由 Google DeepMind 和 Google Research 開發的人工智慧模型 WeatherNext，在颶風梅麗莎登陸牙買加前五天，就以高達 80% 的置信度準確預測了它將發展為五級颶風。這項在《自然》雜誌上發表的研究指出，該模型能以史無前例的準確度預測氣旋，平均為預報員爭取到比現有模型多一天的預警時間。這額外的一天對於安排疏散和調度資源等決策至關重要，能有效幫助減輕災情。

預測極端天氣對人工智慧來說是一大挑戰，因為機器學習通常需要大量數據，而極端天氣相對罕見。此外，颶風預測不僅需要全球尺度的數據來預測路徑，還需要局部海洋與大氣條件的數據來預測強度。然而，WeatherNext 即使僅使用較低解析度的輸入數據，依然能在路徑和強度的預測上展現出卓越的表現，甚至讓預報中心首次能在風暴僅為一級階段時，就成功預測其將快速增強為五級颶風。（關鍵數字：5, 1）

除了提供單一預測，WeatherNext 還能為發展中的風暴生成多達 1000 種潛在情境，幫助捕捉微小偏差可能帶來的「蝴蝶效應」，這是依賴現有計算能力的傳統數值模型難以實現的。儘管 AI 模型帶來重大突破，專家仍強調人類在將這些預測轉化為具體影響評估上的關鍵角色。目前 Google DeepMind 已開源該模型，期望藉由開放給研究社群使用，能進一步揭開氣旋運作的未知科學機制。

Developed by Google DeepMind and Google Research, the artificial intelligence model WeatherNext accurately predicted that Hurricane Melissa would hit Jamaica as a Category 5 hurricane five days before landfall with 80 percent confidence. According to a study published in Nature, the model predicts cyclones with unprecedented accuracy, giving forecasters an average of one more day of lead time compared to existing models. This crucial extra day is extremely valuable for making time-sensitive decisions like organizing evacuations and deploying resources, ultimately helping to mitigate disasters.

Forecasting extreme weather events poses a significant challenge for AI since machine learning requires ample data, and such events are rare. Furthermore, predicting hurricanes requires multi-scale data: global data for the storm's track and local atmospheric and oceanic data for its intensity. However, WeatherNext excels at predicting both track and intensity despite using relatively coarse-resolution input data. Its outstanding performance even allowed forecasters to predict a Category 5 hurricane when the storm was only at a Category 1 stage for the first time.

Instead of providing a single forecast, WeatherNext generates up to 1,000 potential scenarios for a developing storm, helping forecasters account for the butterfly effect where small deviations lead to significant changes—a feat impossible with current numerical models and computing power. While the AI model represents a major breakthrough, experts emphasize that human interpretation remains critical in translating these forecasts into actual real-world impacts. Google DeepMind has now open-sourced the model, hoping that giving the research community access will help uncover new scientific insights into how cyclones operate.