Professor Zhang Changjiang from the School of Electronics and Information Engineering of TU was invited to participate in the 21st National Workshop on Tropical Cyclones (NWTC-XXI) held in Changsha, Hunan Province. At a specially convened session on “AI + Typhoons,” Professor Zhang delivered an academic presentation titled “Deep Learning and Wavelet Transform Combined with Multi-Channel Satellite Images for Tropical Cyclone Intensity Estimation.” The presentation showcased the latest research achievements of our university in the field of intelligent tropical cyclone monitoring and early warning, garnering significant attention from conference participants.

Professor Zhang delivers a presentation

Co-sponsored by the Chinese Meteorological Society and the Shanghai Typhoon Institute of the China Meteorological Administration, the conference was organized by the Typhoon Committee of the Chinese Meteorological Society and the Asia-Pacific Typhoon Collaborative Research Center, with support from the Hunan Provincial Meteorological Bureau and the College of Meteorology and Oceanography at the National University of Defense Technology.

Representatives were specially invited from the ESCAP/WMO Typhoon Committee, the WMO Regional Office, the Macao Meteorological and Geophysical Bureau, and the Hong Kong Observatory. The specially arranged “AI + Typhoons” session and its accompanying roundtable forum became focal points of the event. Discussions centered on topics such as “Seamlessly Integrating Physical Laws with AI,” “Future Directions for AI Method Development,” and “Opportunities and Challenges of AI for Typhoon Research and Operations.”

Experts highlighted that the rapid advancement of AI technology presents both new opportunities and challenges for typhoon forecasting. AI can effectively address the limitations of traditional numerical models in data processing and rapid scenario projection. By utilizing machine learning to uncover patterns within historical typhoon data and integrating multi-source observational information, AI holds promise for breaking through existing “forecasting blind spots.”

Attendees also engaged in multi-dimensional discussions focusing on five core themes: “Key Technologies for Typhoon Monitoring, Forecasting, and Early Warning,” “Typhoon Mechanisms and Modeling Research,” “Typhoon Disaster Impact Assessment and Risk Prevention,” “Typhoon Observation and Data Compilation,” and “Typhoon Climatology and Climate Change.”

The “National Workshop on Tropical Cyclones” has been a bellwether in China’s typhoon science and technology sector since its inception in 1972. Held every two to four years, this conference series aims to establish a national platform for cooperation and exchange within the typhoon research community. It facilitates concentrated discussions on cutting-edge topics and hot issues in the field, promotes talent development and the translation of research into practical applications, and drives progress in typhoon science and operational forecasting technology.

Professor Zhang Changjiang at the Conference

At the conference, Professor Zhang Changjiang provided an in-depth exploration of tropical cyclone intensity estimation using multi-channel satellite data combined with deep learning techniques. He proposed a novel method for intensity estimation by fusing infrared, water vapor, and microwave data with deep learning and wavelet transform. This achievement offers a new approach for objective and intelligent tropical cyclone intensity estimation, providing valuable technical support for typhoon disaster prevention and mitigation efforts in China.

Zhang’s research attracted considerable interest from conference experts, particularly representatives from the National Meteorological Center and the Typhoon and Marine Meteorology Forecast Center of the China Meteorological Administration. These experts recognized the significance of the findings for enhancing the level of objective intensity estimation and forecasting of tropical cyclones in China. This academic exchange further elevated the influence of our university within the academic community and demonstrated its strength in applied fundamental research and frontier exploration.