Separating mixtures of aerosol types in airborne High Spectral Resolution Lidar data

Knowledge of aerosol type is important for determining the magnitude and assessing the consequences of aerosol radiative forcing, and can provide useful information for source attribution studies. However, atmospheric aerosol is frequently not a single pure type, but instead occurs as a mixture of types, and this mixing affects the optical and radiative properties of the aerosol. This paper extends the work of earlier researchers by using the aerosol intensive parameters measured by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL-1) to develop a comprehensive and unified set of rules for characterizing the external mixing of several key aerosol intensive parameters: extinction-to-backscatter ratio (i.e., lidar ratio), backscatter color ratio, and depolarization ratio. We present the mixing rules in a particularly simple form that leads easily to mixing rules for the covariance matrices that describe aerosol distributions, rather than just single values of measured parameters. These rules can be applied to infer mixing ratios from the lidar-observed aerosol parameters, even for cases without significant depolarization. We demonstrate our technique with measurement curtains from three HSRL-1 flights which exhibit mixing between two aerosol types, urban pollution plus dust, marine plus dust, and smoke plus marine. For these cases, we infer a time-height cross-section of extinction mixing ratio along the flight track, and partition aerosol extinction into portions attributed to the two pure types.