Articles | Volume 16, issue 5
https://doi.org/10.5194/esd-16-1539-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-16-1539-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Bayesian analysis of early warning signals using a time-dependent model
Eirik Myrvoll-Nilsen
CORRESPONDING AUTHOR
Department of Mathematics and Statistics, UiT The Arctic University of Norway, 9037 Tromsø, Norway
Luc Hallali
Department of Mathematics and Statistics, UiT The Arctic University of Norway, 9037 Tromsø, Norway
Martin Rypdal
Department of Mathematics and Statistics, UiT The Arctic University of Norway, 9037 Tromsø, Norway
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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.
Before a climate component reaches a tipping point, there may be observable changes in its...
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