Abstract

Abstract. This study introduces a novel methodology for the characterization of atmospheric aerosol based on lidar-derived intensive optical properties. The proposed aerosol-typing scheme is based on the optimal estimation method (OEM) and allows the identification of up to four different aerosol components of an aerosol mixture, as well as the quantification of their contribution to the aerosol mixture in terms of relative volume. The four aerosol components considered in this typing scheme are associated with the most commonly observed aerosol particles in nature and are assumed to be physically separated from each other and, therefore, can create external mixtures. Two components represent absorbing and less-absorbing fine-mode particles, and the other two components represent spherical and non-spherical coarse-mode particles. These components reflect adequately the most frequently observed aerosol types in the atmosphere: combustion- and pollution-related aerosol, sea salt, and desert dust, respectively. In addition, to consolidate the calibration and validation efforts for the upcoming EarthCARE mission, the typing scheme proposed here is in accordance with the Hybrid End-To-End Aerosol Classification (HETEAC) model of EarthCARE. The lidar-derived optical parameters used in this typing scheme are the lidar ratio and the particle linear depolarization ratio at two distinct wavelengths (355 and 532 nm), the backscatter-related color ratio for the wavelength pair of 532/1064 nm and the extinction-related Ångström exponent for the wavelength pair of 355/532 nm. These intensive optical properties can be combined in different ways, making the methodology flexible, thus allowing its application to lidar systems with different configurations (e.g., single wavelength or multiwavelength, Raman, high spectral resolution). The typing scheme was therefore named HETEAC-Flex due to its compatibility with EarthCARE's HETEAC and its methodological flexibility. The functionality of the typing scheme is demonstrated by its application to three case studies based on layer-averaged optical properties.

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