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<br />- <br /> <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br />I <br /> <br />expense of a full-bin-resolving model and can readily be implemented in three- <br />dimensional storm models. <br /> <br />To better model the precipitating ice, Farley developed a hybrid method that <br />utilizes twenty categories (now twenty-one), or bins, for these particles, The sizes range <br />in diameter from 100 ~m to 5,0 cm (recently increased to 7.0 cm by adding the extra bin). <br />Bulk-water microphysical methods are used for the cloud liquid, cloud ice and rain fields, <br />hence the hybrid terminology, The dynamic framework for the microphysics has been a <br />two-dimensional, time-dependent cloud model and a three-dimensional, time-dependent, <br />cloud-resolving mesoscale model developed by Clark (1977,1979), Clark and Farley <br />(1984) and Clark and Hall (1991). The lAS two-dimensional framework has been used <br />to simulate hail formation and fallout in an Alberta hailstorm (Farley, 1987) in both <br />seeded and unseeded conditions, and in a North Dakota hailstorm (Farley et aI., 1996, <br />2004a,b). Good agreement with radar observations was obtained in the Alberta and <br />North Dakota hailstorms, This model framework allows the type of hailstone embryos, <br />either frozen raindrop or graupel, to be identified (Kubesh et aI., 1988), A critical <br />component of the Kubesh study was the data provided by the armored T-28 aircraft <br />involving particles types and sizes inside the strong updrafts of a supercell storm. Both <br />model and observations indicated the importance of shedding from graupel and hail <br />particles to produce rain for fallout and for hailstone embryos in the rich supercooled <br />liquid water environment. <br /> <br />In addition, the three-dimensional Clark model has been used to simulate snow <br />and rainfall over the Black Hills of South Dakota and Wyoming (Farley et aI., 2000) <br />during a four-day storm period, Simulation of the cold precipitation period produced <br />reasonably accurate precipitation patterns, but not as accurate for the warmer, weakly <br />forced situation, This last result indicated that a simulation of a drizzle process should <br />improve the rainfall comparisons, as was also called for in the NRC report. A simulation <br />of ground-generator cloud seeding of the storm system was reported in Farley et al. <br />(1997), which showed that the cloud seeding was effective on only one of the four days. <br />Other orographic simulations of precipitation formation and the effects of cloud seeding <br />are found in Meyers et al. (1992, 1995). <br /> <br />Some success has also been obtained in the three-dimensional modeling of <br />convective clouds and storms. The 3D cloud-resolving model of Clark (with the bin ice <br />microphysics of Farley) has been used to simulate hailfall in northern Italy (Wobruck et <br />aI., 2000) and in southern France (Wobruck et aI., 2003). This last study showed good <br />agreement with observations of the hailstone spectrum at the ground, Johnson et aI., <br />(1993) simulated the 2 August 1981 CCOPE supercell with both liquid water <br />microphysics (L WM) only and with a hail category version (HCM) of the model (similar <br />to the hail formulation of Farley). The ice microphysics was shown to be important for <br />the better comparison with the actual storm, but the L WM simulation reproduced some of <br />the important dynamics of the supercell storm, The T-28 armored aircraft provided <br />critical information from inside the storm that was used for the comparisons. Farley et al. <br />(1992) used the 3D Clark model with bulk-water microphysics to simulate a moderate <br /> <br />26 <br />