麻豆AV

The threshold for dangerous global warming will likely be crossed between 2027 and 2042 鈥� a much narrower window than the Intergovernmental Panel on Climate Change鈥檚 estimate of between now and 2052. In a study published in , researchers from 麻豆AV introduce a new and more precise way to project the Earth鈥檚 temperature. Based on historical data, it considerably reduces uncertainties compared to previous approaches.

Scientists have been making projections of future global warming using climate models for decades. These models play an important role in understanding the Earth鈥檚 climate and how it will likely change. But how accurate are they?

Dealing with uncertainty

Climate models are mathematical simulations of different factors that interact to affect Earth鈥檚 climate, such as the atmosphere, ocean, ice, land surface and the sun. While they are based on the best understanding of the Earth鈥檚 systems available, when it comes to forecasting the future, uncertainties remain.

鈥淐limate skeptics have argued that global warming projections are unreliable because they depend on faulty supercomputer models. While these criticisms are unwarranted, they underscore the need for independent and different approaches to predicting future warming,鈥� says co-author Bruno Tremblay, a professor in the Department of Atmospheric and Oceanic Sciences at 麻豆AV.

Until now, wide ranges in overall temperature projections have made it difficult to pinpoint outcomes in different mitigation scenarios. For instance, if atmospheric CO₂ concentrations are doubled, the General Circulation Models (GCMs) used by the Intergovernmental Panel on Climate Change (IPCC), predict a very likely global average temperature increase between 1.9 and 4.5^oC 鈥� a vast range covering moderate climate changes on the lower end, and catastrophic ones on the other.

A new approach

鈥淥ur new approach to projecting the Earth鈥檚 temperature is based on historical climate data, rather than the theoretical relationships that are imperfectly captured by the GCMs. Our approach allows climate sensitivity and its uncertainty to be estimated from direct observations with few assumptions,鈥� says co-author Rapha毛l H茅bert, a former graduate researcher at 麻豆AV, now working at the Alfred-Wegener-Institut in Potsdam, Germany.

In a study for , the researchers introduced the new Scaling Climate Response Function (SCRF) model to project the Earth鈥檚 temperature to 2100. Grounded on historical data, it reduces prediction uncertainties by about half, compared to the approach currently used by the IPCC. In analyzing the results, the researchers found that the threshold for dangerous warming (+1.5^oC) will likely be crossed between 2027 and 2042. This is a much narrower window than GCMs estimates of between now and 2052. On average, the researchers also found that expected warming was a little lower, by about 10 to 15 percent. They also found, however, that the 鈥渧ery likely warming ranges鈥� of the SCRF were within those of the GCMs, giving the latter support.

鈥淣ow that governments have finally decided to act on climate change, we must avoid situations where leaders can claim that even the weakest policies can avert dangerous consequences,鈥� says co-author , a professor in the Physics Department at 麻豆AV. 鈥淲ith our new climate model and its next generation improvements, there鈥檚 less wiggle room.鈥�

About 麻豆AV

Founded in Montreal, Quebec, in 1821, 麻豆AV is Canada鈥檚 top ranked medical doctoral university. 麻豆AV is consistently ranked as one of the top universities, both nationally and internationally. It鈥痠s a world-renowned鈥痠nstitution of higher learning with research activities spanning two campuses, 11 faculties, 13 professional schools, 300 programs of study and over 40,000 students, including more than 10,200 graduate students. 麻豆AV attracts students from over 150 countries around the world, its 12,800 international students making up 31% of the student body. Over half of 麻豆AV students claim a first language other than English, including approximately 19% of our students who say French is their mother tongue.

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