1.6.2 Case studies of empirically measured EWS

The EWS proposed above have been searched for in a number of real-world cases, using data from sources ranging from remotely sensed products from satellites to growth layers in marine bivalve shells. 

A systematic review of academic papers that mention phrases associated with ‘early warning’ and ‘tipping point’, which we further filter based on using empirical data only, yields 229 studies, of which 33 are associated with the climate (Dakos et al., 2023); 22 of these climate studies find positive EWS, 1 negative, 9 mixed (from calculating EWS on different records and having conflicting results) and 1 inconclusive. These climate studies are further subsetted into palaeoclimate (12 total, 9 positive, 1 mixed, 1 negative), cryosphere (6 total, 3 positive, 2 mixed, 1 inconclusive), weather (3 total, 2 positive, 1 mixed), and modern climate, including AMOC collapse, El Niño, and monsoons, etc (12 total, 8 positive, 4 mixed). Overall, the most commonly used EWS are temporal AR(1) (17) and temporal variance (17 also, 13 of these using both together). Further details can be found in Dakos et al. (2023), and discussion of EWS beyond climate and ecological systems in Box 1.6.1.

Figure 1.6.3 below shows which climate systems have had studies searching for EWS of potential tipping points using empirical data. Below we detail some of these case studies specifically. We discuss where models suggest we may see EWS of climate tipping points and cases where empirical data has shown a loss of resilience in these systems. However, not all potential tipping points in the climate system have shown EWS in empirical data. In many cases this is due to observations being unavailable or the records being too short to see a significant movement towards tipping using EWS.

Figure: 1.6.3
Figure 1.6.3: Map of studies that use empirical data to look for early warning signals (EWS) of tipping points in climate systems, and if they found evidence of EWS (red circles), no evidence (blue circles), or the evidence was unclear (grey circles). Specifically, these studies use real-world observations rather than being restricted to modelling studies.
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