A useful approach to sensitivity and predictability studies in geophysical fluid dynamics: conditional non-linear optimal perturbation
文献类型：CNKI期刊论文
| 作者 | Qiang Wang; Mu Mu; Guodong Sun |
| 发表日期 | 2020-01-15 |
| 出处 | National Science Review
 |
| 关键词 | CNOP non-linear optimization atmosphere ocean |
| 英文摘要 | In atmospheric and oceanic studies, it is important to investigate the uncertainty of model solutions. The conditional non-linear optimal perturbation(CNOP) method is useful for addressing the uncertainty. This paper reviews the development of the CNOP method and its computational aspects in recent years.Specifically, the CNOP method was first proposed to investigate the effects of the optimal initial perturbation on atmosphere and ocean model results. Then, it was extended to explore the influences of the optimal parameter perturbation, model tendency perturbation and boundary condition perturbation. To obtain solutions to these optimal perturbations, four kinds of optimization approaches were developed: the adjoint-based method, the adjoint-free method, the intelligent optimization method and the unconstrained optimization method. We illustrate the calculation process of each method and its advantages and disadvantages. Then, taking the Zebiak–Cane model as an example, we compare the CNOPs related to initial conditions(CNOP-Is) calculated by the above four methods. It was found that the dominant structures of the CNOP-Is for different methods are similar, although some differences in details exist.Finally, we discuss the necessity and possible direction for designing a more effective optimization approach related to the CNOP in the future. |
| 文献子类 | CNKI期刊论文 |
| 资助机构 | supported by the National Natural Science Foundation of China(41576015) ; the Qingdao National Laboratory for Marine Science and Technology(QNLM2016ORP0107) ; the Strategic Priority Research Program of Chinese Academy of Sciences(XDA20060502) ; the NSFC Innovative Group(41421005) ; the National Programme on Global Change and AirSea Interaction(GASI-IPOVAI-06) ; the NSFC-Shandong Joint Fund for Marine Science Research Centers(U1606402) ; the Youth Innovation Promotion Association,Chinese Academy of Sciences(2015060) |
| 卷 | v.7期:01页:219-228 |
| 语种 | 英文; |
| 分类号 | P73;P40 |
| ISSN号 | 2095-5138 |
| 源URL | [http://ir.qdio.ac.cn/handle/337002/188350]  |
| 专题 | 中国科学院海洋研究所 |
| 作者单位 | 1.CenterforOceanMega-Science,ChineseAcademyofSciences 2.CASKeyLaboratoryofOceanCirculationandWaves,InstituteofOceanology,ChineseAcademyofSciences 3.PilotNationalLaboratoryforMarineScienceandTechnology(Qingdao) 4.DepartmentofAtmosphericandOceanicSciences,InstituteofAtmosphericSciences,FudanUniversity 5.LASG,InstituteofAtmosphericPhysics,ChineseAcademyofSciences 6.UniversityofChineseAcademyofSciences |
| 推荐引用方式 GB/T 7714 | Qiang Wang,Mu Mu,Guodong Sun. A useful approach to sensitivity and predictability studies in geophysical fluid dynamics: conditional non-linear optimal perturbation. 2020. |
入库方式： OAI收割
来源：海洋研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。