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

作　　者：GAO Yongli MU Mu ZHANG Kun 

机构地区：[1]Key Laboratory of Ocean Circulation and Waves,Institute of Oceanology,Chinese Academy of Sciences,Qingdao 266071,China [2]University of Chinese Academy of Sciences,Beijing 100049,China [3]College of Science,China University of Petroleum(East China),Qingdao 266580,China [4]Institute of Atmospheric Sciences,Fudan University,Shanghai 200433,China [5]Qingdao National Laboratory for Marine Science and Technology,Qingdao 266237,China [6]Center for Ocean Mega-Science,Chinese Academy of Sciences,Qingdao 266071,China

出　　处：《Journal of Oceanology and Limnology》2020年第5期1382-1393,共12页海洋湖沼学报（英文）

基　　金：Supported by the Qingdao National Laboratory for Marine Science and Technology(No.2016OPR0107);the National Natural Science Foundation of China(No.41806013)。

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 eff ects 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 specifi cally.The most sensitive parameter(background turbidity)aff ects the light supply for DCM formation,whereas the other three parameters(nutrient content of phytoplankton,nutrient recycling coeffi cient,and vertical turbulent diff usivity)control nutrient supply.To explore the interactions among diff erent 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 diff erences.Finally,we found that reducing the uncertainties of sensitive parameters could improve DCM simulations remarkably.Compared with the sensitive parameters identifi ed 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 

分 类 号：X145[环境科学与工程—环境科学] P73[天文地球—海洋科学]