Using snowflake surface-area-to-volume ratio to model and interpret snowfall triple-frequency radar signatures

Abstract. The snowflake microstructure determines the microwave scattering properties of individual snowflakes and has a strong impact on snowfall radar signatures. In this study, the microstructure of individual snowflakes is approximated by collections of randomly distributed ice spheres where the size and number of the constituent ice spheres are specified by the snowflake mass and ice surface area-to-volume ratio (SAV) and the bounding volume is given by the snowflake maximum dimension. Radar backscatter cross sections for the ice sphere collections are calculated at X-, Ku-, Ka-, and W-band frequencies and then used to model snowfall triple-frequency radar signatures for exponential snowflake size distributions (SSDs). Additionally, first results are presented for using snowflake complexity values derived from high-resolution multi-view snowflake images as indicator of snowflake SAV. The modeled snowfall triple-frequency radar signatures cover a wide range of triple-frequency signatures that were previously determined from radar reflectivity measurements and illustrate characteristic differences related to snow type, quantified through snowflake SAV, and snowflake size. The results show high sensitivity to snowflake SAV and SSD maximum size but are less affected by uncertainties in the parameterization of snowflake mass, indicating the importance of a realistic description of snowflake SAV for a quantitative interpretation of snowfall triple-frequency radar signatures.