  Critical transitions, ubiquitous in nature and technology, necessitate
anticipation to avert adverse outcomes. While many studies focus on
bifurcation-induced tipping, where a control parameter change leads to
destabilization, alternative scenarios are conceivable, e.g. noise-induced
tipping by an increasing noise level in a multi-stable system. Although the
generating mechanisms can be different, the observed time series can exhibit
similar characteristics. Therefore, we propose a Bayesian Langevin approach,
implemented in an open-source tool, which is capable of quantifying both
deterministic and intrinsic stochastic dynamics simultaneously. After a
detailed proof of concept, we analyse two bus voltage frequency time series of
the historic North America Western Interconnection blackout on 10th August
1996. Our results unveil the intricate interplay of changing resilience and
noise influence. A comparison with the blackout's timeline supports our
frequency dynamics' Langevin model, with the BL-estimation indicating a
permanent grid state change already two minutes before the officially defined
triggering event. A tree-related high impedance fault or sudden load increases
may serve as earlier triggers during this event, as suggested by our findings.
This study underscores the importance of distinguishing destabilizing factors
for a reliable anticipation of critical transitions, offering a tool for better
understanding such events across various disciplines.
