Abstract. Diversity plays critical roles in ecosystem functioning, but it remains unclear how best to model phytoplankton diversity in order to better understand those roles and reproduce consistently observed patterns in the ocean. In contrast to the typical approach of resolving distinct species or functional groups, we present a ContInuous TRAiT-basEd phytoplankton model (CITRATE) that focuses on macroscopic properties such as total biomass, mean trait values, and trait variance. This phytoplankton component is embedded within a Nitrogen-Phytoplankton-Zooplankton-Detritus-Iron model that itself is coupled with a simplified one-dimensional ocean model. Size is used as the master trait for phytoplankton. CITRATE also incorporates trait diffusion for sustaining diversity, as well as simple representations of physiological acclimation, i.e. flexible chlorophyll-to-carbon and nitrogen-to-carbon ratios. We implemented CITRATE 1.0 at two contrasting stations in the Northwest Pacific where several years of observational data are available. The model is driven by physics forcing including vertical eddy diffusivity imported from three-dimensional ocean circulation models. One common set of model parameters for the two stations was optimized using the Delayed Rejection Adaptive Metropolis-Hasting Monte Carlo (DRAM) algorithm. The model faithfully reproduced most of the observational patterns and gave robust predictions on phytoplankton mean size and size diversity. With proper physical forcing, CITRATE 1.0 can be applied to any oceanic station where either nitrogen or iron limits phytoplankton growth.