Envision's Tianji Weather Foundation Model Tops ECMWF's AI Weather Quest, Setting a New Global Benchmark for Physics-AI Forecasting

SHANGHAI, Oct. 30, 2026 /PRNewswire/ -- Envision, a global leader in green technology, today announced that its independently developed weather foundation model, Envision Tianji, ranked first overall in the latest edition of the AI Weather Quest, an AI weather competition organized by the European Centre for Medium-Range Weather Forecasts (ECMWF). Tianji outperformed nearly 20 top teams worldwide, taking first place across all assessed metrics, including variable-averaged, near-surface temperature, mean sea level pressure, and precipitation for the 19–25 day forecast window.

The AI Weather Quest evaluates models through continuous, real-time forecasting and verification, assessing sustained performance under varying weather conditions. Beyond the 15-day medium-range forecast horizon, the competition focuses on probabilistic forecasts of weekly mean temperature and mean sea level pressure, and weekly accumulated precipitation, for days 19–25. Temperature and precipitation are evaluated over predominantly land-covered grid cells, while mean sea level pressure is assessed globally, emphasizing the ability to anticipate weekly conditions and their uncertainty several weeks in advance. Teams submit forecasts weekly, and organizers evaluate them against subsequent actual weather, publicly updating the leaderboard.

This win follows a series of top-tier results for Tianji, including a top-tier placement in the global WeatherBench 2 evaluation, on par with Google WeatherNext2 Model, and first place overall in the deterministic forecast track of the AI Weather Forecast Model Demonstration Program organized by China's National Meteorological Center. Tianji has also proven its value in energy applications, winning first place in State Grid's AI load forecasting competition and China Southern Power Grid's business competition. With this latest result, Envision has again demonstrated Tianji's full-chain capability, from short-term forecasting to subseasonal prediction.

"Subseasonal forecasting — two weeks to two months out — is one of the hardest challenges in meteorology," said Robert Zheng, head of Envision's Tianji Weather Foundation Model. "The longer the horizon, the greater the uncertainty in atmospheric changes, and the higher the demand on a model's ability to identify evolving weather trends. Building on Envision's years of practical experience in new energy, we have developed the world's first physics-AI weather model, leveraging petabyte-scale high spatiotemporal resolution data and a 'space–air–ground' three-dimensional data network to deliver reliable forecasts across full time scales."

Powered by high-performance computing, Tianji delivers rapid short-term and global forecasts with significantly improved accuracy for wind speed and irradiance in key regions. Covering full time scales from minute-level nowcasting to subseasonal trend assessment, it provides end-to-end meteorological intelligence for real-time monitoring and long-term planning.