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Google DeepMind: WeatherNext 3: More accurate, timely, and local weather forecasts

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YouTube · Google DeepMind
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WeatherNext 3: More accurate, timely, and local weather forecasts

Predicting the weather is one of the oldest, most complex challenges we face. Traditional numerical weather prediction models are powerful, but they can be slow to run and costly at a global scale. WeatherNext 3 takes a different approach. Built on a fundamentally different architecture, WeatherNext 3 learns directly from real-world observations, including live satellite feeds and ground-level weather station data.


What makes WeatherNext 3 different?
Hourly refresh: While traditional models typically refresh every six hours, WN3 produces a fresh forecast every single hour.
Hyper-Local resolution: Native 5km resolution for temperature and humidity, enabling better detail for coastal regions, mountains, and urban areas.
Actionable data: Includes variables like 100m wind speeds for wind energy management and detailed cloud/radiation metrics for solar energy planning.
Global reach: Delivering high-resolution insights everywhere.
You can now use WeatherNext 3 through Google Search, Gemini, Google Maps and more.

Learn more: https://blog.google/innovation-and-ai/models-and-research/google-deepmind/introducing-weathernext-3/
Read the full paper: https://storage.googleapis.com/deepmind-media/papers/weathernext_3.pdf
Disclaimer: For official weather forecasts, severe weather warnings, and public safety advisories, please refer to your local meteorological agency or national weather service.

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