Simulation vs. Note on Arctic Ice Melting | News Releases


Per Sonia Fernandez by UCSB | November 18, 2018 | 9:00 in the morning.

As an indicator of the impacts of climate change, Arctic sea ice is hard to beat. Scientists have observed the advance of the frozen polar ocean and have receded in this most sensitive region of the Earth over decades for insights into the possible effects of ripples on varied natural systems: global ocean circulation, surrounding habitats and ecosystems, food sources, sea levels and much more.

Despite efforts to make model simulations closer to the actual observations of the Arctic ice melt, a breach has opened: reports indicate that ice is melting at a much faster rate than predicted by global climate models.

"Based on this phenomenon, people have different opinions," said UCSB climate scientist Qinghua Ding, an assistant professor at the campus's Earth Research Institute.

The consensus of the climate science community, he said, is tilted to the idea that the discrepancy is due to defective modeling. "It's something like the model has some bias, it has some low sensitivity to anthropogenic stress," he said.

Ding and his group disagree. In a study titled "Fingerprints of Internal Engines of Arctic Sea Ice Loss in Model Observations and Simulations," published in the journal Nature Geoscience, the group says the models are well.

About 40% to 50% of the loss of sea ice in the last three decades, they say, is attributable to significant, but still poorly understood, internal factors – among them, the effects that originate partially into the tropics.

"Actually, we're comparing apples to oranges," Ding said of the discrepancy between real-time observation and simulated Arctic ice driven by anthropogenic forces.

The average model, he explained, explains only what effects are the result of the historical radiative forcing – calculations based primarily on greenhouse gas levels – but do not depend, for example, on short-term variations in sea surface temperatures, humidity , atmospheric pressure and other local factors and connected to other phenomena in other parts of the Earth.

Such higher frequency events often appear as noise in repeated individual executions of the simulations, as scientists look for general, long-term trends.

"Any execution of a model will have random noises," said Bradley Markle, a postdoctoral researcher at Ding's research group. "If you get 20 or 30 races from a model, each of them will have its own random noise, but they will cancel each other."

The resulting value is the average of all simulation runs without random variability. But this random variability may also be affecting what is being observed on the ice, in addition to the forced signal.

Due to their nature, internal variability may also result in periods when Arctic melting will appear to slow or even reverse, but in the big picture, climate scientists will still see the eventual melting of Arctic sea ice for part of the year . .

"There are so many reasons why we focus on the Arctic sea ice, but one of the main things that people really care about is the summer time without ice," Ding said, referring to a time when the North Pole will cease to be the frozen border was even in the summer.

"At the moment, the forecast is that in about 20 years, we will see a summer without ice," Ding said.

More than just a climatic issue, he continued, ice-free summer is also a social issue, considering the effects on fishing and other food sources as well as natural resources and habitats that benefit from a frozen polar ocean.

One of the things that this discrepancy between simulation and observation indicates, he said, is that the predictions about when this ice-free summer will occur will have to be tempered with some recognition of the effects of internal variabilities.

"There is a lot of uncertainty associated with this time window," Ding said. "As we consider internal variabilities, in addition to forcing CO2, we should be more cautious about the ice-free summer time."

For Markle, this situation highlights the disconnect that often occurs when talking about long-term climate trends versus short-term observations.

Throughout our human time scales, from hours to days, we experience changes in atmospheric temperature to varying degrees, so that an average global or mean temperature rise of one or two degrees does not seem so significant.

"Similarly, year-to-year temperature variability, such as that associated with these internal tropical variations, can be several degrees in the annual average temperature in a specific area, so close to the magnitude of the global warming signal of centuries," he said.

An example of this relatively short-term climate variability is the known El Niño Southern Oscillation (ENSO), the constant oscillation between the El Niño and La Niña climate systems, which bring drought and rain, scarcity and abundance to different parts of the planet. the world.

More extreme weather behavior is expected due to ENSO, as the Earth's climate seeks equilibrium in the face of an average global temperature rise of up to two degrees.

"Just for reference, 20,000 years ago, there was a layer of ice covering most of Canada during the height of the last ice age – which was an annual average temperature change of four or five degrees," said Markle, "but it is a huge difference.

Ding's research group continues to investigate the mysterious and complex internal boosters that affect Arctic sea ice, particularly those that originate in the hot and humid tropics.

"We are more interested in the period from the early 2000s to the present day, where we see such a strong meltdown," said graduate student Ian Baxter, who also works with Ding.

It is known, he added, that the effects of the changes in the Arctic are no longer confined to the region and indeed spread to the mid-latitudes – often in the form of cold-weather outbreaks. The group is interested in how effects in the tropics can spread beyond this region and affect the Arctic.

"We're trying to establish a mechanism by which that happens," Baxter said.

– Sonia Fernandez from UCSB.


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