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DOI10.1007/s11430-016-9065-9
A study of parameter uncertainties causing uncertainties in modeling a grassland ecosystem using the conditional nonlinear optimal perturbation method
Sun GuoDong1,4; Xie DongDong1,2,3
通讯作者Sun GuoDong
来源期刊SCIENCE CHINA-EARTH SCIENCES
ISSN1674-7313
EISSN1869-1897
出版年2017
卷号60期号:9页码:1674-1684
英文摘要

In this paper, we apply the approach of conditional nonlinear optimal perturbation related to the parameter (CNOP-P) to study parameter uncertainties that lead to the stability (maintenance or degradation) of a grassland ecosystem. The maintenance of the grassland ecosystem refers to the unchanged or increased quantity of living biomass and wilted biomass in the ecosystem, and the degradation of the grassland ecosystem refers to the reduction in the quantity of living biomass and wilted biomass or its transformation into a desert ecosystem. Based on a theoretical five-variable grassland ecosystem model, 32 physical model parameters are selected for numerical experiments. Two types of parameter uncertainties could be obtained. The first type of parameter uncertainty is the linear combination of each parameter uncertainty that is computed using the CNOP-P method. The second type is the parameter uncertainty from multi-parameter optimization using the CNOP-P method. The results show that for the 32 model parameters, at a given optimization time and with greater parameter uncertainty, the patterns of the two types of parameter uncertainties are different. The different patterns represent physical processes of soil wetness. This implies that the variations in soil wetness (surface layer and root zone) are the primary reasons for uncertainty in the maintenance or degradation of grassland ecosystems, especially for the soil moisture of the surface layer. The above results show that the CNOP-P method is a useful tool for discussing the abovementioned problems.


英文关键词Parameter optimization Grassland ecosystem Simulation Conditional nonlinear optimal perturbation
类型Article
语种英语
国家Peoples R China
收录类别SCI-E
WOS记录号WOS:000409376600010
WOS关键词BOUND-CONSTRAINED OPTIMIZATION ; SPRING PREDICTABILITY BARRIER ; NET PRIMARY PRODUCTION ; ABRUPT TRANSITIONS ; CLIMATE-CHANGE ; EASTERN CHINA ; LPJ MODEL ; VEGETATION ; ALGORITHM ; EVENTS
WOS类目Geosciences, Multidisciplinary
WOS研究方向Geology
来源机构兰州大学 ; 中国科学院大气物理研究所
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/202180
作者单位1.Chinese Acad Sci, Inst Atmospher Phys, State Key Lab Numer Modeling Atmospher Sci & Geop, Beijing 100029, Peoples R China;
2.95915 Unit, Tianjin 301612, Peoples R China;
3.Lanzhou Univ, Coll Atmospher Sci, Key Lab Semiarid Climate Change, Minist Educ, Lanzhou 730000, Peoples R China;
4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714
Sun GuoDong,Xie DongDong. A study of parameter uncertainties causing uncertainties in modeling a grassland ecosystem using the conditional nonlinear optimal perturbation method[J]. 兰州大学, 中国科学院大气物理研究所,2017,60(9):1674-1684.
APA Sun GuoDong,&Xie DongDong.(2017).A study of parameter uncertainties causing uncertainties in modeling a grassland ecosystem using the conditional nonlinear optimal perturbation method.SCIENCE CHINA-EARTH SCIENCES,60(9),1674-1684.
MLA Sun GuoDong,et al."A study of parameter uncertainties causing uncertainties in modeling a grassland ecosystem using the conditional nonlinear optimal perturbation method".SCIENCE CHINA-EARTH SCIENCES 60.9(2017):1674-1684.
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