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Google says its AI weather model is getting better

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Why This Matters

Google's new WeatherNext 3 AI weather model significantly enhances forecast accuracy and resolution by leveraging real-time satellite data and richer observational datasets. This advancement allows for faster, more precise predictions, especially for rapid weather changes like rain and snowfall, benefiting both the tech industry and consumers by improving weather reliability and safety. It marks a notable step forward in AI-driven meteorology, potentially transforming how weather forecasts are generated and utilized globally.

Key Takeaways

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Google is rolling out an updated AI weather model that’s supposed to be more accurate, especially when it comes to predicting rain and snowfall.

In the announcement today, the company says it’s now able to make forecasts with “unprecedented resolution” using its new WeatherNext 3 AI model. It can produce a global picture that’s five times sharper than Google’s previous model by learning from real-time weather observations, according to the company.

“One of the main developments is for [WeatherNext 3] to go beyond what data most global AI models train on,” says Samier Merchant, a research engineer at Google Research. “We’re able to leverage fresher and richer observational data sets.”

“We’re able to leverage fresher and richer observational data sets.”

Weather forecasting has traditionally relied primarily on supercomputers that simulate the physics of the atmosphere. That involves solving complex equations, and ultimately comes with a time-lag. AI weather models created by Google and other developers, in contrast, can make faster predictions by recognizing patterns in historical weather data.

Google is going a step further by incorporating live satellite data in its new model. WeatherNext 3 is able to produce a forecast each hour based on the most recent satellite observations. That allows for faster predictions than its previous AI models, as well as higher spatial and temporal resolution.

For comparison, the previous model, WeatherNext 2, produced forecasts every 6 hours on a 25-kilometer grid. The newer model can visualize certain variables, including temperature and moisture, at up to a 5-kilometer resolution.

That speed and resolution is particularly helpful when it comes to predicting rain and snow stemming from fast-moving weather systems, Google says. Using satellite data to make predictions also fills in gaps left in locations where there are fewer rain gauges on the ground. These are places — primarily outside of the US and Europe — where Google says WeatherNext 3 can provide the biggest improvements to weather forecasts. Google says users will see precipitation forecasts that are up to 50 percent more accurate when looking at least a day in advance.

This comparison of 2-meter temperature forecasts over the UK shows WeatherNext 2 with 25-kilometer resolution, while WeatherNext 3 has a 5-kilometer resolution. Image: Google

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