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Volume 14, issue 3 | Copyright
Ocean Sci., 14, 371-386, 2018
https://doi.org/10.5194/os-14-371-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 01 Jun 2018

Research article | 01 Jun 2018

Biological data assimilation for parameter estimation of a phytoplankton functional type model for the western North Pacific

Yasuhiro Hoshiba1,2, Takafumi Hirata1, Masahito Shigemitsu3, Hideyuki Nakano4, Taketo Hashioka3, Yoshio Masuda1, and Yasuhiro Yamanaka1 Yasuhiro Hoshiba et al.
  • 1Faculty of Environmental Earth Science, Hokkaido University, Sapporo, Japan
  • 2Atmosphere and Ocean Research Institute, The University of Tokyo, Kashiwa, Japan
  • 3Japan Agency for Marine-Earth Science and Technology, Yokosuka, Japan
  • 4Meteorological Research Institute, Tsukuba, Japan

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.

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We developed a three-dimensional lower-trophic-level marine ecosystem model (NSI-MEM) and employed biological data assimilation using a micro-genetic algorithm to estimate physiological parameters for two phytoplankton functional types in the western North Pacific. The 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.
We developed a three-dimensional lower-trophic-level marine ecosystem model (NSI-MEM) and...
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