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Buoy, island stations, and platform stations play a crucial role in advancing atmospheric and ocean sciences by providing essential marine observational data. This paper explores the potential impact of assimilating sea-based observation data from the South China Sea and the coast on forecasts of heavy rainfall during annually first rainy seasons in South China. In addition to ground station observations, seabased observations are added to conduct continuous cycle assimilation experiments. The experiment results suggest that the continuous cycle assimilation scheme significantly improves precipitation forecasting compared to the cold-start assimilation scheme. The assimilation of additional sea-based observations effectively enhances the humidity field and wind field at the lower levels of the analysis field, thereby improving the water vapor transport and dynamic conditions in the South China Sea region. While the assimilation of sea-based observations does not show significant improvement in precipitation forecasts over land areas, it notably enhances precipitation forecasts for coastal and offshore regions, particularly for heavy rainfall forecasts at 18 - and 24-hour lead times. Overall, the inclusion of sea-based observations positively contributes to the prediction of heavy rainfall along the coastal and offshore regions of the South China Sea during annually first rainy seasons. This study provides an important basis for the CMA-MESO model to achieve more operational assimilation of sea-based observations, improve heavy rainfall forecasting in South China, and conduct marine observation experiments in the South China Sea. [ABSTRACT FROM AUTHOR]