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  1. Climate Models: How to Assess Their Reliability.Martin Carrier & Johannes Lenhard - 2019 - International Studies in the Philosophy of Science 32 (2):81-100.
    The paper discusses modelling uncertainties in climate models and how they can be addressed based on physical principles as well as based on how the models perform in light of empirical data. We ar...
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  • Structural uncertainty through the lens of model building.Marina Baldissera Pacchetti - forthcoming - Synthese:1-17.
    An important epistemic issue in climate modelling concerns structural uncertainty: uncertainty about whether the mathematical structure of a model accurately represents its target. How does structural uncertainty affect our knowledge and predictions about the climate? How can we identify sources of structural uncertainty? Can we manage the effect of structural uncertainty on our knowledge claims? These are some of the questions that an epistemology of structural uncertainty faces, and these questions are also important for climate scientists and policymakers. I develop (...)
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  • The Argument From Surprise.Adrian Currie - 2018 - Canadian Journal of Philosophy 48 (5):639-661.
    I develop an account of productive surprise as an epistemic virtue of scientific investigations which does not turn on psychology alone. On my account, a scientific investigation is potentially productively surprising when results can conflict with epistemic expectations, those expectations pertain to a wide set of subjects. I argue that there are two sources of such surprise in science. One source, often identified with experiments, involves bringing our theoretical ideas in contact with new empirical observations. Another, often identified with simulations, (...)
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  • A Practical Philosophy of Complex Climate Modelling.Gavin A. Schmidt & Steven Sherwood - 2015 - European Journal for Philosophy of Science 5 (2):149-169.
    We give an overview of the practice of developing and using complex climate models, as seen from experiences in a major climate modelling center and through participation in the Coupled Model Intercomparison Project. We discuss the construction and calibration of models; their evaluation, especially through use of out-of-sample tests; and their exploitation in multi-model ensembles to identify biases and make predictions. We stress that adequacy or utility of climate models is best assessed via their skill against more naïve predictions. The (...)
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  • Introduction to Assessing Climate Models: Knowledge, Values and Policy.Joel Katzav & Wendy S. Parker - 2015 - European Journal for Philosophy of Science 5 (2):141-148.
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  • Calibration: Modelling the Measurement Process.Eran Tal - 2017 - Studies in History and Philosophy of Science Part A 65:33-45.
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  • Model-Selection Theory: The Need for a More Nuanced Picture of Use-Novelty and Double-Counting.Katie Steele & Charlotte Werndl - 2016 - British Journal for the Philosophy of Science:axw024.
    This article argues that common intuitions regarding (a) the specialness of ‘use-novel’ data for confirmation and (b) that this specialness implies the ‘no-double-counting rule’, which says that data used in ‘constructing’ (calibrating) a model cannot also play a role in confirming the model’s predictions, are too crude. The intuitions in question are pertinent in all the sciences, but we appeal to a climate science case study to illustrate what is at stake. Our strategy is to analyse the intuitive claims in (...)
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  • Computer Simulations and Experiments: The Case of the Higgs Boson.Michela Massimi & Wahid Bhimji - 2015 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 51:71-81.
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  • On Defining Climate and Climate Change.Charlotte Werndl - 2016 - British Journal for the Philosophy of Science 67 (2):337-364.
    The aim of the article is to provide a clear and thorough conceptual analysis of the main candidates for a definition of climate and climate change. Five desiderata on a definition of climate are presented: it should be empirically applicable; it should correctly classify different climates; it should not depend on our knowledge; it should be applicable to the past, present, and future; and it should be mathematically well-defined. Then five definitions are discussed: climate as distribution over time for constant (...)
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  • Predictivism and Old Evidence: A Critical Look at Climate Model Tuning.Mathias Frisch - 2015 - European Journal for Philosophy of Science 5 (2):171-190.
    Many climate scientists have made claims that may suggest that evidence used in tuning or calibrating a climate model cannot be used to evaluate the model. By contrast, the philosophers Katie Steele and Charlotte Werndl have argued that, at least within the context of Bayesian confirmation theory, tuning is simply an instance of hypothesis testing. In this paper I argue for a weak predictivism and in support of a nuanced reading of climate scientists’ concerns about tuning: there are cases, model-tuning (...)
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