Feasibility of polarized all-sky imaging for aerosol characterization

Abstract

In this study, we investigate the method of polarized all-sky imaging with respect to aerosol characterization. As a technical frame work for image processing and analysis, we propose Zernike polynomials to decompose the relative Stokes parameter distributions. This defines a suitable and efficient feature vector which is also appealing because it is independent of calibration, circumvents overexposure problems and is robust against pixel noise. We model the polarized radiances of realistic aerosol scenarios and construct the feature vector space of the key aerosol types in terms of the first two principal components describing the maximal variances. We show that, using this representation, aerosol types can be clearly distinguished with respect to fine and coarse mode dominated size distribution and index of refraction. We further investigate the individual influences of varying aerosol properties and solar zenith angle. This suggests that polarized all-sky imaging may improve aerosol characterization in combination with sky scanning radiometers of the existing Aerosol Robotic Network (AERONET) especially at low aerosol optical depths and low solar zenith angles.