Are All Tipping Points Predictable? A Test of Early Warning Signal Theory on Three Distinct Holocene Climate Events

Gururaj H C, Nithya A S, Vasudha Hegde

The detection of Early Warning Signals (EWS) in noisy paleoclimate time series is a significant analytical challenge. Previous studies have often focused on individual events or single metrics, leaving the broader robustness and universality of the EWS framework unresolved.

In this study, we apply a comprehensive analytical pipeline to a δ¹⁸O proxy record from the NGRIP ice core, testing for EWS preceding three distinct climate transitions: the Younger Dryas termination, the 8.2k event, and the onset of the Holocene Thermal Maximum. Our approach includes a parameter sweep across four detrending methods and six window sizes, with statistical significance assessed using phase-randomized surrogate data.

We find that rising lag-1 autocorrelation (a signature of critical slowing down) shows a consistent positive trend before all three transitions and is robust to methodological choices in two of the three cases. In contrast, variance-based signals exhibit context-dependent behaviour, and in some cases such as the Younger Dryas, variance initially rises but then decreases markedly during the transition itself, producing a 'pre-rise followed by collapse' pattern rather than a monotonic increase. We also perform a state-based statistical comparison of distributional shifts, finding the strongest distributional shift for the Younger Dryas event, though this did not survive bootstrapped significance testing.

These results provide empirical support for the partial predictability of past climate tipping points. They also establish a multi-metric, statistically validated blueprint for future EWS detection studies using paleoclimate proxies.