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Google DeepMind and Google Research have introduced WeatherNext 3, a global forecasting model that uses real-time observations and raw satellite data to produce hourly, high-resolution predictions.
WeatherNext 3 is positioned as Google’s latest major update to its global weather forecasting technology. By incorporating current observations directly into the forecasting process, the model is designed to deliver faster, more localized guidance and improve predictions for events such as precipitation.
Google says the system is being integrated across Search, Gemini, Google Maps, Google Maps Platform and Cloud. The company cites independent live evaluations by Brightband when describing its performance gains, although the significance of those gains depends on the evaluation methodology and local conditions.
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Today, Google DeepMind and Google Research are introducing WeatherNext 3, the most advanced and accurate global weather model to date, according to independent live evaluations by Brightband. Our model learns directly from real-time observations, enabling it to provide timely and more localized predictions for the weather events that impact people the most. By using raw satellite data to produce a forecast every hour in high resolution, our model makes reliable forecasts accessible across Google products worldwide. ## Rapid weather prediction at unprecedented resolution [...] Sep 03, 2026 Our flagship AI weather forecasting model now includes real-time satellite data, hourly refreshes, higher resolution, precise precipitation forecasting, and clean energy variables. It’s now integrated across Search, Gemini, Maps, Google Maps Platform, and Cloud. The WeatherNext team Text "WeatherNext3" over a blue and yellow saturated image of clouds Your browser does not support the audio elemen
Skip to content Artificial Intelligence # Google DeepMind Just Rolled Out Its Most Accurate AI Global Weather Model The tech giant claims WeatherNext 3 can deliver up to 50% more accurate precipitation forecasts a day or more in advance. By Bruce Gil Reading time 2 minutes The Google DeepMind logo on the walls of an office © Dan Kitwood/Getty Images Comments (0) In the year 2026, predicting hyper-local weather is still tricky, even though it impacts everything from supply chains and sporting events to tourism and energy production. Now, Google says its latest AI model is getting a lot better at it. Google DeepMind and Google Research rolled out WeatherNext 3 on Thursday, which the company calls its most advanced and accurate global AI weather model yet. [...] AI weather models, on the other hand, can generate forecasts much faster, but still mostly rely heavily on data produced by those traditional systems. Google says that can result in a roughly six-hour lag, making
Log in Log in Forgotten account? # Video Home Live Reels Explore More Home Live Reels Explore Video 1 0:01 / 1:19 Today, Google DeepMind and Google Research introduced WeatherNext 3, our most advanced and accurate global weather AI model to date. It learns directly from real-time observations and uses raw satellite data to produce a high-res forecast every hour — meaning you’ll get more accurate predictions across Google products worldwide, including Search, Gemini, and Maps, to help you plan your day. Learn more about this major breakthrough in weather forecasting → Like Comment Share Image 1 Image 2 296 · 49 comments · 29K views
@GoogleDeepMind Google DeepMind @GoogleDeepMind WeatherNext 3 is a major breakthrough in how we forecast global weather. ⛅ Developed with @GoogleResearch, the model learns directly from real-world, real-time observations to give more localized highly accurate predictions faster. 🧵 00:00 3:03 PM · Sep 3, 2026508.8KViews 163 @GoogleDeepMind Google DeepMind @GoogleDeepMind Sep 3 While traditional compute constraints limit standard weather updates to six-hour intervals, WeatherNext 3 ingests real-time satellite data directly to launch a brand-new forecast every single hour. 10 @GoogleDeepMind Google DeepMind @GoogleDeepMind Sep 3 [...] Log inSign up ## Post # Google DeepMind on X: "WeatherNext 3 is a major breakthrough in how we forecast global weather. ⛅ Developed with @GoogleResearch, the model learns directly from real-world, real-time observations to give more localized highly accurate predictions faster. 🧵" @GoogleDeepMind Go
@NewsFromGoogle News from Google Google @NewsFromGoogle Introducing WeatherNext 3, our most advanced and accurate global weather AI model to date, from @GoogleDeepMind and @GoogleResearch. This new forecasting model learns directly from real-time observations, and uses raw satellite data to produce a forecast every hour in high resolution. These breakthroughs mean it can provide timely and more localized predictions, bringing even more reliable forecasts across Google products worldwide, including Search, Gemini and Maps. 00:00 3:12 PM · Sep 3, 2026235.8KViews 72 @NewsFromGoogle News from Google Google @NewsFromGoogle [...] News from Google Google @NewsFromGoogle Introducing WeatherNext 3, our most advanced and accurate global weather AI model to date, from @GoogleDeepMind and @GoogleResearch. This new forecasting model learns directly from real-time observations, and uses raw satellite data to produce a forecast every hour in high resolution. These breakthro
## 5. Localized Weather Predictions The next major forecasting gain is not only longer lead time. It is better local relevance. AI makes weather products more useful when it can translate coarse global output into neighborhood-scale or corridor-scale guidance without pretending that uncertainty disappears. That is where downscaling and regional AI models matter most. Localized Weather Predictions Localized Weather Predictions: A smartphone app displaying hyper-local weather forecasts for a specific neighborhood or street, tailored by AI based on real-time local sensor data. [...] Google's 2025 NeuralGCM work focused on better long-range global precipitation simulation, while WMO highlighted ECMWF's AI Weather Quest as an effort to advance sub-seasonal forecasting with artificial intelligence. Inference: AI is increasingly useful in the space between daily weather and long-term climate, where decision-makers need better early signals of regime shifts rather than a simple long-range d