Arctic Winter Sea Ice Loss May Be Underestimated, New Study Reveals

Ancient climate data from warmer periods helps researchers refine climate models and project future ice cover with greater accuracy.

Generic image of abstract swirling blue and white patterns representing shrinking sea ice, with soft diffused light.
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Generic image of abstract swirling blue and white patterns representing shrinking sea ice, with soft diffused light.

Researchers from the University of Cambridge and CIMAT have improved climate models, suggesting Arctic winter sea ice could shrink by around one million square kilometres more than previously thought.

New findings, reported in the journal Nature Geoscience, indicate that future Arctic winter sea ice extent may be significantly underestimated. This is based on improved climate models that incorporate clues from a warm period approximately 6,000 years ago.
While summer sea ice retreat has been widely documented, winter sea ice loss has received less attention, despite its crucial role in regulating weather patterns beyond the Arctic. The loss of winter ice has been linked to colder winters and heavier snowfall in regions including the UK and North America. In March 2025, the Arctic recorded its lowest maximum sea ice extent since modern measurements began, a record that was tied again this year.
A collaborative effort between the University of Cambridge and the Centro de Investigación en Matemáticas (CIMAT) in Mexico compiled the largest-ever database of a key biomarker, IP25, produced by algae living in sea ice. Samples from mid-Holocene ocean sediment cores, a period of reduced Arctic sea ice due to orbital shifts, were analysed.
By measuring IP25 levels alongside biomarkers from open-water organisms, scientists estimated ancient sea ice cover. These historical measurements were then compared to 27 climate model simulations of the same period. Using Bayesian weighting, models were weighted based on their accuracy in reproducing ancient conditions. These weights were then applied to simulations of the recent past and future.
Lead author Crystal Fu, from Cambridge’s Scott Polar Research Institute, stated that applying the model weights eliminated a positive bias in historical simulations. "The future projections similarly end up being lower than previous estimates, by about a million square kilometres," she said.
The approach, which uses palaeoclimate data to inform future predictions, helped reduce the range of uncertainty in projections by up to 85%. "By using evidence from the past, we can now produce more reliable maps of where Arctic winter sea ice is likely to disappear," said co-author Marco Aquino-López of CIMAT. "These give us a much clearer picture of what the Arctic might look like in the coming decades, and how much uncertainty remains."
Fu noted that while the mid-Holocene warming had different causes than today's, sea ice responds similarly regardless of the warming trigger. "It doesn’t matter if the warming is natural variation or caused by human activity: if it warms, sea ice is going to melt," she explained.
The research also hinted at potentially larger knock-on effects. Revised climate model weights applied to precipitation projections suggest that snowfall over southeast Greenland and rainfall in the Mediterranean may also be underestimated, with implications for the Greenland ice sheet's stability and future flood risk in southern Europe.
The study received support from the US National Science Foundation and the Cambridge Trust. Crystal Fu is a Member of Girton College, Cambridge.
Based on information from the official source: University of Cambridge (16/10/2026)