Light Scattering by Quasi-Spherical Ice Crystals

Abstract

The shapes and single-scattering properties of small, irregular, quasi-spherical ice crystals, with equivalent radii between approximately 8 and 90 ?m and size parameters from about 90 to 1000, are studied using two-dimensional images measured by a cloud particle imager in midlatitude cirrus during the 2000 Cloud Intensive Operation Period conducted over the Atmospheric Radiation Measurement program's Southern Great Plains site. A statistical shape analysis of the ice crystal images is carried out to obtain size-dependent relative standard deviations of radius and correlation functions of logradius, which together define the shape statistics of the sample ice crystals. The former describes the overall variation in the lengths of radius vectors defining the particle surface from a given origin, whereas the latter describes correlations of lengths of radius vectors as functions of angular distance between them. The logradius is essentially the natural logarithm of radius. There is no strong dependence of the shapes of these particles on size. The retrieved correlation functions resemble a power-law correlation function closely, suggesting that the shape statistics based on the power-law correlation function can be used as a first approximation for the shapes of small, quasi-spherical ice crystals in cirrus. By using the retrieved shape statistics as input, a Gaussian random sphere geometry previously used to describe the shapes of desert dust particles is used to generate model particles that obey the retrieved shape statistics. The single-scattering properties of these particles are then computed at a wavelength of 550 nm using ray optics. The scattering simulations give asymmetry parameters around 0.76, slightly smaller than values suggested from previous studies using Chebyshev polynomials to describe the shapes of quasi-spherical ice crystals. Assuming a flux accuracy criterion at the top of the atmosphere of ±5% is needed, this difference in asymmetry parameter is significant.