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How AI can help forecast how much Arctic sea ice will shrink

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In the next week or so, the sea ice floating atop the Arctic Ocean will shrink to its smallest size this year, as summer-warmed waters eat away at the ice's submerged edges. Record lows for sea ice levels will probably not be broken this year, scientists say. In 2020, the ice covered 3.74 million square kilometers of the Arctic at its lowest point, coming nail-bitingly close to an all-time record low. Currently, sea ice is present in just under 5 million square kilometers of Arctic waters, putting it on track to become the 10th-lowest extent of sea ice in the area since satellite record keeping began in 1979. It's an unexpected finish considering that in early summer, sea ice hit a record low for that time of year. The surprise comes in part because the best current statistical- and physics-based forecasting tools can closely predict sea ice extent only a few weeks in advance, but the accuracy of long-range forecasts falters.


On Thin Ice: Arctic AI Model Predicts Sea Ice Loss

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Promising more accurate predictions in an era of rapid climate change, a new tool is harnessing deep learning to help better forecast Arctic sea ice conditions months into the future. As described in a paper published in the science journal Nature Communications Thursday, the new AI tool, dubbed IceNet, could lead to improved early-warning systems to protect Arctic wildlife and coastal communities. Created by an international team of researchers led by the British Antarctic Survey and the Alan Turing Institute, IceNet tackles a challenge that has long vexed scientists. "The Arctic is a region on the frontline of climate change and has seen substantial warming over the last 40 years," explained lead author Tom Andersson, a data scientist at the BAS AI Lab, in a statement. "IceNet has the potential to fill an urgent gap in forecasting sea ice for Arctic sustainability efforts and runs thousands of times faster than traditional methods," he added.


Novel AI tool to help predict Arctic sea ice loss

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Described in the journal Nature Communications, 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 researchers said. 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, they said. These accelerating changes, the researchers noted, have dramatic consequences for the world climate, for Arctic ecosystems, and Indigenous and local communities whose livelihoods are tied to the seasonal sea ice cycle. IceNet is almost 95 per cent accurate in predicting whether sea ice will be present two months ahead – better than the leading physics-based model, according to the researchers.


Artificial intelligence to help predict Arctic sea ice loss

#artificialintelligence

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.


Artificial intelligence to help predict Arctic sea ice loss

#artificialintelligence

Published this week (Thursday 26 August) 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. These accelerating changes have dramatic consequences for our climate, for Arctic ecosystems, and Indigenous and local communities whose livelihoods are tied to the seasonal sea ice cycle. IceNet, the AI predictive tool, is almost 95% accurate in predicting whether sea ice will be present two months ahead -- better than the leading physics-based model.