Lagrangian model of zooplankton dispersion:numerical schemes comparisons and parameter sensitivity tests
文献类型:CNKI期刊论文
作者 | Qiu ZF(丘仲锋); Andrea M.DOGLIOLI; He YJ(何宜军); Francois CARLOTTI |
发表日期 | 2011-03-15 |
出处 | Chinese Journal of Oceanology and Limnology
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关键词 | Lagrangian numerical scheme time steps zooplankton |
英文摘要 | This paper presents two comparisons or tests for a Lagrangian model of zooplankton dispersion:numerical schemes and time steps.Firstly,we compared three numerical schemes using idealized circulations.Results show that the precisions of the advanced Adams-Bashfold-Moulton(ABM) method and the Runge-Kutta(RK) method were in the same order and both were much higher than that of the Euler method.Furthermore,the advanced ABM method is more efficient than the RK method in computational memory requirements and time consumption.We therefore chose the advanced ABM method as the Lagrangian particle-tracking algorithm.Secondly,we performed a sensitivity test for time steps,using outputs of the hydrodynamic model,Symphonie.Results show that the time step choices depend on the fluid response time that is related to the spatial resolution of velocity fields.The method introduced by Oliveira et al.in 2002 is suitable for choosing time steps of Lagrangian particle-tracking models,at least when only considering advection. |
文献子类 | CNKI期刊论文 |
资助机构 | Supported by the Project Lagrangian Zooplankton Computation and Experiment (CNRS Programme EC2CO) ; the National Natural Science Fundation of China (Nos. 40821004,40706059) |
卷 | v.29期:02页:208-215 |
语种 | 英文; |
分类号 | Q958.8 |
ISSN号 | 0254-4059 |
源URL | [http://ir.qdio.ac.cn/handle/337002/191766] ![]() |
专题 | 中国科学院海洋研究所 |
作者单位 | 1.KeyLaboratoryofOceanCirculationandWaves,InstituteofOceanologyCAS 2.Laboratoired'OcanographiePhysiqueetBiogochimie,AixMarseilleUniversite,CNRS,UMR6535,Marseille,France |
推荐引用方式 GB/T 7714 | Qiu ZF,Andrea M.DOGLIOLI,He YJ,et al. Lagrangian model of zooplankton dispersion:numerical schemes comparisons and parameter sensitivity tests. 2011. |
入库方式: OAI收割
来源:海洋研究所
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