Google is expanding the role of artificial intelligence in the energy industry with WeatherNext 3, a new AI-powered weather forecasting model designed to deliver more frequent and detailed forecasts.
Developed by Google DeepMind and Google Research, WeatherNext 3 provides global forecasts every hour at resolutions of up to five kilometres. It can predict variables including wind speeds at approximately 100 metres above the ground, cloud cover and surface sunlight — data that can be particularly valuable for wind and solar energy operators.
AI Meets Renewable Energy
The growing use of renewable energy is creating a greater need for accurate weather forecasting. Unlike conventional power plants, wind and solar facilities depend heavily on changing weather conditions.
More accurate predictions can help grid operators estimate renewable generation, balance electricity supply with demand and make better decisions when weather conditions change.
WeatherNext 3 also represents a major improvement over its predecessor, WeatherNext 2, which operated on a 25-kilometre grid and updated forecasts every six hours.
From Weather Data to Enterprise Intelligence
Google is making WeatherNext 3 available beyond consumer products. Forecast data can be accessed through platforms including BigQuery, Earth Engine and Google Cloud Storage, giving businesses opportunities to integrate AI-generated weather intelligence into their existing workflows.
This could support applications across renewable energy, energy trading, grid management, infrastructure planning and other industries where weather directly influences operational decisions.
A Growing Role for AI in the Energy Sector
The launch highlights a broader trend: AI is increasingly becoming an infrastructure technology rather than simply a software feature.
By combining real-time data, machine learning and large-scale computing, AI systems can help businesses make faster predictions and respond to changing conditions.
As renewable energy capacity and electricity demand continue to grow, technologies that connect AI, data and intelligent infrastructure could become increasingly important to the future of energy management.
WeatherNext 3 is another example of how advanced AI models are moving from research environments into practical, industry-specific applications.
Source: artificialintelligence-news.com