{
  "id": 552659,
  "title": "China bets on AI weather forecasting as extreme weather intensifies",
  "url": "https://urgent.news/2026/08/11/china-bets-on-ai-weather-forecasting-as-extreme-weather-intensifies",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-11T08:43:17.000Z",
  "source": {
    "name": "Economic Times Tech",
    "slug": "economic-times-tech",
    "url": "https://economictimes.indiatimes.com/tech/artificial-intelligence/china-bets-on-ai-weather-forecasting-as-extreme-weather-intensifies/articleshow/133147991.cms"
  },
  "original_language": "en",
  "account": "As Typhoon Dolphin approached China, AI-powered weather forecasting systems emerged as a critical tool in predicting the storm's path. Chinese-developed models, such as Shanghai AI Laboratory's Fengwu, Huawei's Pangu, and Fudan University's Fuxi, showcased their ability to generate forecasts more swiftly than conventional systems while maintaining comparable accuracy. These AI models learn patterns from extensive archives of historical weather data, enabling them to produce predictions in a fraction of the time required by traditional numerical models running on supercomputers.\n\nThe competition in AI weather forecasting has intensified, with global leaders like Google's GraphCast and GenCast, Nvidia-backed FourCastNet, and the European Centre for Medium-Range Weather Forecasts' AI Forecasting System (AIFS) contributing to the growing field. However, despite their advantages, AI systems are not poised to completely replace traditional forecasting methods in the near future. While AI models can accurately predict typhoon tracks, they still struggle to predict storm intensity and have yet to prove their reliability in predicting major climate developments.\n\nSun Zhi, CTO of Techwind, the company behind Fengwu's industrial applications, emphasized the importance of AI systems in providing timely information to decision-makers, including local governments, the national government, farmers, and fishermen. Fengwu's developers noted that the system outperformed GraphCast across approximately 80% of evaluated weather variables and extended skillful global medium-range forecasts beyond 10 days. However, Sun cautioned that the technology required years of scientific research to build trust among the public, as people need reliable predictions to make informed decisions, particularly regarding climate change events and their potential impacts.",
  "summary": "Artificial intelligence is increasingly being tested during typhoon season in East Asia, where even small improvements in track forecasts can help authorities better prepare for flooding, organise evacuations and manage potential transport disruptions. The rise of AI weather forecasting has created a new arena of competition among technology companies, research institutes and meteorological…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}