Artificial intelligence is powering weather forecasts that are generally more accurate than conventional forecasts and are faster and cheaper to produce.
Artificial intelligence is powering weather forecasts that are generally more accurate than conventional forecasts and are faster and cheaper to produce. But new research shows A.I. may fail to predict unprecedented weather events, a troubling finding as warming fuels new extremes.
Weather prediction relies on neural networks, a form of A.I. that can learn to make predictions by identifying patterns in vast amounts of data. The problem, the study finds, is that neural networks may not be able to predict events that lie outside their training data. For A.I. weather models, that means failing to forecast droughts, storms, and heat waves that have little or no precedent in the weather record.
For the new study, scientists trained an A.I. model on decades of weather data, but omitted any hurricane stronger than Category 2. When the A.I. was given the conditions that would lead to a Category 5 hurricane and asked to make a forecast, it consistently came up short.
Read More: Yale Environment 360
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