Variability of plankton production during the spring bloom in NW Iberia

A coupled physical (Regional Ocean Modeling System, ROMS)-biogeochemical model (N2PZD2) at a horizontal resolution of 3.5 km was implemented for N and NW Iberia, an area of high productivity associated with upwelling. The physical model has been the object of previous studies and has proven its capability to perform well in reproducing the main oceanographic features in the area (upwelling, river plumes, slope currents, fronts, filaments), which is fundamental to properly representing the variability and distribution of the biogeochemical variables. The biogeochemical model was set up to account for the main nutrient inputs in the area: upwelling and rivers. Upwelling input required proper characterization of the nutrient content variability of the Eastern North Atlantic Central Water, which was achieved by using a temperature-nitrate relationship obtained from observations to impose nitrate at the open boundaries. The resulting biophysical model accurately reproduced the timing and interannual variability of the spring bloom compared with satellite chlorophyll (chl a) observations. A comparison with the Instituto Espanol de Oceanografia's in situ spring-monitoring Pelacus cruises (which include plankton) revealed that the model was able to reproduce the variability at shorter scales (days) and demonstrated its ability to complement the observational data and reveal the variability in the area around the spring transition. In this respect, both the model and observations showed that productivity on this narrow shelf is affected by seasonal upwelling that results from the interplay of wind, river plumes and light intensity, all varying at interannual, seasonal and event scales.

Automated summary

This study successfully implemented a coupled physical-biogeochemical model to accurately simulate the variability of biogeochemical variables in the N and NW Iberia region. The model accurately reproduced the timing and interannual variability of the spring bloom and complemented observational data to reveal the variability in the area around the spring transition.