Articles | Volume 17, issue 19
Atmos. Chem. Phys., 17, 12011–12030, 2017
https://doi.org/10.5194/acp-17-12011-2017
Atmos. Chem. Phys., 17, 12011–12030, 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 et al.

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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Mathias Gergely on behalf of the Authors (23 Aug 2017)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (23 Aug 2017) by Ari Laaksonen
RR by Anonymous Referee #1 (23 Aug 2017)
RR by Anonymous Referee #2 (03 Sep 2017)
ED: Publish as is (05 Sep 2017) by Ari Laaksonen
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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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