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The snowflake microstructure determines the microwave scattering propertiesof individual snowflakes and has a strong impact on snowfall radarsignatures. In this study, individual snowflakes are represented bycollections of randomly distributed ice spheres where the size and number ofthe constituent ice spheres are specified by the snowflake mass andsurface-area-to-volume ratio (SAV) and the bounding volume of each ice spherecollection is given by the snowflake maximum dimension. Radar backscattercross sections for the ice sphere collections are calculated at X-, Ku-, Ka-,and W-band frequencies and then used to model triple-frequency radarsignatures for exponential snowflake size distributions (SSDs). Additionally,snowflake complexity values obtained from high-resolution multi-viewsnowflake images are used as an indicator of snowflake SAV to derive snowfalltriple-frequency radar signatures. The modeled snowfall triple-frequencyradar signatures cover a wide range of triple-frequency signatures that werepreviously determined from radar reflectivity measurements and illustratecharacteristic differences related to snow type, quantified through snowflakeSAV, and snowflake size. The results show high sensitivity to snowflake SAVand SSD maximum size but are generally less affected by uncertainties in theparameterization of snowflake mass, indicating the importance of snowflakeSAV for the interpretation of snowfall triple-frequency radar signatures

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