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Ensembles as Evidence, Not Experts: On the Value and Interpretation of Climate Models

Dethier, Corey (2022) Ensembles as Evidence, Not Experts: On the Value and Interpretation of Climate Models. [Preprint]

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Abstract

Climate scientists frequently interpret climate models as providing probabilistic information, a practice that has come under substantial criticism from philosophers of science. In this paper, I argue that this practice has (previously unacknowledged) advantages. In particular, though the literature has focused on the use of probabilities in communicating results, climate scientists regularly treat probabilities generated by models not as the final products of research but instead as evidence or as an intermediate step in a longer reasoning process. In these cases, inter-model variation provides important information about the amount of uncertainty that is warranted by the evidence---information that can only be captured in some sort of probability distribution. Even if we accept extant arguments against the probabilistic interpretation of climate models in the context of communication, therefore, the advantages of the probabilistic interpretation of climate models in other areas makes it a substantive question whether those arguments can be extended to the more general case.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Dethier, Coreycorey.dethier@gmail.com0000-0002-1240-8391
Additional Information: Draft; comments extremely welcome. Please contact at corey.dethier[at]gmail.com before citing or quoting.
Keywords: climate models; probabilities; ensembles; statistics; higher-order evidence
Subjects: Specific Sciences > Climate Science and Meteorology
General Issues > Confirmation/Induction
Specific Sciences > Probability/Statistics
Depositing User: Dr. Corey Dethier
Date Deposited: 05 Feb 2022 00:58
Last Modified: 05 Feb 2022 00:58
Item ID: 20172
Subjects: Specific Sciences > Climate Science and Meteorology
General Issues > Confirmation/Induction
Specific Sciences > Probability/Statistics
Date: 2022
URI: https://philsci-archive.pitt.edu/id/eprint/20172

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