Why AI has trouble predicting the fury of hurricane intensity

Artificial intelligence (AI) has significantly improved weather forecasting in recent years, with global AI models now matching some of the best traditional physics-based prediction systems.

This progress is driven by three key factors: vast amounts of weather data, advanced AI models, and powerful computing resources.

Global weather data, collected over decades, provides millions of examples of atmospheric changes, enabling AI to identify patterns that were previously impossible to detect.

For instance, datasets like those from the National Oceanic and Atmospheric Administration (NOAA) contain decades of climate records covering the entire Earth.

However, this success is more pronounced at the global scale.

When focusing on smaller regions, such as hurricane intensity forecasting, AI faces greater challenges due to the need for more detailed and localized data.