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Skillful prediction of boreal winter-spring seasonal precipitation in Southern China based on machine learning approach and dynamical ENSO prediction.

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Title: Skillful prediction of boreal winter-spring seasonal precipitation in Southern China based on machine learning approach and dynamical ENSO prediction.
Authors: Cao, Ting-wei1,2 (AUTHOR), Xu, Yi-ran1,3,4 (AUTHOR), Zheng, Fei1 (AUTHOR) zhengfei@mail.iap.ac.cn, Yang, Ruo-wen3 (AUTHOR)
Source: Theoretical & Applied Climatology. Jul2024, Vol. 155 Issue 7, p6529-6543. 15p.
Database: Environment Complete
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  Data: Skillful prediction of boreal winter-spring seasonal precipitation in Southern China based on machine learning approach and dynamical ENSO prediction.
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  Data: <searchLink fieldCode="JN" term="%22Theoretical+%26+Applied+Climatology%22">Theoretical & Applied Climatology</searchLink>. Jul2024, Vol. 155 Issue 7, p6529-6543. 15p.
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s00704-024-05011-8
    Languages:
      – Code: eng
        Text: English
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        PageCount: 15
        StartPage: 6529
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      – TitleFull: Skillful prediction of boreal winter-spring seasonal precipitation in Southern China based on machine learning approach and dynamical ENSO prediction.
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            NameFull: Cao, Ting-wei
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            NameFull: Xu, Yi-ran
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            NameFull: Zheng, Fei
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            NameFull: Yang, Ruo-wen
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          Dates:
            – D: 01
              M: 07
              Text: Jul2024
              Type: published
              Y: 2024
          Identifiers:
            – Type: issn-print
              Value: 0177798X
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              Value: 155
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              Value: 7
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            – TitleFull: Theoretical & Applied Climatology
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