This project asks: what might we learn from today’s climate models? This is a tremendously important question for the social science of climate change. The evidence produced by complex computer simulation models has the capacity to make or break social scientific analysis, as well as the use of such information in decision-making by governments, businesses and households. The hope is that adaptation planning will be informed by these predictions. Where does the balance lie? The project is divided into two sections: i) Interpreting climate models: climate science (L.A.Smith and Piers Forster) This draws on computer science, physics and statistics to understand in detail the uncertainties in state-of-the-art climate models. ii) Interpreting climate models (N. Cartright) This applies the philosophy of science and the philosophy of social science to climate change modelling. It aims to understand and clarify the standards of evidence provided by climate models, linked to economic models, and to articulate the philosophical assumptions behind the predictive expectations projected on to these models. No data was generated in this project but secondary data was used.

This data collection consists solely of a ReadMe file describing the project and the secondary data used. The research produced publications that can be placed into three categories. i) Research of a philosophical nature or perspective pieces that reflect on the procedures used in climate science and their relevance for policy. ii) Research which uses simple nonlinear or statistical models to understand issues in climate model interpretation. iii) Research which involves analysis of the output of large ensembles of climate models which has been generated by other projects; often international projects.