Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 19, issue 12
Articles | Volume 19, issue 12
https://doi.org/10.5194/amt-19-4367-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-19-4367-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 12
Research article
 | 
01 Jul 2026
Research article |  | 01 Jul 2026

An ensemble machine-learning first-guess approach for physics-based retrieval of ice particle size distributions from multi-frequency radar, validated with CCREST-M aircraft observations

Anthony J. Baran, Stuart Fox, Richard Cotton, Julien Delanoë, Christopher J. Walden, Karina McCusker, Christopher D. Westbrook, and Peter G. Huggard

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Short summary
We demonstrate how multi-frequency ground-based radars at 3, 35 and 94 GHz can be used to determine vertical profiles of ice-particle size spectra by combining reflectivity with machine-learning prior information on UK wintertime ice clouds. The method is validated using independent profiles from a 200 GHz radar and aircraft-based in-situ observations. It gives a consistent representation to compare with aircraft-based radiometric measurements in future radiative-transfer closure studies.
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