As Arctic Sea Ice Breaks Up, AI Is Starting to Predict Where the Ice Will Go

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As Arctic Sea Ice Breaks Up, AI Is Starting to Predict Where the Ice Will Go
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Sea ice is changing fast. Are forecasts, created by artificial intelligence, the best way to keep up with the pace of a warming climate in the far north?

Sea ice is changing fast. Are forecasts, created by artificial intelligence, the best way to keep up with the pace of a warming climate in the far north?In October 2019 an international team of scientists onboard an icebreaker intentionally let Arctic Sea ice freeze up around the ship. They wante d to learn more about the ice itself. But in April 2020, just halfway through the year-long experiment, it was unclear if that ice would stay frozen for the remaining six months of the project.

By the year 2050, the Arctic could be ice-free in the summer months. And shipping traffic in the region is on the rise, but predicting sea ice extent is complicated. Today we’re looking at how machine learning—artificial intelligence—could become the tool of the future for sea ice forecasting. When you take two water molecules, and you freeze them together, you know, like, right, this is how they freeze together. But there’s a lot of assumptions in that. And when you extrapolate to the ocean, there’s a lot of error.... And statistical modeling is based on, like, historical things of what’s happened.

According to the Arctic Council, marine traffic increased by 44 percent through the Northwest Passage between 2013 and 2019. Search-and-rescue capabilities in the region are limited, and there has been increased attention on the region for its vast natural resource development potential. Leslie says AI can create a forecast on a smaller scale, homing in on specific locations and timing to benefit those user groups.

Sometimes, she says, AI happens upon the right answer but for the wrong reasons. That’s why Marika at the National Center for Atmospheric Research says the most effective sea ice forecasts are likely to come from combining both machine learning and five decades’ worth of physics and statistical modeling.If machine learning can help to improve those physics-based models, that’s wonderful.

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