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<br />results of less robust evaluations of large numbers of non-randomized cloud seeding <br />events over decades. See Garstang et al. (2005) for an analysis of the differences of <br />opinion between the WMA and NRC regarding level of proof. It is the responsibility of <br />individual decision makers to determine which level of proof is appropriate for their <br />project. <br /> <br />The NAIWMC has prepared a position paper discussing this topic. It posits that although <br />weather modification may not stand up to the kind of rigorous, even allegedly <br />unreasonable standards of scientific proof advocated by the NRC, it is seen by many (for <br />example the ASCE; see above) as a viable tool. The NAIWMC also opines that weather <br />forecasting cannot meet the statistical and reproducible standards imposed on weather <br />modification, yet attempts to forecast weather continue. The logic continues with the <br />point that: "It seems reasonable that if we can affect negative changes to weather by <br />inadvertent means, we also have the potential to produce positive changes by intentional <br />means" (NAIWMC, 2004).5 <br /> <br />Although limited to small scale experiments, scientists have been able to trace the <br />physical effects of seeding from the point of seeding to the end product of precipitation <br />on the ground. Examples of documented cases appear in Deshler et al (1990) in the <br />Sierra Nevada, Super and Boe (1988) over the Grand Mesa of Colorado and Holroyd et al <br />(1995) for the Wasatch Plateau in Utah. Although the ability to measure the amount of <br />precipitation reaching the surface is often inexact becanse of gauge limitations, recent <br />work in Utah (Super and Heimbach, 2005) shows that seeding experiments can be <br />evaluated with well-sited high resolution gauges. Recent advances in radar technology <br />have led to better areal precipitation measurement, but conventional radars still have <br />significant limitations, particularly for snowfall measurement. Polarized radars show <br />much more promise in providing better estimates of precipitation, in differentiating <br />between precipitation particle types and in tracking seeding plumes embedded in mixed <br />phase clouds. <br /> <br />Atmospheric dynamics and the physical processes in clouds are complex and difficult to <br />diagnose, let alone predict. If one looks at a radar depiction of precipitation and <br />compares it to large-scale dynamics, one sees patterns that have little resemblance to <br />model predictions of large-scale lifting. There is an internal complexity that cannot be <br />predicted by current models. Some believe that the state of the art is unable to assess in <br />real time where a WxMod intervention could provide predictable results on a meaningful <br />scale.6 In wintertime cloud seeding situations numerous remote sensing and in situ <br />measurement platforms have been used to document seeding opportunities, which have <br />been found to be quite lengthy in many winter storm situations. While we cannot predict <br />or model all the internal complexities of a storm, the real time recognition of opportunity <br />is within the capability of modem observing systems and this has led to the design of <br />experiments which have produced predictable results when all criteria for seeding <br /> <br />'p.2 <br />6 Personal communicalion. Dr. Charles L. Hosler, Departmenl of Meleorology, College of Earth and <br />Mineral Sciences, The Pennsylvania Stale University. <br /> <br />-18- <br />