A cost-effective data assimilation system for improving ROMS simulations in the Southwest Atlantic

This study presents for the first time the integration of the low-cost REMO Ocean Data Assimilation System (RODAS) into the Regional Ocean Modeling System (ROMS) for assimilating Sea Surface Temperature (SST) observations. RODAS is an Ensemble Optimal Interpolation (EnOI)-based data assimilation system originally developed for use with the HYCOM model. Here, it is adapted to ROMS and applied to the Southwest Atlantic, with a focus on evaluating its impact on short-term ocean hindcasts. We conducted 4-years simulations with and without SST assimilation, referred to as RODAS_SST and Free, respectively. The RODAS_SST experiment showed a 70% reduction in SST root mean square deviation (RMSD) relative to the Free run, and a 55% reduction compared to 72-hour hindcasts generated from previous analysis cycles. When compared with the GLORYS reanalysis, SST RMSD was reduced by 64%. Ocean heat content estimates also improved, with reductions in mean absolute error of 15% during summer and 25% in winter. While assimilation improved surface and subsurface thermal structure in general, comparisons with Argo profiles revealed occasional degradations near the thermocline, highlighting the need for better multivariate covariance representation in the EnOI scheme. The successful implementation of RODAS in ROMS provides a cost-effective tool for enhancing model initial conditions and regional ocean simulations. Future developments will include the assimilation of Argo temperature and salinity profiles, sea level anomaly (SLA) data, and observations from the SWOT satellite. The code will be openly released, aiming to broaden access to ocean data assimilation by enabling robust performance even on limited computational resources.