Description: Application of biogeochemical models to the study of marine ecosystems is pervasive, yet objective quantification of these models' performance is rare. Here, 12 lower trophic level models of varying complexity are objectively assessed in two distinct regions (equatorial Pacific and Arabian Sea). Each model was run within an identical one-dimensional physical framework. A consistent variational adjoint implementation assimilating chlorophyll-a, nitrate, export, and primary productivity was applied and the same metrics were used to assess model skill. Experiments were performed in which data were assimilated from each site individually and from both sites simultaneously. A cross-validation experiment was also conducted whereby data were assimilated from one site and the resulting optimal parameters were used to generate a simulation for the second site. When a single pelagic regime is considered, the simplest models fit the data as well as those with multiple phytoplankton functional groups. However, those with multiple phytoplankton functional groups produced lower misfits when the models are required to simulate both regimes using identical parameter values. The cross-validation experiments revealed that as long as only a few key biogeochemical parameters were optimized, the models with greater phytoplankton complexity were generally more portable. Furthermore, models with multiple zooplankton compartments did not necessarily outperform models with single zooplankton compartments, even when zooplankton biomass data are assimilated. Finally, even when different models produced similar least squares model-data misfits, they often did so via very different element flow pathways, highlighting the need for more comprehensive data sets that uniquely constrain these pathways.

Description: 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.

Description: A marine ecosystem model, that had previously been calibrated in a one-dimensional (1D) mode against observations at three time-series and process-study sites simultaneously, is coupled to a three-dimensional (3D) circulation model of the North and Equatorial Atlantic. Compared to an experiment with a previously employed subjectively tuned ecosystem model, the new 3D-model does not only reduce the model-data misfit at those locations at which observations entered the 1D optimization procedure, but also at an oligotrophic site in the subtropics that had not been considered in the 1D calibration. Basin-scale gridded climatological data sets of nitrate, surface chlorophyll, and satellite-derived primary production also reveal a generally lower model-data misfit for the optimized model. The most significant improvement is found in terms of simulated primary production: on average, primary production is about 2.5 times higher in the optimized model which primarily results from the inclusion of a phytoplankton recycling pathway back to dissolved inorganic nitrogen. This recycling pathway also allows for a successful reproduction of nonvanishing surface nitrate concentrations over large parts of the subpolar North Atlantic. Apart from primary production, the parameter optimization reduces root-mean-square misfits by merely 10–25% and remaining misfits are still much larger than observational error estimates. These residual misfits can be attributed both to errors in the physical model component and to errors in the structure of the ecosystem model, which an objective estimation of ecosystem model parameters by data assimilation alone cannot resolve.

Description: By means of numerical modeling, we analyze the cycling of iron between its various physical (dissolved, colloidal, particulate) and chemical (redox state and organic complexation) forms in the upper mixed layer. With our proposed model it is possible to obtain a first quantitative assessment of how this cycling influences iron uptake by phytoplankton and its loss via particle export. The model is forced with observed dust deposition rates, mixed layer depths, and solar radiation at the site of the Bermuda Atlantic Time-series Study (BATS). It contains an objectively optimized ecosystem model which yields results close to the observational data from BATS that has been used for the data-assimilation procedure. It is shown that the mixed layer cycle strongly influences the cycling of iron between its various forms. This is mainly due to the light dependency of photoreductive processes, and to the seasonality of primary production. The daily photochemical cycle is driven mainly by the production of superoxide, and its amplitude depends on the concentration and speciation of dissolved copper. Model results are almost insensitive to the dominant form of dissolved iron within dust deposition, and also to the form of iron that is taken up directly during algal growth. In our model solutions, the role of the colloidal pumping mechanism depends strongly on assumptions on the colloid aggregation and photoreduction rate.

Description: This study relates the performance of an optimized one-dimensional ecosystem model to observations at three sites in the North Atlantic Ocean: the Bermuda Atlantic Time Series Study (BATS, 31N 64W), the location of the North Atlantic Bloom Experiment (NABE, 47N 20W), and Ocean Weather Ship INDIA (OWS-INDIA, 59N 19W). The ecosystem model is based on nitrogen and resolves dissolved inorganic nitrogen (N), phytoplankton (P), zooplankton (Z) and detritus (D), therefore called the NPZD-model. Physical forcing, such as temperature and eddy diffusivities are taken from an eddy-permitting general circulation model of the North Atlantic Ocean, covering a period from 1989 through 1993. When an optimized parameter set is applied, the recycling of organic nitrogen becomes significantly enhanced, compared to previously published results of the NPZD model. The optimized model yields improved estimates of the annual ratio of regenerated to total primary production (f-ratio). The annual f-ratios are 0.09, 0.31, and 0.42 for the locations of BATS, NABE, and OWS-INDIA, respectively. Nevertheless, three major model deficiencies are identified. Most conspicuous are systematic discrepancies between measured 14C-fixation rates and modeled primary production under nutrient depleted conditions. This error is primarily attributed to the assumption of a constant carbon-to-nitrogen ratio for nutrient acquisition. Secondly, the initial period of the modeled phytoplankton blooms is hardly tracked by the model. That particular model deficiency becomes most apparent at the OWS-INDIA site. The interplay between algal growth and short-term alterations in stratification and mixing is believed to be insufficiently resolved by the physical model. Eventually, the model's representation of the vertical nitrogen export appears to be too simple in order to match, at the same time, remineralization within the upper 300 meters and the biomass export to greater depths.

Description: The seasonal variation in concentration of transparent exopolymer particles (TEPs), particulate organic carbon (POC) and particulate organic nitrogen (PON) were investigated together with floc size and the concentration of suspended particulate matter (SPM) along the cross-shore gradient, from the high turbid nearshore toward the low-turbid offshore waters in the Southern Bight of the North Sea. Our data demonstrate that biophysical flocculation cannot be explained by these heterogeneous parameters, but requires a distinction between a more reactive labile (“fresh”) and a less reactive refractory (“mineral-associated”) fraction. Based on all data, we separated the labile and mineral-associated POC, PON, and TEP using a semi-empirical model approach. The model's estimates of fresh and mineral-associated organic matter (OM) show that great parts of the POC, PON, and TEP are associated with suspended minerals, which are present in the water column throughout the year, whereas the occurrence of fresh TEP, POC, and PON is restricted to spring and summer months. In spite of a constantly high abundance of total TEP throughout the entire year, it is its fresh fraction that promotes the formation of larger and faster sinking biomineral flocs, thereby contributing to reducing the SPM concentration in the water column over spring and summer. Our results show that the different components of the SPM, such as minerals, extracellular OM and living organisms, form an integrated dynamic system with direct interactions and feedback controls.