Implementation of daily river discharge into Southeast Asia regional ocean model NEMO

The ocean basins of Southeast Asia (SEA) are significantly influenced by a dynamic water cycle characterized by intense precipitation, evaporation, and substantial river runoff. The freshening of shelf seas in this region - where precipitation and river discharge exceed evaporation - plays a critical role in shaping regional ocean circulation and the marine environment. However, a lack of sufficient observational data has limited our understanding of these processes, particularly their seasonal and spatial variability.

In regional ocean modeling, climatological river runoff is usually employed to account for freshwater input. This approach may underrepresent seasonal extremes and might not fully capture the daily variation of river discharge, leading to substantial biases in the simulated sea surface salinity (SSS). To address this limitation, we implemented daily river runoff from the JRA55-do global reanalysis into a high-resolution (~4.5 km) regional ocean model based on Nucleus for European Modelling of the Ocean (NEMO).

The JRA55-do runoff dataset, produced by Japan Meteorological Agency (JMA) Meteorological Research Institute (MRI), derived from the CaMa-Flood global river routing model and provided on a 0.25°×0.25° grid. The JRA55-do runoff data was remapped onto the NEMO model grid. The model simulations were forced with 10 m winds and surface heat flux data from the ERA5 reanalysis, available from the European Centre for Medium-Range Weather Forecasts (ECMWF). Lateral boundary conditions and initial states were obtained from the GLORYS12, which is an ocean reanalysis dataset based on a 1/12^o eddy-resolving global NEMO and was carried out in the framework the European Copernicus Marine Environment Monitoring Service (CMEMS). Simulations were conducted for the year 2022, and the model outputs were validated against satellite observations of SSS and sea surface temperature (SST).

The results indicate that the high-resolution regional NEMO model successfully captured the seasonal variability of SSS observed in satellite data. Notably, the incorporation of river runoff improved the spatial representation of SSS in some areas. In a comparison, simulations using daily runoff demonstrated higher modelling skill in some regions than those with climatological runoff. By enhancing the accuracy of SSS in our regional ocean model, this study provides critical insights into the role of freshwater input in shaping the oceanographic processes of the Southeast Asia.