4D-Var data assimilation system for a coupled physical-biological model

Abstract

A 3-compartment model of phytoplankton growth dynamics has been coupled with a primitive-equation circulation model to better understand and quantify physical and biological processes in the Adriatic Sea. This paper presents the development and application of a data assimilation procedure based on optimal control theory. The aim of the procedure is to identify a set of model coefficient values that ensures the best fit between data and model results by minimizing a function that measures model and data discrepancies. In this sense, twin experiments have been successfully implemented in order to have a better estimation of biological model parameters and biological initial conditions.