Nansen Guest Lecture 10.07.2024

Prof. Mu Mu, Academician of the Chinese Academy of Sciences, Fudan University, China

Conditional Nonlinear Optimal Perturbation and its application in the investigations of weather and climate predictability

In atmospheric and oceanic studies, it is important to investigate the uncertainty of model solutions. By fully considering nonlinearity under appropriate physical constraints, the conditional nonlinear optimal perturbation (CNOP) approach was proposed to reveal the optimal perturbations of initial conditions, boundary conditions, model parameters, and model tendencies that cause the largest simulation or prediction uncertainties. This talk reviews the progress of applying the CNOP approach to atmosphere-ocean sciences during the past years. Following an introduction of the CNOP approach, the algorithm developments for solving the CNOP are discussed. Then, recent CNOP applications, including predictability studies of some high-impact ocean-atmospheric environmental events, ensemble forecast, parameter sensitivity analysis, uncertainty estimation caused by errors of model tendency or boundary condition, are reviewed. Finally, a summary and discussion on future applications and challenges of the CNOP approach are presented.

When and where?

Wednesday, the 10.07.24, at 10:00 – 10:45.

Copernicus lecture room, 1st floor, Nansen Center, Jahnebakken 3, Bergen

About Prof. Mu Mu 

Prof. Mu Mu, Academician of the Chinese Academy of Sciences, Academician of the Academy of Sciences for the Developing World (TWAS), member of the Chinese Society of Industrial and Applied Mathematics, member of the Chinese Operations Research Society. He is currently a member of the Executive Committee of the International Association of Meteorology and Atmospheric Sciences (IAMAS), Chairman of the IAMAS Committee of China, and a member of the 8th Expert Advisory Committee of the Earth Science Department of the National Natural Science Foundation of China. Professor Mu is also one of the first winners of the “National Science Foundation for Distinguished Young Scholars”. He has won the Ho Leung Ho Lee Foundation for Science and Technology Progress Award, the First Class Prize of Nature Scientific Award of Chinese Academy of Sciences, the Chinese Academy of Sciences “Procter & Gamble Excellent Graduate Tutor” award. His research interests include predictability of weather and climate, data assimilation, ensemble prediction and adaptive observation, and nonlinear stability and instability problems in geophysical fluid dynamics.