Paris Agreement does not rule out ice-free Arctic, researchers say

Scientists from South Korea, Australia and the US used results from climate models and a new statistical approach to calculate the likelihood of Arctic sea ice disappearing at different warming levels.

Climate projections are usually obtained from global climate computer models, based on several hundred thousand lines of computer code, developed to solve the physical equations of the atmosphere, ocean, sea-ice and other climate components.

By applying future greenhouse gas concentrations to these projections, each computer model produces a version of what the Earth's climate might look like in the future.

However, transforming this information into practical decisions still remains a challenge, due to the remaining uncertainties in the magnitude of future climate change on regional scales.

Furthermore, it has been difficult for researchers in the field to extract meaningful probabilities from climate models. This is because these models sometimes share common computer code or make similar assumptions regarding the implementation of less well understood processes, such as clouds or vegetation, some experts say.

To obtain more accurate probability estimates for future climate change in the Arctic region, the research team developed a novel statistical method which translates results from a suite of climate computer model simulations to probabilities.

The method developed by IBS ranks the models in terms of the quality in which they agree with present-day observations and also accounts for interdependencies among the models.

“Translating model dependence into mathematical equations has been a long-standing issue in climate science. It is exciting to see that our method can provide a general framework to solve this problem,” said Won Chang, assistant professor in the department of Mathematical Sciences at the University of Cincinnati.

The researchers applied the statistical method to climate model projections of the 21st century by using 31 different climate models, which also show considerable interdependence.

As a result, the scientists found there is at least a 6 per cent probability that summer sea ice in the Arctic Ocean will disappear at 1.5°C warming above pre-industrial levels – the lower limit recommended by the Paris Agreement of the United Nations Framework Convention on Climate Change.

Furthermore, the models found that with a 2°C warming, the probability for losing the ice rises by at least 28 per cent – likely seeing a sea ice-free summer Arctic Ocean for the first time.

“Our work provides a new statistical and mathematical framework to calculate climate change and impact probabilities,” said Jason Evans, professor at the Climate Change Research Centre in UNSW Australia in Sydney.

“Up to now, there was no established mathematical framework to assign probabilities on non-exclusive theories,” added Roman Olson, lead author and researcher at IBS, Centre for Climate Physics (ISSP) in South Korea.

“While we only tested the new approach on climate models, we are eager to see if the technique can be applied to other fields, such as stock market predictions, plane accident investigations or in medical research.”