Comparison of Data Assimilation for Biogeochemical Ocean Models of Different Complexities -- an Example Using Joint Physical-Biological Assimilation for a 3D Regional Model

3-dimensional coupled physical-biogeochemical numerical ocean models, which simulate physical and lower tropic level ecosystem dynamics in the ocean, are now commonly combined with data assimilation in order to improve state or parameter estimates. Yet much remains to be learned about important aspects of biogeochemical data assimilation, such as the effect of model complexity and the importance of more realistic model formulations on assimilation results. Here, we present a comparison of the effects of applying 4DVAR data assimilation to two biogeochemical ocean models of different complexities: a simpler NPZD model with 4 biological variables and 1 phytoplankton compartment, and the more complex NEMURO model, containing 11 biological variables and 2 phytoplankton compartments. Both models are coupled to a 3-dimensional physical ocean model of the US west coast based on the Regional Ocean Modelling System (ROMS). Chlorophyll satellite observations and physical observations are jointly assimilated into the model, yielding substantial improvements in state estimates for the observed physical and biological variables in both model formulations. We examine the effects of data assimilation on the two models; besides the fit to observed variables, we assess improvements with respect to unobserved variables and compare the models' forecasting skill.