This is a guest post by Nic Lewis.
In July 2004 the IPCC held a Working Group 1 (WG1) Workshop on climate sensitivity, as part of the work plan leading up to AR4. In one session, Myles Allen of Oxford university and a researcher in his group, David Frame, jointly gave a presentation entitled “Observational constraints and prior assumptions on climate sensitivity”. They developed the work presented into what became an influential paper, Frame et al 2005,[i] here, with Frame as lead author and Allen as senior author.
Frame and Allen pointed out that climate sensitivity studies could be – whether or not they explicitly were – couched in a Bayesian formulation. That formulation applies Bayes’ theorem to produce a posterior probability density function (PDF), from which best estimates and uncertainty ranges are derived. The posterior PDF represents, at each value for climate sensitivity (ECS), and of any other parameters (fixed but uncertain variables) being estimated, the product of the likelihood of the observations at that value and the “prior” for the uncertain parameters that is also required in Bayes’ theorem. Continue reading