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Projecting the risk of future climate shifts

Recent research has shown that decadal‐to‐multidecadal (D2M) climate variability is associated with environmental changes that have important consequences for human activities, such as public health, water availability, frequency of hurricanes, and so forth. As scientists, how do we convert these relationships into decision support products useful to water managers, insurance actuaries, and others, whose principal interest lies in knowing when future climate regime shifts will likely occur that affect long‐horizon decisions? Unfortunately, numerical models are far from being able to make deterministic predictions for future D2M climate shifts. However, the recent development of paleoclimate reconstructions of the Atlantic Multidecadal Oscillation (AMO) (Gray et al., 2004 ) and Pacific Decadal Oscillation (PDO); (MacDonald and Case, 2005 ) give us a viable alternative: to estimate probability distribution functions from long climate index series that allow us to calculate the probability of future D2M regime shifts. In this paper, we show how probabilistic projections can be developed for a specific climate mode—the AMO as represented by the Gray et al. ( 2004 ) tree‐ring reconstruction. The methods are robust and can be applied to any D2M climate mode for which a sufficiently long index series exists, as well as to the growing body of paleo‐proxy reconstructions that have become available. The target index need not be a paleo‐proxy calibrated against a climate index; it may profitably be calibrated against a specific resource of interest, such as stream flow or lake levels. Copyright © 2006 Royal Meteorological Society