[Seminar on April 7] Machine-learning Facilitates Numerical Modeling of Weather and Climate
Prof. Wei-Chyung Wang
University at Albany,
State University of New York
9:30 April 7, 2024
Abstract:
The numerical models, based on the solutions of the fundamental equations governing the dynamics, physics, and chemistry of the Earth's surface-atmosphere system, are considered the "best" available tools for studying weather and climate. In recent years, machine-learning method which automatically extract spatiotemporal features in data and reveal physical associations show promising prospect in many applications. Here, I used our studies related to model “prediction, physical parameterization, and diagnosis” to illustrate its usefulness in facilitating further development and application of numerical models.
Bio:
Wei-Chyung Wang is Professor of Applied Sciences at the University at Albany, State University of New York (SUNY), and a member of Norwegian Academy of Science and Letters. He received Doctor of Engineering Sciences from Columbia University studying the radiative effect of atmospheric aerosols, and has been using models and observations to study the climate effects of atmospheric greenhouse gases, ozone, and aerosols. His current research focuses on atmospheric aerosol-cloud-radiation-climate interactions, and extreme weather. During 1987-2019, Professor Wang has been serving as the U.S. Chief Scientist for the “Climate Sciences” agreement between the U. S. Department of Energy and the China’s Ministry of Sciences and Technology, in which one unique task is to use the historical documents of the past 2,000 years in China for climate reconstruction. He was awarded by SUNY-Albany in 1994 for Excellence in Research and by European Physical Society/Balkan Physical Union in 2002 for Scientific Achievements in Environmental Physics. His research Interests include modeling and observational studies of climate changes due to changes in atmospheric constituents (gases and aerosols) and the effects of global warming on weather extremes (snow storms, heat waves, heavy rainfall). So far, Prof. Wang has more than 180 publications over 30-refereed journals (including Nature and Science).
