Ise Bay Reanalysis (IBRA): An Ecological Hydrodynamic Dataset Based on EcoPARI

Abstract. Reanalysis datasets based on coupled ocean circulation and ecosystem models are essential tools for understanding coastal environmental variability and supporting water quality management. However, the development of such datasets for highly enclosed coastal systems remains limited, particularly those incorporating subsurface biogeochemical observations, such as dissolved oxygen (DO). This study presents the Ise Bay Reanalysis (IBRA), a 12-year (2011–2022), high-resolution reanalysis dataset of hydrodynamic and biogeochemical variables for Ise Bay, Japan. The dataset was generated using the Ecological hydrodynamic simulation system of the Port and Airport Research Institute (EcoPARI)-simulator, coupled with an ensemble Kalman filter data assimilation system that assimilates in situ observations of water temperature, salinity, and bottom-layer DO at 6 h intervals. The resulting dataset has an hourly temporal resolution and resolves the full water column. IBRA has three key distinguishing features: first, unlike many previous reanalysis datasets that rely primarily on satellite observations, IBRA assimilates continuous in situ measurements throughout the water column, including high-frequency DO observations, allowing improved representation of subsurface dynamics; second, the 6-hour assimilation cycle enables the dataset to resolve short-term variability driven by tidal processes, which are a dominant control on coastal transport and mixing; third, spatially coherent corrections are applied over the entire bay using an ensemble Kalman filter, ensuring spatial consistency of both physical and biogeochemical fields while avoiding artificial discontinuities often associated with simpler assimilation approaches. Its quality was evaluated using statistical metrics and detailed comparisons with in situ observations. Data assimilation improved the overall agreement with observations across multiple stations and depths, particularly for bottom-layer DO. The dataset successfully reproduced seasonal variability, vertical stratification, and the formation and persistence of hypoxic conditions in the inner bay, while also capturing well-oxygenated conditions near the bay mouth. Furthermore, the spatial distributions of temperature, salinity, and DO were realistically represented, including the intrusion of offshore water masses and associated horizontal gradients. The IBRA dataset thus provides a dynamically consistent and comprehensive description of both physical and biogeochemical variability in a highly enclosed coastal system. It is expected to serve as a valuable resource for studies of coastal hypoxia, water quality assessment, and environmental management.