AI to outperform meteorologists? A look at DeepMind's GraphCast AI weather prediction tool

Researchers at DeepMind have unveiled a cutting-edge weather prediction program named "GraphCast," leveraging machine learning to forecast weather variables up to 10 days in advance, all within an impressive one-minute timeframe. DeepMind, a subsidiary of Alphabet, concentrates on artificial intelligence, machine learning, and neuroscience research. A recent report in the Science journal spotlights GraphCast's remarkable success, boasting a 90% verification rate that surpasses conventional weather prediction technologies.

The functionality of this AI-powered weather prediction tool relies on assimilating "the two most recent states of Earth’s weather," encompassing variables from both the present moment and the preceding six hours. Utilising this data, GraphCast can accurately predict the state of the weather six hours into the future.

Demonstrating its real-world applicability, the AI algorithm preemptively identified the landfall of Hurricane Lee in Long Island a full 10 days before it occurred, outpacing traditional weather prediction technologies then in use by meteorologists. The advantage lies in GraphCast's ability to swiftly process information, whereas traditional simulations often lag due to the intricate physics and fluid dynamics involved in generating precise forecasts.

Beyond its rapid pace, GraphCast seemingly excels in predicting severe weather events, including tropical cyclones and extreme temperature fluctuations across regions. “GraphCast can be re-trained periodically with recent data, which in principle allows it to capture weather patterns that change over time, such as the effects of climate change, and long climate oscillations,” the report mentioned.

The potential integration of GraphCast, or its underlying AI algorithm, into mainstream services is on the horizon. Google is reportedly exploring possibilities to incorporate GraphCast into its products.

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