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<br />d \8'596fH,J-62 AI f h '. . . 1 "" h" <br />egrees' , . ' , . l~' ore measurements 0 t e vanatlons 01 Ice crysta concentrations "dt m <br />seeded plumes arc needed6J:60. Even if such measurements arc lacking, it is prudent to space <br />generators/dispensers close enough across the wind to produce m'erlapping plumes and <br />sutlicient crystal mass for significant snowfall increases (20 per liter minimum requirement, <br />Section C3a). These instrument sitings and configurations are among the most important ways <br />to optimize seeding. Operational projects should assess these issues and make changes as <br />needed, Much more detail on SLW availability, T&D, and generator siting may be found in a <br />recent seeding feasibility studyt>4. <br /> <br />Finally, Agl generators should be able to adjust and measure solution flow rate and name <br />temperature, to ensure that seeding is occurring as planned. Likewise for LP dispensers. propane <br />flow rate and temperature downstream of the expansion nozzle should be monitored, The search <br />for optimum chemistry fonnulations, burners and particle sizes from generators should continue. <br /> <br />c) Evaluation Techniques <br /> <br />Scientilic evaluation of seeding efTects adds cost to operational seeding programs, and therefore <br />has not been commonly pursued as part of those programs. Thcre have been several research <br />projects in which evaluation of efYects was the primary objective. The main goal here should be <br />to optimize seeding methods through applied research. This research should demonstrate that <br />seeding materials arc producing the desired precipitation increases in the target area, The three <br />primary evaluation methods may be catcgori7.cd as physical. modeling, and statistical. <br /> <br />Physical Techniques. The approaches in this category involve either remote or in situ <br />measurements of seeded plumes. their effects on precipitation, or other atmospheric parameters <br />related to cloud seeding. To measure seeded plumes and their effects on precipitation, aircratl <br />sampling and tra~c chemical anal.yses of s~o\\' have bec~ uscd, Exa6Tgl~ ~ncludc single and <br />dual traccr techmques, and combmcd phYSical and chemical methods . -. .6. An examplc of <br />measuring sccding-related paramcters would be microwave radiometer (remote sensing) and <br />aircraft or ground (in situ) measurcments of SLW. Satellite sensors continue to be improvcd and <br />techniques for monitoring eloud hydrometeors, such as the one used to produce Figurc 3, will <br />certainly contributc to weather modification-related knowledge. Satellites have the advantage of <br />a much wider sampling arca than other instruments. and may bc able to measure cloud SI. W in <br />certain cases. Radar has also been used to track seeding plumes68;6'l. There is a consensus among <br />scientilic organizationsI1:Jo;31 that physical mcasurcments are crucial to evaluations, since thcy <br />arc needed to verify and quantify the physical chain of events rcquired for succcssful seeding. <br />Monitoring of natural ambient conditions such as SL Wand temperature in admnce of any <br />seeding is highly desirable, since it would set a baseline for evaluating seeding feasibility and <br />evcntual seeding effccts. <br /> <br />Modeling Techniques. lllis approach has gained popularity in the last decade. fuel cd by <br />increascs in computing pov.'er. Recent examplcs include the Colorado and Nevada WDMP <br />experiments and the Wyoming pilot project (Section C3a), These projects have lIsed <br />sophisticated 3-D numcrical cloud modcls coupled with dispersion models. Thesc models <br />pn:dict sceded plume dispcrsion in mountainous tcrrain. which have been used for targeting <br /> <br />22 <br />