Simultaneous data-based optimization of a 1D-ecosystem model at three locations in the North Atlantic: Part I—Method and parameter estimates

Abstract

An optimization experiment is performed with a vertically resolved, nitrogen-based ecosystem model, composed of four state variables (NPZD-model): dissolved inorganic nitrogen (N), phytoplankton (P), herbivorous zooplankton (Z) and detritus (D). Parameter values of the NPZD-model are optimized while assimilating observations at three locations in the North Atlantic simultaneously, namely at the sites of the Bermuda Atlantic Time-Series Study (BATS; 31N 64W), of the North Atlantic Bloom Experiment (NABE; 47N 20W), and of Ocean Weather Ship-India (OWS-INDIA; 59N 19W). A method is described for a simultaneous optimization which effectively merges different types of observational data at distinct sites in the ocean. A micro-genetic algorithm is applied for the minimization of a weighted least square misfit function. The optimal parameter estimates are shown to represent a compromise among local parameter estimates that would be obtained from single-site optimizations at the individual locations. The optimization yields a high estimate of the initial slope parameter of photosynthesis (alpha), which is shown to be necessary to match the initial phases of phytoplankton growth. The estimate of alpha is well constrained by chlorophyll observations at the BATS and OWS-INDIA sites and likely compensates for a deficiency in the parameterization of light-limited growth. The optimization also points toward an enhanced recycling of organic nitrogen which is perceived from a high estimate for the phytoplankton mortality/excretion rate.