (CSIP
IOP1). It is apparent in many convective case studies that the 1 km simulations suffer from an
over-prediction of rainfall from small convective cells. Using the Smagorinsky scheme
instead of the 1D boundary layer produces fewer vigorous small scale convective cells, closer
to that observed from the radar network. Although appropriate at very high resolution, it is
probably not the complete answer at resolutions of 1km and coarser. Work is ongoing to
investigate other approaches, such as combining the current 1D vertical boundary layer
scheme with the Smagorinsky scheme in the horizontal and outside the boundary layer, and
use of a shallow convection parametrization scheme to represent the under-resolved smallscale
convective cells at this resolution.
Cloud and Precipitation Microphysics
The details of the cloud and precipitation microphysical processes that are parametrized in the
model play a vital role in the development of deep convective cells in the forecast, yet there
are still uncertainties in many aspects of the parametrization and the degree of complexity of
the system that needs to be adequately represented. Observations from CSIP are being used to
assess the model performance and suggest improvements to the microphysics parametrization
for operational forecasting of deep convection. Particular aspects being investigated include
the representation of graupel, the most appropriate way to represent the range of ice particles
in the atmosphere from pristine ice crystals to large snow aggregates (i.e. two separate
prognostics, double-moment scheme, particle characteristics), the numerics of hydrometeor
sedimentation and the impact of latent heat exchange processes on the dynamics. These
developments are being informed by comparisons with the Met Office Large Eddy Model
with its more complex double-moment 5-category microphysics.
The impact of the microphysics on the dynamics of convective storms is of key importance as
it can significantly affect the strength and longevity of a storm and subsequent initiation of
daughter cells through the formation and interaction of evaporation-driven cold pools. Given
the uncertainty in many aspect of the microphysical parametrization we need to know the
impact of particular assumptions on the evolution of the storm dynamics in idealised and real
cases and a number of sensitivity studies are currently being performed. This provides
information on where to focus the effort to improve the representation of microphysics in the
model. Figure 11 shows a snapshot of the rainfall from a convective case study in 2005 (CSIP
IOP 6). Figure 12 shows the difference in surface rainfall rate during the simulation when
aspects of the microphysics are modified and the correlation of the spatial pattern of rainfall
with time. The correlation graph provides an indication of how much each change is affecting
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