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Ground-based High Spectral Resolution Lidar observation of aerosol vertical...

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Reid, J., R. Kuehn, R. E. Holz, E. W. Eloranta, K. C. Kaku, S. Kuang, M. Newchurch, A. M. Thompson, C. Trepte, J. Zhang, S. A. Atwood, J. L. Hand, B. Holben, P. Minnis, and D. Posselt (2017), Ground-based High Spectral Resolution Lidar observation of aerosol vertical distribution in the summertime Southeast United States, J. Geophys. Res., 122, doi:10.1002/2016JD025798.

As part of the Southeast United States-based Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS), and collinear with part of the Southeast Atmosphere Study, the University of Wisconsin High Spectral Resolution Lidar system was deployed to the University of Alabama from 19 June to 4 November 2013. With a collocated Aerosol Robotic Network (AERONET) sun photometer, a nearby Chemical Speciation Network (PM2.5) measurement station, and near daily ozonesonde releases for the August–September SEAC4RS campaign, the site allowed the region’s first comprehensive diurnal monitoring of aerosol particle vertical structure. A 532 nm lidar ratio of 55 sr provided good closure between aerosol backscatter and AERONET (aerosol optical thickness, AOT). A principle component analysis was performed to identify key modes of variability in aerosol backscatter. “Fair weather” days exhibited classic planetary boundary layer structure of a mixed layer accounting for ~50% of AOT and an entrainment zone providing another 25%. An additional 5–15% of variance is gained from the lower free troposphere from either convective detrainment or frequent intrusions of western United States biomass burning smoke. Generally, aerosol particles were contained below the 0°C level, a common level of stability in convective regimes. However, occasional strong injections of smoke to the upper troposphere were also observed, accounting for the remaining 10–15% variability in AOT. Examples of these common modes of variability in frontal and convective regimes are presented, demonstrating why AOT often has only a weak relationship to surface PM2.5 concentration.

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