典型文献
Recent Progress in Applications of the Conditional Nonlinear Optimal Perturbation Approach to Atmosphere-Ocean Sciences
文献摘要：
The conditional nonlinear optimal perturbation(CNOP for short)approach is a powerful tool for predictability and targeted observation studies in atmosphere-ocean sciences.By fully considering nonlinearity under appropriate physical constraints,the CNOP approach can reveal the optimal perturbations of initial conditions,boundary con-ditions,model parameters,and model tendencies that cause the largest simulation or prediction uncertainties.This paper reviews the progress of applying the CNOP approach to atmosphere-ocean sciences during the past five 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 analy-sis,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.
文献关键词：
中图分类号：
作者姓名：
Mu MU;Kun ZHANG;Qiang WANG
作者机构：
Department of Atmospheric and Oceanic Sciences and Institute of Atmospheric Sciences,Fudan Univer-sity,Shanghai 200438,China;CMA-FDU Joint Laboratory of Marine Meteorology,Shanghai 200438,China;Shanghai Frontiers Science Center of Atmosphere-Ocean Interaction,Shanghai 200438,China;CAS Key Laboratory of Ocean Circulation and Waves,Institute of Oceanology,Chinese Academy of Sciences and Qingdao National Laboratory for Marine Science and Technology,Qingdao 266071,China;Key Laboratory of Marine Hazards Forecasting,Ministry of Natural Resources,Hohai University,Nan-jing 210098,China;College of Oceanography,Hohai University,Nanjing 210098,China
文献出处：
引用格式：
[1]Mu MU;Kun ZHANG;Qiang WANG-.Recent Progress in Applications of the Conditional Nonlinear Optimal Perturbation Approach to Atmosphere-Ocean Sciences)[J].数学年刊B辑（英文版）,2022(06):1033-1048
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Recent,Progress,Applications,Conditional,Nonlinear,Optimal,Perturbation,Approach,Atmosphere,Ocean,Sciences,conditional,optimal,CNOP,short,approach,powerful,tool,predictability,targeted,observation,studies,atmosphere,ocean,sciences,By,fully,considering,nonlinearity,under,appropriate,physical,constraints,can,reveal,perturbations,initial,conditions,boundary,model,parameters,tendencies,that,largest,simulation,prediction,uncertainties,This,paper,reviews,progress,applying,during,past,five,years,Following,introduction,algorithm,developments,solving,are,discussed,Then,recent,applications,including,some,high,impact,atmospheric,environmental,events,ensemble,forecast,sensitivity,analy,sis,uncertainty,estimation,caused,by,errors,tendency,reviewed,Finally,summary,discussion,future,challenges,presented
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0.642555
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