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Improved state estimations of lower trophic ecosystems in the global ocean based on a Green's function approach

机译:基于格林函数法的全球海洋中低层营养生态系统状态的改进估计

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摘要

A lower trophic ecosystem model, which was originally developed for describing the variability in plankton distribution in the western North Pacific, is applied to the global ocean. A realistic time series of dynamically self-consistent circulation fields obtained by a 4-dimensional variational ocean data assimilation experiment is used for the environmental fields in the ecosystem model. An optimization of the bio-ecological parameter values in 40 provinces by a Green's function approach enables the ecosystem model to represent the observed variabilities of nutrients and surface chlorophyll concentration with a relatively small number (11) of compartments. In addition, artificial trends of the ecosystem variables due to model errors are generally suppressed by the optimization. The obtained parameter values and ecosystem fields are generally consistent with observations in terms of assimilated and non-assimilated metrics. The integrated lower-trophic ecosystem and physical fields in the global ocean offer important information on the mechanisms (such as El Ninos) responsible for the seasonal-interannual variability in the lower trophic ecosystem. Our results demonstrate that, with adequate parameter sets capable of modifying indirectly the model and significance of each pathway to reflect the characteristics of local species, a simple ecosystem model can be applied in quantitative analyses to enhance our understanding of the influence of climate variations on the ocean ecosystem.
机译:一种较低层的营养生态系统模型最初用于描述北太平洋西部浮游生物分布的变化性,现已应用于全球海洋。通过4维变分海洋数据同化实验获得的动态自洽环流场的真实时间序列被用于生态系统模型中的环境场。通过格林函数方法对40个省的生物生态参数值进行优化,使生态系统模型能够以相对较少的数量(11)来表示观察到的养分和表面叶绿素浓度的变化。此外,由于模型误差,生态系统变量的人为趋势通常会通过优化得到抑制。就同​​化和非同化指标而言,获得的参数值和生态系统领域通常与观察结果一致。全球海洋的低营养生态系统和物理场的整合提供了有关造成低营养生态系统季节-年际变化的机制(如厄尔尼诺现象)的重要信息。我们的结果表明,通过适当的参数集能够间接修改每种路径的模型和重要性以反映本地物种的特征,可以将简单的生态系统模型应用于定量分析,以增强我们对气候变化对气候变化影响的理解。海洋生态系统。

著录项

  • 来源
    《Progress in Oceanography》 |2013年第12期|90-107|共18页
  • 作者单位

    Oceanography and Geochemistry Research Department, Meteorological Research Institute, Japan Meteorological Agency, 1-1 Nagamine, Tsukuba 305-0052, Japan;

    Data Management and Engineering Department, Data Research Center for Marine-Earth Science, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama 235-0001, Japan,Department of Geophysics, Graduate School of Science, Kyoto University, Kyoto 606-8502, Japan;

    Ocean Climate Change Research Program, Research Institute for Global Change, JAMSTEC, Yokohama 235-0001, Japan;

    Ocean Climate Change Research Program, Research Institute for Global Change, JAMSTEC, Yokohama 235-0001, Japan;

    Data Management and Engineering Department, Data Research Center for Marine-Earth Science, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama 235-0001, Japan;

    Data Management and Engineering Department, Data Research Center for Marine-Earth Science, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama 235-0001, Japan;

    Data Management and Engineering Department, Data Research Center for Marine-Earth Science, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama 235-0001, Japan;

    Data Management and Engineering Department, Data Research Center for Marine-Earth Science, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama 235-0001, Japan;

    Faculty of Fisheries Sciences, Hokkaido University, Hakodate 041-8611, Japan;

    Graduate School of Environmental Science, Hokkaido University, Sapporo 060-0810, Japan;

    Marine Research Division, Japan Marine Research Foundation, Mutsu 035-0064, Japan;

    Faculty of Fisheries Sciences, Hokkaido University, Hakodate 041-8611, Japan,Graduate School of Environmental Science, Hokkaido University, Sapporo 060-0810, Japan;

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