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Thursday, December 2, 2021

As the Arctic warms, artificial intelligence predicts changes in sea ice




For generations, The inhabitants of the Arctic rely on seasonal sea ice, which grows and recedes throughout the year. Polar bears and marine mammals rely on it as a hunting place and resting place; indigenous people fish from openings on the ice known as the glacial lake and use the famous route through the ice to travel from one place to another. But according to a report in May 2021, since 1971, the Arctic air and water have warmed three times faster than the rest of the planet. Arctic Council report, And this warming is causing ice to expand and contract in unpredictable ways.

Some scientists and research companies are now deploying artificial intelligence-driven tools to more accurately and timely predict which parts of the Arctic Ocean will be covered by ice, and when. Artificial intelligence algorithms complement existing models that use physics to understand what is happening on the surface of the ocean, which is a dynamic region where cold underwater ocean currents meet strong winds to form floating ice rafts. For tribal members in the Arctic, commercial fishermen in Alaska and other places, and global shipping companies interested in taking shortcuts in open waters, this information is becoming more and more valuable.

Polarctic CEO Leslie Canavera (Leslie Canavera), a scientific consulting company headquartered in Lorton, Virginia, has developed artificial intelligence-based predictive models. He expressed the uncertainty about the speed of climate change. The existing sea ice models are becoming increasingly inaccurate. That’s because they are based on rapidly changing environmental processes.

“We don’t have a good understanding of climate change and what is happening on Earth. [Arctic] System,” said Canavera, who is a member of the Yup’ik tribe and grew up in Alaska. “We have statistical models, but then you will see more averages. Then you have artificial intelligence, which can see the trends in the system and learn. “

Existing physics-based models capture hundreds of years of scientific records on ice conditions, current weather conditions, the speed and position of polar jets, cloud cover, and ocean temperature. These models use this data to estimate future ice cover. But processing these numbers requires a lot of computing power, and it takes hours or days to generate forecasts using traditional programs.

Although artificial intelligence also requires complex data and a large amount of initial computing power, according to Data Thomas Anderson, once the algorithm is trained on the appropriate amount and type of data, it can detect weather conditions faster than physical-based models. model. A scientist from the British Antarctic Survey, he developed an artificial intelligence ice prediction called IceNet. “As we found in our model IceNet, the speed of artificial intelligence methods can be increased thousands of times,” Anderson said. “And they will learn automatically. Artificial intelligence is not smart. It will not replace physics-based models. I think these two sources of information are being used in the future.”

Anderson and his colleagues published their new sea ice prediction model in the journal in August Nature Communications. IceNet uses a form of artificial intelligence called deep learning (also used to automatically detect credit card fraud, operate self-driving cars, and run personal digital assistants) to train itself to provide six months of predictions in every 25-kilometer square This area is based on simulations of the Arctic climate from 1850 to 2100 and actual observational data recorded from 1979 to 2011.Once the model has been trained and given the current weather and ocean conditions, IceNet will make seasonal predictions of whether there is sea ice in each grid square, especially in summer, when sea ice undergoes annual retreat, according to nature Learn.





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