Modeling the Microwave Single-scattering Properties of Aggregate Snowflakes
Monday, 15 December 2014
A new snowflake aggregation model is developed to study single-scattering properties of aggregate snowflakes. Snowflakes are generated by random aggregation of 6-bullet rosette crystals and constrained by size-density relationships derived from previous field observations. Due to random generation, aggregates may have the same size or mass, yet differing morphology allowing for a study into how shape influences their scattering properties. Furthermore, three different aggregate shapes are created: randomly generated, oblate and prolate flakes. The single-scattering properties of the aggregates are investigated using the discrete dipole approximation (DDA) at 10 frequencies. Results are compared to those of Mie theory for solid and soft spheres (density 10% that of solid ice) and to T-matrix results for solid and soft spheroidal cases with aspect ratios of 0.8 (randomly generated) and 0.6 (oblate and prolate). Above size parameter 0.75, neither the solid nor the soft sphere and spheroidal approximations accurately represent the DDA results for the randomly generated or oblate aggregates. Asymmetry and the normalized scattering and backscattering cross-sections of the randomly generated and oblate aggregates fall between the soft and solid spherical and spheroidal approximations. This implies that evaluating snow scattering properties using realistic shapes, such as the aggregates created in this study instead of a simplified crystal shape, is of paramount importance. The dependence of the single-scattering properties on each aggregate’s detailed structure seems of secondary importance. Oblate and prolate preliminary results indicate that backscattering for prolate and oblate flakes is lower than that of the randomly generated flakes. Detailed analyses are conducted to answer: (a) why aggregates of similar size yet dissimilar shape backscatter differently and (b) why prolate and oblate aggregates backscatter differently than randomly generated aggregates.