Reconstruction of 1-min Cumulated Rainfall Time Series Based on t-min Cumulated Rainfall Rate

Rain attenuation is crucial for millimeter-wave communication. The propagation characteristics in rainfall environments can be evaluated by analyzing the statistical characteristics of the 1-min cumulated rainfall rate. However, 1-min cumulated rainfall rate data cannot be directly obtained from most meteorological stations. Therefore, this study proposed a novel reconstruction method based on t-mins cumulated rainfall rate to generate 1-min cumulated rainfall rate time series, such that the statistical minute rainfall rate can be obtained. A probability density function was constructed, and the constraint conditions at which the mean and standard deviation parameters were satisfied during cumulated rainfall rate time series conversion were combined. The proposed method was used to analyze the 5-mins cumulated rainfall rate data of Xi’an, Haikou and Qingdao, collected in 2022, and the 1-min long-term statistical distribution characteristics were obtained. The results showed that the proposed model outperformed the ITU model and Emiliani model, confirming its feasibility and effectiveness. The proposed method applies to minute rainfall rate statistics, crucial for designing communication link systems.