Biological data assimilation for parameter estimation of a phytoplankton functional type model for the western North Pacific
Biological data assimilation for parameter estimation of a phytoplankton functional type model for the western North Pacific
复制标题
DOI：
10.5194/os-14-371-2018
复制
发表时间：
2017-05
期刊：
影响因子：
3.2
通讯作者：
Y. Hoshiba;T. Hirata;M. Shigemitsu;H. Nakano;T. Hashioka;Y. Masuda;Y. Yamanaka
中科院分区：
文献类型：
--
作者：
Y. Hoshiba;T. Hirata;M. Shigemitsu;H. Nakano;T. Hashioka;Y. Masuda;Y. Yamanaka
抽象的。生态系统模型用于了解生态系统动态和海洋生物地球化学循环，并需要最佳的生理参数来最好地代表生物行为。这些生理参数通常根据经验进行调整，而生态系统模型已经发展到增加了生理参数的数量。我们开发了三维 (3-D) 低营养级海洋生态系统模型，称为氮、硅和铁调节海洋生态系统模型 (NSI-MEM)，并利用微遗传算法进行生物数据同化，估计北太平洋西部两种浮游植物功能类型的 23 个生理参数。参数的估计基于一维模拟，该模拟参考卫星数据来约束生理参数。与没有数据同化的模型相比，通过数据同化优化的 3-D NSI-MEM 改善了亚北极和亚热带地区浮游生物水华建模的时间。此外，该模型不仅能够提高浮游植物的表面浓度，而且能够提高其地下最大浓度。我们的结果表明，来自两个对比观测站的生理参数的表面数据同化有利于北太平洋西部浮游生物垂直分布的表征。
Abstract. Ecosystem models are used to understand ecosystem dynamics and ocean biogeochemical cycles and require optimum physiological parameters to best represent biological behaviours. These physiological parameters are often tuned up empirically, while ecosystem models have evolved to increase the number of physiological parameters. We developed a three-dimensional (3-D) lower-trophic-level marine ecosystem model known as the Nitrogen, Silicon and Iron regulated Marine Ecosystem Model (NSI-MEM) and employed biological data assimilation using a micro-genetic algorithm to estimate 23 physiological parameters for two phytoplankton functional types in the western North Pacific. The estimation of the parameters was based on a one-dimensional simulation that referenced satellite data for constraining the physiological parameters. The 3-D NSI-MEM optimized by the data assimilation improved the timing of a modelled plankton bloom in the subarctic and subtropical regions compared to the model without data assimilation. Furthermore, the model was able to improve not only surface concentrations of phytoplankton but also their subsurface maximum concentrations. Our results showed that surface data assimilation of physiological parameters from two contrasting observatory stations benefits the representation of vertical plankton distribution in the western North Pacific.