"Our goal is to save lives by providing policymakers with the information they need to anticipate and perhaps prevent catastrophic disasters," said Auroop Ganguly of Oak Ridge's Computational Sciences and Engineering Division and project lead. "The insights we're providing can be acted upon to prevent the disasters from becoming catastrophic in terms of loss of lives and property or to the critical civil infrastructure."

Ganguly and his colleagues examined daily observations from 7,900 stations in South America from 1940 to 2004 mapped to spatial grids, paying attention to rainfall extremes and regions with dense populations.

By examining past extremes, researchers developed a predictive tool "that helps us set priorities according to the likelihood of an extreme event," said co-author George Ostrouchov, a mathematician in Oak Ridge's Computational Sciences and Mathematics Division.

Ganguly said the project goes beyond current disaster preparation.

"The risks and impacts from such (weather) extremes may be reduced or even eliminated in some situations through well-designed policies," he said.