Joint Seminar: Theory, Method, and Implementation of Targeted Observation for Improving Forecasts of High-impact Ocean-Atmospheric Events
High-impact ocean-atmospheric events, such as ENSO, typhoons, Kuroshio large meander and blocking, often result in substantial economic and societal losses on regional or even global scales. Accurately forecasting these events is crucial, yet it remains a persistent challenge. Observations play a pivotal role not only in comprehending these events but also in enhancing predictive capabilities. Targeted observation, an optimized strategy dedicated to numerical forecasting, addresses the critical question of “Where the best observations should be deployed?” Its theoretical foundation relies on the faster growth rate of patterned perturbations in contrast to their random counterparts. Essentially, identifying optimally growing perturbations and locating sensitive areas significantly affecting related prediction results are the key of targeted observation.
Given the complex environments of high-impact ocean-atmospheric events, the conditional non-linear optimal perturbation (CNOP) approach was proposed. This method seeks the optimal perturbation that causes the largest prediction errors at a future time within a fully nonlinear framework. The CNOP-based targeted observations have been widely explored across various fields, including typhoon, ENSO, IOD, Ural blocking, anomalous Kuroshio variations, etc. In Observing System Simulation Experiments (OSSEs), observation arrays built within the CNOP-based sensitive areas have demonstrated noteworthy superiority over conventional observations. Additionally, certain applications, such as targeted observations for predicting typhoons and vertical temperature profiles in the Yellow Sea, have yielded meaningful results in realistic field experiments within Observing System Experiments (OSEs). These findings indicate that the CNOP-based targeted observation is an efficient strategy for enhancing the forecast skills of high-impact ocean-atmospheric events. Its effectiveness and cost-saving properties make it urgently needed. This presentation will introduce the theory of targeted observation, demonstrate related applications using the CNOP approach, and discuss its future prospects and challenges.
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, Distinguished Professor of Fudan University. 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. Director of the Academic Committee of the State Key Laboratory of Numerical Simulation of Atmospheric Sciences and Earth Fluid Dynamics, Director of the Academic Committee of the Key Laboratory of Mesoscale Severe Weather of the Ministry of Education, and Deputy Director of the Academic Committee of the Key Laboratory of Marine Disaster Prediction Technology of the Ministry of Natural Resources. Co-editor of Advances in Atmospheric Sciences and Deputy Editor-in-Chief of Science China: Earth Sciences.
Professor Mu has ever served as convenor of the Atmospheric Science Assessment Group of the Academic Degrees Committee of the State Council, member of the IAMAS Committee on Dynamic Meteorology (ICDM) and the Committee on Planetary Atmospheres and Their Evolution (ICPAE), Associate Editor of Monthly Weather Review for the American Meteorological Society (AMS), and Editorial Board of Quarterly Journal of the Royal Meteorological Society, et al.
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.