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

CORC > 海洋研究所 > 中国科学院海洋研究所 > 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, Guodong 1; Mu, Mu 1,2
刊名	THEORETICAL AND APPLIED CLIMATOLOGY
	2017-05-01
卷号	128 期号:3-4 页码:587-601
英文摘要	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.
收录类别	SCI
语种	英语
WOS记录号	WOS:000399702200008
内容类型	期刊论文
版本	出版稿
源URL	[http://ir.qdio.ac.cn/handle/337002/136694]
专题	海洋研究所_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
推荐引用方式 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.