This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: Future Arctic winter sea ice is likely to shrink by around 1 million square kilometers (386,000 square miles) more than previously thought, after researchers used clues from a warm period 6,000 years ago to improve the reliability of climate models. The results, reported in the journal Nature Geoscience, could have implications for future winter conditions in the U.K. and across Europe.
The retreat of Arctic sea ice in the summer months has been widely reported. However, the loss of winter sea ice has received far less attention, despite the fact that climate models disagree with each other most during the winter months. Winter ice cover plays an outsize role in weather patterns beyond the Arctic, as it regulates the release of heat and moisture to the atmosphere.
Its loss has been linked to colder winters and heavier snowfall in the U.K., the rest of northern Europe and North America. In March 2025, the Arctic recorded its lowest maximum sea ice extent since modern measurements began. That record was tied again this year.
Now, researchers from the University of Cambridge and the Centro de Investigación en Matematicas in Mexico (CIMAT) have compiled the largest-ever database of a key biomarker produced by algae living in sea ice to improve winter sea ice projections. The samples were taken from ocean sediment cores dating from the mid-Holocene period, when subtle shifts in the Earth's orbit contributed to warmer conditions and reduced sea ice cover in the Arctic, offering clues into how the region might respond to future warming. By measuring levels of the biomarker, called IP₂₅, alongside complementary biomarkers from organisms that live in open water, the researchers were able to estimate the extent of sea ice cover thousands of years ago.
These ancient measurements were then compared to simulations from 27 climate models of the same period. Using a type of statistical analysis called Bayesian weighting, the researchers gave different weights to models based on how well they reproduced the ancient sea ice conditions. Because the same physical processes govern sea ice across different climates, these model weights could then be applied to simulations of the recent past and future.
Taken together, the models overpredicted how much winter sea ice there should be. "When we apply the model weights to historical simulations, we completely eliminate the positive bias," said lead author Crystal Fu, from Cambridge's Scott Polar Research Institute. "The future projections similarly end up being lower than previous estimates, by about a million square kilometers (386,000 square miles)." Using past climate data, known as paleoclimate data, to make predictions about the future is challenging.
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