Satellites can now measure the thickness of the sea ice that covers the Arctic Ocean all year round.
Traditionally, spacecraft have struggled to determine the complete state of the shoals in the summer months because the presence of surface meltwater confused their instruments.
But by using new “deep learning” techniques, scientists have overcome this limitation to obtain reliable observations in all seasons.
The breakthrough has far-reaching implications.
Aside from the obvious benefit to ships, which need to know those parts of the Arctic that will be safe to navigate, there are significant benefits to climate and weather forecasting.
At present, there is considerable variation in projections for when the polar ocean could be totally ice-free in an increasingly warm world.
Having a better view of the casting processes in those key months when the banks are reduced in area and thickness should now improve the output of the computer models.
“Despite the excellent efforts of many researchers, these climate models’ predictions of when we will see the first completely ice-free Arctic Ocean in the summer – vary by over 30 years,” said Dr. Jack Landy, of UiT The Arctic University of Norway, told BBC News.
“We need to strengthen these predictions, so we are much more confident about what will happen and when, and how climate feedback will accelerate as a result.”
The extent of Arctic sea ice coverage has been on the decline for the entire period that satellites have monitored it, which is over 40 years, a reduction that is occurring at an average rate of 13% per decade.
But it’s only since 2011 that spacecraft have been able to consistently measure their thickness – and thickness (or more properly, volume) is the true measure of reef health.
This is because the extent of sea ice cover strongly depends on whether winds have widened the shoals or pushed them together.
To measure thickness, scientists use satellite altimeters.
The European Space Agency’s (ESA) pioneering Cryosat-2 mission carries a radar to measure the difference in height between the top of sea ice and the top of the water in the cracks, or cables, that separate the shoals.
From this difference, scientists can then, with a relatively simple calculation, calculate the thickness of the ice.
The approach works well in the winter months, but in the summer, when the snow on top of the ice and the ice itself begin to melt, the accumulation of water effectively dazzles the radar. Scientists can’t be sure whether the echo signal returning to Cryosat comes from the open ocean or from the surface of a molten pond on ice.
May to September – the key melt season – was a blind period for the spacecraft.
To solve the problem, the researchers used an artificial intelligence (AI) technique in which an algorithm was able to learn and identify reliable observations from a large library of synthetic radar signals.
The teacher. Julienne Stroeve, of University College London (UCL), explained: “We simulated what echo shapes we would get for different types of ice surfaces, regardless of whether they had melting ponds, whether they were flooded ice or ice of different asperities; or simply leads. We created this huge database of physics-based estimates of what radar return should look like, and then matched them to individual radar pulses from the instrument to find the echoes that matched the better”.
Esa has kept all Cryosat measurements from May to September in its data archives, even if they have been almost useless in the last decade. But now, thanks to this new approach, Dr. Landy’s team has been able to go back through records to retrieve ice thickness measurements for the entire year for as long as the satellite has been operational.
Dr. Rachel Tilling worked extensively with Cryosat data before transferring her studies to the recently launched Icesat-2 laser altimeter mission by the US space agency.
He applauded the innovation.
“Summer is when the extent of sea ice in the Arctic is seeing its fastest decline and having this extra dimension will help us understand more about how the ice pack is changing,” the NASA scientist told BBC News. .
“Icesat-2 has its unique challenges in the summer, but we are fortunate that its photon counting technology allows us to measure the height of sea ice, water and melt ponds all year round.
“That said, Cryosat-2 will always be my first love, so I’m really excited to see it used in this new way.”
One of the main beneficiaries of the new thickness measurements would be Inuit populations in the Arctic, said Dr Michel Tsamados, also from UCL.
“[They] have identified sea ice roughness and slush (melted snow and ice) as the key impediment to safe ice travel with climate change already negatively affecting these characteristics and causing an increase in travel and research accidents and relief efforts, “he explained.
“Both are related to ice thickness. Therefore, measuring the thickness of sea ice from space from Cryosat-2 throughout the year, but also Icesat-2 and other satellite sensors will ultimately help provide better maps to Inuit populations for safety. travel on this rapidly changing terrain “.
Dr Landy and colleague published their new Cryosat approach in the journal Nature.
How satellites measure the thickness of sea ice from orbit
Cryosat’s radar has the resolution to see the “reefs” and “offshoots” of the Arctic
Some 8/9 of the ice tends to stay below the waterline – the draft
The radar detects the height of the freeboard, the ice above the waterline
Knowing this 1/9 figure allows Cryosat to calculate the thickness of the sea ice
The thickness multiplied by the area of the ice cover produces a volume
Icesat-2 does exactly the same as Cryosat but with a laser tool
The biggest uncertainty for both is the snow cover on the ice