{
  "id": 9340772,
  "title": "Why AI has trouble predicting the fury of hurricane intensity",
  "url": "https://urgent.news/2026/09/23/why-ai-has-trouble-predicting-the-fury-of-hurricane-intensity",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-23T12:44:25.000Z",
  "source": {
    "name": "The Conversation",
    "slug": "the-conversation",
    "url": "https://theconversation.com/why-ai-has-trouble-predicting-the-fury-of-hurricane-intensity-287281"
  },
  "original_language": "en",
  "account": "Hurricane Irma's rapid intensification before making landfall in 2017 has highlighted the difficulty in predicting hurricane intensity, a challenge that persists for AI models. NASA's artificial intelligence has improved weather forecasting in recent years, but these models still struggle with capturing the fine-scale processes necessary for accurate intensity forecasts. Global datasets have been crucial for AI, providing millions of examples of atmospheric condition changes over time, yet these datasets may not be sufficient for regional forecasting, particularly for hurricanes. Rapid intensification events, such as Hurricane Polo in 2026, can surprise forecasters, leaving communities with little time to prepare. While data from observations and simulations are used to train AI models, the limited availability of detailed data in open ocean regions and uncertainties in model simulations pose challenges. Additionally, the chaotic nature of hurricanes, where tiny differences in initial conditions can lead to drastic changes over time, further complicates prediction efforts. Despite advancements in AI technology, accurately forecasting hurricane intensity remains a complex and ongoing challenge.",
  "summary": "Storms like 2026’s Hurricane Polo that rapidly intensify can catch communities off guard and leave little time to prepare or evacuate. Being able to forecast those risks can save lives.",
  "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."
}