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<br />002573 <br /> <br />now being analyzed at CSU (Colorado State University), and initial <br />results support CSU's previous characterizations that most of the <br />natural precipitation in eastern Colorado, western Kansas, and <br />western Nebraska which occurs during the growing season comes from <br />organized mesoscale and synoptic scale cloud systems. Development <br />and organization of cloud systems appears to be highly influenced by <br />mountain-valley circulations that are established between the Rocky <br />Mountains and the High Plains, leading to the formation of clouds in <br />genesis areas along the east-facing slopes of the Rockies. Clouds <br />forming in cumulus genesis areas, such as South Park, Colorado, are <br />not only influenced by the cloud system development, but also are <br />controlled by terrain, both spatially and temporally. <br /> <br />A second purpose of the contract was to evaluate the utility of the <br />PAM (Portable Automated Mesonet) and multiple Doppler radar for <br />summertime weather modification research and operational programs. <br />The PAM system was extremely valuable for operational deci~ionmaking <br />and was an excellent tool for real-time and post hoc analyses. The <br />triple Doppler radar data were useful in detailed analysis of case <br />studies. <br /> <br />, <br />CDNTRACTOR: Amos Eddy, Inc., Norman, Oklahoma <br />CONTRACT NO. 7-07-83-V0007 <br />PRINCIPAL INVESTIGATOR: Amos Eddy <br />PERIOD: June 1, 1977, to September 30, 1978 <br />FUNDING: FY77 - $ 6,000 <br />FY78 - $17,600 <br /> <br />The contract's purpose was to develop and perform objective analysis <br />for optimal placement of rain gage networks in HIPLEX. The Eddy <br />statistical objective analysis algorithm was subjected to intensive <br />testing to determine its capabi lit ies and limitations. In analyzing <br />a "worst case" convective complex, scientists were able to deduce a <br />lag between the appearance of precipitation (reflectivities) in radar <br />data and the occurrenCe of rain on the ground. Results from a large <br />storm demonstrated the value of using radar when part of the rainfall <br />occurs out of the range of the gage network. <br /> <br />To test the performance of the analysis algorithms on a "gage only" <br />data set, the contractor constructed a siqnal generator which would <br />provide rainfall at any point on the ground within an asymmetric <br />circular pattern. Findings indicate that to define covariance (the <br />expected value) using gages from a single storm, .25 gages per storm <br />would be required. However, to analyze a storm using prior or inde- <br />pendent knowledge (such as from climatology) about the storm's shape <br />from the covariance structure between gage and radar, only about 10to <br /> <br />III-31 <br />