Slowing down as an early warning signal for abrupt climate change

Abstract

In the Earth's history, periods of relatively stable climate have often been interrupted by sharp transitions to a contrasting state. One explanation for such events of abrupt change is that they happened when the earth system reached a critical tipping point. However, this remains hard to prove for events in the remote past, and it is even more difficult to predict if and when we might reach a tipping point for abrupt climate change in the future. Here, we analyze eight ancient abrupt climate shifts and show that they were all preceded by a characteristic slowing down of the fluctuations starting well before the actual shift. Such slowing down, measured as increased autocorrelation, can be mathematically shown to be a hallmark of tipping points. Therefore, our results imply independent empirical evidence for the idea that past abrupt shifts were associated with the passing of critical thresholds. Because the mechanism causing slowing down is fundamentally inherent to tipping points, it follows that our way to detect slowing down might be used as a universal early warning signal for upcoming catastrophic change. Because tipping points in ecosystems and other complex systems are notoriously hard to predict in other ways, this is a promising perspective.

Fig. 1.

Eight reconstructed time series of abrupt climate shifts in the past. (A) The end of the greenhouse Earth, (M) the end of the Younger Dryas, (K) the Bølling-Alleröd transition, (O) the desertification of North Africa, (I) the end of the last glaciation, and (G, E, and F) the ends of earlier glaciations. In all cases the dynamics of the system slow down before the transition, as revealed by an increasing trend in autocorrelation (B, D, F, H, J, L, N, and P). The gray bands identify transition phases. The arrows mark the width of the moving window used to compute slowness. The smooth gray line through the time series is the Gaussian kernel function used to filter out slow trends. Data in A come from tropical Pacific sediment core records, data in M are from the Cariaco basin sediment, data in K come from the Greenland GISP2 ice core, data in O from the sediment core ODP Hole 658C off the west coast of Africa, and data presented in C, E, G, and I are from the Antarctica Vostok ice core (additional details are in supporting information (SI) Table S1 and Fig. S1).

Fig. 2.

Three simulated abrupt climate transitions. Transition to an icehouse Earth (A), collapse of the thermo-haline circulation (C), and desertification of North Africa (E) (see SI Text for details on simulations). As in the reconstructed real dynamics, the transition is preceded by slowing down as revealed by increased autocorrelation (B, D, and F). The gray bands identify the transition phases. The arrows mark the width of the sliding window used to compute slowness. The smooth gray line through the time series is the Gaussian kernel function used to filter out slow trends. All models pass a fold bifurcation F as a control parameter is slowly changing (relative radiation, freshwater forcing, and insolation, respectively). In the case of the ocean circulation and desertification model (C and E), there are also alternative attractors present implying hysteresis (dashed line), if the change in the control variable would be reversed on the shift. Points F₁ and F₂ are saddle-node bifurcation points.