ArticleScience advances2025
Lessened projections of Arctic warming and wetting after correcting for model errors in global warming and sea ice cover.
Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Role of Atlantic multidecadal variability in modulating Arctic sea ice loss and wetting.Science advances · 2026Article
- Machine learning helps to strongly reduce future warming uncertainty.Nature communications · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Credible projections of Arctic warming and wetting (AWW) are essential for informed decision-making in a changing climate. However, current AWW projections from state-of-the-art climate models carry uncertainties. Using observational datasets and CMIP6 model simulations, we demonstrate that the observed historical global warming trend and the climatological mean pattern of Arctic sea ice can serve as effective constraints on AWW projections. Under SSP2-4.5, the constrained warming by the end of the century is reduced from 5.5° to 4.6°C. Similarly, the projected wetting decreases from 6.8 to 5.7 millimeter per month. The inter-model spread in warming and wetting is reduced by 25 and 15%, respectively. The reduction is the largest in the Barents-Kara seas, reducing warming by 1.2°C, lessening wetting by 1.7 millimeter per month, and decreasing the inter-model spread by one-third. Our findings suggest that unconstrained CMIP6 projections overestimate future AWW, particularly in the Barents-Kara seas, due to an overestimation of historical global warming and excessive sea ice in the models.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.