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<br /> <br />FigUfte 7. Sample 06 .6maU hail.; <br />c.oUec;ted in utah, <br />Novembeft, 1978; <br />magn~6ic.ation 0.62. <br /> <br /> <br />FigUfte 8. HaiU.tonu c.oUec;ted ~n <br />F.iA c. hbac.h, Swi.:tzel!iand, <br />in June, 1957. MajOft <br />.6hape: :tM.a.ual eUip- <br />.6oid with indentatio/'l.J.> <br />along minoft ax.iA, with <br />di66eftent .6Uft6ac.e ftough- <br />n~.6~; diameteft 06 <br />laftg~:t. .6.tone 4 em. <br /> <br />- 24- <br /> <br />He made another key assumption: while the <br />evolution of drops depends on theit size and <br />fall speed the drop ensembles neveitheless <br />stay together and fall at an average speed. <br />This assumption is still applied in essen- <br />tially all cloud models because dr9pping it <br />would require Lagrangian treatment of parti- <br />cles with all its enormous complications <br />(Girard and List, 1976). <br /> <br />It is unlikely that future progress <br />~n parameterization will result from general- <br />izations of deeper insights into t~e micro- <br />physics of precipitation processes. It will <br />rather come from instinctive, canny insights <br />into essentials of the precipitation pro- <br />cesses or from empirical equations'fitted to <br />observations which were taken by radar, other <br />means of remote sensing, aircraft platforms <br />and ground networks. <br /> <br />6. Cloud Modelling <br /> <br />Cloud modelling is based :on the <br />dynamic and thermodynamic equations as well <br />as some type of kinetic equation dealing with <br />the particle growth and feedback, as listed <br />in Sections 2 and 3. Due to the limitations <br />of electrical calculators and early computers <br />and insufficiently developed mathematical <br />skills modelling was first confined to either <br />one-dimensional (I-D) cloud models of the <br />Weinstein (1970) type or to two dimensions <br />for clouds without precipitation (Ogura and <br />Phillips, 1962). There is one big drawback <br />in l-D models: the pressure gradient term - <br />which is of the order of the liquid water <br />drag term but opposite in sign - cannot be <br />properly handled (List and Lozowski, 1970) <br />and leads to results which do not instill <br />confidence. If the pretense of representing <br />exact physical processes would be dropped and <br />better empirical equations would be, developed, <br />their use - particularly in view of develop- <br />ing seeding criteria for weather modification <br />purposes - would be made more paletable and <br />attractive. <br /> <br />2-D models (for example, Orville <br />and Kopp, 1977. Clark, 1973; Schle$inger, <br />1973) improved insight into cloud physics and <br />allow computations of flow patternS and cloud <br />water mixing ratios (Figure 10) or :even the <br />evolution in time of particle spectra in <br /> <br />" <br />