Improving hail prediction with a new triple-moment hail microphysics scheme
Adrian M. Loftus, Colorado State Univ., Fort Collins, CO; and W. R. Cotton
Hail can have a significant impact on the dynamic and thermodynamic properties of convective downdrafts and cold-pools, which in turn can affect storm evolution and propagation, and perhaps even the possibility of tornadogenesis. In addition, large and often destructive hail commonly occurs in severe convection, yet most one- and two-moment bulk microphysics schemes are incapable of producing large hail (diameter D ≥ 2 cm). The limits imposed by fixing one or two of the distribution parameters in these schemes often lead to particularly poor representations of particles within the tails of size distribution spectra; an especially important consideration for hail, which covers a broad range of sizes in nature. In order to improve the representation of hail distributions in simulations of deep moist convection in a cloud-resolving numerical model, a new efficient triple-moment (3M) bulk hail microphysics scheme is presented and evaluated. The 3M-hail scheme predicts the relative dispersion parameter for a gamma distribution function via the prediction of the reflectivity factor (sixth moment) of the distribution in addition to the mass mixing ratio and number concentration (third and zeroeth moments, respectively) thereby allowing for a fully prognostic distribution function. The new scheme is applied only to the hail distribution at this time due to complicating factors such as uncertain collection efficiencies, raindrop breakup, and irregular shapes and varying densities for graupel and snow that greatly hinder the computations of the sixth moment. Other key features of this scheme include bin-emulating riming, melting, and sedimentation, with the additional prediction of the relative dispersion parameter leading to substantial improvements to sedimentation as discussed in recent studies.
The 3M-hail scheme was employed within the Regional Atmospheric Modeling System (RAMS) to simulate the 29 June 2000 tornadic supercell that occurred during the Severe Thunderstorm and Electrification and Precipitation Study (STEPS). Two-moment bulk microphysics was used to predict the mass mixing ratios and number concentrations of all other hydrometeors [small and large cloud droplets, rain, pristine ice, snow, aggregates, and graupel]. The model was able to successfully reproduce the key characteristics of the observed convection, such as an initial multicell phase, a transition to a 'right-moving' supercell phase with a well-defined mesocyclone and a bounded weak echo region in the hail reflectivity field, and large hail at the surface. Regions of large hail and hail undergoing wet growth analyzed in the model output data also matched well with observations as deduced from analyses of polarimetric radar data. A similar simulation that used two-moment microphysics for hail also generated a supercell, but failed to produce any hail at the surface and, in general, did not resemble the observed storm. Given the recent increase in attention to aerosol effects on clouds and precipitation, the initial evaluations of the 3M-hail scheme suggest that it is ideal for future investigations of aerosol effects on hail as well.
Session 12B, Numerical Weather Prediction: Data assimilation, Ensemble Initialization, and Microphysics
Wednesday, 13 October 2010, 2:00 PM-3:30 PM, Grand Mesa Ballroom D
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