Articles | Volume 17, issue 19
https://doi.org/10.5194/acp-17-12011-2017
https://doi.org/10.5194/acp-17-12011-2017
Research article
 | 
10 Oct 2017
Research article |  | 10 Oct 2017

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

Mathias Gergely, Steven J. Cooper, and Timothy J. Garrett

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Latest update: 20 Jul 2024
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Short summary
This study investigates the importance of snowflake surface-area-to-volume ratio (SAV) for the interpretation of snowfall triple-frequency radar signatures. The results indicate that snowflake SAV has a strong impact on modeled snowfall radar signatures and therefore may be used to further constrain (the large variety and high natural variability of) snowflake shape for snowfall remote sensing, e.g., to distinguish graupel snow from snowfall characterized by large aggregate snowflakes.
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