92nd American Meteorological Society Annual Meeting (January 22-26, 2012)

Monday, 23 January 2012: 1:30 PM
Comparison of Vertical Velocity Measurements From a Coherent Doppler Lidar and a Vertically Staring 915 MHz Radar Wind Profiler
Room 239 (New Orleans Convention Center )
Rob K. Newsom, PNNL, Richland, WA; and E. Campos, R. L. Coulter, and M. L. Fischer

The US Department of Energy Atmospheric Radiation Measurement (ARM) Program recently added a scanning Doppler lidar to its extensive suite of instrumentation at the Southern Great Plains (SGP) site in north-central Oklahoma. In April 2011, the lidar was deployed close to two cloud radar systems and immediately next to a 915 MHz radar wind profiler. Since March 2011 the radar profiler has been configured to sample only in the zenith direction. One of the scientific motivations for this set up was to enable complimentary estimates of in-cloud and clear-air vertical velocities. Such estimates are crucial for the evaluation of large-eddy simulations, cloud-resolving models and certain aspects of large-scale model parameterizations. Detailed comparisons between vertical air velocities from these various systems are equally important in order to identify and understand potential biases. The focus of this study is to evaluate and compare vertical velocity estimates of the (vertically staring) 915 MHz radar wind profiler and Doppler lidar at the ARM SGP site. Additionally, the representativeness of the lidar measurements are assessed by comparison with three-dimensional sonic anemometer measurements at two levels on a nearby 60-m tower. The sonic-lidar comparison was performed over the course of two days, under clear conditions. The radar-lidar comparison was carried out over the course of several months, and under a variety of meteorological conditions. Differences between the lidar and the radar measurements are affected by significant differences in scattering mechanisms and sampling volumes. The results of the comparisons are discussed and quantified in terms of cross-correlation, bias and root-mean-squared differences.

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