Influence of model geometrical fitting and turbulence parameterization on phytoplankton simulation in the Gulf of Maine

Abstract

Abstract Numerical experiments were made to examine the influences of model geometrical fitting and turbulence parameterization on the temporal and spatial distributions of simulated phytoplankton in the Gulf of Maine. The assessment of the role of geometrical fitting was made by running a state-of-the-art Nutrient-Phytoplankton-Zooplankton (NPZ) model with physical fields provided from unstructured-grid, finite-volume coastal ocean model (FVCOM) and structured-grid, finite-difference coastal ocean model (ECOM-si), respectively. The impact of turbulence parameterization was studied by running a coupled NPZ–FVCOM system with various vertical turbulence modules implemented in the General Ocean Turbulence Model (GOTM). Comparisons were focused on three large tidal dissipation regions: Georges Bank (characterized by strong tidal rectification over steep bottom topography and tidal mixing fronts), Bay of Fundy (featuring large semidiurnal tidal oscillations due to the gulf-scale resonance), and Nantucket Shoals (a tidal energy flux convergence zone). For the same given tidal forcing and initial physical and biological conditions, the ability of a model to accommodate the irregular coastal geometry and steep bottom topography is critical in determining the robustness of the simulated spatial and temporal structure of N and P. For the same given external forcing in FVCOM, turbulence parameterizations have less impact on N and P in mixed regions than in stratified regions. In mixed regions, both q–e and q–ql models reproduced the observed vertical mixing intensity. Since biological variables remained vertically mixed in these regions, their structures were little affected by turbulence closure schemes. In stratified regions, q–e models predicted stronger mixing than q–ql models, which produced more nutrient fluxes over the slope and thus influenced the growth and distribution of P around the tidal mixing front. A direct comparison between observed and model-predicted turbulence dissipation rates suggests that q–e models with a mixing cutoff at Richardson number of 1.0 predict more realistic mixing intensity than q–ql models in stratified regions on Georges Bank.