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A discussion of the problem of double-counting in climate modeling, specifically when the same evidence is used to both calibrate a model and then confirm the adequacy of the results. Steele and Werndl turn to a Baysian approach to argue for a method of incremental confirmation, making double-counting unproblematic. For a response to this argument see Mathias Frisch’s 2015 paper “Predictivism and old evidence: a critical look at climate model tuning”.

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Cited by (7)

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  1. Climate Models: How to Assess Their Reliability. International Studies in the Philosophy of Science. 2019 Carrier, Martin, Lenhard, Johannes

    Confirmation & evaluation, Confirmational holism, Robustness

  2. Building confidence in climate model projections: an analysis of inferences from fit. WIREs Climate Change. 2017 Baumberger, Christoph, Knutti, Reto, Hirsch Hadorn, Gertrude

    Confirmation & evaluation, Robustness

  3. Philosophy of Climate Science Part II: Modelling Climate Change. Philosophy Compass. 2015 Frigg, Roman, Thompson, Erica, Werndl, Charlotte

  4. Introduction to Assessing climate models: knowledge, values and policy. European Journal for Philosophy of Science. 2015 Katzav, Joel, Parker, Wendy S.

    Confirmation & evaluation, Values

  5. Predictivism and old evidence: a critical look at climate model tuning. European Journal for Philosophy of Science. 2015 Frisch, Mathias

    Calibration/tuning, Confirmation & evaluation, Confirmational holism

  6. Predictivism and old evidence: a critical look at climate model tuning. European Journal for Philosophy of Science. 2015 Frisch, Mathias

    Calibration/tuning, Confirmation & evaluation

  7. A practical philosophy of complex climate modelling. European Journal for Philosophy of Science. 2014 Schmidt, Gavin A., Sherwood, Steven

    Calibration/tuning, Confirmation & evaluation