Enhancing Ocean Biogeochemical Models With Phytoplankton Variable Composition

Chlorophyll (Chl) is widely taken as a proxy for phytoplankton biomass, despite well-known variations in Chl:C:biomass ratios an acclimative response to changing environmental conditions. For the sake of simplicity and computational efficiency, many large scale biogeochemical models ignore this flexibility, compromising their ability capture dynamics. Here we evaluate modelling approaches differing complexity growth response: fixed stoichiometry, stoichiometry with photoacclimation, classical variable-composition Instantaneous Acclimation optimal resource allocation. Model performance evaluated against observations from time-series sites BATS ALOHA, where composition varies substantially. We analyse sensitivity each model variant affinity parameters light nutrient, respectively. Models are more sensitive parameter perturbations, but inclusion photoacclimation fixed-stoichiometry generally captures Chl better than other variants when individually tuned site using similar sets both sites. Compared including variable C:N ratio perform cross-validation experiments model-specific site; i.e., they portable. typical approaches, instantaneous acclimation, which requires fewer state variables, yields somewhat lower portability fully dynamic variant. Further assessments objective optimisation contrasting stations suggested.