Climate models

When it rains… Climate models could underestimate future floods

According to a new study led by Yale, climate models could significantly underestimate how extreme rainfall will become in response to an increase in greenhouse gases in the atmosphere.

It all comes down to the physics of raindrops, researchers Ryan Li and Joshua Studholme explain in the paper Natural climate change. Even a slight change in the percentage of each raindrop reaching the Earth’s surface can make the difference between a climate of light drizzles and one that creates unprecedented downpours.

Yet, for now, many climate projections appear to underestimate future flooding, the researchers say.

Whether the rainfall produced by a cloud over its lifetime will increase or decrease in warmer climates is a research question that dates back more than half a century. We’re still looking for the answer,” said Li, a graduate student in Yale’s Department of Earth and Planetary Sciences and first author of the new study.

What we have shown is that the answer to this seemingly isolated question actually plays an important role in projections of global climate change.

Recent years have brought a wave of large storms that have exceeded expectations for rainfall severity. These storms hit world damage records in 2021, costing the United States $65 billion, Europe $43 billion and China $30 billion. These financial losses resulted from widespread land destabilization in Germany and flooded subway systems in New York and Henan, China, among other impacts.

According to the authors of the new study, many leading climate models did not see the rise in extreme storms coming. For their study, they analyzed models to understand if, and why, greenhouse gas impacts are underestimated. They trace the problem back to a central question: how much rain will reach the Earth’s surface from a given cloud as the planet continues to warm?

Climate models used for current projections of global warming are divided on this crucial issue,” said co-author Studholme, a physicist and postdoctoral associate in the Department of Earth and Planetary Sciences in the Faculty of Arts and Sciences at Yale.

The answer is a staggering two-fold difference in extreme rainfall projections,” said Studholme, who also contributed to the United Nations Intergovernmental Panel on Climate Change Sixth Assessment Report.

For the study, the researchers developed a new way to measure precipitation efficiency (PE), the amount of rain that is re-evaporated as it falls from a thundercloud. A PE measurement of 0 would mean that no rain reaches the Earth’s surface; a PE of 1 would mean that all the water in the cloud has rained onto the surface. The researchers paid particular attention to the cloud “drying” time scale – the time a cloud would need to drop all of its water.

The researchers found that atmospheric models using more detailed, higher-resolution cloud information often use a higher PE, which means more precipitation. “Unfortunately, the computing power to run these high-resolution models for global climate change projections does not yet exist,” Studholme said. “But they can be used to contextualize conventional climate models.”

They also found that traditional climate models—those that predict increasing EP, such as high-resolution models—predict a two-fold increase in extreme precipitation events by the 21st century, compared to models with decreasing PE.

The study’s co-authors are Alexey Fedorov, professor of ocean and atmospheric sciences at Yale; and Trude Storelvmo, a former Yale professor who is now at the University of Oslo.

The work was funded, in part, by the National Science Foundation, Yale University Graduate Fellowship, the National Oceanic and Atmospheric Administration, and the “Make Our Planet Great Again” initiative of the government of the French Republic.