Climate prediction: an evidence-based perspective

This paper considers climate prediction from the perspective of the experimental, physical sciences, and discusses three ways in which the two differ. First, the construction of long-term climate series requires benchmark measurements, i.e., measurements calibrated in situ against international standards. An instrument capable of accurate, benchmark measurements of thermal, spectral radiances from space is available but has yet to be used. Second, objective criteria are needed to evaluate measurements for the purpose of improving climate predictions. Techniques based on Bayesian inference are now available. Third is the question of how to use suitable data to improve a climate prediction, when they are available. A method based on the Bayesian Evidence Function is, in principle, available, but has yet to be exploited. None of these three aspects are considered in current operational climate forecasting. All three are potentially capable of improving forecasts, and all are subjects of current research programs, with the likelihood of their eventual adoption.