Press Release

Johns Hopkins Scientists Leverage AI to Discover Climate ‘Tipping Points’

Climate tipping points have become a source of growing concern, particularly among policymakers and scientists. They are critical thresholds that, once crossed, could “tip” a natural climate system into an entirely different state. Speculation around these abrupt changes points to potentially irreversible, catastrophic impacts for the planet.

Researchers have been working on ways to predict these climate tipping points to avoid crossing them in the first place. However, the impacts have remained difficult to capture with high resolution, accuracy, and confidence because of the complexity and dynamics of the interconnected Earth systems involved.

To overcome these challenges, artificial intelligence (AI) experts at the Johns Hopkins Applied Physics Laboratory (APL), in Laurel, Maryland, have teamed up with oceanographers from the Johns Hopkins University Department of Earth and Planetary Sciences to integrate AI with traditional climate modeling methods to enable scientific researchers to better understand climate tipping points.

The project — the Physics-informed AI Climate Model Agent Neuro-symbolic Simulator (PACMANS) for Tipping Point Discovery — is led by Principal Investigator Jennifer Sleeman, a computer scientist in APL’s Research and Exploratory Development Department. It is supported by the Defense Advanced Research Projects Agency (DARPA) as part of its AI-assisted Climate Tipping-point Modeling (ACTM) program, which aims to leverage AI and machine learning to better model the complex processes that affect Earth’s climate.

“This emerging field will also be of interest beyond the climate community, as tipping point discovery methods also apply to social, political and economic systems,” Sleeman said.