Since satellites first measured Arctic sea ice in the 1980s, scientists have noticed a sharp decline in its extent due to global warming. The trend is clear: summer Arctic sea ice is now declining at a rate of 13% per decade, but our picture of how much sea ice cover is shrinking is not yet complete.
So far, satellites have only been able to measure the thickness of Arctic sea ice between October and April. That’s because in the summer, meltwater pools that form on the ice confuse satellites — they can’t tell what’s ocean and what’s meltpool.
However, that deficiency recently changed when researchers reported they found a way around the problem by training artificial intelligence (AI) to distinguish between ocean and melted ice. Their new method, a machine learning technique, is described in Naturecould improve shipping safety and predictions of when the Arctic will see its first ice-free summer.
New AI method
Scientists have traditionally estimated sea ice thickness in summer using buoys and specially equipped aircraft. However, satellite measurements are far more accurate and holistic than these methods.
“A lot happens in the arctic summer – and fast. With thickness measurements throughout the summer, we can finally begin to understand ice melting processes.”
Jack Landy, Associate Professor of Earth Observation at the University of Tromsø – The Arctic University of Norway, led the new research. “It was a high-risk project,” said Landy, who has been developing the project for 5 years. “Sometimes we didn’t know if it was possible.”
Landy and his team applied a machine learning technique to satellite data from the European Space Agency’s CryoSat-2 mission. They also built a model of the satellite’s radar system to verify that CryoSat-2 is accurately measuring ice thickness. The model would allow them to make adjustments if necessary.
The hard work of Landy and his nearly a dozen employees has paid off, he said: “A lot happens in the arctic summer – and fast. With thickness measurements throughout the summer, we can finally begin to understand ice melting processes.”
Improved sea ice forecasts
The new summer dataset brings clear benefits to shipping, Landy said. A key observation was that early summer sea ice thickness was a good predictor of ice extent at its minimum in September. This correlation stems from the simple fact that thinner sea ice is more likely to melt and break up – a pattern observed in previous modeling studies but lacking supporting observational data from satellites.
“Communities depend on thick summer ice for transportation, but it’s not reliable when it’s thinning. We sounded the alarm, but without satellite observations to back it up, it was never taken seriously.”
Reviewing the relationship between sea ice in late spring and early fall, Landy explained, could improve the accuracy of sea ice forecasts for shipping. For example, the Norwegian Meteorological Institute currently issues sea ice forecasts, but due to data availability, the entire Arctic is not included in the reports.
The new study could also pave the way for improved long-term climate projections. “Improved thickness estimates will help us better quantify how quickly we might see the transition to ice-free summers in the Arctic,” said study co-author Julienne Stroeve, Professor of Polar Observations at University College London.
The new work supports many climate model predictions, said Cecilia Bitz, a professor of atmospheric sciences at the University of Washington, who was not involved with the study. “This shows that we’re on the right track – the patterns we’ve observed in our models are real.”
In addition to shipping and science, the new data is also valuable for communities in the Arctic. “Municipalities depend on thick summer ice for transportation,” Bitz said, “but it’s not reliable when it’s thinning. We sounded the alarm, but without satellite observations to back it up, it was never taken seriously.”
satellite collaborations
“The thickness of summer Arctic sea ice is one of the biggest unknowns in my research area,” said Rachel Tilling, a sea ice scientist at the University of Maryland and NASA’s Goddard Space Flight Center, who was not involved in the study.
Tilling said the new method is a key development for scientists studying trends in sea ice change.
Tilling works on NASA’s ICESat-2 satellite mission, but previously studied CryoSat-2 data for her PhD. The two missions use the same altimeter-based principle to measure ice thickness, but CryoSat-2 looks for reflections of radar pulses off the ice surface, while ICESat-2 sends laser pulses downward.
“The resolution of ICESat-2 means we can see individual melt pools, so we’re doing a lot of work to understand how [the ponds] affect our signal and make our summer sea ice thick [measurements] as accurate as possible,” said Tilling. “Both missions complement each other – there are many exciting opportunities for cooperation.”
—Erin Martin Jones (@Erin_M_J), science writer
Citation: Martin-Jones, E. (2022), Satellites Get First Year-Round View of Arctic Sea Ice Thickness, Eos, 103, https://doi.org/10.1029/2022EO220501. Released October 20, 2022.
Text © 2022. The Authors. CC BY-NC-ND 3.0
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