Articles | Volume 17, issue 14
https://doi.org/10.5194/amt-17-4337-2024
https://doi.org/10.5194/amt-17-4337-2024
Research article
 | 
23 Jul 2024
Research article |  | 23 Jul 2024

The Chalmers Cloud Ice Climatology: retrieval implementation and validation

Adrià Amell, Simon Pfreundschuh, and Patrick Eriksson

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Short summary
The representation of clouds in numerical weather and climate models remains a major challenge that is difficult to address because of the limitations of currently available data records of cloud properties. In this work, we address this issue by using machine learning to extract novel information on ice clouds from a long record of satellite observations. Through extensive validation, we show that this novel approach provides surprisingly accurate estimates of clouds and their properties.