Goodwin, William M. 2015. “Global Climate Modeling as Applied Science,” Journal for General Philosophy of Science. An incisive paper that argues for a “relative strategy” for securing the epistemic reliability of climate models. The strategy is to try to show that they are epistemically on a par with other scientific techniques that have not been called into question.Google Scholar

Mauritsen, Thorsten et al. 2012. “Tuning the Climate of a Global Model,” Journal of Advances in Modeling Earth Systems. An indispensable resource for understanding the practice of tuning in climate modeling.Google Scholar

Barnes, Eric Christian. 2008. The Paradox of Predictivism, Cambridge University Press. An excellent monograph on the topic of predictivism – the thesis that predicting evidence is more confirmatory than accommodating it.Google Scholar

Schmidt, Gavin A. and Sherwood., Steven 2015. “A Practical Philosophy of Complex Climate Modelling,” European Journal for Philosophy of Science. A very nice philosophy paper by two climate scientists. Offers the climate scientist’s take on two of the philosophical topics we have discussed in the book: values in science and the issue of “double counting” old evidence.Google Scholar

Steele, Katie and Werndl., Charlotte 2013. “Climate Models, Calibration, and Confirmation,” The British Journal for the Philosophy of Science. Argues that climate scientists are confused about the issue of double counting old evidence by appealing to the Bayesian framework of confirmation theory.Google Scholar

Frisch, Mathias. 2015. “Predictivism and Old Evidence: A Critical Look at Climate Model Tuning,” European Journal for Philosophy of Science. A response to Steele and Werndl, above. Argues that the Bayesian framework itself is fundamentally silent on the question of how to deal with old evidence and that there are features of climate models that make using old evidence for confirmation especially problematic.CrossRefGoogle Scholar