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Simulation vs Observation in Arctic Sea Ice | press release


to Sonia Fernandez for UCSB | November 18, 2018 | 9 am.

As an indicator of the impact of climate change, sea ice in the Arctic is difficult to defeat. Scientists have observed that polar regions freeze and retreat from the most sensitive areas on earth to gain insights into the potential ripple effects of various natural systems, including the global ocean circulation, surrounding habitats and ecosystems, food sources, and sea level.

However, despite the efforts to make the model simulations closer to the actual observations of Arctic sea ice, the gap widened. Earth reports indicate that ice is melting at a much faster rate than predicted by global climate models.

An assistant professor at UCSB climate scientist, Tsinghua University District (CCS) District Research Institute, said, "Based on this phenomenon, people have different opinions.

He believes that the consensus of the climate science community is the result of incorrect modeling of inconsistencies. "There is a slight prejudice in the model, and the sensitivity to anthropogenic forcing is low," he said.

Ding and his group disagree. In a study in Nature Geoscience, entitled "Fingerprinting of Internal Drivers of Arctic Ocean Ice Loss in Observation and Model Simulation," the model says the model is good.

They claimed that about 40-50% of the sea ice loss over the last 30 years is important, but is due to insignificant internal factors so far.

"In fact we compare apples to oranges." Ding said of the inconsistency between real-time observations and simulated Arctic ice melting by artificial forcing.

He explains only what the model average is as a result of past radiative forcing (a calculation based mainly on greenhouse gas levels), but for example, short-term variations in sea surface temperature, humidity, atmospheric pressure, and other phenomena elsewhere on earth And other factors connected to it.

These high frequency events are often seen as noise in repeated individual runs of simulations, as scientists are finding common long-term trends.

Bradley Markle, a postdoctoral researcher at Ding's research group, said, "No matter what model you turn, it will be random." "Running the model 20-30 times will have their own random noise, but they will cancel each other."

The result is the average of all simulation runs without random variability. However, the random variability may affect what is observed on the ice in addition to the forced signal.

Because of the nature of nature, internal volatility may seem to slow or warp the Arctic ice melt, but in the larger picture, climate scientists are still witnessing melting of the Arctic ice completely in some parts of the year.

"There are many reasons to focus on the Arctic sea ice, but one of the main things people really care about is the summer time without the ice age," Ding said. It was even in the summer when the North Pole was no longer frozen.

"It is predicted that now, in about 20 years, there will be an ice-free summer," Ding said.

In addition to climate problems, summer without ice is also a social problem, given the impact of polar regions on frozen natural resources and habitats, as well as fish and other food.

One of these discrepancies between simulations and observations is that predictions about when ice-free summers will occur should be mitigated by some recognition of the effects of internal variability, he said.

"There is a huge uncertainty associated with this time window," Ding said. "When we consider internal volatility and CO2 forcing, we need to be more cautious about the ice-free summer time."

For Markle, this situation highlights frequent disconnects when talking about short-term observations and long-term climate trends.

Over a few hours to a few hours of human time scales, we experience atmospheric temperature changes above a few degrees. So the average temperature rise of a couple degrees does not really matter.

"Likewise, the yearly temperature variability associated with these tropical internal changes is close to the same as the century's global warming signal, because it can be several degrees of average annual temperature in a given area." .

An example of relatively short-term climate variability is the well-known El Nino Southern Oscillation (ENSO). The constant steep movement between El Niño and La Niña climate systems brings drought, rain, scarcity and richness to the rest. World.

More extreme ENSO meteorological behavior is expected as the Earth's climate pursues equilibrium, even if the global mean temperature rises by several degrees.

"There was an ice sheet covering most of Canada in the year when the last ice age began for reference 20,000 years ago, which is an average temperature change of 4 to 5 degrees Celsius," Markle said. "But it makes a big difference."

Ding's research group continues to investigate mysterious and complex internal factors that affect the Arctic sea ice, particularly those that occur in warm, humid tropical regions.

"We are mainly interested in the early 2000s to today, and we can see that strong rust," said graduate student Ian Baxter.

It is also known that the influence of the Arctic change is no longer confined to the region but actually spreads to the mid-latitude in the form of cold weather. This group is interested in how the effects of the tropics can spread beyond the region and affect the Arctic.

"We're trying to build a mechanism that will happen," Baxter said.

– Sonia Fernandez of UCSB.

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