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

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 Holocene 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 behavior, and in some cases—such as the Younger Dryas—variance decreases rather than increases prior to the transition. We also perform a state-based statistical comparison of distributional shifts, finding a significant change only for the Younger Dryas event. 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.