Abstract. The West Antarctic Peninsula (WAP) is a rapidly warming region, with substantial ecological and biogeochemical responses to climate change and variability for the past decades, revealed by multi-decadal observations from the Palmer Antarctica Long-Term Ecological Research (LTER) program. The wealth of these long-term observations provides an important resource for ecosystem modelling, but there has been a lack of focus on the development of numerical models that simulate time-evolving plankton dynamics over the Austral growth season along the coastal WAP. Here we developed a one-dimensional, data assimilation planktonic ecosystem model (i.e., the WAP-1D-VAR model v1.0) equipped with a variational adjoint and model parameter optimization scheme. We first demonstrate the modified and newly added model schemes to the pre-existing food-web and biogeochemical components of the WAP-1D-VAR model, including diagnostic sea-ice forcing and trophic interactions specific to the WAP region. We then conducted model experiments by assimilating eleven different data types from an example Palmer LTER growth season (October 2002–March 2003) directly related to corresponding model state variables and intercompartmental flows. The iterative, data assimilation procedure reduced by 80 % the misfits between observations and model results, compared to before optimization, via an optimized set of 14 parameters out of total 72 free parameters. The optimized model results captured key WAP ecological features, such as blooms during seasonal sea-ice retreat, the lack of macronutrient limitation, and comparable values of the assimilated and non-assimilated model state variables and flows to other studies, as well as several important ecosystem metrics. One exception was slightly underestimated particle export flux, for which we discuss fully potential underlying reasons. The data assimilation scheme of the WAP-1D-VAR model enabled the available observational data to constrain previously poorly understood processes, including the partitioning of primary production by different phytoplankton groups, the optimal chlorophyll to carbon ratio of the WAP phytoplankton community, and the partitioning of dissolved organic carbon pools with different lability. The WAP-1D-VAR model was successfully employed to glue the snapshots from a range of the available data sets together to explain and understand the observed dynamics along the coastal WAP.