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When is an ensemble like a sample? “Model-based” inferences in climate modeling

Dethier, Corey (2022) When is an ensemble like a sample? “Model-based” inferences in climate modeling. Synthese, 200. pp. 1-20. ISSN 1573-0964

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Abstract

Climate scientists often apply statistical tools to a set of different estimates generated by an “ensemble” of models. In this paper, I argue that the resulting inferences are justified in the same way as any other statistical inference: what must be demonstrated is that the statistical model that licenses the inferences accurately represents the probabilistic relationship between data and target. This view of statistical practice is appropriately termed “model-based,” and I examine the use of statistics in climate fingerprinting to show how the difficulties that climate scientists encounter in applying statistics to ensemble-generated data are the practical difficulties of normal statistical practice. The upshot is that whether the application of statistics to ensemble-generated data yields trustworthy results should be expected to vary from case to case.


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Item Type: Published Article or Volume
Creators:
CreatorsEmailORCID
Dethier, Coreycorey.dethier@gmail.com0000-0002-1240-8391
Keywords: Climate models Ensemble methods Statistics Model-based
Subjects: Specific Sciences > Climate Science and Meteorology
General Issues > Computer Simulation
Specific Sciences > Probability/Statistics
Depositing User: Mr Corey Dethier
Date Deposited: 03 Mar 2022 17:35
Last Modified: 03 Mar 2022 17:35
Item ID: 20261
Journal or Publication Title: Synthese
Publisher: Springer (Springer Science+Business Media B.V.)
Official URL: https://link.springer.com/article/10.1007/s11229-0...
DOI or Unique Handle: https://doi.org/10.1007/s11229-022-03477-5
Subjects: Specific Sciences > Climate Science and Meteorology
General Issues > Computer Simulation
Specific Sciences > Probability/Statistics
Date: 2022
Page Range: pp. 1-20
Volume: 200
Number: 0
ISSN: 1573-0964
URI: http://philsci-archive.pitt.edu/id/eprint/20261

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