P2.14
Storm structures and precipitation characteristics of snow events in the southern Appalachian Mountains
Sandra E. Yuter, North Carolina State University, Raleigh, NC; and L. B. Perry
Orographic snowfall presents an opportunity to observe ice-phase precipitation growth processes in isolation from liquid-phase processes. In this study, we examine the natural variability of the physical characteristics of precipitation during snow events in the southern Appalachians using a suite of instruments at Poga Mountain, NC. The site has instruments at elevations between 1021 m and 1137 m above sea level and is located close to the North Carolina/Tennessee border near the crest of the Appalachian Mountains. Average snowfall is 125 cm per year. Most snow events are associated with northwest flow of low-level moist air emanating from the Midwest and Great Lakes area that moves upslope along the northwestern slopes of the southern Appalachians.
The ground-based instruments include a vertically-pointing MicroRainRadar (Ku-band), meteorological tower, weighing gauge, and PARSIVEL disdrometer. The PARSIVEL disdrometer measures the particle size and fall speed simultaneously making possible the discrimination between rain, wet snow, and dry snow particles. The vertically-pointing Ku-band radar is used to observe the vertical profile of reflectivity and Doppler velocity of storms as they pass overhead. Additional measurements were made of snow depth and snow water equivalent.
During the 2006-2007 winter season there have been 19 snowfall events at the site with accumulations ranging from 0.25 cm to 14.7 cm. Echo top heights tended to be shallow, less than 2 km above ground level, for most events. Twelve of the 19 snow events occurred when the wind was out of the northwest and flowing up the mountain slopes. The three heaviest snow events (10.2 cm, 13.9 cm, 14.7 cm) occurred when Canadian air masses pushed southeastward into the Appalachian range. Ratios of snow liquid water equivalent to snow depth ranged from 0.0125 to 0.5 with most values < 0.1. Results from the analysis will be used to improve understanding of the physics of snow and to refine model forecasts of snow events.
Poster Session 2, Poster Viewing/reception
Wednesday, 8 August 2007, 4:30 PM-6:00 PM, White Mountain Room
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