When is an ensemble like a sample? “Model-based” inferences in climate modeling.
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 l...
| Publicado en: | Synthese Vol. 200; no. 1; pp. 1 - 21 |
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| Autor principal: | |
| Formato: | Artículo |
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Springer Nature
Feb2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=155534498&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 155534498 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00397857 4LI jtl: Synthese issn: 00397857 maglogo: N pubinfo: dt: Feb2022 vid: 200 iid: 1 pid: 237 pub: Springer Nature artinfo: ui: 155534498 10.1007/s11229-022-03477-5 ppf: 1 ppct: 20 formats: fmt: – @attributes: type: T – @attributes: type: P size: 347KB tig: atl: When is an ensemble like a sample? “Model-based” inferences in climate modeling. aug: au: Dethier, Corey affil: Leibniz Universitȧt Hannover, Hannover, Germany sug: keyword: Climate models Ensemble methods Model-based Statistics ab: 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. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Synthese is a copyright of Springer, 2022. All Rights Reserved. item: Synthese holder: Springer Nature dt: @attributes: year: 2022 holdings: @attributes: islocal: N |
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