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<br /> <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br />. <br /> <br /> <br />- <br /> <br />The 2003-2004 prototype real-time forecast version of RAMS@CSU was <br />based on version 4.3. The physics of the model is described in some detail in <br />Cotton et al. (2003). The model was set up on a cluster of PCs. The forecast <br />model configuration has three interactive nested grids. Grid 1 has 48-km grid <br />spacing that covers the entire conterminous United States. Grid 2 has 12-km <br />grid spacing that covers all of Colorado, most of Wyoming, and portions of <br />adjacent states. Grid 3 has 3-km ~rid spacing for 82 x 82 grid points covering a <br />246 km x 246 km area (60,516 km ) that is relocateable anywhere within Grid 2. <br />Figure 1.2 shows RAMS Grid 1 covering the contiguous U.S. with nested Grids 2 <br />and 3. Figure 1.3 shows the 12-km regional grid, and Figure 1.4 shows the 3-km <br />fine grid with the project target area and some town IDs. <br /> <br />Vertical grid spacing on all grids starts with 150-km spacing at the lowest <br />levels and is stretched to 1000 m aloft, with a total of 36 vertical levels extending <br />into the stratosphere. The model is initialized with 0000 UTC Eta model analysis <br />fields and run for a period of 48 hours, with the lateral boundary region of the <br />coarse grid nudged to the Eta 3-hr forecast fields. A 48-hr run typically begins at <br />0300 UTC (2000 MST) when the 0000 UTC Eta forecast data are available. The <br />run takes 4-5 hours of computer time to finish, and is completed by 0200 MST. <br />Because RAMS has been able to reproduce high-elevation snowfall amounts <br />with considerable accuracy (Gaudet and Cotton, 1998; Wetzel et aI., 2003), it <br />was believed that RAMS could be useful in forecasting the effects of cloud <br />seeding on precipitation for an entire winter season. <br /> <br />7 <br />