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Last modified
7/28/2009 2:29:16 PM
Creation date
5/16/2007 3:02:42 PM
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Template:
Weather Modification
Title
The Feasibility of Operational Cloud Seeding in the North Platte River Basin Headwaters to Increase Mountain Snowfall
Prepared For
US Department of the Interior Bureau of Reclaimation
Prepared By
Jonnie G. Medina, Technical Service Center, Water Resources Services
Date
5/1/2000
County
Statewide
State
CO
Weather Modification - Doc Type
Scientific Study
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<br />It <br /> <br />;; <br /> <br />implemented in the operational seeding phase. These must be tested in the design phase. Should the <br />automated systems work without local power plant generation at most locations, the program <br />operational costs are significantly reduced. <br /> <br />. The conduct of an operational program over the relatively large Headwaters Region will cause <br />scrutiny from the scientific community, the general public and water interests of the Platte River. <br />Water users will be concerned about scientific proof of additional water. Design studies must <br />produce a viable operational program plan with a credible evaluation component to deal with what is <br />likely to be considerable program scrutiny. <br /> <br />3.2. Design Phase Components <br /> <br />The design phase must produce answers to questions concerning influences on cloud seeding of the <br />regional winter weather, clouds that form in the Headwaters Region, terrain and intra-area differences. <br />Questions regarding the seedability factor of clouds previously discussed must be further addressed. The <br />accuracy of cloud modeling for that area must be determined early in the program. Design studies should <br />be selected and structured to speed the advent of the operational program, yet provide the necessary <br />answers and support that will withstand scientific scrutiny. The proposed design phase time length is <br />recommended to be three years. This phase length fits well with obtaining permits for installing field <br />equipment, conducting cloud seeding operations, and satisfying environmental compliance. Additionally, <br />there is the need for two years offield studies for developing a seeding plan, determining equipment <br />locations and testing automated seeding and data gathering systems. <br /> <br />The principal components of the design phase field studies are outlined in the following. <br /> <br />· Conduct weather and cloud modeling during the first year ofthe program. Analyze modeling results <br />and previous information from the Headwaters Region. A decision would be made to continue or <br />discontinue the study based on results in this study component. <br /> <br />· Plan a limited field program during the first year of the program and install field equipment in the late <br />summer and fall of the first year. <br /> <br />Conduct limited field studies for two winters. Evaluate results and determine the feasibility of an <br />operational program in the summer ofY2002. Based on randomized results, a decision would be <br />made to continue or discontinue the study. <br /> <br />3.3. Cloud Modeling Studies <br /> <br />Numerical modeling of winter orographic clouds has significantly improved in the past 20 years and with <br />faster computers increased the understanding of cloud airflow and microphysical processes (Young, <br />1974; Cotton et aI., 1986; Bruintjes et aI., 1992). High resolution three-dimensional modeling can now <br />enable the study of cloud precipitation processes for areas such as the Headwaters Region. A few <br />qualitative comparisons of the RAMS model's simulation of several days of 1999 winter precipitation <br />conditions in the Headwaters Region are given in section 4.6. I. Modeling with a sophisticated model <br />such as RAMS is needed to assist the design process for the Headwaters Region. Model runs should <br />include simulation of effects of cloud seeding for comparison with the nonseeded model results. <br />Comparisons of modeling results with field measurements are needed to study model deficiencies and <br />possibly improve the model. Routine application of a model during the operational seeding phase will <br /> <br />9 <br />
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