Ask a Scientist: How do researchers use AI to predict a cyclone?
A Google DeepMind scientist explains how AI weather prediction works and how it can help warn communities earlier than ever.
Researchers are employing artificial intelligence to greatly enhance cyclone forecasting accuracy. By training models on historical data, these tools can now operate on a single processor rather than requiring massive supercomputers. This innovation enables communities to receive vital extra time to prepare for extreme weather, increasing safety during dangerous storms.
Google researchers have achieved a significant leap in cyclone forecasting accuracy by combining 50 years of historical atmospheric data with advanced AI, transforming what once required large supercomputers into models that can run on a single TPU. Ferran Alet, a research scientist at Google DeepMind, discussed how his team developed the WeatherNext forecasting models to aid meteorologists and scientists in accessing AI-powered extreme weather predictions.
These predictions help people receive more accurate forecasts and warnings ahead of potentially devastating weather events like cyclones. By applying AI to physics-based models, the meteorological community saw a decade's worth of forecast improvement in a single generation with the WeatherNext models. AI allows researchers to better predict the future by analyzing patterns from the past and current data, improving predictions for where and how intense a cyclone will be.
The ability to accurately predict a storm's path is crucial for keeping people safe as extreme weather events impact more communities worldwide.
Written by urgent.news from Google Blog's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
