Real-time satellite inputs
WeatherNext 3 ingests live geostationary satellite mosaics and uses them as fresh input for forecast generation, rather than relying only on lagged simulation data.
WeatherNext 3 is Google DeepMind and Google Research’s global weather AI model for localized, hourly forecasts, integrated with Search, Gemini, Maps, Google Maps Platform, and Cloud.
WeatherNext 3 is Google DeepMind and Google Research’s flagship global weather AI model. The launch article describes it as their most advanced and accurate weather model to date, with WeatherNext 3 now integrated into Search, Gemini, Maps, Google Maps Platform, and Cloud.
The model is designed to improve forecasting for rapidly changing weather by using real-time satellite data, hourly refreshes, and higher spatial resolution. Google says this makes forecasts more localized and better suited to decisions that depend on rain, snow, temperature, wind, and other weather variables, including planning for agriculture, renewable energy, and day-to-day travel or activities.
WeatherNext 3 ingests live geostationary satellite mosaics and uses them as fresh input for forecast generation, rather than relying only on lagged simulation data.
The model produces a new forecast every hour, which is useful for fast-changing conditions and for keeping weather views current across products.
The article states that key surface variables such as temperature and moisture are available at 5-kilometer resolution, other surface variables at 10 kilometers, and atmospheric variables such as wind speed at 25 kilometers.
WeatherNext 3 is described as roughly five times sharper than WeatherNext 2, which used a 25-kilometer grid in 6-hour increments.
The model includes predictions for clean energy variables, in addition to weather variables highlighted in the launch post.
The end-to-end system outputs dense gridded fields, discrete cyclone tracks, and station-level sparse coordinates natively, according to the article's figure caption.
Use WeatherNext 3 to check current and near-term weather before leaving home, especially when conditions can change within the hour.
Teams working in agriculture can use more localized forecasts to make decisions around rain, temperature, and changing field conditions.
Renewable energy operators can use weather inputs and clean energy variables to support operational planning and forecasting.
Developers and teams using Google Cloud or Google Maps Platform can integrate weather forecasts into their own workflows and products.
Meteorologists and researchers can use the model’s cyclone track outputs and higher-resolution fields to study severe weather behavior.
WeatherNext 3 is intended for people who need more localized and more frequently updated weather forecasts, including users of Google Search, Gemini, Maps, Google Maps Platform, and Cloud.
The launch article says WeatherNext 3 provides hourly forecasts using real-time satellite data, with higher spatial resolution for surface and atmospheric variables. It is designed to improve predictions for fast-changing weather.
According to the article, WeatherNext 3 is integrated into Google Search, Gemini, Maps, Google Maps Platform, and Cloud.
The article mentions WeatherNext 3 supporting better rain and snow predictions, along with clean energy variables. It does not provide a complete published list of every output variable.
The source does not include pricing details. It says the model is integrated into Google products and Cloud, but does not explain commercial terms or access limits.
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