88th Annual Meeting (20-24 January 2008)

Wednesday, 23 January 2008
Long-term lidar and radar observations of Arctic stratus at two locations
Exhibit Hall B (Ernest N. Morial Convention Center)
Gijs de Boer, Lawrence Berkeley National Lab, Berkeley, CA; and E. W. Eloranta and J. P. Garcia
Mixed-phase clouds remain a difficult problem for both the observational and modeling communities. In particular, improved understanding of mixed-phase clouds in the Arctic is crucial because of radiative effects they impart on a region that is particularly sensitive to change. In order to better understand these cloud structures, the University of Wisconsin Arctic High Spectral Resolution Lidar has been deployed to two different Arctic locations. The first deployment lasted two months and was to Barrow, AK in support of the Mixed-Phase Arctic Clouds Experiment (M-PACE). The second deployment is ongoing, and so far over two years of data have been collected at Eureka, Canada. In both locations, the lidar was co-located with a NOAA Millimeter Cloud Radar (MMCR). Mixed phase stratus has been readily detected at both locations, and we currently have measurements for hundreds of hours of stratus cases.

Measurements from both the radar and lidar are currently being analyzed in order to derive a statistical database of cloud properties and atmospheric conditions. Analyzed properties include cloud base and top (from lidar and radar), vertical velocity (from the radar Doppler measurement), temperature, pressure, dew point, wind-speed and wind direction (from radiosondes), particle effective size, particle number density and water content (from combined lidar-radar retrieval techniques) and particle phase (from lidar depolarization and radar).

In this presentation we will give an overview of the measurement and analysis techniques used, the retrieval methods implemented, and our results. In addition, we will review how these measurements have increased our understanding of mixed-phase clouds and how that knowledge is being applied towards the improvement of numerical models.

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