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.

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Title: 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.
Authors: Baran, Anthony J.1,2 (AUTHOR) anthony.baran@metoffice.gov.uk, Fox, Stuart2 (AUTHOR), Cotton, Richard2 (AUTHOR), Delanoë, Julien3 (AUTHOR), Walden, Christopher J.4,5 (AUTHOR), McCusker, Karina6 (AUTHOR), Westbrook, Christopher D.6 (AUTHOR), Huggard, Peter G.5 (AUTHOR)
Source: Atmospheric Measurement Techniques. 2026, Vol. 19 Issue 12, p4367-4392. 26p.
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  Data: 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.
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  Data: <searchLink fieldCode="JN" term="%22Atmospheric+Measurement+Techniques%22">Atmospheric Measurement Techniques</searchLink>. 2026, Vol. 19 Issue 12, p4367-4392. 26p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=195125917
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