- Google has launched a new AI-based forecasting model called WeatherNext 2
- WeatherNext 2 has faster, more accurate and higher resolution predictions by simulating hundreds of possible weather outcomes in less than a minute.
- WeatherNext 2 now powers forecasts on Google Search, Gemini, Pixel and Maps
Google is overhauling its weather forecast with AI that thinks in probabilities. Instead of new radar towers or satellite launches, the new WeatherNext 2 AI-based forecasting model developed by Google DeepMind and Google Research delivers results up to eight times faster than traditional systems and can predict hundreds of possible weather outcomes from a single starting point with higher resolution and greater accuracy than its predecessors.
WeatherNext 2 is being integrated into many of the most popular Google platforms, including Google Search, Gemini, Pixel Weather, and Maps, and will soon be rolled out more widely via the Google Maps Platform Weather API.
What makes this update more than just a back-end update is the magnitude of its ambition. WeatherNext 2 is designed to take uncertainty into account in unusual ways. While older models could return a single most likely outcome, WeatherNext 2 can generate hundreds of potential futures, allowing forecasters and you to see a full range of possibilities.
It also means that your forecast may not just say “Rain, 40% chance,” but instead show multiple consistent outcomes for your evening walk, with a better view of what could actually happen and when.
Look
WeatherNext 2 uses what Google calls Functional Generative Network (FGN). The model is not based solely on finished forecasts or complete weather systems; instead, it is trained on individual, independent variables, such as temperature, wind speed, and humidity. The model then determines how those variables interact to create “junctions,” the complex real-world patterns such as storm fronts, heat waves, or regional wind changes.
Google claims that this architecture allows WeatherNext 2 to outperform even its own previous best-in-class model, offering more accurate forecasts for 99.9% of variables for up to 15 days.
It is also much faster at making predictions, completing a full forecast in less than a minute. By comparison, traditional physics-based forecasts can take hours on a supercomputer. This efficiency allows for more frequent and detailed forecast updates.
Weathering the future
After considerable testing, Google Gemini will begin showing forecasts based on WeatherNext 2 results, just like Google Maps. In theory, the average person could get a lot of benefits from the upgrade. The weather forecast is one of those invisible systems that underpins an extraordinary variety of decisions. Make it more precise and you’ll eliminate a thousand little sources of stress from people’s daily lives.
There are also larger implications. For example, with smarter weather predictions, renewable energy providers can better estimate wind and solar production, and emergency services can respond more accurately when forecasts capture uncertainty rather than masking it.
That emphasis on uncertainty is key. Forecasting is not about being completely right, but about preparing wisely for what could happen. By providing a variety of physically realistic and interconnected scenarios, WeatherNext 2 pushes the forecast toward something more strategic.
This may not solve the chaos of climate change and related natural disasters, but it could be a boon for those planning ways to better address them. AI-based forecasting is starting to look like essential infrastructure.
Better data means making better decisions. And for the weather, that means a lot more than just helping us decide what kind of coat we need in the morning.
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