Articles | Volume 16, issue 5
https://doi.org/10.5194/esd-16-1539-2025
https://doi.org/10.5194/esd-16-1539-2025
Research article
 | 
24 Sep 2025
Research article |  | 24 Sep 2025

Bayesian analysis of early warning signals using a time-dependent model

Eirik Myrvoll-Nilsen, Luc Hallali, and Martin Rypdal

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Short summary
Before a climate component reaches a tipping point, there may be observable changes in its statistical properties. These are known as early warning signals and include increased fluctuation and correlation times. We present a Bayesian approach to detect these signals, using a model where the correlation parameter depends linearly on time for which the slope can be estimated directly from the data. The model is then applied to Dansgaard–Oeschger events using Greenland ice core data.
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