Advancements in Weather Forecasting with AI

A groundbreaking artificial intelligence (AI) model has recently been deployed at the Hong Kong Observatory and the National Meteorological Centre in mainland China. This innovative system utilizes machine learning algorithms to enhance the accuracy of weather forecasts, particularly in predicting when a typhoon will rapidly intensify. The ability to forecast such events is crucial for ensuring public safety and minimizing disruptions caused by severe weather conditions.

Li Qinglan, a professor at the Shenzhen Institutes of Advanced Technology (SIAT), who is leading the project, mentioned that the system was installed around three weeks ago and has already provided real-time updates on the progression of Typhoon Jangmi. Jangmi, which formed late last month and made landfall in Japan on June 3, had significant impacts on air travel, forcing carriers like Cathay Pacific Airways and Hong Kong Airlines to cancel or reschedule flights to Japan.

The Hong Kong Observatory has predicted that the region will experience between four to seven typhoons between now and October. They have also warned that some of these typhoons could become super typhoons due to the El Nino phenomenon. Forecasting rapid intensification, which involves a tropical cyclone's maximum sustained winds increasing by 15 metres per second within a 24-hour period, or by 10m/s within 12 hours, has long been one of the most challenging aspects of meteorology.

"Rapid intensification rarely happens, and is highly unpredictable, making preventive measures and responses extremely likely to be delayed," Li said in a statement issued by SIAT last week. SIAT is affiliated with the Chinese Academy of Sciences.

Traditional numerical weather prediction technology has struggled to accurately reflect the evolution of typhoon intensity, while statistical-dynamic methods have failed to capture the non-linear characteristics of typhoon intensity changes.

The new model uses machine learning, a field of AI where algorithms learn the patterns of given data and make predictions about new ones. Li's team, which started research on typhoon intensity in 2013, integrated four types of machine learning algorithms to improve forecast accuracy. They used the model to simulate results for 24-hour rapid intensification in the North Atlantic Ocean between 2016 and 2020. Compared with forecasts from the US National Hurricane Centre (NHC), it "achieved a higher hit rate and a lower false alarm rate," SIAT said.

Wong Wai-kin, a senior scientific officer working on forecast development at the observatory, stated that the team would continue to use real-time data to evaluate the model's performance. He noted that the observatory uses a variety of AI tools to support weather forecasting, with some forecast products powered by AI models made available to the public on its Earth Weather web portal.

The United States has also been developing AI for weather forecasting. The NHC said on its website that it had teamed up with Google DeepMind to develop a new AI hurricane forecast model, which was used experimentally last year.

Chinese meteorologists have also used AI in other areas. Two years ago, the Shanghai AI Laboratory, Hong Kong University of Science and Technology, and other organizations launched FengWu-GHR, an advanced, AI-driven global high-resolution weather forecasting model that extended the effective forecast lead time by 12 hours to 11.25 days.

Li mentioned that her team is also working on the use of AI for forecasting strong winds, heavy rain, and storm surges. This ongoing research highlights the growing role of AI in improving weather prediction and disaster preparedness.