A team of scientists at MIT has developed an artificial intelligence (AI) tool that could save lives. According to MIT News, the AI tool can accurately predict flooding following a large storm like a hurricane.

As the planet continues to warm, stronger hurricanes fueled by warming oceans are becoming more frequent and causing worse flooding when they occur. But it's not just hurricanes that will cause the damage. A recent Princeton study shows that certain parts of the country will experience more flooding in the coming years due to extreme weather. A study by the Environmental Protection Agency (EPA) shows that coastal flooding has increased dramatically since the mid-20th century.

The tool developed by the MIT team combines a generative AI model with a physics-based model to essentially create a satellite image of what a certain area will look like with flooding caused by a particular storm based on the strength of the oncoming storm.

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To test the tool, which the scientists are calling Earth Intelligence Engine (EIE), they applied the method to Houston and compared the results to satellite images of the flooding that occurred following Hurricane Harvey in 2017. The scientists found that the images created by EIE were realistic.

"We were thinking: How can we use these generative AI models in a climate-impact setting, where having trusted data sources is so important," said Björn Lütjens, a postdoc in MIT's Department of Earth, Atmospheric, and Planetary Sciences, who led the research while he was a doctoral student.

The hope is to get the technology to policymakers and local leaders so they can make decisions based on the models ahead of storms and potentially save lives.

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"One of the biggest challenges is encouraging people to evacuate when they are at risk," Lütjens said. "Maybe this could be another visualization to help increase that readiness."

The team also hopes the tool will help city planners act accordingly to mitigate flood risks. They've made examples available online.

The method is currently in the proof-of-concept stage as it analyzes other regions to predict the outcomes of storms more accurately.

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