A new artificial intelligence (AI) tool has been developed to enable more accurate prediction of Arctic sea ice conditions months into the future. Led by the British Antarctic Survey (BAS) and the Alan Turing Institute, the research team believes its improved forecasts could underpin new systems to protect Arctic wildlife and coastal communities from the impacts of sea ice loss. The paper has been published in Nature Communications. Sea ice that appears at the North and South poles is difficult to forecast due to its complex relationship with the atmosphere and the ocean below it. The summer Arctic sea ice area has halved over the past four decades due to its sensitivity to increasing temperatures caused by global warming.

A new AI (artificial intelligence) tool is set to enable scientists to more accurately forecast Arctic sea ice conditions months into the future. The improved predictions could underpin new early-warning systems that protect Arctic wildlife and coastal communities from the impacts of sea ice loss. Published this week in the journal Nature Communications, an international team of researchers led by British Antarctic Survey (BAS) and The Alan Turing Institute describe how the AI system, IceNet, addresses the challenge of producing accurate Arctic sea ice forecasts for the season ahead--something that has eluded scientists for decades. Sea ice, a vast layer of frozen sea water that appears at the North and South poles, is notoriously difficult to forecast because of its complex relationship with the atmosphere above and ocean below. The sensitivity of sea ice to increasing temperatures has caused the summer Arctic sea ice area to halve over the past four decades, equivalent to the loss of an area around 25 times the size of Great Britain.

A new artificial intelligence (AI) system is about to be used to predict ice loss in the Arctic, a study reveals. The deep learning tool, called IceNet was created by scientists at the British Antarctic Survey (BAS) and has been trained with the past four decades of satellite data from the region. It's almost 95 per cent accurate in predicting whether sea ice will be present two months ahead – better than the leading physics-based model previously used by BAS – but it's been trained to predict as far as six months ahead. Sea ice in both the north and south poles naturally expands in the winter and shrinks in the summer. But sea ice is very hard to predict because it has'very complex interactions' with the atmosphere above and the ocean below.