The method, called Extreme Event Aware, or “η-learning”, does not need previous extreme events to create these scenarios. (Representational AP photo) What would a once-in-a-century storm look like if it was stronger than anything recorded before? Researchers at the Massachusetts Institute of Technology (MIT) have developed a machine-learning method that can generate realistic scenarios for extreme events that have not happened before.According to Massachusetts Institute of Technology, the new system can generate maps showing the likely size, intensity and duration of extreme weather events, even when similar events are missing from the data used to train the system. This can help weather experts issue early warnings and help disaster relief teams prepare.The new method is called Extreme Event Aware, or 'η-learning'. It learns statistical patterns from available data and uses them to rule out unrealistic possibilities while generating events that could still plausibly happen.The research was published in an open-access paper in Nature Communications.AI models unseen stormsExtreme weather events are difficult to study because they happen rarely. Existing methods of predictions often ...







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