Google’s AI weather model now uses more raw satellite data
Google launched WeatherNext 3, an AI weather model using raw satellite data that beats ECMWF and now powers Search, Gemini, and Maps.
Google released WeatherNext 3, an AI weather forecasting model that incorporates physical surface information (land/ocean type and elevation) to improve surface temperature and dewpoint calculations, improving point location temperature accuracy by up to 30 percent. Its white paper reports roughly 5 percent better upper-atmosphere accuracy than WeatherNext 2, equating to about six additional hours of forecast lead time, outperforming the ECMWF AI model on these metrics. The model now supplies forecast information across Google Search, Gemini, and Maps, though the paper notes unexplained short-lead degraded results and grid-shaped artifacts in some predictions.
- WeatherNext 3 adds physical surface data to ML forecasting, improving surface temperature accuracy up to 30%.
- Upper-atmosphere accuracy improved about 5% over WeatherNext 2, adding roughly six hours of lead time.
- Reported metrics beat the ECMWF AI weather model across a 15-day horizon.
- Model now powers forecasts in Google Search, Gemini, and Maps.
- Vendors
- Products
- WeatherNext 3GeminiGoogle Search
- AI models
- WeatherNext 3
From the original article
2 min read at arstechnica.com
Like traditional weather models, it benefits from an expanded set of inputs.
By Scott K. Johnson · arstechnica.com
A short excerpt; the article and its images belong to the publisher. Summary, key facts and assessment above are AI-written from the article and can be wrong.