A new paper released in the Journal Nature is the latest in a growing series that project larger impacts than previously predicted or conclude that climate change is unfolding faster than once believed.
published on Wednesday in Nature, found that global temperatures could rise nearly 5 °C by the end of the century under the the UN Intergovernmental Panel on Climate Change’s steepest prediction for greenhouse-gas concentrations. That’s 15 percent hotter than the previous estimate. The odds that temperatures will increase more than 4 degrees by 2100 in this so-called “business as usual” scenario increased from 62 percent to 93 percent, according to the new analysis.
For this study, the scientists collected more than a decade’s worth of satellite observations concerning the amount of sunlight reflected back into space by things like clouds, snow, and ice; how much infrared radiation is escaping from Earth; and the net balance between the amount of energy entering and leaving the atmosphere. Then the researchers compared that “top-of-atmosphere” data with the results of earlier climate models to determine which ones most accurately predicted what the satellites actually observed.
The simulations that turned out to most closely match real-world observations of how energy flows in and out of the climate system were the ones that predicted the most warming this century. In particular, the study found, the models projecting that clouds will allow in more radiation over time, possibly because of decreased coverage or reflectivity, “are the ones that simulate the recent past the best,” says Patrick Brown, a postdoctoral research scientist at the Carnegie Institution and lead author of the study. This cloud feedback phenomenon remains one of the greatest areas of uncertainty in climate modeling.
But an emerging challenge is that the climate is changing faster than the models are improving, as real-world events occur that the models didn’t predict. Notably, Arctic sea ice is melting more rapidly than the models can explain, suggesting that the simulations aren’t fully capturing certain processes.