Abstract

Early warning signals (EWS) can in principle allow society to anticipate potentially devas-

tating and practically irreversible abrupt critical transitions in climate systems. Several

tipping elements of the climate systems such as the Amazon rainforest, the Greenland ice

sheet, and the Indian monsoon are already identified as being at risk of abruptly tipping

to undesirable states. However, there is no clear consensus on how to estimate EWS from

observed climatic time series. Moreover, in the context of paleoclimate, early warning

analyses that take dating uncertainties into account are rather uncommon. Here, we present

an overview of the state-of-the-art of EWS in climate systems and potential pitfalls of a

purely data-driven approach to estimate EWS. Last, we present two ways in which complex

networks can help to detect EWS in climate systems: one based on recurrence networks of

paleoclimate time series, and the other based on climate networks constructed from extreme

rainfall time series.