Articles | Volume 20, issue 23
Atmos. Chem. Phys., 20, 14491–14507, 2020
https://doi.org/10.5194/acp-20-14491-2020

Special issue: Winter weather research in complex terrain during ICE-POP...

Atmos. Chem. Phys., 20, 14491–14507, 2020
https://doi.org/10.5194/acp-20-14491-2020

Research article 30 Nov 2020

Research article | 30 Nov 2020

Microphysical properties of three types of snow clouds: implication for satellite snowfall retrievals

Hwayoung Jeoung et al.

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Status: closed
Status: closed
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 Guosheng Liu on behalf of the Authors (15 Oct 2020)  Author's response    Manuscript
ED: Publish as is (19 Oct 2020) by Timothy Garrett

Post-review adjustments

AA: Author's adjustment | EA: Editor approval
AA by Guosheng Liu on behalf of the Authors (27 Nov 2020)   Author's adjustment   Manuscript
EA: Adjustments approved (27 Nov 2020) by Timothy Garrett
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Short summary
Radar and radiometer observations were used to study cloud liquid and snowfall in three types of snow clouds. While near-surface and shallow clouds have an area fraction of 90 %, deep clouds contribute half of the total snowfall volume. Deeper clouds have heavier snowfall, although cloud liquid is equally abundant in all three cloud types. The skills of a GMI Bayesian algorithm are examined. Snowfall in deep clouds may be reasonably retrieved, but it is challenging for near-surface clouds.
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