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Application of Nonlinear Local Lyapunov Exponents in Predictability and Ensemble Forecast Research
Time:2023-11-20Keywords: Source of article:Pageviews:38

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Presentation Title

Application of Nonlinear Local Lyapunov Exponents in Predictability and Ensemble Forecast Research   


Time

November 27, 2023 (Monday) 10:00 a.m.-11:30 a.m.   


Contents

The uncertainty of initial conditions and external forcing conditions, and the resulting uncertainty in forecast results, are the two types of predictability issues of greatest concern in practical weather and climate forecast. These issues are categorized as the first and second types of predictability issues, respectively. To address these two predictability issues, we propose the Nonlinear Local Lyapunov Exponents (NLLE) method, which can characterize the average error growth of nonlinear systems over a finite time and provide a quantitative estimate of the predictability limit of nonlinear systems. For highly nonlinear atmospheric and oceanic systems, the NLLE method not only theoretically surpasses the linear constraints found in methods like Lyapunov exponents but also directly employs observational data to quantitatively assess the actual predictability of the atmosphere and oceans, thus addressing the limitations associated with predictability estimates relying on numerical models. Additionally, to tackle the uncertainty in initial conditions and external forcing conditions, we put forth a new method for ensemble forecast initial perturbations using Nonlinear Local Lyapunov Vectors (NLLV). This method preserves the benefits of singular vector (SV) and breeding vector (BV) methods while rectifying their drawbacks. Moreover, this method not only enhances the forecast skills of ensemble forecasts but also saves a significant amount of computation time. It provides an ensemble field of perturbations that can better reflect the uncertainty of initial conditions for ensemble forecasts.


About the Honored Guest

Ding Ruiqiang, professor and doctoral supervisor at Beijing Normal University, is a recipient of the National Science Fund for Distinguished Young Scholars of China. Currently, he serves as a member of the International Commission on Climate (ICCL), a Regular Associate of the International Centre for Theoretical Physics (ICTP), a member of the China National Committee for the International Association of Meteorology and Atmospheric Sciences (IAMAS), and a member of the Tropical and Oceanic Meteorology Committee of the China Meteorological Society. He has earned awards such as the First Early Career Scientist Awards of IUGG and the Lu Jiaxi Young Talent Award from the Chinese Academy of Sciences. He is primarily engaged in research on areas such as weather and climate predictability, ensemble forecast, and air-sea interaction. He has attained systematic innovative achievements in new methods and applications of predictability and ensemble forecast. The Nonlinear Local Lyapunov Exponents (NLLE) method he proposed has been widely applied by scholars at home and abroad in research on predictability, nonlinear dynamics, and ensemble forecast. He has published over 120 SCI papers, including more than 70 papers as the first/corresponding author (including two in Nature Communications). He has championed projects such as the National Key Research and Development Program, the China Meteorological Administration's Public Welfare (Meteorology) Industry Special Project, and General Projects and Youth Fund Projects from the National Natural Science Foundation of China (NSFC).  


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