Articles | Volume 10, issue 1
https://doi.org/10.5194/amt-10-83-2017
https://doi.org/10.5194/amt-10-83-2017
Research article
 | 
06 Jan 2017
Research article |  | 06 Jan 2017

Profiling aerosol optical, microphysical and hygroscopic properties in ambient conditions by combining in situ and remote sensing

Alexandra Tsekeri, Vassilis Amiridis, Franco Marenco, Athanasios Nenes, Eleni Marinou, Stavros Solomos, Phil Rosenberg, Jamie Trembath, Graeme J. Nott, James Allan, Michael Le Breton, Asan Bacak, Hugh Coe, Carl Percival, and Nikolaos Mihalopoulos

Abstract. We present the In situ/Remote sensing aerosol Retrieval Algorithm (IRRA) that combines airborne in situ and lidar remote sensing data to retrieve vertical profiles of ambient aerosol optical, microphysical and hygroscopic properties, employing the ISORROPIA II model for acquiring the particle hygroscopic growth. Here we apply the algorithm on data collected from the Facility for Airborne Atmospheric Measurements (FAAM) BAe-146 research aircraft during the ACEMED campaign in the Eastern Mediterranean. Vertical profiles of aerosol microphysical properties have been derived successfully for an aged smoke plume near the city of Thessaloniki with aerosol optical depth of  ∼  0.4 at 532 nm, single scattering albedos of  ∼  0.9–0.95 at 550 nm and typical lidar ratios for smoke of  ∼  60–80 sr at 532 nm. IRRA retrieves highly hydrated particles above land, with 55 and 80 % water volume content for ambient relative humidity of 80 and 90 %, respectively. The proposed methodology is highly advantageous for aerosol characterization in humid conditions and can find valuable applications in aerosol–cloud interaction schemes. Moreover, it can be used for the validation of active space-borne sensors, as is demonstrated here for the case of CALIPSO.

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Short summary
The In situ/Remote sensing aerosol Retrieval Algorithm (IRRA) provides vertical profiles of aerosol optical, microphysical and hygroscopic properties from airborne in situ and remote sensing measurements. The algorithm is highly advantageous for aerosol characterization in humid conditions, employing the ISORROPIA II model for acquiring the particle hygroscopic growth. IRRA can find valuable applications in aerosol–cloud interaction schemes and in validation of active space-borne sensors.