Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 14, issue 11
Articles | Volume 14, issue 11
https://doi.org/10.5194/amt-14-7079-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-7079-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 11
Research article
 | 
11 Nov 2021
Research article |  | 11 Nov 2021

The University of Washington Ice–Liquid Discriminator (UWILD) improves single-particle phase classifications of hydrometeors within Southern Ocean clouds using machine learning

Rachel Atlas, Johannes Mohrmann, Joseph Finlon, Jeremy Lu, Ian Hsiao, Robert Wood, and Minghui Diao

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Latest update: 03 Nov 2024
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Short summary
Many clouds with temperatures between 0 °C and −40 °C contain both liquid and ice particles, and the ratio of liquid to ice particles influences how the clouds interact with radiation and moderate Earth's climate. We use a machine learning method called random forest to classify images of individual cloud particles as either liquid or ice. We apply our algorithm to images captured by aircraft within clouds overlying the Southern Ocean, and we find that it outperforms two existing algorithms.
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