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

 

Authors

David D. Turner — NOAA- Global Systems Laboratory
Jennifer M. Comstock — Pacific Northwest National Laboratory
Rob K Newsom — Pacific Northwest National Laboratory
Qiang Fu — University of Washington
Tyler Thorsen — NASA - Langley Research Center

Category

General Topics

Description

The ARM Raman lidars (RL) are currently deployed at both the SGP and NSA sites, with the main goal of measuring water vapor profiles at a high temporal and vertical spatial resolution. While cloud observations were originally considered of secondary importance for this system, Thorsen et al. (2013) showed that the RL provides far superior observations of clouds compared to the ARM micropulse lidar (MPL). However, the identification of clouds is treated in a simple manner in current ARM RL data products and many clouds, especially cirrus, are not identified. In this work, an improved algorithm for Feature (cloud+aerosol) detection and EXtinction retrieval (FEX) is developed for the ARM Raman lidar (RL). FEX uses multiple quantities--- scattering ratios derived using elastic and nitrogen channel signals from two fields of view, the scattering ratio derived using only the elastic channel, and the total volume depolarization ratio--- to identify features using range-dependent detection thresholds. FEX is designed to be content-sensitive with thresholds determined for each profile by calculating the expected clear-sky signal and noise. The use of multiple quantities provides complementary depictions of cloud and aerosol locations and allows for consistency checks to improve the accuracy of the feature mask. Directly-retrieved particulate extinction profiles are obtained using the Raman method and supplemented by other retrieval methods developed for elastic backscatter lidars. Portions of features where the extinction-to-backscatter ratios (i.e., lidar ratios) can be obtained directly are used to infer the lidar ratios for the regions where no such estimate can be made. When neither directly-retrieved nor an inferred value can be determined, a climatological lidar ratio is used. A classification of feature type is made guided by the atmosphere's thermodynamic state and the feature's scattering properties: lidar ratio, backscatter and depolarization. The contribution of multiple scattering is explicitly considered for each of the ARM RL channels.