Impacts of parameter uncertainties on deep chlorophyll maximum simulation revealed by the CNOP-P approach

doi:10.1007/s00343-020-0020-y

IOCAS-IR > 海洋环流与波动重点实验室

	Impacts of parameter uncertainties on deep chlorophyll maximum simulation revealed by the CNOP-P approach
	Gao Yongli 1,2,3; Mu Mu 4; Zhang Kun1,5,6
	2020-06-07
发表期刊	JOURNAL OF OCEANOLOGY AND LIMNOLOGY
ISSN	2096-5508
页码	12
通讯作者	Zhang Kun(kzhang@qdio.ac.cn)
摘要	Parameter uncertainty is a primary source of uncertainty in ocean ecosystem simulations. The deep chlorophyll maximum (DCM) is a ubiquitous ecological phenomenon in the ocean. Using a theoretical nutrients-phytoplankton model and the conditional nonlinear optimal perturbation approach related to parameters, we investigated the effects of parameter uncertainties on DCM simulations. First, the sensitivity of single parameter was analyzed. The sensitivity ranking of 10 parameters was obtained by analyzing the top four specifically. The most sensitive parameter (background turbidity) affects the light supply for DCM formation, whereas the other three parameters (nutrient content of phytoplankton, nutrient recycling coefficient, and vertical turbulent diffusivity) control nutrient supply. To explore the interactions among different parameters, the sensitivity of multiple parameters was further studied by examining combinations of four parameters. The results show that background turbidity is replaced by the phytoplankton loss rate in the optimal parameter combination. In addition, we found that interactions among these parameters are responsible for such differences. Finally, we found that reducing the uncertainties of sensitive parameters could improve DCM simulations remarkably. Compared with the sensitive parameters identified in the single parameter analysis, reducing parameter uncertainties in the optimal combination produced better model performance. This study shows the importance of nonlinear interactions among various parameters in identifying sensitive parameters. In the future, the conditional nonlinear optimal perturbation approach related to parameters, especially optimal parameter combinations, is expected to greatly improve DCM simulations in complex ecosystem models.
关键词	deep chlorophyll maximum (DCM) simulation parameter uncertainty conditional nonlinear optimal perturbation related to parameters (CNOP-P) sensitivity
DOI	10.1007/s00343-020-0020-y
收录类别	SCI
语种	英语
资助项目	Qingdao National Laboratory for Marine Science and Technology[2016OPR0107] ; National Natural Science Foundation of China[41806013]
WOS研究方向	Marine & Freshwater Biology ; Oceanography
WOS类目	Limnology ; Oceanography
WOS记录号	WOS:000538711200001
出版者	SCIENCE PRESS
引用统计	被引频次：2[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.qdio.ac.cn/handle/337002/167757
专题	海洋环流与波动重点实验室
通讯作者	Zhang Kun
作者单位	1.Chinese Acad Sci, Inst Oceanol, Key Lab Ocean Circulat & Waves, Qingdao 266071, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.China Univ Petr East China, Coll Sci, Qingdao 266580, Peoples R China 4.Fudan Univ, Inst Atmospher Sci, Shanghai 200433, Peoples R China 5.Qingdao Natl Lab Marine Sci & Technol, Qingdao 266237, Peoples R China 6.Chinese Acad Sci, Ctr Ocean Megasci, Qingdao 266071, Peoples R China
第一作者单位	海洋环流与波动重点实验室
通讯作者单位	海洋环流与波动重点实验室; 中国科学院海洋大科学研究中心
推荐引用方式 GB/T 7714	Gao Yongli,Mu Mu,Zhang Kun. Impacts of parameter uncertainties on deep chlorophyll maximum simulation revealed by the CNOP-P approach[J]. JOURNAL OF OCEANOLOGY AND LIMNOLOGY,2020:12.
APA	Gao Yongli,Mu Mu,&Zhang Kun.(2020).Impacts of parameter uncertainties on deep chlorophyll maximum simulation revealed by the CNOP-P approach.JOURNAL OF OCEANOLOGY AND LIMNOLOGY,12.
MLA	Gao Yongli,et al."Impacts of parameter uncertainties on deep chlorophyll maximum simulation revealed by the CNOP-P approach".JOURNAL OF OCEANOLOGY AND LIMNOLOGY (2020):12.

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