IMPROVEMENT ASSESSMENT OF PRIMARY PRODUCTION MODELLING USING FOUR DIMENSIONAL VARIATIONAL DATA ASSIMILATION

Abstract

 Oxygen production in the photosynthetic process of phytoplankton coded in some biochemical models is limited by surrounding nutrient concentration, which does not directly affect oxygen production in the actual process. This study examined the validity of applying a model-process-modification using four-dimensional variational data assimilation method for Osaka Bay, and propose this approach as one of model improvement techniques driven by observations and data assimilation. The oxygen production-growth ratio parameter was defined as a state variable, and initial field estimation was conducted to evaluate the relationships between the parameter and other state variables. The assimilated results showed that the oxygen production-growth ratio was increased while dissoleved inorganic nitrogen decreased. The results partly support the validity of the modification of primary production in our model.