A Statistical Approach to Retrieve Rainfall Intensity by Attenuation Measurements From Commercial Microwave Links

Commercial microwave link (CML) has become one of the most widely used opportunistic sensors for rainfall monitoring. The high density and coverage of CMLs enable us to monitor near-ground rainfall in high spatial resolution. The empirical power-law (PL) model proposed in 1978 is the leading approach in relating CML attenuation with rain rate. However, while giving good rain rate estimates for CMLs longer than 1 km, in short CMLs, large errors are observed when the PL approach is applied. In this paper, we studied a statistical approach to convert CML attenuation measurement to rainfall intensity. The proposed approach calculates the exceedance probability, p, of rain-induced attenuation and derives the corresponding rainfall intensity based on the rain rate cumulative distribution curve. Data from two cities in two countries were used to validate the approach. The results of the proposed approach were compared with that of the PL model. Results show that the models derived using our approach outperform PL for short CMLs, while showing similar performance for long ones. Since in the next generation mobile networks short CMLs will become more and more dominant, our work provides a way to derive retrieval models for the future generation CML networks.