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<br />2 <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 />The seeding effect on ice crystal concentrations is expected to follow <br /> <br />the estimate of the nucleating activity of the seeding agent, which has <br /> <br /> <br />historically been determined for a variety of generation devices by <br /> <br />tests in an isothermal cloud chamber (Grant and Steele, 1966; Garvey, <br /> <br />1975). For most cloud seeding programs, this approach does not <br /> <br />adequately consider the differences between the conditions in the real <br /> <br />cloud and the environmental conditions in the cloud chamber where the <br /> <br /> <br />nucleant was characterized. This has been a necessary simplification, <br /> <br />since there is not enough known about the differences in nuclei <br /> <br />response to ambient conditions, transport through warm cloud, or <br /> <br />seeding method. A complete description of these effects is not <br />available for even one nucleant. <br /> <br />Cloud models can play an important role in answering questions <br /> <br />concerning the consequences of seeding a supercooled cloud with an ice <br /> <br />nucleating aerosol, but model descriotions of nucleation orocesses must <br /> <br />be derived from exoerimental evidence, because adequate descriptive <br /> <br />theories do not exist. An example of an experimental and model <br /> <br />interactive study was demonstrated by the incorporation into computer <br /> <br />simulations by Lamb et a1. (1981) of mathematical descriptions of <br />secondary ice formation processes derived from laboratory studies of <br />this phenomenon by Hallett and Mossop (1974). The characteristics of <br /> <br />clouds which form by simple lifting over short time periods (orographic <br /> <br />clouds, cumulus clouds and some stratiform clouds) can be closely <br /> <br />simulated with computer models. However, mathematical parameterizations <br /> <br /> <br />or simplifications based on analogy are often used in models in place <br /> <br /> <br />of physical laws, in order to circumvent limits of computer power and <br /> <br /> <br />cost or when theory and understanding are insufficient or incomplete. <br />