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A new approach to identify the sensitivity and importance of physical parameters combination within numerical models using the Lund-Potsdam-Jena (LPJ) model as an example
Sun, Guodong1; Mu, Mu1,2
2017-05-01
发表期刊THEORETICAL AND APPLIED CLIMATOLOGY
卷号128期号:3-4页码:587-601
文章类型Article
摘要An important source of uncertainty, which causes further uncertainty in numerical simulations, is that residing in the parameters describing physical processes in numerical models. Therefore, finding a subset among numerous physical parameters in numerical models in the atmospheric and oceanic sciences, which are relatively more sensitive and important parameters, and reducing the errors in the physical parameters in this subset would be a far more efficient way to reduce the uncertainties involved in simulations. In this context, we present a new approach based on the conditional nonlinear optimal perturbation related to parameter (CNOP-P) method. The approach provides a framework to ascertain the subset of those relatively more sensitive and important parameters among the physical parameters. The Lund-Potsdam-Jena (LPJ) dynamical global vegetation model was utilized to test the validity of the new approach in China. The results imply that nonlinear interactions among parameters play a key role in the identification of sensitive parameters in arid and semi-arid regions of China compared to those in northern, northeastern, and southern China. The uncertainties in the numerical simulations were reduced considerably by reducing the errors of the subset of relatively more sensitive and important parameters. The results demonstrate that our approach not only offers a new route to identify relatively more sensitive and important physical parameters but also that it is viable to then apply "target observations" to reduce the uncertainties in model parameters.
DOI10.1007/s00704-015-1690-9
收录类别SCI
语种英语
WOS记录号WOS:000399702200008
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文献类型期刊论文
版本出版稿
条目标识符http://ir.qdio.ac.cn/handle/337002/136694
专题海洋环流与波动重点实验室
作者单位1.Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing 100029, Peoples R China
2.Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Circulat & Waves, Qingdao 266071, Peoples R China
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Sun, Guodong,Mu, Mu. A new approach to identify the sensitivity and importance of physical parameters combination within numerical models using the Lund-Potsdam-Jena (LPJ) model as an example[J]. THEORETICAL AND APPLIED CLIMATOLOGY,2017,128(3-4):587-601.
APA Sun, Guodong,&Mu, Mu.(2017).A new approach to identify the sensitivity and importance of physical parameters combination within numerical models using the Lund-Potsdam-Jena (LPJ) model as an example.THEORETICAL AND APPLIED CLIMATOLOGY,128(3-4),587-601.
MLA Sun, Guodong,et al."A new approach to identify the sensitivity and importance of physical parameters combination within numerical models using the Lund-Potsdam-Jena (LPJ) model as an example".THEORETICAL AND APPLIED CLIMATOLOGY 128.3-4(2017):587-601.
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