Monday, 30 August 2010
Alpine Ballroom B (Resort at Squaw Creek)
A substantial portion of orographic precipitation generation is related to structures well above the surface such as gravity waves, turbulent layers, and seeder-feeder clouds. Therefore, comparison of a model's vertical structure of precipitation and winds with three dimensional radar observations is particularly critical for understanding orographic precipitation. There have been many field study comparisons of mesoscale models with radar over steep terrain, but there have been fewer long-term comparisons using operational radars. In comparison to many field project radar data sets, the National Weather Service (NWS) radar scan strategies have coarser vertical spatial resolution. Particularly problematic are the NWS 9 elevation angle volume coverage patterns (VCPs 21, 121 and 221), which are currently used much more frequently than the 14 elevation angle patterns (VCPs 11 and 12). Interpolating the NWS radar data into a filled Cartesian grid creates too many artifacts. Thus, we have taken the alternative approach of comparing the model output to the subset of the 3-D grid where the radar data exists (i.e. along the slant-range elevation angle sweeps). This sparse grid method emphasizes comparisons between the radar data and model output in azimuth and range where the radar data spatial resolution is high. For this study, we compare spatial patterns and distributions of storm accumulated statistics including means, percentiles, and frequency of occurrence above a threshold; the latter two are less prone to the influence of outliers. Additionally, we use objective methods of quantifying differences in spatial patterns including measures of error in position and amplitude. Although not as simple as horizontal and vertical cross-sections, these slant-range comparisons provide an objective means of evaluating critical vertical structures in model forecasts of orographic precipitation.
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