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Skillful marine biogeochemical (BGC) models are requiredto understand a range of coastal and global phenomena such as changes innitrogen and carbon cycles. The refinement of BGC models through theassimilation of variables calculated from observed in-water inherent opticalproperties (IOPs), such as phytoplankton absorption, is problematic.Empirically derived relationships between IOPs and variables such aschlorophyll-a concentration (Chl a), total suspended solids (TSS) andcoloured dissolved organic matter (CDOM) have been shown to have errors thatcan exceed 100 % of the observed quantity. These errors are greatest inshallow coastal regions, such as the Great Barrier Reef (GBR), due to theadditional signal from bottom reflectance. Rather than assimilate quantitiescalculated using IOP algorithms, this study demonstrates the advantages ofassimilating quantities calculated directly from the less error-pronesatellite remote-sensing reflectance (RSR). To assimilate the observed RSR,we use an in-water optical model to produce an equivalent simulated RSR andcalculate the mismatch between the observed and simulated quantities toconstrain the BGC model with a deterministic ensemble Kalman filter (DEnKF).The traditional assumption that simulated surface Chl a is equivalent to theremotely sensed OC3M estimate of Chl a resulted in a forecast error ofapproximately 75 %. We show this error can be halved by instead usingsimulated RSR to constrain the model via the assimilation system. When theanalysis and forecast fields from the RSR-based assimilation system arecompared with the non-assimilating model, a comparison against independentin situ observations of Chl a, TSS and dissolved inorganic nutrients (NO3,NH4 and DIP) showed that errors are reduced by up to 90 %. In allcases, the assimilation system improves the simulation compared to thenon-assimilating model. Our approach allows for the incorporation of vastquantities of remote-sensing observations that have in the past beendiscarded due to shallow water and/or artefacts introduced byterrestrially derived TSS and CDOM or the lack of a calibrated regional IOPalgorithm

Use of remote-sensing reflectance to constrain a data assimilating marine biogeochemical model of the Great Barrier Reef