Automated retrieval of cloud and aerosol properties from the ARM Raman lidar

Description

The ARM Raman lidars (RL) are far more advance systems than the ARM program's primary lidar the MPL (micropulse lidar) with the ability to directly measure extinction and a shorter wavelength laser--- which reduces the impact of solar background noise in the elastic channel. However, current RL products don't take advantage of the full capabilities of the Raman lidar, particularly as a tool for observing clouds. The identification of clouds in the current ARM products is handled in a relatively simple way which results is many cloud layers going undetected. Therefore, in this work, we develop a more rigorous automated algorithm to objectively identify the presence of particulate (cloud and aerosol) layers using context-sensitive thresholds. These thresholds are applied to multiple quantities measured by the RL to obtain the most complete description possible of the vertical extent of particulate layers. The algorithm is also able to directly retrieve extinction for thinner cloud types by an adaptive smoothing technique. Examples of the algorithm's performance are presented for the Darwin site.