Projecting the Risk of Future Climate Regime Shifts

Research Phase

For the statistical work we will initially use sea surface temperature (SST) indices for two of the foremost D2M climate modes, the Atlantic multidecadal oscillation (AMO) and the Pacific decadal oscillation (PDO). The indices will be of two types: an annualized version based on 150 years of instrumental data (1856-2005); and annualized multi-century indices of the oscillations reconstructed from tree rings in North America and Europe, calibrated against the instrumental indices [17,18]. To discourage unwanted short-interval occurrences, the time series are first smoothed, the sample size is increased through Monte Carlo resampling methods [19], and the durations of positive and negative climate regimes are estimated by the intervals between successive zero crossings of the resampled series (Figure 2). The empirical distributions of sampled intervals are then fitted by a gamma probability density function (pdf) and a Kolmogorov-Smirnov test is used to determine the goodness of fit (Figure 3). The random resampling and fitting procedure is repeated many times to obtain stable means of the distribution parameters. Finally, the estimated distributions are used to determine the probability of future D2M regime shifts conditional on the time elapsed since the last shifts, and the parameter spreads are used to estimate the uncertainty of the probability projections.