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Using Machine Learning to Generate a GISS ModelE Calibrated Physics Ensemble (CPE).

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Title: Using Machine Learning to Generate a GISS ModelE Calibrated Physics Ensemble (CPE).
Authors: Elsaesser, Gregory S.1,2 (AUTHOR) gregory.elsaesser@columbia.edu, van Lier‐Walqui, Marcus2,3 (AUTHOR), Yang, Qingyuan4,5 (AUTHOR), Kelley, Maxwell2 (AUTHOR), Ackerman, Andrew S.2 (AUTHOR), Fridlind, Ann M.2 (AUTHOR), Cesana, Gregory V.2,3 (AUTHOR), Schmidt, Gavin A.2 (AUTHOR), Wu, Jingbo2,3 (AUTHOR), Behrangi, Ali6 (AUTHOR), Camargo, Suzana J.7 (AUTHOR), De, Bithi1,2 (AUTHOR), Inoue, Kuniaki2,3 (AUTHOR), Leitmann‐Niimi, Nicolas M.2,3 (AUTHOR), Strong, Jeffrey D. O.8 (AUTHOR)
Source: Journal of Advances in Modeling Earth Systems. Apr2025, Vol. 17 Issue 4, p1-26. 26p.
Database: Academic Search Ultimate
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An: 184801143
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  Data: Using Machine Learning to Generate a GISS ModelE Calibrated Physics Ensemble (CPE).
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Advances+in+Modeling+Earth+Systems%22">Journal of Advances in Modeling Earth Systems</searchLink>. Apr2025, Vol. 17 Issue 4, p1-26. 26p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=184801143
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      – Type: doi
        Value: 10.1029/2024MS004713
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      – Code: eng
        Text: English
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        PageCount: 26
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      – TitleFull: Using Machine Learning to Generate a GISS ModelE Calibrated Physics Ensemble (CPE).
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              Text: Apr2025
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