Jason Milbrandt
With continuously increasing computer power, numerical weather prediction
(NWP) models are moving to higher and higher resolution. With decreased
grid-spacing there is an increased potential for grid-scale saturation.
Thus, explicit microphysics schemes are moving out of the exclusive realm
of research and are playing an increasingly important role in operational
NWP. It is therefore important to develop schemes that sufficiently
account for the important cloud microphysical processes and yet are
computationally efficient.
To this end, the requirements of a bulk scheme to model the hydrometeor
size distributions are investigated. A number of existing microphysics
schemes use the double-moment method with a three-parameter gamma
distribution function to represent the size spectrum. In general, two of
the parameters vary with the predicted moments while the third, normally
the shape parameter, is held constant. In a simple 1D context, the role
of the shape parameter, which represents the relative spectral dispersion,
is analyzed by comparing results from bulk schemes using different numbers
of predicted moments and an analytic bin model. It is shown that this
parameter is important in the overall prediction of the size distribution
by affecting both the instantaneous growth rates and the sedimentation.
In view of this, two alternatives to the fixed-value approach are
presented. One is a double-moment method, where the shape parameter is
diagnosed from the predicted moments; the other is a triple-moment
approach, where all distribution parameters are fully prognosed.
A new microphysics scheme using the proposed approaches has been designed
and interfaced with the MC2 mesoscale model. High-resolution (1 km)
simulations of a severe hailstorm are conducted. The control simulation
using the full triple-moment version of the scheme is compared to radar
observations and is shown to realistically simulate the observed storm,
including the spatial distribution and sizes of hail at the ground.
Experiments are performed to determine the sensitivity of the different
approaches on the simulation of hail. The results indicated that for a
double-moment scheme, the diagnostic approach for the shape parameter
exhibits distinct improvement over the fixed-value approach. It is also
shown that double-moment schemes are dramatically better in reproducing
the control simulation than single-moment schemes, due largely to the
ability of multi-moment schemes to account for the effects of
size-sorting.