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Google WeatherNext 3
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About Google WeatherNext 3
WeatherNext 3 is Google DeepMind’s global AI weather model that generates hourly forecasts at 5–10 km resolution directly from raw satellite data. It powers Google Search, Maps, and Gemini while offering enterprise access through BigQuery, Earth Engine, Maps Platform, and Cloud Storage. Teams can query forecast grids, overlay weather layers on maps, and export data for analytics without maintaining forecasting infrastructure. The model supports monitoring precipitation, wind, temperature, humidity, and radiation to inform scheduling, routing, energy dispatch, and risk alerts. It reduces operational overhead by eliminating the need for numerical weather prediction setup and maintenance, providing production-ready access for data-driven operators and researchers. Designed for global coverage and low latency, WeatherNext 3 enables renewable energy forecasting, fleet routing, severe weather monitoring, and live weather integration into applications via Google Cloud services.
Google DeepMind
London, United Kingdom · Founded 2010
- Founders
- Shane Legg, Demis Hassabis
- Founded
- 2010
- Headquarters
- London, United Kingdom
Key features
- Hourly global forecasts from satellite-native inputs
- 5 km resolution for temperature and humidity, 10 km for wind and surface variables
- Access via BigQuery, Earth Engine, Maps Platform, and Cloud Storage
- Nowcasting for precipitation and flood-aware routing
- Wind and radiation data for renewable energy forecasting
- Severe-weather monitoring and operational risk alerts
- Live weather layer embedding in Maps-powered products
- No numerical weather prediction setup or maintenance required
- Ensemble approach for improved reliability across regions and seasons
- Hourly updates to capture rapidly evolving weather patterns
Use cases
- Renewable energy operators forecasting solar and wind output
- Logistics and mobility teams routing fleets with real-time weather
- Insurers and risk teams monitoring severe weather for claims and alerts
Pros
- Generates hourly forecasts at 5–10 km resolution directly from raw satellite data
- Provides global coverage with low latency for real-time decision-making
- Eliminates the need for traditional numerical weather prediction infrastructure
- Supports integration with Google Cloud services like BigQuery, Earth Engine, and Maps Platform
- Designed for enterprise use with production-ready access and analytics capabilities
Cons
- Requires access to Google Cloud services for full functionality
- Dependent on satellite data availability and quality
- May have limitations in regions with sparse observational data coverage
Google WeatherNext 3 videos
Frequently asked questions about Google WeatherNext 3
What is WeatherNext 3?
WeatherNext 3 is Google DeepMind’s most advanced global AI weather model that generates hourly forecasts at 5–10 km resolution directly from raw satellite data.
Who should use WeatherNext 3?
It is designed for data-driven operators, researchers, and enterprises needing high-resolution, real-time weather data for applications like renewable energy forecasting, fleet routing, and severe weather monitoring.
How does WeatherNext 3 work?
The model processes raw satellite imagery to produce hourly forecasts, including variables like temperature, humidity, wind, precipitation, and radiation, without relying on traditional numerical weather prediction methods.
What integrations does WeatherNext 3 support?
It integrates with Google Cloud services such as BigQuery, Earth Engine, Maps Platform, and Cloud Storage for data querying, visualization, and analytics.
Can WeatherNext 3 be used for live weather integration in applications?
Yes, WeatherNext 3 enables live weather integration into applications via Google Cloud services, supporting real-time decision-making.
How do I get started with WeatherNext 3?
Access to WeatherNext 3 is available through Google Cloud services, where users can query forecast grids, overlay weather layers, and export data for analytics.
