Local Model-Data Symbiosis in Meteorology and Climate Science.
I introduce a distinction between general and local model-data symbiosis and offer three examples of local symbiosis in the fields of meteorology and climate science. Local model-data symbiosis refers to a beneficial, two-way interdependence between a particular model and data set or between closely...
| Publicado en: | Philosophy of Science Vol. 87; no. 5; pp. 807 - 819 |
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| Formato: | Artículo |
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Cambridge University Press
Dec2020
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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=147626967&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 147626967 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00318248 PSC jtl: Philosophy of Science issn: 00318248 maglogo: N pubinfo: dt: Dec2020 vid: 87 iid: 5 pid: 15979 pub: Cambridge University Press artinfo: ui: 147626967 10.1086/710621 ppf: 807 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P size: 735KB tig: atl: Local Model-Data Symbiosis in Meteorology and Climate Science. aug: au: Parker, Wendy su: Climatology Symbiosis Meteorology Data modeling sug: subj: Climatology Symbiosis Meteorology Data modeling ab: I introduce a distinction between general and local model-data symbiosis and offer three examples of local symbiosis in the fields of meteorology and climate science. Local model-data symbiosis refers to a beneficial, two-way interdependence between a particular model and data set or between closely related models and data sets. For each example presented here, I show how the symbiotic relationship works—what the interdependence consists in and how it is supposed to be beneficial—and I consider whether, alongside the benefits, there is some risk of problematic circularity. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y custom: Copyright of Philosophy of Science is the property of Cambridge University Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. item: Philosophy of Science holder: Cambridge University Press dt: @attributes: year: 2020 holdings: @attributes: islocal: N |
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