China releases first AI models based on Fenyun satellite data for typhoon analysis and severe storm warnings
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China releases first AI models based on Fenyun satellite data for typhoon analysis and severe storm warnings

China has introduced the first batch of artificial intelligence models for predicting extreme weather events, developed using meteorological data from the Fenyun satellite. The presentation took place on October 29 at the Fenyun Satellite User Conference 2026, according to CCTV News. The goal of this release is to transition from describing current weather using the Fenyun satellite to forecasting future weather conditions.

The first model is designed to interpret images of typhoon clouds. It combines multi-channel Fenyun cloud imagery with other satellite products to automatically determine the position, structure, intensity, and probable evolution of a typhoon, after which it generates a textual interpretation. The model covers seven categories of typhoon features and utilizes over 20 real-time satellite observation products. Interpretation is performed every 15 minutes and takes only 27 seconds.

As an example, the developers used Typhoon Surigae, which occurred this year. After automatically detecting the storm, the model provided a comprehensive analysis of its intensity, wind radius, and precipitation characteristics to support monitoring and forecasting. Previously, similar work required manual analysis of satellite images by meteorologists; therefore, automating the initial stage provides them with a faster and more consistent starting point.

The second model aims for earlier warning of severe convective phenomena, such as thunderstorms. It applies artificial intelligence to two hours of continuous observations from the Fenyun-4 satellite to predict cloud development. The main idea is to divide cloud evolution into two components: the general movement of large weather systems and the local growth and decay of smaller ones. This approach increases the lead time for warnings to four hours.

The conference also featured an innovation team in satellite meteorology and artificial intelligence technologies from the Xu Jiangmin Meteorological Satellite Innovation Center. This team comprises 49 researchers from 12 institutions and will jointly work on multimodal representation of satellite meteorological data, as well as monitoring and early warning of extreme weather conditions.

These satellite models complement the growing suite of AI tools for weather forecasting in China, which previously focused on medium-range forecasts based on reanalysis data. The new models work directly with satellite observation data, which meteorologists most frequently use when a storm is already forming.

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China's Meteorological Administration Implements AI-Based Weather Forecasting System Fengqing
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China's Meteorological Administration Implements AI-Based Weather Forecasting System Fengqing

The China Meteorological Administration (CMA) has begun using a global artificial intelligence-based forecasting system nationwide. The system, named Fengqing, is a global short- and medium-range weather forecasting system based on artificial intelligence and is designated as CMA-AIM-GFS-Fengqing-ENS-V1.0.

According to Chinese publications in China Science Daily and IT Home, this system recently passed an operational test conducted at the National Meteorological Center.

It is important to note that the new system differs from the original Fengqing model. The earlier version, developed by the National Meteorological Center in collaboration with Tsinghua University in 2024, is a deterministic model that produces a single forecast run. This model contains approximately 3 billion parameters and can generate global forecasts for 15 days with a resolution of 25 kilometers in about three minutes.

The new version, however, functions as an ensemble system because it creates multiple forecast members to describe the uncertainty of atmospheric movements. This forms the basis for probabilistic forecasts of heavy rainfall, typhoons, and intense convection.

System Development and Technical Features

The system's development was led by the National Meteorological Center in cooperation with the Xunyan Institute of Artificial Intelligence Innovation for Meteorology, the National Meteorological Information Center, and Sugon. It is reported that the model combines the Vision Transformer architecture with physical constraints derived from meteorology, and all its data, algorithms, and computing power were sourced domestically.

Training and iterations were carried out on an AI cluster for science, which comprises about 100,000 accelerator cards located at the National Supercomputing Center in Tianjin.

Performance Results

CMA presents the results of an independent verification on samples covering the period from January 2025 to August 2026. The effective forecasting range for the mean global geopotential height at the 500 hPa level reached 11.0 days. Developers claim that key ensemble metrics, including the continuous ranked probability score of members and the error-spread ratio, showed good results. Some indicators surpassed those of the European Centre for Medium-Range Weather Forecasts' numerical ensemble and its AI-based system, AIFS-CRPS. It should be noted that these comparisons are proprietary to the developers, and detailed evaluations have not been published.

Like other AI-based forecasting models, this system is capable of completing a global calculation in mere minutes after training. CMA stated that the system will be used for disaster prevention, transportation, energy distribution, and environmental protection, and the team will continue working to improve forecasting accuracy and lead time.

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