IOCAS-IR  > 海洋环流与波动重点实验室
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
Source PublicationTHEORETICAL AND APPLIED CLIMATOLOGY
Volume128Issue:3-4Pages:587-601
SubtypeArticle
AbstractAn 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
Indexed BySCI
Language英语
WOS IDWOS:000399702200008
Citation statistics
Cited Times:6[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Version出版稿
Identifierhttp://ir.qdio.ac.cn/handle/337002/136694
Collection海洋环流与波动重点实验室
Affiliation1.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
Recommended Citation
GB/T 7714
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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