9.3 Visualizing Atmospheric Phenomena in Mountainous Terrain with a Surface-based Scanning Aerosol Lidar. First Results of REAL from T-REX

Wednesday, 30 August 2006: 9:00 AM
Ballroom South (La Fonda on the Plaza)
Stephan F. J. De Wekker, NCAR, Boulder, CO; and S. D. Mayor, S. M. Spuler, B. M. Morley, D. J. Kirshbaum, G. S. Poulos, and T. M. Weckwerth

We present first results from the deployment of the Raman-shifted Eye-safe Aerosol Lidar (REAL) in the Owens Valley, CA, during the Terrain-induced Rotor Experiment (T-REX) in March and April 2006. REAL operated in both a Range Height Indicator (RHI) and Plan Position Indicator (PPI) scanning mode to document the horizontal and vertical structure of the aerosol and cloud distribution in a mountainous environment. The scans produce two-dimensional cross sections that can be linked together to form high resolution time-lapse animations of the structure, evolution, and motion of aerosol layers and plumes. The two-month data set reveals a number of interesting atmospheric phenomena and an attempt is made to categorize these phenomena in terms of rotor, mountain wave, and boundary-layer development. In synoptically disturbed conditions, the animations reveal rotor-like circulations of boundary layer aerosols and mountain waves from elevated aerosol layers and clouds. Position, wavelength and amplitude of the waves appear highly variable. Clouds apparently spilling over the Sierra mountains were a recurring feature in the animations during westerly flow. Kelvin-Helmholtz and shear instabilities occasionally leading to breaking waves were observed in cloud and aerosol layers under high wind conditions. In quiescent conditions, aerosol backscatter cross sections reveal the evolution of the daytime boundary layer and the onset and development of cumuli. Upslope and downslope flows were documented by tracking dust plumes at the base of the Sierra mountains. We demonstrate that a rapidly scanning surface-based aerosol lidar can contribute significantly to an improved understanding of mountain meteorological phenomena and encourage the research community to use the dataset in support of their observational analysis and/or modeling efforts.
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