16.2 Effects of atmospheric conditions and cloud seeding on orographic snowfall characteristics during the Silver Iodide (AgI) Seeding of Clouds Impact Investigation (ASCII) experiment

Thursday, 23 August 2012: 4:00 PM
Priest Creek C (The Steamboat Grand)
Katja Friedrich, University of Colorado at Boulder, Boulder, CO; and E. A. Kalina, B. Geerts, K. A. Kosiba, and J. M. Wurman

One of the objectives of the ASCII experiment is to investigate the relationship between cloud seeding, mountain topography, upstream conditions, and snowfall characteristics. The main challenges of measuring snowfall are related to the high spatial and temporal variability of snowfall, the complexity of snow (crystal habit, density, particle size distribution), and it's strong dependency on environmental conditions (temperature, saturation, humidity, vertical velocity, amount of supercooled liquid). Using data from 17 intensive observation periods during the ASCII experiment, we investigate the impact of low-level convergence (e.g., terrain-induced, small scale turbulence, mountain waves), local temperature disturbances (e.g., surface cold-pool, mid-level warm noses, diabatic cooling effects) and orographic enhancement mechanisms and how these parameters affect the growth of precipitation and alter snow accumulation. Low-level convergence and turbulence is investigated using the Doppler on Wheels (DOW) radar and the University of Wyoming Cloud Radar and Lidar. Surface radiometers and vertically-pointing Ku-band micro rain radars (MRRs) deployed at the valley and mountain stations are used to study diabatic cooling effects and local temperature distribution. Precipitation efficiency is further analyzed by monitoring the vertical profiles of liquid water content and temperature obtained from two microwave radiometers deployed at the valley and mountain top, the precipitation characteristics from the surface precipitation stations (disdrometers, snow gauges) and the dual-polarization DOW radar deployed at the mountain top. The investigation distinguishes between seeding periods when the surface-based seeding generators located upstream of the surface instruments were operated and no seeding periods. Reflectivity structures and particle size distributions (PSDs) during seeding periods with similar synoptic and mesoscale forcing will be compared against no seeding periods.
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