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<br />:1 <br />--1 <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 />I <br />I <br /> <br />5.0 ASSESSMENT OF SEEDING EFFECTS <br /> <br />5.1 Back2round <br /> <br />Evaluating the results of a cloud seeding program is unfortunately rather difficult. <br />The seemingly simple problem of determining the effects of cloud seeding has received <br />considerable attention over the years. The primary reason for the difficulty stems from <br />the large natural variability in the amounts of precipitation that occur in any given area. <br />Since cloud seeding is only feasible when clouds exist, and usually only when the clouds <br />are near to or are producing precipitation naturally, the question then becomes, "How <br />much did the seeding increase the observed precipitation over that which would have <br />occurred naturally?". The ability to detect a seeding effect becomes a function of the <br />magnitude of the seeding increase compared to the natural variability in the precipitation <br />pattern. Larger seeding effects can be detected more easily and with smaller numbers <br />of seeded cases than are required to detect small increases. <br /> <br />Historically, the most significant seeding results have been observed in wintertime <br />seeding programs in mountainous areas. However, the apparent differences due to <br />seeding are relatively small, being on the order of a 5-15 percent seasonal increase. In <br />part, the relatively small percent increase accounts for the significant number of cases <br />required to establish these results with strong statistical significance, often five years or <br />more. <br /> <br />Despite the difficulties involved, techniques are available to evaluate the effects <br />of operational seeding programs. These techniques are not as statistically rigorous or <br />scientifically pure as are randomization techniques used in research, where roughly one <br />half the sample of storm periods is randomly not seeded. The less rigorous techniques <br />do, however, offer the potential of at least establishing an indication of the effects of <br />seeding on operational programs. <br /> <br />5-1 <br />