Mendonça, FernandoMartins, FlávioBertino, Laurent2025-10-222025-10-222025-09-212077-1312http://hdl.handle.net/10400.1/27844Observing System Simulation Experiments (OSSEs) provide a framework in which to evaluate the impact of prospective ocean-observation networks on model forecasting performance prior to their actual deployment. This study presents the design and validation of an OSSE tailored for the operational coastal model of southern Portugal, SOMA. The system adopts the fraternal twins approach and a univariate data-assimilation scheme based on Ensemble Optimal Interpolation to update the model’s 3D temperature structure with SST. The methodology provides a flexible framework that preserves the statistical structure of real observation errors while remaining independent of SOMA. This allows straightforward transfer to other applications, thereby broadening its applicability and making it useful as a starting point in the design of observation networks beyond that presented in this case study. The OSSE experiments were compared against corresponding Observing System Experiments (OSEs) using real satellite SST products. Results show that the designed OSSE is internally consistent, sensitive to observation density, and capable of reproducing realistic correction patterns that closely match those obtained in the OSEs. These findings provide strong evidence that the SOMA OSSE system is a reliable tool for assessing the potential impact of future surface-observation strategies.engCoastal modelOcean observationData assimilationEnsemble optimal interpolationObservation experimentsjournal article10.3390/jmse13091830