Climate models and robustness analysis – part II:the justificatory challenge

Robustness analysis (RA) is the prescription to consider a diverse range of evidence and only regard a hypothesis as well-supported if all the evidence agrees on it. In contexts like climate science, the evidence in support of a hypothesis often comes from scientific models. This leads to model-based RA (MBRA), whose core notion is that a hypothesis ought to be regarded as well-supported on grounds that a sufficiently diverse set of models agrees on the hypothesis. This chapter, which is the second part of a two-part review of MBRA, addresses the thorny issue of justifying the inferential steps taking us from the premises to the conclusions. We begin by making explicit what exactly the problem is. We then turn to a discussion of two broad families of justificatory strategies, namely top-down and bottom-up justifications. In the latter group we distinguish between the likelihood approach, independence approaches, and the explanatory approach. This discussion leads us to the sober conclusion that multi-model situations raise issues that are not yet fully understood and that the methods and approaches that MBRA has not yet reached a stage of maturity. Important questions remain open, and these will have to be addressed in future research.