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<br />4), The results from the various operational cloud seeding programs should be compared. <br />The difTerences and similarities in secding efTectivencss should provide insights on the extent to <br />which secding efTectivencss is a function of seeding operational procedures and/or topography. <br />In this way, thc optimization of the various seeding programs \viU benefit by learning from each <br />other on what appcars to work best. For example, do the opcrational seeding programs that <br />includc aircrall seeding yield bctter or more consistent results than those that usc ground-based <br />gcnerators alone. 'llIis would be a logical first step in detennining the most etTective mix of <br />ground and airborne seeding systems. <br /> <br />b, Ph)'sicllI studies <br />Physical studies should be conducted to corroborate and explain the statistical results, <br />Morc in-depth study of past seeding opcrations should be conducted with the aim of optimizing <br />the cost effectiveness of future seeding operations. Toward this end. two complementary scts of <br />studies arc necded, analytical studics and field/laboratory studies. <br />I) Analytical studies should be conducted to dctcmline the physical cause of the <br />signilicant changes in secding etTectivcness identified in this study. The results of these <br />analytical studies would provide a basis for focusing the complemcntary set of field and <br />laboratory studies on those issues of greatcst importancc to optimizing future seeding operations. <br />Specilic analytical studies should include but not necessarily limitcd to the following analyses: <br />a), Investigation using rawinsonde and documentcd seeding date data as to whethcr the <br />observed changes in seeding elTectivencss is due to changcs in meteorological conditions, that is <br />changes in secdability conditions. <br />b), Investigation using sceding log data as to whether the observcd changes in seeding <br />effcctivcncss is due to changes in seeding frequency and/or changes in seeding opcrational <br />procedures such as sceding dclivcry systems, sccding conligurations, and seeding agcnt chemical <br />fonnulations. <br />2) Field and laboratory studics should be conducted with the aim of conlimling the key <br />findings ofthc analytical studies, cspecially thosc that Icad to the optimization of future seeding <br />opcrations, The field and laboratory studies should takc into account and be based on the results <br />of the complementary analytical studies of differences in seeding etTcctivencss within and <br />between Sierra opcrational seeding programs and the physical infercnces on how and why they <br />occurred, Specific field and laboratory studies should include but not nccessarily limitcd to the <br />following: <br />a), Field tracer experimcnts to detemline thc transport and dispersion of airbornc and <br />ground-dispensed silvcr iodidc nuclei to improvc ground gencralor conligurations and airbornc <br />secding stratcgics. This should include silver-in-snow measurcments similar to those carried in <br />1994 (McGurty, 1999). <br />b). Laboratory studics to dctenninc thc silver iodide nuclei activation characteristics of <br />various silvcr iodide mixtures used in the Sierra seeding programs <br />c). Aircralt and remote measurements to develop methods of rccognizing conditions of <br />fa\"Orable seedability to improve the efficiency of seeding operations <br />It is emphasized that thc rccommended field measuremcnt programs is a valuable tool in <br />pro\'iding physical cxplanations of statistical seeding results; however, scveral ycars of <br />measurcmcnts are needcd to gct physical insights that arc rcpresentativc of the metcorological <br />conditions over long-tenn operational periods. <br /> <br />49 <br />