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Characterizing the Vertical Distribution of Aerosols above SGP using CHARMS data

 

Authors

Richard A. Ferrare — NASA - Langley Research Center
Tyler Thorsen — NASA - Langley Research Center
Marian B. Clayton — Science Systems and Applications, Inc. (SSAI)
Detlef Mueller — Science Systems and Applications, Inc.
Eduard Chemyakin — Science Systems and Applications, Inc.
Sharon P Burton — NASA - Langley Research Center
John E. M. Goldsmith — Sandia National Laboratories
Robert E. Holz — University of Wisconsin/CIMMS
Ralph Kuehn — University of Wisconsin Madison
Edwin W. Eloranta — University of Wisconsin
Willem Jacobus Marais — University of Wisconsin - CIMSS
Rob K Newsom — Pacific Northwest National Laboratory
Patricia Sawamura — Oak Ridge Associated Universities/NASA Langley Research Cent
Richard Moore — NASA Langley Research Center
Brent Holben — NASA - Goddard Space Flight Center
Evgueni Kassianov — Pacific Northwest National Laboratory
Yan Shi — Pacific Northwest National Laboratory
Chris A. Hostetler — NASA Langley Research Center
Xu Liu — NASA LANGLEY RESEARCH CENTER

Category

Boundary layer structure, including land-atmosphere interactions and turbulence

Description

Continuous (24/7) operation of the co-located SGP Raman lidar and University of Wisconsin (UW) High-Spectral-Resolution Lidar (HSRL) during the 10-week Combined HSRL And Raman lidar Measurement Study (CHARMS) mission (mid-July through September, 2015) allowed the acquisition of a unique, multi-wavelength, ground-based lidar data set. The ARM SGP Raman lidar measured profiles of aerosol backscatter, extinction, and depolarization at 355 nm and profiles of water vapor mixing ratio and temperature. The UW HSRL simultaneously measured profiles of aerosol backscatter, extinction and depolarization at 532 nm and aerosol backscatter at 1064 nm. We use these CHARMS data to classify the vertical distribution of aerosols and apportion aerosol optical thickness and extinction to aerosol type. The lidar profiles of aerosol intensive properties (lidar ratio, depolarization ratio, backscatter color ratio), which provide information about the aerosol physical properties, are used in a semi-supervised algorithm to provide profiles of aerosol type. Initial indications show that, in terms of aerosol extinction and optical thickness, the dominant aerosol types observed near the surface were smoke/urban and a dusty mix; the smoke/urban mix was the dominant type above the mixed layer. We also apply unique, automated, unsupervised algorithms that use multi-wavelength lidar measurements of aerosol backscatter and extinction to the CHARMS data to derive profiles of aerosol microphysical (e.g., effective radius, concentration, fine mode fraction) properties aloft. These algorithms, which are based on Tikhonov regularization and Optimal Estimation, were developed for analyzing data from the NASA Langley airborne multi-wavelength HSRL and for possible satellite applications. When applied to the airborne HSRL data, these algorithms produce aerosol microphysical profiles that compare well with coincident airborne in situ measurements. We apply these to the CHARMS data and compare column-average aerosol properties derived from these algorithms to corresponding values retrieved from AERONET and MFRSR measurements. Column-averaged comparisons of fine mode effective radius, fine mode fraction, and volume concentration derived from the CHARMS data show generally good agreement with corresponding values derived from AERONET. We also use the lidar measurements to study how these aerosol properties vary within and above the boundary layer and with changes in relative humidity.