Optimization of the Spatiotemporal Parameters in a Dynamical Marine Ecosystem Model Based on the Adjoint AssimilationReport as inadecuate




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Mathematical Problems in EngineeringVolume 2013 2013, Article ID 373540, 12 pages

Research Article

Laboratory of Physical Oceanography, Ocean University of China, Qingdao 266100, China

Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China

Key Laboratory of Marine Spill Oil Identification and Damage Assessment Technology, The organaization of North China Sea Monitoring Center, Qingdao 266033, China

Key Laboratory of Ocean Circulation and Waves, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China

Received 15 January 2013; Accepted 28 April 2013

Academic Editor: Ker-Wei Yu

Copyright © 2013 Xiaoyan Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

By utilizing spatiotemporal biological parameterizations, the adjoint variational method was applied to a 3D marine ecosystem dynamical model. The results of twin experiments demonstrated that the mean absolute error MAE of phytoplankton in the surface layer and the reduced cost function RCF could be used to evaluate both the simulation results and parameter estimation. Spatiotemporal variation of key parameters KPs was optimized in real experiments. The RCF and MAE in each assimilation period 72 periods per year decreased obviously. The spatially varying KP KPS, temporally varying KP KPT, and constant KP KPC were obtained by averaging KPs of spatiotemporal variation. Another type of spatiotemporal KP KPST was represented by KPS, KPT, and KPC. The correlation analysis of KPs, either KPS or KPT, accorded with the real ecological mechanism. Running the model with KPS, KPT, KPC, and KPST, respectively, we found that MAE was the minimum when KPs were spatiotemporal variation KPST, while MAE reached its maximum when KPs were constant KPC. Using spatiotemporal KPs could improve simulation precision compared with only using spatially varying KPs, temporally varying KPs, or constant KPs these forms are the results in a previous study. KPST, a representation of spatiotemporal variation, reduces the variable number in calculation.





Author: Xiaoyan Li, Chunhui Wang, Wei Fan, and Xianqing Lv

Source: https://www.hindawi.com/



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