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Radar meteorological algorithms play a crucial role in meteorological monitoring and forecasting, and their rapid deployment and application in operational systems significantly improve radar data quality and operational efficiency. To improve the data quality of weather radar and the effectiveness of localised applications, this study relies on the open interface architecture of the new generation weather radar operational software (ROSE 3.0) to carry out localised design and system integration research of radar meteorological algorithm modules. At first, the open interface functionality, modular development process, and integration methods of ROSE 3.0 are introduced in detail. Subsequently, taking the radar data quality control algorithm as the research object, a non-meteorological echo recognition model for dual-polarisation radar is developed using the fuzzy logic method. Key radar parameters such as radial velocity, differential reflectivity texture, correlation coefficient, and differential phase shift texture are utilised to implement the radar data quality control algorithm through the ROSE 3.0 standard API function and dynamic link library. Then, this radar data quality control algorithm is successfully deployed in the ROSE 3.0 operational systems of Suizhou and Jingzhou radar stations in Hubei Province. Using two radar observation cases from Suizhou and Jingzhou radar stations for operational tests, it is shown that the radar data quality control algorithm robustly and efficiently identifies and eliminates non-meteorological echoes such as ground clutter, biological targets, and aluminium foil interference, while the precipitation echoes experience no loss. By comparing and analysing the radar reflectivity factors before and after quality control, a significant improvement in the quality and reliability of radar data is found, which enhances the operational efficiency of precipitation monitoring and short-term forecasting systems. Additionally, the results of this study also validate the significant advantages of ROSE 3.0 in supporting rapid algorithm integration, flexible expansion, and business transformation, effectively promoting the localised deployment of radar meteorological algorithms. It should be pointed out that this study mainly focuses on the interface mechanism and integration process of ROSE 3.0. The effectiveness of radar data quality control is mainly analysed through case studies, and there is a lack of systematic analysis on the accuracy evaluation and localisation optimisation strategies of radar data quality control algorithms. In future research, it is necessary to continuously improve the accuracy evaluation of weather radar quality control algorithms and further expand ROSE 3.0 functionality to support multiple data formats and more complex meteorological processing techniques, in order to better serve the new needs of meteorological operational development.