ArticleScience advances2024
Uncertainties too large to predict tipping times of major Earth system components from historical data.
Article in Science advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Reversible Atlantic overturning despite continued Greenland ice sheet melt.Science advances · 2026Article
- Data gaps and outliers distort critical-slowing-down-based resilience indicators.Science advances · 2026Article
- Recent and early 20th century destabilization of the subpolar North Atlantic recorded in bivalves.Science advances · 2025Article
- Non-linear dynamical approaches for characterizing multi-sector climate impacts under irreducible uncertainty.NPJ climate and atmospheric science · 2025Review
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
One way to warn of forthcoming critical transitions in Earth system components is using observations to detect declining system stability. It has also been suggested to extrapolate such stability changes into the future and predict tipping times. Here, we argue that the involved uncertainties are too high to robustly predict tipping times. We raise concerns regarding (i) the modeling assumptions underlying any extrapolation of historical results into the future, (ii) the representativeness of individual Earth system component time series, and (iii) the impact of uncertainties and preprocessing of used observational datasets, with focus on nonstationary observational coverage and gap filling. We explore these uncertainties in general and specifically for the example of the Atlantic Meridional Overturning Circulation. We argue that even under the assumption that a given Earth system component has an approaching tipping point, the uncertainties are too large to reliably estimate tipping times by extrapolating historical information.
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Registered trials
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