Chinese scientists have introduced a novel artificial intelligence (AI) approach to predict the rapid intensification of tropical cyclones, contributing to improved global disaster preparedness.
Researchers from the Institute of Oceanology at the Chinese Academy of Sciences recently published their findings in the journal Proceedings of the National Academy of Sciences.
The rapid intensification of tropical cyclones, characterized by a sudden and significant increase in storm intensity, remains one of the most difficult weather events to predict due to its unpredictable and destructive nature.
The study highlights that conventional forecasting techniques, including numerical weather prediction and statistical models, often fail to account for the complex environmental and structural elements influencing rapid intensification. While AI has been explored for better forecasting, previous models have struggled with high false alarm rates and inconsistent reliability.
To overcome these challenges, the researchers developed an advanced AI model that integrates satellite, atmospheric, and oceanic data. When applied to tropical cyclone data from the Northwest Pacific between 2020 and 2021, the model demonstrated an impressive accuracy of 92.3 percent while reducing false alarms to 8.9 percent.
The new approach improved forecasting accuracy by nearly 12 percent compared to existing methods and reduced false alarms by threefold, marking a significant breakthrough in cyclone prediction, according to the study.
“This research tackles the issues of low accuracy and high false alarm rates in rapid intensification forecasts,” stated Li Xiaofeng, the study’s corresponding author.
“Our method enhances the understanding of these extreme weather events and strengthens preparedness against their devastating consequences,” Li added.
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