
WeatherNext By Google
WeatherNext is Google DeepMind's state-of-the-art AI-based weather forecasting technology that delivers faster, more accurate predictions up to 15 days ahead with superior reliability compared to traditional forecasting methods.
https://deepmind.google/technologies/weathernext?ref=aipure

Product Information
Updated:Jun 16, 2025
WeatherNext By Google Monthly Traffic Trends
WeatherNext By Google achieved 11.2M visits with a 162.8% growth in July. This significant increase is likely driven by the deeper Android integration and new collaborative tools introduced in the recent Gemini 2.5 update, enhancing the product's usability and appeal.
What is WeatherNext By Google
WeatherNext is a new family of AI models developed by Google DeepMind and Google Research to revolutionize weather forecasting. In a world of increasingly extreme weather events, this technology combines advanced machine learning with atmospheric science to produce highly accurate weather predictions. The system consists of two main components - WeatherNext Graph for single predictions and WeatherNext Gen for ensemble forecasts - both designed to outperform current industry-standard forecasting systems.
Key Features of WeatherNext By Google
WeatherNext is Google DeepMind's state-of-the-art AI-based weather forecasting technology that combines two main models: WeatherNext Graph and WeatherNext Gen. The technology produces faster and more accurate weather predictions than traditional physics-based models, offering both deterministic (single) and ensemble (multiple) forecasts up to 15 days ahead. The system processes massive amounts of data to generate reliable forecasts four times per day, accessible through Google Cloud platforms like BigQuery and Earth Engine.
Dual Model System: Combines WeatherNext Graph for deterministic forecasts (single predictions) and WeatherNext Gen for ensemble forecasts (multiple scenarios), providing comprehensive weather predictions
Extended Forecast Range: Capable of producing accurate weather predictions up to 10-15 days ahead, with WeatherNext Gen offering ensemble forecasts of up to 50 different weather scenarios
High Processing Efficiency: Generates forecasts in minutes rather than hours, with WeatherNext Gen taking just 8 minutes on a Google Cloud TPU v5 chip to create a forecast
Cloud Platform Integration: Accessible through Google Cloud services including BigQuery and Earth Engine, with live forecasts updated four times daily and historical data available
Use Cases of WeatherNext By Google
Disaster Prevention and Response: Helps authorities and emergency services prepare for and respond to extreme weather events like hurricanes and cyclones with more accurate advance warnings
Renewable Energy Management: Assists in optimizing renewable energy generation by providing accurate wind and solar power forecasting for better grid management
Supply Chain Planning: Enables businesses to better plan their logistics and supply chain operations by anticipating weather-related disruptions
Agricultural Planning: Helps farmers make better decisions about planting, harvesting, and crop protection by providing accurate medium-range weather forecasts
Pros
Superior accuracy compared to traditional forecasting methods
Significantly faster processing time than conventional models
Ability to handle both deterministic and probabilistic forecasting
Cons
Still requires traditional models for initial weather conditions and training data
Limited ability to predict certain extreme weather characteristics like hurricane intensity
Requires significant computational resources and specialized hardware
How to Use WeatherNext By Google
Choose the appropriate WeatherNext model: Select between WeatherNext Graph (for single 10-day forecasts) or WeatherNext Gen (for ensemble 15-day forecasts) based on your needs
Access WeatherNext via Google Cloud: Go to Google Cloud Platform and choose either BigQuery or Earth Engine access method for your selected model
For WeatherNext Graph access: Visit BigQuery (console.cloud.google.com/bigquery) or Earth Engine (developers.google.com/earth-engine) to access single prediction forecasts with 6-hour temporal resolution up to 10 days ahead
For WeatherNext Gen access: Access via BigQuery or Earth Engine to get ensemble forecasts (up to 50 scenarios) with 12-hour temporal resolution up to 15 days ahead
Request historical data access: Fill out the WeatherNext Data Request form if you need access to historical forecast data for research purposes
Access real-time forecasts: Live forecasts are updated four times per day and available within 48 hours of generation through the chosen platform
For developers: Access open source code and documentation through the official GitHub repository at github.com/google-deepmind/graphcast
Cite appropriately: When using historical data, cite DeepMind Technologies Limited's machine learning models according to the CC BY 4.0 license terms
WeatherNext By Google FAQs
WeatherNext is a family of AI models developed by Google DeepMind and Google Research that produces state-of-the-art weather forecasts. It's designed to be faster and more efficient than traditional physics-based weather models while providing superior forecast reliability.
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Analytics of WeatherNext By Google Website
WeatherNext By Google Traffic & Rankings
11.2M
Monthly Visits
#7325
Global Rank
#21
Category Rank
Traffic Trends: Aug 2024-May 2025
WeatherNext By Google User Insights
00:01:16
Avg. Visit Duration
1.58
Pages Per Visit
72.04%
User Bounce Rate
Top Regions of WeatherNext By Google
US: 22.45%
IN: 7.62%
BR: 6.33%
GB: 4.02%
CA: 2.84%
Others: 56.74%