Development of a weather radar simulator for the characterisation of radar reflectivity of tropical rainfall

Weather radar systems are important tools for rainfall monitoring, atmospheric research, and the design of microwave communication systems. However, the high cost and limited availability of radar instrumentation in many tropical regions necessitate the development of alternative tools for studying radar–rainfall interactions. This study presents the development of a weather radar simulator designed to characterise the radar reflectivity of tropical rainfall and provides a cost-effective platform for radar signal analysis. The simulator integrates physically based rainfall modelling techniques, including the lognormal drop size distribution, realistic raindrop shape representations, and T-matrix electromagnetic scattering calculations. Simulations were performed for both convective and stratiform rainfall conditions at a radar frequency of 24.1 GHz. The simulator-generated reflectivity was validated using observations obtained from a Micro Rain Radar (MRR) installed at the Department of Physics, Federal University of Technology, Akure, Nigeria. The results show that convective rainfall exhibits higher radar reflectivity values than stratiform rainfall. Validation against MRR observations revealed coefficients of determination (R²) of 0.956 and 0.870 for convective and stratiform rainfall, respectively, during a 20-minute simulation period, while corresponding values of 0.809 and 0.731 were obtained for a 40-minute simulation period. The percentage difference between simulated and observed reflectivity was approximately 10% for the 20-minute simulations and approximately 35% for the 40-minute simulations. The simulator generally overestimated reflectivity, with better agreement observed for convective rainfall than for stratiform rainfall. The findings demonstrate that the developed simulator is capable of reproducing the general reflectivity characteristics of tropical rainfall and can serve as a useful tool for investigating radar–rainfall interactions. Future improvements should include the incorporation of alternative drop size distribution models, uncertainty quantification, and validation using a broader range of rainfall events.