Articles | Volume 24, issue 11
https://doi.org/10.5194/acp-24-6613-2024
https://doi.org/10.5194/acp-24-6613-2024
Research article
 | 
06 Jun 2024
Research article |  | 06 Jun 2024

A survey of radiative and physical properties of North Atlantic mesoscale cloud morphologies from multiple identification methodologies

Ryan Eastman, Isabel L. McCoy, Hauke Schulz, and Robert Wood

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Cited articles

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Short summary
Cloud types are determined using machine learning image classifiers applied to satellite imagery for 1 year in the North Atlantic. This survey of these cloud types shows that the climate impact of a cloud scene is, in part, a function of cloud type. Each type displays a different mix of thick and thin cloud cover, with the fraction of thin cloud cover having the strongest impact on the clouds' radiative effect. Future studies must account for differing properties and processes among cloud types.
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