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  "Title": "Multivariate Bias Correction of Climate Model Outputs",
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  "Description": "Calibrate and apply multivariate bias correction\nalgorithms for climate model simulations of multiple climate\nvariables. Three methods described by Cannon (2016)\n<doi:10.1175/JCLI-D-15-0679.1> and Cannon (2018)\n<doi:10.1007/s00382-017-3580-6> are implemented — (i) MBC\nPearson correlation (MBCp), (ii) MBC rank correlation (MBCr),\nand (iii) MBC N-dimensional PDF transform (MBCn) — as is the\nRank Resampling for Distributions and Dependences (R2D2)\nmethod.",
  "Date": "2024-11-12",
  "License": "GPL-2",
  "Encoding": "UTF-8",
  "NeedsCompilation": "no",
  "Author": "Alex J. Cannon [aut, cre]\n(<https://orcid.org/0000-0002-8025-3790>)",
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      "title": "Multivariate Bias Correction of Climate Model Outputs",
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        "MBC"
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      "page": "cccma",
      "title": "Sample CanESM2 and CanRCM4 data",
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        "cccma"
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      "title": "Energy distance score",
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      "title": "Multivariate bias correction (N-pdft)",
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      "title": "Multivariate bias correction (Pearson correlation)",
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      "page": "MBCr",
      "title": "Multivariate bias correction (Spearman rank correlation)",
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      "title": "Multivariate linear rescaling using Cholesky decomposition",
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      "title": "Multivariate bias correction (R2D2)",
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