[OCES Seminar] Recent Advances in AI-Based Ocean Forecasting
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Artificial Intelligence (AI), as a driving force of the new wave of technological revolution and industrial transformation, is demonstrating tremendous potential in the field of oceanography. Its integration with large-scale observational datasets is revolutionizing traditional modeling approaches, enabling more reliable and efficient extraction of valuable information from complex, multi-source observations. This data-driven paradigm is empowering researchers to explore fundamental oceanic elements and a wide range of dynamic processes in greater depth.
In this talk, we will provide a comprehensive overview of the latest applications of AI in ocean forecasting. Topics will include time-series prediction, mapping from two-dimensional spatial data to one-dimensional point sequences, and forecasting based on image sequences and visual signals. We will highlight recent advances in the prediction of small-scale internal solitary waves, mesoscale typhoons, large-scale equatorial instability waves, sea ice dynamics, and short-term rainfall. The presentation will also discuss the development of next-generation ocean forecast large model - LangYa. These advances not only offer powerful tools for oceanographic research but also enhance our ability to understand and predict diverse oceanic phenomena across multiple scales.
Dr. Xiaofeng Li received the bachelor’s degree in optical engineering from Zhejiang University, Hangzhou, China, in 1985 and the Ph.D. degree in physical oceanography from North Carolina State University, Raleigh, NC, USA, in 1997. From 1997 to 2019, he was with the National Ocean and Atmospheric Administration (NOAA), Washington, DC, USA, where he was involved in developing many operational satellite ocean remote sensing products. He is currently with the Institute of Oceanology, Chinese Academy of Sciences, Qingdao, China. His research interests include synthetic aperture radar applications in oceanography and marine meteorology, the application of artificial intelligence in oceanographic studies, big data analytics, and satellite image processing.
Dr. Li currently serves as an Editor for JGR: Machine Learning and Computation and as an Associate Editor for IEEE Transactions on Geoscience and Remote Sensing. He is a Fellow of both the IEEE and the U.S. Electromagnetics Academy. His scholarly contributions include three published books and over 200 peer-reviewed SCI journal articles.