AI洞悉“天机” 风云不再“莫测”

Core Viewpoint - The rapid development of artificial intelligence (AI) technology is enhancing the accuracy and efficiency of weather and climate predictions, with AI models expected to match or exceed traditional physical models in both temporal and spatial resolution [1]. Group 1: AI Weather Models - AI weather models, such as Pangu, Fengwu, and Fuxi, are increasingly being utilized in typhoon prediction and short-term climate forecasting, showcasing their potential to improve prediction accuracy and efficiency [2]. - The advantages of AI weather models include faster computation times, higher accuracy in forecasts (e.g., typhoon path predictions), and built-in optimization modules for various predictive studies [2][3]. - AI models have successfully predicted the El Niño-Southern Oscillation (ENSO) phenomenon for over 18 months, significantly surpassing traditional models [2]. Group 2: Integration of AI and Traditional Methods - Current AI weather models face challenges, such as unclear physical mechanisms behind predictions and insufficient temporal resolution, with some models refreshing data only every six hours compared to traditional models that do so in minutes [4]. - The integration of high-performance computing (HPC) with AI is proposed as a solution to enhance prediction accuracy and overcome computational limitations [4][5]. - Future developments in weather forecasting are expected to rely on a combination of HPC and AI, requiring advanced supercomputing systems capable of handling massive computational demands [5].