Related Experiment Video
Updated: May 25, 2026

Using Generative Art to Convey Past and Future Climate Transitions
Published on: March 31, 2023
Early warning of climate tipping points from critical slowing down: comparing methods to improve robustness
T M Lenton1, V N Livina, V Dakos
1College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4PS, UK. t.m.lenton@exeter.ac.uk
None:
We address whether robust early warning signals can, in principle, be provided before a climate tipping point is reached, focusing on methods that seek to detect critical slowing down as a precursor of bifurcation. As a test bed, six previously analysed datasets are reconsidered, three palaeoclimate records approaching abrupt transitions at the end of the last ice age and three models of varying complexity forced through a collapse of the Atlantic thermohaline circulation. Approaches based on examining the lag-1 autocorrelation function or on detrended fluctuation analysis are applied together and compared. The effects of aggregating the data, detrending method, sliding window length and filtering bandwidth are examined. Robust indicators of critical slowing down are found prior to the abrupt warming event at the end of the Younger Dryas, but the indicators are less clear prior to the Bølling-Allerød warming, or glacial termination in Antarctica. Early warnings of thermohaline circulation collapse can be masked by inter-annual variability driven by atmospheric dynamics. However, rapidly decaying modes can be successfully filtered out by using a long bandwidth or by aggregating data. The two methods have complementary strengths and weaknesses and we recommend applying them together to improve the robustness of early warnings.
Related Concept Videos
Global Climate Change
What is Climate?
Precipitation Titration: Endpoint Detection Methods
In the Volhard method, a standard excess of AgNO3 is first added to the...
Microbes and Climate Change
Propagation of Uncertainty from Systematic Error
Design Example: Analyzing Capacity Contours for Flood Risk Assessment