Articles | Volume 20, issue 23
https://doi.org/10.5194/acp-20-14491-2020
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, Guosheng Liu, Kwonil Kim, Gyuwon Lee, and Eun-Kyoung Seo

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Latest update: 11 Apr 2024
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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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