WeatherNext

WeatherNext is AI weather forecasting technology developed by Google DeepMind and Google Research. It runs faster than traditional physical models and produces two kinds of output: deterministic forecasts that give a single prediction, and ensemble forecasts that give multiple possible future scenarios. It reaches up to 15 days ahead with a time resolution of up to 6 hours. Real-time forecasts and historical data are served through Google Cloud, including BigQuery and Earth Engine, and the model code is open source. The technology is offered free of charge to scientists and forecasters.

The distinction between the two output types matters in practice. A deterministic run tells you what the model thinks will happen; an ensemble run tells you how confident it is, by showing the range of outcomes it considers plausible. For warning decisions and for energy scheduling, the spread is often as useful as the central estimate, because it tells you how much margin to build in.

- Pull deterministic or ensemble forecasts out to 15 days

- Access real-time and historical data through Google Cloud

- Support early warnings for heavy rain and hurricanes

- Optimize wind and solar scheduling with better outlooks

- Build on the open-source model code for research

- Meteorological agencies that issue public warnings

- Energy companies balancing renewable generation

- Agricultural planners and academic researchers

- Data teams studying forecast model performance

Using the data requires a Google Cloud account and enough data handling skill to work with large forecast files, and cloud egress costs can apply beyond the free research access. Forecasts are probabilistic, so an ensemble spread is not a promise, and operational decisions still need a qualified meteorologist. Free access is aimed at scientists and forecasters, and the available models, dataset names, and access routes are controlled by Google and can change. Check current documentation before building anything that depends on a specific endpoint.