Artificial Intelligence could save lives by warning where a hurricane will hit land much sooner than traditional forecasting systems, researchers say.
A new AI tool from Google DeepMind predicted where September's hurricane Lee would make landfall in Canada three days ahead of existing methods.
Weather forecasts have become much more accurate over the decades.
But AI's speed and ability to analyse past events to make predictions make it a game-changer, say scientists.
An accurate weather forecast is useful to tell you what to wear when you go out in the morning but - much more importantly - can forewarn us of extreme weather like storms, floods and heatwaves, giving communities crucial time to prepare.
However, traditional weather forecasts take vast amounts of computing power.
They involve creating estimates of hundreds of factors including air pressure, temperature, wind speeds and humidity at different levels of the atmosphere around the globe.
A new AI tool called GraphCast created by Google DeepMind outperforms the European Medium Range Weather Forecasting model - one the best in the world - on more than 90% of those factors, according to a peer-reviewed paper published by DeepMind in the journal Science.
GraphCast produces its forecasts in less than a minute, using a fraction of the computing power of traditional forecasting methods because it takes a very different approach.
Traditional weather forecasting involves taking measurements of what is happening in the atmosphere right now.
The best models take in hundreds of millions of readings from around the world every day.
These come from a huge range of sources including weather stations, satellites, balloons sent up in the atmosphere, buoys in the ocean - even readings taken by sensors on the noses of commercial jet planes.
"We then use our model to select which are going to be the most important," explains Matthew Chantry, of the European Centre for Medium Range Weather Forecasting (ECMRWF) who says about 10 million of the measurements will be used for one of its forecasts.
This ocean of data is fed into a supercomputer to be processed by programmes which can do quadrillions (a thousand trillion) of calculations every second. These use complex equations to simulate what happens in the Earth's atmosphere to predict how the weather will change and evolve over time.
This method has been extraordinarily successful. As the models have improved and the computers have got more powerful over the decades, weather forecasts have got significantly more accurate.
But these numerical weather prediction (NWP) models, as they are known, take vast amounts of computer resources, using some of the biggest supercomputers in the world and typically take hours to produce their forecasts.
