Review of artificial intelligence application in typhoon forecasting

This paper reviews the applications of AI models, particularly Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), in typhoon forecasting and analyzes the performance of AI models in 2024 by comparing them with traditional numerical models like the European Centre for Medium-Range Weather Forecasts (ECMWF, TC). As global climate warming intensifies, the frequency and intensity of typhoon (tropical cyclone) have become increasingly uncertain, posing significant challenges to human society.

Traditional typhoon forecasting methods, while having made remarkable progress over the past few decades, still face numerous limitations in handling complex meteorological data and providing accurate predictions. In recent years, the rapid development of artificial intelligence (AI) technologies has brought new opportunities to the field of typhoon forecasting and is revolutionizing typhoon forecasting by improving the accuracy of track and intensity predictions. A case study of Typhoon Gaemi demonstrates AI's capabilities and limitations. The study highlights AI's advantages, challenges, and future recommendations for enhancing typhoon prediction system.