Polar ice, atmospheric water vapor, the main drivers of variation among climate models

A Florida State University researcher is part of a team that found that various projections of global warming trends advanced by climate change scientists can be explained by the models’ different predictions of ice loss and vapor. atmospheric water.

The work will help climatologists reconcile various models to improve their accuracy, said Florida State University professor of meteorology Ming Cai, one of the authors of the study published in Nature Communication .

Climatologists agree that the Earth’s surface temperature is warming, but details on exactly where and to what extent are less clear. A worst-case climate change scenario (known as the “representative 8.5-degree pathway”) predicted a likely increase in mean global temperatures from about 2.6 degrees Celsius to 4.8 degrees Celsius (or approximately 4.7 degrees Fahrenheit to 8.6 degrees Fahrenheit) by 2100.

“This uncertainty limits our ability to predict the severity of the impacts of global warming on nature and human civilization,” Cai said. “The more information we have about the effects of climate change around the world, the better prepared we will be.”

The difference between these conclusions would mean the difference between a sea level rise of about half a meter to almost a meter, for example.

As scientists around the world have studied the climate, they have developed their own models. Although the main components of these climate models are based on the same general physical principles, such as the conservations of energy and mass, they still differ from each other in many details, leading to a series of conclusions on something like the future average. global temperature.

“What are the best ways to represent these details in a climate model? Cai said. “This is a question that climate science is always trying to answer. The model fits into the ‘artistic’ part of science.”

The researchers studied the variability among 25 climate models that participated in the United Nations Intergovernmental Panel on Climate Change. They found that climate models that predicted higher average temperatures for the entire surface of the Earth also produced results showing more loss of polar ice and more water vapor in the atmosphere.

“We found that these two factors account for almost 99% of the difference in the forecast for global mean warming among these 25 climate models,” Cai said. “Our results suggest that variability between climate models could be significantly reduced by reducing uncertainty in models simulating albedo feedbacks from ice and water vapor.”

The research also found that cloud cover is less important than scientists previously thought in explaining the variation between models.

These models are tools for making predictions for things like sea level rise, flood risk, crop and wildlife viability, and other considerations.

“Knowing that polar ice and water vapor in the atmosphere are the most important drivers of variability in different climate models will help climatologists to further refine these models,” Cai said.